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ABSTRACT:
PROVIDER: PRJNA130933 | ENA |
REPOSITORIES: ENA
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Project description:Background: Advanced Renal cell carcinoma (RCC) is therapeutically challenging. RCC progression is facilitated by mesenchymal stem/stromal cells (MSCs) that exert remarkable tumor tropism. The specific mechanisms mediating MSCs’ migration to RCC remain unknown. Here, we comprehensively analyzed RCC secretome to identify MSCs attractants. Methods: Conditioned media (CM) were collected from five RCC-derived cell lines (Caki-1, 786-O, A498, KIJ265T, KIJ308T) and non-tumorous control cell line (RPTEC/TERT1) and analyzed using cytokine arrays targeting 274 cytokines in addition to global CM proteomics. MSCs were isolated from bone marrow of patients undergoing standard orthopedic surgeries. RCC CM and the selected recombinant cytokines were used to analyze their influence on MSCs migration and microarray-targeted gene expression. The expression of genes encoding cytokines was evaluated in 100 matched-paired control-RCC tumor samples. Results: When compared with normal cells, CM from advanced RCC cell lines (Caki-1, KIJ265T) were the strongest stimulators of MSCs migration. Targeted analysis of 274 cytokines and global proteomics of RCC CM revealed decreased DPP4 and EGF, as well as increased AREG, FN1, and MMP1, with consistently altered gene expression in RCC cell lines and tumors. AREG and FN1 stimulated, while DPP4 attenuated MSCs migration. RCC CM induced MSCs’ transcriptional reprogramming, stimulating the expression of CD44, PTX3, and RAB27B. RCC cells secreted hyaluronic acid (HA), a CD44 ligand mediating MSCs’ homing to the kidney. AREG emerged as an upregulator of MSCs’ transcription. Conclusions: advanced RCC cells secrete AREG, FN1 and HA to induce MSCs migration, while DPP4 loss prevents its inhibitory effect on MSCs homing. RCC secretome induces MSCs’ transcriptional reprograming to facilitate their migration. The identified components of RCC secretome represent potential therapeutic targets. We used microarrays to determine the effect of the conditioned media (CM) collected from two RCC-derived cell lines (Caki-1, KIJ265T) and non-tumorous control cell line (RPTEC/TERT1) on the transcriptome change in mesenchymal stem/stromal cells (MSCs).
2023-07-18 | GSE232951 | GEO
Project description:Expression data from RCC paired tumors to study metastasis progression
| PRJNA133357 | ENA
Project description:Immune checkpoint blockade (ICB) demonstrates durable clinical benefit only in a minority of renal cell carcinoma (RCC) patients. Identifying molecular features that determine response and developing approaches to enhance the response remain an urgent clinical need. Here we found that, in multiple RCC cell lines, targeting the ATR-CHK1 axis with pharmacological inhibitors increased cytosolic DNA accumulation, activated the cGAS-IRF3-dependent cytosolic DNA sensing pathway, and resulted in the inflammatory cytokine expression. SETD2 mutated RCC cell lines or tumor samples were associated with preferential ATR-CHK1 activation over ATM-CHK2 activation. SETD2 knockdown promoted the cytosolic DNA sensing pathway and conferred greater sensitivity in response to ATR-CHK1 inhibition. In murine Renca tumors, Setd2 knockdown and ATR inhibitor VE822 synergistically promoted cytosolic DNA sensing pathway, immune cell infiltration, and immune checkpoint protein expression. Setd2 deficient Renca tumors demonstrated greater vulnerability to ICB monotherapy or in combination with VE822 than Setd2 proficient tumors. SETD2 mutations were associated with a higher response rate and prolonged overall survival in ICB-treated RCC patients, but not in non-ICB-treated RCC patients. This study provides a mechanism-based guidance to develop more personalized combination therapy regimens for RCC patients with SETD2 mutations.
2023-07-25 | GSE234732 | GEO
Project description:Background: Renal cell carcinoma (RCC) is characterized by a number of diverse molecular aberrations that differ among individuals. Recent approaches to molecularly classify RCC were based on clinical, pathological as well as on single molecular parameters. As a consequence, gene expression patterns reflecting the sum of genetic aberrations in individual tumors may not have been recognized. In an attempt to uncover such molecular features in RCC, we used a novel, unbiased and integrative approach. Methods: We integrated gene expression data from 97 primary RCCs of different pathologic parameters, 15 RCC metastases as well as 34 cancer cell lines for two-way nonsupervised hierarchical clustering using gene groups suggested by the PANTHER Classification System. We depicted the genomic landscape of the resulted tumor groups by means of Single Nuclear Polymorphism (SNP) technology. Finally, the achieved results were immunohistochemically analyzed using a tissue microarray (TMA) composed of 254 RCC. Results: We found robust, genome wide expression signatures, which split RCC into three distinct molecular subgroups. These groups remained stable even if randomly selected gene sets were clustered. Notably, the pattern obtained from RCC cell lines was clearly distinguishable from that of primary tumors. SNP array analysis demonstrated differing frequencies of chromosomal copy number alterations among RCC subgroups. TMA analysis with group-specific markers showed a prognostic significance of the different groups. Conclusion: We propose the existence of characteristic and histologically independent genome-wide expression outputs in RCC with potential biological and clinical relevance.
2012-07-24 | GSE19949 | GEO
Project description:This study investigates the molecular signatures that drive Renal Cell Carcinoma (RCC) metastatic conversion using the metastatic (LM2) and non-metastatic (SN12C) RCC cell lines.
2010-08-17 | GSE23633 | GEO
Project description:Analysis of the small non-coding RNA expression profile in cell-free serum RNA of patients with clear cell renal cell carcinoma (RCC) and patients with benign renal tumors (BRT) in order to identify novel non-invasive biomarkers for patients with RCC. Aims: (1) to compare the expression profile of patients with RCC and BRT. (2) to compare the expression profile of patients with localized (M=0) and metastatic (M=1) RCC.
2017-11-18 | GSE85699 | GEO
Project description:This study investigates for the miRNAs that drive or regulates Renal Cell Carcinoma (RCC) metastatic progression using two different RCC cell lines, the metastatic (LM2 and LM1) and non-metastatic (SN12C).
2010-08-19 | GSE23690 | GEO
Project description:PBRM1 was found to be mutated in a high percentage of clear cell RCCs. We performed knockdown of PBRM1 via siRNA and compared with scrambled control in three different RCC cell lines. PBRM1 siRNA and mock treated cell lines were normalized together with 'hypoxic' clear cell renal tumors and normal renal tissue samples from GSE17818.
2011-01-20 | E-GEOD-22316 | biostudies-arrayexpress
Project description:Background: Renal cell carcinoma (RCC) is characterized by a number of diverse molecular aberrations that differ among individuals. Recent approaches to molecularly classify RCC were based on clinical, pathological as well as on single molecular parameters. As a consequence, gene expression patterns reflecting the sum of genetic aberrations in individual tumors may not have been recognized. In an attempt to uncover such molecular features in RCC, we used a novel, unbiased and integrative approach. Methods: We integrated gene expression data from 97 primary RCCs of different pathologic parameters, 15 RCC metastases as well as 34 cancer cell lines for two-way nonsupervised hierarchical clustering using gene groups suggested by the PANTHER Classification System. We depicted the genomic landscape of the resulted tumor groups by means of Single Nuclear Polymorphism (SNP) technology. Finally, the achieved results were immunohistochemically analyzed using a tissue microarray (TMA) composed of 254 RCC. Results: We found robust, genome wide expression signatures, which split RCC into three distinct molecular subgroups. These groups remained stable even if randomly selected gene sets were clustered. Notably, the pattern obtained from RCC cell lines was clearly distinguishable from that of primary tumors. SNP array analysis demonstrated differing frequencies of chromosomal copy number alterations among RCC subgroups. TMA analysis with group-specific markers showed a prognostic significance of the different groups. Conclusion: We propose the existence of characteristic and histologically independent genome-wide expression outputs in RCC with potential biological and clinical relevance. Expression profiling by array, combined data analysis with genomic profiling data. Genomic DNA from renal cell was hybridized to renal cell carcinoma samples and matched normal kidney tissue biopsies, using the Affymetrix GenomewideSNP_6 platform. CEL files were processed using R, Bioconductor and software from the aroma.affymetrix project. Visualized Copy number profiles are accessible through the Progenetix site (www.progenetix.net). CN,raw.csv and segments.csv: Probes are mapped by their position in genome build 36 / HG18. Probes are ordered according to their linear position on the Golden Path.
2012-07-23 | E-GEOD-19949 | biostudies-arrayexpress