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Poster Display session

325P - Identifying novel somatic mutations in SCLC through next generation sequencing

Date

28 Mar 2025

Session

Poster Display session

Presenters

Pragya Kashyap

Citation

Journal of Thoracic Oncology (2025) 20 (3): S181-S207. 10.1016/S1556-0864(25)00632-X

Authors

P. Kashyap

Author affiliations

  • IITJ - Indian Institute of Technology Jodhpur, Jodhpur/IN

Resources

This content is available to ESMO members and event participants.

Abstract 325P

Background

Small cell lung cancer (SCLC) is an aggressive neuroendocrine carcinoma with limited treatment options due to its high metastatic potential and complex genetic mutations. To address this, we developed a computational pipeline to detect novel somatic mutations, offering deeper insights into SCLC’s mutational landscape and potential therapeutic targets.

Methods

RNA-seq data from SCLC patients was retrieved from GEO database and preprocessed using quality control, trimming, and alignment to GRCh38 genome. Somatic mutations were identified using GATK MuTect2 and filtered through LODN classification, yielding high-confidence variants. Variants were annotated using ANNOVAR, focusing on rare, non-synonymous, and splice-site mutations. Functional enrichment was performed, identifying known and novel SCLCassociated genes involved in cancer-related pathways. Integration of database-driven and novel discovery approaches highlighted key molecular mechanisms, providing insights into SCLC progression and potential therapeutic targets.

Results

Somatic variant analysis of SCLC RNA-seq data identified high-confidence mutations using GATK MuTect2 and annotation tools. Enrichment analyses revealed key pathways, including PI3K-Akt signaling, apoptosis, and cell adhesion. Known genes including AKT2, BCL2, PTEN and novel genes including TUBA1A, KIF1A, CHD7 were linked to cancer-related and neuroendocrine processes. KEGG and PPI analyses highlighted TP53, MYC, and BCL2 as central to SCLC pathogenesis, offering insights into therapeutic targets and biomarkers.

Conclusions

This study utilized RNA-seq data to identify high-confidence somatic mutations in SCLC, uncovering novel genetic alterations and pathways critical to tumor progression. These findings offer valuable insights into SCLC’s molecular mechanisms and highlight potential therapeutic targets, advancing the development of precision medicine approaches. Notably, this represents the first application of RNA-seq for detecting somatic mutations in SCLC, marking a significant step forward in understanding and addressing this aggressive cancer.

Legal entity responsible for the study

Indian Institute of Technology Jodhpur.

Funding

Indian Institute of Technology Jodhpur.

Disclosure

The author has declared no conflicts of interest.

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