Dataset Information

Systematic evaluation of the prognostic impact and intratumour heterogeneity of clear cell renal cell carcinoma biomarkers.

ABSTRACT:

Background

Candidate biomarkers have been identified for clear cell renal cell carcinoma (ccRCC) patients, but most have not been validated.

Objective

To validate published ccRCC prognostic biomarkers in an independent patient cohort and to assess intratumour heterogeneity (ITH) of the most promising markers to guide biomarker optimisation.

Design, setting, and participants

Cancer-specific survival (CSS) for each of 28 identified genetic or transcriptomic biomarkers was assessed in 350 ccRCC patients. ITH was interrogated in a multiregion biopsy data set of 10 ccRCCs.

Outcome measurements and statistical analysis

Biomarker association with CSS was analysed by univariate and multivariate analyses.

Results and limitations

A total of 17 of 28 biomarkers (TP53 mutations; amplifications of chromosomes 8q, 12, 20q11.21q13.32, and 20 and deletions of 4p, 9p, 9p21.3p24.1, and 22q; low EDNRB and TSPAN7 expression and six gene expression signatures) were validated as predictors of poor CSS in univariate analysis. Tumour stage and the ccB expression signature were the only independent predictors in multivariate analysis. ITH of the ccB signature was identified in 8 of 10 tumours. Several genetic alterations that were significant in univariate analysis were enriched, and chromosomal instability indices were increased in samples expressing the ccB signature. The study may be underpowered to validate low-prevalence biomarkers.

Conclusions

The ccB signature was the only independent prognostic biomarker. Enrichment of multiple poor prognosis genetic alterations in ccB samples indicated that several events may be required to establish this aggressive phenotype, catalysed in some tumours by chromosomal instability. Multiregion assessment may improve the precision of this biomarker.

Patient summary

We evaluated the ability of published biomarkers to predict the survival of patients with clear cell kidney cancer in an independent patient cohort. Only one molecular test adds prognostic information to routine clinical assessments. This marker showed good and poor prognosis results within most individual cancers. Future biomarkers need to consider variation within tumours to improve accuracy.

SUBMITTER: Gulati S

PROVIDER: S-EPMC4410302 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:Clear cell renal cell carcinoma (ccRCC) is the most common lethal subtype of renal cancer, and changes in tumor metabolism play a key role in its development. Solute carriers (SLCs) are important in the transport of small molecules in humans, and defects in SLC transporters can lead to serious diseases. The expression patterns and prognostic values of SLC family transporters in the development of ccRCC are still unclear. The current study analyzed the expression levels of SLC family members and their correlation with prognosis in ccRCC patients with data from Oncomine, Gene Expression Profiling Interactive Analysis (GEPIA), The Cancer Genome Atlas (TCGA), cBioPortal, the Human Protein Atlas (HPA), the International Cancer Genome Consortium (ICGC), and the Gene Expression Omnibus (GEO). We found that the mRNA expression levels of SLC22A6, SLC22A7, SLC22A13, SLC25A4, SLC34A1, and SLC44A4 were significantly lower in ccRCC tissues than in normal tissues and the protein expression levels of SLC22A6, SLC22A7, SLC22A13, and SLC34A1 were also significantly lower. Except for SLC22A7, the expression levels of SLC22A6, SLC22A13, SLC25A4, SLC34A1, and SLC44A4 were correlated with the clinical stage of ccRCC patients. The lower the expression levels of SLC22A6, SLC22A13, SLC25A4, SLC34A1, and SLC44A4 were, the later the clinical stage of ccRCC patients was. Further experiments revealed that the expression levels of SLC22A6, SLC22A7, SLC22A13, SLC25A4, SLC34A1, and SLC44A4 were significantly associated with overall survival (OS) and disease-free survival (DFS) in ccRCC patients. High SLC22A6, SLC22A7, SLC22A13, SLC25A4, SLC34A1, and SLC44A4 expression predicted improved OS and DFS. Finally, GSE53757 and ICGC were used to revalidate the differential expression and clinical prognostic value. This study suggests that SLC22A6, SLC22A7, SLC22A13, SLC25A4, SLC34A1, and SLC44A4 may be potential targets for the clinical diagnosis, prognosis, and treatment of ccRCC patients.

Project description:BackgroundThe interplay between tumor-infiltrating immune cells and cancer cells affects cancer initiation, progression, and treatment. C chemokines are critically involved in immune cell chemotaxis, self-tolerance formation, antigen cross-presentation, and cytotoxic immune response. However, their roles in cancer development are still largely unknown.MethodsWe comprehensively analyzed the expression, prognostic value, functions, and immune implication of C chemokines in clear cell renal cell carcinoma (ccRCC) using multiple databases. Besides, we detected the expression of C chemokines in RCC cell lines using quantitative real-time polymerase chain reaction (qPCR).ResultsThrough analyzing The Cancer Genome Atlas (TCGA), Oncomine and Gene Expression Omnibus (GEO) ccRCC datasets, we found that C chemokines were significantly upregulated in ccRCC tumor tissues and associated with tumor progression. Besides, qPCR revealed the overexpression of C chemokines in RCC cell lines. Promoter hypomethylation was a potential factor causing the upregulation of C chemokines. ccRCC patients with higher levels of C chemokines had significantly poorer overall survival (OS), progression-free interval (PFI), and disease-speciﬁc survival (DSS). C chemokines and related genes were involved mainly in cytokine-cytokine receptor interactions and the chemokine signaling and Toll-like receptor signaling pathways. Correlation analysis revealed a positive correlation between C chemokines and the infiltration of 25 immune cell subtypes, many of which affected the prognosis of ccRCC. Moreover, C chemokines were positively correlated with the expression of genes associated with M2 macrophage polarization and T-cell exhaustion, and the expression of several immune checkpoints in ccRCC.ConclusionsOur research provides preliminary insights into the prognostic value and immune implication of C chemokines in ccRCC, which is conducive to the prediction of survival and immunotherapy response, and the development of novel therapeutic targets for ccRCC.

Project description:BackgroundThe immune microenvironment is a critical regulator of clear cell renal cell carcinoma (ccRCC) progression. However, the underlying mechanisms the regulatory role of immune-related long non-coding RNAs (irlncRNAs) in the ccRCC tumor microenvironment (TME) are still obscure. Herein, we investigated prognostics role of irlncRNAs for ccRCC.MethodsThe raw data of patients with ccRCC were downloaded from The Cancer Genome Atlas (TCGA) database, and immune-related genes were obtained from the ImmPort database. First, we investigated the correlation between the immune-related genes and irlncRNAs. Then, we identified the differentially expressed irlncRNA pairs (ILRPs) between normal and cancer tissue samples, and prognostic model was constructed with the differentially expressed ILRPs. We further explored whether the signature risk scores of ILRPs had a considerable impact on immune cell infiltration. Finally, we performed a drug sensitivity analysis based on risk score.ResultsThere were 13 upregulated and 40 downregulated irlncRNAs between the ccRCC and normal tissue samples. We further selected the irlncRNAs that significantly affect the prognosis of patients with ccRCC via univariate Cox, lasso regression, and multivariate regression analyses. Twelve ILRPs were used to construct a prognostic signature. The model showed the ILRPs model could be used to assess the prognosis of ccRCC patients. Study of the influence of risk score and clinical characteristics on the prognosis of patients with ccRCC showed risk score to be an independent factor affecting the outcome of ccRCC. We further performed the difference analysis of immune cell abundance between ccRCC and normal tissue samples. The results showed that patients with higher abundance of M0 macrophages, plasma cells, follicular helper T cells, and regulatory T cells (Tregs) had a poor outcome. Finally, we performed a drug sensitivity analysis based on risk score. The results showed that high-risk score patients are sensitive to orafenib, sunitinib, temsirolimus, cisplatin, and gemcitabine.ConclusionsOur study has developed a novel and reasonable ILPRs model for prognostic prediction, which does not require transcriptional levels to be detected.