Archive for the ‘CANCER BIOLOGY & Innovations in Cancer Therapy’ Category

Alliance for Cancer Gene Therapy to honor Dr. Crystal Mackall with Edward Netter Leadership Award

Posted in Biological Engineering, Biological Networks, Gene Regulation and Evolution, Cancer - General, Cancer and Current Therapeutics, Cell Level, Childhood cancer, Drug Delivery Platform Technology, Gene Therapy & Gene Editing Development, Genetics & Innovations in Treatment, Interviews with Key Opinion Leaders (KOLs), Interviews with Scientific Leaders, Life Sciences Breakthrough Prize, Metabolic Immuno-Oncology, Metastasis Process, Oligonucleotide Therapeutics & Delivery, tagged Alliance for Cancer Gene Therapy, Cancer immunotherapy, CART therapy, Edward Netter Leadership Award, gene therapy, modulation of cell and gene therapies, Stanford, University of Pennsylvania on April 8, 2023| Leave a Comment »

Alliance for Cancer Gene Therapy to honor Dr. Crystal Mackall with Edward Netter Leadership Award

Reporter: Stephen J. Williams, PhD

Past recipient and cancer research pioneer Carl June, MD, to present award to Dr. Mackall

Alliance for Cancer Gene Therapy (ACGT) will award the Edward Netter Leadership Award to Crystal Mackall, MD, of Stanford University, at the ACGT Awards Luncheon on March 30 at Riverpark restaurant at the Alexandria Center for Life Science, located at 450 E. 29th St., New York City.

Named for ACGT co-founder, Edward Netter, the award recognizes a researcher who has made unparalleled and groundbreaking contributions to the field of cell and gene therapy for cancer. Dr. Mackall is a leader in advancing cell and gene therapies for the treatment of solid tumors, with a major focus on children’s cancers.

In addition to being an ACGT research fellow and a member of ACGT’s Scientific Advisory Council, Dr. Mackall is the Ernest and Amelia Gallo Family professor of Pediatrics and Medicine at Stanford University, the founding director of the Stanford Center for Cancer Cell Therapy, associate director of the Stanford Cancer Institute, leader of the Cancer Immunotherapy Program and director of the Parker Institute for Cancer Immunotherapy. She has led numerous groundbreaking clinical trials to treat children with sarcomas and brain cancers.

“There is exciting progress happening in the field of cancer cell and gene therapy,” said Kevin Honeycutt, CEO and president of ACGT. “We continue to see the FDA approve cell and gene therapy treatments for blood cancers, while research for solid tumors is now progressing to clinical trials. These successes are linked to the funding of ACGT, and Dr. Crystal Mackall is one of the best examples of a researcher who refused to accept the status-quo of standard cancer treatment and committed to developing novel cell and gene therapies for children with difficult-to-treat tumors. ACGT is proud that Dr. Mackall is an ACGT Research Fellow, a member of ACGT’s Scientific Advisory Council, and the newest recipient of the Edward Netter Leadership Award.”

The ACGT Awards Luncheon will celebrate the non-profit organization’s 20th anniversary and usher in a new decade as the only nonprofit dedicated exclusively to funding cancer cell and gene therapy research. ACGT funds innovative scientists and biotechnology companies working to harness the power of cell and gene therapy to transform how cancer is treated and to drive momentum toward a cure.

The Edward Netter Leadership Award will be presented to Dr. Mackall by Carl June, MD, of the University of Pennsylvania, who received the honor at ACGT’s 2019 Awards Gala. ACGT grant funding enabled Dr. June to research and develop cell and gene therapies that led to the first FDA approvals of CAR T-cell therapies for cancer.

For information about purchasing a ticket to the ACGT Awards Luncheon, visit the ACGT Awards Luncheon website (https://acgtfoundation.org/awards/), call Keri Eisenberg at (475) 400-4373, or email keisenberg@acgtfoundation.org.

Alliance for Cancer Gene Therapy (ACGT)

For more than 20 years, Alliance for Cancer Gene Therapy has funded research that is bringing innovative treatment options to people living with deadly cancers – treatments that save lives and offer new hope to all cancer patients. Alliance for Cancer Gene Therapy funds researchers who are pioneering the potential of cancer cell and gene therapy – talented visionaries whose scientific advancements are driving the development of groundbreaking treatments for ovarian, prostate, sarcoma, glioblastoma, melanoma and pancreatic cancers. One hundred percent of all public funds raised by Alliance for Cancer Gene Therapy directly support research and programs. For more information, visit acgtfoundation.org, call (203) 358-5055, or join the Alliance for Cancer Gene Therapy community on Facebook, Twitter, LinkedIn, Instagram and YouTube @acgtfoundation.

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Mission 4: Use of Systems Biology for Design of inhibitor of Galectins as Cancer Therapeutic – Strategy and Software

Posted in Artificial Intelligence in CANCER, Artificial Intelligence in Medicine - Applications in Therapeutics, BioIT: BioInformatics, BioSimilars, BioTechnology - Venture Creation, Cancer - General, Cancer and Current Therapeutics, CANCER BIOLOGY & Innovations in Cancer Therapy, Cancer Genomics, Cancer Informatics, cancer metabolism, Cell Biology, Signaling & Cell Circuits, Computational Biology/Systems and Bioinformatics, Genetics & Pharmaceutical, Genome Biology, Genomic Expression, Glycobiology: Biopharmaceutical Production, Glycobiology: Biopharmaceutical Production, Pharmacodynamics and Pharmacokinetics, Innovations, LPBI Group, e-Scientific Media, DFP, R&D-M3DP, R&D-Drug Discovery, US Patents: SOPs and Team Management, MicroEngineering Cell-Tissue & Systems, Natural Language Processing (NLP), Phosphorylation, S-nitrosylation, Signaling, Signaling & Cell Circuits, Small Molecules in Development of Therapeutic Drugs, Ubiquitin, Ubiquitinylation, tagged angiogenesis, Cancer, carbohydrate, galectin-3, LPBI, metastasis, PROTAC, Synthetic biology, systems biology on December 13, 2022| Leave a Comment »

Use of Systems Biology for Design of inhibitor of Galectins as Cancer Therapeutic – Strategy and Software

Curator: Stephen J. Williams, Ph.D.

Below is a slide representation of the overall mission 4 to produce a PROTAC to inhibit Galectins 1, 3, and 9.

Using A Priori Knowledge of Galectin Receptor Interaction to Create a BioModel of Galectin 3 Binding

Now after collecting literature from PubMed on “galectin-3” AND “binding” to determine literature containing kinetic data we generate a WordCloud on the articles.

This following file contains the articles needed for BioModels generation.

https://pharmaceuticalintelligence.com/wp-content/uploads/2022/12/Curating-Galectin-articles-for-Biomodels.docx

From the WordCloud we can see that these corpus of articles describe galectin binding to the CRD (carbohydrate recognition domain). Interestingly there are many articles which describe van Der Waals interactions as well as electrostatic interactions. Certain carbohydrate modifictions like Lac NAc and Gal 1,4 may be important. Many articles describe the bonding as well as surface interactions. Many studies have been performed with galectin inhibitors like TDGs (thio-digalactosides) like TAZ TDG (3-deoxy-3-(4-[m-fluorophenyl]-1H-1,2,3-triazol-1-yl)-thio-digalactoside). This led to an interesting article

Dual thio-digalactoside-binding modes of human galectins as the structural basis for the design of potent and selective inhibitors

Tung-Ju Hsieh¹, Hsien-Ya Lin^1 2, Zhijay Tu¹, Ting-Chien Lin^1 2, Shang-Chuen Wu^1 3, Yu-Yao Tseng¹, Fu-Tong Liu⁴, Shang-Te Danny Hsu^1 3, Chun-Hung Lin^1 2 3 5

Affiliations 2016 Jul 15;6:29457.

doi: 10.1038/srep29457.

PMID: 27416897
PMCID: PMC4945863
DOI: 10.1038/srep29457

Free PMC article

Abstract

Human galectins are promising targets for cancer immunotherapeutic and fibrotic disease-related drugs. We report herein the binding interactions of three thio-digalactosides (TDGs) including TDG itself, TD139 (3,3′-deoxy-3,3′-bis-(4-[m-fluorophenyl]-1H-1,2,3-triazol-1-yl)-thio-digalactoside, recently approved for the treatment of idiopathic pulmonary fibrosis), and TAZTDG (3-deoxy-3-(4-[m-fluorophenyl]-1H-1,2,3-triazol-1-yl)-thio-digalactoside) with human galectins-1, -3 and -7 as assessed by X-ray crystallography, isothermal titration calorimetry and NMR spectroscopy. Five binding subsites (A-E) make up the carbohydrate-recognition domains of these galectins. We identified novel interactions between an arginine within subsite E of the galectins and an arene group in the ligands. In addition to the interactions contributed by the galactosyl sugar residues bound at subsites C and D, the fluorophenyl group of TAZTDG preferentially bound to subsite B in galectin-3, whereas the same group favored binding at subsite E in galectins-1 and -7. The characterised dual binding modes demonstrate how binding potency, reported as decreased Kd values of the TDG inhibitors from μM to nM, is improved and also offer insights to development of selective inhibitors for individual galectins.

Figures

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The drug efflux pump MDR1 promotes intrinsic and acquired resistance to PROTACs in cancer cells

Posted in CANCER BIOLOGY & Innovations in Cancer Therapy, Cancer Genomics, Cell Biology, Drug Development Process, Drug Discovery Chemistry, Genomic Expression, Loss of function gene, Metabolomics, Pharmaceutical Drug Discovery, tagged AAAS, anti-cancer therapy, Cancer - General, Cancer research, cancer resistance, chemoresistance, PROTAC, Proteasome, Proteolysis on October 11, 2022| Leave a Comment »

The drug efflux pump MDR1 promotes intrinsic and acquired resistance to PROTACs in cancer cells

Reporter: Stephen J. Williams, PhD.

Below is one of the first reports on the potential mechanisms of intrinsic and acquired resistance to PROTAC therapy in cancer cells.

SOURCE

https://www.science.org/doi/10.1126/scisignal.abn2707

ALISON M. KURIMCHAK HTTPS://ORCID.ORG/0000-0003-2608-0128CARLOS HERRERA-MONTÁVEZSARA MONTSERRAT-SANGRÀDANIELA ARAIZA-OLIVERA HTTPS://ORCID.ORG/0000-0002-8207-9765JIANPING HU HTTPS://ORCID.ORG/0000-0002-6000-4922RYAN NEUMANN-DOMERMATHEW KURUVILLAALFONSO BELLACOSA HTTPS://ORCID.ORG/0000-0001-6278-6801JOSEPH R. TESTAJIAN JIN HTTPS://ORCID.ORG/0000-0002-2387-3862 AND JAMES S. DUNCAN

Proteolysis-targeting chimeras (PROTACs) are a promising new class of drugs that selectively degrade cellular proteins of interest. PROTACs that target oncogene products are avidly being explored for cancer therapies, and several are currently in clinical trials. Drug resistance is a substantial challenge in clinical oncology, and resistance to PROTACs has been reported in several cancer cell models. Here, using proteomic analysis, we found intrinsic and acquired resistance mechanisms to PROTACs in cancer cell lines mediated by greater abundance or production of the drug efflux pump MDR1. PROTAC-resistant cells were resensitized to PROTACs by genetic ablation of ABCB1 (which encodes MDR1) or by coadministration of MDR1 inhibitors. In MDR1-overexpressing colorectal cancer cells, degraders targeting either the kinases MEK1/2 or the oncogenic mutant GTPase KRAS^G12C synergized with the dual epidermal growth factor receptor (EGFR/ErbB)/MDR1 inhibitor lapatinib. Moreover, compared with single-agent therapies, combining MEK1/2 degraders with lapatinib improved growth inhibition of MDR1-overexpressing KRAS-mutant colorectal cancer xenografts in mice. Together, our findings suggest that concurrent blockade of MDR1 will likely be required with PROTACs to achieve durable protein degradation and therapeutic response in cancer.

INTRODUCTION

Proteolysis-targeting chimeras (PROTACs) have emerged as a revolutionary new class of drugs that use cancer cells’ own protein destruction machinery to selectively degrade essential tumor drivers (1). PROTACs are small molecules with two functional ends, wherein one end binds to the protein of interest, whereas the other binds to an E3 ubiquitin ligase (2, 3), bringing the ubiquitin ligase to the target protein, leading to its ubiquitination and subsequent degradation by the proteasome. PROTACs have enabled the development of drugs against previously “undruggable” targets and require neither catalytic activity nor high-affinity target binding to achieve target degradation (4). In addition, low doses of PROTACs can be highly effective at inducing degradation, which can reduce off-target toxicity associated with high dosing of traditional inhibitors (3). PROTACs have been developed for a variety of cancer targets, including oncogenic kinases (5), epigenetic proteins (6), and, recently, KRAS^G12C proteins (7). PROTACs targeting the androgen receptor or estrogen receptor are avidly being evaluated in clinical trials for prostate cancer (NCT03888612) or breast cancer (NCT04072952), respectively.

However, PROTACs may not escape the overwhelming challenge of drug resistance that befalls so many cancer therapies (8). Resistance to PROTACs in cultured cells has been shown to involve genomic alterations in their E3 ligase targets, such as decreased expression of Cereblon (CRBN), Von Hippel Lindau (VHL), or Cullin2 (CUL2) (9–11). Up-regulation of the drug efflux pump encoded by ABCB1—MDR1 (multidrug resistance 1), a member of the superfamily of adenosine 5′-triphosphate (ATP)–binding cassette (ABC) transporters—has been shown to convey drug resistance to many anticancer drugs, including chemotherapy agents, kinase inhibitors, and other targeted agents (12). Recently, PROTACs were shown to be substrates for MDR1 (10, 13), suggesting that drug efflux represents a potential limitation for degrader therapies. Here, using degraders (PROTACs) against bromodomain and extraterminal (BET) bromodomain (BBD) proteins and cyclin-dependent kinase 9 (CDK9) as a proof of concept, we applied proteomics to define acquired resistance mechanisms to PROTAC therapies in cancer cells after chronic exposure. Our study reveals a role for the drug efflux pump MDR1 in both acquired and intrinsic resistance to protein degraders in cancer cells and supports combination therapies involving PROTACs and MDR1 inhibitors to achieve durable protein degradation and therapeutic responses.

Fig. 1. Proteomic characterization of degrader-resistant cancer cell lines.
(A) Workflow for identifying protein targets up-regulated in degrader-resistant cancer cells. Single-run proteome analysis was performed, and changes in protein levels among parent and resistant cells were determined by LFQ. m/z, mass/charge ratio. (B and C) Cell viability assessed by CellTiter-Glo in parental and dBET6- or Thal SNS 032–resistant A1847 cells treated with increasing doses of dBET6 (B) or Thal SNS 032 (C) for 5 days. Data were analyzed as % of DMSO control, presented as means ± SD of three independent assays. Growth inhibitory 50% (GI50) values were determined using Prism software. (D to G) Immunoblotting for degrader targets and downstream signaling in parental A1847 cells and their derivative dBET6-R or Thal-R cells treated with increasing doses of dBET6 or Thal SNS 032 for 4 hours. The dBET6-R and Thal-R cells were continuously cultured in 500 nM PROTAC. Blots are representative, and densitometric analyses are means ± SD from three blots, each normalized to the loading control, GAPDH. DC50 values, quantitating either (E) the dose of dBET6 that reduces BRD2, BRD3, or BRD4 or (G) the dose of Thal SNS 032 that reduces CDK9 protein levels 50% of the DMSO control treatment, were determined with Prism software. Pol II, polymerase II. (H to K) Volcano plot of proteins with increased or reduced abundance in dBET6-R (H) or Thal-R (I) A1847 cells relative to parental cells. Differences in protein log2 LFQ intensities among degrader-resistant and parental cells were determined by paired t test permutation-based adjusted P values at FDR of <0.05 using Perseus software. The top 10 up-regulated proteins in each are shown in (J) and (K), respectively. FC, fold change. (L and M) ABCB1 log2 LFQ values in dBET6-R cells from (H) and Thal-R cells from (I) compared with those in parental A1847 cells. Data are presented as means ± SD from three independent assays. By paired t test permutation-based adjusted P values at FDR of <0.05 using Perseus software, ***P ≤ 0.001. (N) Cell viability assessed by CellTiter-Glo in parental and MZ1-resistant SUM159 cells treated with increasing doses of MZ1 for 5 days. Data were analyzed as % of DMSO control, presented as means of three independent assays. GI50 values were determined using Prism software. (O and P) Immunoblotting for degrader targets and downstream signaling in parental or MZ1-R SUM159 cells treated with increasing doses of MZ1 for 24 hours. The MZ1-R cells were continuously cultured in 500 nM MZ1. Blots are representative, and densitometric analyses are means ± SD from three blots, each normalized to the loading control, GAPDH. DC50 values were determined in Prism software. (Q and R) Top 10 up-regulated proteins (Q) and ABCB1 log2 LFQ values (R) in MZ1-R cells relative to parental SUM159 cells

Fig. 2. Chronic exposure to degraders induces MDR1 expression and drug efflux activity.
(A) ABCB1 mRNA levels in parental and degrader-resistant cell lines as determined by qRT-PCR. Data are means ± SD of three independent experiments. ***P ≤ 0.001 by Student’s t test. (B) Immunoblot analysis of MDR1 protein levels in parental and degrader-resistant cell lines. Blots are representative of three independent experiments. (C to E) Immunofluorescence (“IF”) microscopy of MDR1 protein levels in A1847 dBET6-R (C), SUM159 MZ1-R (D), and Thal-R A1847 cells (E) relative to parental cells. Nuclear staining by DAPI. Images are representative of three independent experiments. Scale bars, 100 μm. (F) Drug efflux activity in A1847 dBET6-R, SUM159 MZ1-R, and Thal-R A1847 cells relative to parental cells (Par.) using rhodamine 123 efflux assays. Bars are means ± SD of three independent experiments. ***P ≤ 0.001 by Student’s t test. (G) Intracellular dBET6 levels in parental or dBET-R A1847 cells transfected with a CRBN sensor and treated with increasing concentrations of dBET6. Intracellular dBET6 levels measured using the CRBN NanoBRET target engagement assay. Data were analyzed as % of DMSO control, presented as means ± SD of three independent assays. *P ≤ 0.05, **P ≤ 0.01, and ***P ≤ 0.001 by Student’s t test. (H and I) FISH analysis of representative drug-sensitive parental and drug-resistant A1847 (H) and SUM159 (I) cells using ABCB1 and control XCE 7 centromere probes. Images of interphase nuclei were captured with a Metasystems Metafer microscope workstation, and the raw images were extracted and processed to depict ABCB1 signals in magenta, centromere 7 signals in cyan, and DAPI-stained nuclei in blue. (J and K) CpG methylation status of the ABCB1 downstream promoter (coordinates: chr7.87,600,166-87,601,336) by bisulfite amplicon sequencing in parent and degrader-resistant A1847 (J) and SUM159 (K) cells. Images depict the averaged percentage of methylation for each region of the promoter, where methylation status is depicted by color as follows: red, methylated; blue, unmethylated. Schematic of the ABCB1 gene with the location of individual CpG sites is shown. Graphs are representative of three independent experiments. (L and M) Immunoblot analysis of MDR1 protein levels after short-term exposure [for hours (h) or days (d) as indicated] to BET protein degraders dBET6 or MZ1 (100 nM) in A1847 (L) and SUM159 (M) cells, respectively. Blots are representative of three independent experiments. (N to P) Immunoblot analysis of MDR1 protein levels in A1847 and SUM159 cells after long-term exposure (7 to 30 days) to BET protein degraders dBET6 (N), Thal SNS 032 (O), or MZ1 (P), each at 500 nM. Blots are representative of three independent experiments. (Q and R) Immunoblot analysis of MDR1 protein levels in degrader-resistant A1847 (Q) and SUM159 (R) cells after PROTAC removal for 2 or 7 days. Blots are representative of three independent experiments.

Fig. 3. Blockade of MDR1 activity resensitizes degrader-resistant cells to PROTACs.
(A and B) Cell viability by CellTiter-Glo assay in parental and degrader-resistant A1847 (A) and SUM159 (B) cells transfected with control siRNA or siRNAs targeting ABCB1 and cultured for 120 hours. Data were analyzed as % of control, presented as means ± SD of three independent assays. ***P ≤ 0.001 by Student’s t test. (C and D) Immunoblot analysis of degrader targets after ABCB1 knockdown in parental and degrader-resistant A1847 (C) and SUM159 (D) cells. Blots are representative, and densitometric analyses using ImageJ are means ± SD of three blots, each normalized to the loading control, GAPDH. (E) Drug efflux activity, using the rhodamine 123 efflux assay, in degrader-resistant cells after MDR1 inhibition by tariquidar (0.1 μM). Data are means ± SD of three independent experiments. ***P ≤ 0.001 by Student’s t test. (F to H) Cell viability by CellTiter-Glo assay in parental and dBET6-R (F) or Thal-R (G) A1847 cells or MZ1-R SUM159 cells (H) treated with increasing concentrations of tariquidar. Data are % of DMSO control, presented as means ± SD of three independent assays. GI50 value determined with Prism software. (I to K) Immunoblot analysis of degrader targets after MDR1 inhibition (tariquidar, 0.1 μM for 24 hours) in parental and degrader-resistant A1847 cells (I and J) and SUM159 cells (K). Blots are representative, and densitometric analyses are means ± SD from three blots, each normalized to the loading control, GAPDH. (L and M) A 14-day colony formation assessed by crystal violet staining of (L) A1847 cells or (M) SUM159 cells treated with degrader (0.1 μM; dBET6 or MZ1, respectively) and MDR1 inhibitor tariquidar (0.1 μM). Images are representative of three biological replicates. (N) Immunoblotting for MDR1 in SUM159 cells stably expressing FLAG-MDR1 after selection with hygromycin. (O) Long-term 14-day colony formation assay of SUM159 cells expressing FLAG-MDR1 that were treated with DMSO, MZ1 (0.1 μM), or MZ1 and tariquidar (0.1 μM) for 14 days, assessed by crystal violet staining. Representative images of three biological replicates are shown. (P and Q) RT-PCR (P) and immunoblot (Q) analysis of ABCB1 mRNA and MDR1 protein levels, respectively, in parental or MZ1-R HCT116, OVCAR3, and MOLT4 cells.

Fig. 4. Overexpression of MDR1 conveys intrinsic resistance to degrader therapies in cancer cells.
(A) Frequency of ABCB1 mRNA overexpression in a panel of cancer cell lines, obtained from cBioPortal for Cancer Genomics using Z-score values of >1.2 for ABCB1 mRNA levels (30). (B) Immunoblot for MDR1 protein levels in a panel of 10 cancer cell lines. Blots are representative of three independent experiments. (C) Cell viability by CellTiter-Glo assay in cancer cell lines expressing high or low MDR1 protein levels and treated with Thal SNS 032 for 5 days. Data were analyzed as % of DMSO control, presented as means ± SD of three independent assays. GI50 values were determined with Prism software. (D to F) Immunoblot analysis of CDK9 in MDR1-low (D) or MDR1-high (E) cell lines after Thal SNS 032 treatment for 4 hours. Blots are representative, and densitometric analyses using ImageJ are means ± SD from three blots, each normalized to the loading control, GAPDH. DC50 value determined with Prism. (G and H) Immunoblotting of control and MDR1-knockdown DLD-1 cells treated for 4 hours with increasing concentrations of Thal SNS 032 [indicated in (H)]. Blots are representative, and densitometric analysis data are means ± SD from three blots, each normalized to the loading control, GAPDH. DC50 value determined with Prism. (I) Drug efflux activity using rhodamine 123 efflux assays in DLD-1 cells treated with DMSO or 0.1 μM tariquidar. Data are means ± SD of three independent experiments. ***P ≤ 0.001 by Student’s t test. (J) Intracellular Thal SNS 032 levels, using the CRBN NanoBRET target engagement assay, in MDR1-overexpressing DLD-1 cells treated with DMSO or 0.1 μM tariquidar and increasing doses of Thal SNS 032. Data are % of DMSO control, presented as means ± SD of three independent assays. **P ≤ 0.01 and ***P ≤ 0.001 by Student’s t test. (K to N) Immunoblotting in DLD-1 cells treated with increasing doses of Thal SNS 032 (K and L) or dBET6 (M and N) alone or with tariquidar (0.1 μM) for 4 hours. Blots are representative, and densitometric analyses are means ± SD from three blots, each normalized to the loading control, GAPDH. DC50 value of Thal SNS 032 for CDK9 reduction (L) or of dBET6 for BRD4 reduction (N) determined with Prism. (O to T) Bliss synergy scores based on cell viability by CellTiter-Glo assay, colony formation, and immunoblotting in DLD-1 cells treated with the indicated doses of Thal SNS 032 (O to Q) or dBET6 (R to T) alone or with tariquidar. Cells were treated for 14 days for colony formation assays and 24 hours for immunoblotting.

Fig. 5. Repurposing dual kinase/MDR1 inhibitors to overcome degrader resistance in cancer cells.
(A and B) Drug efflux activity by rhodamine 123 efflux assays in degrader-resistant [dBET-R (A) or Thal-R (B)] A1847 cells after treatment with tariquidar, RAD001, or lapatinib (each 2 μM). Data are means ± SD of three independent experiments. *P ≤ 0.05 by Student’s t test. (C and D) CellTiter-Glo assay for the cell viability of parental, dBET6-R, or Thal-R A1847 cells treated with increasing concentrations of RAD001 (C) or lapatinib (D). Data were analyzed as % of DMSO control, presented as means ± SD of three independent assays. GI50 values were determined with Prism software. (E to I) Immunoblot analysis of degrader targets in parental (E), dBET6-R (F and G), and Thal-R (H and I) A1847 cells treated with increasing concentrations of RAD001 or lapatinib for 4 hours. Blots are representative, and densitometric analyses are means ± SD from three blots, each normalized to the loading control, GAPDH. DC50 value of dBET6 for BRD4 reduction (G) or of Thal SNS 032 for CDK9 reduction (I) determined with Prism. (J) Immunoblotting for cleaved PARP in dBET6-R or Thal-R A1847 cells treated with RAD001, lapatinib, or tariquidar (each 2 μM) for 24 hours. Blots are representative of three independent blots. (K to N) Immunoblotting for BRD4 in DLD-1 cells treated with increasing doses of dBET6 alone or in combination with either RAD001 or lapatinib [each 2 μM (K and L)] or KU-0063794 or afatinib [each 2 μM (M and N)] for 4 hours. Blots are representative of three independent experiments and, in (L), are means ± SD from three blots, each normalized to the loading control, GAPDH. DC50 value for BRD4 reduction (L) determined in Prism. (O) Colony formation by DLD-1 cells treated with DMSO, dBET6 (0.1 μM), lapatinib (2 μM), afatinib (2 μM), RAD001 (2 μM), KU-0063794 (2 μM), or the combination of inhibitor and dBET6 for 14 days. Images representative of three independent assays. (P and Q) Immunoblotting for CDK9 in DLD-1 cells treated with increasing doses of Thal SNS 032 and/or RAD001 (2 μM) or lapatinib (2 μM) for 4 hours. Blots are representative, and densitometric analyses are means ± SD from three blots, each normalized to the loading control, GAPDH. DC50 value for CDK9 reduction determined with Prism (Q). (R) Colony formation in DLD-1 cells treated with DMSO, Thal SNS 032 (0.5 μM), lapatinib (2 μM), and/or RAD001 (2 μM) as indicated for 14 days.

Fig. 6. Combining MEK1/2 degraders with lapatinib synergistically kills MDR1-overexpressing KRAS-mutant CRC cells and tumors.
(A and B) ABCB1 expression in KRAS-mutant CRC cell lines from cBioPortal (30) (A) and MDR1 abundance in select KRAS-mutant CRC cell lines (B). (C) Cell viability assessed by CellTiter-Glo in CRC cells treated with increasing doses of MS432 for 5 days, analyzed as % of DMSO control. GI50 value determined with Prism software. (D) Colony formation by CRC cells 14 days after treatment with 1 μM MS432. (E) MEK1/2 protein levels assessed by immunoblot in CRC lines SKCO1 (low MDR1) or LS513 (high MDR1) treated with increasing doses of MS432 for 4 hours. (F) Rhodamine 123 efflux in LS513 cells treated with DMSO, 2 μM tariquidar, or 2 μM lapatinib. (G and H) Immunoblotting analysis in LS513 cells treated with increasing doses of MS432 alone or in combination with tariquidar (0.1 μM) or lapatinib (5 μM) for 24 hours. DC50 value for MEK1 levels determined with Prism. (I) Immunoblotting in LS513 cells treated with DMSO, PD0325901 (0.01 μM), lapatinib (5 μM), or the combination for 48 hours. (J and K) Immunoblotting in LS513 cells treated either with DMSO, MS432 (1 μM), tariquidar (0.1 μM) (J), or lapatinib (5 μM) (K), alone or in combination. (L) Bliss synergy scores determined from cell viability assays (CellTiter-Glo) in LS513 cells treated with increasing concentrations of MS432, lapatinib, or the combination. (M and N) Colony formation by LS513 cells (M) and others (N) treated with DMSO, lapatinib (2 μM), MS432 (1 μM), or the combination for 14 days. (O and P) Immunoblotting in LS513 cells treated with increasing doses of MS934 alone (O) or combined with lapatinib (5 μM) (P) for 24 hours. (Q and R) Tumor volume of LS513 xenografts (Q) and the body weights of the tumor-bearing nude mice (R) treated with vehicle, MS934 (50 mg/kg), lapatinib (100 mg/kg), or the combination. n = 5 mice per treatment group. In (A) to (R), blots and images are representative of three independent experiments, and quantified data are means ± SD [SEM in (Q) and (R)] of three independent experiments; ***P ≤ 0.001 by Student’s t test.

Fig. 7. Lapatinib treatment improves KRASG12C degrader therapies in MDR1-overexpressing CRC cell lines.
(A and B) Colony formation by SW1463 (A) or SW837 (B) cells treated with DMSO, LC-2 (1 μM), or MRTX849 (1 μM) for 14 days. Images representative of three independent assays. (C to E) Immunoblotting in SW1463 cells (C and D) and SW837 cells (E) treated with DMSO, LC-2 (1 μM), tariquidar (0.1 μM) (C), or lapatinib (5 μM) (D and E) alone or in combination for 48 hours. Blots are representative of three independent experiments. (F and G) Bliss synergy scores based on CellTiter-Glo assay for the cell viability of SW1463 (F) or SW837 (G) cells treated with increasing concentrations of LC-2, lapatinib, or the combination. Data are means of three experiments ± SD. (H and I) Colony formation of SW1463 (H) or SW837 (I) cells treated as indicated (−, DMSO; LC-2, 1 μM; lapatinib, 2 μM; tariquidar, 0.1 μM) for 14 days. Images representative of three independent assays. (J) Rationale for combining lapatinib with MEK1/2 or KRASG12C degraders in MDR1-overexpressing CRC cell lines. Simultaneous blockade of MDR1 and ErbB receptor signaling overcomes degrader resistance and ErbB receptor kinome reprogramming, resulting in sustained inhibition of KRAS effector signaling.

SOURCE

https://www.science.org/doi/10.1126/scisignal.abn2707

Accelerating PROTAC drug discovery: Establishing a relationship between ubiquitination and target protein degradation

The Vibrant Philly Biotech Scene: Proteovant Therapeutics Using Artificial Intelligence and Machine Learning to Develop PROTACs

The Map of human proteins drawn by artificial intelligence and PROTAC (proteolysis targeting chimeras) Technology for Drug Discovery

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Cancer Policy Related News from Washington DC and New NCI Appointments

Posted in Bio-Ethics, Cancer - General, Funding Opportunities for Cancer Research, Interviews with Scientific Leaders, Precision Cancer Medicine, SBIR, SBA, NIH, NSF, Translational Science, Women in Life Sciences, tagged cancer news, Joe Biden, NCI, NIH, Obama "Moonshot" program, US government on October 4, 2022| Leave a Comment »

Cancer Policy Related News from Washington DC and New NCI Appointments

Reportor: Stephen J. Williams, PhD.

Biden to announce appointees to Cancer Panel, part of initiative to cut death rate

The president first launched the initiative in 2016 as vice president.

By Mary Kekatos

July 13, 2022, 3:00 PM

1:50

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President Joe Biden will announce Wednesday his appointees to the President’s Cancer Panel, ABC News can exclusively reveal.

The Cancer Panel is part of Biden’s Cancer Moonshot Initiative, which was relaunched in February, with a goal of slashing the national cancer death rate by 50% over the next 25 years.MORE: Biden relaunches cancer ‘moonshot’ initiative to help cut death rate

Biden will appoint Dr. Elizabeth Jaffee, Dr. Mitchel Berger and Dr. Carol Brown to the panel, which will advise him and the White House on how to use resources of the federal government to advance cancer research and reduce the burden of cancer in the United States.

Jaffee, who will serve as chair of the panel, is an expert in cancer immunology and pancreatic cancer, according to the White House. She is currently the deputy director of the Sidney Kimmel Comprehensive Cancer Center at Johns Hopkins University and previously led the American Association for Cancer Research.

PHOTO: In this Sept. 8, 2016, file photo, Dr. Elizabeth M. Jaffee of the Pancreatic Dream Team attends Stand Up To Cancer (SU2C), a program of the Entertainment Industry Foundation (EIF), in Hollywood, Calif. — In this Sept. 8, 2016, file photo, Dr. Elizabeth M. Jaffee of the Pancreatic Dream Team attends Stand Up To Cancer (SU2C), a program of the Entertainment Industry Foundation (EIF), in Hollywood, Calif.ABC Handout via Getty Images, FILE

Berger, a neurological surgeon, directs the University of California, San Francisco Brain Tumor Center and previously spent 23 years at the school as a professor of neurological surgery.

Brown, a gynecologic oncologist, is the senior vice president and chief health equity officer at Memorial Sloan Kettering Cancer Center in New York City. According to the White House, much of her career has been focused on eliminating cancer care disparities due to racial, ethnic, cultural or socioeconomic factors.

Additionally, First Lady Jill Biden, members of the Cabinet and other administration officials are holding a meeting Wednesday of the Cancer Cabinet, made up of officials across several governmental departments and agencies, the White House said.

The Cabinet will introduce new members and discuss priorities in the battle against cancer including closing the screening gap, addressing potential environmental exposures, reducing the number of preventable cancer and expanding access to cancer research.MORE: Long Island school district found to have higher rates of cancer cases: Study

It is the second meeting of the cabinet since Biden relaunched the initiative in February, which he originally began in 2016 when he was vice president.

Both Jaffee and Berger were members of the Blue Ribbon Panel for the Cancer Moonshot Initiative led by Biden.

The initiative has personal meaning for Biden, whose son, Beau, died of glioblastoma — one of the most aggressive forms of brain cancer — in 2015.

“I committed to this fight when I was vice president,” Biden said at the time, during an event at the White House announcing the relaunch. “It’s one of the reasons why, quite frankly, I ran for president. Let there be no doubt, now that I am president, this is a presidential, White House priority. Period.”

The initiative has several priority actions including diagnosing cancer sooner; preventing cancer; addressing inequities; and supporting patients, caregivers and survivors.

PHOTO: In this June 14, 2016, file photo, Dr. Carol Brown, physician at Memorial Sloan Kettering Cancer Center, gives a presentation, at The White House Summit on The United State of Women, in Washington, D.C. — In this June 14, 2016, file photo, Dr. Carol Brown, physician at Memorial Sloan Kettering Cancer Center, gives a presentation, at The White House Summit on The United State of Women, in Washington, D.C.NurPhoto via Getty Images, FILE

The White House has also issued a call to action to get cancer screenings back to pre-pandemic levels.

More than 9.5 million cancer screenings that would have taken place in 2020 were missed due to the COVID-19 pandemic, according to the National Institutes of Health.MORE: Louisiana’s ‘Cancer Alley’ residents in clean air fight

“We have to get cancer screenings back on track and make sure they’re accessible to all Americans,” Biden said at the time.

Since the first meeting of the Cancer Cabinet, the Centers for Disease Control and Prevention has issued more than $200 million in grants to cancer prevention programs, the Centers for Medicaid & Medicare Services implemented a new model to reduce the cost of cancer care, and the U.S. Patent and Trademark Office said it will fast-track applications for cancer immunotherapies.

ABC News’ Sasha Pezenik contributed to this report.

Biden to tap prominent Harvard cancer surgeon to head National Cancer Institute

Monica Bertagnolli brings leadership experience in cancer clinical trials funded by the $7 billion research agency

21 JUL 2022
7:15 PM
BYJOCELYN KAISER

Monica BertagnolliASCO; GLENN DAVENPORT

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President Joe Biden is expected to pick cancer surgeon Monica Bertagnolli as the next director of the National Cancer Institute (NCI). Bertagnolli, a physician-scientist at Brigham and Women’s Hospital, the Dana-Farber Cancer Center, and Harvard Medical School, specializes in gastrointestinal cancers and is well known for her expertise in clinical trials. She will replace Ned Sharpless, who stepped down as NCI director in April after nearly 5 years.

The White House has not yet announced the selection, first reported by STAT, but several cancer research organizations closely watching for the nomination have issued statements supporting Bertagnolli’s expected selection. She is “a national leader” in clinical cancer research and “a great person to take the job,” Sharpless told ScienceInsider.

With a budget of $7 billion, NCI is the largest component of the National Institutes of Health (NIH) and the world’s largest funder of cancer research. Its director is the only NIH institute director selected by the president. Bertagnolli’s expected appointment, which does not require Senate confirmation, drew applause from the cancer research community

Margaret Foti, CEO of the American Association for Cancer Research, praised Bertagnolli’s “appreciation for … basic research” and “commitment to ensuring that such treatment innovations reach patients … across the United States.” Ellen Sigal, chair and founder of Friends of Cancer Research, says Bertagnolli “brings expertise the agency needs at a true inflection point for cancer research.”

Bertagnolli, 63, will be the first woman to lead NCI. Her lab research on tumor immunology and the role of a gene called APC in colorectal cancer led to a landmark trial she headed showing that an anti-inflammatory drug can help prevent this cancer. In 2007, she became the chief of surgery at the Dana-Farber Brigham Cancer Center.

She served as president of the American Society of Clinical Oncology in 2018 and currently chairs the Alliance for Clinical Trials in Oncology, which is funded by NCI’s National Clinical Trials Network. The network is a “complicated” program, and “Monica will have a lot of good ideas on how to make it work better,” Sharpless says.

One of Bertagnolli’s first tasks will be to shape NCI’s role in Biden’s reignited Cancer Moonshot, which aims to slash the U.S. cancer death rate in half within 25 years. NCI’s new leader also needs to sort out how the agency will mesh with a new NIH component that will fund high-risk, goal-driven research, the Advanced Research Projects Agency for Health (ARPA-H).

Bertagnolli will also head NCI efforts already underway to boost grant funding rates, diversify the cancer research workplace, and reduce higher death rates for Black people with cancer.

The White House recently nominated applied physicist Arati Prabhakar to fill another high-level science position, director of the White House Office of Science and Technology Policy (OSTP). But still vacant is the NIH director slot, which Francis Collins, acting science adviser to the president, left in December 2021. And the administration hasn’t yet selected the inaugural director of ARPA-H.

Correction, 22 July, 9 a.m.: This story has been updated to reflect that Francis Collins is acting science adviser to the president, not acting director of the White House Office of Science and Technology Policy.

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Accelerating PROTAC drug discovery: Establishing a relationship between ubiquitination and target protein degradation

Posted in Apoptosis, Bio Instrumentation in Experimental Life Sciences Research, Biological Networks, Biomedical Measurement Science, Cancer - General, Cancer and Current Therapeutics, CANCER BIOLOGY & Innovations in Cancer Therapy, Cell Biology, Signaling & Cell Circuits, Childhood cancer, Enzymatic mechanism underlying the synthesis of adenosine triphosphate (ATP), KRAS Mutation, Li-fraumeni syndrome., Proteosome, TP53 - Germline mutations, Ubiquitin, tagged breast cancer, Cancer - General, E3 Ligase, high throughput, MDM2, PROTAC, TUBEs, Ubiquitin ligase, ubiquitin-proteosome, VHL on October 4, 2022| Leave a Comment »

Accelerating PROTAC drug discovery: Establishing a relationship between ubiquitination and target protein degradation

Curator: Stephen J. Williams, Ph.D.

PROTACs have been explored in multiple disease fields with focus on only few ligases like cereblon (CRBN), Von Hippel-Lindau (VHL), IAP and MDM2. Cancer targets like androgen receptor, estrogen receptor, BTK, BCL2, CDK8 and c-MET [[6], [7], [8], [9], [10], [11]] have been successfully targeted using PROTACs. A variety of BET family (BRD2, BRD3, and BRD4)- PROTACs were designed using multiple ligases; MDM2-based BRD4 PROTAC [12], CRBN based dBET1 [13] and BETd-24-6 [14] for triple-negative breast cancer, enhanced membrane permeable dBET6 [15], and dBET57 PROTAC [16]. PROTACs for Hepatitis c virus (HCV) protease, IRAK4 and Tau [[17], [18], [19]] have been explored for viral, immune and neurodegenerative diseases, respectively. Currently, the PROTAC field expansion to vast undruggable proteome is hindered due to narrow focus on select E3 ligases. Lack of reliable tools to rapidly evaluate PROTACs based on new ligases is hindering the progress. Screening platforms designed must be physiologically relevant and represent true PROTAC cellular function, i.e., PROTAC-mediated target ubiquitination and degradation.

In the current study, we employ TUBEs as affinity capture reagents to monitor PROTAC-induced poly-ubiquitination and degradation as a measure of potency. We established and validated proof-of-concept cell-based assays in a 96-well format using PROTACS for three therapeutic targets BET family proteins, kinases, and KRAS. To our knowledge, the proposed PROTAC assays are first of its kind that can simultaneously 1) detect ubiquitination of endogenous, native protein targets, 2) evaluate the potency of PROTACs, and 3) establish a link between the UPS and protein degradation. Using these TUBE assays, we established rank order potencies between four BET family PROTACs dBET1, dBET6, BETd246 and dBET57 based on peak ubiquitination signals (“Ub_Max”) of the target protein. TUBE assay was successful in demonstrating promiscuous kinase PROTACs efficiency to degrade Aurora Kinase A at sub-nanomolar concentrations within 1 h. A comparative study to identify changes in the ubiquitination and degradation profile of KRAS G12C PROTACs recruiting two E3 ligases (CRBN and VHL). All of the ubiquitination and degradation profiles obtained from TUBE based assays correlate well with traditional low throughput immunoblotting. Significant correlation between DC₅₀ obtained from protein degradation in western blotting and Ub_Max values demonstrates our proposed assays can aid in high-throughput screening and drastically eliminate artifacts to overcome bottlenecks in PROTAC drug discovery.

To successfully set up HTS screening with novel PROTACs without pre-existing knowledge, we recommend the following steps. 1. Identify a model PROTAC that can potentially demonstrate activity based on knowledge in PROTAC design or in vitro binding studies. 2. Perform a time course study with 2–3 doses of the model PROTAC based on affinities of the ligands selected. 3. Monitor ubiquitination and degradation profiles using plate-based assay and identify time point that demonstrates Ub_Max. 4. Perform a dose response at selected time point with a library of PROTACs to establish rank order potency.

INTRODUCTION

Ubiquitination is a major regulatory mechanism to maintain cellular protein homeostasis by marking proteins for proteasomal-mediated degradation [1]. Given ubiquitin’s role in a variety of pathologies, the idea of targeting the Ubiquitin Proteasome System (UPS) is at the forefront of drug discovery [2]. “Event-driven” protein degradation using the cell’s own UPS is a promising technology for addressing the “undruggable” proteome [3]. Targeted protein degradation (TPD) has emerged as a new paradigm and promising therapeutic option to selectively attack previously intractable drug targets using PROteolytic TArgeting Chimeras (PROTACs) [4]. PROTACs are heterobifunctional molecules with a distinct ligand that targets a specific E3 ligase which is tethered to another ligand specific for the target protein using an optimized chemical linker. A functional PROTAC induces a ternary E3-PROTAC-target complex, resulting in poly-ubiquitination and subsequent controlled protein degradation [5]. Ability to function at sub-stoichiometric levels for efficient degradation, a significant advantage over traditional small molecules.

PROTACs have been explored in multiple disease fields with focus on only few ligases like cereblon (CRBN), Von Hippel-Lindau (VHL), IAP and MDM2. Cancer targets like androgen receptor, estrogen receptor, BTK, BCL2, CDK8 and c-MET [[6], [7], [8], [9], [10], [11]] have been successfully targeted using PROTACs. A variety of BET family (BRD2, BRD3, and BRD4)- PROTACs were designed using multiple ligases; MDM2-based BRD4 PROTAC [12], CRBN based dBET1 [13] and BETd-24-6 [14] for triple-negative breast cancer, enhanced membrane permeable dBET6 [15], and dBET57 PROTAC [16]. PROTACs for Hepatitis c virus (HCV) protease, IRAK4 and Tau [[17], [18], [19]] have been explored for viral, immune and neurodegenerative diseases, respectively. Currently, the PROTAC field expansion to vast undruggable proteome is hindered due to narrow focus on select E3 ligases. Lack of reliable tools to rapidly evaluate PROTACs based on new ligases is hindering the progress. Screening platforms designed must be physiologically relevant and represent true PROTAC cellular function, i.e., PROTAC-mediated target ubiquitination and degradation.

Cellular PROTAC screening is traditionally performed using cell lines harboring reporter genes and/or Western blotting. While Western blotting is easy to perform, they are low throughput, semi-quantitative and lack sensitivity. While reporter gene assays address some of the issues, they are challenged by reporter tags having internal lysines leading to artifacts. Currently, no approaches are available that can identify true PROTAC effects such as target ubiquitination and proteasome-mediated degradation simultaneously. High affinity ubiquitin capture reagents like TUBEs [20] (tandem ubiquitin binding entities), are engineered ubiquitin binding domains (UBDs) that allow for detection of ultralow levels of polyubiquitinated proteins under native conditions with affinities as low as 1 nM. The versatility and selectivity of TUBEs makes them superior to antibodies, and they also offer chain-selectivity (-K48, -K63, or linear) [21]. High throughput assays that can report the efficacy of multiple PROTACs simultaneously by monitoring PROTAC mediated ubiquitination can help establish rank order potency and guide chemists in developing meaningful structure activity relationships (SAR) rapidly.

In the current study, we employ TUBEs as affinity capture reagents to monitor PROTAC-induced poly-ubiquitination and degradation as a measure of potency. We established and validated proof-of-concept cell-based assays in a 96-well format using PROTACS for three therapeutic targets BET family proteins, kinases, and KRAS. To our knowledge, the proposed PROTAC assays are first of its kind that can simultaneously 1) detect ubiquitination of endogenous, native protein targets, 2) evaluate the potency of PROTACs, and 3) establish a link between the UPS and protein degradation. Using these TUBE assays, we established rank order potencies between four BET family PROTACs dBET1, dBET6, BETd246 and dBET57 based on peak ubiquitination signals (“Ub_Max”) of the target protein. TUBE assay was successful in demonstrating promiscuous kinase PROTACs efficiency to degrade Aurora Kinase A at sub-nanomolar concentrations within 1 h. A comparative study to identify changes in the ubiquitination and degradation profile of KRAS G12C PROTACs recruiting two E3 ligases (CRBN and VHL). All of the ubiquitination and degradation profiles obtained from TUBE based assays correlate well with traditional low throughput immunoblotting. Significant correlation between DC₅₀ obtained from protein degradation in western blotting and Ub_Max values demonstrates our proposed assays can aid in high-throughput screening and drastically eliminate artifacts to overcome bottlenecks in PROTAC drug discovery.

Fig. 1. Schematic representation of TUBE assay to monitor PROTAC mediated cellular ubiquitination of target proteins.

Fig. 2. TUBE based assay screening of PROTACs: Jurkat cell lysates were treated with BRD3-specific PROTACs A) dBET1, B) dBET6, C) BETd24-6, and D) dBET57. Polyubiquitination profiles and Ubmax of BRD3 for each PROTAC were represented as relative CL intensity. Relative CL intensities were calculated by dividing raw CL signals from a given PROTAC dose over DMSO treated samples. Error bars represent standard deviations, n = 3.

Fig. 3. PROTAC mediated degradation of bromodomain proteins analyzed by anti-BRD3 western blotting. Dose response of PROTACs dBET1, dBET6, Betd-24-6 and dBET57 at 45 min in Jurkat cells demonstrates degradation of BRD3, Acting as loading control.

Fig. 4. PROTAC mediated ubiquitination and degradation of AURKA in K562 cells. (A) Time course study to evaluate intracellular ubiquitination and degradation. (B) Western blot analysis of time course study: degradation kinetics (C) A dose response study to evaluate DC50 of the promiscuous kinase PROTAC in K562 cells. (D) Western blot analysis of dose response study to monitor degradation, GAPDH as loading control. Error bars represent standard deviation, n = 3.

SOURCE

https://www.sciencedirect.com/science/article/abs/pii/S0006291X22011792

Sperm epigenetic clock and pregnancy outcomes

Posted in Biological Engineering, Biological Networks, Gene Regulation and Evolution, Biomarkers & Medical Diagnostics, Biomedical Measurement Science, Cell Biology, Cell Biology, Signaling & Cell Circuits, Cell Processing System in Cell Therapy Process Development, Epigenetics and Environmental Factors, Genomic Endocrinology, Human aging, Methylation, MicroEngineering Cell-Tissue & Systems, Molecular Genetics & Pharmaceutical, Population Health Management, Genetics & Pharmaceutical, Preimplantation Genetic Diagnosis and Reproductive Genomics, Reproductive Andrology, Embryology, Genomic Endocrinology, Preimplantation Genetic Diagnosis and Reproductive Genomics, Reproductive Biology & Bio Instrumentation, tagged DNA methylation, Epigenetics, infertility, pregnancy, sperm on May 14, 2022| 1 Comment »

Reporter and Curator: Dr. Sudipta Saha, Ph.D.

Infertility has been primarily treated as a female predicament but around one-half of infertility cases can be tracked to male factors. Clinically, male infertility is typically determined using measures of semen quality recommended by World Health Organization (WHO). A major limitation, however, is that standard semen analyses are relatively poor predictors of reproductive capacity and success. Despite major advances in understanding the molecular and cellular functions in sperm over the last several decades, semen analyses remain the primary method to assess male fecundity and fertility.

Chronological age is a significant determinant of human fecundity and fertility. The disease burden of infertility is likely to continue to rise as parental age at the time of conception has been steadily increasing. While the emphasis has been on the effects of advanced maternal age on adverse reproductive and offspring health, new evidence suggests that, irrespective of maternal age, higher male age contributes to longer time-to-conception, poor pregnancy outcomes and adverse health of the offspring in later life. The effect of chronological age on the genomic landscape of DNA methylation is profound and likely occurs through the accumulation of maintenance errors of DNA methylation over the lifespan, which have been originally described as epigenetic drift.

In recent years, the strong relation between age and DNA methylation profiles has enabled the development of statistical models to estimate biological age in most somatic tissue via different epigenetic ‘clock’ metrics, such as DNA methylation age and epigenetic age acceleration, which describe the degree to which predicted biological age deviates from chronological age. In turn, these epigenetic clock metrics have emerged as novel biomarkers of a host of phenotypes such as allergy and asthma in children, early menopause, increased incidence of cancer types and cardiovascular-related diseases, frailty and cognitive decline in adults. They also display good predictive ability for cancer, cardiovascular and all-cause mortality.

Epigenetic clock metrics are powerful tools to better understand the aging process in somatic tissue as well as their associations with adverse disease outcomes and mortality. Only a few studies have constructed epigenetic clocks specific to male germ cells and only one study reported that smokers trended toward an increased epigenetic age compared to non-smokers. These results indicate that sperm epigenetic clocks hold promise as a novel biomarker for reproductive health and/or environmental exposures. However, the relation between sperm epigenetic clocks and reproductive outcomes has not been examined.

There is a critical need for new measures of male fecundity for assessing overall reproductive success among couples in the general population. Data shows that sperm epigenetic clocks may fulfill this need as a novel biomarker that predicts pregnancy success among couples not seeking fertility treatment. Such a summary measure of sperm biological age is of clinical importance as it allows couples in the general population to realize their probability of achieving pregnancy during natural intercourse, thereby informing and expediting potential infertility treatment decisions. With the ability to customize high throughput DNA methylation arrays and capture sequencing approaches, the integration of the epigenetic clocks as part of standard clinical care can enhance our understanding of idiopathic infertility and the paternal contribution to reproductive success and offspring health.

References:

https://academic.oup.com/humrep/advance-article/doi/10.1093/humrep/deac084/6583111?login=false

https://pubmed.ncbi.nlm.nih.gov/33317634/

https://clinicalepigeneticsjournal.biomedcentral.com/articles/10.1186/s13148-019-0656-7

https://pubmed.ncbi.nlm.nih.gov/19319879/

https://pubmed.ncbi.nlm.nih.gov/31901222/

https://pubmed.ncbi.nlm.nih.gov/25928123/

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New studies link cell cycle proteins to immunosurveillance of premalignant cells

Posted in Apoptosis, Biological Networks, Biological Networks, Gene Regulation and Evolution, Cancer - General, CANCER BIOLOGY & Innovations in Cancer Therapy, Cancer-Immune Interactions, Cell Biology, Signaling & Cell Circuits, Circulating Tumor Cells (CTC), Disease Biology, DNA repair, Efficacy of Anti-Tumor T Cells, Exosomes, Exosomes: Natural Carriers for siRNA Delivery, Immune Modulatory, Immuno-Oncology & Genomics, Immunology, KRAS Mutation, Modulating Macrophages in Cancer Immunotherapy, NK Cell-Based Cancer Immunotherapy, TP53 - Germline mutations, tagged CDKI, cell cycle, cell cycle arrest, cell cycle protein, cellular senescence, DNA repair or transcription factor genes, Immunology, immunosuppression, immunosurveillance, NF-kB, p21, p53, premalignant, transcriptional, transcriptional regulation, tumor suppressors on December 16, 2021| Leave a Comment »

New studies link cell cycle proteins to immunosurveillance of premalignant cells

Curator: Stephen J. Williams, Ph.D.

The following is from a Perspectives article in the journal Science by Virinder Reen and Jesus Gil called “Clearing Stressed Cells: Cell cycle arrest produces a p21-dependent secretome that initaites immunosurveillance of premalignant cells”. This is a synopsis of the Sturmlechener et al. research article in the same issue (2).

Complex organisms repair stress-induced damage to limit the replication of faulty cells that could drive cancer. When repair is not possible, tissue homeostasis is maintained by the activation of stress response programs such as apoptosis, which eliminates the cells, or senescence, which arrests them (1). Cellular senescence causes the arrest of damaged cells through the induction of cyclin-dependent kinase inhibitors (CDKIs) such as p16 and p21 (2). Senescent cells also produce a bioactive secretome (the senescence-associated secretory phenotype, SASP) that places cells under immunosurveillance, which is key to avoiding the detrimental inflammatory effects caused by lingering senescent cells on surrounding tissues. On page 577 of this issue, Sturmlechner et al. (3) report that induction of p21 not only contributes to the arrest of senescent cells, but is also an early signal that primes stressed cells for immunosurveillance.Senescence is a complex program that is tightly regulated at the epigenetic and transcriptional levels. For example, exit from the cell cycle is controlled by the induction of p16 and p21, which inhibit phosphorylation of the retinoblastoma protein (RB), a transcriptional regulator and tumor suppressor. Hypophosphorylated RB represses transcription of E2F target genes, which are necessary for cell cycle progression. Conversely, production of the SASP is regulated by a complex program that involves super-enhancer (SE) remodeling and activation of transcriptional regulators such as nuclear factor κB (NF-κB) or CCAAT enhancer binding protein–β (C/EBPβ) (4).

Senescence is a complex program that is tightly regulated at the epigenetic and transcriptional levels. For example, exit from the cell cycle is controlled by the induction of p16 and p21, which inhibit phosphorylation of the retinoblastoma protein (RB), a transcriptional regulator and tumor suppressor. Hypophosphorylated RB represses transcription of E2F target genes, which are necessary for cell cycle progression. Conversely, production of the SASP is regulated by a complex program that involves super-enhancer (SE) remodeling and activation of transcriptional regulators such as nuclear factor κB (NF-κB) or CCAAT enhancer binding protein–β (C/EBPβ) (4).

Sturmlechner et al. found that activation of p21 following stress rapidly halted cell cycle progression and triggered an internal biological timer (of ∼4 days in hepatocytes), allowing time to repair and resolve damage (see the figure). In parallel, C-X-C motif chemokine 14 (CXCL14), a component of the PASP, attracted macrophages to surround and closely surveil these damaged cells. Stressed cells that recovered and normalized p21 expression suspended PASP production and circumvented immunosurveillance. However, if the p21-induced stress was unmanageable, the repair timer expired, and the immune cells transitioned from surveillance to clearance mode. Adjacent macrophages mounted a cytotoxic T lymphocyte response that destroyed damaged cells. Notably, the overexpression of p21 alone was sufficient to orchestrate immune killing of stressed cells, without the need of a senescence phenotype. Overexpression of other CDKIs, such as p16 and p27, did not trigger immunosurveillance, likely because they do not induce CXCL14 expression.In the context of cancer, senescent cell clearance was first observed following reactivation of the tumor suppressor p53 in liver cancer cells. Restoring p53 signaling induced senescence and triggered the elimination of senescent cells by the innate immune system, prompting tumor regression (5). Subsequent work has revealed that the SASP alerts the immune system to target preneoplastic senescent cells. Hepatocytes expressing the oncogenic mutant NRAS^G12V (Gly¹²→Val) become senescent and secrete chemokines and cytokines that trigger CD4⁺ T cell–mediated clearance (6). Despite the relevance for tumor suppression, relatively little is known about how immunosurveillance of oncogene-induced senescent cells is initiated and controlled.

Source of image: Reen, V. and Gil, J. Clearing Stressed Cells. Science Perspectives 2021;Vol 374(6567) p 534-535.

References

2. Sturmlechner I, Zhang C, Sine CC, van Deursen EJ, Jeganathan KB, Hamada N, Grasic J, Friedman D, Stutchman JT, Can I, Hamada M, Lim DY, Lee JH, Ordog T, Laberge RM, Shapiro V, Baker DJ, Li H, van Deursen JM. p21 produces a bioactive secretome that places stressed cells under immunosurveillance. Science. 2021 Oct 29;374(6567):eabb3420. doi: 10.1126/science.abb3420. Epub 2021 Oct 29. PMID: 34709885.

UK Biobank Makes Available 200,000 whole genomes Open Access

Posted in Big Data, Bio-Ethics, BioBanking, BioIT: BioInformatics, BioIT: BioInformatics, NGS, Clinical & Translational, Pharmaceutical R&D Informatics, Clinical Genomics, Cancer Informatics, Biological Networks, Gene Regulation and Evolution, Disease Biology, Genome Biology, Genomic Expression, Intelligent Information Systems, Personalized and Precision Medicine & Genomic Research, Population Health Management, Genetics & Pharmaceutical, tagged Amgen, biobank, biomedical, Genome-wide association study, genomics, Icelanders, NIH, Population genetics, UKBB, Whole genome sequencing on December 7, 2021| Leave a Comment »

UK Biobank Makes Available 200,000 whole genomes Open Access

Reporter: Stephen J. Williams, Ph.D.

The following is a summary of an article by Jocelyn Kaiser, published in the November 26, 2021 issue of the journal Science.

To see the full article please go to https://www.science.org/content/article/200-000-whole-genomes-made-available-biomedical-studies-uk-effort

The UK Biobank (UKBB) this week unveiled to scientists the entire genomes of 200,000 people who are part of a long-term British health study.

The trove of genomes, each linked to anonymized medical information, will allow biomedical scientists to scour the full 3 billion base pairs of human DNA for insights into the interplay of genes and health that could not be gleaned from partial sequences or scans of genome markers. “It is thrilling to see the release of this long-awaited resource,” says Stephen Glatt, a psychiatric geneticist at the State University of New York Upstate Medical University.

Other biobanks have also begun to compile vast numbers of whole genomes, 100,000 or more in some cases (see table, below). But UKBB stands out because it offers easy access to the genomic information, according to some of the more than 20,000 researchers in 90 countries who have signed up to use the data. “In terms of availability and data quality, [UKBB] surpasses all others,” says physician and statistician Omar Yaxmehen Bello-Chavolla of the National Institute for Geriatrics in Mexico City.

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Data drives discovery. We have curated a uniquely powerful biomedical database that can be accessed globally for public health research. Explore data from half a million UK Biobank participants to enable new discoveries to improve public health.

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This UKBB biobank represents genomes collected from 500,000 middle-age and elderly participants for 2006 to 2010. The genomes are mostly of a European descent. Other large scale genome sequencing ventures like Iceland’s DECODE, which collected over 100,000 genomes, is now a subsidiary of Amgen, and mostly behind IP protection, not Open Access as this database represents.

UK Biobank is a large-scale biomedical database and research resource, containing in-depth genetic and health information from half a million UK participants. The database is regularly augmented with additional data and is globally accessible to approved researchers undertaking vital research into the most common and life-threatening diseases. It is a major contributor to the advancement of modern medicine and treatment and has enabled several scientific discoveries that improve human health.

A summary of some large scale genome sequencing projects are show in the table below:

Biobank	Completed Whole Genomes	Release Information
UK Biobank	200,000	300,000 more in early 2023
TransOmics for Precision Medicien	161,000	NIH requires project specific request
Million Veterans Program	125,000	Non-Veterans Affairs researchers get first access
100,000 Genomes Project	120,000	Researchers must join Genomics England collaboration
All of Us	90,000	NIH expects to release 2022

#TUBiol5227: Biomarkers & Biotargets: Genetic Testing and Bioethics

Posted in and Bioethics, Bio-Ethics, BioBanking, BioIT: BioInformatics, BioIT: BioInformatics, NGS, Clinical & Translational, Pharmaceutical R&D Informatics, Clinical Genomics, Cancer Informatics, Biological Networks, Biomarkers & Medical Diagnostics, BioSimilars, Biotechnology, BioTechnology - Venture Creation, Cancer and Current Therapeutics, Cancer Genomics, Clinical Diagnostics, Clinical Genomics, Conference Coverage with Social Media, Ethics and Leadership, FDA, FDA Regulatory Affairs, Federal Budget Appropriations, Health Economics and Outcomes Research, Health Law Policy, Healthcare costs and reimbursement, Intellectual Property, Innovations, Commercialization, Investment in technological breakthrough, interventional oncology, Next Generation Sequencing (NGS), Patent Law in Biotech, Patents, Patient Experience, Personal Health Applications: Tech Innovations serves HealhCare, Personalized and Precision Medicine & Genomic Research, Personalized Medicine Coalition, Precision Cancer Medicine, Regulated Clinical Trials: Design, Methods, Components and IRB related issues, Voices of Patients and Healthcare Providers, tagged #TUBiol5227, bioethics, biomarkers, Drug development, FDA, healthcare, insurers, legal, Patient, payers, physician-patient, Regulatory on September 28, 2021| Leave a Comment »

#TUBiol5227: Biomarkers & Biotargets: Genetic Testing and Bioethics

Curator: Stephen J. Williams, Ph.D.

The advent of direct to consumer (DTC) genetic testing and the resultant rapid increase in its popularity as well as companies offering such services has created some urgent and unique bioethical challenges surrounding this niche in the marketplace. At first, most DTC companies like 23andMe and Ancestry.com offered non-clinical or non-FDA approved genetic testing as a way for consumers to draw casual inferences from their DNA sequence and existence of known genes that are linked to disease risk, or to get a glimpse of their familial background. However, many issues arose, including legal, privacy, medical, and bioethical issues. Below are some articles which will explain and discuss many of these problems associated with the DTC genetic testing market as well as some alternatives which may exist.

‘Direct-to-Consumer (DTC) Genetic Testing Market to hit USD 2.5 Bn by 2024’ by Global Market Insights

This post has the following link to the market analysis of the DTC market (https://www.gminsights.com/pressrelease/direct-to-consumer-dtc-genetic-testing-market). Below is the highlights of the report.

As you can see,this market segment appears to want to expand into the nutritional consulting business as well as targeted biomarkers for specific diseases.

Rising incidence of genetic disorders across the globe will augment the market growth

Increasing prevalence of genetic disorders will propel the demand for direct-to-consumer genetic testing and will augment industry growth over the projected timeline. Increasing cases of genetic diseases such as breast cancer, achondroplasia, colorectal cancer and other diseases have elevated the need for cost-effective and efficient genetic testing avenues in the healthcare market.

For instance, according to the World Cancer Research Fund (WCRF), in 2018, over 2 million new cases of cancer were diagnosed across the globe. Also, breast cancer is stated as the second most commonly occurring cancer. Availability of superior quality and advanced direct-to-consumer genetic testing has drastically reduced the mortality rates in people suffering from cancer by providing vigilant surveillance data even before the onset of the disease. Hence, the aforementioned factors will propel the direct-to-consumer genetic testing market overt the forecast timeline.

DTC Genetic Testing Market By Technology

Get more details on this report – Request Free Sample PDF

Nutrigenomic Testing will provide robust market growth

The nutrigenomic testing segment was valued over USD 220 million market value in 2019 and its market will witness a tremendous growth over 2020-2028. The growth of the market segment is attributed to increasing research activities related to nutritional aspects. Moreover, obesity is another major factor that will boost the demand for direct-to-consumer genetic testing market.

Nutrigenomics testing enables professionals to recommend nutritional guidance and personalized diet to obese people and help them to keep their weight under control while maintaining a healthy lifestyle. Hence, above mentioned factors are anticipated to augment the demand and adoption rate of direct-to-consumer genetic testing through 2028.

Browse key industry insights spread across 161 pages with 126 market data tables & 10 figures & charts from the report, “Direct-To-Consumer Genetic Testing Market Size By Test Type (Carrier Testing, Predictive Testing, Ancestry & Relationship Testing, Nutrigenomics Testing), By Distribution Channel (Online Platforms, Over-the-Counter), By Technology (Targeted Analysis, Single Nucleotide Polymorphism (SNP) Chips, Whole Genome Sequencing (WGS)), Industry Analysis Report, Regional Outlook, Application Potential, Price Trends, Competitive Market Share & Forecast, 2020 – 2028” in detail along with the table of contents:
https://www.gminsights.com/industry-analysis/direct-to-consumer-dtc-genetic-testing-market

Targeted analysis techniques will drive the market growth over the foreseeable future

Based on technology, the DTC genetic testing market is segmented into whole genome sequencing (WGS), targeted analysis, and single nucleotide polymorphism (SNP) chips. The targeted analysis market segment is projected to witness around 12% CAGR over the forecast period. The segmental growth is attributed to the recent advancements in genetic testing methods that has revolutionized the detection and characterization of genetic codes.

Targeted analysis is mainly utilized to determine any defects in genes that are responsible for a disorder or a disease. Also, growing demand for personalized medicine amongst the population suffering from genetic diseases will boost the demand for targeted analysis technology. As the technology is relatively cheaper, it is highly preferred method used in direct-to-consumer genetic testing procedures. These advantages of targeted analysis are expected to enhance the market growth over the foreseeable future.

Over-the-counter segment will experience a notable growth over the forecast period

The over-the-counter distribution channel is projected to witness around 11% CAGR through 2028. The segmental growth is attributed to the ease in purchasing a test kit for the consumers living in rural areas of developing countries. Consumers prefer over-the-counter distribution channel as they are directly examined by regulatory agencies making it safer to use, thereby driving the market growth over the forecast timeline.

Favorable regulations provide lucrative growth opportunities for direct-to-consumer genetic testing

Europe direct-to-consumer genetic testing market held around 26% share in 2019 and was valued at around USD 290 million. The regional growth is due to elevated government spending on healthcare to provide easy access to genetic testing avenues. Furthermore, European regulatory bodies are working on improving the regulations set on the direct-to-consumer genetic testing methods. Hence, the above-mentioned factors will play significant role in the market growth.

Focus of market players on introducing innovative direct-to-consumer genetic testing devices will offer several growth opportunities

Few of the eminent players operating in direct-to-consumer genetic testing market share include Ancestry, Color Genomics, Living DNA, Mapmygenome, Easy DNA, FamilytreeDNA (Gene By Gene), Full Genome Corporation, Helix OpCo LLC, Identigene, Karmagenes, MyHeritage, Pathway genomics, Genesis Healthcare, and 23andMe. These market players have undertaken various business strategies to enhance their financial stability and help them evolve as leading companies in the direct-to-consumer genetic testing industry.

For example, in November 2018, Helix launched a new genetic testing product, DNA discovery kit, that allows customer to delve into their ancestry. This development expanded the firm’s product portfolio, thereby propelling industry growth in the market.

The following posts discuss bioethical issues related to genetic testing and personalized medicine from a clinicians and scientisit’s perspective

Question: Each of these articles discusses certain bioethical issues although focuses on personalized medicine and treatment. Given your understanding of the robust process involved in validating clinical biomarkers and the current state of the DTC market, how could DTC testing results misinform patients and create mistrust in the physician-patient relationship?

Personalized Medicine, Omics, and Health Disparities in Cancer: Can Personalized Medicine Help Reduce the Disparity Problem?

Diversity and Health Disparity Issues Need to be Addressed for GWAS and Precision Medicine Studies

Genomics & Ethics: DNA Fragments are Products of Nature or Patentable Genes?

The following posts discuss the bioethical concerns of genetic testing from a patient’s perspective:

Ethics Behind Genetic Testing in Breast Cancer: A Webinar by Laura Carfang of survivingbreastcancer.org

Ethical Concerns in Personalized Medicine: BRCA1/2 Testing in Minors and Communication of Breast Cancer Risk

23andMe Product can be obtained for Free from a new app called Genes for Good: UMich’s Facebook-based Genomics Project

Question: If you are developing a targeted treatment with a companion diagnostic, what bioethical concerns would you address during the drug development process to ensure fair, equitable and ethical treatment of all patients, in trials as well as post market?

Articles on Genetic Testing, Companion Diagnostics and Regulatory Mechanisms

Centers for Medicare & Medicaid Services announced that the federal healthcare program will cover the costs of cancer gene tests that have been approved by the Food and Drug Administration

Real Time Coverage @BIOConvention #BIO2019: Genome Editing and Regulatory Harmonization: Progress and Challenges

New York Times vs. Personalized Medicine? PMC President: Times’ Critique of Streamlined Regulatory Approval for Personalized Treatments ‘Ignores Promising Implications’ of Field

Live Conference Coverage @Medcitynews Converge 2018 Philadelphia: Early Diagnosis Through Predictive Biomarkers, NonInvasive Testing

Protecting Your Biotech IP and Market Strategy: Notes from Life Sciences Collaborative 2015 Meeting

Question: What type of regulatory concerns should one have during the drug development process in regards to use of biomarker testing? From the last article on Protecting Your IP how important is it, as a drug developer, to involve all payers during the drug development process?

Read Full Post »

Novartis uses a ‘dimmer switch’ medication to fine-tune gene therapy candidates

Posted in Alzheimer's Disease, Biomarkers & Medical Diagnostics, Cerebrovascular and Neurodegenerative Diseases, CRISPR alternative for editing genes without cutting, CRISPR applied to Human Germ Line, CRISPR/Cas9 & Gene Editing, Etiology, Gene Therapy & Gene Editing Development, Genome Biology, Genomic Expression, Neurodegenerative Diseases, Open Access Journals, RNA Biology, Scientific Publishing, tagged Alternate splicing, Chronic renal disease, CRISPR-Cas9, gene therapy, Huntington's disease, Spinal muscular atrophy on August 7, 2021| Leave a Comment »

Novartis uses a ‘dimmer switch’ medication to fine-tune gene therapy candidates

Reporter: Amandeep Kaur, BSc., MSc.

Using viral vectors, lipid nanoparticles, and other technologies, significant progress has been achieved in refining the delivery of gene treatments. However, modifications to the cargo itself are still needed to increase safety and efficacy by better controlling gene expression.

To that end, researchers at Children’s Hospital of Philadelphia (CHOP) have created a “dimmer switch” system that employs Novartis’ investigational Huntington’s disease medicine branaplam (LMI070) as a regulator to fine-tune the quantity of proteins generated from a gene therapy.

The investigational medicine branaplam was shown to fine-tune the expression of an erythropoietin gene therapy in mice by scientists from Children’s Hospital of Philadelphia and Novartis. (Novartis)

According to a new study published in Nature, the X^on system altered quantities of erythropoietin—which is used to treat anaemia associated with chronic renal disease—delivered to mice using viral vectors. The method has previously been licenced by Novartis, the maker of the Zolgensma gene therapy for spinal muscular atrophy.

The X^on system depends on a process known as “alternative splicing,” in which RNA is spliced to include or exclude specific exons of a gene, allowing the gene to code for multiple proteins. The team used branaplam, a small-molecule RNA-splicing modulator, for this platform. The medication was created to improve SMN2 gene splicing in order to cure spinal muscular atrophy. Novartis shifted its research to try the medication against Huntington’s disease after a trial failure.

A gene therapy’s payload remains dormant until oral branaplam is given, according to X^on. The medicine activates the expression of the therapy’s functional gene by causing it to splice in the desired way. Scientists from CHOP and the Novartis Institutes for BioMedical Research put the dimmer switch to the exam in an Epo gene therapy carried through adeno-associated viral vectors. The usage of branaplam increased mice Epo levels in the blood and hematocrit levels (the proportion of red blood cells to whole blood) by 60% to 70%, according to the researchers. The researchers fed the rodents branaplam again as their hematocrit decreased to baseline levels. The therapy reinduced Epo to levels similar to those seen in the initial studies, according to the researchers.

The researchers also demonstrated that the X^on system could be used to regulate progranulin expression, which is utilised to treat PGRN-deficient frontotemporal dementia and neuronal ceroid lipofuscinosis. The scientists emphasised that gene therapy requires a small treatment window to be both safe and effective.

In a statement, Beverly Davidson, Ph.D., the study’s senior author, said, “The dose of a medicine can define how high you want expression to be, and then the system can automatically ‘dim down’ at a pace corresponding to the half-life of the protein.”

“We may imagine scenarios in which a medication is used only once, such as to control the expression of foreign proteins required for gene editing, or only on a limited basis. Because the splicing modulators we examined are administered orally, compliance to control protein expression from viral vectors including X^on-based cassettes should be high.”

In gene-modifying medicines, scientists have tried a variety of approaches to alter gene expression. For example, methyl groups were utilised as a switch to turn on or off expression of genes in the gene-editing system CRISPR by a team of researchers from the Massachusetts Institute of Technology and the University of California, San Francisco.

Auxolytic, a biotech company founded by Stanford University academics, has described how knocking down a gene called UMPS could render T-cell therapies ineffective by depriving T cells of the nutrition uridine. X^on could also be tailored to work with cancer CAR-T cell therapy, according to the CHOP-Novartis researchers. The dimmer switch could help prevent cell depletion by halting CAR expression, according to the researchers. According to the researchers, such a tuneable switch could help CRISPR-based treatments by providing “a short burst” of production of CRISPR effector proteins to prevent undesirable off-target editing.

Source: https://www.fiercebiotech.com/research/novartis-fine-tunes-gene-therapy-a-huntington-s-disease-candidate-as-a-dimmer-switch?mkt_tok=Mjk0LU1RRi0wNTYAAAF-q1ives09mmSQhXDd_jhF0M11KBMt0K23Iru3ZMcZFf-vcFQwMMCxTOiWM-jHaEvtyGOM_ds_Cw6NuB9B0fr79a3Opgh32TjXaB-snz54d2xU_fw

Other Related Articles published in this Open Access Online Scientific Journal include the following:

Gene Therapy could be a Boon to Alzheimer’s disease (AD): A first-in-human clinical trial proposed

Reporter: Dr. Premalata Pati, Ph.D., Postdoc

https://pharmaceuticalintelligence.com/2021/03/22/gene-therapy-could-be-a-boon-to-alzheimers-disease-ad-a-first-in-human-clinical-trial-proposed/

Top Industrialization Challenges of Gene Therapy Manufacturing

Guest Authors: Dr. Mark Szczypka and Clive Glover

https://pharmaceuticalintelligence.com/2021/03/29/top-industrialization-challenges-of-gene-therapy-manufacturing/

Dysregulation of ncRNAs in association with Neurodegenerative Disorders

Curator: Amandeep Kaur

https://pharmaceuticalintelligence.com/2021/01/11/dysregulation-of-ncrnas-in-association-with-neurodegenerative-disorders/

Cancer treatment using CRISPR-based Genome Editing System