A Multicomponent Biomarker Approach Will Shift Cancer Care

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For many years we have been working towards creating a paradigm shift in cancer care, and precision oncology is rapidly evolving, with the potential to revolutionize our current standards and guidelines. But while we have made giant strides in our understanding of the disease, the current approach to biomarker development is still simplistic and fragmented, limiting our ability to understand the underlying biology of the patient’s cancer, tailor treatment to individual patients, monitor treatment response, detect early signs of relapse, and identify potential new targets for therapy. True precision oncology requires a comprehensive and integrated approach to biomarker development to really make a dent.

Currently, the development of biomarkers is carried out in isolation, focusing on a single technology or approach, without collaboration among researchers, clinicians, and industry partners. This results in individual biomarkers being developed with no consideration of their potential interaction with other biomarkers or therapies – an inadequate tactic that limits the potential of precision oncology to truly improve patient outcomes.

Furthermore, the development of biomarkers is often carried out using small, homogeneous patient groups, which does not reflect the complexity and heterogeneity of real-world patient populations. This limits the generalizability of biomarker results and may not accurately predict treatment response in a broader patient population. As a result, patients are not receiving the personalized care that they need and deserve.

Cancer is a complex disease driven by multiple biological pathways, and to fully understand the underlying biology of a patient’s cancer and identify potential mechanisms of resistance, a change in our approach to biomarker development is needed.

OncoHost’s PROphet® Test provides clinicians with actionable clinical insights into optimal first-line therapeutic choices, and a better understanding of their patients’ personalized cancer dynamics. Requiring just one pre-treatment blood test, PROphet® scans approximately 7,000 proteins in a patient’s blood plasma and delivers a report that predicts their clinical benefit from anti-PD-1/PD-L1 immunotherapy-based treatment plans. The PROphet® algorithm is trained on OncoHost’s large-scale clinical trial, PROPHETIC. To date, the trial has over 1,500 patients recruited across 40 sites worldwide, making it one of the largest prospective cohorts in the precision oncology field. The PROphet® test is supported by a blinded validation demonstrating that it accurately predicts a patient’s clinical benefit and associated overall survival differences with single-agent versus combination treatment plans.

Integrating multi-component biomarkers into clinical workflows

Cancer is a complex, whole-body disease that involves multiple abnormalities in the levels of DNA, RNA, protein, metabolite, and microbiome. Biological omics, including genomics, transcriptomics, proteomics, metabolomics and radiomics, aim to systematically understand cancer cell transformation at different biological levels. Multi-component biomarkers have the potential to play a crucial role in precision oncology, and this is the key to driving the shift of our cancer research paradigm.

A multi-component biomarker approach involves the use of various biomarkers to create a more comprehensive profile of a patient’s cancer. This allows for more accurate diagnosis, treatment selection, and monitoring of the disease. By using a combination of biomarkers, we can better understand the underlying biology of a patient’s cancer, which in turn can inform treatment decisions and improve outcomes.

The benefits of multi-component biomarkers in cancer care and research have been extensively documented in literature. For example, a Nature Medicine study found that a multi-omics approach can identify different subtypes of breast cancer with distinct responses to therapy. [1] Multi-component biomarkers can also be used to monitor treatment response and detect early signs of relapse, and regular measurement of a combination of biomarkers can help physicians track changes in a patient’s cancer and adjust treatment accordingly. For example, a study published in Clinical Cancer Research found that monitoring a panel of biomarkers in prostate cancer patients can predict treatment response and improve survival outcomes.[2]

In addition, multi-component biomarkers can be used to identify potential new targets for therapy. By analyzing the molecular profiles of tumors, researchers can identify key pathways and targets that may be susceptible to therapy, which can help to identify new therapeutic options for patients with resistant disease. A study published in the Journal of Clinical Oncology highlighted this point by finding that the use of multi-gene biomarker panels improved the accuracy of predicting recurrence in patients with early-stage breast cancer. [3]

Despite the clear benefits of multi-component biomarkers, the integration of these into clinical workflows has been slow. One of the primary reasons for this is the current design of clinical trials, which are mostly focused on the development of single biomarkers. While this may be useful in some cases, it is not sufficient for most patients, who often have complex and heterogeneous tumors.

The current approach to biomarker development simply overlooks the importance of integrating multiple biomarkers into a comprehensive profile, and this needs to change.

Collaboration = Success

The importance of collaboration in the precision oncology industry cannot be overstated. Collaboration allows for the pooling of resources, knowledge, and expertise, which can lead to unimaginable advances in the field of cancer care.

Many companies may have excellent technological solutions that have great value for some patients and clinicians in some clinical situations, but none has the perfect biomarker. This is why collaboration, co-development, and licensing agreements are crucial in the precision oncology industry. Imagine a biomarker company that has a full pipeline of technologies, including multiple solutions for different indications and stages of cancer. Each technology could be a separate business unit or part of a ‘multi-omics’ super biomarker platform. Joint clinical trials, teams, and data science capabilities, combined with the risk reduction of clinical development plans and the ability to demonstrate a clear value proposition across the continuum of the disease, can massively save resources.

At OncoHost, we believe that the integration of multi-component biomarkers into clinical workflows is the key to unlocking the full potential of precision oncology. We are committed to collaborating with other companies in the industry to create the comprehensive and integrated approach to biomarker development so desperately needed. By doing so, we can provide patients with the personalized care that they deserve and improve outcomes for those living with cancer.

We recently announced a multi-year research collaboration with the Baylor Scott & White (BSW) Research Institute, the research arm of Baylor Scott & White Health and the Translational Genomics Research Institute (TGen), part of City of Hope, a nonprofit biomedical research center.

This novel study will utilize BSW’s Texas Immuno-Oncology Biorepository (TIOB)—which collects, catalogs and stores samples of biological material for cancer research—to analyze resistance mechanisms in cancer using multi-omics tools. These will include plasma and tumor proteomics, transcriptomics, and genomics, cell-free DNA, immunoprofiling and microbiome analysis combined with bioinformatics and machine learning tools. A comprehensive analysis will be conducted on lung cancer patients at various stages of the disease, analyzing elements such as the host response, the patient’s microbiome communication with the immune system, tumor profiling, and immune system activity. Testing will involve analysis of blood, stool, and tissue, with the study including some 350 patients who will receive follow-ups for up to five years.

This is one of the most comprehensive profiling processes ever done for cancer patients to date. The long-term study will provide an extensive assessment of cancer dynamics and a multi-system understanding of response to treatment. We are working towards gaining a better understanding of patient response and, ultimately, improved overall survival for patients with advanced cancer.

Let’s unlock the full potential of precision oncology – together

We have learned that integrating multi-component biomarkers into clinical workflows and collaborating with other companies in the industry can create a paradigm shift in the way cancer care is managed. The potential benefits of this approach are enormous, and we are excited to be at the forefront of this vital innovation.

Developing multi-component biomarkers is crucial for the advancement of precision oncology. Clinicians will finally be able to understand the underlying biology of the patient’s cancer, tailor treatment to individual patients, monitor treatment response, detect early signs of relapse, and identify likely new targets for therapy.

This is the key to unlocking the full potential of precision oncology, and the time is now.

Clinical trial

Predicting Responsiveness in Oncology Patients Based on Host Response Evaluation During Anti-Cancer Treatments (PROPHETIC) – NCT04056247

Reference

[1] Su Y, Ko ME, Cheng H, Zhu R, Xue M, Wang J, Lee JW, Frankiw L, Xu A, Wong S, Robert L, Takata K, Yuan D, Lu Y, Huang S, Ribas A, Levine R, Nolan GP, Wei W, Plevritis SK, Li G, Baltimore D, Heath JR. Multi-omic single-cell snapshots reveal multiple independent trajectories to drug tolerance in a melanoma cell line. Nat Commun. 2020 May 11;11(1):2345. doi: 10.1038/s41467-020-15956-9. PMID: 32393797; PMCID: PMC7214418[2] Ross AE, Feng FY, Ghadessi M, Erho N, Crisan A, Buerki C, Sundi D, Mitra AP, Vergara IA, Thompson DJ, Triche TJ, Davicioni E, Bergstralh EJ, Jenkins RB, Karnes RJ, Schaeffer EM. A genomic classifier predicting metastatic disease progression in men with biochemical recurrence after prostatectomy. Prostate Cancer Prostatic Dis. 2014 Mar;17(1):64-9. doi: 10.1038/pcan.2013.49. Epub 2013 Oct 22. PMID: 24145624; PMCID: PMC4332821.[3] Sinn P, Aulmann S, Wirtz R, Schott S, Marmé F, Varga Z, Lebeau A, Kreipe H, Schneeweiss A. Multigene Assays for Classification, Prognosis, and Prediction in Breast Cancer: a Critical Review on the Background and Clinical Utility. Geburtshilfe Frauenheilkd. 2013 Sep;73(9):932-940. doi: 10.1055/s-0033-1350831. PMID: 24771945; PMCID: PMC3859151.