Systematic pathway‐level analysis defines conserved transcriptional divergence between primary lung tumors and cell line models
- 1Centre for Integrative Omics Data Science (CIODS) Yenepoya (Deemed to be University) Mangalore Karnataka India
Abstract
Background: Cancer cell lines are widely used in preclinical oncology, yet their fidelity in modeling primary tumors remains uncertain.
Methods: We performed a systematic pathway‐level transcriptomic comparison of lung adenocarcinoma (LUAD) primary tumors from The Cancer Genome Atlas (TCGA; n = 513) and LUAD cell lines from the Cancer Cell Line Encyclopedia (CCLE; n = 45). Single‐sample gene set enrichment analysis (ssGSEA) combined with L1‐penalized logistic regression was applied to identify a discriminatory pathway signature.
Results: Five Hallmark pathways (E2F targets, interferon‐gamma response, epithelial‐mesenchymal transition, coagulation, and G2M checkpoint) distinguished primary lung tumors from cell line models. Cell lines exhibited significant enrichment of proliferation‐associated pathways, whereas primary tumors retained immune‐ and microenvironment‐related programs. Tumor–normal comparisons revealed significant pathway alterations in TCGA samples that were not fully recapitulated in CCLE models. Gene‐level analyses confirmed depletion of stromal and vascular markers in cell lines. CCLE samples also demonstrated significantly higher tumor mutational burden and increased frequencies of TP53 and STK11 mutations. These pathway‐level distinctions were conserved in lung squamous cell carcinoma, indicating generalizability across major NSCLC subtypes.
Conclusion: These findings define a pathway‐based framework for evaluating transcriptional fidelity between cell lines and primary tumors, highlighting fundamental transcriptional divergence with implications for rational model selection in lung cancer research.
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BibTeX
@article{bera2026systematic,
title = {{Systematic pathway‐level analysis defines conserved transcriptional divergence between primary lung tumors and cell line models}},
author = {Pritam Bera and Rajesh Raju and Debodipta Das},
journal = {Animal Models and Experimental Medicine},
year = {2026},
month = jul,
doi = {10.1002/ame2.70258},
url = {https://doi.org/10.1002/ame2.70258},
note = {CC BY-NC 4.0},
}
RIS
TY - JOUR
TI - Systematic pathway‐level analysis defines conserved transcriptional divergence between primary lung tumors and cell line models
AU - Pritam Bera
AU - Rajesh Raju
AU - Debodipta Das
PY - 2026
DA - 2026/07/26
JO - Animal Models and Experimental Medicine
DO - 10.1002/ame2.70258
UR - https://doi.org/10.1002/ame2.70258
AB - Background: Cancer cell lines are widely used in preclinical oncology, yet their fidelity in modeling primary tumors remains uncertain. Methods: We performed a systematic pathway‐level transcriptomic comparison of lung adenocarcinoma (LUAD) primary tumors from The Cancer Genome Atlas (TCGA; n = 513) and LUAD cell lines from the Cancer Cell Line Encyclopedia (CCLE; n = 45). Single‐sample gene set enrichment analysis (ssGSEA) combined with L1‐penalized logistic regression was applied to identify a discriminatory pathway signature. Results: Five Hallmark pathways (E2F targets, interferon‐gamma response, epithelial‐mesenchymal transition, coagulation, and G2M checkpoint) distinguished primary lung tumors from cell line models. Cell lines exhibited significant enrichment of proliferation‐associated pathways, whereas primary tumors retained immune‐ and microenvironment‐related programs. Tumor–normal comparisons revealed significant pathway alterations in TCGA samples that were not fully recapitulated in CCLE models. Gene‐level analyses confirmed depletion of stromal and vascular markers in cell lines. CCLE samples also demonstrated significantly higher tumor mutational burden and increased frequencies of TP53 and STK11 mutations. These pathway‐level distinctions were conserved in lung squamous cell carcinoma, indicating generalizability across major NSCLC subtypes. Conclusion: These findings define a pathway‐based framework for evaluating transcriptional fidelity between cell lines and primary tumors, highlighting fundamental transcriptional divergence with implications for rational model selection in lung cancer research.
SN - 2096-5451
SN - 2576-2095
ER -