Imagine a world where lung cancer treatment isn’t just about targeting genetic mutations, but about understanding the intricate dance of proteins and leveraging the power of artificial intelligence. That future is rapidly becoming a reality, transforming how we approach non-small cell lung cancer (NSCLC). But here’s the catch: this revolution demands that we rethink how we test and interpret biomarkers.
Dr. Soo-Ryum (Stewart) Yang, a leading pathologist at Memorial Sloan Kettering Cancer Center, shed light on these groundbreaking advancements at the 20th Annual New York Lung Cancers Symposium®. His presentation (held on November 15, 2025) highlighted the surge of protein-based biomarkers, the increasing actionability of tumor suppressor genes, and the dawn of computational pathology – all crucial elements in the next generation of personalized therapies for NSCLC. Let’s dive into the key takeaways from his talk.
The Rise of Protein Biomarkers: More Than Just Genes
For years, genetic mutations have been the cornerstone of targeted therapies in NSCLC. But what if we could also target the proteins expressed by those genes? This is where protein biomarkers, specifically measured using immunohistochemistry (IHC), come into play. Instead of only focusing on the presence of a mutated gene, pathologists are now measuring the intensity of protein expression on the surface of cancer cells. This opens new avenues for treatment, especially with antibody-drug conjugates (ADCs).
Dr. Yang pinpointed two “must-test” protein biomarkers: HER2 and c-MET. Now, here’s where it gets controversial… While HER2 mutations are well-known, HER2 overexpression (high levels of the HER2 protein) can occur independently of mutations. In fact, up to 20% of NSCLC patients exhibit HER2 overexpression, with the highest level (IHC 3+) seen in up to 3%. Dr. Yang emphasized that high-level gene amplification usually translates to IHC 3+ staining, but the reverse isn’t always true – not all 3+ cases are driven by amplification.
This distinction is critical because the ADC fam-trastuzumab deruxtecan-nxki (T-DXd; Enhertu) has received accelerated approval for HER2-positive (IHC 3+) solid tumors, including pre-treated NSCLC, based on the DESTINY-Lung01 trial. This approval is based on HER2 scoring guidelines initially developed for gastric cancer, which Dr. Yang suggests should now be adopted for NSCLC testing. It’s a subtle shift, but one that could dramatically impact patient access to this life-extending therapy.
Similarly, c-MET overexpression is common in NSCLC, with an actionable c-MET–high status (defined as over 50% of tumor cells with 3+ staining) found in up to 17% of EGFR wild-type cases. Just like HER2, c-MET overexpression is distinct from MET exon 14 skipping mutations and MET amplification.
Telisotuzumab vedotin-tllv (teliso-V; Emrelis) received accelerated FDA approval in May 2025 for this patient population, based on the LUMINOSITY trial. This further solidifies the importance of c-MET IHC testing. But this begs the question: How do we efficiently integrate HER2 and c-MET IHC screening into existing diagnostic workflows?
Dr. Yang proposes two main strategies:
- Upfront Reflex Testing: Automatically order HER2 and c-MET IHC testing on the initial diagnostic sample alongside NGS and other IHC tests.
- Testing at Progression: Order the tests upon disease progression, either on a new biopsy or an archived sample, aligning with their current approval in the second-line setting.
He acknowledges that there’s no one-size-fits-all solution and advocates for a flexible approach with standardized options, allowing institutions to tailor workflows based on their resources and multidisciplinary expertise. What do you think? Which approach makes the most sense for your practice?
Emerging Biomarkers: The Next Wave of Personalized Medicine
Beyond HER2 and c-MET, several other biomarkers are showing promise in NSCLC. These include:
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KRAS Mutations: These mutations occur in up to 40% of lung adenocarcinomas, with G12C being the most common. While KRAS G12C-specific therapies are available, Dr. Yang highlighted the challenges posed by KRAS G12D mutations, which are associated with poorer response to chemoimmunotherapy. The good news? New inhibitors targeting KRAS G12D, like zoldonrasib (RMC-9805), and multi-RAS inhibitors, like daraxonrasib (RMC-6236), are showing encouraging results in clinical trials. The best part is that KRAS mutations are easily detected by existing NGS and PCR technologies.
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STK11 and KEAP1 Mutations: These tumor suppressor genes, mutated in up to 20% of lung cancers, are often co-mutated with KRAS and promote an immunosuppressive tumor microenvironment, leading to resistance to immunotherapy. And this is the part most people miss… The POSEIDON trial suggests that adding a CTLA-4 inhibitor (tremelimumab) to a PD-L1 inhibitor (durvalumab) and chemotherapy can overcome this resistance. This positions STK11/KEAP1 mutations as biomarkers for escalating checkpoint therapy, requiring broad-panel NGS for detection.
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MTAP Deletions and Synthetic Lethality: MTAP deletions, occurring in up to 18% of lung cancers, impair the purine salvage pathway, creating a metabolic vulnerability that can be exploited through synthetic lethality. Inhibiting PRMT5 or MAT2a in MTAP-deleted cells can selectively kill cancer cells. Dr. Yang proposes a diagnostic workflow using NGS for initial screening, followed by confirmatory IHC in borderline or low-purity samples.
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TROP2 and Computational Pathology: TROP2, a cell surface protein widely expressed in NSCLC, is a target for ADCs like datopotamab deruxtecan-dlnk (Dato-DXd; Datroway). While the TROPION-Lung01 study showed a PFS benefit with Dato-DXd, it didn’t enrich for a biomarker, as previous studies found no correlation between TROP2 expression and response. But here’s the twist: researchers are using AI-driven computational pathology to generate a TROP2 quantitative continuous score (QCS) or normalized membrane ratio (NMR) from IHC slides. This score, when applied retrospectively to TROPION-Lung01, was predictive of response. However, Dr. Yang rightly points out that this requires prospective validation and raises concerns about accessibility, as it’s currently tied to a specific digital pathology ecosystem. Is this the future of biomarker analysis, or a proprietary hurdle?
The Future of Personalized Medicine: A Holistic Approach
Dr. Yang concluded by emphasizing that the future of NSCLC management lies in a holistic approach that integrates protein analysis, AI-driven insights, and novel therapeutic strategies. He envisions a future where broad-panel NGS and IHC, along with AI, are the cornerstones of comprehensive biomarker testing.
But a crucial challenge remains: tissue scarcity. As Dr. Yang aptly stated, “Despite this progress, I think tissue will still be the issue. We have the same small biopsy, and we’re required to [test for] an expanding list of biomarkers that may require additional separate tissues.” The development and implementation of multiplex IHC and the integration of broad panel NGS, IHC, and AI are crucial for delivering the next generation of personalized therapies to a larger segment of the NSCLC patient population.
What are your thoughts on these advancements? Do you agree with Dr. Yang’s assessment of the challenges and opportunities? How can we best address the issue of tissue scarcity to ensure all patients have access to comprehensive biomarker testing? Share your insights in the comments below!