A novel 10 glycolysis-related genes signature could predict overall survival for clear cell renal cell carcinoma

Xing, Qianwei; Zeng, Taidui; Liu, Shouyong; Cheng, Hong; Ma, Limin; Wang, Yi

doi:10.1186/s12885-021-08111-0

Cited by 28 publications

(25 citation statements)

References 34 publications

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“…In line with our findings, overexpression of HS6ST2 has been found to be a poor prognostic factor in several malignant tumors [ 20 , 24 , 30 , 31 , 32 , 33 ]. Interestingly, HS6ST2 has been recently described as part of a novel 10 glycolysis-related gene signature to predict overall survival in ccRCC [ 34 ]. Liep et al [ 35 ] found that overexpression of miR-145-5p and miR-141-3p could inhibit the migration and invasion of RCC cells by decreasing HS6ST2 expression in cellular transfection experiments.…”

Section: Discussionmentioning

confidence: 99%

Clinicopathological and Molecular Prognostic Classifier for Intermediate/High-Risk Clear Cell Renal Cell Carcinoma

Roldán

Lozano

Ingelmo-Torres

et al. 2021

Cancers

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The probability of tumor progression in intermediate/high-risk clear cell renal cell carcinoma (ccRCC) is highly variable, underlining the lack of predictive accuracy of the current clinicopathological factors. To develop an accurate prognostic classifier for these patients, we analyzed global gene expression patterns in 13 tissue samples from progressive and non-progressive ccRCC using Illumina Hi-seq 4000. Expression levels of 22 selected differentially expressed genes (DEG) were assessed by nCounter analysis in an independent series of 71 ccRCCs. A clinicopathological-molecular model for predicting tumor progression was developed and in silico validated in a total of 202 ccRCC patients using the TCGA cohort. A total of 1202 DEGs were found between progressive and non-progressive intermediate/high-risk ccRCC in RNAseq analysis, and seven of the 22 DEGs selected were validated by nCounter. Expression of HS6ST2, pT stage, tumor size, and ISUP grade were found to be independent prognostic factors for tumor progression. A risk score generated using these variables was able to distinguish patients at higher risk of tumor progression (HR 7.27; p < 0.001), consistent with the results obtained from the TCGA cohort (HR 2.74; p < 0.002). In summary, a combined prognostic algorithm was successfully developed and validated. This model may aid physicians to select high-risk patients for adjuvant therapy.

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Section: Discussionmentioning

confidence: 99%

Clinicopathological and Molecular Prognostic Classifier for Intermediate/High-Risk Clear Cell Renal Cell Carcinoma

Roldán

Lozano

Ingelmo-Torres

et al. 2021

Cancers

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“…Considering the individual heterogeneity of the TME, it is urgent to quantify the scoring pattern of individual tumours and establish an effective treatment and prognosis evaluation model for patients with ccRCC. Although previous studies have explored the value of different signatures in the prognostic evaluation of ccRCC, their validity remains limited ( 31 , 32 ). Meanwhile, the analysis of cell-cell communication reveals that the expression of ligands and receptors and the type of interaction vary in different tumour types.…”

Section: Discussionmentioning

confidence: 99%

Identification of Ligand-Receptor Pairs Associated With Tumour Characteristics in Clear Cell Renal Cell Carcinoma

et al. 2022

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The tumour microenvironment (TME) of clear cell renal cell carcinoma (ccRCC) comprises multiple cell types, which promote tumour progression and modulate drug resistance and immune cell infiltrations via ligand-receptor (LR) interactions. However, the interactions, expression patterns, and clinical relevance of LR in the TME in ccRCC are insufficiently characterised. This study characterises the complex composition of the TME in ccRCC by analysing the single-cell sequencing (scRNA-seq) data of patients with ccRCC from the Gene expression omnibus database. On analysing the scRNA-seq data combined with the cancer genome atlas kidney renal clear cell carcinoma (TCGA-KIRC) dataset, 46 LR-pairs were identified that were significantly correlated and had prognostic values. Furthermore, a new molecular subtyping model was proposed based on these 46 LR-pairs. Molecular subtyping was performed in two ccRCC cohorts, revealing significant differences in prognosis between the subtypes of the two ccRCC cohorts. Different molecular subtypes exhibited different clinicopathological features, mutational, pathway, and immune signatures. Finally, the LR.score model that was constructed using ten essential LR-pairs that were identified based on LASSO Cox regression analysis revealed that the model could accurately predict the prognosis of patients with ccRCC. In addition, the differential expression of ten LR-pairs in tumour and normal cell lines was identified. Further functional experiments showed that CX3CL1 can exert anti-tumorigenic role in ccRCC cell line. Altogether, the effects of immunotherapy were connected to LR.scores, indicating that potential medications targeting these LR-pairs could contribute to the clinical benefit of immunotherapy. Therefore, this study identifies LR-pairs that could be effective biomarkers and predictors for molecular subtyping and immunotherapy effects in ccRCC. Targeting LR-pairs provides a new direction for immunotherapy regimens and prognostic evaluations in ccRCC.

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“…Notably, Wu et al reported that redox-related genes were associated with immune infiltration and could accurately predict ccRCC prognosis (39). Xing et al identified 10 glycolysisrelated genes that predicted OS for ccRCC patients (40).…”

Section: Discussionmentioning

confidence: 99%

PANK1 associates with cancer metabolism and immune infiltration in clear cell renal cell carcinoma: a retrospective prognostic study based on the TCGA database

Wang¹,

Liu²,

Luo³

et al. 2022

Transl Cancer Res TCR

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Background: Identify key biomarkers to improve the clinical prognosis of patients with advanced and metastatic clear cell renal cell carcinoma (ccRCC) remains an important research topic. Recently, ccRCC has been regarded as a metabolic disease. Pantothenate kinase-1 (PANK1) has been shown to play an important regulatory role in global metabolism and associates with the pathogenesis of hepatocellular carcinoma. Therefore, we aimed to investigate the role of PANK1 in the prognosis of ccRCC and in metabolism and immunity. Methods: PANK1 messenger ribonucleic acid (RNA) expression patterns in ccRCC using The Cancer Genome Atlas (TCGA) database. The clinical prognostic significance of PANK1 in ccRCC and a Cox regression was performed to evaluate the clinical factors associated with prognosis with confounding factors adjusted. The signaling pathways related to PANK1 expression were identified by Gene Ontology (GO) investigation and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis. The Tumor Immune Estimation Resource database was used to analyze the correlation between PANK1 and tumor-infiltrating immune cells.Results: A total of 539 ccRCC patients and corresponding clinical samples and data from TCGA were included in this analysis. Significant differences were observed in PANK1 expression levels between tumor tissues and adjacent normal tissues in both TCGA-Kidney Renal Clear Cell Carcinoma cohort (4.40 vs.2.94, P<0.001). PANK1 expression was found to be correlated with pathological stage, histological grade, age, sex, and clinical prognosis. Specifically, the low expression of PANK1 was found to be closely related to poor overall survival (OS), disease-specific survival (DSS), and the progression-free survival (PFS) in ccRCC patients. The receiver operating characteristic curve suggested that PANK1 could be a potential prognostic biomarker (area under the curve =0.880), and that the promoter methylation levels of PANK1 were correlated with clinical factors. Further, PANK1 expression was found to be associated with multiple immune cell types and correlated with the enrichment of these cells. Finally, we further investigated the role of PANK1 in tumor growth and mitochondrial metabolism using ccRCC cells.Conclusions: PANK1 correlates with ccRCC prognosis, tumor immune status and metabolism using the TGCA data. PANK1 might be a prognostic marker of clinical prognosis for ccRCC patients. the following article in accordance with the TRIPOD reporting checklist (available at https://tcr.amegroups.com/ article/view/10.21037/tcr-22-1488/rc). Methods Study design and research proceduresThis study is a retrospective prognostic study analyzing the expression difference of PANK1 between tumor and adjacent normal tissues, correlations with the clinical factors, overall

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A novel 10 glycolysis-related genes signature could predict overall survival for clear cell renal cell carcinoma

Cited by 28 publications

References 34 publications

Clinicopathological and Molecular Prognostic Classifier for Intermediate/High-Risk Clear Cell Renal Cell Carcinoma

Clinicopathological and Molecular Prognostic Classifier for Intermediate/High-Risk Clear Cell Renal Cell Carcinoma

Identification of Ligand-Receptor Pairs Associated With Tumour Characteristics in Clear Cell Renal Cell Carcinoma

PANK1 associates with cancer metabolism and immune infiltration in clear cell renal cell carcinoma: a retrospective prognostic study based on the TCGA database

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