DYSF expression in clear cell renal cell carcinoma: A retrospective study of 2 independent cohorts

Ha, Mihyang; Jeong, Hoim; Roh, Jong Seong; Lee, Beomgu; Han, Myoung‐Eun; Oh, Sae‐Ock; Kim, Yun Hak

doi:10.1016/j.urolonc.2019.07.007

Cited by 13 publications

(11 citation statements)

References 50 publications

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“…With further exploration of public databases and wide application of bioinformatic methods, increasing evidence indicated promising biomarkers and predictive signatures in renal cancer. Based on TCGA and International Cancer Genome Consortium (ICGC) cohorts, DYSF, VNN3, TMED3, and TEK were found and validated to exert as promising biomarkers to predict the prognosis of ccRCC patients [30–33]. A 3-mRNA signature consisting of ERG, RRM2, and EGF was constructed to predict survival in papillary renal cell cancer with satisfactory accuracy [34].…”

Section: Discussionmentioning

confidence: 99%

Deciphering Immune-Associated Genes to Predict Survival in Clear Cell Renal Cell Cancer

Zhou

Zhu

2019

BioMed Research International

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Background To elucidate the correlations between tumor microenvironment and clinical characteristics as well as prognosis in clear cell renal cell cancer (ccRCC) and investigate the immune-associated genes by a comprehensive analysis of The Cancer Genome Atlas (TCGA) database. Methods We collected mRNA expression profiles of 537 ccRCC samples from the TCGA database. Immune scores and stromal scores were calculated by applying the ESTIMATE algorithm. We evaluated the correlation between immune/stromal scores and clinical characteristics as well as prognosis. The differentially expressed genes (DEGs) were screened between high immune/stromal score and low immune/stromal score groups by the cutoff of |log (fold change)| > 1, P value <0.05 by using package “limma” in R. Functional enrichment analysis was performed by DAVID, and the protein-protein interaction network of intersected DEGs between stromal score and immune score groups was conducted using the STRING database. The Kaplan–Meier method was used to explore DEGs with predictive values in overall survival, and the prognostic DEGs were further validated in a Gene Expression Omnibus (GEO) dataset GSE29609. Results A higher immune score was associated with T3/4 (vs. T1/2, P < 0.001), N1 (vs. N0, P=0.05), M1 (vs. M0, P=0.004), G3/4 (vs. G1/2, P < 0.001), advanced AJCC stage (P < 0.001), and shorter overall survival (P=0.04). Intersected DEGs between immune and stromal score groups were 48 upregulated and 47 downregulated genes, with 43 DEGs associated with overall survival in ccRCC. After validation by a cohort of 39 ccRCC cases with detailed follow-up information from GSE29609, six immune-associated DEGs including CASP5, HSD11B1, VSIG4, HMGCS2, HSD11B2, and OGDHL were demonstrated to be predictive of prognosis in ccRCC. Conclusions Our study elucidated tight associations between immune score and clinical characteristics as well as prognosis in ccRCC. Moreover, six DEGs were explored and validated to exert predictive values in overall survival of ccRCC.

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Section: Discussionmentioning

confidence: 99%

Deciphering Immune-Associated Genes to Predict Survival in Clear Cell Renal Cell Cancer

Zhou

Zhu

2019

BioMed Research International

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“…We used the following methods: Kaplan‐Meier survival curves with log‐rank test, Uno's C ‐index in the time‐dependent area under the curve (AUC) analysis, and AUC values in receiver operating characteristics (ROC) at 3 years to evaluate the accuracy of the risk stratification. These methods were performed in accordance with previously published studies . Values were obtained using the R packages “survival” and “survAUC.” In the Kaplan‐Meier analyses, we determined the optimal cutoff expression value of FAM213A that had the maximal Uno's C ‐index by fivefold cross‐validation.…”

Section: Methodsmentioning

confidence: 99%

“…These methods were performed in accordance with previously published studies. [16][17][18][19] Values were obtained using the R packages "survival" and "survAUC." In the Kaplan-Meier analyses, we determined the optimal cutoff expression value of FAM213A that had the maximal Uno's C-index by fivefold cross-validation.…”

Section: Survival Analysesmentioning

confidence: 99%

FAM213A is linked to prognostic significance in acute myeloid leukemia through regulation of oxidative stress and myelopoiesis

Han

et al. 2020

Hematological Oncology

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Accurate prediction of malignancies is important in choosing therapeutic strategies. Although there are many genetic and cytogenetic prognostic factors for acute myeloid leukemia (AML), prognosis is difficult to predict because of the heterogeneity of AML. Prognostic factors, including messenger RNA (mRNA) expression, have been determined for other malignancies, but not for AML. A total of 402 patients from The Cancer Genome Atlas, GSE12417 (GPL96, 97), and GSE12417 (GPL570) were included in this study. In Kaplan-Meier curve analyses, high expression of family with sequence similarity 213 member A (FAM213A), which activates antioxidant proteins, was associated with worse prognosis of AML. Similar to the results of the survival

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“…Given the relation between hypercalcemia and poor prognosis in ccRCC patients (IMDC), investigators have recently studied the prognostic role of calcium-sensing genes on plasma membrane. In one study, higher levels of DYSF (Dysferlin) were found in ccRCC cells compared with normal kidney cells and this, within ccRCC patients, was a predictor of improved prognosis[ 92 ]. It is postulated that DYSF may act as a metastasis suppressive gene and perhaps be a promising prognostic tool in ccRCC patients, but replication of data is required by future studies.…”

Section: Treatment Selectionmentioning

confidence: 99%

Combination drug regimens for metastatic clear cell renal cell carcinoma

Khetani¹,

Portal²,

Shah³

et al. 2020

WJCO

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Renal cell carcinomas (RCC) make up about 90% of kidney cancers, of which 80% are of the clear cell subtype. About 20% of patients are already metastatic at the time of diagnosis. Initial treatment is often cytoreductive nephrectomy, but systemic therapy is required for advanced RCC. Single agent targeted therapies are moderately toxic and only somewhat effective, leading to development of immunotherapies and combination therapies. This review identifies limitations of monotherapies for metastatic renal cell carcinoma, discusses recent advances in combination therapies, and highlights therapeutic options under development. The goal behind combining various modalities of systemic therapy is to potentiate a synergistic antitumor effect. However, combining targeted therapies may cause increased toxicity. The initial attempts to create therapeutic combinations based on inhibition of the vascular endothelial growth factor or mammalian target of rapamycin pathways were largely unsuccessful in achieving a profile of increased synergy without increased toxicity. To date, five combination therapies have been approved by the U.S. Food and Drug Administration, with the most recently approved therapies being a combination of checkpoint inhibition plus targeted therapy. Several other combination therapies are under development, including some in the phase 3 stage. The new wave of combination therapies for metastatic RCC has the potential to increase response rates and improve survival outcomes while maintaining tolerable side effect profiles.

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DYSF expression in clear cell renal cell carcinoma: A retrospective study of 2 independent cohorts

Cited by 13 publications

References 50 publications

Deciphering Immune-Associated Genes to Predict Survival in Clear Cell Renal Cell Cancer

Deciphering Immune-Associated Genes to Predict Survival in Clear Cell Renal Cell Cancer

FAM213A is linked to prognostic significance in acute myeloid leukemia through regulation of oxidative stress and myelopoiesis

Combination drug regimens for metastatic clear cell renal cell carcinoma

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