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

Hu, Daixing; Zhou, Mi; Zhu, Xin

doi:10.1155/2019/2506843

Cited by 56 publications

(50 citation statements)

References 33 publications

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“…Current literature indicated that the recruitment of CD4 + T cells in tumor microenvironment could promote RCC proliferation and regulatory T cells can also inhibit tumor immune responses. [ 34 , 35 ] Hu et al reported that higher immune scores may predict the advanced TNM stage, [ 36 ] which is similar to our results. Additionally, we found that patients with lower immune scores tended to have lower stromal scores.…”

Section: Discussionsupporting

confidence: 91%

An immune scores-based nomogram for predicting overall survival in patients with clear cell renal cell carcinoma

Ouyang²,

Peng

2020

Medicine

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The role of immune cell infiltration in the prognosis of clear cell renal cell carcinoma (ccRCC) has received increasing attention. However, immune scores have not yet been introduced into routine clinical practice of ccRCC patients. The principal objective of our research was to study the correlation between immune scores and overall survival (OS) of ccRCC. In this study, Cox regression analyses were used to identify risk factors associated with OS of ccRCC based on the Cancer Genome Atlas datasets. Furthermore, an integrated nomogram combining immune scores and clinicopathologic factors was built for predicting 3- and 5-year OS of ccRCC patients. The receiver operating characteristic curve, concordance index, and calibration curves were used for the evaluation of our nomogram. Also, Kaplan–Meier (KM) survival analysis of immune scores, stromal scores, and different clinicopathological factors was performed. A total of 514 patients were divided into the low- or high-immune scores group. KM and multivariate Cox regression analyses demonstrated that ccRCC patients with high-immune scores had significantly poor OS compared with those with low-immune scores. Calibration curves showed good consistency between the predicted OS and the actual OS probability. Areas under the receiver operating characteristic curves for 3- and 5-year OS were 0.816 and 0.769, and the concordance index was 0.775, indicating that our nomogram had good accuracy for predicting OS of ccRCC patients. Additionally, KM analysis showed that older age, later T stage, distant metastasis, advanced tumor lymph node metastasis stage, higher tumor grade, left site, and low stromal scores were associated with worse OS in ccRCC patients. High-immune scores show a significant correlation with unsatisfactory prognosis in ccRCC patients. Furthermore, the immune scores-based nomogram may be helpful in predicting ccRCC prognosis.

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Section: Discussionsupporting

confidence: 91%

An immune scores-based nomogram for predicting overall survival in patients with clear cell renal cell carcinoma

Ouyang²,

Peng

2020

Medicine

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“…reprogramming described in diverse cancers which involve the overexpression of both HMGC2 (28,29) and PGC-1α transcripts (24). Overexpression of HMGC2/PGC-1α has been observed in high-grade colorectal cancer (30), colitisassociated cancer (31), clear cell renal cell cancer (32,33), ovarian (34), liver (35), oral squamous cell carcinoma (36) and high-grade prostate cancer (37), and is reflective of recurrence and poor prognosis (38). The dual induction of HMGCS2/PGC-1α also propels oncogenic mediated ketogenic events within the cancer milieu/stroma (for example, in cancer-associated fibroblasts) (39).…”

Section: Discussionmentioning

confidence: 99%

Whole-transcriptome Analysis of Fully Viable Energy Efficient Glycolytic-null Cancer Cells Established by Double Genetic Knockout of Lactate Dehydrogenase A/B or Glucose-6-Phosphate Isomerase

Mazzio

Badisa

Mack

et al. 2020

Cancer Genomics Proteomics

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Background/Aim: Nearly all mammalian tumors of diverse tissues are believed to be dependent on fermentative glycolysis, marked by elevated production of lactic acid and expression of glycolytic enzymes, most notably lactic acid dehydrogenase (LDH). Therefore, there has been significant interest in developing chemotherapy drugs that selectively target various isoforms of the LDH enzyme. However, considerable questions remain as to the consequences of biological ablation of LDH or upstream targeting of the glycolytic pathway. Materials and Methods: In this study, we explore the biochemical and whole transcriptomic effects of CRISPR-Cas9 gene knockout (KO) of lactate dehydrogenases A and B [LDHA/B double KO (DKO)] and glucose-6-phosphate isomerase (GPI KO) in the human colon cancer cell line LS174T, using Affymetrix 2.1 ST arrays. Results: The metabolic biochemical profiles corroborate that relative to wild type (WT), LDHA/B DKO produced no lactic acid, (GPI KO) produced minimal lactic acid and both KOs displayed higher mitochondrial respiration, and minimal use of glucose with no loss of cell viability. These findings show a high biochemical energy efficiency as measured by ATP in glycolysis-null cells. Next, transcriptomic analysis conducted on 48,226 mRNA transcripts reflect 273 differentially expressed genes (DEGS) in the GPI KO clone set, 193 DEGS in the LDHA/B DKO clone set with 47 DEGs common to both KO clones. Glycolytic-null cells reflect up-regulation in gene transcripts typically associated with nutrient deprivation / fasting and possible use of fats for energy: thioredoxin interacting protein (TXNIP), mitochondrial 3-hydroxy-3-methylglutaryl-CoA synthase 2 (HMGCS2), PPARγ coactivator 1α (PGC-1α), and acetyl-CoA acyltransferase 2 (ACAA2). Other changes in non-ergometric transcripts in both KOs show losses in "stemness", WNT signaling pathway, chemo/radiation resistance, retinoic acid synthesis, drug detoxification, androgen/estrogen activation, and extracellular matrix reprogramming genes. Conclusion: These findings demonstrate that: 1) The "Warburg effect" is dispensable, 2) loss of the LDHAB gene is not only inconsequential to viability but fosters greater mitochondrial energy, and 3) drugs that target LDHA/B are likely to be ineffective without a plausible combination second drug target. Common features across diverse mammalian tumors include the rapid glycolytic activity, greater expression of lactate dehydrogenases (LDH) and subsequent overproduction of lactic acid, occurring regardless of the presence of oxygen (Warburg effect) (1,2). This unique trait of cancer has been studied for decades, where researchers have geared off original focus from its role in metabolism to its role in acidification of the tumor microenvironment (TME), a formidable driving force for tumor growth, metastasis, aggressiveness, chemo/radiation resistance and loss of immune surveillance (3-8). This loss of immune surveillance 469 This article is freely accessible online.

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“…The estimated score was also related to overall survival ( p = 0.0359) [ 16 ]. In ccRCC, a higher immune score was associated with shorter overall survival ( p = 0.04), and a close association was reported between immune scores, clinical characteristics, as well as prognosis in ccRCC [ 28 ]. These data indicate that TME plays an important role in tumorigenesis and prognosis.…”

Section: Discussionmentioning

confidence: 99%

Identification of Key Genes of Prognostic Value in Clear Cell Renal Cell Carcinoma Microenvironment and a Risk Score Prognostic Model

Zhao

Bai

2020

Disease Markers

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Objective. We aimed at identifying the key genes of prognostic value in clear cell renal cell carcinoma (ccRCC) microenvironment and construct a risk score prognostic model. Materials and Methods. Immune and stromal scores were calculated using the ESTIMATE algorithm. A total of 539 ccRCC cases were divided into high- and low-score groups. The differentially expressed genes in immune and stromal cells for the prognosis of ccRCC were screened. The relationship between survival outcome and gene expression was evaluated using univariate and multivariate Cox proportional hazard regression analyses. A risk score prognostic model was constructed based on the immune/stromal scores. Results. The median survival time of the low immune score group was longer than that of the high immune score group (p=0.044). Ten tumor microenvironment-related genes were selected by screening, and a predictive model was established, based on which patients were divided into high- and low-risk groups with markedly different overall survival (p<0.0001). Multivariate Cox analyses showed that the risk score prognostic model was independently associated with overall survival, with a hazard ratio of 1.0437 (confidence interval: 1.0237–1.0641, p<0.0001). Conclusions. Low immune scores were associated with extended survival time compared to high immune scores. The novel risk predictive model based on tumor microenvironment-related genes may be an independent prognostic biomarker in ccRCC.

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

Cited by 56 publications

References 33 publications

An immune scores-based nomogram for predicting overall survival in patients with clear cell renal cell carcinoma

An immune scores-based nomogram for predicting overall survival in patients with clear cell renal cell carcinoma

Whole-transcriptome Analysis of Fully Viable Energy Efficient Glycolytic-null Cancer Cells Established by Double Genetic Knockout of Lactate Dehydrogenase A/B or Glucose-6-Phosphate Isomerase

Identification of Key Genes of Prognostic Value in Clear Cell Renal Cell Carcinoma Microenvironment and a Risk Score Prognostic Model

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