A cluster of metabolism-related genes predict prognosis and progression of clear cell renal cell carcinoma

Liu, Mei; Pan, Qiufeng; Xiao, Ruihai; Yu, Yi; Lu, Wenbao; Wang, Longwang

doi:10.1038/s41598-020-67760-6

Cited by 26 publications

(22 citation statements)

References 38 publications

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“…IL4I1 was strongly detected in the tumor bed of most human tumor types [ 44 ] and was identified as a prognostic biomarker [ 45 , 46 ]. Our results were similar with them.…”

Section: Discussionmentioning

confidence: 99%

Single-cell analysis revealed that IL4I1 promoted ovarian cancer progression

et al. 2021

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Background Ovarian cancer was one of the leading causes of female deaths. Patients with OC were essentially incurable and portends a poor prognosis, presumably because of profound genetic heterogeneity limiting reproducible prognostic classifications. Methods We comprehensively analyzed an ovarian cancer single-cell RNA sequencing dataset, GSE118828, and identified nine major cell types. Relationship between the clusters was explored with CellPhoneDB. A malignant epithelial cluster was confirmed using pseudotime analysis, CNV and GSVA. Furthermore, we constructed the prediction model (i.e., RiskScore) consisted of 10 prognosis-specific genes from 2397 malignant epithelial genes using the LASSO Cox regression algorithm based on public datasets. Then, the prognostic value of Riskscore was assessed with Kaplan–Meier survival analysis and time-dependent ROC curves. At last, a series of in-vitro assays were conducted to explore the roles of IL4I1, an important gene in Riskscore, in OC progression. Results We found that macrophages possessed the most interaction pairs with other clusters, and M2-like TAMs were the dominant type of macrophages. C0 was identified as the malignant epithelial cluster. Patients with a lower RiskScore had a greater OS (log-rank P < 0.01). In training set, the AUC of RiskScore was 0.666, 0.743 and 0.809 in 1-year, 3-year and 5-year survival, respectively. This was also validated in another two cohorts. Moreover, downregulation of IL4I1 inhibited OC cells proliferation, migration and invasion. Conclusions Our work provide novel insights into our understanding of the heterogeneity among OCs, and would help elucidate the biology of OC and provide clinical guidance in prognosis for OC patients.

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“…IL4I1 was strongly detected in the tumor bed of most human tumor types [ 44 ] and was identified as a prognostic biomarker [ 45 , 46 ]. Our results were similar with them.…”

Section: Discussionmentioning

confidence: 99%

Single-cell analysis revealed that IL4I1 promoted ovarian cancer progression

et al. 2021

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“…Together with our report here, the search for ccRCC biomarkers has shown promising progress lately. Based on the metabolic feature of ccRCC, a 10-gene set was recently reported, which predicts ccRCC OS [ 62 ]. A set of 10 mRNAs and a group of 10 lncRNAs have been demonstrated to significantly assess OS possibility [ 63 ].…”

Section: Discussionmentioning

confidence: 99%

Construction of a Novel Multigene Panel Potently Predicting Poor Prognosis in Patients with Clear Cell Renal Cell Carcinoma

Lin

Kapoor

et al. 2020

Cancers

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We observed associations of IQGAP1 downregulation with poor overall survival (OS) in clear cell renal cell carcinoma (ccRCC). Differentially expressed genes (DEGs, n = 611) were derived from ccRCCs with (n = 111) and without IQGAP1 (n = 397) reduction using the TCGA PanCancer Atlas ccRCC dataset. These DEGs exhibit downregulations of immune response and upregulations of DNA damage repair pathways. Through randomization of the TCGA dataset into a training and testing subpopulation, a 9-gene panel (SigIQGAP1NW) was derived; it predicts poor OS in training, testing, and the full population at a hazard ratio (HR) 2.718, p < 2 × 10−16, p = 1.08 × 10−5, and p < 2 × 10−16, respectively. SigIQGAP1NW independently associates with poor OS (HR 1.80, p = 2.85 × 10−6) after adjusting for a set of clinical features, and it discriminates ccRCC mortality at time-dependent AUC values of 70% at 13.8 months, 69%/31M, 69%/49M, and 75.3%/71M. All nine component genes of SigIQGAP1NW are novel to ccRCC. The inclusion of RECQL4 (a DNA helicase) in SigIQGAP1NW agrees with IQGAP1 DEGs enhancing DNA repair. THSD7A affects kidney function; its presence in SigIQGAP1NW is consistent with our observed THSD7A downregulation in ccRCC (n = 523) compared to non-tumor kidney tissues (n = 100). Collectively, we report a novel multigene panel that robustly predicts poor OS in ccRCC.

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“…Over the past few years, various prognostic models have been constructed for the underlying mechanism of KIRC based on metabolism-related genes, long non-coding RNAs, alternative splicing variants, immunerelated genes, RNA binding proteins, microRNA related genes, and autophagy-related genes [14][15][16][17][18][19][20]. In our current study, the independent prognostic value of STON1 was validated using online bioinformatics databases.…”

Section: Introductionmentioning

confidence: 97%

Integrated analysis of the underlying immunomodulator and survival signature of STON1 gene in kidney renal clear cell carcinoma

Zheng

Bai

et al. 2021

Preprint

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Background Stonin 1 (STON1) is an endocytic protein but its role in cancer remains unclear. Here, we investigated the role of STON1 in kidney renal clear cell carcinoma (KIRC). Methods We undertook bioinformatics analyses of a series of public databases to determine the expression and clinical significance of STON1 in KIRC and focused on STON1-related immunomodulator and survival signatures. A nomogram model integrating clinicopathological characteristics and risk scores for KIRC was established and validated. Results Through TGCA and GEO databases, STON1 mRNA was found to be significantly downregulated in KIRC compared with normal controls, and decreased STON1 was related to grade, TNM stage, distant metastasis, and vital status of KIRC. Furthermore, OncoLnc, UALCAN, Kaplan–Meier, and GEPIA2 analyses supported that KIRC patients with high STON1 expression had better overall survival. STON1 was positively associated with mismatch proteins including MLH1, PMS2, MSH2, MSH6 and EpCAM, and was negatively correlated with tumor mutational burden. Interestingly, arm-level deletion of STON1 was clearly related to the abundance of immune cells and the infiltration abundance in the majority of 26 immune cell types that were positively related to STON1 mRNA level in the TIMER database. The TISIDB database revealed 21 immunostimulators and 10 immunoinhibitors that were obviously related to STON1 in KIRC. In univariate and multivariate Cox regression analyses, CTLA4 , KDR , LAG3 , PDCD1 , HHLA2 , TNFRSF25 , and TNFSF14 were screened to establish a risk score model, and the low-risk group had a better prognosis for KIRC. Furthermore, a nomogram integrating clinicopathological characteristics and risk score had better accuracy and practicability in predicating the survival of KIRC patients. Conclusions Decreased STON1 expression in KIRC leads to clinical progression and poor survival. Mechanically, loss of STON1 is associated with the aberrant immune microenvironment in KIRC. Integrated clinicopathological characteristics and risk score derived from STON1 -related immunomodulators can aid the prediction of KIRC survival.

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A cluster of metabolism-related genes predict prognosis and progression of clear cell renal cell carcinoma

Cited by 26 publications

References 38 publications

Single-cell analysis revealed that IL4I1 promoted ovarian cancer progression

Single-cell analysis revealed that IL4I1 promoted ovarian cancer progression

Construction of a Novel Multigene Panel Potently Predicting Poor Prognosis in Patients with Clear Cell Renal Cell Carcinoma

Integrated analysis of the underlying immunomodulator and survival signature of STON1 gene in kidney renal clear cell carcinoma

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