Coexistence of three EGFR mutations in an NSCLC patient: A brief report

Francesca Belardinilli1, Angela Gradilone1, Alain Gelibter2

  • 11 Dipartimento di Medicina Molecolare, Sapienza Università di Roma, Roma, Italia.

Abstract

Insights

This study reports a non-small cell lung cancer (NSCLC) patient with three coexisting epidermal growth factor receptor (EGFR) gene mutations, including two on the same allele. This complex mutation pattern highlights the need for advanced detection methods for improved lung cancer risk assessment.

Area of Science:

  • Oncology
  • Genetics
  • Molecular Biology

Background:

  • Epidermal growth factor receptor (EGFR) is a key target for tyrosine kinase inhibitors in non-small cell lung cancer (NSCLC).
  • EGFR mutations are crucial for targeted therapy in NSCLC patients.
  • Multiple EGFR mutations on the same allele are challenging to detect and analyze.

Purpose of the Study:

  • To investigate the presence of EGFR gene mutations in an advanced NSCLC patient.
  • To analyze complex EGFR mutation patterns, including multiple mutations on a single allele.
  • To evaluate the clinical implications of complex EGFR mutations in NSCLC.

Main Methods:

  • Sanger sequencing and Ion Torrent sequencing were employed to detect EGFR mutations in tumor tissue.
  • Sanger sequencing was used to analyze EGFR mutations in peripheral blood lymphocytes.
  • Clinical data and treatment response were assessed for the NSCLC patient.

Main Results:

  • Three coexisting mutations in the EGFR gene were identified in the NSCLC patient.
  • Two of the EGFR mutations were located on exon 21 and present on the same allele.
  • The third EGFR mutation was found on exon 20, and the patient showed clinical benefit from afatinib treatment.

Conclusions:

  • This case highlights an NSCLC patient with a rare pattern of three coexisting EGFR mutations, two on the same allele.
  • Such complex mutation profiles may indicate a genetic predisposition to cancer in offspring.
  • Future screening guidelines may benefit from improved risk calculation for lung cancer susceptibility, considering complex EGFR mutation patterns.

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