INTEGRATIVE PHARMACOGENOMIC ANALYSIS OF DRUG RESPONSE HETEROGENEITY ACROSS CANCER CELL LINES: INSIGHTS FROM LARGE-SCALE GDSC DATA
- 1General Practitioner, Elova Hospitals, 27, 5th Cross, Lalbagh Main Rd, Sudhama Nagar, Bengaluru – 560027
Abstract
Cancer treatment outcomes vary significantly due to heterogeneity in tumor biology and differences in drug response. Understanding the determinants of drug sensitivity is essential for improving therapeutic strategies and advancing precision oncology. This study utilized a secondary dataset from the Genomics of Drug Sensitivity in Cancer (GDSC) database, comprising large-scale drug response profiles across multiple cancer cell lines. Drug sensitivity was assessed using LN-IC50, AUC, and Z-score metrics. Pharmacological variables, including drug targets and pathways, along with biological context such as cancer type and tissue origin, were analyzed to evaluate their influence on drug response patterns. The analysis revealed substantial variability in drug response across cancer cell lines, reflecting the heterogeneous nature of cancer. Pharmacological pathways emerged as key determinants of drug sensitivity, with pathway-specific drugs demonstrating more consistent effectiveness. Cancer lineage also contributed to variability in response, indicating the importance of biological context. A strong association was observed between drug pathway classification and sensitivity patterns, highlighting the role of pharmacological mechanisms in therapeutic outcomes. The study demonstrates that drug response in cancer cell lines is primarily influenced by pharmacological determinants, with additional contributions from biological context. These findings support pathway-based approaches in cancer therapy and emphasize the importance of integrating pharmacological and molecular context to optimize treatment strategies.
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BibTeX
@article{rajendran2026integrative,
title = {{INTEGRATIVE PHARMACOGENOMIC ANALYSIS OF DRUG RESPONSE HETEROGENEITY ACROSS CANCER CELL LINES: INSIGHTS FROM LARGE-SCALE GDSC DATA}},
author = {Latha Kiran Krishna Rajendran},
journal = {Research},
year = {2026},
month = jun,
doi = {10.5281/zenodo.20767385},
url = {https://doi.org/10.5281/zenodo.20767385},
note = {CC BY},
}
RIS
TY - JOUR
TI - INTEGRATIVE PHARMACOGENOMIC ANALYSIS OF DRUG RESPONSE HETEROGENEITY ACROSS CANCER CELL LINES: INSIGHTS FROM LARGE-SCALE GDSC DATA
AU - Latha Kiran Krishna Rajendran
PY - 2026
DA - 2026/06/19
JO - Research
DO - 10.5281/zenodo.20767385
UR - https://doi.org/10.5281/zenodo.20767385
AB - Cancer treatment outcomes vary significantly due to heterogeneity in tumor biology and differences in drug response. Understanding the determinants of drug sensitivity is essential for improving therapeutic strategies and advancing precision oncology. This study utilized a secondary dataset from the Genomics of Drug Sensitivity in Cancer (GDSC) database, comprising large-scale drug response profiles across multiple cancer cell lines. Drug sensitivity was assessed using LN-IC50, AUC, and Z-score metrics. Pharmacological variables, including drug targets and pathways, along with biological context such as cancer type and tissue origin, were analyzed to evaluate their influence on drug response patterns. The analysis revealed substantial variability in drug response across cancer cell lines, reflecting the heterogeneous nature of cancer. Pharmacological pathways emerged as key determinants of drug sensitivity, with pathway-specific drugs demonstrating more consistent effectiveness. Cancer lineage also contributed to variability in response, indicating the importance of biological context. A strong association was observed between drug pathway classification and sensitivity patterns, highlighting the role of pharmacological mechanisms in therapeutic outcomes. The study demonstrates that drug response in cancer cell lines is primarily influenced by pharmacological determinants, with additional contributions from biological context. These findings support pathway-based approaches in cancer therapy and emphasize the importance of integrating pharmacological and molecular context to optimize treatment strategies.
SN - 2407-9529
ER -