Overcoming resistance to EGFR monotherapy in HNSCC by identification and inhibition of individualized cancer processes

Maria R. Jubran, Daniela Vilenski, Efrat Flashner-Abramson, Efraim Shnaider, Swetha Vasudevan, Ariel M. Rubinstein, Amichay Meirovitz, Shay Sharon, David Polak*, Nataly Kravchenko-Balasha*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

4 Scopus citations


Therapeutic strategies for advanced head and neck squamous carcinoma (HNSCC) consist of multimodal treatment, including Epidermal Growth Factor Receptor (EGFR) inhibition, immune-checkpoint inhibition, and radio (chemo) therapy. Although over 90% of HNSCC tumors overexpress EGFR, attempts to replace cytotoxic treatments with anti-EGFR agents have failed due to alternative signaling pathways and inter-tumor heterogeneity. Methods: Using protein expression data obtained from hundreds of HNSCC tissues and cell lines we compute individualized signaling signatures using an information-theoretic approach. The approach maps each HNSCC malignancy according to the protein-protein network reorganization in every tumor. We show that each patient-specific signaling signature (PaSSS) includes several distinct altered signaling subnetworks. Based on the resolved PaSSSs we design personalized drug combinations. Results: We show that simultaneous targeting of central hub proteins from each altered subnetwork is essential to selectively enhance the response of HNSCC tumors to anti-EGFR therapy and inhibit tumor growth. Furthermore, we demonstrate that the PaSSS-based drug combinations lead to induced expression of T cell markers and IFN-γ secretion, pointing to higher efficiency of the immune response. Conclusion: The PaSSS-based approach advances our understanding of how individualized therapies should be tailored to HNSCC tumors.

Original languageAmerican English
Pages (from-to)1204-1219
Number of pages16
Issue number3
StatePublished - 2022

Bibliographical note

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  • Head and neck squamous cell carcinoma
  • Information-theoretic approach
  • Patient-specific signaling signatures
  • Precision medicine
  • Targeted therapy


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