Dataset Information

Intratumoral heterogeneity analysis reveals hidden associations between protein expression losses and patient survival in clear cell renal cell carcinoma.

ABSTRACT: Intratumoral heterogeneity (ITH) is a prominent feature of kidney cancer. It is not known whether it has utility in finding associations between protein expression and clinical parameters. We used ITH that is detected by immunohistochemistry (IHC) to aid the association analysis between the loss of SWI/SNF components and clinical parameters.160 ccRCC tumors (40 per tumor stage) were used to generate tissue microarray (TMA). Four foci from different regions of each tumor were selected. IHC was performed against PBRM1, ARID1A, SETD2, SMARCA4, and SMARCA2. Statistical analyses were performed to correlate biomarker losses with patho-clinical parameters. Categorical variables were compared between groups using Fisher's exact tests. Univariate and multivariable analyses were used to correlate biomarker changes and patient survivals. Multivariable analyses were performed by constructing decision trees using the classification and regression trees (CART) methodology. IHC detected widespread ITH in ccRCC tumors. The statistical analysis of the "Truncal loss" (root loss) found additional correlations between biomarker losses and tumor stages than the traditional "Loss in tumor (total)". Losses of SMARCA4 or SMARCA2 significantly improved prognosis for overall survival (OS). Losses of PBRM1, ARID1A or SETD2 had the opposite effect. Thus "Truncal Loss" analysis revealed hidden links between protein losses and patient survival in ccRCC.

SUBMITTER: Jiang W

PROVIDER: S-EPMC5514919 | biostudies-literature | 2017 Jun

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Intratumoral heterogeneity analysis reveals hidden associations between protein expression losses and patient survival in clear cell renal cell carcinoma.

Jiang Wei W Dulaimi Essel E Devarajan Karthik K Parsons Theodore T Wang Qiong Q O'Neill Raymond R Solomides Charalambos C Peiper Stephen C SC Testa Joseph R JR Uzzo Robert R Yang Haifeng H

Oncotarget 20170601 23

Intratumoral heterogeneity (ITH) is a prominent feature of kidney cancer. It is not known whether it has utility in finding associations between protein expression and clinical parameters. We used ITH that is detected by immunohistochemistry (IHC) to aid the association analysis between the loss of SWI/SNF components and clinical parameters.160 ccRCC tumors (40 per tumor stage) were used to generate tissue microarray (TMA). Four foci from different regions of each tumor were selected. IHC was pe ...[more]

PMID: 28445125

Similar Datasets

Project description:Recent studies have shown that intratumoral heterogeneity (ITH) is prevalent in clear cell renal cell carcinoma (ccRCC), based on DNA sequencing and chromosome aberration analysis of multiple regions from the same tumor. VHL mutations were found to be universal throughout individual tumors when it occurred (ubiquitous), while the mutations in other tumor suppressor genes tended to be detected only in parts of the tumors (subclonal). ITH has been studied mostly by DNA sequencing in limited numbers of samples, either by whole genome sequencing or by targeted sequencing. It is not known whether immunohistochemistry (IHC) can be used as a tool to study ITH. To address this question, we examined the protein expression of PBRM1, and PBRM1-related proteins such as ARID1A, SETD2, BRG1, and BRM. Altogether, 160 ccRCC (40 per stage) were used to generate a tissue microarray (TMA), with four foci from each tumor included. Loss of expression was defined as 0-5% of tumor cells with positive nuclear staining in an individual focus. We found that 49/160 (31%), 81/160 (51%), 23/160 (14%), 24/160 (15%), and 61/160 (38%) of ccRCC showed loss of expression of PBRM1, ARID1A, SETD2, BRG1, and BRM, respectively, and that IHC could successfully detect a high prevalence of ITH. Phylogenetic trees were constructed that reflected the ITH. Striking co-losses among proteins were also observed. For instance, ARID1A loss almost always accompanied PBRM1 loss, whereas BRM loss accompanied loss of BRG1, PBRM1 or ARID1A. SETD2 loss frequently occurred with loss of one or more of the other four proteins. Finally, in order to learn the impact of combined losses, we compared the tumor growth after cells acquired losses of ARID1A, PBRM1, or both in a xenograft model. The results suggest that ARID1A loss has a greater tumor-promoting effect than PBRM1 loss, indicating that xenograft analysis is a useful tool to investigate how these losses impact on tumor behavior, either alone or in combination.

Project description:Renal cell carcinoma (RCC) is one of the leading causes of cancer-related death worldwide. Tumour metastasis and heterogeneity lead to poor survival outcomes and drug resistance in patients with metastatic RCC (mRCC). In this study, we aimed to assess intratumoural heterogeneity (ITH) in mRCC cells by performing a combined analysis of bulk data and single-cell RNA-sequencing data, and develop novel biomarkers for prognosis prediction on the basis of the potential molecular mechanisms underlying tumorigenesis. Eligible single-cell cohorts related to mRCC were acquired using the Gene Expression Omnibus (GEO) dataset to identify potential mRCC subpopulations. We then performed gene set variation analysis to understand the differential function in primary RCC and mRCC samples. Subsequently, we applied weighted correlation network analysis to identify coexpressing gene modules that were related to the external trait of metastasis. Protein-protein interactions were used to screen hub subpopulation-difference (sub-dif) markers (ACTG1, IL6, CASP3, ACTB and RAP1B) that might be involved in the regulation of RCC metastasis and progression. Cox regression analysis revealed that ACTG1 was a protective factor (HR < 1), whereas the other four genes (IL6, CASP3, ACTB and RAP1B) were risk factors (HR > 1). Kaplan-Meier survival analysis suggested the potential prognostic value of these sub-dif markers. The expression of sub-dif markers in mRCC was further evaluated in clinical samples by immunohistochemistry (IHC). Additionally, the genetic features of sub-dif marker expression patterns, such as genetic variation profiles, correlations with tumour-infiltrating lymphocytes (TILs), and targeted signalling pathway activities, were assessed in bulk RNA-seq datasets. In conclusion, we established novel subpopulation markers as key prognostic factors affecting EMT-related signalling pathway activation in mRCC, which could facilitate the implementation of a treatment for mRCC patients.

Dataset Information

Intratumoral heterogeneity analysis reveals hidden associations between protein expression losses and patient survival in clear cell renal cell carcinoma.

Publications

Intratumoral heterogeneity analysis reveals hidden associations between protein expression losses and patient survival in clear cell renal cell carcinoma.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets