Differential gene expression profiling of matched primary renal cell carcinoma and metastases reveals upregulation of extracellular matrix genes

Abstract

Background: The majority of renal cell carcinoma (RCC) studies analyze primary tumors, and the corresponding results are extrapolated to metastatic RCC tumors. However, it is unknown if gene expression profiles from primary RCC tumors differs from patient-matched metastatic tumors. Thus, we sought to identify differentially expressed genes between patient-matched primary and metastatic RCC tumors in order to understand the molecular mechanisms underlying the development of RCC metastases. Patients and methods:We compared gene expression profiles between patient-matched primary and metastatic RCC tumors using a two-stage design. First, we used Affymetrix microarrays on 15 pairs of primary RCC [14 clear cell RCC (ccRCC), 1 papillary] tumors and patient-matched pulmonary metastases. Second, we used a custom NanoString panel to validate seven candidate genes in an independent cohort of 114 ccRCC patients. Differential gene expression was evaluated using a mixed effect linear model; a random effect denoting patient was included to account for the paired data. Third, The Cancer Genome Atlas (TCGA) data were used to evaluate associations with metastasis-free and overall survival in primary ccRCC tumors.Results: We identified and validated up regulation of seven genes functionally involved in the formation of the extracellular matrix (ECM): DCN, SLIT2, LUM, LAMA2, ADAMTS12, CEACAM6 and LMO3. In primary ccRCC, CEACAM6 and LUM were significantly associated with metastasis-free and overall survival (P < 0.01). Conclusions:We evaluated gene expression profiles using the largest set to date, to our knowledge, of patient-matched primary and metastatic ccRCC tumors and identified up regulation of ECM genes in metastases. Our study implicates up regulation of ECM genes as a critical molecular event leading to visceral, bone and soft tissue metastases in ccRCC.

The Genes—Candidates for Prognostic Markers of Metastasis by Expression Level in Clear Cell Renal Cell Cancer

“…The received data was not validated. Expression profiles were also compared on kidney cancer samples and lung metastases using Affymetrix microarrays to identify genes that could potentially be targets of therapy [61]. Gene expression profiles were studied using microarrays on cultured metastatic RCC (ACHN) and primary RCC (CAKI-2) cell lines, to identify and analyze cancer stem cells [62].…”

Integrative Radiogenomics Approach for Risk Assessment of Post-Operative Metastasis in Pathological T1 Renal Cell Carcinoma: A Pilot Retrospective Cohort Study

“…The aberrant overexpression of key proteins via cap-dependent mRNA translation is known to be a requisite for tumor progression and metastasis via the strong activation of the eukaryotic initiation factor (eIF) 4E-binding protein 1 (4EBP1/eIF4E) axis in RCC [41]. Furthermore, an ECM remodeling program and an ECM-receptor interaction pathway facilitate cell survival, angiogenesis, EMT, and metastasis of RCC via the subsequent activation of the focal adhesion kinase (FAK)/c-Jun N-terminal kinase pathway and PI3K/AKT pathway [42][43][44]. Finally, cytoskeletal-rearrangement-associated proteins rearrange the actin cytoskeleton driving cell cycle progression, invasiveness, and EMT [45][46][47].…”

Integrative Epigenetic and Gene Expression Analysis of Renal Tumor Progression to Metastasis

“…Despite the difference in prognosis between localized and metastatic disease, datasets examining metastatic tumor deposits in the context of RCC are generally lacking. Although prior studies from our group and others have performed transcriptomic analyses of primary and metastatic sites, molecular analyses using epigenetic profiling platforms were not performed (14,39,40). A recent study analyzed the transcriptomes and methylomes of both primary and metastatic RCC samples with a focus on pharmacogenes; however, normal samples were not included in the analysis (11).…”