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Identification of Potential Biomarkers and Biological Pathways for Poor Clinical Outcome in Mucinous Colorectal Adenocarcinoma.

ABSTRACT: Colorectal cancer (CRC) comprises several histological subtypes, but the influences of the histological subtypes on prognosis remains unclear. We sought to evaluate the prognosis of mucinous adenocarcinoma (MAC), compared to that of traditional adenocarcinoma (TAC). This study used the data of patients diagnosed with CRC between 2004 and 2016, as obtained from the Surveillance, Epidemiology, and End Results database. We established a predictive model for disease-specific survival using conditional survival forest, model, non-linear Cox proportional hazards, and neural multi-task logistic regression model and identified the gene signatures for predicting poor prognosis based on the arrayexpress datasets. In total, 9096 (42.1%) patients with MAC and 12,490 (58.9%) patients with TAC were included. Those with the MAC subtype were more likely to have a poorer overall survival rate compared to those with the TAC subtype in stage II CRC (p = 0.002). The eight major genes including RPS18, RPL30, NME2, USP33, GAB2, RPS3A, RPS25, and CEP57 were found in the interacting network pathway. MAC was found to have a poorer prognosis compared to TAC, especially in Stage II CRC. In addition, our findings suggest that identifying potential biomarkers and biological pathways can be useful in CRC prognosis.

SUBMITTER: Kim CW

PROVIDER: S-EPMC8268122 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Breast carcinoma (BC) is the leading cause of death in women worldwide, making up 23% of all cancers in women, with 1.38 million new cases worldwide annually and responsible for 460,000 deaths. Despite the significant advances in the identification of molecular markers and different modalities of treatment in primary BC, the ability to predict the metastatic behavior in breast cancer is still limited. The purpose of this study was to help identify novel molecular markers associated with clinical outcome in a cohort of Brazilian BC patients. We generated global gene expression profiles from 24 patients with invasive ductal BC followed for â¥ 5-years, including 15 samples from patients classified as presenting good prognosis based on traditional markers and clinical criteria and 9 patients that developed metastasis. We identified a set of 58 differentially expressed genes (p â¤0.01) between groups of patients with good and poor prognosis. Up-regulation of B3GNT7, PPM1D, TNKS2, PHB and GTSE1 in patients with poor prognosis was confirmed by quantitative RT-PCR in an independent sample set from patients with BC (47 with good prognosis and 8 that presented metastasis). Expression of BAD protein was investigated by immunohistochemistry in 1276 BC samples and confirmed the reduced expression levels in metastatic cases observed in the oligoarray data. These findings point to novel prognostic markers that can distinguish breast carcinoma samples according to clinical course and progression of the disease. Global expression profiles from 38 ductal breast tumor patient samples were used to search for molecular signatures correlated with current prognostic markers. A subset of 24 cases comprising 15 patients that remained free of disease after surgery and 9 patients that developed metastasis was used to identify candidate biomarkers associated with metastatic progression. Candidates were subsequently validated in additional independent samples by RT-qPCR or immunohistochemistry.

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Identification of Potential Biomarkers and Biological Pathways for Poor Clinical Outcome in Mucinous Colorectal Adenocarcinoma.

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