Healthcare analytics, AI solutions for biological big data, providing an AI platform for the biotech, life sciences, medical and pharmaceutical industries, as well as for related technological approaches, i.e., curation and text analysis with machine learning and other activities related to AI applications to these industries.
Shaping the Future: The Rise of Structural Nanomedicine
Curator: Dr. Sudipta Saha, Ph.D.
In their 2025 review, Mirkin, Mrksich, and Artzi describe how the field of structural nanomedicine is being transformed to revolutionize biomedical science. Therapeutic materials are now being designed with precise nanoscale architectures to optimize biological interactions, improve efficacy, and reduce side effects.
It is explained that, unlike traditional drug delivery methods, structural nanomedicine is centered on the engineering of form and function at the molecular level. Advances in DNA and RNA nanotechnology, self-assembling peptide systems, and engineered nanoparticles have been utilized to create customizable platforms capable of navigating complex biological environments. These structures are being programmed to respond to specific physiological triggers, thereby enabling targeted delivery and controlled release.
A strong emphasis is placed on how rational design principles—borrowed from materials science, chemistry, and bioengineering—are driving innovation. Examples are presented where precisely constructed nanostructures have been shown to outperform conventional therapies in cancer treatment, immunomodulation, and regenerative medicine.
Attention is drawn to the challenges that must still be addressed, including the scalability of manufacturing, regulatory barriers, and the need for deeper insights into nano-bio interactions at the systems level. It is argued that interdisciplinary collaboration will be required for the successful translation of structural nanomedicine from laboratory research to clinical application.
Ultimately, structural nanomedicine is portrayed as a paradigm shift—where passive carrier systems are being replaced by dynamic, functional architectures that actively engage in therapeutic processes. Optimism is expressed that through continued technological convergence, a new generation of precision therapies tailored to individual patients will be realized.
This review is recommended for researchers, clinicians, and industry professionals seeking to remain informed about future directions in biomedical innovation.
Resitu Medical Sets Stage for Breakthrough in Breast Tumour Removal
Curator: Dr. Sudipta Saha, Ph.D.
Resitu Medical, a Swedish company specializing in minimally invasive breast tumour removal, has announced the appointment of Stefan Sowa as its new Chief Executive Officer. Strategic leadership is being strengthened as the company moves towards commercialization in both European and American markets.
A novel electrosurgical device, designed to excise entire breast lesions during the biopsy procedure, is being developed by Resitu. The device is intended to minimize the need for open surgery by allowing intact removal of tissue with minimal bleeding, guided by real-time ultrasound imaging. Preclinical studies are currently being conducted, and preparations for FDA clearance and CE marking are underway.
ISO 13485 certification for the design, development, manufacturing, and sales of the device has been successfully obtained. Investment has been secured from major shareholders, including Novoaim, ALMI Invest Stockholm, and STOAF, to support the finalization of the product and the initiation of serial production for clinical trials.
Through the use of its technology, false negatives are hoped to be reduced, while patient outcomes and diagnostic accuracy are expected to be significantly improved. The burden on healthcare systems may also be alleviated by minimizing the need for recalls and secondary biopsies.
Positive attention has been garnered at major medical conferences, with workshops hosted at events such as the Uppsala Breast Meeting, and favourable media coverage has been achieved. With Stefan Sowa at the helm, Resitu’s innovative device is poised to transform breast cancer management practices globally.
SNU-BioTalk 2025: Symphony of Cellular Signals in Metabolism and Immune Response – International Conference at Sister Nivedita University, Kolkata, India on 16 & 17 January 2025
Joint Convenor: Dr. Sudipta Saha (Member of LPBI since 2012)
About the Conference:
The International Conference on ‘Symphony of Cellular Signals in Metabolism and Immune Response’ focuses on the complex signalling pathways governing cellular functions in health and disease. It will explore the cellular mechanisms that regulate metabolism, immune responses, and survival, highlighting advances in medical science and biotechnology. Bringing together leading experts and emerging researchers, the conference will feature keynote lectures, panel discussions, research presentations, and interactive sessions, all designed to foster collaboration and innovation. By promoting an exchange of ideas, the event aims to drive transformative insights and solutions that impact human health and sustainable healthcare practices.
The conference will also be livestreamed on YouTube and Facebook
This programme will also host I-STEM: Indian Science, Technology and Engineering facilities Map (I-STEM) is a dynamic and interactive national portal for research cooperation.
Thrust areas:
Intracellular signalling processes of cellular metabolism
Signalling pathways in physiological and pathological processes
A large clinical trial has shown that pembrolizumab (Keytruda), an immunotherapy drug, nearly doubles the cancer-free survival time for patients with high-risk, muscle-invasive bladder cancer following surgery. The study, published on September 15, 2024, in The New England Journal of Medicine, was led by NIH researchers and demonstrated that pembrolizumab outperforms traditional observation methods post-surgery. Patients receiving pembrolizumab had a median cancer-free survival of 29.6 months, compared to 14.2 months for the observation group.
The trial enrolled 702 participants, some of whom had previously undergone cisplatin-based chemotherapy (neoadjuvant therapy). Pembrolizumab was administered every three weeks for a year. The drug was well tolerated, with common side effects including fatigue, itching, diarrhea, and thyroid issues.
Interestingly, the benefit of pembrolizumab was seen regardless of the tumor’s PD-L1 status.
Patients with PD-L1-positive tumors had a median cancer-free survival of 36.9 months.
Patients with PD-L1-negative tumors experienced 17.3 months cancer-free.
These results suggest that PD-L1 status should not be the sole factor in selecting patients for this therapy.
While overall survival rates were similar between the pembrolizumab and observation groups, many patients in the observation group began taking nivolumab once it was approved, complicating survival comparisons. Researchers are continuing to explore other treatment combinations and biomarkers to better personalize adjuvant therapy for bladder cancer patients.
Regulatory T cells (Tregs) are important for sperm tolerance and male fertility
Reporter and Curator: Dr. Sudipta Saha, Ph.D.
Regulatory T cells (Tregs) are specialized immune cells that modulate tissue homeostasis. They are a specialized subset of T lymphocytes that function as suppressive immune cells and inhibit various elements of immune response in vitro and in vivo. While there are constraints on the number or function of Tregs which can be exploited to evoke an effective anti-tumor response, sufficient expansion of Tregs is essential for successful organ transplantation and for promoting tolerance of self and foreign antigens. Current studies have provided evidence that a defect in the number or function of Tregs contributes to the etiology of several reproductive diseases.
In the male reproductive tract, prevention of autoimmune responses against antigenic spermatozoa, while ensuring protection against stressors, is a key determinant of fertility. Using an autoimmunity-induced model, it was uncovered that the role of Tregs in maintaining the tolerogenic state of the testis and epididymis. The loss of tolerance induced an exacerbated immune cell infiltration and the development of anti-sperm antibodies, which caused severe male subfertility. By identifying immunoregulatory mechanisms in the testis and epididymis.
Tregs modulate tissue homeostatic processes and immune responses. Understanding tissue-Treg biology will contribute to developing precision-targeting treatment strategies. Here, it was reported that Tregs maintain the tolerogenic state of the testis and epididymis, where sperm are produced and mature. It was found that Treg depletion induces severe autoimmune orchitis and epididymitis, manifested by an exacerbated immune cell infiltration [CD4 T cells, monocytes, and mononuclear phagocytes (MPs)] and the development of anti-sperm antibodies (ASA).
In Treg-depleted mice, MPs increased projections toward the epididymal lumen as well as invading the lumen. ASA-bound sperm enhance sperm agglutination and might facilitate sperm phagocytosis. Tolerance breakdown impaired epididymal epithelial function and altered extracellular vesicle cargo, both of which play crucial roles in the acquisition of sperm fertilizing ability and subsequent embryo development. The affected mice had reduced sperm number and motility and severe fertility defects.
Deciphering these immunoregulatory mechanisms may lead to the development of therapies for infertility and identifying potential targets for immuno-contraception. Ultimately, such knowledge fills gaps related to reproductive mucosa, which is an understudied facet of human male health.
Eight Subcellular Pathologies driving Chronic Metabolic Diseases – Methods for Mapping Bioelectronic Adjustable Measurements as potential new Therapeutics: Impact on Pharmaceuticals in Use
In this curation we wish to present two breaking through goals:
Goal 1:
Exposition of a new direction of research leading to a more comprehensive understanding of Metabolic Dysfunctional Diseases that are implicated in effecting the emergence of the two leading causes of human mortality in the World in 2023: (a) Cardiovascular Diseases, and (b) Cancer
Goal 2:
Development of Methods for Mapping Bioelectronic Adjustable Measurements as potential new Therapeutics for these eight subcellular causes of chronic metabolic diseases. It is anticipated that it will have a potential impact on the future of Pharmaceuticals to be used, a change from the present time current treatment protocols for Metabolic Dysfunctional Diseases.
According to Dr. Robert Lustig, M.D, an American pediatric endocrinologist. He is Professor emeritus of Pediatrics in the Division of Endocrinology at the University of California, San Francisco, where he specialized in neuroendocrinology and childhood obesity, there are eight subcellular pathologies that drive chronic metabolic diseases.
These eight subcellular pathologies can’t be measured at present time.
In this curation we will attempt to explore methods of measurement for each of these eight pathologies by harnessing the promise of the emerging field known as Bioelectronics.
Unmeasurable eight subcellular pathologies that drive chronic metabolic diseases
Glycation
Oxidative Stress
Mitochondrial dysfunction [beta-oxidation Ac CoA malonyl fatty acid]
Insulin resistance/sensitive [more important than BMI], known as a driver to cancer development
Membrane instability
Inflammation in the gut [mucin layer and tight junctions]
Epigenetics/Methylation
Autophagy [AMPKbeta1 improvement in health span]
Diseases that are not Diseases: no drugs for them, only diet modification will help
Image source
Robert Lustig, M.D. on the Subcellular Processes That Belie Chronic Disease
These eight Subcellular Pathologies driving Chronic Metabolic Diseases are becoming our focus for exploration of the promise of Bioelectronics for two pursuits:
Will Bioelectronics be deemed helpful in measurement of each of the eight pathological processes that underlie and that drive the chronic metabolic syndrome(s) and disease(s)?
IF we will be able to suggest new measurements to currently unmeasurable health harming processes THEN we will attempt to conceptualize new therapeutic targets and new modalities for therapeutics delivery – WE ARE HOPEFUL
In the Bioelecronics domain we are inspired by the work of the following three research sources:
Michael Levin is an American developmental and synthetic biologist at Tufts University, where he is the Vannevar Bush Distinguished Professor. Levin is a director of the Allen Discovery Center at Tufts University and Tufts Center for Regenerative and Developmental Biology. Wikipedia
THE VOICE of Dr. Justin D. Pearlman, MD, PhD, FACC
PENDING
THE VOICE of Stephen J. Williams, PhD
Ten TakeAway Points of Dr. Lustig’s talk on role of diet on the incidence of Type II Diabetes
25% of US children have fatty liver
Type II diabetes can be manifested from fatty live with 151 million people worldwide affected moving up to 568 million in 7 years
A common myth is diabetes due to overweight condition driving the metabolic disease
There is a trend of ‘lean’ diabetes or diabetes in lean people, therefore body mass index not a reliable biomarker for risk for diabetes
Thirty percent of ‘obese’ people just have high subcutaneous fat. the visceral fat is more problematic
there are people who are ‘fat’ but insulin sensitive while have growth hormone receptor defects. Points to other issues related to metabolic state other than insulin and potentially the insulin like growth factors
At any BMI some patients are insulin sensitive while some resistant
Visceral fat accumulation may be more due to chronic stress condition
Fructose can decrease liver mitochondrial function
A methionine and choline deficient diet can lead to rapid NASH development
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 NRASG12V (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.
More Articles on Cancer, Senescence and the Immune System in this Open Access Online Scientific Journal Include
Yet another Success Story: Machine Learning to predict immunotherapy response
Curator and Reporter: Dr. Premalata Pati, Ph.D., Postdoc
Immune-checkpoint blockers(ICBs) immunotherapy appears promising for various cancer types, offering a durable therapeutic advantage. Only a number of cases with cancer respond to this therapy. Biomarkers are required to adequately predict the responses of patients. This article evaluates this issue utilizing a system method to characterize the immune response of the anti-tumor based on the entire tumor environment. Researchers build mechanical biomarkers and cancer-specific response models using interpretable machine learning that predict the response of patients to ICB.
The lymphatic and immunological systems help the body defend itself by combating. The immune system functions as the body’s own personal police force, hunting down and eliminating pathogenic baddies.
According to Federica Eduati, Department of Biomedical Engineering at TU/e, “The immune system of the body is quite adept at detecting abnormally behaving cells. Cells that potentially grow into tumors or cancer in the future are included in this category. Once identified, the immune system attacks and destroys the cells.”
Immunotherapy and machine learning are combining to assist the immune system solve one of its most vexing problems: detecting hidden tumorous cells in the human body.
It is the fundamental responsibility of our immune system to identify and remove alien invaders like bacteria or viruses, but also to identify risks within the body, such as cancer. However, cancer cells have sophisticated ways of escaping death by shutting off immune cells. Immunotherapy can reverse the process, but not for all patients and types of cancer. To unravel the mystery, Eindhoven University of Technology researchers used machine learning. They developed a model to predict whether immunotherapy will be effective for a patient using a simple trick. Even better, the model outperforms conventional clinical approaches.
“Tumor also contains multiple types of immune and fibroblast cells which can play a role in favor of or anti-tumor, and communicates among themselves,” said Oscar Lapuente-Santana, a researcher doctoral student in the computational biology group. “We had to learn how complicated regulatory mechanisms in the micro-environment of the tumor affect the ICB response. We have used RNA sequencing datasets to depict numerous components of the Tumor Microenvironment (TME) in a high-level illustration.”
Using computational algorithms and datasets from previous clinical patient care, the researchers investigated the TME.
Eduati explained
While RNA-sequencing databases are publically available, information on which patients responded to ICB therapy is only available for a limited group of patients and cancer types. So, to tackle the data problem, we used a trick.
All 100 models learned in the randomized cross-validation were included in the EaSIeR tool. For each validation dataset, we used the corresponding cancer-type-specific model: SKCM for the melanoma Gide, Auslander, Riaz, and Liu cohorts; STAD for the gastric cancer Kim cohort; BLCA for the bladder cancer Mariathasan cohort; and GBM for the glioblastoma Cloughesy cohort. To make predictions for each job, the average of the 100 cancer-type-specific models was employed. The predictions of each dataset’s cancer-type-specific models were also compared to models generated for the remaining 17 cancer types.
From the same datasets, the researchers selected several surrogate immunological responses to be used as a measure of ICB effectiveness.
Lapuente-Santana stated
One of the most difficult aspects of our job was properly training the machine learning models. We were able to fix this by looking at alternative immune responses during the training process.
DREAM is an organization that carries out crowd-based tasks with biomedical algorithms. “We were the first to compete in one of the sub-challenges under the name cSysImmunoOnco team,” Eduati remarks.
The researchers noted,
We applied machine learning to seek for connections between the obtained system-based attributes and the immune response, estimated using 14 predictors (proxies) derived from previous publications. We treated these proxies as individual tasks to be predicted by our machine learning models, and we employed multi-task learning algorithms to jointly learn all tasks.
The researchers discovered that their machine learning model surpasses biomarkers that are already utilized in clinical settings to evaluate ICB therapies.
But why are Eduati, Lapuente-Santana, and their colleagues using mathematical models to tackle a medical treatment problem? Is this going to take the place of the doctor?
Eduati explains
Mathematical models can provide an overview of the interconnection between individual molecules and cells and at the same time predicting a particular patient’s tumor behavior. This implies that immunotherapy with ICB can be personalized in a patient’s clinical setting. The models can aid physicians with their decisions about optimum therapy, it is vital to note that they will not replace them.
Furthermore, the model aids in determining which biological mechanisms are relevant for the biological response.
The researchers noted
Another advantage of our concept is that it does not need a dataset with known patient responses to immunotherapy for model training.
Further testing is required before these findings may be implemented in clinical settings.
Main Source:
Lapuente-Santana, Ó., van Genderen, M., Hilbers, P. A., Finotello, F., & Eduati, F. (2021). Interpretable systems biomarkers predict response to immune-checkpoint inhibitors. Patterns, 100293. https://www.cell.com/patterns/pdfExtended/S2666-3899(21)00126-4
Other Related Articles published in this Open Access Online Scientific Journal include the following:
Inhibitory CD161 receptor recognized as a potential immunotherapy target in glioma-infiltrating T cells by single-cell analysis
Deep Learning for In-silico Drug Discovery and Drug Repurposing: Artificial Intelligence to search for molecules boosting response rates in Cancer Immunotherapy: Insilico Medicine @John Hopkins University
Inhibitory CD161 receptor recognized as a potential immunotherapy target in glioma-infiltrating T cells by single-cell analysis
Reporter: Dr. Premalata Pati, Ph.D., Postdoc
Brain tumors, especially the diffused Gliomas are of the most devastating forms of cancer and have so-far been resistant to immunotherapy. It is comprehended that T cells can penetrate the glioma cells, but it still remains unknown why infiltrating cells miscarry to mount a resistant reaction or stop the tumor development.
Gliomas are brain tumors that begin from neuroglial begetter cells. The conventional therapeutic methods including, surgery, chemotherapy, and radiotherapy, have accomplished restricted changes inside glioma patients. Immunotherapy, a compliance in cancer treatment, has introduced a promising strategy with the capacity to penetrate the blood-brain barrier. This has been recognized since the spearheading revelation of lymphatics within the central nervous system. Glioma is not generally carcinogenic. As observed in a number of cases, the tumor cells viably reproduce and assault the adjoining tissues, by and large, gliomas are malignant in nature and tend to metastasize. There are four grades in glioma, and each grade has distinctive cell features and different treatment strategies. Glioblastoma is a grade IV glioma, which is the crucial aggravated form. This infers that all glioblastomas are gliomas, however, not all gliomas are glioblastomas.
Decades of investigations on infiltrating gliomas still take off vital questions with respect to the etiology, cellular lineage, and function of various cell types inside glial malignancies. In spite of the available treatment options such as surgical resection, radiotherapy, and chemotherapy, the average survival rate for high-grade glioma patients remains 1–3 years (1).
A recent in vitro study performed by the researchers of Dana-Farber Cancer Institute, Massachusetts General Hospital, and the Broad Institute of MIT and Harvard, USA, has recognized that CD161 is identified as a potential new target for immunotherapy of malignant brain tumors. The scientific team depicted their work in the Cell Journal, in a paper entitled, “Inhibitory CD161 receptor recognized in glioma-infiltrating T cells by single-cell analysis.” on 15th February 2021.
To further expand their research and findings, Dr. Kai Wucherpfennig, MD, PhD, Chief of the Center for Cancer Immunotherapy, at Dana-Farber stated that their research is additionally important in a number of other major human cancer types such as
melanoma,
lung,
colon, and
liver cancer.
Dr. Wucherpfennig has praised the other authors of the report Mario Suva, MD, PhD, of Massachusetts Common Clinic; Aviv Regev, PhD, of the Klarman Cell Observatory at Broad Institute of MIT and Harvard, and David Reardon, MD, clinical executive of the Center for Neuro-Oncology at Dana-Farber.
Hence, this new study elaborates the effectiveness of the potential effectors of anti-tumor immunity in subsets of T cells that co-express cytotoxic programs and several natural killer (NK) cell genes.
The Study-
IMAGE SOURCE: Experimental Strategy (Mathewson et al., 2021)
The group utilized single-cell RNA sequencing (RNA-seq) to mull over gene expression and the clonal picture of tumor-infiltrating T cells. It involved the participation of 31 patients suffering from diffused gliomas and glioblastoma. Their work illustrated that the ligand molecule CLEC2D activates CD161, which is an immune cell surface receptor that restrains the development of cancer combating activity of immune T cells and tumor cells in the brain. The study reveals that the activation of CD161 weakens the T cell response against tumor cells.
Based on the study, the facts suggest that the analysis of clonally expanded tumor-infiltrating T cells further identifies the NK gene KLRB1 that codes for CD161 as a candidate inhibitory receptor. This was followed by the use of
CRISPR/Cas9 gene-editing technology to inactivate the KLRB1 gene in T cells and showed that CD161 inhibits the tumor cell-killing function of T cells. Accordingly,
genetic inactivation of KLRB1 or
antibody-mediated CD161 blockade
enhances T cell-mediated killing of glioma cells in vitro and their anti-tumor function in vivo. KLRB1 and its associated transcriptional program are also expressed by substantial T cell populations in other forms of human cancers. The work provides an atlas of T cells in gliomas and highlights CD161 and other NK cell receptors as immune checkpoint targets.
Further, it has been identified that many cancer patients are being treated with immunotherapy drugs that disable their “immune checkpoints” and their molecular brakes are exploited by the cancer cells to suppress the body’s defensive response induced by T cells against tumors. Disabling these checkpoints lead the immune system to attack the cancer cells. One of the most frequently targeted checkpoints is PD-1. However, recent trials of drugs that target PD-1 in glioblastomas have failed to benefit the patients.
In the current study, the researchers found that fewer T cells from gliomas contained PD-1 than CD161. As a result, they said, “CD161 may represent an attractive target, as it is a cell surface molecule expressed by both CD8 and CD4 T cell subsets [the two types of T cells engaged in response against tumor cells] and a larger fraction of T cells express CD161 than the PD-1 protein.”
However, potential side effects of antibody-mediated blockade of the CLEC2D-CD161 pathway remain unknown and will need to be examined in a non-human primate model. The group hopes to use this finding in their future work by
utilizing their outline by expression of KLRB1 gene in tumor-infiltrating T cells in diffuse gliomas to make a remarkable contribution in therapeutics related to immunosuppression in brain tumors along with four other common human cancers ( Viz. melanoma, non-small cell lung cancer (NSCLC), hepatocellular carcinoma, and colorectal cancer) and how this may be manipulated for prevalent survival of the patients.
References
(1) Anders I. Persson, QiWen Fan, Joanna J. Phillips, William A. Weiss, 39 – Glioma, Editor(s): Sid Gilman, Neurobiology of Disease, Academic Press, 2007, Pages 433-444, ISBN 9780120885923, https://doi.org/10.1016/B978-012088592-3/50041-4.
4.1.3 Single-cell Genomics: Directions in Computational and Systems Biology – Contributions of Prof. Aviv Regev @Broad Institute of MIT and Harvard, Cochair, the Human Cell Atlas Organizing Committee with Sarah Teichmann of the Wellcome Trust Sanger Institute
4.1.7 Norwich Single-Cell Symposium 2019, Earlham Institute, single-cell genomics technologies and their application in microbial, plant, animal and human health and disease, October 16-17, 2019, 10AM-5PM
Positron Emission Tomography (PET) and Near-Infrared Fluorescence Imaging: Noninvasive Imaging of Cancer Stem Cells (CSCs) monitoring of AC133+ glioblastoma in subcutaneous and intracerebral xenograft tumors
LPBI Group’s decision to publish the Table of Contents of this Report does not imply endorsement of the Report
Aviva Lev-Ari, PhD, RN, Founder 1.0 & 2.0 LPBI Group
Guest Reporter: MIKE WOOD
Marketing Executive BIOTECH FORECASTS
ABOUT BIOTECH FORECASTS
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CAR T-cell therapy as a part of adoptive cell therapy (ACT), has become one of the most rapidly growing and promising fields in the Immuno-oncology. As compared to the conventional cancer therapies, CAR T-cell therapy is the single-dose solution for the treatment of various cancers, significantly for some lethal forms of hematological malignancies.
CAR T-cell therapy mainly involves the use of engineered T-cells, the process starts with the extraction of T-cells through leukapheresis, either from the patient (autologous) or a healthy donor (allogeneic). After the expression of a synthetic receptor (Chimeric Antigen Receptor) in the lab, the altered T-cells are expanded to the right dose and administered into the patient’s body. where they target and attach to a specific antigen on the tumor surface, to kill the cancerous cells by igniting the apoptosis.
The global CAR T-cell therapy market was valued at $734 million in 2019 and is estimated to reach $4,078 million by 2027, registering a CAGR of 23.91% from 2020 to 2027.
Factors that drive the market growth involve, (1)Increased in fundingfor R&D activities pertaining to cell and gene therapy. By H1 2020 cell and gene therapy companies set new records in the fundraising despite the pandemic crisis. For Instance, by June 2020 totaled $1,452 Million raised in Five IPOs including, Legend Biotech ($487M), Passage Bio ($284M), Akouos ($244M), Generation Bio ($230M), and Beam Therapeutics ($207M), which is 2.5 times the total IPO of 2019.
Moreover, in 2019 cell therapy companies specifically have raised $560 million of venture capital, including Century Therapeutics ($250M), Achilles Therapeutics Ltd. ($121M in series B), NKarta Therapeutics Inc. ($114M), and Tmunity Therapeutics ($75M in Series B).
(2)Increased in No. of Approved Products, By July 2020, there are a total of 03 approved CAR T-cell therapy products, including KYMRIAH®, YESCARTA®, and the most recently approved TECARTUS™ (formerly KTE-X19). Furthermore, two CAR T-cell therapies BB2121, and JCAR017 are expected to get the market approval by the end of 2020 or in early 2021.
Other factors that boost the market growth involves; (3) increase in government support, (4) ethical acceptance of Cell and Gene therapy for cancer treatment, (5) rise in the prevalence of cancer, and (6) an increase in awareness regarding the CAR T-cell therapy.
However, high costs associated with the treatment (KYMRIAH® cost around $475,000, and YESCARTA® costs $373,000 per infusion), long production hours, obstacles in treating solid tumors, and unwanted immune responses & potential side effects might hamper the market growth.
The report also presents a detailed quantitative analysis of the current market trends and future estimations from 2020 to 2027.
The forecasts cover 2 Approach Types, 5 Antigen Types, 5 Application Types, 4 Regions, and 14 Countries.
The report comes with an associated file covering quantitative data from all numeric forecasts presented in the report, as well as with a Clinical Trials Data File.
KEY FINDINGS
The report has the following key findings:
The global CAR T-cell therapy market accounted for $734 million in 2019 and is estimated to reach $4,078 million by 2027, registering a CAGR of 23.91% from 2020 to 2027.
By approach type the autologous segment was valued at $655.26 million in 2019 and is estimated to reach $ 3,324.52 million by 2027, registering a CAGR of 22.51% from 2020 to 2027.
By approach type, the allogeneic segment exhibits the highest CAGR of 32.63%.
Based on the Antigen segment CD19 was the largest contributor among the other segments in 2019.
The Acute lymphocytic leukemia (ALL) segment generated the highest revenue and is expected to continue its dominance in the future, followed by the Diffuse large B-cell lymphoma (DLBCL) segment.
North America dominated the global CAR T-cell therapy market in 2019 and is projected to continue its dominance in the future.
China is expected to grow the highest in the Asia-Pacific region during the forecast period.
TOPICS COVERED
The report covers the following topics:
Market Drivers, Restraints, and Opportunities
Porters Five Forces Analysis
CAR T-Cell Structure, Generations, Manufacturing, and Pricing Models
Top Winning Strategies, Top Investment Pockets
Analysis of by Approach Type, Antigen Type, Application, and Region
51 Company Profiles, Product Portfolio, and Key Strategies
Approved Products Profiles, and list of Expected Approvals
COVID-19 Impact on the Cell and Gene Therapy Industry
CAR T-cell therapy clinical trials analysis from 1997 to 2019
Market analysis and forecasts from 2020 to 2027
FORECAST SEGMENTATION
By Approach Type
Autologous
Allogeneic
By Antigen Type
CD19
CD20
BCMA
MSLN
Others
By Application
Acute lymphoblastic leukemia (ALL)
Diffuse large B-Cell lymphoma (DLBCL)
Multiple Myeloma (MM)
Acute Myeloid Leukemia (AML)
Other Cancer Indications
By Region
North America: USA, Canada, Mexico
Europe: UK, Germany, France, Spain, Italy, Rest of Europe
Asia-Pacific: China, Japan, India, South Korea, Rest of Asia-Pacific
LAMEA: Brazil, South Africa, Rest of LAMEA
Contact at info@biotechforecasts.com for any Queries or Free Report Sample
2012pharmaceutical
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