Mechanism-driven biomarkers to guide immune checkpoint blockade in cancer therapy
Abstract
With recent approvals for multiple therapeutic antibodies that block cytotoxic T lymphocyte associated antigen 4 (CTLA4) and programmed cell death protein 1 (PD1) in melanoma, non-small-cell lung cancer and kidney cancer, and additional immune checkpoints being targeted clinically, many questions still remain regarding the optimal use of drugs that block these checkpoint pathways. Defining biomarkers that predict therapeutic effects and adverse events is a crucial mandate, highlighted by recent approvals for two PDL1 diagnostic tests. Here, we discuss biomarkers for anti-PD1 therapy based on immunological, genetic and virological criteria. The unique biology of the CTLA4 immune checkpoint, compared with PD1, requires a different approach to biomarker development. Mechanism-based insights from such studies may guide the design of synergistic treatment combinations based on immune checkpoint blockade
Conclusions and future biomarker considerations
Recent clinical advances with drugs that block immune checkpoints have brought immunotherapy out of the realm of highly specialized therapy and into the mainstream of oncology. To date, anti-CTLA4 therapy has shown reproducible activity only in patients with advanced melanoma. In contrast, anti-PD1–PDL1 drugs blocking a related but distinct immune checkpoint seem to have a broad range of activity extending beyond melanoma to an expanding list of cancers, including those of the lung, kidney, bladder, head and neck, breast, liver and gastrointestinal tract, and certain lymphoma subtypes. However, other cancer types such as prostate cancer and CRC have proved much more resistant to anti-PD1 therapies, underscoring the need for biomarker development. The evolution of our basic mechanistic understanding of immune checkpoint pathways has facilitated the search for pretreatment and on-treatment biomarkers that predict clinical response in different tumour types and the individual patients associated with them. The functional attributes of CTLA4, PD1 and other immune checkpoints will guide future biomarker discovery strategies uniquely suited to these non-redundant regulatory pathways. The predominant impact of the PD1 pathway in peripheral tissues suggests that the tumour site itself contains the most important clues for the development of anti-PD1 therapy biomarkers; in fact, this has been a rich source of promising biomarker leads pertaining to the expression of immunoregulatory molecules, oncogenic driver mutations, mutational burden and cancer-associated viruses. In contrast, the global inhibitory effects of CTLA4 in the immune system are consistent with systemic pharmacodynamic alterations found in circulating lymphocytes.
Whereas CTLA4 and PD1 blockade have reached the stage of regulatory approval, the list of additional checkpoint receptors and ligands being targeted clinically is growing. Examples include LAG3, T-cell immunoglobulin mucin receptor 3 (TIM3; also known as HAVCR2), B7H3 (also known as CD276), CD39, CD73 and the adenosine A2a receptor113–117. Inhibitory metabolic enzymes, such as IDO1, are also being targeted by small molecules118. Most of these immune checkpoints are being targeted in conjunction with PD1 pathway blocking antibodies. As mentioned above, some of these checkpoints are co-expressed with PDL1, providing a rationale for this dual blockade therapy. However, because clinical trials are in their early stages, there are as yet no validated biomarkers to predict which patients will benefit most from dual blockade of these molecules. Although several trials involve analysis of expression of the target in tumour biopsies, it is not yet clear which of these operate predominantly within the TME compared with outside the TME, that is, during T cell activation within lymph nodes. Nonetheless, intensive pharmacodynamic and correlative immune studies will be needed as part of all early-stage clinical trials — this is the only way that biomarker candidates can be identified as combinatorial checkpoint blockade approaches proliferate.
As more is learned about the TME and about regulation of systemic immunity to cancer, it is likely that additional biomarkers will emerge. For example, recent studies on metabolism demonstrate that tumours and T cells compete for glucose and that this competition can affect the glycolysis-dependent function of TILs119, raising the notion that metabolic biomarkers may be crucial factors in antitumour responsiveness. Another potential biomarker is the gut microbiome. Two recent studies speak to this possibility. One study in mice suggested that microbiomes high in Bifidobacter species enhanced tumour response to anti-PDL1 therapy120. A study in humans suggested that Bacteroides species (Bacteroides fragilis and Bacteroides thetaiotaomicron) in the microbiome might enhance the response of patients with melanoma to anti-CTLA4 therapy121. Even though the mechanisms by which these species may enhance systemic antitumour immunity are unknown at this time, these data suggest that microbiome-derived biomarkers may be developed to guide immunotherapy.
Unlike static biomarkers defined by driver mutations directly linked to the activity of targeted kinase inhibitors, the ever-changing immune system poses unique challenges to biomarker development. However, it is the adaptability of the immune system that also underlies its vast potential to keep pace with cancer evolution and provide durable treatment responses that are not achievable with most other forms of cancer therapy.
https://www.ncbi.nlm.nih.gov/pmc/articl ... n_sectitle
Mechanism-driven biomarkers to guide immune checkpoint blockade in cancer therapy
What are Biomarkers?
What are Biomarkers?
Abstract
Purpose
This article provides working definitions and a conceptual framework to understand the roles of biomarkers in clinical research.
Conclusion
Biomarkers play a critical role in improving the drug development process as well as in the larger biomedical research enterprise. Understanding the relationship between measurable biological processes and clinical outcomes is vital to expanding our arsenal of treatments for all diseases, and for deepening our understanding of normal, healthy physiology. Since at least the 1980s, the necessity of using biomarkers as surrogate outcomes in large trials of major diseases, such as cancer [10] and heart disease [11], has been widely discussed. The FDA continues to promote the use of biomarkers in basic and clinical research, as well as research on potential new biomarkers to use as surrogates in future trials [12]. However, for all their potential to do good—to speed drug development, to reduce exposure to ineffective experimental treatments, and so on—biomarkers present substantial risks when trial designers confuse them with clinical endpoints.
Biomarkers could only serve as true replacements for clinical relevant endpoints if we completely understood the normal physiology of a biological process, the pathophysiology of that process in the disease state, and effects of an intervention – pharmacological, device, or otherwise – on these processes. Since we rarely if ever have the full picture of those types of processes, since there are always more details we don't know or understand, biomarkers as surrogate endpoints need constant reevaluation. Studies using biomarkers should always have as ultimate measures clinical outcomes, at least for retrospective analysis of biomarker correlation success. Without continual reevaluation of the relationship between surrogate endpoints and true clinical endpoints, we risk again approving whole classes of drugs that either have no additional benefit or, worse, that harm patients.
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3078627/
Abstract
Purpose
This article provides working definitions and a conceptual framework to understand the roles of biomarkers in clinical research.
Conclusion
Biomarkers play a critical role in improving the drug development process as well as in the larger biomedical research enterprise. Understanding the relationship between measurable biological processes and clinical outcomes is vital to expanding our arsenal of treatments for all diseases, and for deepening our understanding of normal, healthy physiology. Since at least the 1980s, the necessity of using biomarkers as surrogate outcomes in large trials of major diseases, such as cancer [10] and heart disease [11], has been widely discussed. The FDA continues to promote the use of biomarkers in basic and clinical research, as well as research on potential new biomarkers to use as surrogates in future trials [12]. However, for all their potential to do good—to speed drug development, to reduce exposure to ineffective experimental treatments, and so on—biomarkers present substantial risks when trial designers confuse them with clinical endpoints.
Biomarkers could only serve as true replacements for clinical relevant endpoints if we completely understood the normal physiology of a biological process, the pathophysiology of that process in the disease state, and effects of an intervention – pharmacological, device, or otherwise – on these processes. Since we rarely if ever have the full picture of those types of processes, since there are always more details we don't know or understand, biomarkers as surrogate endpoints need constant reevaluation. Studies using biomarkers should always have as ultimate measures clinical outcomes, at least for retrospective analysis of biomarker correlation success. Without continual reevaluation of the relationship between surrogate endpoints and true clinical endpoints, we risk again approving whole classes of drugs that either have no additional benefit or, worse, that harm patients.
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3078627/
Debbie
Re: Mechanism-driven biomarkers to guide immune checkpoint blockade in cancer therapy
Love utube. :)
A comprehensive video on what biomarkers are-
NHS sponsored
https://m.youtube.com/watch?v=cT-iUJwEy0E
A comprehensive video on what biomarkers are-
NHS sponsored
https://m.youtube.com/watch?v=cT-iUJwEy0E
Debbie
Secreted Tumor Antigens - Immune Biomarkers for Diagnosis and Therapy.
Abstract
With the advent of immunotherapies for cancer, there is growing interest in the identification of tumor antigens. Tumor antigens are self-molecules altered through e.g. genetic mutations ( neoantigens)
protein truncation, protein misfolding, or abnormal posttranslational modifications. To induce an immune response, tumor antigens need to be secreted into the tumor environment and presented to the immune system in the draining lymph nodes, resulting in the generation of tumor-specific effector cells and antibodies. Cytotoxic T cells are thought to be responsible for killing of tumor cells, and several recent studies have used MS, combined with exome/transcriptome sequencing and bioinformatics, to identify their cognate peptide ligands on tumor MHC class I molecules. Circulating (serum) antibodies have been more widely used to identify tumor antigens in a range of human cancers, using 2D Western blots, immunoaffinity, and microarray technologies. More specific antibody probes have been generated by harvesting antibodies directly from antibody-secreting cells through in vitro cultures of lymph node cells (antibody-secreting cells probes) or B-cell immortalization. Further identification and characterization of tumor antigens is likely to have important implications for cancer diagnostic and biomarker discovery, immune profiling, and the development of cancer vaccines and targeted immunotherapies.
https://www.ncbi.nlm.nih.gov/m/pubmed/28714192/
With the advent of immunotherapies for cancer, there is growing interest in the identification of tumor antigens. Tumor antigens are self-molecules altered through e.g. genetic mutations ( neoantigens)
protein truncation, protein misfolding, or abnormal posttranslational modifications. To induce an immune response, tumor antigens need to be secreted into the tumor environment and presented to the immune system in the draining lymph nodes, resulting in the generation of tumor-specific effector cells and antibodies. Cytotoxic T cells are thought to be responsible for killing of tumor cells, and several recent studies have used MS, combined with exome/transcriptome sequencing and bioinformatics, to identify their cognate peptide ligands on tumor MHC class I molecules. Circulating (serum) antibodies have been more widely used to identify tumor antigens in a range of human cancers, using 2D Western blots, immunoaffinity, and microarray technologies. More specific antibody probes have been generated by harvesting antibodies directly from antibody-secreting cells through in vitro cultures of lymph node cells (antibody-secreting cells probes) or B-cell immortalization. Further identification and characterization of tumor antigens is likely to have important implications for cancer diagnostic and biomarker discovery, immune profiling, and the development of cancer vaccines and targeted immunotherapies.
https://www.ncbi.nlm.nih.gov/m/pubmed/28714192/
Debbie
What are neoantigens ?
“What are neoantigens? Neoantigens are newly formed antigens that have not been previously recognized by the immune system. Neoantigens can arise from altered tumor proteins formed as a result of tumor mutations or from viral proteins.1
How is neoantigenicity measured? The number of neoantigens in a tumor genome can be measured by next-generation sequencing. Neoantigen prediction algorithms have been developed to identify which neoantigens will likely solicit an immune response.1,2
Why are neoantigens important? Tumor antigens may be recognized by the immune system as non-self and elicit an immune response. Tumors with high TMB and/or MSI-H/dMMR may lead to an increase in neoantigens.3-6”
Jussi pointed out the neoantigen possibly of ICIs being successful with ASPS good results-
https://www.cureasps.org/forum/viewtopi ... mmr#p12702
https://www.bms.com/modals/neoantigens.html
How is neoantigenicity measured? The number of neoantigens in a tumor genome can be measured by next-generation sequencing. Neoantigen prediction algorithms have been developed to identify which neoantigens will likely solicit an immune response.1,2
Why are neoantigens important? Tumor antigens may be recognized by the immune system as non-self and elicit an immune response. Tumors with high TMB and/or MSI-H/dMMR may lead to an increase in neoantigens.3-6”
Jussi pointed out the neoantigen possibly of ICIs being successful with ASPS good results-
https://www.cureasps.org/forum/viewtopi ... mmr#p12702
https://www.bms.com/modals/neoantigens.html
Debbie