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Gene expression profiling of pancreatic ductal adenocarcinomas in response to neoadjuvant chemotherapy
Sumit Sahni1,2,3, Christopher Nahm4, Mahsa S Ahadi1,2,5
1Northern Clinical School, Faculty of Medicine and Health, University of Sydney, St Leonards, New South Wales, Australia.
Aim:
Pancreatic ductal adenocarcinoma (PDAC) has the lowest survival rate of all major cancers. Chemotherapy is the mainstay systemic therapy for PDAC, and chemoresistance is a major clinical problem leading to therapeutic failure. This study aimed to identify key differences in gene expression profile in tumors from chemoresponsive and chemoresistant patients.
Methods:
Archived formalin-fixed paraffin-embedded tumor tissue samples from patients treated with neoadjuvant chemotherapy were obtained during surgical resection. Specimens were macrodissected and gene expression analysis was performed. Multi- and univariate statistical analysis was performed to identify differential gene expression profile of tumors from good (0%-30% residual viable tumor [RVT]) and poor (>30% RVT) chemotherapy-responders.
Results:
Initially, unsupervised multivariate modeling was performed by principal component analysis, which demonstrated a distinct gene expression profile between good- and poor-chemotherapy responders. There were 396 genes that were significantly (p < 0.05) downregulated (200 genes) or upregulated (196 genes) in tumors from good responders compared to poor responders. Further supervised multivariate analysis of significant genes by partial least square (PLS) demonstrated a highly distinct gene expression profile between good- and poor responders. A gene biomarker of panel (IL18, SPA17, CD58, PTTG1, MTBP, ABL1, SFRP1, CHRDL1, IGF1, and CFD) was selected based on PLS model, and univariate regression analysis of individual genes was performed. The identified biomarker panel demonstrated a very high ability to diagnose good-responding PDAC patients (AUROC: 0.977, sensitivity: 82.4%; specificity: 87.0%).
Conclusion:
A distinct tumor biological profile between PDAC patients who either respond or not respond to chemotherapy was identified.
Insights
Researchers identified distinct gene expression profiles in pancreatic ductal adenocarcinoma (PDAC) tumors. This discovery could lead to better prediction of chemotherapy response in PDAC patients.
Area of Science:
- Oncology
- Genomics
- Translational Research
Background:
- Pancreatic ductal adenocarcinoma (PDAC) has a very low survival rate.
- Chemotherapy resistance is a significant obstacle in PDAC treatment.
- Identifying biomarkers for treatment response is crucial for improving patient outcomes.
Purpose of the Study:
- To investigate gene expression differences between chemoresponsive and chemoresistant PDAC tumors.
- To identify potential gene expression biomarkers that predict chemotherapy response in PDAC.
Main Methods:
- Gene expression analysis of tumor samples from PDAC patients undergoing neoadjuvant chemotherapy.
- Utilized unsupervised (Principal Component Analysis) and supervised (Partial Least Square) multivariate statistical methods.
- Statistical analysis to identify differentially expressed genes and develop a predictive biomarker panel.
Main Results:
- Unsupervised analysis revealed distinct gene expression profiles between good and poor chemotherapy responders.
- Identified 396 significantly differentially expressed genes (200 downregulated, 196 upregulated) in good responders.
- A panel of 10 genes (IL18, SPA17, CD58, PTTG1, MTBP, ABL1, SFRP1, CHRDL1, IGF1, CFD) accurately predicted good PDAC responders (AUROC: 0.977).
Conclusions:
- A unique tumor biological profile distinguishes PDAC patients based on their response to chemotherapy.
- The identified gene biomarker panel shows high diagnostic potential for predicting chemotherapy response in PDAC.
