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Genomic analysis of pancreatic cancer reveals 3 molecular subtypes with different clinical outcomes.

ABSTRACT:

Abstract

Pancreatic cancer has a very high mortality with a 5-year survival of <5%. The purpose of this study was to classify specific molecular subtypes associated with prognosis of pancreatic cancer using The Cancer Genome Atlas (TCGA) multiplatform genomic data.Multiplatform genomic data (N = 178), including gene expression, copy number alteration, and somatic mutation data, were obtained from cancer browser (https://genome-cancer.ucsc.edu, cohort: TCGA Pancreatic Cancer). Clinical data including survival results were analyzed. We also used validation cohort (GSE50827) to confirm the robustness of these molecular subtypes in pancreatic cancer.When we performed unsupervised clustering using TCGA gene expression data, we found three distinct molecular subtypes associated with different survival results. Copy number alteration and somatic mutation data showed different genomic patterns for these three subtypes. Ingenuity pathway analysis revealed that each subtype showed differentially altered pathways. Using each subtype-specific genes (200 were selected), we could predict molecular subtype in another cohort, confirming the robustness of these molecular subtypes of pancreatic cancer. Cox regression analysis revealed that molecular subtype is the only significant prognostic factor for pancreatic cancer (P = .042, 95% confidence interval 0.523-0.98).Genomic analysis of pancreatic cancer revealed 3 distinct molecular subtypes associated with different survival results. Using these subtype-specific genes and prediction model, we could predict molecular subtype associated with prognosis of pancreatic cancer.

SUBMITTER: Hwang JW

PROVIDER: S-EPMC8036077 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Pancreatic cancer (PC) is the fourth leading cause of cancer deaths in the United States with a five-year patient survival rate of only 6%. Early detection and treatment of this disease is hampered due to lack of reliable diagnostic and prognostic markers. Recent studies have shown that dynamic changes in the global DNA methylation and gene expression patterns play key roles in the PC development; hence, provide valuable insights for better understanding the initiation and progression of PC. In the current study, we used DNA methylation, gene expression, copy number, mutational and clinical data from pancreatic patients. We independently investigated the DNA methylation and differential gene expression profiles between normal and tumor samples and correlated methylation levels with gene expression patterns. We observed a total of ~23-thousand differentially methylated CpG sites (???0.1) between normal and tumor samples, where majority of the CpG sites are hypermethylated in PC, and this phenomenon is more prominent in the 5'UTRs and promoter regions compared to the gene bodies. Differential methylation is observed in genes associated with the homeobox domain, cell division and differentiation, cytoskeleton, epigenetic regulation and development, pancreatic development and pancreatic signaling and pancreatic cancer core signaling pathways. Correlation analysis suggests that methylation in the promoter region and 5'UTR has mostly negative correlations with gene expression while gene body and 3'UTR associated methylation has positive correlations. Regulatory element analysis suggests that HOX cluster and histone core proteins are upstream regulators of hypomethylation, while SMAD4, STAT4, STAT5B and zinc finger proteins (ZNF) are upstream regulators of hypermethylation. Non-negative matrix factorization (NMF) clustering of differentially methylated sites generated three clusters in PCs suggesting the existence of distinct molecular subtypes. Cluster 1 and cluster 2 showed samples enriched with clinical phenotypes like neoplasm histological grade and pathologic T-stage T3, respectively, while cluster 3 showed the enrichment of samples with neoplasm histological grade G1. To the best of our knowledge, this is the first genome-scale methylome analysis of PC data from TCGA. Our clustering analysis provides a strong basis for future work on the molecular subtyping of epigenetic regulation in pancreatic cancer.

Project description:BackgroundAlthough the conversion of clinically used breast cancer biomarkers such as estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2) between primary tumors and metastatic lesions is well recognized, data on whether receptor conversion has an effect on therapy management and survival in patients with metastatic breast cancer is limited. This study aimed to investigate the clinical implications of receptor conversion throughout tumor progression.MethodsIn total, 2450 patients diagnosed with metastatic breast cancer in Tianjin Medical University Cancer Institute and Hospital were analyzed and 426 female patients with available biopsy results from both primary and metastatic sites were included in this study. We investigated the alteration of ER, PR and HER2 during breast cancer progression and evaluated the therapy management and prognostic value of receptor conversion.ResultsThe conversion rates of ER, PR, and HER2 between primary tumors and metastasis were 21.1% (McNemar's test p < 0.001), 33.2% (p < 0.001), and 11.6% (p = 0.868), respectively. Evaluation of ER, PR, and HER2 status in multiple consecutive metastases revealed a change in 19.1% (p > 0.05), 23.5% (p = 0.021), and 9.8% (p > 0.05) of patients, respectively. Adjuvant therapy (chemotherapy/endocrine therapy) was related to hormone receptor conversion (p < 0.05). A statistically significant differential survival associated with hormone receptor (ER/PR) conversion (log-rank p < 0.05) was observed. In the multivariate analysis, ER conversion was an independent influence factor of survival (p < 0.05). Molecular typing conversion in primary and metastatic lesions also had a significant effect on survival (p < 0.05). We found that changing treatment based on the receptor conversion could affect clinical outcomes (p < 0.05).ConclusionsOur findings indicated that receptor conversion during breast tumor progression had a significant effect on survival. Most importantly, our findings proved that patients with receptor conversion benefited from a change in therapy.

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Genomic analysis of pancreatic cancer reveals 3 molecular subtypes with different clinical outcomes.

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