Posts Tagged ‘research’

Tumor Associated Macrophages: The Double-Edged Sword Resolved?

Posted in Cancer and Current Therapeutics, CANCER BIOLOGY & Innovations in Cancer Therapy, Immuno-Oncology & Genomics, tagged Adaptive immune system, Biology, breast cancer, Cancer - General, Cancer immunology, Cell Biology, Conditions and Diseases, gene expression, genomics, macrophages, modulation of tumor tolerance, research, Stem cell, tumor associated macrophage, tumor microenvironment, Weill Cornell on September 15, 2015| Leave a Comment »

Tumor Associated Macrophages: The Double-Edged Sword Resolved?

Writer/Curator: Stephen J. Williams, Ph.D.

UPDATED 10/04/2021 TAMs Enhance Tumor Hypoxia and Aerobic Glycolysis

Cell-based immunity is vital for our defense against pathologic insult but recent evidence has shown the role of cell-based immunity, especially macrophages to play an important role in both the development and hindrance of tumor growth, including role in ovarian, hematologic cancers, melanoma, and breast cancer.  In the past half century, new immunological concepts of cancer initiation and progression have emerged, including the importance of the harnessing the immune system as a potential anti-cancer strategy. However, as our knowledge of the immune system and tumor biology has grown, the field has realized an immunological conundrum: how can an immune system act to both prevent tumor growth and promote the tumor’s growth?

As discussed in the lower section of this post, authors of a paper in the journal Science show how different populations of tumor-associated macrophages (TAMs) may exert both positive and negative effects on tumor cells, producing a sort of ying-yang war between the tumor and the immune system.

The Immune System: Brief Overview and Role in Cancer

Figure. Cell lineage of the immune system. A description of the different cell types can be found here.

Histologic evaluation of multiple tumor types, especially solid tumors, reveal the infiltration of diverse immunological cell types, including myeloid and lymphoid cell lineages, such as macrophages and NK, T cell and B cells respectively.

The immunological conundrum

Figure. Potential inflammatory signaling pathways in breast cancer stem cells.
Breast cancer stem cells may be regulated by chemokine- and/or cytokine-mediated inflammatory signaling in an autocrine or paracrine manner. (from University of Tokyo at http://www.ims.u-tokyo.ac.jp/system-seimei/en/research2_e.htm)

Role of Tumor Associated Macrophages

There are conflicting reports as to the functional consequence of these infiltrating tumor-associated macrophages (TAMs). TAMs have been shown to secrete mediators such as interleukins and cytokines in a paracrine manner such as CCL2, IL10 and TGFβ. In certain instances these cytokines and mediators actually promote the growth of the surrounding tumors.

Figure.  TAMs can be divided into subpopulations with distinctive functions and secretogogues.

For Further Reference

Tumor-associated macrophages and the profile of inflammatory cytokines in oral squamous cell carcinoma. http://www.ncbi.nlm.nih.gov/pubmed/23089461 anti-inflamm IL10 and TGFB

Tumor-associated macrophage-derived IL-6 and IL-8 enhance invasive activity of LoVo cells induced by PRL-3 in a KCNN4 channel-dependent manner

Figure 2: TAM functions in tumor progression. Tumor cells and stromal cells, which produce a series of chemokines and growth factors, induce monocytes to differentiate into macrophages. In the tumor, most macrophages are M2-like, and they express some cytokines, chemokines, and proteases, which promote tumor angiogenesis, metastasis, and immunosuppression. From Macrophages in Tumor Microenvironments and the Progression of Tumors

Macrophages integrate metabolic and environmental signals to promote tumor growth. Area within dotted rectangle indicates proposed mechanisms of action. ARG, arginase; HIF, hypoxia-inducible factor; MCT, monocarboxylate transporter; NADH, nicotine adenine dinucleotide, reduced; PKM2, M2 isoform of pyruvate kinase; VEGF, vascular endothelial growth factor from Tumor cells hijack macrophages via lactic acid adapted from Colegio OR, Chu N-Q, Szabo AL, Chu T, Rhebergen AM, Jairam V et al. Functional polarization of tumour-associated macrophages by tumour-derived lactic acid. Nature (e-pub ahead of print 13 July 2014; doi:10.1038/nature13490). | Article |

Depletion of M2-Like Tumor-Associated Macrophages Delays Cutaneous T-Cell Lymphoma Development In Vivo

Targeting tumor-associated macrophages in an orthotopic murine model of diffuse malignant mesothelioma

Crosstalk between colon cancer cells and macrophages via inflammatory mediators and CD47 promotes tumour cell migration

Tumor-Associated Macrophages Regulate Murine Breast Cancer Stem Cells Through a Novel Paracrine EGFR/Stat3/Sox-2 Signaling Pathway

Science Paper: Different Populations of TAMS Have Different Tumor Effects

The cellular and molecular origin of tumor-associated macrophages Eric G. Pamer¹ Ruth A. Franklin¹,², Will Liao³, Abira Sarkar¹, Myoungjoo V. Kim¹,², Michael R. Bivona¹, Kang Liu⁴, Ming O. Li¹, Science 23 May 2014: Vol. 344 no. 6186 pp. 921-925

A recent Science paper from Cornel has investigated the origin, function, and characterization of TAMs on breast cancer growth. In summary, their efforts and research suggest different populations of TAMs with varied tumorigenic effects, a finding which may help explain the immunologic conundrum with respect to solid tumors.

The authors characterized the infiltrating immune cell types in a MMTV-PyMt model of breast cancer.

The MMTV-PyMt mouse breast cancer model:

is a transgenic model where mammary gland expression of the polyoma middle T antigen (PyMT) is driven by the Mouse Mammary Tumor Virus promoter (MMTV).

For a review of mouse models of breast cancer please see

Mouse models of breast cancer metastasis. Anna Fantozzi¹ and Gerhard Christofori. Breast Cancer Res. 2006; 8(4): 212.

Results

1.     Macrophages constitute the predominate myeloid cell population in MMTV-PyMT mammary tumors

Tumor infiltrating immune cells included

• Myeloid cells comprised 50% of CD45+ infiltrating leukocytes.
• The CD45 antigen, also known as Protein tyrosine phosphatase, receptor type, C (PTPRC) is an enzyme that, in humans, is encoded by the PTPRC gene, and acts as a regulator of B and T-lymphocytes.
• Authors noted three types of cells classified as Type I, II, and III based on

1. Cell morphology
2. Major histocompatibility complex

• Infiltrating monocytes and neutrophils
• Cells with dendritic and macrophage markers

2. TAMS differentiate from CCR2+ inflammatory monocytes

• To determine whether Ly6C⁺CCR2⁺ inflammatory monocytes contributed to TAMs and MTMs, authors crossed PyMT mice to Ccr2^−/− mice and found MTMs (mammary tumor macrophages) were significantly reduced in Ccr2^−/− PyMT mice, implying that MTMs are constitutively repopulated by inflammatory monocytes
• To determine whether inflammatory monocytes were required for TAM maintenance, we generated CCR2^DTR PyMT mice expressing diphtheria toxin receptor (DTR) under control of the Ccr2 locus DT treatment resulted in 96% depletion of tumor-associated monocytes compared to 80% depletion in Ccr2^−/− mice
• To investigate whether monocytes could differentiate into TAMs in vivo, we transferred CCR2⁺ bone marrow cells isolated from CCR2^GFP reporter mice into congenically marked CCR2^DTR PyMT mice depleted of endogenous monocytes, we observed transferred cells in developing tumors demonstrate that tumor growth induces the differentiation of CCR2⁺ monocytes into TAMs.

3.     TAMs are phenotypically distinct from AAMs (M2 or alternatively activated macrophages)

• Gene-expression profiling revealed the integrin CD11b (Itgam) was expressed at lower levels in TAMs than in MTMs while several other integrins and the integrin receptor Vcam1 were up-regulated in TAMs
• AM population did not express AAM markers such as Ym1, Fizz1, and Mrc1; instead, MTMs more closely resembled AAMs. The authors detected Vcam1 up-regulation on TAMs as a late differentiation event

4.    RBPJ-dependent TAMs modulate the adaptive immune response

• In DCs, canonical Notch signaling mediated by the key transcriptional regulator RBPJ controls lineage commitment and terminal differentiation. To explore whether Notch signaling played a role in TAM differentiation, authors used CD11c^cre mice that efficiently deleted floxed DNA sequences to a greater extent in TAMs than MTMs, but not in monocytes or neutrophils (fig. S14). CD11c^creRbpj^fl/fl PyMT mice exhibited a selective loss of MHCII^hiCD11b^lo TAMs ( 4A). However, a MHCII^hiCD11b^hi population still remained
• Transcriptional profiling comparing this population to WT TAMs confirmed a loss of the Notch-dependent program in RBPJ-deficient cells revealing that in the absence of RBPJ, inflammatory monocytes are unable to terminally differentiate into TAMs.

UPDATED 10/04/2021 TAMs Enhance Tumor Hypoxia and Aerobic Glycolysis

Tumor-Associated Macrophages Enhance Tumor Hypoxia and Aerobic Glycolysis

From:

Tumor-Associated Macrophages Enhance Tumor Hypoxia and Aerobic Glycolysis

Hoibin Jeong, Sehui Kim, Beom-Ju Hong, Chan-Ju Lee, Young-Eun Kim, Seoyeon Bok, Jung-Min Oh, Seung-Hee Gwak, Min Young Yoo, Min Sun Lee, Seock-Jin Chung, Joan Defrêne, Philippe Tessier, Martin Pelletier, Hyeongrin Jeon, Tae-Young Roh, Bumju Kim, Ki Hean Kim, Ji Hyeon Ju, Sungjee Kim, Yoon-Jin Lee, Dong-Wan Kim, Il Han Kim, Hak Jae Kim, Jong-Wan Park, Yun-Sang Lee, Jae Sung Lee, Gi Jeong Cheon, Irving L. Weissman, Doo Hyun Chung, Yoon Kyung Jeon and G-One Ahn

Cancer Res February 15 2019 (79) (4) 795-806; DOI: 10.1158/0008-5472.CAN-18-2545

Abstract

Tumor hypoxia and aerobic glycolysis are well-known resistance factors for anticancer therapies. Here, we demonstrate that tumor-associated macrophages (TAM) enhance tumor hypoxia and aerobic glycolysis in mice subcutaneous tumors and in patients with non–small cell lung cancer (NSCLC). We found a strong correlation between CD68 TAM immunostaining and PET ¹⁸fluoro-deoxyglucose (FDG) uptake in 98 matched tumors of patients with NSCLC. We also observed a significant correlation between CD68 and glycolytic gene signatures in 513 patients with NSCLC from The Cancer Genome Atlas database. TAM secreted TNFα to promote tumor cell glycolysis, whereas increased AMP-activated protein kinase and peroxisome proliferator-activated receptor gamma coactivator 1-alpha in TAM facilitated tumor hypoxia. Depletion of TAM by clodronate was sufficient to abrogate aerobic glycolysis and tumor hypoxia, thereby improving tumor response to anticancer therapies. TAM depletion led to a significant increase in programmed death-ligand 1 (PD-L1) expression in aerobic cancer cells as well as T-cell infiltration in tumors, resulting in antitumor efficacy by PD-L1 antibodies, which were otherwise completely ineffective. These data suggest that TAM can significantly alter tumor metabolism, further complicating tumor response to anticancer therapies, including immunotherapy.

Significance: These findings show that tumor-associated macrophages can significantly modulate tumor metabolism, hindering the efficacy of anticancer therapies, including anti-PD-L1 immunotherapy.

Introduction

Tumor hypoxia and glycolysis have long been recognized as major resistance factors contributing to failures of chemo- and radiotherapy (1, 2). Traditionally, tumor hypoxia is known to occur by two mechanisms: chronic or acute hypoxia (2). Chronic hypoxia occurs as a result of rapid proliferation of cancer cells and hence being constantly forced away from blood vessels beyond the oxygen diffusion distance of approximately 150 μm (2). Acute hypoxia on the other hand occurs by a temporary cessation of the blood flow due to highly disorganized tumor vasculature (2). Regardless of the mechanism, tumor hypoxia has been extensively documented for their contribution to resistance to all anticancer therapies including chemotherapy (2), surgery (3), radiotherapy (2), and recently immunotherapy (4).

Aerobic glycolysis, also known as Warburg effect, is a phenomenon whereby many types of tumors exhibit a preference of glucose over the oxygen for their energy substrate (5), and this has allowed us to track solid tumors in patients with PET using ¹⁸fluoro-deoxyglucose (FDG) radioactive tracer (6). Although several mechanisms for Warburg effect have been suggested including mitochondrial defects, adaptation to hypoxia [hence activation of hypoxia-inducible factor (HIF)], and oncogenic signals such as MYC and RAS (7), the exact mechanism is still controversial. Tumor glycolysis has also been reported to influence the therapy outcome (8). Preclinical studies have suggested that glycolysis can increase DNA repair enzyme expressions including Rad51 and Ku70, which can facilitate radiation-induced DNA double-strand break repair (9). Lactate, a major byproduct of glycolysis, has recently been shown to be utilized as a fuel source for oxidative phosphorylation in nearby cancer cells (10), which can promote the tumor recurrence following anticancer therapies.

Tumor-associated macrophages (TAM) are bone marrow–derived immune cells recruited to tumors and have been extensively reported for their protumoral role (11). Recruited to tumors by various tumor-secreting factors including stromal cell–derived factor-1 (SDF1; ref. 12), VEGF (13), semaphorin 3A (14), and colony-stimulating growth factor-1 (CSF1; ref. 15), TAMs have been shown to produce various growth factors and proteases necessary for tumor survival (11) or immunosuppressive cytokines inhibiting antitumor immune responses (16). Macrophages in general are known to be polarized to either classically activated M1 macrophages or alternatively activated M2 phenotype depending on the cytokine milieu in which they are exposed (17). Bacterial-derived products such as lipopolysaccharide have been shown to polarize macrophages toward M1 phenotype (17), while parasite-associated signals such as IL4 and IL13 can lead to M2-polarized macrophages with increased tissue repair abilities (17). It has been suggested that TAMs are M2-like, although various subpopulations of TAM have been also identified including TIE2-positive macrophages (18), programmed cell death protein-1 (PD-1)–expressing TAM (19), and C-C chemokine receptor type-2 (CCR2)–expressing TAM (20).

In this study, we demonstrate clinically and preclinically that TAMs are a novel contributor to tumor hypoxia and aerobic glycolysis by competing oxygen and glucose with cancer cells. We further observed that TAM can significantly interfere with T-cell infiltration thereby masking programmed death-ligand 1 (PD-L1) expression in the tumors. We believe that our results have an important clinical implication such that patients with high infiltration of TAM in their tumors may poorly respond to all anticancer therapies, including the latest immunotherapy.

• Download figure
• Open in new tab
• Download powerpoint

Figure 1.

Strong correlations between TAM infiltration and glycolysis in patients with NSCLC. A, Representative PET/CT images for FDG uptake (top) and immunostaining of CD68 (bottom) from paired tumors of patients with NSCLC. Top, yellow circles, location of tumors. Bottom, red arrowheads, CD68-positive TAM. Scale bar, 100 μm. B, Correlation between glycolysis and CD68-positive TAM in 98 patients with NSCLC paired results as in A. Glycolysis was analyzed as FDG maximal standardized uptake value (FDG SUV_max; left) or 40% total lesion glycolysis (TLG; right). C, FDG SUV_max values for CD68^low (n = 49) or CD68^Hi (n = 49) NSCLC tumors. D, Subgroup analyses of FDG uptake in adenocarcinomas (n = 48; left) or squamous cell carcinomas (n = 50; right) of NSCLC. *, P < 0.05; ***, P < 0.001 in C and D as determined by the Student t test. Data are the mean ± SEM. E, TCGA analysis between CD68 and SLC2A1 (left) or HK2 (right) in 513 patients with adenocarcinoma NSCLC. P values are indicated in each plot.

TAMs make tumors more glycolytic

• Download figure
• Open in new tab
• Download powerpoint

Figure 2.

TAMs make tumors more glycolytic. A, Left, PET/MRI images for FDG uptake in LLC tumors in mice before (D0, top) and after (D2, bottom) Veh or Clod treatment. Yellow circles, tumors. Right, T2-weighted MR images of LLC tumors treated with Veh or Clod pre (top)- or post (bottom)- contrast. Red arrowheads in Veh tumor, ferumoxytol-labeled TAM. B, FDG uptake SUV_max in A. **, P < 0.01, determined by two-way ANOVA. C, FACS plot indicating Hoechst^brightKeratin⁺ (red boxes) population of cells sorted as aerobic cancer cells. D, Fold changes in gene expression in FACS-sorted aerobic cancer cells from LLC tumors treated with Clod or Veh. E, Glucose uptake (left) and lactate production (right) from the sorted aerobic cancer cells as in C. Data in D and E are the mean ± SEM from at least triplicate samples. *, P < 0.05; ***, P < 0.001 by the Student t test. F, Western blot of FACS-sorted aerobic cancer cells in C for GLUT1. β-Actin was used as the loading control. G, Oxygen consumption kinetics in FACS-sorted aerobic cancer cells as described in C. H, LLC tumor growth in mice treated with Veh, Clod, Veh + metformin (Veh + Met), or Clod + metformin (Clod + Met). *, P < 0.05; **, P < 0.01; ***, P < 0.001, determined by two-way ANOVA. I, LLC tumor growth in mice treated with Veh, Clod, Veh + 2-DG, or Clod + 2-DG. Data in H and I are the mean ± SEM, with number of animals indicated in the graphs.

TAMs secrete TNFα to promote tumor glycolysis

• Download figure
• Open in new tab
• Download powerpoint

Figure 3.

Macrophages secrete TNFα to facilitate glycolysis in cancer cells. A, Gene expression changes in LLC cocultured with (LLC+BMDM) or without (LLC) BMDM. Data are the mean ± SEM from at least triplicate determinations. B, Glucose uptake (left) and lactate production (right) in LLC cocultured with or without BMDM. Data are the mean ± SEM for triplicate samples per group. **, P < 0.01 by Student t test. C, Glucose uptake in LLC cultured alone, cocultured with BMDM, or cocultured with BMDM with glucose added back to the LLC compartment of the coculture system. Data are the mean ± SEM for n = 4 replicates per group. *, P < 0.05; **, P < 0.01 by one-way ANOVA. D, Antibody cytokine arrays in the supernatant obtained from BMDM culture with (BMDM+LLC) or without (BMDM) LLC. Red boxes indicate those cytokines whose expressions were increased in BMDM cocultured with LLC compared with BMDM alone. Blue box, CXCL1, a cytokine produced by LLC cancer cells themselves (Supplementary Fig. S2D). E, Luminex cytokine assays for TNFα in the supernatant from culture media, LLC alone, BMDM alone, or BMDM cocultured with LLC. Data are the mean ± SEM for n = 3 replicates per group. ***, P < 0.001 by one-way ANOVA. F, Glucose uptake in LLC alone (none), LLC cocultured with BMDM (+BMDM), or LLC treated with TNFα (+TNFα) or with IFNγ (+IFNγ). Data are the mean ± SEM from n = 3 samples per group. **, P < 0.01; ***, P < 0.001 by one-way ANOVA. G, Western blot for LLC cells treated with increasing concentrations of recombinant TNFα protein for GLUT1, HK2, or PGC-1α. β-Actin was used as the loading control. H, TNFα concentrations in the supernatant from LLC cultured with (+BMDM) or without (alone) BMDM, or in BMDM cultured with (+LLC) or without (alone) LLC, measured by ELISA. BD, below the detection limit. **, P < 0.01 by Student t test. I, Immunostaining of TNFα (red) and CD68 (green) in LLC tumors grown in mice. Nuclei are shown in blue with DAPI counterstaining. The inset shows magnified regions where indicated with the asterisk (*). White arrowheads, CD68-positive TAM-expressing TNFα. Scale bar, 100 μm. J, TNFα concentrations measured by ELISA in the supernatant from CD11b and F4/80 double-positive TAM sorted by FACS. Data are the mean ± SEM from triplicate determinations. ***, P < 0.001, determined by one-way ANOVA. K, TCGA analysis of clinical correlations between CD68 and TNF (left) or between TNF and HK2 (right) in 513 patients with adenocarcinoma NSCLC. P values are indicated in each plot.

TAMs exacerbate tumor hypoxia

• Download figure
• Open in new tab
• Download powerpoint

Figure 4.

TAMs directly contribute to tumor hypoxia. A, Immunostaining of LLC tumors grown in mice for TAM by using S100A8 (red) and hypoxia by using pimonidazole (PIMO; green) antibodies. Nuclei are shown in blue with DAPI counterstaining. B, FACS analysis demonstrating that CD11b and F4/80 double-positive TAMs are pimonidazole-positive. C, Gene expression in CD11b and F4/80 double-positive TAM isolated from LLC tumors compared with those in cultured BMDM. Data are the mean ± SEM from triplicate determinations. D, Two-photon microscopy images of the dorsal window chamber whereby 5 × HRE-GFP–expressing LLC tumors had been implanted. Images were taken at 24 hours after a single intratumoral injection of PBS (+PBS) or PBS containing FACS-sorted TAM (+TAM). Scale bars in A and D, 100 μm. E, Representative FACS plots demonstrating Hoechst^brightKeratin⁺ as aerobic tumor cells (red boxes) and Hoechst^dimKeratin⁺ as hypoxic tumor cells in LLC tumors grown in mice treated with Veh or Clod. F, Quantification of aerobic or hypoxic tumor cells in E. Data are the mean ± SEM for n = 6 mice per group. *, P < 0.05 by Student t test. G, TCGA analysis between CD68 and HIF1A in 513 patients with adenocarcinoma NSCLC. P value is indicated in the graph. H, Growth of LLC tumor treated with Veh or Clod immediately prior to a single dose of 20 Gy ionizing irradiation. *, P < 0.05 by two-way ANOVA.

 

Other posts on this site on Immunology and Cancer include

The Delicate Connection: IDO (Indolamine 2, 3 dehydrogenase) and Cancer Immunology

Innovations in Tumor Immunology

T cell-mediated immune responses & signaling pathways activated by TLRs

Vaccines, Small Peptides, aptamers and Immunotherapy [9]

Report on Cancer Immunotherapy Market & Clinical Pipeline Insight

Molecular Profiling in Cancer Immunotherapy: Debraj GuhaThakurta, PhD

Immunotherapy in Cancer: A Series of Twelve Articles in the Frontier of Oncology by Larry H Bernstein, MD, FCAP

Share this:

• X
• LinkedIn
• Facebook
• Print
• Email

Like this:

Like Loading…

Read Full Post »

Steroids, Inflammation, and CAR-T Therapy

Posted in Cancer and Current Therapeutics, CANCER BIOLOGY & Innovations in Cancer Therapy, FDA, FDA Regulatory Affairs, Immuno-Oncology & Genomics, Innovation in Immunology Diagnostics, Lymphoma, Personal Health Applications: Tech Innovations serves HealhCare, Personalized and Precision Medicine & Genomic Research, tagged acute and chronic leukemias, b cell lymphoma, Cancer - General, Cancer immunotherapy, CAR-T, chemotherapeutic toxicity, Conditions and Diseases, FDA, Food and Drug Administration, Hodgkin's lymphoma, medicine, Non-Hodgkin lymphoma, Personalized medicine, research, toxicity on September 14, 2015| Leave a Comment »

Steroids, Inflammation, and CAR-T Therapy [6.3.8] (UPDATED)

Reporter: Stephen J. Williams, Ph.D.

UPDATED: 08/31/2020 (CRISPR edited CAR-T clinical trials)

Word Cloud by Daniel Menzin

Corticosteroids have been used as anticancer agents since the 1940s, with activity reported in a wide variety of solid tumors, including breast and prostate cancer, and the lymphoid hematologic malignancies. They are commonly found in regimens for acute lymphocytic leukemia, Hodgkin’s and non-Hodgkin’s lymphoma, myeloma, and chronic lymphocytic leukemia.

A great review on the mechanism of action of prednisone’s antitumoral activity is seen in

Corticosteroids in the Treatment of Neoplasms Lorraine I. McKay, PhD and John A. Cidlowski, PhD. in Holland-Frei Cancer Medicine. 6th edition.

It was first discovered that cortisone caused tumor regression in a transplantable mouse lymphosarcoma,⁸¹ a finding soon extended to a wide variety of murine lymphatic tumors. The effects of corticosteroids were also evaluated on many nonendocrine and nonlymphoid transplantable rodent tumors. Pharmacologic doses of steroid inhibited growth of various tumor systems.⁸² Tissue culture studies confirmed that lymphoid cells were the most sensitive to glucocorticoids, and responded to treatment with decreases in DNA, ribonucleic acid (RNA), and protein synthesis.⁸³ Studies of proliferating human leukemic lymphoblasts supported the hypothesis that glucocorticoids have preferential lymphocytolytic effects. The mechanism of action was initially thought to be caused by impaired energy use via decreased glucose transport and/or phosphorylation; it was later discovered that glucocorticoids induce apoptosis, or programmed cell death, in certain lymphoid cell populations.^84,85

–For review on corticosteroids in cancer therapy see more at: http://www.cancernetwork.com/review-article/corticosteroids-advanced-cancer#sthash.IwHbekuI.dpuf

However, as Dana Farber’s Dr. George Canellos, M.D. ponders in Can MOPP be replaced in the treatment of advanced Hodgkin’s disease? Semin Oncol. Canellos GP¹. 1990 Feb;17(1 Suppl 2):2-6., many dose-limiting toxicities occur with MOPP (mechlorethamine, vincristine, procarbazine, prednisone) therapy used in advanced Hodgkin’s disease.  Although, at the time, he generally was looking to establish combination therapies with less side effect, the advent of more personalized therapies as well as immunotherapies may indeed replace the older regimens for B-cell malignancies and Hodgkin’s disease, and their panels of toxicities.

Short-term side effects of prednisone (Cancer.gov prednisone description with side effects) as with all glucocorticoids, include high blood glucose levels (especially in patients with diabetes mellitus or on other medications that increase blood glucose, such as tacrolimus) and mineralocorticoid effects such as fluid retention.^[10] The mineralocorticoid effects of prednisone are minor, which is why it is not used in the management of adrenal insufficiency, unless a more potent mineralocorticoid is administered concomitantly.

Long-term side effects include Cushing’s syndrome, steroid dementia syndrome, truncal weight gain, osteoporosis, glaucoma and cataracts, type II diabetes mellitus, and depression upon dose reduction or cessation.

Therefore the oncology world has been moving toward therapies which are more selective with less dose-limiting toxicities (e.g. Rituximab), and are looking to CAR-T therapies as a possible replacement for standard chemotherapeutic regimens. However, as with prednisone, there have been serious adverse events in some CAR-T clinical trials. Luckily clinicians, as discussed below, have found supportive therapies to alleviate the most severe side effects to CAR-T.

This section will be refer to supportive therapies as those adjuvant therapy given to alleviate patient discomfort, reduce toxicities and adverse event, or support patient well-being during their course of chemotherapy, not adjuvant therapy to enhance antitumoral effect.

For more background information of CAR-T therapies and related issues please see my previous post

NIH Considers Guidelines for CAR-T therapy: Report from Recombinant DNA Advisory Committee

The following is a brief re-post of some of the important points for reference to this new posting.

1. Evolution of Chimeric Antigen Receptors

Early evidence had suggested that adoptive transfer of tumor-infiltrating lymphocytes, after depletion of circulating lymphocytes, could result in a clinical response in some tumor patients however developments showed autologous T-cells (obtained from same patient) could be engineered to express tumor-associated antigens (TAA) and replace the TILS in the clinical setting.

A brief history of construction of 2^nd and 3^rd generation CAR-T cells given by cancer.gov:

http://www.cancer.gov/cancertopics/research-updates/2013/CAR-T-Cells

Differences between  second- and third-generation chimeric antigen receptor T cells. (Adapted by permission from the American Association for Cancer Research: Lee, DW et al. The Future Is Now: Chimeric Antigen Receptors as New Targeted Therapies for Childhood Cancer. Clin Cancer Res; 2012;18(10); 2780–90. doi:10.1158/1078-0432.CCR-11-1920)

Constructing a CAR T Cell (from cancer.gov)

The first efforts to engineer T cells to be used as a cancer treatment began in the early 1990s. Since then, researchers have learned how to produce T cells that express chimeric antigen receptors (CARs) that recognize specific targets on cancer cells.

The T cells are genetically modified to produce these receptors. To do this, researchers use viral vectors that are stripped of their ability to cause illness but that retain the capacity to integrate into cells’ DNA to deliver the genetic material needed to produce the T-cell receptors.

The second- and third-generation CARs typically consist of a piece of monoclonal antibody, called a single-chain variable fragment (scFv), that resides on the outside of the T-cell membrane and is linked to stimulatory molecules (Co-stim 1 and Co-stim 2) inside the T cell. The scFv portion guides the cell to its target antigen. Once the T cell binds to its target antigen, the stimulatory molecules provide the necessary signals for the T cell to become fully active. In this fully active state, the T cells can more effectively proliferate and attack cancer cells.

2. Consideration for Design of Trials and Mitigating Toxicities

• Early Toxic effects– Cytokine Release Syndrome– The effectiveness of CART therapy has been manifested by release of high levels of cytokines resulting in fever and inflammatory sequelae. One such cytokine, interleukin 6, has been attributed to this side effect and investigators have successfully used an IL6 receptor antagonist, tocilizumab (Acterma™), to alleviate symptoms of cytokine release syndrome (see review Adoptive T-cell therapy: adverse events and safety switches by Siok-Keen Tey).

• Early Toxic effects – Over-activation of CAR T-cells; mitigation by dose escalation strategy (as authors in reference [3] proposed). Most trials give billions of genetically modified cells to a patient.
• Late Toxic Effects – long-term depletion of B-cells . For example CART directing against CD19 or CD20 on B cells may deplete the normal population of CD19 or CD20 B-cells over time; possibly managed by IgG supplementation

References

1. Ertl HC, Zaia J, Rosenberg SA, June CH, Dotti G, Kahn J, Cooper LJ, Corrigan-Curay J, Strome SE: Considerations for the clinical application of chimeric antigen receptor T cells: observations from a recombinant DNA Advisory Committee Symposium held June 15, 2010. Cancer research 2011, 71(9):3175-3181.
2. Morgan RA, Yang JC, Kitano M, Dudley ME, Laurencot CM, Rosenberg SA: Case report of a serious adverse event following the administration of T cells transduced with a chimeric antigen receptor recognizing ERBB2. Molecular therapy : the journal of the American Society of Gene Therapy 2010, 18(4):843-851.
3. Kandalaft LE, Powell DJ, Jr., Coukos G: A phase I clinical trial of adoptive transfer of folate receptor-alpha redirected autologous T cells for recurrent ovarian cancer. Journal of translational medicine 2012, 10:157.

3. Case Reports of Adverse Events and Their Amelioration During CAR-T Therapy

CAR-T Therapy have Had reports of Serious Adverse Events

From FierceBiotech UPDATED: Two deaths force MSK to hit the brakes on engineered T cell cancer study

April 6, 2014 | By John Carroll

Safety concerns forced investigators at Memorial Sloan-Kettering Cancer Center to suspend patient recruitment for an early-stage study of a closely watched approach to reengineering the immune system to fight cancer. Several days ago MSK updated a site on clinicaltrials.gov to note that it was halting recruitment for a small study using T cells reengineered with chimeric antigen receptors (CARs) against CD19-positive B cells for aggressive non-Hodgkin lymphoma, triggering concerns about the potential fallout at Juno Therapeutics, the biotech formed to commercialize the effort. And Sunday evening representatives for MSK revealed at the meeting of the American Association for Cancer Research in San Diego that the deaths of two patients spurred investigators to rethink the trial protocol on recruitment, revamping the patient profile to account for the threat of comorbidities while adjusting the dose “based on the extent of disease at the time of treatment.”

For more on this story please see

Source: http://www.fiercebiotech.com/story/memorial-sloan-kettering-hits-brakes-engineered-t-cell-cancer-study/2014-04-06

Keynote presentation by Carl H. June, recipient of The Richard V. Smalley MD 2013 Award

As reported in 2013 in Highlights and summary of the 28th annual meeting of the Society for Immunotherapy of Cancer by Paolo A Ascierto^1†, David H Munn^2†, Anna K Palucka^34† and Paul M Sondel in Journal of ImmunoTherapy of Cancer

“

Since 2005, SITC honors a luminary in the field who has significantly contributed to the advancement of cancer immunotherapy research by presenting the annual Richard V. Smalley MD Memorial Award, which is associated with the Smalley keynote lecture at the Annual SITC meeting. The awardee this year Carl H. June of the University of Pennsylvania, has led innovative translational research for over 25 years, with the most recent focus being the development of the Chimeric Antigen Receptor modified T-cell (CART) approach. Carl June summarized how the past 15 years of progress have expanded upon the original concept presented by Zelig Eshhar [4], in which variable regions of tumor-reactive monoclonal antibodies (mAbs) (V_H and V_L) are linked to transmembrane and signaling domains of T cell activating molecules to create membrane based receptors with specificity for the tumor antigen recognized by the original mAb [4]. These receptors can be transfected into T cells, for example with lentiviruses. Pre-clinical work demonstrated how CD3-ζ and 41BB signaling components enhanced proliferation and survival of T cells in hypoxic conditions. The initial clinical work has been done with CART reactive to CD-19 on malignant B cells, with progress particularly in chronic lymphocytic leukemia (CLL) in adults and acute lymphoblastic leukemia (ALL) in children [5,6]. As of the SITC meeting, CarlJune’s team had treated 35 patients with CLL and 20 with ALL. Of the 20 with ALL, ½ had relapsed after allogeneic BMT. Of these 20 children, 17 were in complete remission, and with persistent B cell aplasia; documenting the persistent effects of the CART cells. Toxicities included the persistent B cell aplasia and profound tumor lysis and cytokine storm, seen 1–2 weeks into the treatment for ALL. This cytokine storm has been ameliorated by using anti-IL6 mAb. The B cell aplasia, while undesired, is acceptable, as patients can receive passive replacement of IgG, thus making their B cells “expendable”. These CART cells can traffic into the CNS. In ALL patients, it appears that each individual CART cell (or its progeny) can destroy 1000 tumor cells. Ongoing efforts in CarlJune’s program, and at other centers, are now moving into analyses of CART reactive with other tumor targets, by using mAbs that recognize antigens expressed on other tumors. Among these are EGFR on glioblastoma, PSMA on prostate cancer, mesothelin on ovarian cancer, HER2 on breast (and other) cancers, and several other targets. Because some of these targets are also expressed on normal tissues that are “not expendable”, novel approaches are being developed to decrease the potency or longevity of the CART effect, to decrease potential toxicity. This includes generating “short lived” CART cells by inducing CAR expression with short-lived RNA, rather than transfecting with a DNA construct that remains permanently.

“

In T-Cell Immunotherapy: Looking Forward Molecular Therapy (2014); 22 9, 1564–1574. doi:10.1038/mt.2014.148 many of the leading CAR-T clinicians and investigators reported on some of the adverse events related o CAR-T therapy including

• 40 severe adverse events (SAE) had been reported from 2010 to 2013.
• B-cell aplasia
• Systemic inflammatory release syndrome (CRS) {the most sever toxicity seen}
• Tumor lysis syndrome
• CNS toxicity
• Macrophage activation syndrome

According to the investigators the systemic inflammatory release syndrome (CRS) is the most severe toxicity seen

“

The most commonly reported adverse event is CRS,⁴⁹ with about three-quarters of the patients with CRS requiring admission to an intensive care unit. In the case of CAR therapy, the onset of CRS is related to the particular signaling domain in the CAR, with early-onset CRS in the first several days after infusion related to CARs that encode a CD28 signaling domain.^4,16 By contrast, CARs encoding a 4-1BB signaling domain tend to have delayed-onset CRS (range, 7 to 50 days) after CAR T-cell infusion.⁶ CRS has also been reported after the infusion of TCR-modified T cells, with onset typically five to seven days after infusion. The development of CRS is often, but not invariably, associated with clinically beneficial tumor regression. Several cytokines have been reported to be elevated in the serum—most commonly, interferon (IFN)-γ, tumor necrosis factor (TNF)-α, and interleukin (IL)-6. Management of CRS has included supportive care, corticosteroids, etanercept, tocilizumab, and alemtuzumab. The role of suicide genes in the management of CRS remains unknown.⁵⁰

“

This supportive therapy have now been included in all protocols now and sites are engaged in developing pharmacovigilance protocol development for CAR-T therapy.

UPDATED 08/31/2020

The following articles discuss the use of the CRISPR Cas9 system to improve the efficacy and reduce immune tolerance and rejection of engineered CAR-T therapies and the evolution of the CAR-T therapy in clinical trials for lung cancer and leukemias.

CRISPR-engineered immune cells reach the bedside

Bence György Science Translational Medicine  13 May 2020: Vol. 12, Issue 543, eabb7095 DOI: 10.1126/scitranslmed.abb7095

Abstract

In a clinical trial, CRISPR editing of T cells to fight lung cancer was feasible and safe.

 

Lung cancer is the most prevalent and fatal malignancy worldwide. Whereas the overall five-year cancer survival rates in the United States increased by 16.7% over the past five decades, lung cancer five-year survival rates only increased by 5.9%. Immune checkpoint inhibitors, such as antibodies against programmed cell death protein 1 (PD-1), are front-line anticancer treatments because PD-1 ligand on tumor cells efficiently inhibits immune responses.

Lu et al. published the results of a clinical trial, which aimed at knocking out PD-1 on T cells to confer antitumor activity against metastatic non–small cell lung cancer. The T cells were expanded ex vivo, then reinfused into 12 patients. The primary aim of the trial was to test feasibility and safety, and the secondary aims included efficiency and tracking of edited T cells. Overall, the treatment was well tolerated, with only mild to moderate adverse effects and no dose-limiting toxicities. Considerable care was taken to analyze clustered regularly interspaced short palindromic repeats (CRISPR)–induced off-target effects, and the study showed that median mutation frequency was 0.05% in off-target sites. Edited T cells were detected in the peripheral blood of 11 out of 12 patients and in tumor biopsy specimens from one patient up to 52 weeks after infusion. After infusion, two patients had stable disease, and it lasted up to 76 weeks in one patient.

This trial was performed cautiously to avoid major issues with off-target effects, and the researchers used T cells with relatively low editing rates (median of 5.8%). Nevertheless, the authors observed signs of biological activity in patients with metastatic disease who had failed several other lines of treatment. To improve biological efficiency, it will be critical to increase editing rates without increasing off-target effects. Although the off-target effects were close to background level in this study, genome-wide unbiased screens will be necessary, particularly when editing rates are boosted. A separate problem to address before broader clinical translation is T cell expansion, which failed in five patients in this study.

These early data suggest that CRISPR editing of T cells in humans is feasible and safe. Several other trials are ongoing and should help assess the potential benefit of ex vivo edited immune cells. With CRISPR-edited immune cells, it may be possible to get a better grip on metastatic lung cancer and other malignancies.

Source: Science at https://stm.sciencemag.org/content/12/543/eabb7095?_ga=2.977329.1688000087.1598874689-944049349.1598112445

Highlighted Article

Lu, J. Xue, T. Deng, X. Zhou, K. Yu, L. Deng, M. Huang, X. Yi, M. Liang, Y. Wang, H. Shen, R. Tong, W. Wang, L. Li, J. Song, J. Li, X. Su, Z. Ding, Y. Gong, J. Zhu, Y. Wang, B. Zou, Y. Zhang, Y. Li, L. Zhou, Y. Liu, M. Yu, Y. Wang, X. Zhang, L. Yin, X. Xia, Y. Zeng, Q. Zhou, B. Ying, C. Chen, Y. Wei, W. Li, T. Mok, Safety and feasibility of CRISPR-edited T cells in patients with refractory non-small-cell lung cancer. Nat. Med. 26, 732–740 (2020).

Abstract

Clustered regularly interspaced short palindromic repeats (CRISPR)–Cas9 editing of immune checkpoint genes could improve the efficacy of T cell therapy, but the first necessary undertaking is to understand the safety and feasibility. Here, we report results from a first-in-human phase I clinical trial of CRISPR–Cas9 PD-1-edited T cells in patients with advanced non-small-cell lung cancer (ClinicalTrials.gov NCT02793856). Primary endpoints were safety and feasibility, and the secondary endpoint was efficacy. The exploratory objectives included tracking of edited T cells. All prespecified endpoints were met. PD-1-edited T cells were manufactured ex vivo by cotransfection using electroporation of Cas9 and single guide RNA plasmids. A total of 22 patients were enrolled; 17 had sufficient edited T cells for infusion, and 12 were able to receive treatment. All treatment-related adverse events were grade 1/2. Edited T cells were detectable in peripheral blood after infusion. The median progression-free survival was 7.7 weeks (95% confidence interval, 6.9 to 8.5 weeks) and median overall survival was 42.6 weeks (95% confidence interval, 10.3–74.9 weeks). The median mutation frequency of off-target events was 0.05% (range, 0–0.25%) at 18 candidate sites by next generation sequencing. We conclude that clinical application of CRISPR–Cas9 gene-edited T cells is generally safe and feasible. Future trials should use superior gene editing approaches to improve therapeutic efficacy.

CRISPR-engineered T cells in patients with refractory cancer

BY EDWARD A. STADTMAUER, JOSEPH A. FRAIETTA, MEGAN M. DAVIS, ADAM D. COHEN, KRISTY L. WEBER, ERIC LANCASTER, PATRICIA A. MANGAN, IRINA KULIKOVSKAYA, MINNAL GUPTA, FANG CHEN, LIFENG TIAN, VANESSA E. GONZALEZ, JUN XU, IN-YOUNG JUNG, J. JOSEPH MELENHORST, GABRIELA PLESA, JOANNE SHEA, TINA MATLAWSKI, AMANDA CERVINI, AVERY L. GAYMON, STEPHANIE DESJARDINS, ANNE LAMONTAGNE, JANUARY SALAS-MCKEE, ANDREW FESNAK, DONALD L. SIEGEL, BRUCE L. LEVINE, JULIE K. JADLOWSKY, REGINA M. YOUNG, ANNE CHEW, WEI-TING HWANG, ELIZABETH O. HEXNER, BEATRIZ M. CARRENO, CHRISTOPHER L. NOBLES, FREDERIC D. BUSHMAN, KEVIN R. PARKER, YANYAN QI, ANSUMAN T. SATPATHY, HOWARD Y. CHANG, YANGBING ZHAO, SIMON F. LACEY, CARL H. JUNE

SCIENCE 28 FEB 2020

CRISPR takes first steps in humans

CRISPR-Cas9 is a revolutionary gene-editing technology that offers the potential to treat diseases such as cancer, but the effects of CRISPR in patients are currently unknown. Stadtmauer et al. report a phase 1 clinical trial to assess the safety and feasibility of CRISPR-Cas9 gene editing in three patients with advanced cancer (see the Perspective by Hamilton and Doudna). They removed immune cells called T lymphocytes from patients and used CRISPR-Cas9 to disrupt three genes (TRAC, TRBC, and PDCD1) with the goal of improving antitumor immunity. A cancer-targeting transgene, NY-ESO-1, was also introduced to recognize tumors. The engineered cells were administered to patients and were well tolerated, with durable engraftment observed for the study duration. These encouraging observations pave the way for future trials to study CRISPR-engineered cancer immunotherapies.

Structured Abstract

INTRODUCTION

Most cancers are recognized and attacked by the immune system but can progress owing to tumor-mediated immunosuppression and immune evasion mechanisms. The infusion of ex vivo engineered T cells, termed adoptive T cell therapy, can increase the natural antitumor immune response of the patient. Gene therapy to redirect immune specificity combined with genome editing has the potential to improve the efficacy and increase the safety of engineered T cells. CRISPR coupled with CRISPR-associated protein 9 (Cas9) endonuclease is a powerful gene-editing technology that potentially allows the ability to target multiple genes in T cells to improve cancer immunotherapy.

RATIONALE

Our first-in-human, phase 1 clinical trial (clinicaltrials.gov; trial NCT03399448) was designed to test the safety and feasibility of multiplex CRISPR-Cas9 gene editing of T cells from patients with advanced, refractory cancer. A limitation of adoptively transferred T cell efficacy has been the induction of T cell dysfunction or exhaustion. We hypothesized that removing the endogenous T cell receptor (TCR) and the immune checkpoint molecule programmed cell death protein 1 (PD-1) would improve the function and persistence of engineered T cells. In addition, the removal of PD-1 has the potential to improve safety and reduce toxicity that can be caused by autoimmunity. A synthetic, cancer-specific TCR transgene (NY-ESO-1) was also introduced to recognize tumor cells. In vivo tracking and persistence of the engineered T cells were monitored to determine if the cells could persist after CRISPR-Cas9 modifications.

RESULTS

Four cell products were manufactured at clinical scale, and three patients (two with advanced refractory myeloma and one with metastatic sarcoma) were infused. The editing efficiency was consistent in all four products and varied as a function of the single guide RNA (sgRNA), with highest efficiency observed for the TCR α chain gene (TRAC) and lowest efficiency for the TCR β chain gene (TRBC). The mutations induced by CRISPR-Cas9 were highly specific for the targeted loci; however, rare off-target edits were observed. Single-cell RNA sequencing of the infused CRISPR-engineered T cells revealed that ~30% of cells had no detectable mutations, whereas ~40% had a single mutation and ~20 and ~10% of the engineered T cells were double mutated and triple mutated, respectively, at the target sequences. The edited T cells engrafted in all three patients at stable levels for at least 9 months. The persistence of the T cells expressing the engineered TCR was much more durable than in three previous clinical trials during which T cells were infused that retained expression of the endogenous TCR and endogenous PD-1. There were no clinical toxicities associated with the engineered T cells. Chromosomal translocations were observed in vitro during cell manufacturing, and these decreased over time after infusion into patients. Biopsies of bone marrow and tumor showed trafficking of T cells to the sites of tumor in all three patients. Although tumor biopsies revealed residual tumor, in both patients with myeloma, there was a reduction in the target antigens NY-ESO-1 and/or LAGE-1. This result is consistent with an on-target effect of the engineered T cells, resulting in tumor evasion.

CONCLUSION

Preliminary results from this pilot trial demonstrate that multiplex human genome engineering is safe and feasible using CRISPR-Cas9. The extended persistence of the engineered T cells indicates that preexisting immune responses to Cas9 do not appear to present a barrier to the implementation of this promising technology.

CRISPR-Cas9 engineering of T cells in cancer patients. T cells were isolated from the blood of a patient with cancer. CRISPR-Cas9 rebonuclear protein complexes loaded with three sgRNAs were electroporated into the normal T cells, resulting in gene editing of the TRAC, TRBC1, TRBC2, and PDCD1 (encoding PD-1) loci. The cells were then transduced with a lentiviral vector to express a TCR specific for the cancer-testis antigens NY-ESO-1 and LAGE-1 (right). The engineered T cells were then returned to the patient by intravenous infusion, and patients monitored for safety and efficacy. Taken from Science 28 Feb 2020:Vol. 367, Issue 6481, eaba7365 DOI: 10.1126/science.aba7365

UPDATED 10/04/2021 (Advances in CAR-T therapy for solid tumors)

The following contains a curation of the latest advances on CAR-T therapy for solid tumors, which has been a challenge for the field.

NK cells expressing a chimeric activating receptor eliminate MDSCs and rescue impaired CAR-T cell activity against solid tumors

From: Parihar, R., Rivas, C., Huynh, M., Omer, B., Lapteva, N., Metelitsa, L. S., Gottschalk, S. M., & Rooney, C. M. (2019). NK Cells Expressing a Chimeric Activating Receptor Eliminate MDSCs and Rescue Impaired CAR-T Cell Activity against Solid Tumors. Cancer immunology research, 7(3), 363–375. https://doi.org/10.1158/2326-6066.CIR-18-0572

Abstract

Solid tumors are refractory to cellular immunotherapies in part because they contain suppressive immune effectors such as myeloid-derived suppressor cells (MDSCs) that inhibit cytotoxic lymphocytes. Strategies to reverse the suppressive tumor microenvironment (TME) should also attract and activate immune effectors with antitumor activity. To address this need, we developed gene-modified natural killer (NK) cells bearing a chimeric receptor in which the activating receptor NKG2D is fused to the cytotoxic ζ-chain of the T-cell receptor (NKG2D.ζ). NKG2D.ζ–NK cells target MDSCs, which overexpress NKG2D ligands within the TME. We examined the ability of NKG2D.ζ–NK cells to eliminate MDSCs in a xenograft TME model and improve the antitumor function of tumor-directed chimeric antigen receptor (CAR)-modified T cells. We show that NKG2D.ζ–NK cells are cytotoxic against MDSCs, but spare NKG2D ligand-expressing normal tissues. NKG2D.ζ–NK cells, but not unmodified NK cells, secrete pro-inflammatory cytokines and chemokines in response to MDSCs at the tumor site and improve infiltration and antitumor activity of subsequently infused CAR-T cells, even in tumors for which an immunosuppressive TME is an impediment to treatment. Unlike endogenous NKG2D, NKG2D.ζ is not susceptible to TME-mediated down-modulation and thus maintains its function even within suppressive microenvironments. As clinical confirmation, NKG2D.ζ–NK cells generated from patients with neuroblastoma killed autologous intra-tumoral MDSCs capable of suppressing CAR-T function. A combination therapy for solid tumors that includes both NKG2D.ζ–NK cells and CAR-T cells may improve responses over therapies based on CAR-T cells alone.

INTRODUCTION

T lymphocytes can be engineered to target tumor-associated antigens by forced expression of CARs (1). Although successful when directed against leukemia-associated antigens such as CD19 (2, 3), CAR-T cell therapy for solid tumors has been less effective, with best responses in patients with minimal disease (4, 5). Solid tumors recruit inhibitory cells such as myeloid-derived suppressor cells (MDSCs) (6). These immature myeloid cells are a component of innate immunity and strengthen the suppressive TME (7, 8). The frequency of circulating or intra-tumoral MDSCs correlates with cancer stage, disease progression, and resistance to standard chemo- and radio-therapies (9). Hence, MDSCs are worth targeting in the quest to enhance CAR-T cell efficacy against solid tumors.

Natural killer (NK) cells, a lymphoid component of the innate immune system, produce MHC-unrestricted cytotoxicity and secrete pro-inflammatory cytokines and chemokines (10). NK cells also modulate the activity of antigen-presenting myeloid cells within lymphoid organs, and recruit and activate effector T cells at sites of inflammation (11, 12). NK cells express NKG2D, a cytotoxicity receptor that is activated by non-classical MHC molecules expressed on cells stressed by events such as DNA damage, hypoxia, or viral infection (13). NKG2D ligands are overexpressed on several solid tumors and on tumor-infiltrating MDSCs (14). NK cells, therefore, could alter the TME in favor of an antitumor response by eliminating suppressive elements such as MDSCs. However, the NKG2D cytotoxic adapter molecule, DAP10, is downregulated by suppressive molecules of the TME, such as TGFβ (15), limiting the antitumor functions of NK cells.

To overcome the repressive effect of the solid TME on NKG2D function, we used a retroviral vector to modify NK cells with a chimeric NKG2D receptor (NKG2D.ζ) comprising the extracellular domain of the native NKG2D molecule fused to the intracellular cytotoxic ζ-chain of the T-cell receptor (16). We hypothesized that primary human NK cells expressing NKG2D.ζ (NKG2D.ζ–NK cells) would maintain NKG2D.ζ expression within the suppressive TME, kill NKG2D ligand-expressing MDSCs, secrete pro-inflammatory cytokines and chemokines, and recruit and activate effector cells, including CAR-T cells, derived from the adaptive immune system. These benefits are not attainable from NK cells expressing the native NKG2D receptor as its functions are down-modulated in the TME. Here we show that when NK cells express NKG2D.ζ, immune suppression is sufficiently countered to enable tumor-specific CAR-T cells to persist within the TME and eradicate otherwise resistant tumors.

Go to:

MATERIALS AND METHODS

Cytokines, cell lines, and antibodies.

Recombinant human interleukin (IL)2 was obtained from National Cancer Institute Biologic Resources Branch (Frederick, MD). Recombinant human IL6, GM-CSF, IL7, and IL15 were purchased from Peprotech (Rocky Hill, NJ, USA). The human neuroblastoma cell line LAN-1 was purchased from American Type Culture Collection (Manassas, VA, USA) and cultured in DMEM culture medium supplemented with 2 mM L-glutamine (Gibco-BRL) and 10% FBS (Hyclone, Waltham, MA, USA). The human CML cell line K562 was purchased from American Type Culture Collection and cultured in complete-RPMI culture medium composed of RPMI-1640 medium (Hyclone) supplemented with 2 mM L-glutamine and 10% FBS. A modified version of parental K562 cells, genetically modified to express a membrane-bound version of IL15 and 41BB-ligand, K562-mb15–41BB-L, was kindly provided by Dr. Dario Campana (National University of Singapore). All cell lines were verified by either genetic or flow cytometry-based methods (LAN-1 and K562 authenticated by ATCC in 2009) and tested for mycoplasma contamination monthly via MycoAlert (Lonza) mycoplasma enzyme detection kit (last mycoplastma testing of LAN-1, K562 parental line, and K562-mb15–41BB-L on November 2, 2018; all negative). All cell lines were used within one month of thawing from early-passage (< 3 passages of original vial) lots.

CAR-encoding retroviral vectors.

The construction of the SFG-retroviral vector encoding GD2-CAR.41BB.ζ, as shown in Supplementary Fig. S1A, was previously described (17). The SFG-retroviral vector encoding NKG2D.ζ, an internal ribosomal entry site (IRES), and truncated CD19 (tCD19), was generated by sub-cloning NKG2D.ζ from a retroviral vector (18) kindly provided by Dr. Charles L. Sentman (Dartmouth Geisel School of Medicine, Hanover, NH, USA) into pSFG.IRES.tCD19 (19). RD114-speudotyped viral particles were produced by transient transfection in 293T cells, as previously described (20).

Expansion and retroviral transduction of human NK and T cells.

Human NK cells were activated, transduced with retroviral constructs (Fig. 1A) and expanded as previously described by our laboratory (21). Briefly, peripheral blood mononuclear cells (PBMCs) obtained from healthy donors under Baylor College of Medicine IRB-approved protocols, were cocultured with irradiated (100 Gy) K562-mb15–41BB-L at a 1:10 (NK cell:irradiated tumor cell) ratio in G-Rex^® cell culture devices (Wilson Wolf, St. Paul, MN, USA) for 4 days in Stem Cell Growth Medium (CellGenix) supplemented with 10% FBS and 500 IU/mL IL2. Cell suspensions on day 4 (containing 50–70% expanded/activated NK cells) were transduced with SFG-based retroviral vectors, as previously described (22). The transduced cell population was then subjected to secondary expansion to generate adequate cell numbers for experiments in G-Rex^® devices at the same NK cell:irradiated tumor cell ratio with 100 IU/mL IL2. This 17-day human gene-modified NK cell protocol resulted in > 97% pure CD56⁺/CD3⁻ NK cell population with avg. 77.4% ± 18.2% (n = 25) of NK cells transduced with the construct of interest. For most experiments, transduced NK cells were purified to > 95% by magnetic column selection of truncated CD19 selection marker-positive cells.

 

Open in a separate window

Figure 1.

NKG2D.ζ–NK cells expand and kill ligand-expressing targets.

(A) Schematic of SFG-based retroviral vector constructs for transduction of human NK cells. (B) Human NK cells were expanded as described in Methods and percentage of CD56⁺/CD3⁻ NK cells at time of retroviral transduction (day 4) is shown. Expanded NK cells (red circle in A) purified via depletion of CD3⁺ cells were transduced with NKG2D.ζ retroviral vector or empty vector control (referred to as “unmodified”), and transduction efficiencies are shown inset. (C) NKG2D expression on NK cells (MFI, inset) was assessed with isotype antibody as control. Non-transduced NK cells exhibited similar NKG2D expression to empty vector-transduced NK cells. * p = 0.003 vs. unmodified condition. (D) Expression of NKG2D (absolute MFI on y-axis) on NK cells from each donor (n = 25) transduced with either empty vector or NKG2D.ζ construct was determined by flow cytometry. Each pair of data points connected by a line represent cells from a single donor, to confirm surface expression of our chimeric molecule after transduction. Black line with grey block next to each group are mean MFI ± SEM. (E) NKG2D.ζ–NK cell cytotoxicity against K562 and LAN-1 tumor targets in a 4-hour ⁵¹Cr-release assay. Given that K562 and LAN-1 are both NK-sensitive targets, low E:T ratios were utilized to observe differences. Experiment is representative of at least three separate determinations from n = 10 donors. * p < 0.01 vs. unmodified NK cells at same E:T ratio. (F) NKG2D.ζ–NK cells were expanded after transduction culture (as shown in schema), and fold-expansion and cytotoxicity both pre- (day 7) and post- (day 17) secondary expansion were determined.

For production of GD2.CAR-T cells (autologous to MDSCs and NK cells), PBMCs from healthy donors were suspended in T-cell medium (TCM) consisting of RPMI-1640 supplemented with 45% Click’s Medium (Gibco-BRL), 10% FBS, and 2 mM L-glutamine, and cultured in wells pre-coated with CD3 (OKT3, CRL-8001, American Type Culture Collection) and CD28 (Clone CD28.2, BD Biosciences) antibodies for activation. Human IL15 and IL7 were added on day +1, and cells underwent retroviral transduction on day +2, as previously described (22). T-cells were used for experiments between days +9 to +14 post-transduction, with phenotype as shown in Supplementary Figs. S1B–C.

Induction and enrichment of human MDSCs.

Our method for ex vivo generation of human PBMC-derived MDSCs was derived from published reports (23), with slight modifications. Briefly, PBMCs were sequentially depleted of CD25^hi-expressing cells and CD3-expressing cells by magnetic column separation (Miltenyi Biotec). Resultant CD25^lo/−, CD3⁻ PBMCs were plated at 4×10⁶ cells/mL in complete-RPMI medium with human IL6 and GM-CSF (both at 20 ng/mL) onto 12-well culture plates (Sigma Corning) at 1 mL/well. Plates were incubated for 7 days with medium and cytokines being replenished on days 3 and 5. Resultant cells were harvested by gentle scraping and MDSCs were purified by magnetic selection using CD33 magnetic microbeads (Miltenyi Biotec). Cells were analyzed by multi-color flow cytometry for CD33, CD14, CD15, HLA-DR, CD11b, CD83, and CD163 (BD Biosciences). MDSCs were defined as either monocytic (M-MDSCs; CD14⁺, HLA-DR^low/−), PMN-MDSCs (CD14⁻, CD15⁺, CD11b⁺), or early-stage MDSCs (lineage⁻, HLA-DR^low/−, CD33⁺), as per published guidelines (24). In addition to the above markers, MDSCs were stained for PD-L1, PD-L2, and NKG2D ligands via an NKG2D-Fc chimera (BD Biosciences) followed by FITC-labeled anti-Fc. This pan-ligand staining approach was determined to be the most efficient way to assess NKG2D ligand expression on human MDSCs because (1.) NKG2D ligand expression had not previously been reported for human MDSCs and thus simultaneous evaluation of the eight different NKG2D ligands would have been required, and (2.) we found poor reproducibility in staining patterns using individual commercially-available ligand antibodies, even within the same donor.

In vitro T-cell suppression assay.

T-cell proliferation was assessed using Cell Trace Violet (Thermo Fisher) dye dilution analysis, as per manufacturer’s recommendations. Briefly, 1×10⁵ Cell Trace Violet-labeled T cells (isolated at the time of MDSC generation) were plated onto 96-well plates in the presence of plate-bound 1 μg/mL CD3 and 1 μg/mL CD28 antibodies with 50 IU/mL IL2 in the absence or presence of autologous MDSCs or peripheral blood monocytes (as a myeloid cell control) at 1:1, 4:1 and 8:1 T cell:MDSC ratios. In some experiments, only the 4:1 ratio is shown as this was determined as optimal for assessment of suppression. After 4 days of coculture, T cells were labeled with CD3 antibody and assessed for cell division using Cell Trace Violet dye dilution by flow cytometry. Percent suppression was calculated as follows: [(% proliferating T cells in the absence of MDSCs – % proliferating T cells in presence of MDSCs)/% proliferating T cells in the absence of MDSCs] x 100. Proliferation was defined as % T cells undergoing active division as represented by Cell Trace Violet dilution peaks, as previously described (25).

In vitro CAR-T chemotaxis assay.

Transwell 5-μm pore inserts (Corning, Somerset, NJ) for migration experiments were prepared by coating with 0.01% gelatin at 37 °C overnight, followed by 3 μg of human fibronectin (Life Technologies, Grand Island, NY) at 37 °C for 3 hours to mimic endothelial and extracellular matrix components, as previously described (26). Briefly, 2×10⁵ purified GD2.CAR-T cells were placed in 100 μL of TCM in the upper chambers of the pre-coated Transwell inserts that were then transferred into wells of a 24-well plate. Culture supernatants (400 μL) from NKG2D.ζ or unmodified NK cells cultured with autologous MDSCs or monocytes, were placed in the lower chambers of the wells. Plain medium or medium supplemented with 1 μg/mL of the T-cell recruiting chemokine, MIG, served as negative and positive controls, respectively. The plates were then incubated for 4 hours at 37 °C with 5% CO₂, followed by a 10-minute incubation at 4 °C to loosen any cells adhering to the undersides of the insert membranes. The fluid in the lower chambers was collected separately and migrated cells were counted using trypan blue exclusion. The cells were analyzed for CAR expression by flow cytometry to confirm phenotype of migrated T cells.

In vivo tumor microenvironment model.

12–16 week old female NSG mice were implanted subcutaneously in the dorsal right flank with 1×10⁶ Firefly luciferase(FfLuc)-expressing LAN-1 neuroblastoma cells admixed with 3×10⁵ ex vivo-generated MDSCs, suspended in 100 μL of basement membrane Matrigel (Corning). Matrigel basement membrane was important in keeping tumor and MDSCs confined so as to establish a localized solid TME. 10–14 days later, when tumors measured at least 100 mm³ by caliper measurement, mice were injected intravenously with 5×10⁶ GD2.CAR-T cells. Tumor growth was measured twice weekly by live bioluminescence imaging using the IVIS^® system (IVIS, Xenogen Corporation) 10 minutes after 150 mg/kg D-luciferin (Xenogen)/mouse was injected intraperitoneally. In experiments examining the ability of NKG2D.ζ–NK cells to reduce intra-tumoral MDSCs, 1×10⁷ unmodified or NKG2D.ζ–NK cells were injected intravenously when tumors measured at least 100 mm³. At end of experiment, tumors were harvested en bloc, digested ex vivo, and intra-tumoral human MDSCs (CD33⁺, HLA-DR^low cells) were enumerated by flow cytometry. The absolute number of human MDSCs within a tumor digest was enumerated per mouse (n = 5 mice/group), compared to pre-treatment MDSC numbers, and presented as mean % MDSCs remaining per treatment group. In experiments examining the effects of NKG2D.ζ–NK cells on GD2.CAR-T cell antitumor activity, 5×10⁶ (cell dose chosen to mitigate direct antitumor effects of NK cells) unmodified or NKG2D.ζ–NK cells were injected intravenously 3 days prior to GD2.CAR-T injection. In GD2.CAR-T cell homing experiments, CAR-T were transduced with GFP-luciferase retroviral construct prior to injection into mice bearing unmodified tumor cells (27). Mice received 5000 IU human IL2 intraperitoneally three times per week for 3 weeks following NK cell injection to promote NK cell survival in NSG mice (28). Tumor size was measured twice weekly with calipers and the mice were imaged for bioluminescence signal from T cells at the same time. Mice were euthanized for excessive tumor burden, as per protocol guidelines. The animal studies protocol was approved by Baylor College of Medicine Institutional Animal Care and Use Committee and mice were treated in strict accordance with the institutional guidelines for animal care.

Immunohistochemistry of neuroblastoma xenografts.

On day 32 of in vivo experiments, animals were sacrificed, tumors were harvested and sectioned bluntly ex vivo to separate tumor periphery (outer 1/3 of tumor volume) vs. core (non-necrotic inner 2/3 of tumor volume), and n = 5 sections/tumor sample were analyzed for presence of GD2.CAR-T and NKG2D.ζ–NK cells by H&E and human CD3 and CD57 immunostaining performed by the Human Tissue Acquisition and Pathology Core of Baylor College of Medicine. Lack of CD57 expression on infused GD2.CAR-T was confirmed by flow cytometry prior to administration. CD57 was chosen as the marker for NK cells in tumor tissue in our study because LAN-1 tumors naturally express the prototypical NK marker CD56, truncated CD19 expression was inadequate for in situ staining, and CD57 had previously been used as a marker for tissue-localized activated NK cells (29). The number of human CD3+ and CD57+ cells in representative sections of tumors from periphery vs. core of the treatment groups indicated were enumerated per high-powered field (HPF) at 40x magnification and percent of the total number of cells enumerated within tumors found in the periphery vs. core in each treatment group indicated from tumors with and without MDSCs is shown as mean ± SEM of n = 5 sections/periphery or core, n = 5 tumors/group.

Analysis of intra-tumoral MDSCs from patients with neuroblastoma.

Tumor tissue and matched peripheral blood of neuroblastoma patients obtained in the context of a specimen/laboratory study after patient identification had been removed were thawed and analyzed for MDSC subsets by flow cytometry or utilized in in vitro assays, as described in legends or Results. The tissue acquisition protocol was performed after review and approval by the Baylor College of Medicine Institutional Review Board. Briefly, subjects with a diagnosis of high-risk or intermediate-risk neuroblastoma were eligible to participate. Written informed consent, or appropriate assent for participation, in accordance with the Declaration of Helsinki was obtained from each subject or subject’s guardian for procurement of patient blood and tumor tissue and for subsequent analyses of stored patient materials.

Statistics.

Data are presented as mean ± SEM of either experimental replicates or number of donors, as indicated. Paired two-tailed t-test was used to determine significance of differences between means with p < 0.05 indicating a significant difference. For in vivo bioluminescence, changes in tumor radiance from baseline at each time point were calculated and compared between groups using two-sample t-test. Multiple group comparisons were conducted via ANOVA via GraphPad Prism v7 software. Survival determined from the time of tumor cell injection was analyzed by Kaplan-Meier and differences in survival between groups were compared by the log-rank test.

Go to:

RESULTS

NKG2D.ζ NK cells expand and have cytotoxicity against target cells.

To increase killing of NKG2D ligand-expressing MDSCs, we generated primary human NK cells stably expressing NKG2D.ζ and a truncated CD19 (tCD19) marker from a retroviral vector (Fig. 1A). NK cells were expanded from PBMCs obtained from normal donors, transduced with retroviral construct expressing chimeric NKG2D, then cultured for 3 additional days. Transduction efficiency, as measured by the expression of tCD19 on CD56⁺CD3⁻ NK cells after the additional 3 days, was 71.3 ± 16% (n = 25 normal donors) and produced a 5.4 ± 1.1-fold increase in NKG2D expression on the NK cell surface (Fig. 1B–D). NKG2D.ζ–NK cells showed greater cytotoxicity (79.2 ± 5.6%, n = 10 normal donors) against wild-type K562, a highly NK cell-sensitive tumor cell line that naturally expresses NKG2D ligands, than mock vector-transduced (hereafter referred to as, unmodified) NK cells (40.5 ± 2.1%) at 2:1 E:T ratio in a 4-hr cytotoxicity assay (Fig. 1E). In contrast, transgenic NKG2D.ζ expression did not increase NK cell killing of LAN-1 neuroblastoma cells that are marginally NK-sensitive, but lack NKG2D ligands. To determine if in vitro expansion affected the cytotoxic function of NKG2D.ζ–NK cells, we secondarily expanded NKG2D.ζ–NK cells for an additional 10-days (Fig. 1F schema). As seen in Fig. 1F, NKG2D.ζ–NK cells expanded (120 ± 7.3-fold by day 17 of culture; n = 10 donors) similarly to unmodified and non-transduced NK cells and maintained stable cytotoxic function between days 7 and 17 of expansion. Thus, we generated and expanded high numbers of primary human NKG2D.ζ-expressing NK cells capable of cytotoxicity against ligand-expressing targets, even after prolonged culture.

Transgenic NKG2D.ζ is unaffected by TGFβ or soluble NKG2D ligands.

Expression of the native NKG2D receptor on NK cells is down-modulated by tumor-derived TGFβ and soluble NKG2D ligands, both of which are abundant in the TME (15, 30) and likely impair NK cell function in solid tumors. To determine the effect of TGFβ and soluble NKG2D ligands on NKG2D.ζ receptor expression and function, we cultured NKG2D.ζ–NK cells in the presence of TGFβ or the soluble NKG2D ligands, MICA and MICB, and examined NKG2D expression and NK cytotoxicity after 24-, 48-, and 72-hours. After exposure to TGFβ or soluble MICA/B, unmodified NK cells significantly down-regulated NKG2D (MFI of 25 vs. 95 in non-exposed NK cells at 48 hours) and were less cytotoxic (20 ± 5.1% killing vs. 40 ± 3.7% killing by non-exposed NK cells at 48 hours) to NKG2D ligand-expressing K562 targets (Fig. 2A, ​,B).B). In contrast, NKG2D.ζ–NK cells maintained NKG2D expression and cytotoxicity after exposure to the same concentrations of TGFβ and soluble MICA/B (Fig. 2C, ​,D).D). This lack of sensitivity to down-regulation by these tumor-associated components should benefit the function of NKG2D.ζ–NK cells within the TME.

 

Open in a separate window

Figure 2.

Transgenic NKG2D.ζ is unaffected by TGFβ or soluble NKG2D ligands.

NKG2D.ζ or unmodified NK cells (n = 5 donors) were cultured in the presence of TGFβ (5 ng/mL) (A, B) or the soluble NKG2D ligands MICA and MICB (C, D) for 24-, 48-, and 72-hours. NKG2D receptor expression was determined by flow cytometry and NK cytotoxicity against K562 targets was assessed in a 4-hr Cr-release assay at an 5:1 E:T ratio using 48-hr exposed NK cells. Viability of transduced NK cells after exposure to TGFβ for 24, 48, and 72 hours, as assessed by 7-AAD vital staining, was > 90%. * p = 0.001 vs. non-TGFβ/MICA-treated NK groups at same time-points.

Human MDSCs express NKG2D ligands and are killed by NKG2D.ζ–NK cells.

To study the effects of human NK cells on autologous MDSCs, we generated human MDSCs by culture of CD3-/CD25^lo PBMC with IL6 plus GM-CSF for 7 days, followed by CD33⁺ selection, as described in the Methods. The phenotypic characterization of these MDSCs and confirmation of their suppressive capacity is shown in Supplementary Fig. S2. Routinely, our ex vivo-generated MDSCs contained monocytic (M)-MDSC and early(e)-MDSC subsets, with few (avg. < 1%) polymorphonuclear (PMN)-MDSCs (Supplementary Fig. S2A), roughly reflecting the subset composition reported in patients with solid tumors (9, 31). The MDSCs expressed the suppressive factors TGFβ, IL6, IL10, and PDL-1 in amounts often greater than tumor cells (Supplementary Figs. S2B–C), and suppressed proliferation and cytokine secretion by autologous T cells stimulated with plate-bound CD3/CD28 antibodies (Supplementary Figs. S2D–E) and by 2^nd generation GD2.CAR-T cells encoding 4–1BB and CD3-ζ endodomains stimulated with the GD2⁺ tumor line LAN-1 (Supplementary Figs. S2F–G). As seen in Fig. 3A, MDSCs expressed as much or more NKG2D ligand than the positive control tumor line, K562 (ligand MFI of 78.2 vs. 29.7, respectively). Freshly isolated peripheral blood T cells did not express NKG2D ligands, whereas immature and mature dendritic cells expressed little, consistent with previous data (13). The neuroblastoma cell line, LAN-1, subsequently used in our in vivo TME model, did not express NKG2D ligands.

 

Open in a separate window

Figure 3.

Human MDSCs express ligands for NKG2D and are killed by NKG2D.ζ–NK cells.

(A) NKG2D ligand expression on human MDSCs by flow cytometry. Immature dendritic cells (iDC) and mature DCs (mDC) were used as myeloid controls. T cells activated with CD3 and CD28 mAbs plus 100 IU/mL IL2 for 24 hours were used as lymphocyte control. LAN-1 and K562 cells were used as negative and positive controls, respectively. MFI of NKG2D ligand expression in parenthesis. Representative data from single donor (of n = 25 normal donors). Isotype control for NKG2D staining routinely fell within the 1^st log. (B) NKG2D.ζ–NK cell cytotoxicity against autologous MDSCs as targets in a 4-hour ⁵¹Cr-release assay. In some wells of the cytotoxicity assay, a blocking mAb to NKG2D was added. Representative data from triplicate samples per data point from a single donor (of n = 25 normal donors) is shown. * p < 0.01 vs. unmodified NK cells at same E:T ratio. (C) In the same experiment as (B), the same batch of NKG2D.ζ–NK cells were analyzed for cytotoxicity against autologous B cells, monocytes, monocyte-derived iDC and mDC, and activated T cells (n = 10 donors examined). (D) M-MDSC frequency by flow cytometry from neuroblastoma tumor samples obtained from high-risk patients, as described in Methods. (E) Cytotoxicity by NKG2D.ζ–NK cells derived from patient PBMC (harvested and frozen at time of tumor sampling) against autologous tumor-derived MDSCs in a 4-hour ⁵¹Cr-release assay. Data shown are from triplicate samples per data point at a 10:1 E:T ratio. * p < 0.001 vs. unmodified NK cells from same donor. (F) NKG2D.ζ–NK cells were cocultured with autologous MDSCs at 1:1 ratio plus low-dose 50 IU/mL IL2 to maintain NK survival, and fold change in the number of each cell type from the start of coculture was determined by flow cytometry at indicated time-points. * p < 0.001 vs. NK/MDSC fold-change in unmodified NK cell cocultures. (G) Cell-free supernatants were harvested from cocultures at day 3 and analyzed for IFNγ, TNFα, IL6, and IL10 by ELISA. # p < 0.01 vs. corresponding cytokine in cocultures with unmodified NK cells. (H) NKG2D ligand expression was determined for activated T cells (ATCs) expressing NKG2D.ζ and NKG2D.ζ–NK cells. Expression of NKG2D ligands on non-transduced ATCs as control for T-cell activation. (I) NKG2D.ζ–NK cells or NKG2D.ζ T cells were cocultured with autologous ATCs at 1:1 ratio and fold change in the number of each cell type from the start of coculture was determined by flow cytometry at indicated time-points. * p < 0.001 vs. ATC fold-change at days 0 and 3 cocultures.

To evaluate MDSC susceptibility to killing by NKG2D.ζ–NK cells, we performed both short- and long-term killing assays. Fig. 3B shows enhanced killing of MDSCs by autologous NKG2D.ζ–NK cells compared to unmodified NK cells (35 ± 5.5% vs. 8 ± 2.4% cytotoxicity, respectively, at an E:T ratio of 5:1) in a 4-hr chromium-release assay. MDSC killing was dependent on NKG2D, as pre-incubation with an NKG2D blocking Ab reduced the cytotoxicity to levels achieved by unmodified NK cells. NKG2D.ζ–NK cells mediated no cytotoxicity against other autologous immune cells such as freshly-isolated monocytes, monocyte-derived mature dendritic cells, T cells, or B cells (Fig. 3C). Only immature dendritic cells, which expressed little NKG2D ligand (approx. 7% of cells; MFI 11.4), were mildly susceptible to lysis by NKG2D.ζ–NK cells (4.2 ± 1.7 % lysis at an E:T ratio of 20:1). As confirmation of the clinical applicability of our approach, we assessed whether NKG2D.ζ–NK cells generated from patient PBMCs were able to kill highly suppressive MDSCs isolated from the patient’s tumor. Tumor samples obtained from two patients with high-risk neuroblastoma at time of first biopsy/resection contained M-MDSCs (Fig. 3D). NKG2D.ζ–NK cells generated from patient PBMCs (harvested and frozen at time of tumor sampling) mediated significant cytotoxicity in vitro against M-MDSCs purified from patient tumors, whereas unmodified patient NK cells did not (Fig. 3E). These results provide further clinical evidence for the capacity of NKG2D.ζ–NK cells to eliminate MDSCs in patients with suppressive TMEs.

To determine whether NKG2D.ζ–NK cells could control MDSC survival in long-term cultures, we cocultured NKG2D.ζ–NK cells with autologous MDSCs at a 1:1 ratio for 7 days in the presence of low-dose IL2 to maintain NK survival, and quantified each cell type by flow cytometry every two days. As shown in Fig. 3F, NKG2D.ζ–NK cells expanded in cocultures (mean 9.5 ± 0.7-fold increase) with a concomitant reduction in MDSCs (mean 81.3 ± 9.4-fold decrease), whereas unmodified NK cells failed to expand or eliminate MDSCs. NK cells cultured alone or with autologous monocyte controls did not expand (0.8 ± 0.1-fold change). As seen in Fig. 3G, NK cell expansion and MDSC reduction correlated with a shift in the culture cytokine milieu from one that is immune suppressive (more IL6 and IL10; less IFN-γ and TNF-α) in cocultures containing unmodified NK cells, to one that is immune stimulatory and enhances CAR-T antitumor function (less IL6 and IL10; more IFN-γ and TNF-α) in cocultures containing NKG2D.ζ–NK cells. Hence, NKG2D.ζ–NK cells mediate potent cytotoxicity against suppressive MDSCs via their highly expressed NKG2D ligands. In addition, through selective depletion of MDSCs in combination with immune stimulatory cytokine secretion, NKG2D.ζ–NK cells skew the cytokine microenvironment to one that can support CAR-T effector functions (32).

Previous studies have reported that expression of chimeric NKG2D constructs in T lymphocytes can direct these cells to target NKG2D ligand-expressing tumors (16, 33). However, activated T cells (ATCs) themselves upregulate NKG2D ligands (34), with variable ligand expression intensity dependent on the T-cell activation protocol employed, leading to fratricide when the chimeric NKG2D is expressed. To determine if this off-tumor side-effect occurred when the same NKG2D.ζ was expressed in NK cells, we compared the killing of ATCs by autologous NK cells or by autologous T cells expressing our NKG2D.ζ transgene. ATCs and NKG2Dζ.-T cells both upregulated NKG2D ligands during ex vivo expansion with CD3/CD28 antibodies plus IL7 and IL15, whereas NKG2D.ζ-transduced NK cells undergoing expansion in our K562-mb15–41BB-L culture system did not (Fig. 3H). Coculture without additional stimulation of NKG2D.ζ-T cells with autologous ATCs produced fratricide, of both the NKG2D.ζ effector T cells (35 ± 7.2% decrease in cell number) and the non-transduced ATC targets (98 ± 11.5% decrease in cell number) (n = 3). By contrast, ATC numbers were unaffected by coculture with autologous NKG2D.ζ–NK cells (Fig. 3I). These results show that NK cells expressing NKG2D.ζ can kill autologous MDSCs while sparing other NKG2D ligand expressing populations, thus avoiding the fratricide seen with NKG2D.ζ-expressing T cells.

NKG2D.ζ–NK cells eliminate intra-tumoral MDSCs and reduce tumor burden.

To determine if NKG2D.ζ–NK cells could eliminate MDSCs from tumor sites in vivo, we created an MDSC-containing TME in a xenograft model of neuroblastoma. We chose NKG2D ligand-negative LAN-1 tumor for this experiment so that the effects of NKG2D.ζ–NK cells on MDSCs were not confused with their effects on the tumor cells. LAN-1 tumor cells admixed with human MDSCs were inoculated subcutaneously in NSG mice. These animals had increases in the suppressive cytokines IL10 (10-fold vs. tumor alone) and TGFβ (2.6-fold vs. tumor alone) in circulation by day 16 as compared to animals bearing tumors initiated without MDSCs, and the resultant tumors grew more rapidly due to increased neovascularization and tumor-associated stroma (Supplementary Fig. S3A–D), consistent with clinical reports of MDSC-dense tumors (35). As seen in Fig. 4A, in mice bearing NKG2D ligand-negative tumors without MDSCs, a single infusion of 1×10⁷ NKG2D.ζ–NK cells resulted in a small delay in tumor growth but eventual progression, suggesting that the LAN-1 tumor itself (a marginally NK-sensitive target) can be killed at higher NK cell doses independent of NKG2D ligand expression. In mice bearing MDSC-containing tumors, 1×10⁷ NKG2D.ζ–NK cells inhibited tumor growth (Fig. 4B), reduced NKG2D ligand-expressing intra-tumoral MDSCs with only 8.7 ± 3.5% of the input MDSCs remaining (Fig. 4C), and prolonged mouse survival (median survival of 73 days vs. 29 days after unmodified NK cells; Fig. 4D). Since LAN-1 tumor cells do not express NKG2D ligands and are only marginally sensitive to ligand-independent lysis, tumors subsequently regrew in these mice once the NKG2D.ζ–NK cells had disappeared (> day 40). Thus, NKG2D.ζ–NK cells can traffic to tumor sites and reduce intra-tumoral MDSCs but cannot themselves eradicate NKG2D ligand-negative malignant cells in our model.

 

Open in a separate window

Figure 4.

NKG2D.ζ–NK cells eliminate intra-tumoral MDSCs and reduce tumor burden.

LAN-1 tumor cells, either alone (A) or admixed with human MDSCs (B), were injected S.C. in the flanks of NSG mice. When tumors reached a volume of approx. 100 mm³ (day 14, gray block arrow inset), no NK cells (PBS control), 1×10⁷ unmodified or NKG2D.ζ–NK cells were injected I.V. and tumor growth was measured over time via calipers. * p < 0.03 vs. other conditions shown at same time point. (C) On day 26, intra-tumoral human MDSCs (CD33⁺, HLA-DR^low) were enumerated by flow cytometry and are presented as mean % MDSCs remaining per treatment group. ** p < 0.005 vs. unmodified NK treatment. (D) Survival of groups by Kaplan-Meyer analysis. # p = 0.024. Representative experiment of three performed.

NKG2D.ζ–NK cells secrete chemokines that recruit GD2.CAR-T cells.

To determine if NKG2D.ζ–NK cells can recruit T cells modified with a tumor-specific CAR to tumor sites containing MDSCs, we cocultured NKG2D.ζ–NK cells with autologous MDSCs and analyzed culture supernatants for chemokines by multiplex ELISA. Compared to unmodified NK cells, NKG2D.ζ–NK cells produce significantly greater CCL5 (RANTES; 10-fold increase), CCL3 (MIP-1α; 2-fold increase), and CCL22 (MDC; 5-fold increase) in response to autologous MDSCs (Fig. 5A). Large amounts of CXCL8 (IL8) were also produced, but there was no significant difference from the production by unmodified NK cells. Analysis of chemokine receptor expression on 2^nd generation GD2.CAR-T cells revealed CXCR1 (binds CXCL8), CCR2 (binds CCL2), CCR5 (binds CCL3), and CCR4 (binds CCL5) (see Supplementary Fig. S1C). These GD2.CAR-T cells were assayed for chemotaxis to supernatants derived from unmodified or NKG2D.ζ–NK cells cocultured with autologous MDSCs. Supernatants from NKG2D.ζ–NK cell-containing cocultures induced chemotaxis of 41.1 ± 5.5% of GD2.CAR-T cells (Fig. 5B), whereas supernatants from unmodified NK cells induced chemotaxis no greater than produced by medium (14.9 ± 6.4% vs. 17.3 ± 1.9%, respectively). Chemotaxis was not induced by supernatants from unmodified or NKG2D.ζ–NK cells cocultured with monocytes. Thus, following their encounter with MDSCs, NKG2D.ζ–NK cells secrete chemokines that recruit CAR-Ts in vitro.

 

Open in a separate window

Figure 5.

NKG2D.ζ–NK cells secrete chemokines that recruit GD2.CAR-T cells.

(A) NKG2D.ζ or unmodified NK cells were cocultured with autologous MDSCs and cell-free culture supernatants harvested at 48 hours were analyzed for chemokines CXCL8, CCL5, CCL3, and CCL22 by ELISA. Shown are mean chemokine concentration ± SEM for n = 5 cocultures/donor (data from one of five representative donors is shown). * p < 0.005 vs. unmodified NK cocultures. (B) GD2.CAR-T cells were assayed for chemotaxis in Transwells (described in Methods) in response to supernatants derived from unmodified or NKG2D.ζ–NK cells cocultured with autologous MDSCs. Supernatants derived from monocyte (non-suppressive myeloid cell control)-stimulated NK cells were also used. # p < 0.001 vs. Medium, ** p = 0.009 vs. “unmodified NK plus MDSCs” condition. (C) LAN-1 tumor cells, alone or admixed with human MDSCs, were injected S.C. into the flank of NSG mice. When tumors reached a volume ~100 mm³, 5×10⁶ GD2.CAR-T cells were injected I.V. alone on day 13 (GD2.CAR-T), or preceded by 5×10⁶ NKG2D.ζ–NK cells I.V. injected on day 10 (chNK + GD2.CAR-T). GD2.CAR-T signal at tumor site was measured over time via live-animal bioluminescence imaging. (D) Shown is mean ± SEM (n=5 mice/group) bioluminescent signal of GD2.CAR-T cells expressed as radiance. * p = 0.01 vs. all other groups.

NKG2D.ζ NK cells improve GD2.CAR-T cell trafficking to tumor sites.

To determine the effects of the MDSC-induced, NKG2D.ζ–NK cell chemokines on CAR-T cell recruitment in vivo, we used our MDSC-containing TME xenograft model (see Fig. 4). When tumors reached a volume of ~100 mm³ (day 10), 5×10⁶ NKG2D.ζ–NK cells were infused, followed three days later (day 13) by infusion of 5×10⁶ luciferase gene-transduced GD2.CAR-T cells. Tumor localization and expansion of GD2.CAR-T cells was measured over time via live-animal bioluminescence imaging. As seen in Fig. 5C, GD2.CAR-T cells injected alone on day 13 after tumor inoculation (without pre-administration of NKG2D.ζ–NK cells) into mice bearing tumors devoid of MDSCs localized effectively to subcutaneous tumors in the flank (4 of 5 mice showed bioluminescent signal on days 14 and 18; Fig. 5C). There was a 10.5 ± 0.8-fold increase in bioluminescent signal on day 18, with CAR-T cell bioluminescence remaining above baseline levels for the duration of the experiment (Fig. 5D). However, in tumors containing MDSCs, CAR-T cells localized poorly: only 1 of 5 mice exhibited bioluminescent signal (Fig. 5C), with only a 1.02 ± 0.1-fold increase in bioluminescent signal on day 18 and bioluminescence falling below pre-infusion levels within 10 days after injection (Fig. 5D). In contrast, pre-administration of NKG2D.ζ–NK cells on day 10 into mice bearing MDSC-containing tumors allowed subsequently infused GD2.CAR-T cells to localize effectively to tumor sites, with bioluminescence in 5 of 5 mice at the tumor site and a 10.9 ± 0.2-fold increase in bioluminescent signal on day 18, within 5 days of injection (Fig. 5D).

To determine if NKG2D.ζ–NK cells could promote GD2.CAR-T infiltration into the tumor bed, we compared the frequency of human GD2.CAR-T and human NK cells in the tumor periphery and the tumor core by immunohistochemistry (Supplementary Fig. S4A–B). In tumors without MDSCs, 89 ± 11% of the total T cells in the tumor had infiltrated into the tumor core. In contrast, a much smaller fraction (39 ± 16%) infiltrated into the core of tumors containing MDSCs, suggesting TME suppression of CAR-T infiltration. However, pre-treatment of tumors containing MDSCs with NKG2D.ζ–NK cells increased the fraction of intra-tumoral CAR-T cells (70 ± 13%) within the tumor core. Equal numbers of NKG2D.ζ–NK cells were observed within both peripheral and core samples from MDSC-positive and MDSC-negative tumors (Supplementary Fig. S5), suggesting the ability of NK cells to traffic well within tumors despite the presence of MDSCs.

Elimination of MDSCs increases antitumor activity of GD2.CAR-T cells.

To determine if the activities of NKG2D.ζ–NK cells described above enhance the antitumor function of CAR-T cells, we treated mice bearing subcutaneous, luciferase-labeled neuroblastoma containing MDSCs with GD2.CAR-T cells preceded by NKG2D.ζ–NK cells, in a similar set-up to experiments in Fig. 5C. As seen in Fig. 6A–B, a single injection of 5×10⁶ NKG2D.ζ–NK cells (a dose that achieved intra-tumoral MDSC depletion with only 26.8 ± 5.8% of the input MDSCs remaining) resulted in no significant tumor regression or prolongation of survival in mice bearing xenografts containing human MDSCs. A single infusion of 5×10⁶ GD2.CAR-T cells significantly reduced tumor in mice whose xenografts lacked human MDSCs with a median survival of 95 days (Fig. 6C–D). However, the same GD2.CAR-T cells were ineffective against xenografts containing human MDSCs, worsening overall median survival to 39 days (Fig. 6B). In contrast, when the same GD2.CAR-T cell injection was preceded 3 days earlier by a single injection of 5×10⁶ NKG2D.ζ–NK cells (that had no direct antitumor effect by themselves within the other arm of the same experiment, see Fig. 6A–B), the antitumor activity of the GD2.CAR-T cells in mice bearing MDSC-containing tumors was restored to the level observed in mice whose tumors lacked MDSCs (Fig. 6C). NKG2D.ζ–NK cells pre-injection also improved the overall survival of the mice with MDSC-containing tumors to a median 120 days with durable cure in 2 of 5 mice (Fig. 6D). Taken together, our results suggest that NKG2D.ζ–NK cells not only eliminate MDSCs from the TME, but also recruit CAR-T cells to intra-tumoral sites which facilitates antitumor efficacy.

 

Open in a separate window

Figure 6.

Elimination of MDSCs by NKG2D.ζ–NK cells increases antitumor activity of GD2.CAR-T cells.

Luciferase gene-transduced LAN-1 tumor cells, alone or admixed with human MDSCs, were injected S.C. into NSG mice. (A) When tumors reached a volume ~100 mm³, no treatment (No Tx; PBS control) or 5×10⁶ NKG2D.ζ–NK cells alone (chNK) were injected I.V. on day 10 and tumor growth was measured over time via live-animal bioluminescence imaging. Shown is mean ± SEM (n=5 mice/group) bioluminescent signal expressed as radiance. # ns, p = 0.18 vs. No treatment (+MDSC) group. (B) Survival of groups in A was determined by Kaplan-Meyer analysis. # ns, p = 0.059. (C) In other groups of mice within the same experiment, 5×10⁶ GD2.CAR-T cells were injected I.V. alone on day 13 (GD2.CAR-T), or preceded by 5×10⁶ NKG2D.ζ–NK cells injected on day 10 (chNK+GD2.CAR-T). * p = 0.001; # ns, p = 0.59 vs. each other. (D) Survival of groups in C by Kaplan-Meyer analysis. Representative experiment of 5 separate experiments. * p = 0.002; ** p = 0.001.

Go to:

DISCUSSION

We have developed a TME-disrupting approach that eliminates MDSCs and rescues MDSC-mediated impairment of tumor-directed CAR-T cells. We show that when co-implanted with a neuroblastoma cell line, human MDSCs both enhance tumor growth and suppress the infiltration, expansion, and antitumor efficacy of tumor-specific CAR T-cells. In this model, NK cells bearing a chimeric version of the activating receptor NKG2D (NKG2D.ζ–NK cells) are directly cytotoxic to autologous MDSCs, thus eliminating MDSCs from tumors. In addition, NKG2D.ζ–NK cells secrete pro-inflammatory cytokines and chemokines in response to MDSCs at the tumor site, improving CAR-T cell infiltration and function, and resulting in tumor regression and prolonged survival compared to treatment with CAR-T cells alone. Our cell therapy approach utilizes an engineered innate immune effector that targets the TME, and shows potential to enhance efficacy of combination immune-based therapies for solid tumors.

NKG2D.ζ–NK cells directly killed highly suppressive MDSCs generated in vitro as well as those from patient tumors. NKG2D.ζ–NK cells also secreted cytokines that favored immune activation in response to MDSCs. Unmodified NK cells were unable to mediate these effects. The ability of NKG2D.ζ–NK cells to eliminate MDSCs from the TME should have several beneficial effects for antitumor immunity. First, as MDSCs express suppressive cytokines such as TGFβ and the checkpoint ligands PDL-1 and PDL-2, elimination of MDSCs should help relieve the suppression of endogenous T cell responses and potentiate the activity of adoptive T cell therapies. Given that high baseline numbers of MDSCs have been reported as a biomarker of poor response in the context of trials with the checkpoint inhibitors ipilimumab and pembrolizumab (36, 37), elimination of MDSCs by NKG2D.ζ–NK cells may also enhance checkpoint inhibition. Second, elimination of MDSCs should also decrease other MDSC-associated effects, including neovascularization via their expression of VEGF, production of immunosuppressive metabolic products such as PGE₂ and adenosine, and establishment of tumor-supportive stroma via their expression of iNOS, FGF, and matrix metalloproteinases (8). In short, the ability of NKG2D.ζ–NK cells to eliminate MDSCs alters the tumor microenvironment in multiple ways that should improve antitumor immunity.

Previous strategies for modulation of MDSCs within the TME have included use of agents that block single functions such as secretion of nitric oxide (38) or expression of checkpoint molecules (39); induce MDSC differentiation such as with all-trans retinoic acid (40); or eliminate MDSCs such as with the cytotoxic agents doxorubicin or cyclophosphamide (41). The MDSC eliminating effects were dependent on continued administration of the agents, with a rapid rebound in MDSCs after discontinuation. Moreover, many of these agents have off-target toxicities that include damage to endogenous tumor-specific T cells. In contrast, NKG2D.ζ–NK cells produce prolonged and specific elimination of MDSCs with the potential to kill MDSCs that are recruited to the tumor from the bone marrow, while continually secreting cytokines and chemokines which respectively alter TME suppression and recruit and activate tumor-specific T cells. Thus, NKG2D.ζ–NK cells exert a prolonged combination of simultaneous immune modulatory effects that enhance antitumor immune function in ways that could not be achieved by previous methods that target MDSCs.

We observed no toxicity against normal hematopoietic cells when NKG2D.ζ was expressed in autologous human NK cells. Previous studies overexpressing an NKG2D.ζ receptor containing co-stimulatory endodomains (e.g., CD28 or 41BB) and DAP10, a signaling adaptor molecule for enhanced surface expression of NKG2D, in T cells showed activity against NKG2D ligand-overexpressing tumors, but at the cost of fratricide in vitro and lethal toxicity in mice (16, 33, 34). Using our standard T-cell activation/expansion protocol (22), we also observed upregulation of NKG2D ligands, leading to fratricide in T cells expressing NKG2D.ζ. When NKG2D.ζ-T cells engage NKG2D ligands expressed on normal tissues, they will not receive the physiologic NK cell-directed inhibitory inputs that would safely regulate this potent and unopposed chimeric receptor activity. By contrast, when NKG2D.ζ is expressed on NK cells, they are able to recognize inhibitory NK cell ligands such as self-MHC expressed on healthy self-tissues, counteracting otherwise unopposed positive signals from NKG2D ligands. Thus, an NK cell platform for NKG2D enhancement may limit toxicity while taking advantage of the cytotoxic and immune modulatory potential of the receptor-ligand system.

Unlike wild-type NKG2D, transgenic NKG2D.ζ expression and activity were not sensitive to down-modulation by TGFβ or soluble NKG2D ligands, allowing improved function in the TME. Native NKG2D relies solely on the intra-cytoplasmic adaptor DAP10 for mediating its cytolytic activity in human NK cells (42). TGFβ1 and soluble NKG2D ligands both decrease DAP10 gene transcription and protein activity, and thus reduce NKG2D function in endogenous NK cells (43, 44). In contrast, transgenic NKG2D.ζ does not rely on DAP10-based signaling for its activity, since signaling occurs through the ζ-chain. Thus, this construct provides a stable cytolytic pathway capable of circumventing TME-mediated down-modulation of native NKG2D activity. A previous study expressing a chimeric NKG2D.ζ molecule that incorporated DAP10 reported enhanced NK cytotoxicity compared to NKG2D.ζ alone in vitro against a variety of human cancer cell lines as well as in a xenograft model of osteosarcoma (45). However, this report did not address the susceptibility of this complex to down-modulation by TGFβ or soluble NKG2D ligands, or whether these NK cells had activity against MDSCs.

NKG2D.ζ–NK cells countered immunosuppression mediated by MDSCs leading to enhanced CAR-T cell tumor infiltration and expansion at tumor sites, CAR-T functions that are impaired in patients with solid tumors (46). Unlike the GD2.CAR-T cells in our model, NKG2D.ζ–NK cells homed effectively to MDSC-engrafted tumors and released an array of chemokines that increased T cell infiltration of tumor. Unlike pharmacologic strategies aimed at enhancing leukocyte trafficking, including administration of lymphotactin or TNFα (47), our approach does not require continuous cytokine administration. In fact, the ability of chimeric NKG2D to augment NK immune function specifically within the immunosuppressive TME provides for the local release of chemotactic factors, reflecting a more homeostatic method by which to increase CAR-T infiltration. Once there, CAR-T cells should meet an environment favorably modified by NKG2D.ζ–NK cell mediated elimination of MDSCs and production of pro-inflammatory cytokines. Indeed, elimination of MDSCs from a GD2⁺ tumor xenograft enhanced the activity of GD2.CAR-T cells in our model, including T-cell survival and intratumoral expansion. Given the suppressive effects of MDSCs in neuroblastoma (48, 49), the model shows how reversal of an MDSC-mediated suppressive microenvironment can improve antitumor functions of effector T cells.

Clinical neuroblastoma contains intense infiltrates of MDSCs (50), which are not included in tumor xenograft models currently used to study human cell therapeutics. Our data suggest that co-inoculation of tumors with suppressive components (such as MDSCs) can model TME-mediated suppression of CAR-T activity against solid tumors, and provides a method by which to understand and counter immunosuppression. Although NSG mice lack a complete immune system in which to examine the effects of multiple endogenous immune components, our ability to engraft exogenous components (e.g., human MDSCs) within our TME model provides the possibility of simulating different immunosuppressive aspects of the solid TME. In fact, further model development utilizing human inhibitory macrophages and regulatory T cells (Tregs) as additional suppressive components of the TME is currently underway in our laboratory.

In summary, we describe an approach to reverse the suppressive TME using engineered human NK cells. We have shown that generation and expansion of our NK cell product is feasible and that NKG2D.ζ–NK cells have antitumor activity within a suppressive solid tumor microenvironment without toxicity to normal NKG2D ligand-expressing tissues. Hence, the elimination of suppressive MDSCs by NKG2D.ζ–NK cells may safely enhance adoptive cellular immunotherapy for neuroblastoma and for many other tumors that are supported and protected by MDSCs.

Other posts on this site on Immunotherapy and Cancer include

Combined anti-CTLA4 and anti-PD1 immunotherapy shows promising results against advanced melanoma

Molecular Profiling in Cancer Immunotherapy: Debraj GuhaThakurta, PhD

Pancreatic Cancer: Genetics, Genomics and Immunotherapy

$20 million Novartis deal with ‘University of Pennsylvania’ to develop Ultra-Personalized Cancer Immunotherapy

Upcoming Meetings on Cancer Immunogenetics

Tang Prize for 2014: Immunity and Cancer

ipilimumab, a Drug that blocks CTLA-4 Freeing T cells to Attack Tumors @DM Anderson Cancer Center

Juno’s approach eradicated cancer cells in 10 of 12 leukemia patients, indicating potential to transform the standard of care in oncology

Report on Cancer Immunotherapy Market & Clinical Pipeline Insight

New Immunotherapy Could Fight a Range of Cancers

Share this:

• X
• LinkedIn
• Facebook
• Print
• Email

Like this:

Like Loading…

Read Full Post »

How NGS Will Revolutionize Reproductive Diagnostics: November Meeting, Boston MA

Posted in Clinical Diagnostics, Clinical Genomics, Embryology, Endocrine Diseases, Genetics & Innovations in Treatment, Genomic Testing: Methodology for Diagnosis, Next Generation Sequencing (NGS), Reproductive Andrology, Embryology, Genomic Endocrinology, Preimplantation Genetic Diagnosis and Reproductive Genomics, Reproductive Biology & Bio Instrumentation, tagged Conditions and Diseases, DNA, female reproductive system, genetic testing, genetics, genomics, health, human reproduction, medicine, National Institutes of Health, next generation sequencing, NGS, research, science on September 10, 2015| Leave a Comment »

Reporter: Stephen J. Williams, Ph.D. Reproductive Genetic Diagnostics Advances in Carrier Screening, Preimplantation Diagnostics, and POC Testing November 18-19, 2015  |  Boston, MA healthtech.com/reproductive-genetic-diagnosticsMount Sinai Hospital’s Dr. Tanmoy Mukherjee to Present at Reproductive Genetic Diagnostics ConferenceNumerical Chromosomal Abnormalities after PGS and D&C Tanmoy Mukherjee, M.D., Assistant Clinical Professor, Obstetrics, Gynecology and Reproductive Science, Mount Sinai Hospital This review provides an analysis of the most commonly identified numerical chromosome abnormalities following PGS and first trimester D&C samples in an infertile population utilizing ART. Although monosomies comprised >50% of all cytogenetic anomalies identified following PGS, there were very few identified in the post D&C samples. This suggests that while monosomies occur frequently in the IVF population, they commonly do not implant. In a CHI podcast, Dr. Mukherjee discusses the current challenges facing reproductive specialists in regards to genetic diagnosis of recurrent pregnancy loss, as well as how NGS is affecting this type of testing > Listen to Podcast Register  SAVE up to $200, Register by October 9 Learn More  |  Present a Poster  |  Sponsorship & Exhibit Information  |  View Brochure CONFERENCE-AT-A-GLANCE ADVANCES IN NGS AND OTHER TECHNOLOGIES Keynote Presentation: Current and Expanding Invitations for Preimplantation Genetic Diagnosis (PGD) Joe Leigh Simpson, MD, President for Research and Global Programs, March of Dimes Foundation Next-Generation Sequencing: Its Role in Reproductive Medicine Brynn Levy, Professor of Pathology & Cell Biology, CUMC; Director, Clinical Cytogenetics Laboratory, Co-Director, Division of Personalized Genomic Medicine, College of Physicians and Surgeons, Columbia University Medical Center, and the New York Presbyterian Hospital CCS without WGA Nathan Treff, Director, Molecular Biology Research, Reproductive Medicine Associates of New Jersey, Associate Professor, Department of Obstetrics, Gynecology, and Reproductive Sciences, Rutgers-Robert Wood Johnson Medical School, Adjunct Faculty Member, Department of Genetics, Rutgers-The State University of New Jersey Concurrent PGD for Single Gene Disorders and Aneuploidy on a Single Trophectoderm Biopsy Rebekah S. Zimmerman, Ph.D., FACMG, Director, Clinical Genetics, Foundation for Embryonic Competence Live Birth of Two Healthy Babies with Monogenic Diseases and Chromosome Abnormality Simultaneously Avoided by MALBAC-based Combined PGD and PGS Xiaoliang Sunney Xie, Ph.D., Mallinckrodt Professor of Chemistry and Chemical Biology, Department of Chemistry and Chemical Biology, Harvard University Analytical Validation of a Novel NGS-Based Pre-implantation Genetic Screening Technology Mark Umbarger, Ph.D., Director, Research and Development, Good Start Genetics CLINICAL APPLICATIONS FOR ADVANCED TESTING TECHNOLOGIES Expanded Carrier Screening for Monogenic Disorders Peter Benn, Professor, Department of Genetics and Genome Sciences, University of Connecticut Health Center Oocyte Mitochondrial Function and Testing: Implications for Assisted Reproduction Emre Seli, MD, Yale School of Medicine Preventing the Transmission of Mitochondrial Diseases through Germline Genome Editing Alejandro Ocampo, Ph.D., Research Associate, Gene Expression Laboratory – Belmonte, Salk Institute for Biological Studies Recovery and Analysis of Single (Fetal) Cells: DEPArray Based Strategy to Examine CPM and POC Farideh Bischoff, Ph.D., Executive Director, Scientific Affairs, Silicon Biosystems, Inc. > Sponsored Presentation (Opportunities Available) Numerical Chromosomal Abnormalities after PGS and D&C Tanmoy Mukherjee, M.D., Assistant Clinical Professor, Obstetrics, Gynecology and Reproductive Science, Mount Sinai Hospital EMBRYO PREPARATION, ASSESSMENT, AND TREATMENT Guidelines and Standards for Embryo Preparation: Embryo Culture, Growth and Biopsy Guidelines for Successful Genetic Diagnosis Michael A. Lee, MS, TS, ELD (ABB), Director, Laboratories, Fertility Solutions Current Status of Time-Lapse Imaging for Embryo Assessment and Selection in Clinical IVF Catherine Racowsky, Professor, Department of Obstetrics, Gynecology & Reproductive Biology, Harvard Medical School; Director, IVF Laboratory, Brigham & Women’s Hospital The Curious Case of Fresh versus Frozen Transfer Denny Sakkas, Ph.D., Scientific Director, Boston IVF Why Does IVF Fail? Finding a Single Euploid Embryo is Harder than You Think Jamie Grifo, M.D., Ph.D., Program Director, New York University Fertility Center; Professor, New York University Langone Medical Center BEST PRACTICES AND ETHICS Genetic Counseling Bridges the Gap between Complex Genetic Information and Patient Care MaryAnn W. Campion, Ed.D., MS, CGC; Director, Master’s Program in Genetic Counseling; Assistant Dean, Graduate Medical Sciences; Assistant Professor, Obstetrics and Gynecology, Boston University School of Medicine Ethical Issues of Next-Generation Sequencing and Beyond Eugene Pergament, M.D., Ph.D., FACMG, Professor, Obstetrics and Gynecology, Northwestern; Attending, Northwestern University Medical School Memorial Hospital Closing Panel: The Future of Reproductive Genetic Diagnostics: Is Reproductive Technology Straining the Seams of Ethics? Moderator: Mache Seibel, M.D., Professor, OB/GYN, University of Massachusetts Medical School; Editor, My Menopause Magazine; Author, The Estrogen Window Panelists: Rebekah S. Zimmerman, Ph.D., FACMG, Director, Clinical Genetics, Foundation for Embryonic Competence Denny Sakkas, Ph.D., Scientific Director, Boston IVF Michael A. Lee, MS, TS, ELD (ABB), Director of Laboratories, Fertility Solutions Nicholas Collins, MS, CGC, Manager, Reproductive Health Specialists, Counsyl Arrive Early and Attend Advances in Prenatal Molecular Diagnostics – Register for Both Events and SAVE!

CHI, 250 First Avenue, Suite 300, Needham, MA, 02494, Tel: 781-972-5400 | Fax: 781-972-5425

 

 

Share this:

• X
• LinkedIn
• Facebook
• Print
• Email

Like this:

Like Loading…

Read Full Post »

CRISPR/Cas9 Finds Its Way As an Important Tool For Drug Discovery & Development

Posted in Cancer and Current Therapeutics, CANCER BIOLOGY & Innovations in Cancer Therapy, Cell Biology, Cell Biology, Signaling & Cell Circuits, Conference Coverage with Social Media, CRISPR/Cas9 & Gene Editing, Disease Biology, Disease Biology, Small Molecules in Development of Therapeutic Drugs, Drug Delivery Platform Technology, Drug Toxicity, Gene Regulation, Gene Regulation and Evolution, Genetics & Innovations in Treatment, Genetics & Pharmaceutical, Metabolism, Metabolomics, Molecular Genetics & Pharmaceutical, Personalized and Precision Medicine & Genomic Research, Pharmaceutical Drug Discovery, Pharmacodynamics and Pharmacokinetics, Pharmacogenomics, Signaling & Cell Circuits, Small Molecules in Development of Therapeutic Drugs, tagged anti-cancer drugs, Cancer - General, CRISPR-Cas9, Duodna, FDA, gene editing, gene expression, genetics, genome, Genome engineering, health, MIT, mouse model, research, science, tumor model on September 2, 2015| Leave a Comment »

CRISPR/Cas9 Finds Its Way As an Important Tool For Drug Discovery & Development

  UPDATED 6/11/2021

CRISPR Diagnostics: CRISPR-dx Comes of Age: Tool in Drug Development

The past five years has seen a rapid expansion of the ability of CRISPR based tools toward diagnostic testing. Recently, CRISPR has been used to detect SARS-CoV-2 in patients. An article in the journal Science describes the different classes of CRISPR diagnostics in use today .

Update near end of post

UPDATED 8/08/2020

Association to Causation: Using GWAS to Identify Druggable Targets

A Gen Webinar Thursday, August 6, 2020; 11:00am – 12:30pm EST

See at end of post

Curator: Stephen J. Williams, Ph.D.

• 

 

CRISPR/Cas9 Finds Its Way As an Important Tool For Drug Discovery & Development, Volume 2 (Volume Two: Latest in Genomics Methodologies for Therapeutics: Gene Editing, NGS and BioInformatics, Simulations and the Genome Ontology), Part 2: CRISPR for Gene Editing and DNA Repair

The RNA-guided Cas9 nuclease from the microbial clustered regularly interspaced short palindromic repeats (CRISPR) adaptive immune system can be used to facilitate efficient genome engineering in eukaryotic cells by simply specifying a 20-nt targeting sequence within its guide RNA.

CRISPR/Cas systems are part of the adaptive immune system of bacteria and archaea, protecting them against invading nucleic acids such as viruses by cleaving the foreign DNA in a sequence-dependent manner. Although CRISPR arrays were first identified in the Escherichia coli genome in 1987 (Ishino et al., 1987), their biological function was not understood until 2005, when it was shown that the spacers were homologous to viral and plasmid sequences suggesting a role in adaptive immunity (Bolotin et al., 2005; Mojica et al., 2005; Pourcel et al., 2005). Two years later, CRISPR arrays were confirmed to provide protection against invading viruses when combined with Cas genes (Barrangou et al., 2007). The mechanism of this immune system based on RNA-mediated DNA targeting was demonstrated shortly thereafter (Brouns et al., 2008; Deltcheva et al., 2011; Garneau et al., 2010; Marraffini and Sontheimer, 2008).

Jennifer Doudna, PhD Professor of Molecular and Cell Biology and Chemistry, University of California, Berkeley Investigator, Howard Hughes Medical Institute has recently received numerous awards and accolades for the discovery of CRISPR/Cas9 as a tool for mammalian genetic manipulation as well as her primary intended research target to understand bacterial resistance to viral infection.

A good post on the matter and Dr. Doudna can be seen below:

http://pharmaceuticalintelligence.com/2014/06/13/215-245-6132014-jennifer-doudna-the-biology-of-crisprs-from-genome-defense-to-genetic-engineering/

In Delineating a Role for CRISPR-Cas9 in Pharmaceutical Targeting inheritable metabolic disorders in which may benefit from a CRISPR-Cas9 mediated therapy is discussed. However this curation is meant to focus on CRISPR/CAS9 AS A TOOL IN PRECLINICAL DRUG DEVELOPMENT.

 

Three Areas of Importance of CRISPR/Cas9 as a TOOL in Preclinical Drug Discovery Include:

1. Gene-Function Studies: CRISPR/CAS9 ability to DEFINE GENETIC LESION and INSERTION SITE
2. CRISPR/CAS9 Use in Developing Models of Disease
3. CRISPR/CAS9 Use as a Diagnostic Tool

• Using CRISPR/Cas9 in PRECLINICAL TOXICOLOGY STUDIES

I.     Gene-Function Studies: CRISPR/CAS9 ability to DEFINE GENETIC LESION and INSERTION SITE

The advent of the first tools for manipulating genetic material (cloning, PCR, transgenic technology, and before microarray and other’omic methods) allowed scientists to probe novel, individual gene functions as well as their variants and mutants in a “one-gene-at-a time” process. In essence, a gene (or mutant gene) was sequenced, cloned into expression vectors and transfected into recipient cells where function was evaluated.

However, some of the experimental issues with this methodology involved

• Lack of knowledge of insertion site of the transgene – this leads to off-target effects usually due to insertion of a transgene in front of unwanted promoters or insertion at a site resulting in gene disruption or even mutagenesis. In an extreme case, such as transposon-induced mutagenesis may lead to transformation as described in an earlier post on this site How Mobile Elements in “Junk” DNA Promote Cancer – Part 1: Transposon-mediated Tumorigenesis

• Most transfections experiments result in NON ISOGENIC cell lines – by definition the insertion of a transgene alters the genetic makeup of a cell line. Simple transfection experiments with one transgene compared to a “null” transfectant compares non-isogenic lines, possibly confusing the interpretation of gene-function studies. Therefore a common technique is to develop cell lines with inducible gene expression, thereby allowing the investigator to compare a gene’s effect in ISOGENIC cell lines.

1. Use of CRSPR in Highthrough-put Screening of Genetic Function

A very nice presentation and summary of CRSPR’s use in determining gene function in a high-throughput manner can be found below

www.rna.uzh.ch/events/journalclub/20140429JCCaihong.pdf

1. Determining Off-target Effects of Gene Therapy Simplified with CRSPR

In GUIDE-seq: First genome-wide method of detecting off-target DNA breaks induced by CRISPR-Cas nucleases (from This Journal’s series on Live Meeting Coverage) at a 2014 Koch lecture

Shengdar Q Tsai and J Keith Joung describe

“

an approach for global detection of DNA double-stranded breaks (DSBs) introduced by RGNs and potentially other nucleases. This method, called genome-wide, unbiased identification of DSBs enabled by sequencing (GUIDE-seq), relies on capture of double-stranded oligodeoxynucleotides into DSBs. Application of GUIDE-seq to 13 RGNs in two human cell lines revealed wide variability in RGN off-target activities and unappreciated characteristics of off-target sequences. The majority of identified sites were not detected by existing computational methods or chromatin immunoprecipitation sequencing (ChIP-seq). GUIDE-seq also identified RGN-independent genomic breakpoint ‘hotspots’.

SOURCE http://www.nature.com/nbt/journal/vaop/ncurrent/full/nbt.3117.html

“

II. CRISPR/Cas9 Use in Developing Models of Disease

 

1. Developing Animal Tumor Models

In a post this year I discussed a talk at the recent 2015 AACR National Meeting on a laboratories ability to use CRISPR gene editing in-vivo to produce a hepatocarcinoma using viral delivery. The post can be seen here: Notes from Opening Plenary Session – The Genome and Beyond from the 2015 AACR Meeting in Philadelphia PA; Sunday April 19, 2015

1) In this talk Dr. Tyler Jacks discussed his use of CRSPR to generate a mouse model of liver tumor in an immunocompetent mouse. Some notes from this talk are given below

1. B) Engineering Cancer Genomes: Tyler Jacks, Ph.D.; Director, Koch Institute for Integrative Cancer Research

• Cancer GEM’s (genetically engineered mouse models of cancer) had moved from transgenics to defined oncogenes
• Observation that p53 -/- mice develop spontaneous tumors (lymphomas)
• then GEMs moved to Cre/Lox systems to generate mice with deletions however these tumor models require lots of animals, much time to create, expensive to keep;
• figured can use CRSPR/Cas9 as rapid, inexpensive way to generate engineered mice and tumor models
• he used CRSPR/Cas9 vectors targeting PTEN to introduce PTEN mutations in-vivo to hepatocytes; when they also introduced p53 mutations produced hemangiosarcomas; took ONLY THREE months to produce detectable tumors
• also produced liver tumors by using CRSPR/Cas9 to introduce gain of function mutation in β-catenin

See an article describing this study by MIT News “A New Way To Model Cancer: New gene-editing technique allows scientists to more rapidly study the role of mutations in tumor development.”

The original research article can be found in the August 6, 2014 issue of Nature[1]

And see also on the Jacks Lab site under Research

2)     In the Upcoming Meeting New Frontiers in Gene Editing multiple uses of CRISPR technology is discussed in relation to gene knockout/function studies, tumor model development and

New Frontiers in Gene Editing

Session Spotlight:
BUILDING IN VIVO MODELS FOR DRUG DISCOVERY

Genome Editing Animal Models in Drug Discovery
Myung Shin, Ph.D., Senior Principal Scientist, Biology-Discovery, Genetics and Pharmacogenomics, Merck Research Laboratories

Recent advances in genome editing have greatly accelerated and expanded the ability to generate animal models. These tools allow generating mouse models in condensed timeline compared to that of conventional gene-targeting knock-out/knock-in strategies. Moreover, the genome editing methods have expanded the ability to generate animal models beyond mice. In this talk, we will discuss the application of ZFN and CRISPR to generate various animal models for drug discovery programs.

In vivo Cancer Modeling and Genetic Screening Using CRISPR/Cas9
Sidi Chen, Ph.D., Postdoctoral Fellow, Laboratories of Dr. Phillip A. Sharp and Dr. Feng Zhang, Koch Institute for Integrative Cancer Research at MIT and Broad Institute of Harvard and MIT

Here we describe a genome-wide CRISPR-Cas9-mediated loss-of-function screen in tumor growth and metastasis. We mutagenized a non-metastatic mouse cancer cell line using a genome-scale library. The mutant cell pool rapidly generates metastases when transplanted into immunocompromised mice. Enriched sgRNAs in lung metastases and late stage primary tumors were found to target a small set of genes, suggesting specific loss-of-function mutations drive tumor growth and metastasis.

FEATURED PRESENTATION: In vivo Chromosome Engineering Using CRISPR-Cas9
Andrea Ventura, M.D., Ph.D., Assistant Member, Cancer Biology and Genetics Program, Memorial Sloan Kettering Cancer Center

We will discuss our experience using somatic genome editing to engineer oncogenic chromosomal rearrangements in vivo. More specifically, we will present the results of our ongoing efforts aimed at modeling cancers driven by chromosomal rearrangements using viral mediated delivery of Crispr-Cas9 to adult animals.

RNAi and CRISPR/Cas9-Based in vivo Models for Drug Discovery
Christof Fellmann, Ph.D., Postdoctoral Fellow, Laboratory of Dr. Jennifer Doudna, Department of Molecular and Cell Biology, The University of California, Berkeley

Genetically engineered mouse models (GEMMs) are a powerful tool to study disease initiation, treatment response and relapse. By combining CRISPR/Cas9 and “Sensor” validated, tetracycline-regulated “miR-E” shRNA technology, we have developed a fast and scalable platform to generate RNAi GEMMs with reversible gene silencing capability. The synergy of CRISPR/Cas9 and RNAi enabled us to not only model disease pathogenesis, but also mimic drug therapy in mice, providing us capability to perform preclinical studies in vivo.

In vivo Genome Editing Using Staphylococcus aureus Cas9
Fei Ann Ran, Ph.D., Post-doctoral Fellow, Laboratory of Dr. Feng Zhang, Broad Institute and Junior Fellow, Harvard Society of Fellows

The RNA-guided Cas9 nuclease from the bacterial CRISPR/Cas system has been adapted as a powerful tool for facilitating targeted genome editing in eukaryotes. Recently, we have identified an additional small Cas9 nuclease from Staphylococcus aureus that can be packaged with its guide RNA into a single adeno-associated virus (AAV) vector for in vivo applications. We demonstrate the use of this system for effective gene modification in adult animals and further expand the Cas9 toolbox for in vivo genome editing.

OriGene, Making the Right Tools for CRISPR Research
Xuan Liu, Ph.D., Senior Director, Marketing, OriGene

CRISPR technology has quickly revolutionized the scientific community. Its simplicity has democratized the genome editing technology and enabled every lab to consider its utility in gene function research. As the largest tool box for gene functional research, OriGene created a large collection of CRISPR-related tools, including various all-in-one vectors for gRNA cloning, donor vector backbones, genome-wide knockout kits, AAVS1 insertion vectors, etc. OriGene’s high quality products will accelerate CRISPR research.

1. Transgenic Animals : Custom Mouse and Rat Model Generation Service Using CRISPR/Cas9 by AppliedStem Cell Inc. (http://www.appliedstemcell.com/)

A critical component of producing transgenic animals is the ability of each successive generations to pass on the transgene. In her post on this site, A NEW ERA OF GENETIC MANIPULATION  Dr. Demet Sag discusses the molecular biology of Cas9 systems and their efficiency to cause point mutations which can be passed on to subsequent generations

“

This group developed a new technology for editing genes that can be transferable change to the next generation by combining microbial immune defense mechanism, CRISPR/Cas9 that is the latest ground breaking technology for translational genomics with gene therapy-like approach.

• In short, this so-called “mutagenic chain reaction” (MCR) introduces a recessive mutation defined by CRISPR/Cas9 that lead into a high rate of transferable information to the next generation. They reported that when they crossed the female MCR offspring to wild type flies, the yellow phenotype observed more than 95 percent efficiency.

“

The advantage of CRISPR/Cas9 over ZFNs or TALENs is its scalability and multiplexibility in that multiple sites within the mammalian genome can be simultaneously modified, providing a robust, high-throughput approach for gene editing in mammalian cells.

Applied StemCell, Inc. offers various services related to animal models including conventional transgenic rats, and phenotype analysis using knock-in, knock-out strategies.

Further explanation of their use of CRSPR can be found at the site below:

http://pharmaceuticalintelligence.com/2014/10/29/gene-editing-at-crispr-speed-services-and-tools/

In addition, ReproCELL Inc., a Tokyo based stem cell company, uses CRSPR to develop

· Tailored disease model cells (hiPSC-Disease Model Cells)

• 2 types of services

• ReproUNUS™-g：human iPS cell derived functional cells involving gene editing by CRISPR/Cas9 system
• eproUNUS™-p：patient derived iPS cell derived functional cells

III. Using CRISPR/Cas9 in PRECLINICAL TOXICOLOGY STUDIES

As of now it is unclear as to the strategy of pharma in how to use this technology for toxicology testing however a few companies have licensed the technology to use across their R&D platforms including

• AstraZeneca
• Thermo
• Novartis
• GE Healthcare

A recent paper used a sister technique TALEN to generate knock-in pigs which suggest that it would be possible to generate pigs with human transgenes, especially in human liver isozymes in orer to study hepatotoxicity of drugs.

Efficient bi-allelic gene knockout and site-specific knock-in mediated by TALENs in pigs

Jing Yao, Jiaojiao Huang, Tang Hai, Xianlong Wang, Guosong Qin, Hongyong Zhang, Rong Wu, Chunwei Cao, Jianzhong Jeff Xi, Zengqiang Yuan, Jianguo Zhao

Sci Rep. 2014; 4: 6926. Published online 2014 November 5. doi: 10.1038/srep06926

UPDATED 8/08/2020

Association to Causation: Using GWAS to Identify Druggable Targets

A Gen Webinar Thursday, August 6⋅11:00am – 12:30pm

This webinar is available at https://www.genengnews.com/resources/webinars/association-to-causation-using-gwas-to-identify-druggable-target/

Speakers:

Martin Kampmann, PhD

Associate Professor
UCSF
Investigator
Chan Zuckerberg Biohub

Kevin Holden, PhD

Head of Science
Synthego

Abhi Saharia, PhD

VP, Commercial Development
Synthego

Human genetics provides perhaps the single best opportunity to innovate and improve clinical success rates, through the identification of novel drug targets for complex disease. Even as correlation identifies multiple genetic variants associated with disease, it is challenging to conduct requisite functional studies to identify the causal variants, especially since most association signals map to non-coding regions of the genome.

Genetic editing technologies, such as CRISPR, have enabled the modeling of associated variants at their native loci, including non-coding loci, empowering the identification of underlying biological mechanisms of disease with potential causal genes. However, genome editing is largely manual today severely limiting scale, and forcing the use of rational filters to prioritize which variants to investigate functionally.

In this GEN webinar, we will discuss several strategies enabling large-scale functional investigation of disease-associated variants in a cost- and time-effective manner, including different types of pooled CRISPR-based screens and the development of a fully automated genome engineering platform. We will also review how optimization of genome engineering on this platform enables the engineering of disease-associated variants at scale in pluripotent cells.

• They will be presenting on use of wide scale CRSPR screens to validate druggable targets
• The presenters will also discuss new platforms for these wide scale screens

Martin Kampmann, PhD UCSF

• Multiple genetic variants associated with disease
• Big gap between accumulation of genetic variant information and functions of these variants
• CRSPRi or CRSPa (siRNA coupled or enhancer coupled CRSPR guides)
• Arrayed screens: multiplate guide RNAs and phenotype measured (phenotype can be morphology, complex biological systems like organoids or non autonomous functions
• Using pooled screens and use of suitable cell model critical for this strategy
• For example in iPSC vs. neurons has different expression patterns upon same CRSPR of UBA1
• Advantage is using CRSPR to take iPSC from diseased variant patient to make a corrected isogenic control then introduce gRNAs and use modifier screens to determine phenotypes
• Generated a platform called CRISPRbrain.org to do bioinformatics on various experiments with different guide RNAs (CRSPRs)

Abhi Saharia, PhD Syntheco

• Target identification with CSRSPR at Scale
• Nature medicine paper did GWAS and found 27 SNV associated with high risk disease and a rational filter focused on 1 SNV in noncoding region but why study a single variant and if studied all 27 would they have been able to identify a more representative druggable set?
• Goal is to reduce or eliminate these rational filters
• HALO (scalable RNA guide), ECLIPSE platform (automated generation of modified cell lines, BIOINFORMATIC platform (integrated informatics)
• Syntheco uses an electroporation with ribonucleic proteins (RNP) to give highest efficiency and minimizes off target as complex is only in cells for a short period of time
• They confirm they are doing single cell cloning by using automated microscopy to confirm single cell growth in each cloning well

Kevin Holden, Head of Science at Syntheco

• Engineering iPSc genetically modified cells at scale
• The closer you get to your target site the more efficient your CRSPR so a big factor when making guides, especially for knock-in CRSPR
• Adding a small molecule non homologous end joining inhibitor increases efficiency to 95%
• Cold shocking the cells also assists in homologous repair
• Use cleavage resistant templates

III. CRISPR/CAS9 AS A DIAGNOSTIC TOOL

     In the journal Science, Omar Abudayyeh and Jonathan Gootenberg discuss how CRISPR-based diagnostic (CRISPR-dx) tools offer a solution, and multiple CRISPR-dx products for detection of the SARS-CoV-2 RNA genome have been authorized by the US Food and Drug Administration (FDA).  In addition they discuss the work by Jiao et al. in combining this technique to develop a rapid and sensitive SARS-CoV2 diagnostic test.

Omar O. Abudayyeh, Jonathan S. Gootenberg. Science  28 May 2021: CRISPR Diagnostics
Vol. 372, Issue 6545, pp. 914-915; DOI: 10.1126/science.abi9335

Summary

Although clinical diagnostics take many forms, nucleic acid–based testing has become the gold standard for sensitive detection of many diseases, including pathogenic infections. Quantitative polymerase chain reaction (qPCR) has been widely adopted for its ability to detect only a few DNA or RNA molecules that can unambiguously specify a particular disease. However, the complexity of this technique restricts application to laboratory settings. The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic has underscored the need for the development and deployment of nucleic acid tests that are economical, easily scaled, and capable of being run in low-resource settings, without sacrifices in speed, sensitivity or specificity. CRISPR-based diagnostic (CRISPR-dx) tools offer a solution, and multiple CRISPR-dx products for detection of the SARS-CoV-2 RNA genome have been authorized by the US Food and Drug Administration (FDA). On page 941 of this issue, Jiao et al. (1) describe a new CRISPR-based tool to distinguish several SARS-CoV-2 variants in a single reaction.

Although clinical diagnostics take many forms, nucleic acid–based testing has become the gold standard for sensitive detection of many diseases, including pathogenic infections. Quantitative polymerase chain reaction (qPCR) has been widely adopted for its ability to detect only a few DNA or RNA molecules that can unambiguously specify a particular disease. However, the complexity of this technique restricts application to laboratory settings. The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic has underscored the need for the development and deployment of nucleic acid tests that are economical, easily scaled, and capable of being run in low-resource settings, without sacrifices in speed, sensitivity or specificity. CRISPR-based diagnostic (CRISPR-dx) tools offer a solution, and multiple CRISPR-dx products for detection of the SARS-CoV-2 RNA genome have been authorized by the US Food and Drug Administration (FDA). On page 941 of this issue, Jiao et al. (1) describe a new CRISPR-based tool to distinguish several SARS-CoV-2 variants in a single reaction.

There are multiple types of CRISPR systems comprising basic components of a single protein or protein complex, which cuts a specific DNA or RNA target programmed by a complementary guide sequence in a CRISPR-associated RNA (crRNA). The type V and VI systems and the CRISPR-associated endonucleases Cas12 (2, 3) and Cas13 (4, 5) bind and cut DNA or RNA, respectively. Furthermore, upon recognizing a target DNA or RNA sequence, Cas12 and Cas13 proteins exhibit “collateral activity” whereby any DNA or RNA, respectively, in the sample is cleaved regardless of its nucleic acid sequence (4, 6). Thus, reporter DNAs or RNAs, which allow for visual or fluorescent detection upon cleavage, can be added to a sample to infer the presence or absence of specific DNA or RNA species (4–8).

Initial versions of CRISPR-dx utilizing Cas13 alone were sensitive to the low picomolar range, corresponding to a limit of detection of millions of molecules in a microliter sample. To improve sensitivity, preamplification methods, such as recombinase polymerase amplification (RPA), PCR, loop-mediated isothermal amplification (LAMP), or nucleic acid sequence–based amplification (NASBA), can be used with Cas12 or Cas13 to enable a limit of detection down to a single molecule (8). This preamplification approach, applicable to both Cas12 and Cas13 (6, 7), enabled a suite of detection methods and multiplexing up to four orthogonal targets (7). Additional developments expanded CRISPR-dx readouts beyond fluorescence, including lateral flow (7), colorimetric (9), and electronic or material responsive readouts (10), allowing for instrument-free approaches. In addition, post–collateral-cleavage amplification methods, such as the use of the CRISPR-associated enzyme Csm6, have been combined with Cas13 to further increase the speed of CRISPR-dx tests (7). As an alternative to collateral-cleavage–based detection, type III CRISPR systems, which involve large multiprotein complexes capable of targeting both DNA and RNA, have been used for SARS-CoV-2 detection through production of colorimetric or fluorometric readouts (11).

FDA-authorized CRISPR-dx tests are currently only for use in centralized labs, because the most common CRISPR detection protocols require fluid handling steps and two different incubations, precluding their immediate use at the point of care. Single-step formulations have been developed to overcome this limitation, and these “one-pot” versions of CRISPR-dx are simple to run, operate at a single temperature, and run without complex equipment, producing either fluorescence or lateral flow readouts. The programmability of CRISPR makes new diagnostic tests easier to develop, and within months of the release of the SARS-CoV-2 genome, many COVID-19–specific CRISPR tests were reported and distributed around the world.

The broader capability for Cas enzyme–enhanced nucleic acid binding or cleavage has led to several other detection modalities. Cas9-based methods for cleaving nucleic acids in solution for diagnostic purposes have been combined with other detection platforms, such as destruction of undesired amplicons for preparation of next-generation sequencing libraries (12), or selective removal of alleles for nucleotide-specific detection (13). Alternatively, the programmable cleavage event from the Cas nuclease can be used to initiate an amplification reaction (14). Cas9-based DNA targeting has also been used for nucleotide detection in combination with solid-state electronics, promising an amplification-free platform for detection. In this platform, called CRISPR-Chip, the Cas9 protein binds nucleotide targets of interest (often in the context of the native genome) to graphene transistors, where the presence of these targets alters either current or voltage (15). By utilizing additional Cas9 orthologs and specific guide designs, CRISPR-Chip approaches have been tuned for single–base-pair sensitivity (15). Because they are integrated with electronic readers, CRISPR-Chip platforms may allow facile point-of-care detection with handheld devices.

 

Other related articles on CRISPR/Cas9 were published in this Open Access Online Scientific Journal, include the following:

Search Results for ‘CRISPR’

Where is the most promising avenue to success in Pharmaceuticals with CRISPR-Cas9?

CRISPR/Cas9 genome editing tool for Staphylococcus aureus Cas9 complex (SaCas9) @ MIT’s Broad Institute

Delineating a Role for CRISPR-Cas9 in Pharmaceutical Targeting

Using CRISPR to investigate pancreatic cancer

Simple technology makes CRISPR gene editing cheaper

RNAi, CRISPR, and Gene Editing: Discussions on How To’s and Best Practices @14th Annual World Preclinical Congress June 10-12, 2015 | Westin Boston Waterfront | Boston, MA

CRISPR/Cas9: Contributions on Endoribonuclease Structure and Function, Role in Immunity and Applications in Genome Engineering

CRISPR-CAS editing brings cloning of woolly mammoth one step closer to reality

GUIDE-seq: First genome-wide method of detecting off-target DNA breaks induced by CRISPR-Cas nucleases

The Patents for CRISPR, the DNA editing technology as the Biggest Biotech Discovery of the Century

CRISPR: Applications for Autoimmune Diseases @UCSF

Share this:

• X
• LinkedIn
• Facebook
• Print
• Email

Like this:

Like Loading…

Read Full Post »

Metabolic Genomics and Pharmaceutics, Vol. 1 of BioMed Series D available on Amazon Kindle

Posted in Academic Publishing, Amino acids, Anaerobic Glycolysis, Biochemical pathways, Biological Networks, Biomarkers & Medical Diagnostics, Bone Disease and Musculoskeletal Disease, Ca2+ triggered activation, Cachexia, Calcium, Calcium Signaling, Calmodulin, Calmodulin Kinase and Contraction, Cancer and Current Therapeutics, CANCER BIOLOGY & Innovations in Cancer Therapy, Cancer Informatics, Cardiac & Vascular Repair Tools Subsegment, Cardiac and Cardiovascular Surgical Procedures, Cardiac muscle regeneration, Cardiomyopathy, Cardiovascular Pharmacogenomics, Cardiovascular Research, Cell Biology, Chemical Biology and its relations to Metabolic Disease, Clinical & Translational, Clinical Diagnostics, Clinical Genomics, Competition in regenerative stem cell science, Curation, Curation methodology, Cytoskeleton, Dehydrogenase, Diabetes Mellitus, Discovery process, Disease Biology, Endocrine Diseases, Enzyme Induction, Enzymes and isoenzymes, Explanatory, Fatty acids, Folate and B12, Frontiers in Cardiology and Cardiovascular Disorders, Gene Regulation, Gene Regulation and Evolution, Genome Biology, Genomic Endocrinology, Genomic Expression, Glycobiology: Biopharmaceutical Production, Health Economics and Outcomes Research, Hexokinase, Historical relevance, Inosine nucleotides, Interviews with Scientific Leaders, Iron deficiency, Kinase, Lipid metabolism, Lipids, Liver & Digestive Diseases Research, Loss of function gene, Metabolism, Metabolomics, Methylation, Mg++, Molecular Genetics & Pharmaceutical, mtDNA, Mutant Gene Expression, Myelodysplasia, Myelofibrosis, Myocardial Ischemia, Myocardial Metabolism, Na-K-ATPase, Neurodegenerative Diseases, Neurohumoral Transmission, Nitric Oxide in Health and Disease, Nutrigenomics, Nutrition, Nutrition and Phytochemistry, Nutrition Disorders, Nutritional Supplements: Atherogenesis, Open Access Journals, Oxidative phosphorylation, Pentose monophosphate shunt, Phosphatase, Phosphorylase, Phosphorylation, PKC, Plant extract, Proteins, Proteomics, Pyridine nucleotide transhydrogenase, Pyridine nucleotides, Pyruvate Kinase, Reproductive Andrology, Embryology, Genomic Endocrinology, Preimplantation Genetic Diagnosis and Reproductive Genomics, RNA Biology, S-nitrosylation, Signaling, Signaling & Cell Circuits, Skeletal muscle regeneration, Small Molecules in Development of Therapeutic Drugs, Theoretic convergence, Transcriptomics, Translational Science, Ubiquitinylation, Warburg effect, tagged ATP, Aviva Lev-Ari, Biology, Cell Biology, cell metabolic regulation, energy metabolism, gene, genetics, health, Heart disease, Larry H. Bernstein, Lipid metabolism, metabolic analysis, metabolic disorders, Metabolomics, Proteomics, research, science on August 15, 2015| Leave a Comment »

Metabolic Genomics and Pharmaceutics, Vol. 1 of BioMed Series D available on Amazon Kindle

Reporter: Stephen S Williams, PhD

Article ID #180: Metabolic Genomics and Pharmaceutics, Vol. 1 of BioMed Series D available on Amazon Kindle. Published on 8/15/2015

WordCloud Image Produced by Adam Tubman

Leaders in Pharmaceutical Business Intelligence would like to announce the First volume of their BioMedical E-Book Series D:

Metabolic Genomics & Pharmaceutics, Vol. I

which is now available on Amazon Kindle at

http://www.amazon.com/dp/B012BB0ZF0.

This e-Book is a comprehensive review of recent Original Research on  METABOLOMICS and related opportunities for Targeted Therapy written by Experts, Authors, Writers. This is the first volume of the Series D: e-Books on BioMedicine – Metabolomics, Immunology, Infectious Diseases.  It is written for comprehension at the third year medical student level, or as a reference for licensing board exams, but it is also written for the education of a first time baccalaureate degree reader in the biological sciences.  Hopefully, it can be read with great interest by the undergraduate student who is undecided in the choice of a career. The results of Original Research are gaining value added for the e-Reader by the Methodology of Curation. The e-Book’s articles have been published on the Open Access Online Scientific Journal, since April 2012.  All new articles on this subject, will continue to be incorporated, as published with periodical updates.

We invite e-Readers to write an Article Reviews on Amazon for this e-Book on Amazon.

All forthcoming BioMed e-Book Titles can be viewed at:

http://pharmaceuticalintelligence.com/biomed-e-books/

Leaders in Pharmaceutical Business Intelligence, launched in April 2012 an Open Access Online Scientific Journal is a scientific, medical and business multi expert authoring environment in several domains of  life sciences, pharmaceutical, healthcare & medicine industries. The venture operates as an online scientific intellectual exchange at their website http://pharmaceuticalintelligence.com and for curation and reporting on frontiers in biomedical, biological sciences, healthcare economics, pharmacology, pharmaceuticals & medicine. In addition the venture publishes a Medical E-book Series available on Amazon’s Kindle platform.

Analyzing and sharing the vast and rapidly expanding volume of scientific knowledge has never been so crucial to innovation in the medical field. WE are addressing need of overcoming this scientific information overload by:

• delivering curation and summary interpretations of latest findings and innovations on an open-access, Web 2.0 platform with future goals of providing primarily concept-driven search in the near future
• providing a social platform for scientists and clinicians to enter into discussion using social media
• compiling recent discoveries and issues in yearly-updated Medical E-book Series on Amazon’s mobile Kindle platform

This curation offers better organization and visibility to the critical information useful for the next innovations in academic, clinical, and industrial research by providing these hybrid networks.

Table of Contents for Metabolic Genomics & Pharmaceutics, Vol. I

Chapter 1: Metabolic Pathways

Chapter 2: Lipid Metabolism

Chapter 3: Cell Signaling

Chapter 4: Protein Synthesis and Degradation

Chapter 5: Sub-cellular Structure

Chapter 6: Proteomics

Chapter 7: Metabolomics

Chapter 8:  Impairments in Pathological States: Endocrine Disorders; Stress

                   Hypermetabolism and Cancer

Chapter 9: Genomic Expression in Health and Disease 

 

Summary 

Epilogue

 

 

Share this:

• X
• LinkedIn
• Facebook
• Print
• Email

Like this:

Like Loading…

Read Full Post »

Cancer Biology and Genomics for Disease Diagnosis (Vol. I) Now Available for Amazon Kindle

Posted in Academic Publishing, Biochemical pathways, Cancer and Current Therapeutics, CANCER BIOLOGY & Innovations in Cancer Therapy, Cancer Informatics, Cancer Prevention: Research & Programs, Cancer Screening, Cancer Surgery of the Heart, Cell Biology, Clinical & Translational, Clinical Diagnostics, Clinical Genomics, Curation, Curation methodology, De novo synthesis, Discovery process, Disease Biology, Drug Delivery Platform Technology, Enzymes and isoenzymes, Evolutionary cognition, Experimental validation, Explanatory, FDA, FDA Regulatory Affairs, Health Economics and Outcomes Research, HealthCare IT, Historical relevance, International Global Work in Pharmaceutical, Interventional Oncology: Radiofrequency Ablation, Transarterial Chemoembolization, Microwave Ablation and Irreversible Electroporation (IRE), Interviews with Scientific Leaders, Metabolism, Metabolomics, Molecular Genetics & Pharmaceutical, Open Access Journals, Personal Health Applications: Tech Innovations serves HealhCare, Pharmaceutical R&D Informatics, Pharmaceutical R&D Investment, Proteomics, REAL TIME Conference Coverage Twitter's Hashtags and Handles per Presentation/session, Scientific & Biotech Conferences: Press Coverage, Signaling & Cell Circuits, Small Molecules in Development of Therapeutic Drugs, Technology Advance Assessment of, Theoretic convergence, tagged Amazon Kindle, anti-cancer drugs, Aviva Lev-Ari, breast cancer, breast cancer genes, Cancer - General, cancer patient management, cancer risk, Cell Biology, Chemotherapy, Clinical trial, Conditions and Diseases, Content Curation, Curation, Curation methodology, DNA, DNA Sequencing, Food and Drug Administration, genetics, genome, genomics, Harvard Medical School, health outcomes research, Larry H. Bernstein, Medical imaging, Metabolomics, National Institutes of Health, personalised medicine, Personalized medicine, Prostate cancer, research, RNA, science, Stem cell on August 14, 2015| Leave a Comment »

Cancer Biology and Genomics for Disease Diagnosis (Vol. I) Now Available for Amazon Kindle

Reporter: Stephen J Williams, PhD

Article ID #179: Cancer Biology and Genomics for Disease Diagnosis (Vol. I) Now Available for Amazon Kindle. Published on 8/14/2015

WordCloud Image Produced by Adam Tubman

Leaders in Pharmaceutical Business Intelligence would like to announce the First volume of their BioMedical E-Book Series C: e-Books on Cancer & Oncology

Volume One: Cancer Biology and Genomics for Disease Diagnosis

which is now available on Amazon Kindle at                          http://www.amazon.com/dp/B013RVYR2K.

This e-Book is a comprehensive review of recent Original Research on Cancer & Genomics including related opportunities for Targeted Therapy written by Experts, Authors, Writers. This ebook highlights some of the recent trends and discoveries in cancer research and cancer treatment, with particular attention how new technological and informatics advancements have ushered in paradigm shifts in how we think about, diagnose, and treat cancer. The results of Original Research are gaining value added for the e-Reader by the Methodology of Curation. The e-Book’s articles have been published on the Open Access Online Scientific Journal, since April 2012.  All new articles on this subject, will continue to be incorporated, as published with periodical updates.

We invite e-Readers to write an Article Reviews on Amazon for this e-Book on Amazon. All forthcoming BioMed e-Book Titles can be viewed at:

http://pharmaceuticalintelligence.com/biomed-e-books/

Leaders in Pharmaceutical Business Intelligence, launched in April 2012 an Open Access Online Scientific Journal is a scientific, medical and business multi expert authoring environment in several domains of  life sciences, pharmaceutical, healthcare & medicine industries. The venture operates as an online scientific intellectual exchange at their website http://pharmaceuticalintelligence.com and for curation and reporting on frontiers in biomedical, biological sciences, healthcare economics, pharmacology, pharmaceuticals & medicine. In addition the venture publishes a Medical E-book Series available on Amazon’s Kindle platform.

Analyzing and sharing the vast and rapidly expanding volume of scientific knowledge has never been so crucial to innovation in the medical field. WE are addressing need of overcoming this scientific information overload by:

• delivering curation and summary interpretations of latest findings and innovations
• on an open-access, Web 2.0 platform with future goals of providing primarily concept-driven search in the near future
• providing a social platform for scientists and clinicians to enter into discussion using social media
• compiling recent discoveries and issues in yearly-updated Medical E-book Series on Amazon’s mobile Kindle platform

This curation offers better organization and visibility to the critical information useful for the next innovations in academic, clinical, and industrial research by providing these hybrid networks.

Table of Contents for Cancer Biology and Genomics for Disease Diagnosis

Preface

Introduction  The evolution of cancer therapy and cancer research: How we got here?

Part I. Historical Perspective of Cancer Demographics, Etiology, and Progress in Research

Chapter 1:  The Occurrence of Cancer in World Populations

Chapter 2.  Rapid Scientific Advances Changes Our View on How Cancer Forms

Chapter 3:  A Genetic Basis and Genetic Complexity of Cancer Emerge

Chapter 4: How Epigenetic and Metabolic Factors Affect Tumor Growth

Chapter 5: Advances in Breast and Gastrointestinal Cancer Research Supports Hope for Cure

Part II. Advent of Translational Medicine, “omics”, and Personalized Medicine Ushers in New Paradigms in Cancer Treatment and Advances in Drug Development

Chapter 6:  Treatment Strategies

Chapter 7:  Personalized Medicine and Targeted Therapy

Part III.Translational Medicine, Genomics, and New Technologies Converge to Improve Early Detection

Chapter 8:  Diagnosis                                     

Chapter 9:  Detection

Chapter 10:  Biomarkers

Chapter 11:  Imaging In Cancer

Chapter 12: Nanotechnology Imparts New Advances in Cancer Treatment, Detection, &  Imaging                                 

Epilogue by Larry H. Bernstein, MD, FACP: Envisioning New Insights in Cancer Translational Biology

 

Share this:

• X
• LinkedIn
• Facebook
• Print
• Email

Like this:

Like Loading…

Read Full Post »

« Newer Posts - Older Posts »

• Follow Blog via Email

  Enter your email address to follow this blog and receive notifications of new posts by email.

  Email Address

  Follow

  Join 2,040 other subscribers

• Recent Posts

  • Protected: KOL on Competitive Dynamics: LPBI Group’s Founder’s Radar Screens on AI in Health, Life Sciences & BioPharma June 15, 2026
  • Tumor Infiltrating Lymphocytes (TIL) as a first of kind FDA approved immunotherapy for cancer June 12, 2026
  • A Systematic Analysis of Competitive Dynamics in the AI Revolution — Strategic Relevance to LPBI Group’s Mission – Alex Wissner-Gross Daily Newsletters by KOL (March 1 – June 10, 2026, to be extended to Present) June 11, 2026
  • In Memoriam: Professor Yitzhak Apeloig, President and Distinguised Professor of the Technion June 4, 2026
  • Top VC Investors in AI / Health AI in 2026 May 26, 2026
  • Grok thinks like PhDs – Hybrid Model for Autonomous Update of Doctoral Dissertations with Original PhD Student Author editing and acceptance of Grok’s updated output. 3rd Joint article, a pilot study for Validation of an Autonomous Journal Articles Updating System (AJAUS) tested on Autonomous Update of Aviva Lev-Ari, PhD, RN Doctoral Thesis, UC, Berkeley, 1983. January 31, 2026
  • 2026 World Economic Forum, 1/19 – 1/23/2026, Davos, Switzerland, LPBI Group’s KOLs interpretation of AI in Health Videos January 24, 2026
  • Evolving LPBI Group’s Portfolio of Intellectual Properties (IP): From 2021 Vision to 2026 Reality January 12, 2026
  • Aviva Lev-Ari, PhD, RN – Biography ->> Grokepedia Entry January 11, 2026
  • List of Articles included in the Article SELECTION from Collection of Aviva Lev-Ari, PhD, RN Scientific Articles on PULSE on LinkedIn.com for Training Small Language Models (SLMs) in Domain-aware Content of Medical, Pharmaceutical, Life Sciences and Healthcare by 15 Subjects Matter January 10, 2026

• Archives

  Archives Select Month June 2026  (4) May 2026  (1) January 2026  (10) December 2025  (8) November 2025  (8) October 2025  (12) September 2025  (2) July 2025  (4) June 2025  (8) May 2025  (4) April 2025  (2) March 2025  (1) February 2025  (2) January 2025  (3) December 2024  (1) November 2024  (5) October 2024  (7) September 2024  (7) August 2024  (1) June 2024  (1) May 2024  (2) April 2024  (2) January 2024  (1) November 2023  (1) October 2023  (3) September 2023  (3) August 2023  (2) July 2023  (2) June 2023  (7) May 2023  (4) April 2023  (2) March 2023  (5) February 2023  (2) January 2023  (3) December 2022  (2) October 2022  (6) September 2022  (2) August 2022  (1) July 2022  (3) June 2022  (3) May 2022  (8) April 2022  (10) March 2022  (7) February 2022  (7) January 2022  (3) December 2021  (3) November 2021  (4) October 2021  (11) September 2021  (5) August 2021  (8) July 2021  (21) June 2021  (8) May 2021  (10) April 2021  (8) March 2021  (15) February 2021  (17) January 2021  (20) December 2020  (10) November 2020  (12) October 2020  (26) September 2020  (17) August 2020  (22) July 2020  (27) June 2020  (33) May 2020  (26) April 2020  (42) March 2020  (22) February 2020  (11) January 2020  (7) December 2019  (20) November 2019  (13) October 2019  (11) September 2019  (3) August 2019  (8) July 2019  (25) June 2019  (47) May 2019  (40) April 2019  (27) March 2019  (29) February 2019  (17) January 2019  (50) December 2018  (14) November 2018  (17) October 2018  (18) September 2018  (17) August 2018  (8) July 2018  (20) June 2018  (22) May 2018  (17) April 2018  (12) March 2018  (20) February 2018  (26) January 2018  (16) December 2017  (6) November 2017  (20) October 2017  (13) September 2017  (16) August 2017  (16) July 2017  (19) June 2017  (20) May 2017  (32) April 2017  (21) March 2017  (10) February 2017  (24) January 2017  (21) December 2016  (43) November 2016  (8) October 2016  (40) September 2016  (67) August 2016  (59) July 2016  (75) June 2016  (37) May 2016  (95) April 2016  (152) March 2016  (175) February 2016  (196) January 2016  (139) December 2015  (90) November 2015  (287) October 2015  (237) September 2015  (115) August 2015  (96) July 2015  (63) June 2015  (44) May 2015  (53) April 2015  (76) March 2015  (95) February 2015  (83) January 2015  (75) December 2014  (75) November 2014  (88) October 2014  (135) September 2014  (117) August 2014  (88) July 2014  (88) June 2014  (109) May 2014  (60) April 2014  (85) March 2014  (58) February 2014  (72) January 2014  (107) December 2013  (104) November 2013  (136) October 2013  (62) September 2013  (32) August 2013  (46) July 2013  (74) June 2013  (110) May 2013  (112) April 2013  (86) March 2013  (92) February 2013  (63) January 2013  (63) December 2012  (46) November 2012  (71) October 2012  (84) September 2012  (82) August 2012  (122) July 2012  (59) June 2012  (34) May 2012  (46) April 2012  (2)

• Categories

  Categories Select Category 3D Printing for Medical Application  (239)    3D Plotting Scaffolds  (44)    BioInks  (34)       Biopolymer Blend Open Porous  (18)       Dental Applications  (10)    BioPrinting in Regenerative Medicine  (77)       Cell Level  (16)       MicroEngineering Cell-Tissue & Systems  (31)       Tissue Engineering  (37)    Cardiovascular and Vascular Systems  (30)       Artificial Vascular Structures  (9)       Cardiovascular Tissue  (8)    Drug Development using MultiOrgan Chip  (11)    Drug Development/Formulation using 3D Printing  (10)    MEMS  (16)       Bio-MEMS  (12)    Organ-on-a-Chip  (11)    Programmable Sensors (Carbon Nano Tubes)  (5) 3rd Party IP: Drug DIscovery  (1) 4D Printing and Meta Materials  (10) Academic Publishing  (223)    Key Opinion Leaders in eScientific Publishing – Interviews with  (8) Advanced Drug Manufacturing Technology  (96)    Antimalarial Preparation  (8)    Autologous Cell Therapy  (14)    Automated Cell Processing  (13) Allergy and Infectious Diseases  (12) Alzheimer’s Disease  (163)    Etiology  (77)    Medical Device Therapies for Altzheimer’s Disease  (15)    Pharmacotherapy and Cell Activity  (51) Anticancer Resistance  (31) Art Exhibits on the Human Condition  (1) Art Inspires Science  (4) Article Type  (2)    Authored  (1)    Curated  (2)    Scientific report  (1) Artificial Heart  (2) Artificial Intelligence – General  (235)    An executive’s guide to AI  (11)    Artificial Intelligence – Breakthroughs in Theories and Technologies  (117)    Artificial Intelligence Applications in Health Care  (127)       Artificial Intelligence in CANCER  (39)       Artificial Intelligence in Health Care – Tools & Innovations  (75)    Artificial Intelligence in Medicine – Application for Diagnosis  (70)       Artificial intelligence applications for cardiology  (31)          AI-assisted Cardiac MRI  (10)       Artificial Intelligence in Psychiatry  (6)       Deep Learning in Pathology  (18)    Artificial Intelligence in Medicine – Applications in Therapeutics  (67)    ChatGPT, GPT-4  (7)       ChatGPT at LPBI Group  (3)       ChatGPT in Academic Education  (3)    Machine Learning  (71)       Deep Learning  (25)       Natural Language Processing (NLP)  (45)    Machine learning in predicting type 2 diabetes  (5) Auditory and vision  (13) Autism Spectrum Disorders  (10) Autoimmune Inflammatory DIseases  (24)    Crohn’s disease  (5)    Tolerance-inducing Autoimmune Disease Therapeutics  (6)    Ulcerative Colitis  (3) Autophagosome  (4) Bacterial Resistance  (25) Behavior  (26) Behavioral Genetics  (21) Big Data  (88)    Intelligent Information Systems  (51) Bio Instrumentation in Experimental Life Sciences Research  (368)    Analytical Instruments Industry  (5)    Microfuidics  (8) Bio-Ethics  (15) BioBanking  (36) Biodegradable Drug-eluting Material  (8) Bioengineering & reverse engineering design  (43) BioIT: BioInformatics  (147) BioIT: BioInformatics, NGS, Clinical & Translational, Pharmaceutical R&D Informatics, Clinical Genomics, Cancer Informatics  (135)    Advanced Computing Platform  (32)       Blockchain Transactions System  (6)          Platform for Content Monetization embedded Content Promotion  (1)    Pancreatic adenocarcinoma classifier  (4)    Simulation Modeling in NGS  (5) Biological Engineering  (43) Biological Networks  (193) Biological Networks, Gene Regulation and Evolution  (479)    Virology  (10) Biomarkers & Medical Diagnostics  (571)    VOC – Volatile Organic Compounds as BioMarkers  (2) Biomedical Measurement Science  (173) BioSimilars  (112) BioTechnology – Venture Creation  (132)    Foundations for supporting Science and Education  (14)    Philanthropy to Academic Institution  (3) BioTechnology – Venture Creation, Venture Capital  (109)    Seeking Talent  (3) BiVAD  (1) Blindness  (6) Bone Disease and Musculoskeletal Disease  (82) Brain Basis of Emotion  (5) Business Career Consideration  (1) Ca2+ triggered activation  (61) Calcium  (21) Calcium Signaling  (71) Calmodulin Kinase and Contraction  (36) Cancer – General  (186) Cancer and Current Therapeutics  (412)    interventional oncology  (49)       Breast Cancer – impalpable breast lesions  (20)       Prostate Cancer: Monitoring vs Treatment  (9) CANCER BIOLOGY & Innovations in Cancer Therapy  (1,123)    Anaerobic Glycolysis  (51)    Cachexia  (18)    Cancer Genomics  (84)       Circulating Tumor Cells (CTC)  (27)          Liquid Biopsy Chip detects an array of metastatic cancer cell markers in blood  (17)             mRNA  (6)          MagSifter chip  (1)       KRAS Mutation  (9)       Li-fraumeni syndrome.  (3)       TP53 – Germline mutations  (8)    cancer metabolism  (28)    Funding Opportunities for Cancer Research  (12)    Genomic Expression  (150)    Glioblastoma  (7)    Hexokinase  (14)    Loss of function gene  (18)    Metabolic Immuno-Oncology  (21)    Metastasis Process  (15)    Methylation  (33)    Microbiome and Responses to Cancer Therapy  (10)    Monoclonal Immunotherapy  (29)    mtDNA  (13)    Oxidative phosphorylation  (56)    Pancreatic cancer  (10)    Pyruvate Kinase  (27)    The NCI Formulary  (1)    tumor microenvironment  (16)    Warburg effect  (50) Cancer Informatics  (104) Cancer Prevention: Research & Programs  (131) Cancer Screening  (108) Cancer Vaccines: Targeting Cancer Genes for Immunotherapy  (30)    Engineering Enhanced Cancer Vaccines  (3) cancer-general  (6) Cardiac and Cardiovascular Surgical Procedures  (328)    Aortic Valve: TAVR, TAVI vs Open Heart Surgery  (91)       Prosthesis-Patient Mismatch (PPM) in TAVI vs SAVR  (2)       TAVI vs Open Heart Surgery  (6)       Transcatheter Aortic Valve Replacement via the Transcarotid Access  (3)       Transcaval TAVR Procedure  (3)       Valve-in-Valve Procedure  (5)    Atrial Fibrilation (a-Fib), Cardiac Pacing and Arrhythmias  (18)    BackBeat’s Cardiac Neuromodulation Therapy (CNT) bioelectronic therapy  (1)    CABG  (47)    Cancer Surgery of the Heart  (10)    Cardiovascular Fluid Management: algorithms  (1)    Heart Transplant  (16)    Heart-Lung Transplant  (11)    Implantation  (3)    Left Main Coronary Artery Disease (LMCAD)  (3)    Mechanical Assist Devices: LVAD, RVAD, BiVAD, Artificial Heart  (22)    Mitral Valve: Repair and Replacement  (64)       TMVR – Transcatheter Mitral Valve Repair  (5)    PCI  (108)       Bioresorbable Vascular Scaffold (BVS)  (4)       Invasive FFR for PCI  (2)       Multivessel PCI FFR Guidance  (1)       Robotic-assisted percutaneous coronary intervention  (2)       Stent Retriever in endovascular thrombectomy  (3)    Peripheral Arterial Disease & Peripheral Vascular Surgery  (65)       Abdominal Aorta  (20)       Carotid Artery  (15)       Limb ischemia  (4)       Thoracic Aorta  (16)    Pulmonary Valve Replacement and Repair  (3)    Renal Denervation  (20)    Replacement  (1)    Robotically assisted Cardiothoracic Surgery  (2)    Tricuspid Valve Repair  (7)    Vena Caval Filters: Device for Prevention of Pulmonary Embolism and Thrombosis  (2) Cardiovascular Pharmacogenomics  (171) Cargo  (3) Cell Biology  (323) Cell Biology, Signaling & Cell Circuits  (672)    Apoptosis  (17)    Autophagy-Modulating Proteins  (6)    “Antibody–enzyme conjugates”  (6)    Cell Processing System in Cell Therapy Process Development  (27)    Endoplasmic reticulum  (3)    Enzymatic mechanism underlying the synthesis of adenosine triphosphate (ATP)  (3)    Ubiquitin  (11) Cerebrovascular and Neurodegenerative Diseases  (123)    Stroke  (9) Chemical Biology and its relations to Metabolic Disease  (464)    #BIGAxisSummit  (1)    Gut Microbiome and Obesity  (8) Chemical Genetics  (350) Child and Adolescent Psychiatry  (13) Childhood cancer  (17) Childhood malnutrition  (3) children  (3) Circulating Progenitor Cells  (27)    Bone marrow derived cells  (17)    Endothelial cells  (7)    Umbilical cord cells  (6) Clinical & Translational  (238) Clinical Diagnostics  (220)    Mass automation of plasma proteins  (13) Clinical Genomics  (144) Coagulation Therapy and Internal Bleeding  (83) Cognition  (47) Commercialization  (20) Components and IRB related issues  (4) Computational Biology/Systems and Bioinformatics  (470)    Computational Histopathology  (3)    Meta-analysis of transcriptome data  (10) Conference Coverage with Social Media  (494)    MassBio  (3) coronavirus  (18) COVID-19  (20) CRISPR/Cas9 & Gene Editing  (192)    CRISPR alternative for editing genes without cutting  (14)       CAST – Alternative to CRISPR/Cas9  (3)       Transposon-encoded CRISPR–Cas systems direct RNA-guided DNA integration  (4)    CRISPR applied to Human Germ Line  (13)       Gene Editing Impact on Longevity  (6) CT  (20) Cytokines  (21) Cytoskeleton  (85) Developmental biology  (107) Diabetes Mellitus  (146)    Artificial Pancreas for Type 2 Diabetes  (4)    Artificial Pancreas for Type1 Diabetes  (8)    Gestational diabetes  (5) Diagnostic Immunology  (61) Diagnostics and Lab Tests  (128)    Liquid Biopsy: Circulating Tumor Cells in Urine and Blood  (9) Digital HealthCare – biotech & internet joint ventures  (47) Disease Biology  (334) Disease Biology, Small Molecules in Development of Therapeutic Drugs  (488) DNA repair  (73)    Apoptosis  (13)    Autophagy  (13)    Cell death pathways  (19)    Proteolysis  (8)    Proteosome  (8) Drug Delivery Platform Technology  (159)    Drug Carrier Design  (21)       Medication Remote Compliance Monitoring  (3)    Exosomes: Natural Carriers for siRNA Delivery  (9) Drug Toxicity  (74) Ecosystems & Industrial Concentration in the Medical Device Sector  (172)    Cardiac & Vascular Repair Tools Subsegment  (128)    Exec Compensation in the Cardiac & Vascular Repair Tools Subsegment  (14)    Massachusetts Niche Suppliers and National Leaders  (20) Electronic Health Record  (10) Embryology  (24) Empathy  (6) Endocrine Diseases  (60) Enzyme Induction  (46)    ion-transporting enzyme  (2)    K + -ATPase.  (1)    Na +  (2) Epigenetics and Environmental Factors  (35) Ethics and Leadership  (10) Executive Compensation – Big Pharma  (3) Fat soluble vitamins  (4) FDA  (71) FDA Regulatory Affairs  (358)    FDA, CE Mark & Global Regulatory Affairs: process management and strategic planning – GCP, GLP, ISO 14155  (52)    ISO 10993 for Product Registration: FDA & CE Mark for Development of Medical Devices and Diagnostics  (30) Fetal Ultrasound  (2) Fiction and medicine  (5) Frontiers in Cardiology and Cardiovascular Disorders  (929)    Acute Myocardial Infarction  (63)       Cardiogenic Shock  (5)    Anemia in CVD Patients  (6)    Cardio-Oncology  (4)    Cardiomyopathy  (57)    Cardiovascular Research  (187)       Myocardial metabolism, Myocardial ischemia, myocardial perfusion, Myocardial adenine nucleotide metabolism  (64)       Pre-Clinical Animal Model Development  (23)    Chronic Thromboembolic Pulmonary Hypertension (CTEPH) and Pulmonary Arterial Hypertension (PAH)  (20)    Cost of Inpatient Stay for Cardiovascular Diagnosis for Admission  (1)    Electrophysiology  (111)       Ablation Procedure vs Drug Therapy  (2)       Arrhythmia Detection with Machine Learning Algorithms  (7)       Cardiotoxic Risks of Immune Checkpoint Inhibitors  (1)       Genomic Analysis of EKG Electrophysiology Genomics  (3)       implantable cardioverter defibrillator (ICD) and External Defibrillation  (1)       implantable pacemaker  (2)       Rare heart rhythm disorders and Long QT syndrome (LQTS)  (7)    Epigenetics and Cardiovascular Risks  (57)    Heart Failure (HF)  (51)       Acute coronary syndrome  (7)       congestive heart failure  (19)       Hypertensive Disorders of Pregnancy  (1)    Medical Devices R&D and Inventions  (212)       Assist Devices: LV  (3)       RV  (1)       Stents & Tools  (90)       Valves & Tools  (67)    Origins of Cardiovascular Disease  (422)       Atherogenic Processes & Pathology  (180)       Congenital Heart Disease  (34)          Genetic Mutations in Congenital Heart Disease  (4)       inflammation independent of lipid levels  (13)       Systemic Inflammatory Diseases as CVD Risk  (12)    Pharmacotherapy of Cardiovascular Disease  (356)       HTN  (176)       HTN in Youth  (8)       Resident-cell-based  (43)       Subarachnoid Hemorrhage (SAH)  (1)       Transthyretin amyloid cardiomyopathy (ATTR-CM)  (1)    Spontaneous Coronary Artery Dissection (SCAD)  (6)    Stroke  (15)       endovascular thrombectomy  (6)    Vascular Diseases  (21)       mesenteric ischemia  (3) Future Pandemics Inform-graphics  (1) Gastroenterology  (38) Gene Regulation  (232) Gene Regulation and Evolution  (137) Genetics & Innovations in Treatment  (176) Genetics & Pharmaceutical  (204) Genome Biology  (967)    Exosomes  (25)    Gene Therapy & Gene Editing Development  (42)    mRNA Therapeutics  (20)    Mutagenesis  (27)    Single Cell Genomics  (25)    Single-cell sequencing  (20)    Variation in human protein-coding regions  (35) Genomic Endocrinology  (42) Genomic Testing: Methodology for Diagnosis  (416) Genomics Pharmacy  (40) Global Market of Medical Devices Technology  (3) Global Medical Publishers by Country  (3) Global Partnering & Biotech Investment  (48) GLP  (4) Glycobiology: Biopharmaceutical Production  (16) Glycobiology: Biopharmaceutical Production, Pharmacodynamics and Pharmacokinetics  (28) Health Care System by Country  (58)    AI Models in Healthcare  (12)    Centers for Medicare & Medicaid Services  (8)    Health in Israel  (2)    India  (1)    United States  (27)       Hospital-based Medical Innovations  (10)       Medical Recertification and Maintenance of Certification (MOC)  (1) Health Economics and Outcomes Research  (384)    Women Health  (18)       Heart and Brain Disease in Women  (3) Health Law & Patient Safety  (165)    and Bioethics  (14)    Biotechnology  (12)    Health Law Policy  (13) HealthCare IT  (139) Healthcare Reform  (117)    Accountable Care Organizations  (26)    Affordable Care Act  (29)       Repair  (1)       Repeal ACA  (1)       Replace  (1)    Federal Budget Appropriations  (26)    Healthcare costs and reimbursement  (59)    Indigent Nutrition  (14)    Medicare and Medicaid  (20)    Prescription Drugs Costs  (21)    Skilled Nursing Facilities  (6)    Technology Capital Expenses  (15)    Uninsured and Underinsured  (20) Hematology  (100)    Acute lymphocytic leukemia  (18)    Acute myelocytic leukemia  (21)    Hematopoiesis  (48)    Lymphoma  (21) History and physical exam  (6) Human aging  (27) Human Immune System in Health and in Disease  (246) Human Sensation and Cellular Transduction: Physiology and Therapeutics  (21) Image Processing/Computing  (41) Imaging-based Cancer Patient Management  (116) Immuno-Oncology & Genomics  (133)    mRNA platform in Drug DIscovery  (6) Immunodiagnostics  (140)    Cancer-Immune Interactions  (30)    CNS-Immune Interface  (5)    Neuronal Circuits  (4) Immunology  (123)    Adaptive Immune Response to Biomaterials and Tissue Repair  (13)    Antibody Responses Predict Antigen Exposure  (17)    Cytokine Receptor Structure  (8)    Human Antibody Response  (18)    Human Circulating Antibody Repertoire  (11)    Human Naive B Cell Repertoire  (8)    MHC Repertoires for Antigen Prediction  (8)    Protection Against Autoimmune Disease  (11)    Synthetic Immunology: Hacking Immune Cells  (15) Immunotherapy  (135)    CAR-T  (15)    combination immunotherapies.  (15)    Efficacy of Anti-Tumor T Cells  (15)    Engineering Better T Cells  (9)    Immune Engineering  (17)    Immune Modulatory  (16)    Integrin-targeted Combination Immunotherapy  (6)    Modulating Macrophages in Cancer Immunotherapy  (17)    NK Cell-Based Cancer Immunotherapy  (20)    Synergistic Innate and Adaptive Immunotherapy  (14) Income Disparity  (2) Infectious Disease & New Antibiotic Targets  (162)    Antibiotic resistance  (7)    Viral diseases  (37)       Myocarditis  (1) Infectious Disease Immunodiagnostics  (58)    Virology – Vector-borne DIsease  (17) Inflammasome  (29)    Anti-tumor necrosis factor drugs (TNF inhibitors)  (3) Innovation in Immunology Diagnostics  (111)    Universal Immune Cell Therapies (uICT)  (11) Innovations  (186)    R&D Expenditure  (8) Innovations in Neurophysiology & Neuropsychology  (145)    Age and Life Expectancy  (3)    autism spectrum disorder  (1)    Circadian Rhythm and Sleep  (6)    hNPCs  (1)    Nervous System Function  (2)    Relapsing Multiple Sclerosis  (1) Intellectual Property  (84)    Disputes and Settlements  (9)    IP Valuation Models – Pricing Intangible Assets  (7)    Patent Law in Biotech  (12) Intellectual Property, Innovations, Commercialization, Investment in technological breakthrough  (120) International Global Work in Pharmaceutical  (190) Interventional Oncology: Radiofrequency Ablation, Transarterial Chemoembolization, Microwave Ablation and Irreversible Electroporation (IRE)  (12) Interviews with Scientific Leaders  (316)    Albany Medical Center Prize in Medicine and Biomedical Research  (2)    Annual Breakthrough Prize  (4)    Annual Lewis S. Rosenstiel Award  (2)    Awards in Cardiology and Cardiovascular Medicine  (6)    CEOs of Biotech Companies  (3)    Gerald D Aurbach Award for Outstanding Translational Research  (2)    Interviews with Key Opinion Leaders (KOLs)  (10)    James Prize in Science and Technology Integration  (2)    Jessie Stevenson Kovalenko Medal – Medical Sciences  (2)    Lemelson-MIT Prize  (2)    Life Sciences Breakthrough Prize  (5)    Mosteller Statistician of the Year Award  (2)    Mourning the Loss of a Scientific Leader  (4)    National Academy of Sciences AWARDS  (4)    Nobel Prize Winners  (29)    Noble Prize (Not Nobel Prize)  (2)    Paul Marks Prize for Cancer Research  (2)    Russ Prize recognizes bioengineering achievements worldwide  (2)    The Dan David Prize  (6)    Warren Alpert Foundation Prize Recipients  (4)    Wolf Prize  (2)    Wolf Prize in Medicine  (2)    women in science  (5) Investment in Technological Breakthrough  (60) Ionic Transporters Na+  (25) IP Development by LPBI Group Team  (14) IP Development by LPBI Group Team & Other Organizations  (8) ISO 14155  (3) Joint Venture – SBH & M3DP: SOP and Arrangements  (1) Justice & Law  (1) K  (15) Lab-on-a-chip  (2) Landscape  (1) Lasers and photonics  (18)    Midrange IR spectroscopy  (1) Law and Medicine Conflicts  (14) Leadership, Power, Social Interlocking Connections  (13) Lipid metabolism  (109)    Fatty acids  (38)    Lipids  (38)    PCSK9 Inhibitor Therapy  (19) Lipidomics  (11) Liposome  (4) Liver & Digestive Diseases Research  (122) LPBI Group, e-Scientific Media, DFP, R&D-M3DP, R&D-Drug Discovery, US Patents: SOPs and Team Management  (143)    Award Nominations  (5)    BioMed e-Books e-Series by LPBI Group  (9)    Feedback from Investors: LPBI Portfolio of Five Businesses  (2)    LPBI Group Founder – Aviva Lev-Ari  (27)    PhD  (1)    RN  (1) LPBI Management  (23) Massachusetts Academy of Sciences (MAS)    (2) Materials Science & Engineering  (37)    Organic BioElectronics  (2) Math  (13)    Great Discoveries  (7) Mechanical Assist Devices: LVAD  (4) Medical and Population Genetics  (193) Medical Devices R&D Investment  (242)    21st Century Cures Act  (2)    CE Mark & Global Regulatory Affairs: process management and strategic planning – GCP  (14)    Rhythm management device hardware: dual-chamber pacemakers  (1)       Systolic HTN  (1) Medical Imaging Technology  (59) Medical Imaging Technology, Image Processing/Computing, MRI, CT, Nuclear Medicine, Ultra Sound  (164)    Circumferential-Intravascular-Radioluminescence-Photoacoustic-Imaging (CIRPI)  (3)    Echocardiography  (3)    MRI  (18)    Noninvasive Diagnostic Fractional Flow Reserve (FFR) CT  (6)    Ultra Sound  (10) Melatonin & Circadian Regulation  (9) memory loss  (1) Metabolism  (239)    Biochemical pathways  (144)       Enzymes and isoenzymes  (73)          Dehydrogenase  (16)          Kinase  (28)          Phosphatase  (9)          Phosphorylase  (22)          tyrosine decarboxylases  (3)    Inosine nucleotides  (9)    Leloir pathway  (6)    microbiome  (7)    Pentose monophosphate shunt  (14)    Pyridine nucleotides  (28)       Pyridine nucleotide transhydrogenase  (7) Metabolomics  (321) Methods  (37) Mg++  (10) Microbiologial genetics  (36) Microbiology  (68)    Virology  (14) Micronutrients  (16) Microvesicle  (7) Microwave Ablation and Irreversible Electroporation (IRE)  (1) Mobile Healthcare  (5) Molecular Genetics & Pharmaceutical  (377)    Organoids  (3) Monoclonal antibody therapy  (14) Mutant Gene Expression  (42) Myocardial adenine nucleotide metabolism  (6) Myocardial Ischemia  (26) Myocardial Metabolism  (36) Na-K transport  (40) Na-K-ATPase  (27) Nanotechnology for Drug Delivery  (99) Nephrology  (46) Nephrology & Regenerative medicine  (9) Neurodegenerative Diseases  (89)    hNPCs  (3)    MS  (5) Neurohumoral Transmission  (68)    Ca2+ triggered activation  (21)    Calmodulin  (13)    Parkinson’s disease dyskinesia levodopa  (3)    PKC  (13)    Synaptic vesicle  (20) Neurological Diseases  (121) Neuroscience  (126) Next Generation Sequencing (NGS)  (27)    Nanopore sequencing  (1) NIH Common Fund  (1) Nitric Oxide in Health and Disease  (136) Nuclear Medicine  (11) Nutrigenomics  (68) Nutrition  (195)    Nutritional Supplements: Atherogenesis, lipid metabolism  (50) Nutrition and Phytochemistry  (62)    Minerals in Medicine  (4)    Plant extract  (22) Nutrition Disorders  (31) Nutritional Supplements: Atherogenesis  (31) Obesity  (19) Oligonucleotide Therapeutics & Delivery  (7) Oncolytic virus & OncoViro-Therapy  (22)    Synthetic Virology  (1) Organ-on-a-Chip & 3D Printing in Life Sciences  (7) Pain: Etiology, Genetics & Innovations in Treatment  (24) Parasitology  (5)    Malaria  (4)    Tropical diseases  (1) Patents  (34) Patient Experience  (66)    Art therapy  (1)    Hospital reputation  (7)    Humor  (1)    Music therapy  (2)    Pain Alleviation  (7)    Patient Outlook  (28)    Reputation of Interventionist  (4)    Support Staff  (13)    Supportive therapies  (6)       laughfter  (1)    Surgical Procedure  (9) Patient Experience: Personal Memories of Invasive Medical Intervantion  (30) Patient’s Voice: Personal Experience with Invasive Medical Procedures  (18) Perioperative Statins at Noncardiac Surgery  (2) Personal Health Applications: Tech Innovations serves HealhCare  (43) Personalized and Precision Medicine & Genomic Research  (737)    Longevity  (3)    New Drug Approval  (5)    Patient-centered Medicine  (39)       cell-based therapy  (9)       stem cell biology and patient-specific  (7)    Personalized Medicine Coalition  (10)    Precision Cancer Medicine  (32) Phagophore  (2) Pharmaceutical Analytics  (261)    Pharmacologic toxicities  (62) Pharmaceutical Discovery  (110)    Rapid automation of plasma protein pools  (18) Pharmaceutical Drug Discovery  (202)    Drug Development Process  (57)       Drug Discovery Chemistry  (31)    drug repurposing  (11) Pharmaceutical Industry Competitive Intelligence  (344)    Pharmacovigilance  (7)    Value-based Drug Pricing  (8) Pharmaceutical R&D Informatics  (44) Pharmaceutical R&D Investment  (300) Pharmacodynamics and Pharmacokinetics  (24) Pharmacogenomics  (160) Photography Collection  (1) Physics  (12) Placenta  (7) Population genetics  (27) Population Health Management  (204)    Evolution of Biology Through Culture  (14)    U.S. Employment-to-Population Ratio  (8) Population Health Management, Genetics & Pharmaceutical  (643)    COVID-19  (157)       Biomarkers: Inflammation  (37)       Cancer Researchers Fighting COVID-19  (14)       COVID-19 effects on Human Heart  (15)       COVID-19: Pandemic Surgery Guidance  (19)       Economic Impact of Coronavirus Pandemic  (41)       number of asymptomatic infections  (27)       Treatment Protocols for COVID-19  (62)    SARS-CoV-2  (141)       Coronavirus Gene Expression  (66)          SARS-CoV-2 circulating variants   (14)          SARS-CoV-2 Viral Variants  (19)       Glycosylation and its Role in SARS-CoV-2 Viral Pathogenesis  (2)       Immune-Mediation (independent immunopathology: lung and reticuloendothelial system)  (30)       Mechanisms of infection by SARS-CoV-2  (21)       SAR-Cov-2 a vasculotropic (blood vessels) RNA Virus  (35)          SARS-COV2 Hijacking the Complement and Coagulation Systems  (19)       Seasonality & Environmental Factors in Resurgence  (26)       Serology tests for coronavirus antibodies  (44)       T-cell response to SARS-CoV-2 infection  (14)       Vaccinology  (51)          Mechanism of Thrombosis with AZ & J&J COVID-19 Vaccines  (5)       Virtual Drug Molecule Screening targeting SAR-CoV-2 proteins  (8)    Virus Infective Acute Respiratory Syndrome: SARS-CoV  (92) Population Health Management, Nutrition and Phytochemistry  (162) Preimplantation Genetic Diagnosis and Reproductive Genomics  (13) Protein-energy malnutrition  (12) Proteomics  (367)    Amino acids  (54)    Proteins  (138) Pulmonary diseases  (16)    Lung and pulmonology  (15) Pulmonary pathology  (8) Radio Frequency (RF)-based Surgical Solutions  (2) REAL TIME Conference Coverage Twitter’s Hashtags and Handles per Presentation/session  (50) Regenerative Biology and Medicine  (92) Regulated Clinical Trials: Design, Methods, Components and IRB related issues  (265) Reproductive Andrology, Embryology, Genomic Endocrinology, Preimplantation Genetic Diagnosis and Reproductive Genomics  (113) Reproductive Biology & Bio Instrumentation  (78) RNA Biology  (81)    RNA interference (RNAi) therapeutic  (4) RNA Biology, Cancer and Therapeutics  (64) RVAD  (1) SBIR, SBA, NIH, NSF  (3) Schizophrenia  (16) Scientific & Biotech Conferences: Press Coverage  (182) Scientific Publishing  (609)    Curation  (585)       Curation methodology  (40)       De novo synthesis  (16)       Dialectic  (17)       Discovery process  (72)       Evolutionary cognition  (52)       Experimental validation  (91)       Explanatory  (91)       Historical relevance  (71)       Technology Advance Assessment of  (69)       Theoretic convergence  (27)    Open Access Journals  (37) Scientist: Career considerations  (197)    Big Data & Analytics  (17)    Data Science  (13)    Women in Life Sciences  (12) Scoop.it  (19) Sensors & Analytics  (18) Sepsis  (2) Severe Autism  (3) Signaling  (102)    Phosphorylation  (43)    S-nitrosylation  (13)    Ubiquitinylation  (34) Signaling & Cell Circuits  (130) single cell sequencing  (3) Small Molecules in Development of Therapeutic Drugs  (71) Social Development  (15) Specialized 3D BioPrinters (Cornea  (1) Statistical Methods for Research Evaluation  (137) Stem Cells for Regenerative Medicine  (177)    Cardiac muscle regeneration  (19)    Competition in regenerative stem cell science  (18)    Human neural progenitor cells  (8)    Skeletal muscle regeneration  (9) STORM  (2) Stress Disorders  (19) Substance Abuse  (4) Systemic Inflammatory Response Related Disorders  (161)    Inflammatory Pathophysiology  (9) Technology Transfer: Biotech and Pharmaceutical  (354) therapeutics  (3) Tissue Engineering and Regenerative Medicine  (22) Tissue Microenvironment  (5) Transarterial Chemoembolization  (2) Transcriptomics  (47) Transformative Technologies in Healthcare  (23) Translational Science  (230)    Best evidence  (52)    Bias measurement tools  (2)    Evidence-based decision-making  (29)    Inferential analysis  (25)    Intra-rater error  (1)    Quality Assurance  (8)    Random Error  (2)    Systematic Error (Bias)  (6)    Total error  (2)    Translational Effectiveness  (49)    Translational Research  (92) Trends in Global Economy  (6) Uncategorized  (1,019) Unfolded Protein Response (UPR)  (6) US and Global Economy: Trends and Findings  (9) Venture Capital  (47)    Income Geographic Distribution  (3)    Institutional Capital Raised by Female Founders  (6) virology  (10) Vision  (7) Voices of Patients and Healthcare Providers  (22) Water Transporters  (8) Wearable Tech + Digital Health  (5) Anemia  (22) Neutropenia  (8) Neutrophilia  (9) Platelet count disorder  (9) Folate and B12  (7) Iron deficiency  (5) Myelodysplasia  (13) Myelofibrosis  (10)

• Meta

  • Log in
  • Entries feed
  • Comments feed
  • WordPress.org

• • 2012pharmaceutical
  • sjwilliamspa