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The Cancer Diagnosis Paradox

Precision oncology has transformed cancer care, marking significant changes over the past two decades in the way cancer patients are diagnosed and treated. This shift is characterized by a departure from the traditional “one-size-fits-all” approach to an increasing emphasis on precision and personalized medicine. This transformation is rooted in genomic and cancer biology and enables a more tailored treatment plan for each individual patient.

Molecular pathology has become a pivotal cornerstone in the diagnosis path of cancer patients by providing information on tumor diagnosis and driving the therapeutic decision in daily practice. With a growing number of actionable genomic targets and FDA-approved targeted treatments in clinical guidelines, cancer treatment decisions are increasingly made based on genomic information. This has created a growing need to identify multiple gene alterations for an accurate molecular diagnosis of cancer.

In 2022, more than 1.9 million Americans will be diagnosed with cancer, according to an American Cancer Society estimate. In 2020, the most recent year for which The World Cancer Research Fund International has statistics, more than 18 million people worldwide received a new cancer diagnosis. So, if the need and demand are definitely there, where is the paradox?

Time And Tissue

Next-Generation Sequencing (NGS) enables a comprehensive analysis of multiple genomic alterations with therapeutic implications and has increasingly substituted conventional techniques such as single-gene testing. Naturally, there has been an increasing uptick in NGS testing to cover multiple biomarkers at once.

Time is one of the key factors when facing cancer: The common turnaround time for NGS is around two to six weeks (sometimes even longer in a community setting). Furthermore, bureaucracy and reimbursement processes play a key role in timing, as well. Based on current guidelines, molecular cancer diagnosis is not routinely covered for all cancer patients; some of them need to undergo a long approval process and tumor type confirmation, which is required for NGS reimbursement approval. The sad part is that in some tumor types, like lung, 10% to 25% of patients will not survive within 1 to 3 months and will not be able to benefit from NGS testing.

But it’s not only time; “tissue is the issue” became a commonplace phrase among physicians discussing biomarker and NGS profiling. Of all tumor tissue samples tested, 10% to 20% fail to meet minimum tissue quantity or quality requirements for standard NGS testing. Moreover, the NGS molecular report is very complex to interpret. Results from a nationally representative survey of oncologists in the United States indicated that more than 75% of oncologists reported using NGS tests to guide patient care and treatment recommendations. However, the study also indicates that 50% of oncologists reported that the NGS test results are frequently ambiguous, present challenges and are difficult to interpret.

These facts present what we call “The Cancer Diagnosis Paradox”: a growing demand for timely and accurate molecular cancer diagnosis facing the complexity, limitations and long turnaround time of current methods.

Solving The Paradox

Although cancer diagnosis understanding is advancing, it is still very complex, with many possible routes to take and decisions to make. One way to face the cancer diagnosis paradox is by developing more methodologies to empower physicians with tools to help navigate the complicated diagnosis process in the most optimal way. Here are three primary methods in use today.

• Liquid Biopsy

One of the technologies that was developed since the early 2000s in order to face the tissue and time limitations is plasma-based NGS (liquid biopsy). This test builds on the phenomenon that fragments of DNA are shed from the tumor into the bloodstream and can be sequenced to detect genomic alterations. The advantages of liquid biopsy in lung cancer mainly derive from its minimally invasive nature of sample collection and the shorter turnaround time, which stands around seven to 10 days. However, when profiling tumor genomics with treatment intentions that require high accuracy levels, the promise in liquid biopsy meets significant barriers, with studies demonstrating an average of 67.8% sensitivities in the clinical practice.


Additionally, there are rapid solutions available, including RT-PCR or FISH. These tests are designed to detect a single genomic alteration at a time, so multiple single-gene tests are required in order to identify the correct alteration. Although these tests are fairly fast, when the frequency of the majority of genomic alterations in NSCLC is typically at 1% to 11%, testing each gene separately may increase waste and burden unless a method that uses no tissue and carries negligible cost and time can flag the likelihood of gene alteration per each case.

• AI-Based Molecular Profiling

For the initial cancer diagnosis, digital pathology labs produce a scanned image of the biopsy H&E slide (WSI). Advanced deep-learning algorithms leverage this existing digital image to identify and profile genomic biomarkers. These algorithms do not need any additional dedicated tissue or time; in fact, one digitized biopsy image—the diagnostic slide that was originally prepared—is all that is needed for an immediate gene alteration identification.

AI-based molecular profiling model validations have already reached high accuracy levels, and the number of biomarkers that can be detected is growing rapidly. The challenge for these technologies is to “translate” these models to clinical use with Real World Evidence research using data that is routinely collected from cancer patients. By opening the doors to more prospective research and real use in clinical settings, healthcare professionals will be exposed in real time to the crucial molecular data they need.

Every year, millions upon millions of people and their families endure the molecular analysis process resulting in the “Cancer Diagnosis Paradox.” Technology can help by providing molecular profiling and gene alterations detection that is highly accurate, fast and, most of all, scalable and available to all patients so that doctors will have the information they need on the spot and no patient will have to wait such a long time for cancer diagnosis and personalized treatment.

Cancer presents us with complex challenges and raises the bar. We should do the same by adopting advanced solutions and new methodologies and technologies as they become viable.

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