Dataset Information

Offsetting Expression Profiles of Prognostic Markers in Prostate Tumor vs. Its Microenvironment.

ABSTRACT: Diagnosis of the presence of tumors and subsequent prognosis based on tumor microenvironment becomes more clinically practical because tumor-adjacent tissues are easy to collect and they are more genetically homogeneous. The purpose of this study was to identify new prognostic markers in prostate stroma that are near the tumor. We have demonstrated the prognostic features of FGFR1, FRS2, S6K1, LDHB, MYPT1, and P-LDHA in prostate tumors using tissue microarrays (TMAs) which consist of 241 patient samples from Massachusetts General Hospital (MGH). In this study, we investigated these six markers in the tumor microenvironment using an Aperio Imagescope system in the same TMAs. The joint prognostic power of markers was further evaluated and classified using a new algorithm named Weighted Dichotomizing. The classifier was verified via rigorous 10-fold cross validation. Statistical analysis of the protein expression indicated that in tumor-adjacent stroma FGFR1 and MYPT1 were significantly correlated with patient outcomes and LDHB showed the outcome-association tendency. More interestingly, these correlations were completely opposite regarding tumor tissue as previously reported. The results suggest that prognostic testing should utilize either tumor-enriched tissue or stroma with distinct signature profiles rather than using mixture of both tissue types. The new classifier based on stroma tissue has potential value in the clinical management of prostate cancer patients.

SUBMITTER: Jia Z

PROVIDER: S-EPMC6611437 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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Offsetting Expression Profiles of Prognostic Markers in Prostate Tumor vs. Its Microenvironment.

Jia Zhenyu Z Zhu Jianguo J Zhuo Yangjia Y Li Ruidong R Qu Han H Wang Shibo S Wang Meiyue M Lu Jianming J Chater John M JM Ma Renyuan R Liu Ze-Zhen ZZ Cai Zhiduan Z Wu Yongding Y Jiang Funeng F He Huichan H Zhong Wei-De WD Wu Chin-Lee CL

Frontiers in oncology 20190626

Diagnosis of the presence of tumors and subsequent prognosis based on tumor microenvironment becomes more clinically practical because tumor-adjacent tissues are easy to collect and they are more genetically homogeneous. The purpose of this study was to identify new prognostic markers in prostate stroma that are near the tumor. We have demonstrated the prognostic features of FGFR1, FRS2, S6K1, LDHB, MYPT1, and P-LDHA in prostate tumors using tissue microarrays (TMAs) which consist of 241 patient ...[more]

PMID: 31316912

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Project description:Background: Gene expression profiling of breast carcinomas has increased our understanding of the heterogeneous biology of this disease and promises to impact clinical care. The aim of this study was to evaluate the prognostic value of gene expression-based classification along with established prognostic markers and mutation status of the TP53 gene, in a group of breast cancer patients with long-term (12-16 years) follow-up. Methods: The clinical and histopathological parameters of 200 breast cancer patients were studied for their effects on clinical outcome using univariate/multivariate Cox regression. The prognostic impact of mutations in the TP53 gene, identified using TTGE and sequencing, was also evaluated. Eighty of the samples were analyzed for gene expression using 42K cDNA microarrays and the patients were assigned to five previously defined molecular expression groups. The strength of the gene expression based classification versus standard markers was evaluated by adding this variable to the Cox regression model used to analyze all samples. Results: Both univariate and multivariate analysis showed that TP53 mutation status, tumor size and lymph node status were the strongest predictors of breast cancer survival for the whole group of patients. Analyses of the patients with gene expression data showed that TP53 mutation status, gene expression based classification, tumor size and lymph node status were significant predictors of survival. The TP53 mutation status showed strong association with the ?basal-like? and ?ERBB2+? gene expression subgroups, and tumors with mutation had a characteristic gene expression pattern. Conclusions: TP53 mutation status and gene-expression based groups are important survival markers of breast cancer, and these molecular markers may provide prognostic information that complements clinical variables. The study adds experience and knowledge to an ongoing characterization and classification of the disease. Experiment set consisting of 80 primary breast carcinomas collected at Ulleval University Hospital (ULL-samples), Oslo, Norway from 1990-94, and one normal sample from breast reduction surgery.

Project description:N6-Adenosine methylation, yielding N6-methyladenosine (m6A), is a reversible epigenetic modification found in messenger RNAs and long non-coding RNAs (lncRNAs), which affects the fate of modified RNA molecules and is essential for the development and differentiation of immune cells in the tumor microenvironment (TME). Osteosarcoma (OS) is the most common primary bone tumor in children and adolescents, and is characterized by high mortality. Currently, the possible role of m6A modifications in the prognosis of OS is unclear. In the present study, we investigated the correlation between m6A-related lncRNA expression and the clinical outcomes of OS patients via a comprehensive analysis. Clinical and workflow-type data were obtained from the Genotype-Tissue Expression Program and The Cancer Genome Atlas. We examined the relationship between m6A modifications and lncRNA expression, conducted Kyoto Encyclopedia of Genes analysis and also gene set enrichment analysis (GSEA), implemented survival analysis to investigate the association of clinical survival data with the expression of m6A-related lncRNAs, and utilized Lasso regression to model the prognosis of OS. Furthermore, we performed immune correlation analysis and TME differential analysis to investigate the infiltration levels of immune cells and their relationship with clinical prognosis. LncRNA expression and m6A levels were closely associated in co-expression analysis. The expression of m6A-related lncRNAs was quite low in tumor tissues; this appeared to be a predicting factor of OS in a prognostic model, independent of other clinical features. The NOD-like receptor signaling pathway was the most significantly enriched pathway in GSEA. In tumor tissues, SPAG4 was overexpressed while ZBTB32 and DEPTOR were downregulated. Tissues in cluster 2 were highly infiltrated by plasma cells. Cluster 2 presented higher ESTIMATE scores and stromal scores, showing a lower tumor cell purity in the TME. In conclusion, m6A-related lncRNA expression is strongly associated with the occurrence and development of OS, and can be used to as a prognostic factor of OS. Moreover, m6A-related lncRNAs and infiltrating immune cells in the TME could serve as new therapeutic targets and prognostic biomarkers for OS.

Dataset Information

Offsetting Expression Profiles of Prognostic Markers in Prostate Tumor vs. Its Microenvironment.

Publications

Offsetting Expression Profiles of Prognostic Markers in Prostate Tumor vs. Its Microenvironment.

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