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Gene expression data to identify molecular characteristics of mucinous colorectal cancer

ABSTRACT: Mucinous adenocarcinoma (MuC), a subtype of colorectal cancer (CRC), exhibits distinct molecular features and a poorer prognosis compared to non-mucinous CRC (NMuC). Standard CRC treatments often fail to address MuC's unique characteristics, especially in stage II, where the benefit of adjuvant chemotherapy is unclear. Biomarkers that improve risk assessment and guide personalized treatment are needed. Based on RNA-seq data and Cox regression models, we developed a signature reflecting the characteristics of MuC which showed a strong prediction ability and clinical utility in both MuC and NMuC. Our signature represents a valuable tool for predicting recurrence and guiding personalized treatment in CRC.

ORGANISM(S): Homo sapiens

PROVIDER: GSE281917 | GEO | 2025/07/02

REPOSITORIES: GEO

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Project description:Mucinous cystic neoplasms (MCN) remain a major riddle in hepato-pancreato-biliary pathology. These cystic tumors are defined by their mucinous epithelium and ovarian-like stroma, with an estimated 10% risk of progression to invasive carcinoma. The origin of the ovarian stroma remains a subject of debate. In this study, we conducted immunohistochemical profiling, targeted DNA sequencing, and genome-wide DNA methylation analysis on a cohort of 15 pancreatic MCNs (MCN-P) and 6 hepatic MCNs (MCN-L). Unsupervised analysis of DNA methylation profiles of pancreatic neoplasms (11 entities and normal pancreatic tissue from 224 unique samples) revealed that MCN-P predominantly forms a distinct group. In the DNA methylation landscape of liver tumors, encompassing 5 tumor types and normal bile duct tissue from 136 unique samples, MCN-L demonstrated a specific methylation profile when compared to all other entities. Furthermore, within the DNA methylation landscape of ovarian tumors—featuring 5 tumor types, normal fallopian tube, and normal ovarian tissue from 90 unique samples—we found that both MCN-P and MCN-L grouped with mucinous ovarian carcinoma and mucinous borderline ovarian tumors. Notably, low-grade MCNs exhibited greater DNA methylation similarities to mucinous borderline ovarian tumors, while high-grade or invasive MCNs were primarily associated with mucinous ovarian carcinomas. When analyzing all samples together (19 tumor types and 4 normal tissue types, n = 430), MCNs similarly grouped with mucinous ovarian tumors and normal ovarian tissue. Additionally, in anetwork analysis of differentially methylated probes indicated that MCN-P and MCN-L share significant methylomic traits, closely resembling mucinous ovarian tumors. In conclusion, our findings highlight that MCN-P and MCN-L are distinct entities in the landscape of pancreatic and hepatic tumors and show DNA methylation profile similarities with mucinous ovarian tumors, suggesting a potential common origin.

Project description:Background & Aims. The current staging system for colorectal cancer (CRC) based on TNM classification allows prediction of potential recurrence. However, it does not necessarily make reliable personalized prediction of prognosis. In this paper we describe combination of clinicopathological data and gene signature of dissected tumor specimen with stage II and III CRC patients would improve the situation.. Methods. A total of 1978 CRC were collected over 5 years, and then 371 stage II and 322 stage III of them with more than 45.9 months records were subjected to clinicopathological feature analyses. Out of this collection, 129 stage II and III CRC cases were selected for analyses of gene expression profiles with resected specimen. The gene signatures were analyzed by repeated random divisions of the samples into training and test sets to extract discriminator genes. After testing the applicability of this discriminator set, it was subjected to validation using a newly obtained set of 69 samples. Results. The pathological factors in solo or in combinations could not make personalized recurrence prediction, except for partial success with stage II patients. The gene signature, on the other hand, was capable of producing a set of discriminator genes, though the accuracy was yet to be improved. We observed that the best result was obtained when discriminators were selected from stage II CRC samples and used for prognosis of stage II CRC. When stage III cases were included in the process of discriminator extraction or in the process to validate samples, the results were poorer. Finally, we examined 31 independent stage II samples with a set of 30 such discriminators and were able to obtain results with 78 % accuracy, 90 % negative predictive value (NPV), and 55% positive predictive value (PPV). Conclusions. Independent clinicopathological variables were not able to predict prognosis of individual patient, unless the factors are combined. On the other hand, gene signatures allowed accurate prediction of prognosis for individuals, especially with stage II CRC, suggesting its potential use for selection of best treatment option for individual patients. The accuracy of discriminator prediction will be further improved when we take the evolution of CRC into consideration. Of 198 samples, 129 represented the discovery phase and 69 represented the validation phase.

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Gene expression data to identify molecular characteristics of mucinous colorectal cancer

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