Personalized key unlocking cancer resistance pathways in lung

Cracking Cancer Resistance: How New Research is Personalizing Lung Cancer Treatment

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Rhea Morgan in Health & Wellness December 2025 • 5 min read.

"Unveiling the complexities of drug resistance in lung cancer, and how personalized approaches using advanced proteomics are paving the way for more effective therapies."


Lung cancer remains a leading cause of cancer-related deaths worldwide, with non-small cell lung cancer (NSCLC) being the most common type. While treatments targeting the epidermal growth factor receptor (EGFR) have shown initial success, resistance to these therapies inevitably emerges, limiting long-term survival. This resistance is a complex puzzle, driven by various mechanisms that allow cancer cells to bypass the intended effects of the drugs.

Traditional research approaches often focus on identifying common resistance pathways, potentially overlooking the unique adaptations that occur in individual tumors. This 'one-size-fits-all' approach may explain why some treatments succeed while others fail, even among patients with seemingly similar cancer profiles.

Now, groundbreaking research is shifting the focus towards personalized strategies that account for the individual characteristics of each tumor. By employing advanced proteomic techniques, scientists are mapping the intricate signaling networks within resistant tumors, revealing both shared and unique mechanisms that drive treatment failure. This deeper understanding is paving the way for more tailored and effective therapies.

Decoding Tumor Resistance: A Personalized Approach

Personalized key unlocking cancer resistance pathways in lung

Researchers at Massachusetts Institute of Technology delved into the mechanisms of resistance to two promising NSCLC treatments: osimertinib, a third-generation EGFR inhibitor, and JNJ-61186372, an EGFR/Met bispecific antibody. Their goal was to identify the molecular changes that enable cancer cells to survive and thrive despite these targeted therapies.

The team established four NSCLC xenograft models, each representing different EGFR mutation profiles and Met pathway activation levels, mirroring the diverse landscape of clinical NSCLC cases. These models were then treated with osimertinib or JNJ-61186372, and the resulting resistant tumors were analyzed using quantitative mass spectrometry-based proteomics. This powerful technique allowed them to map the phosphotyrosine signaling pathways within the tumors, providing a detailed snapshot of the active signaling networks.

  • Uncovering Unique Resistance Patterns: The proteomic analysis revealed a surprising degree of heterogeneity among the resistant tumors. While some common resistance mechanisms were observed, each tumor also displayed a unique signaling profile, indicating that cancer cells can adapt to treatment in a variety of ways.
  • The Role of Met and Bypass Signaling: In some resistant tumors, the Met pathway was found to be upregulated, suggesting that activation of this alternative signaling route can bypass EGFR inhibition and promote continued growth. Other tumors exhibited increased phosphorylation of EGFR and/or ErbB family members, indicating plasticity within these receptor tyrosine kinases (RTKs).
  • Downregulation of EGFR and SFK Signaling: Despite the emergence of resistance, the researchers found that both EGFR and Src family kinase (SFK) signaling networks were generally downregulated in resistant tumors. This seemingly paradoxical finding suggests that cancer cells can survive even when their primary growth pathways are inhibited, highlighting the adaptability of these cells.
Importantly, the researchers discovered that combining EGFR inhibition with SFK inhibition could enhance cell killing in vitro. This finding suggests that residual SFK signaling may contribute to therapeutic resistance and that targeting this pathway in combination with EGFR inhibitors could delay or overcome resistance.

The Future of Lung Cancer Treatment: Personalized Strategies and Combination Therapies

This research underscores the need for personalized approaches to lung cancer treatment. By identifying the unique resistance mechanisms that drive tumor growth in individual patients, clinicians can tailor therapies to target the specific vulnerabilities of each cancer.

The study also highlights the potential of combination therapies. By simultaneously inhibiting multiple signaling pathways, such as EGFR and SFK, it may be possible to overcome resistance and achieve more durable responses.

While further research is needed to translate these findings into clinical practice, this study represents a significant step towards a future where lung cancer treatment is more effective and personalized.

About this Article -

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Everything You Need To Know

1

Why do lung cancer treatments sometimes stop working, and what's being done to address this resistance?

Resistance to lung cancer treatments like EGFR inhibitors occurs because cancer cells adapt through various mechanisms, bypassing the intended drug effects. Traditional research often focuses on common pathways, but personalized strategies using advanced proteomics aim to identify the unique adaptations in individual tumors. By mapping signaling networks, researchers can reveal both shared and unique resistance mechanisms, paving the way for more tailored therapies. This shift acknowledges that a 'one-size-fits-all' approach might not work due to the diverse nature of tumor resistance.

2

How did researchers at MIT study resistance to lung cancer drugs like osimertinib and JNJ-61186372?

Researchers at MIT used NSCLC xenograft models with different EGFR mutation profiles and Met pathway activation levels to study resistance to osimertinib and JNJ-61186372. They treated these models with the drugs and then analyzed the resistant tumors using quantitative mass spectrometry-based proteomics. This technique allowed them to map the phosphotyrosine signaling pathways within the tumors, giving them a detailed look at the active signaling networks. By understanding these pathways, they could identify how cancer cells survive despite targeted therapies.

3

What did proteomic analysis reveal about the different ways lung tumors become resistant to treatment?

Proteomic analysis of resistant tumors revealed significant heterogeneity, with each tumor displaying a unique signaling profile alongside some common resistance mechanisms. The Met pathway was often upregulated, suggesting it can bypass EGFR inhibition. Increased phosphorylation of EGFR and ErbB family members also indicated plasticity within receptor tyrosine kinases (RTKs). Paradoxically, EGFR and Src family kinase (SFK) signaling were generally downregulated, showing cancer cells can survive even when primary growth pathways are inhibited. This adaptability emphasizes the complexity of lung cancer resistance.

4

Why is combining EGFR inhibition with SFK inhibition a promising strategy for lung cancer treatment?

The finding that combining EGFR inhibition with SFK inhibition could enhance cell killing in vitro suggests that residual SFK signaling contributes to therapeutic resistance. Targeting the SFK pathway alongside EGFR inhibitors could delay or overcome resistance. This combined approach highlights the potential of personalized strategies to address the unique vulnerabilities of individual tumors, ultimately improving treatment outcomes for lung cancer patients. Future research will likely focus on identifying specific SFK inhibitors that are most effective in combination with EGFR inhibitors for different NSCLC subtypes.

5

What are personalized approaches to lung cancer treatment, and how might they improve patient outcomes?

Personalized approaches to lung cancer treatment involve identifying the unique resistance mechanisms driving tumor growth in individual patients. Clinicians can then tailor therapies to target the specific vulnerabilities of each cancer. This strategy requires advanced diagnostic techniques like proteomics to map tumor signaling networks and understand the specific adaptations that enable resistance. By moving away from a 'one-size-fits-all' approach and towards personalized combination therapies, there is hope for significantly improving outcomes in lung cancer treatment, especially for those with non-small cell lung cancer (NSCLC).

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