Prognostic Biomarkers Identified for Pancreatic Ductal Adenocarcinoma Using Whole Genome Sequencing

Possible biomarkers for prognosis and clinical outcomes were identified, through the use whole exome sequencing and RNA sequencing, as therapeutic targets for patients with pancreatic ductal adenocarcinoma (PDAC), according to a recent study.

The study, published in Therapeutic Advances in Medical Oncology, also reconfirmed genomic landscapes, major driver mutations, and DNA damage repair pathway mutations associated with PDAC.

“Understanding these molecular aberrations that determine patient outcomes after surgery and chemotherapy has the potential to improve the treatment outcomes of PDAC patients,” wrote the investigators.

With a 5-year survival rate of 9%, PDAC carries the worst prognosis among the most common cancers and is predicted to becomes the second-leading cause of cancer-related deaths in the United States by 2030. The genomic landscape of PDAC has 4 mutational pathways associated with carcinogenesis:

  • Kirsten rat sarcoma virus (KRAS)
  • Cellular tumor antigen p53 (TP53)
  • Cyclin dependent kinase inhibitor 2A (CDKN2A)
  • SMAD family member 4 (SMAD4)

Additionally, ring finger protein 43 (RNF43) and AT-rich interactive domain-containing protein 1A (ARID1A) are frequently mutated genes associated with PDAC and have been identified in systematic genomic profiling in previous literature. However, there is scarce data on whether molecular features are related to clinical outcomes in patients with PDAC who have undergone curative surgery and past research has not specified any correlative information with respect to response to chemotherapy regimens.

The investigators enrolled 83 patients with PDAC who had undergone curative surgery at Samsung Medical Center in Seoul, Republic of Korea, between September 2008 and June 2017. Tumor tissues were obtained during surgery and were analyzed using whole exome sequencing and RNA sequencing. The tissues were also assessed along with matched normal tissues derived from the patients.

Among the patients, 52 (62.7%) were men and the median (range) age was 65 (37-82) years. There were 26 (31.3%) patients diagnosed with stage I disease, 36 (43.3%) with stage II, and 17 (20.5%) with stage III or IV.

The median number of somatic nonsilent coding mutations was 45, ranging from 7 to 10,028. Additionally, there were 5 significantly mutated genes were identified, including KRAS (75%), TP53 (67%), CDKN2A (12%), SMAD4 (20%), and RNF43 (13%).

The tumor-specific transcriptome was divided into 2 clusters that resembled the Moffitt tumor classification (tumor S1 and S2). Tumor S1 demonstrated 2 subclusters, S1-1 and S1-2 Bailey subtypes. Tumor S1-1’s transcriptome was found to overlap with the exocrine-like/aberrantly differentiated endocrine exocrine subtype. The transcriptome for tumor S1-2 primarily consisted of the classical/progenitor subtype.

When conducting an analysis of combinatorial gene alterations, concurrent mutations of KRAS with low-density lipoprotein receptor related protein 1B were linked with significantly worse disease-free survival after surgery (P = .034). One patient (1.2%) had an ultrahypermutant phenotype with microsatellite instability.

The investigators identified high amounts of protein kinase C Iota expression as an overlapping, poor biomarker for disease prognosis between their data set and data obtained and analyzed from the Cancer Genome Atlas Research Network.

“These differences in baseline tumor characteristics and adjuvant treatment strategy may contribute to the discordance of the association between KRAS mutational status and disease-free survival after surgery,” the investigators suggested.


Hong JY, Cho HJ, K, Kim ST, et al. Comprehensive molecular profiling to predict clinical outcomes in pancreatic cancer. Ther Adv Med Oncol. August 28, 2021;13:1-14. doi:10.1177/17588359211038478

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