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. 2022 Sep 29:12:910117.
doi: 10.3389/fonc.2022.910117. eCollection 2022.

Genomic landscape of lung cancer in the young

Rossana Ruiz  1 , Marco Galvez-Nino  1 , Katia Roque  1 , Jaime Montes  1 , Maria Nuñez  1 , Luis Raez  2 , Sergio Sánchez-Gambetta  3 , Sandra Jaúregui  3 , Sandra Viale  3 , Edward S Smith  3 , Joseph A Pinto  4   5 , Luis Mas  1
Affiliations

Genomic landscape of lung cancer in the young

Rossana Ruiz et al. Front Oncol. .

Abstract

Background: Lung cancer in the young is a rare entity of great interest due to the high frequency of targetable mutations. In this study, we explored the genomic landscape of non-small cell lung cancer (NSCLC) in young patients and compared it with genetic alterations in older patients.

Methods: Comparative study of the genomic profile of NSCLC young (≤40 years old) vs older patients (>40 years old) from Instituto Nacional de Enfermedades Neoplásicas (INEN) in Lima, Peru. Archival paraffin-embedded tumor samples were profiled with FoundationOne CDx assay to identify short variants alterations (insertions and deletions), copy number variations (CNV), tumor mutational burden and microsatellite instability in 324 driver genes and rearrangements in 28 commonly rearranged genes. A targetable alteration was defined as any alteration in a driver oncogene for which an FDA approved therapy existed at the time of study enrollment.

Results: Overall, 62 tumors were profiled, 32 from young and 30 from older patients. All clinicopathological features (smoking status, clinical stage, and histology) were similar between groups, except for gender (65.6% of females in the younger group vs 40% in the older group, P=0.043). At least one actionable mutation was present in 84.4% and 83.3% in younger and older patients, respectively. Alteration rates in the main genes were: BRAF, 3.1%(n=1) vs 0%; EGFR, 46.9% (n=15) vs 43.3% (n=13); ERBB2, 12.5% (n=4) vs 16.7% (n=5); KRAS, 15.6% (n=5) vs 16.7% (n=5); ALK, 6.3% (n=2) vs 3.3% (n=1); RET, 0.0% vs 3.3% (n=1); ROS1, 3.1% (n=1) vs 3.3% (n=1); NTRK1, 0.0% vs 3.3% (n=1) and MET, 3.1% (n=1) vs 13.3% (n=4). Mean TMB was 4.04 Mut/Mb (SD ± 3.98) for young vs 8.06 Mut/Mb (SD ± 9.84) for older patients (P=0.016). There were not significant differences in CNV, frequency of gene rearrangements, or microsatellites instability.

Conclusion: NSCLC in the young in our cohort was characterized by a high frequency of actionable genetic aberrations and a low TMB, which was also true for our older patients. The enrichment of actionable mutations in young patients described in other reports might be attributed to differences in the etiology and clinicopathological characteristics between younger and older patients and therefore not be applicable to all populations.

Keywords: genomic alterations; genomic profiling; lung cancer; non-small cell lung cancer; tumor mutational burden.

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Conflict of interest statement

LR has received grants for research support to Institution from Roche, Pfizer, Genetech, BMS, Lilly, Novartis, Syndax, Liquid Genomics and Astra Zeneca. JAP has received payments for scientific projects development from Roche Peru and a research and travel grant from Foundation Medicine. SJ, SV and ES are employees of Roche Farma, Peru. SSG worked at Roche Peru as RWData/Evidence manager Until July 2021. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
Flowchart of the patient included in the study. FM, Foundation Medicine.
Figure 2
Figure 2
Comprehensive visualization of the genomic landscape of NSCLC. (A) young (B) older patients.
Figure 3
Figure 3
Comparative analysis of mutation between age groups in genes more frequently altered (A). Comparison between age groups of the structural alteration in p53 (B) and in EGFR (C).
Figure 4
Figure 4
TMB comparison between younger and older patients with NSCLC (A). (B) Distribution of TMB groups between younger with older patients (B).
Figure 5
Figure 5
Copy number variation in older vs younger patients.
See this image and copyright information in PMC

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