Dataset Information

Cross-omics analysis of archival human renal cell carcinoma biopsies to identify emerging treatment avenues

ABSTRACT: Renal cell cancer is among the most common forms of cancer in humans, with around 35,000 deaths attributed to kidney carcinoma in the European Union (EU) in 2012 alone. Clear cell renal cell carcinoma (ccRCC) represents the most common form of kidney cancer and the most lethal of all genitourinary cancers. Here we apply omics technologies to archival core biopsies to investigate the biology underlying ccRCC. Knowledge of these underlying processes should be useful for the discovery and/or confirmation of novel therapeutic approaches and ccRCC biomarker development. From partial or full nephrectomies of 11 patients, paired core biopsies of ccRCC affected tissue and adjacent non-tumorous tissue were both sampled and subjected to proteomics analyses. We combined proteomics results with our published mRNA-seq from the same patients and with published miRNA-seq data from an overlapping patient cohort from our institution. Statistical analysis and pathway analysis were performed with JMP Genomics (SAS) and Ingenuity Pathway Analysis (IPA, Qiagen), respectively. Proteomics analysis confirmed the involvement of metabolism and oxidative stress-related pathways in ccRCC, while the most affected pathways in the mRNA-seq data were related to the immune system. Unlike proteomics or mRNA-seq alone, a combinatorial cross-omics pathway analysis approach captured a broad spectrum of biological processes underlying ccRCC, such as mitochondrial damage, repression of apoptosis, and immune system pathways. Sirtuins, immunoproteasome genes and CD74 are proposed as potential targets for the treatment of ccRCC.

INSTRUMENT(S): Q Exactive

ORGANISM(S): Homo Sapiens (human)

TISSUE(S): Epithelial Cell, Kidney

DISEASE(S): Renal Clear Cell Carcinoma

SUBMITTER: Kenneth Finne

LAB HEAD: Hans-Peter Marti

PROVIDER: PXD011681 | Pride | 2019-04-25

REPOSITORIES: Pride

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Publications

Transcriptome-proteome integration of archival human renal cell carcinoma biopsies enables identification of molecular mechanisms.

Koch Even E Finne Kenneth K Eikrem Øystein Ø Landolt Lea L Beisland Christian C Leh Sabine S Delaleu Nicolas N Granly Magnus M Vikse Bjørn Egil BE Osman Tarig T Scherer Andreas A Marti Hans-Peter HP

American journal of physiology. Renal physiology 20190306 5

Renal cell cancer is among the most common forms of cancer in humans, with around 35,000 deaths attributed to kidney carcinoma in the European Union in 2012 alone. Clear cell renal cell carcinoma (ccRCC) represents the most common form of kidney cancer and the most lethal of all genitourinary cancers. Here, we apply omics technologies to archival core biopsies to investigate the biology underlying ccRCC. Knowledge of these underlying processes should be useful for the discovery and/or confirmati ...[more]

PMID: 30838877

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Project description:We investigated the expression profiles of microRNAs (miRNA) in 27 renal cell carcinoma (RCC) FFPE tissues (3 chRCC, 5 papRCC and 18 ccRCC), 4 upper urinary tract-urothelial cell carcinomas of the renal pelvis-ureter (UUT-UCCs) and 20 normal kidneys by using the miRCURY LNAM-bM-^DM-" microRNA Array, 6th gen (Exiqon, Woburn MA), containing capture probes that target all miRNAs for all species registered in the miRBASE version 16.0. Real-time PCR (qRT-PCR) using appropriate endogenous controls was performed in order to validate the microarray results of the 27 most differentially expressed (DE) miRNAs. We identified 434 miRNAs that were significantly deregulated in all kidney tumours compared to the normal tissues. A total of 126 miRNAs (29%) had increased expression while 303 (69.8%) had decreased expression in RCC. Out of the 434 DE miRNAs, we detected 94 co-up-regulated and 218 co-down-regulated microRNAs among chRCC, papRCC and ccRCC. Of these, 89 and 203 were co-up- and co-down-regulated between RCCs and UUT-UCCs, respectively. We detected 11, 44 and 24 up-regulated miRNAs, which were specific for ccRCC, chRCC and papRCC, respectively. Moreover, 19, 18 and 8 miRNAs were uniquelly down-regulated in ccRCC, chRCC and papRCC, respectively. We also detected 89 and 203 co-up- and co-down-regulated miRNAs between kidney cancer and UUT-UCCs. Five miRNAs were up-regulated specifically in renal tumours and 49 in UUT-UCCs, whereas 15 miRNAs were down-regulated specifically in renal tumours and 89 in UUT-UCCs, respectively. Our data validicate that expression of miRNAs tends to be down-regulated renal cell carcinomas compared with normal kidney. We used 18 ccRCC, 3 chRCC, 5 papRCC, 4 UUT-UCC, 1 undifferentiated carcinoma and 19 normal tissue samples for miRNA profiling. Total RNA (0.5 M-BM-5g) from each sample and reference was labeled with Hy3M-bM-^DM-" fluorescent label, using the miRCURY LNAM-bM-^DM-" microRNA Hi-Power Labeling Kit (Exiqon, Woburn MA). The Hy3M-bM-^DM-\"-labeled samples were hybridized to the miRCURY LNAM-bM-^DM-" microRNA Array, 6th gen (Exiqon, Woburn MA), using an Agilent hybridization SureHyb chamber and gasket slide kits. After hybridization, the microarray slides were scanned at 10 M-NM-<m using the High-Resolution Microarray Scanner (Agilent Technologies) and stored in an ozone free environment. The image analysis was carried out using the ImaGene 8.0 software (BioDiscovery, Inc., USA). Raw microarray data were filtered, background corrected and quantile normalizated. Normalized data were further extracted, pre-processed and sorted with Microsoft ExcelM-BM-.. MicroRNAs were considered to be significantly differentially expressed if they obtained a p-value<0.05 and a FDRM-bM-^IM-$0.05.

Project description:Traditional serrated adenoma (TSA) remains the least understood of all the colorectal adenomas although these lesions have been associated with a significant cancer risk- twice that of the conventional adenoma (CAD) and of the sessile serrated adenoma (SSA/P). This study was performed to investigate the proteomic profiles of the different colorectal adenomas to better assess the pathogenesis of TSA. We performed a global quantitative expression profile of 44 colorectal adenomas (12 TSA, 15 CAD, 17 SSA/Ps) and 17 normal colonic mucosa, conserved as formalin-fixed paraffin-embedded samples, by the label-free quantification (LFQ) method. Unsupervised consensus hierarchical clustering applied to the whole proteomic profile of the 44 colorectal adenomas identified four subtypes. The C1 and C2 were well-individualized clusters composed of most of the CAD (14/15) and most of the SSA (13/17) respectively. This is consistent with the fact that CAD and SSA/Ps are homogeneous but distinct colorectal adenoma entities. In contrast, TSA were subdivided into C3 and C4 clusters that also contained CAD and SSA/Ps, consistent with the more heterogeneous entity of TSA at the morphological and molecular levels. The comparison of the proteome expression profile between the adenoma subtypes and normal colonic mucosa further confirmed the heterogeneous nature of TSA that merged either on CAD or SSA, while CAD and TSA formed homogeneous and distinct entities. Furthermore, we identified LEFTY1 a new potential marker for TSA that may be relevant for the TSA pathogenesis. LEFTY1 is an inhibitor of the Nodal/TGFb pathway that we found to be one of the most overexpressed proteins specifically in the TSA and confirmed by immunohistochemistry. Taken together, our study confirms that CAD and SSA form homogenous but distinct colorectal adenoma entities while TSA are an heterogeneous entity and may arise from either SSA or from normal mucosa that will evolve along the conventional adenoma pathway.

Dataset Information

Cross-omics analysis of archival human renal cell carcinoma biopsies to identify emerging treatment avenues

Publications

Transcriptome-proteome integration of archival human renal cell carcinoma biopsies enables identification of molecular mechanisms.

Similar Datasets

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