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Personalized MedicineLung Cancer

Bringing Hope to Patients with Stage IV Non–Small-Cell Lung Cancer

November 2022 – Lung Cancer
Ofer Sharon, MD, MBA
CEO, OncoHost
Binyamina, Israel

Lung cancer, in particular, non–small-cell lung cancer (NSCLC), the most common type of lung cancer, remains the leading cause of cancer-related death in the United States and worldwide. The development of new therapeutic approaches, including targeted therapies and immunotherapies, has led to a significant improvement in the survival and quality of life for patients with NSCLC in the past few years.

However, the clinical benefit of targeted therapies and immunotherapies in lung cancer is still limited to a minority of patients diagnosed with advanced NSCLC.

Although about 20% to 50% of patients with advanced or metastatic NSCLC have strong responses to immunotherapy,1 resulting in prolonged duration of survival, this means that up to half of the patients with advanced lung cancer have no response to any of the immunotherapies currently approved for advanced or metastatic (stage IV) NSCLC, leading to disease progression and death.

Even in patients whose tumor initially responds to treatment, after a certain period the tumor usually stops responding to the treatment and the cancer continues to progress.

Why does this happen, and what are we doing to overcome this problem?

The Biomarker Dilemma

We know that many genetic and genomic biomarkers are associated with NSCLC, and if present, targeted therapies are now available that provide doctors and patients the option to treat the cancer with a therapy that targets a specific actionable biomarker in each patient.

These biomarkers are known as “driver mutations” and include mutations such as EGFR, ALK, KRAS, MET, RET, ROS1, or BRAF, for which targeted therapies have been approved for patients with one of these actionable mutations.

But not all patients with lung cancer have one of those biomarkers. In fact, only about 30% of the patients with NSCLC have a driver mutation,2 and the other 70% do not have this option for treatment and, as such, will not benefit from targeted therapies.

Another type of biomarker in NSCLC is a protein known as PD-1 or PD-L1, which is expressed on cancer cells and immune system cells of different types of cancer, including NSCLC. In lung cancer, the PD-L1 expression is the biomarker used to determine who should be treated with immunotherapy, and who should be treated with a combination of immunotherapy plus chemotherapy.

The PD-L1 biomarker measurement is based on its expression in the tumor tissue and has very limited predictive power, as studies have now shown that even patients with a low PD-L1 expression may respond to PD-1 or PD-L1 inhibitors.

In patients with stage IV (metastatic) NSCLC, oncologists have no time to waste, because the disease keeps progressing, and starting with the correct treatment is crucial. Oncologists are faced with the difficult decision of selecting the best appropriate treatment for the individual patient, which can significantly influence the patient’s chance of survival.

The selected treatment is generally based on the current standard-of-care guidelines and the results of the molecular testing that is done before starting therapy. However, we know that these guidelines take a “one-size-fits-all” approach, and we also understand today that patients don’t fall under the “one-size-fits-all” umbrella, but rather require an individualized approach to therapy.

Can We Identify Who Will Benefit from Which Therapy?

If we can discover biomarkers that could guide us in administering the right treatment and predict how each individual patient may respond to that treatment, oncologists could finally make informed decisions based on the patient’s and the tumor’s biology, instead of depending solely on the generalized standard-of-care protocols.

Currently, hundreds of clinical trials are researching varied combinations of treatments for lung cancer. If even just a small percentage of these clinical trials are successful, doctors may have the choice of between 10 and 15 new combinations of first-line treatments within just a few years.

But, to choose correctly, we urgently need appropriate biomarkers to support the clinical decision-making and to help us identify the best treatment option for the individual patient.

How Are We Overcoming This Dilemma?

There is a growing understanding that the search for biomarkers will not end with the silver bullet approach, namely, the one biomarker for all tumor types and all treatment types. Cancer biology is complex and requires a deeper understanding of the interplay between the tumor, the patient, and the therapy.

Companies are attempting to combine several types of biomarkers, bringing together genomics, proteomics, the immune system, and the microbiome to provide a deeper understanding of disease dynamics, and what type of treatment an individual patient should receive.

We now know that the patient’s biological response plays a critical role in determining the response to, and the mechanism of resistance to, therapy, forcing us to consider the therapy-tumor-patient interaction. But how do we get an inside look into the structure and mechanisms of the biological processes in the patient?

Although DNA and RNA analyses have been the basis of recent biomarker discovery, it is proteins that provide us with an overall picture of the fierce fight that is taking place inside the patient’s body. Proteins give us deep insight into the complex interplay between the patient, the tumor, and the treatment, increasing the odds of identifying a clinically meaningful biomarker.

Improving Personalized Medicine

Using protein analysis technology, OncoHost (https://oncohost.com)—a company that is focused on improving personalized medicine in oncology—has identified proteomic patterns, which identify proteins that are overexpressed in the blood of patients with NSCLC and are involved in resistance to therapy.

Identifying these patterns allows for prediction of treatment response and provides us with important clinical insights into the active tumor resistance pathways. At last, we have a blueprint to understanding individual response to therapy, which allows us to truly personalize each patient’s treatment plan.

Deciphering this complex interaction between the therapy and the tumor requires an analysis of thousands of features (not an easy feat), using artificial intelligence and machine-learning technologies. These technologies allow us to assess multidimensional clinical and biological data in a broad range of proteins to measure, monitor, and ultimately improve lung cancer outcomes successfully for the patient.

Our focus at OncoHost is to ensure that your oncologists can select your treatment plan based on your personal biology, which we believe is true personalization of therapy. The chances of a patient’s response to treatment have been vastly improved through a deeper level of personalization.3

Using proteomic analysis to guide our research and clinical trials, we were able to identify whether a patient should be treated with immunotherapy alone, or with immunotherapy combined with chemotherapy.3,4

This is a significant achievement for patients. Why? On the one hand, we want to achieve the best response we can possibly get for the patient. On the other hand, we don’t want to give the patient unnecessary therapies, especially not chemotherapy, which results in increased, and often serious, side effects.

Therefore, having access to a technology that can give actual clinical insight into how each patient should be treated is truly a game changer.

Proteomic profiling is the catalyst in precise, individualized treatment planning. It is allowing us to make educated decisions and improve every patient’s chance of survival. With this new approach, we are replacing the “umbrella approach” to treating patients with NSCLC with an approach that is based on a more precise and better-educated decision-making process.

It is time we start implementing this approach that can change the future for patients with lung cancer.

What Should I Ask My Doctor?

For patients with lung cancer, it is important to consider the current advancements in cancer care, specifically within the area of precision (or personalized) medicine. Precision medicine is a way for healthcare providers to offer and plan specific care for each patient, based on the particular genes, proteins, and other substances in your body.

Precision medicine in oncology often means looking at how changes in certain genes or proteins in your cancer cells may affect your care, such as your treatment options. As mentioned above, it allows us to take a deeper look at the interaction between your tumor, your treatment, and your personal biology.

The progress in personalized medicine provides the physician and you, the patient, with the tools that allow you to play an active role in your cancer journey and treatment plan. That is what personalized medicine is truly about.

Be sure to ask your doctor about the tests that are available for various cancer types and stages, and how they best fit your diagnosis and treatment plan. When obtaining the whole picture during the treatment-planning stage, your oncologist is better equipped to make the right decision. Together, we are revolutionizing precision oncology and the goal of improving the future of our patients with lung cancer.

References

  1. Bezerra De Mello RA, Voscaboinik R, Pires Luciano JV, et al. Immunotherapy in patients with advanced non-small cell lung cancer lacking driver mutations and future perspectives. Cancers. 2021;14(1):122. www.mdpi.com/2072-6694/14/1/122.
  2. Chevallier M, Borgeaud M, Addeo A, Friedlaender A. Oncogenic driver mutations in non-small cell lung cancer: past, present and future. World Journal of Clinical Oncology. 2021;12(4):217-237. www.wjgnet.com/2218-4333/full/v12/i4/217.htm.
  3. Harel M, Lahav C, Jacob E, et al. Longitudinal plasma proteomic profiling of patients with non-small cell lung cancer undergoing immune checkpoint blockade. Journal for Immuno Therapy of Cancer. 2022;10(6):e004582. https://jitc.bmj.com/content/10/6/e004582.
  4. Predicting Responsiveness in Oncology Patients Based on Host Response Evaluation During Anti-Cancer Treatments (PROPHETIC). NLM identifier: NCT04056247. Updated April 19, 2022. https://clinicaltrials.gov/ct2/show/NCT04056247.

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Last modified: November 16, 2022

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