BMC Cancer (Aug 2024)

Comparing clinical and genomic features based on the tumor location in patients with resected pancreatic cancer

  • Won-Gun Yun,
  • Daeun Kim,
  • Mirang Lee,
  • Youngmin Han,
  • Yoon Soo Chae,
  • Hye-Sol Jung,
  • Young Jae Cho,
  • Wooil Kwon,
  • Joon Seong Park,
  • Daechan Park,
  • Jin-Young Jang

DOI
https://doi.org/10.1186/s12885-024-12795-5
Journal volume & issue
Vol. 24, no. 1
pp. 1 – 12

Abstract

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Abstract Background Pancreatic cancer is anatomically divided into pancreatic head and body/tail cancers, and some studies have reported differences in prognosis. However, whether this discrepancy is induced from the difference of tumor biology is hotly debated. Therefore, we aimed to evaluate the differences in clinical outcomes and tumor biology depending on the tumor location. Methods In this retrospective cohort study, we identified 800 patients with pancreatic ductal adenocarcinoma who had undergone upfront curative-intent surgery. Cox regression analysis was performed to explore the prognostic impact of the tumor location. Among them, 153 patients with sufficient tumor tissue and blood samples who provided informed consent for next-generation sequencing were selected as the cohort for genomic analysis. Results Out of the 800 patients, 500 (62.5%) had pancreatic head cancer, and 300 (37.5%) had body/tail cancer. Tumor location in the body/tail of the pancreas was not identified as a significant predictor of survival outcomes compared to that in the head in multivariate analysis (hazard ratio, 0.94; 95% confidence interval, 0.77–1.14; P = 0.511). Additionally, in the genomic analyses of 153 patients, there were no significant differences in mutational landscapes, distribution of subtypes based on transcriptomic profiling, and estimated infiltration levels of various immune cells between pancreatic head and body/tail cancers. Conclusions We could not find differences in prognosis and tumor biology depending on tumor location in pancreatic ductal adenocarcinoma. Discrepancies in prognosis may represent a combination of lead time, selection bias, and clinical differences, including the surgical burden between tumor sites.

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