Prognostic value of D-lactate dehydrogenase in patients with clear cell renal cell carcinoma

Crosstalk between lactate and tumor-associated immune cells: clinical relevance and insight

Lactate, which was traditionally viewed as a metabolic byproduct of anaerobic glycolysis, has emerged as a significant signaling molecule involved in the development of tumors. Current studies highlight its dual function, where it not only fuels tumor development but also modulates immune responses. Lactate has an effect on various tumor-associated immune cells, promoting immunosuppressive conditions that facilitate tumor growth and immune evasion. This phenomenon is strongly associated with the Warburg effect, a metabolic shift observed in many cancers that favors glycolysis over oxidative phosphorylation, resulting in elevated lactate production. Exploring the complex interplay between lactate metabolism and tumor immunity provides a novel understanding regarding the mechanisms of tumor immune evasion and resistance to therapies. This review discusses the unique biology of lactate in the TME, its impact on immune cell dynamics, and its potential as a tumor treatment target.

Advancements in research on lactate dehydrogenase A in urinary system tumors

Tumors of the urinary system, such as prostate cancer, bladder cancer, and renal cell carcinoma, are among the most prevalent types of tumors. They often remain asymptomatic in their early stages, with some patients experiencing recurrence or metastasis post-surgery, leading to disease progression. Lactate dehydrogenase A (LDHA) plays a crucial role in the glycolysis pathway and is closely associated with anaerobic glycolysis in urinary system tumors. Therefore, a comprehensive investigation into the intricate mechanism of LDHA in these tumors can establish a theoretical foundation for early diagnosis and advanced treatment. This review consolidates the current research and applications of LDHA in urinary system tumors, with the aim of providing researchers with a distinct perspective.

Massively parallel screen uncovers many rare 3' UTR variants regulating mRNA abundance of cancer driver genes

Understanding the function of rare non-coding variants represents a significant challenge. Using MapUTR, a screening method, we studied the function of rare 3' UTR variants affecting mRNA abundance post-transcriptionally. Among 17,301 rare gnomAD variants, an average of 24.5% were functional, with 70% in cancer-related genes, many in critical cancer pathways. This observation motivated an interrogation of 11,929 somatic mutations, uncovering 3928 (33%) functional mutations in 155 cancer driver genes. Functional MapUTR variants were enriched in microRNA- or protein-binding sites and may underlie outlier gene expression in tumors. Further, we introduce untranslated tumor mutational burden (uTMB), a metric reflecting the amount of somatic functional MapUTR variants of a tumor and show its potential in predicting patient survival. Through prime editing, we characterized three variants in cancer-relevant genes (MFN2, FOSL2, and IRAK1), demonstrating their cancer-driving potential. Our study elucidates the function of tens of thousands of non-coding variants, nominates non-coding cancer driver mutations, and demonstrates their potential contributions to cancer.

Systematic analysis of the role of LDHs subtype in pan-cancer demonstrates the importance of LDHD in the prognosis of hepatocellular carcinoma patients

BACKGROUND

Lactate dehydrogenase (LDHs) is an enzyme involved in anaerobic glycolysis, including LDHA, LDHB, LDHC and LDHD. Given the regulatory role in the biological progression of certain tumors, we analyzed the role of LDHs in pan-cancers.

METHODS

Cox regression, Kaplan-Meier curves, Receiver Operating Characteristic (ROC) curves, and correlation of clinical indicators in tumor patients were used to assess the prognostic significance of LDHs in pan-cancer. The TCGA, HPA, TIMER, UALCAN, TISIDB, and Cellminer databases were used to investigate the correlation between the expression of LDHs and immune subtypes, immune checkpoint genes, methylation levels, tumor mutational load, microsatellite instability, tumor-infiltrating immune cells and drug sensitivity. The cBioPortal database was also used to identify genomic abnormalities of LDHs in pan-cancer. A comprehensive assessment of the biological functions of LDHs was performed using GSEA. In vitro, HepG2 and Huh7 cells were transfected with LDHD siRNA and GFP-LDHD, the proliferation capacity of cells was examined using CCK-8, EdU, and colony formation assays; the migration and invasion of cells was detected by wound healing and transwell assays; western blotting was used to detect the levels of MMP-2, MMP-9, E-cadherin, N-cadherin and Akt phosphorylation.

RESULTS

LDHs were differentially expressed in a variety of human tumor tissues. LDHs subtypes can act as pro-oncogenes or anti-oncogenes in different types of cancer and have an impact on the prognosis of patients with tumors by influencing their clinicopathological characteristics. LDHs were differentially expressed in tumor immune subtypes and molecular subtypes. In addition, LDHs expression correlated with immune checkpoint genes, tumor mutational load, and microsatellite instability. LDHD was identified to play an important role in the prognosis of HCC patients, according to a comprehensive analysis of LDHs in pan-cancer. In HepG2 and Huh7 cells, knockdown of LDHD promoted cell proliferation, migration, and invasion, promoted the protein expression levels of MMP-2, MMP-9, N-cadherin, and Akt phosphorylation, but inhibited the protein expression level of E-cadherin. In addition, LDHD overexpression showed the opposite changes.

CONCLUSION

LDHs subtypes can be used as potential prognostic markers for certain cancers. Prognostic and immunotherapeutic analysis indicated that LDHD plays an important role in the prognosis of HCC patients. In vitro experiments revealed that LDHD can affect HCC proliferation, migration, and invasion by regulating MMPs expression and EMT via Akt signaling pathway, which provides a new perspective on the anti-cancer molecular mechanism of LDHD in HCC.

Lactate dehydrogenase D is a general dehydrogenase for D-2-hydroxyacids and is associated with D-lactic acidosis

Mammalian lactate dehydrogenase D (LDHD) catalyzes the oxidation of D-lactate to pyruvate. LDHD mutations identified in patients with D-lactic acidosis lead to deficient LDHD activity. Here, we perform a systematic biochemical study of mouse LDHD (mLDHD) and determine the crystal structures of mLDHD in FAD-bound form and in complexes with FAD, Mn2+ and a series of substrates or products. We demonstrate that mLDHD is an Mn2+-dependent general dehydrogenase which exhibits catalytic activity for D-lactate and other D-2-hydroxyacids containing hydrophobic moieties, but no activity for their L-isomers or D-2-hydroxyacids containing hydrophilic moieties. The substrate-binding site contains a positively charged pocket to bind the common glycolate moiety and a hydrophobic pocket with some elasticity to bind the varied hydrophobic moieties of substrates. The structural and biochemical data together reveal the molecular basis for the substrate specificity and catalytic mechanism of LDHD, and the functional roles of mutations in the pathogenesis of D-lactic acidosis.

CDK7-YAP-LDHD axis promotes D-lactate elimination and ferroptosis defense to support cancer stem cell-like properties

Reprogrammed cellular metabolism is essential for maintaining cancer stem cells (CSCs) state. Here, we report that mitochondrial D-lactate catabolism is a necessary initiating oncogenic event during tumorigenesis of esophageal squamous cell carcinoma (ESCC). We discover that cyclin-dependent kinase 7 (CDK7) phosphorylates nuclear Yes-associated protein 1 (YAP) at S127 and S397 sites and enhances its transcription function, which promotes D-lactate dehydrogenase (LDHD) protein expression. Moreover, LDHD is enriched significantly in ESCC-CSCs rather than differentiated tumor cells and high LDHD status is connected with poor prognosis in ESCC patients. Mechanistically, the CDK7-YAP-LDHD axis helps ESCC-CSCs escape from ferroptosis induced by D-lactate and generates pyruvate to satisfy energetic demands for their elevated self-renewal potential. Hence, we conclude that esophageal CSCs adopt a D-lactate elimination and pyruvate accumulation mode dependent on CDK7-YAP-LDHD axis, which drives stemness-associated hallmarks of ESCC-CSCs. Reasonably, targeting metabolic checkpoints may serve as an effective strategy for ESCC therapy.

The novel role of LDHA/LDHB in the prognostic value and tumor-immune infiltration in clear cell renal cell carcinoma

Lactate dehydrogenase (LDH) is a crucial glycolytic enzyme which mediates the metabolic plasticity of cancer cells, however its clinical significance in renal cell carcinoma (RCC) is poorly understood. Herein, we examined the prognostic significance of the two primary components of LDH, i.e., LDHA and LDHB, in clear cell RCC (ccRCC) patients and further explored their association with immune infiltration in ccRCC. In this study, the expression levels of LDHA and LDHB were examined in ccRCC and adjacent normal tissues by Gene Expression Profiling Interactive Analysis 2 (GEPIA2), UALCAN, and western blotting (WB) analyses, and their prognostic values were estimated in 150 ccRCC and 30 adjacent normal tissues by immunohistochemistry (IHC) analysis. The relationship to immune infiltration of LDHA and LDHB genes was further investigated using tumor immune estimation resource 2 (TIMER2) and Tumor-Immune System Interactions and DrugBank (TISIDB) databases, respectively. Public databases and WB analyses demonstrated higher LDHA and lower LDHB in ccRCC than in non-tumor tissues. IHC analysis revealed that LDHA and LDHB expression profiles were significantly associated with tumor grade, stage, size, and overall survival (OS). Univariate survival analysis displayed that high grade, advanced stage, large tumor, metastasis, high LDHA, and low LDHB expression were significantly associated with a poorer OS, and multivariate analysis revealed tumor stage and LDHB were identified as independent predictors for OS in patients with ccRCC. Further TIMER2 and TISIDB analyses demonstrated that LDHA and LDHB expression was significantly related to multiple immune cells and immune inhibitors in over 500 ccRCC patients. These findings revealed that LDHB was an independent favorable predictor, and LDHA and LDHB correlated with tumor immune infiltrates in ccRCC patients, which indicated LDHA/LDHB could be implicated in the tumorigenesis of ccRCC and might be potential therapeutic targets for patients with ccRCC.

Advances of multi-omics applications in hepatic precancerous lesions and hepatocellular carcinoma: The role of extracellular vesicles

Due to the lack of distinct early symptoms and specific biomarkers, most patients with hepatocellular carcinoma (HCC) are usually diagnosed at advanced stages, rendering the treatment ineffective and useless. Therefore, recognition of the malady at precancerous lesions and early stages is particularly important for improving patient outcomes. The interest in extracellular vesicles (EVs) has been growing in recent years with the accumulating knowledge of their multiple cargoes and related multipotent roles in the modulation of immune response and tumor progression. By virtue of the rapid advancement of high-throughput techniques, multiple omics, including genomics/transcriptomics, proteomics, and metabolomics/lipidomics, have been widely integrated to analyze the role of EVs. Comprehensive analysis of multi-omics data will provide useful insights for discovery of new biomarkers and identification of therapeutic targets. Here, we review the attainment of multi-omics analysis to the finding of the potential role of EVs in early diagnosis and the immunotherapy in HCC.

Key therapeutic targets implicated at the early stage of hepatocellular carcinoma identified through machine-learning approaches

Hepatocellular carcinoma (HCC) is the most frequent type of primary liver cancer. Early-stage detection plays an essential role in making treatment decisions and identifying dominant molecular mechanisms. We utilized machine learning algorithms to find significant mRNAs and microRNAs (miRNAs) at the early and late stages of HCC. First, pre-processing approaches, including organization, nested cross-validation, cleaning, and normalization were applied. Next, the t-test/ANOVA methods and binary particle swarm optimization were used as a filter and wrapper method in the feature selection step, respectively. Then, classifiers, based on machine learning and deep learning algorithms were utilized to evaluate the discrimination power of selected features (mRNAs and miRNAs) in the classification step. Finally, the association rule mining algorithm was applied to selected features for identifying key mRNAs and miRNAs that can help decode dominant molecular mechanisms in HCC stages. The applied methods could identify key genes associated with the early (e.g., Vitronectin, thrombin-activatable fibrinolysis inhibitor, lactate dehydrogenase D (LDHD), miR-590) and late-stage (e.g., SPRY domain containing 4, regucalcin, miR-3199-1, miR-194-2, miR-4999) of HCC. This research could establish a clear picture of putative candidate genes, which could be the main actors at the early and late stages of HCC.

Optimization and Application of A Bionic System of Dynamic Co-Culture with Hepatocytes and Renal Cells Based on Microfluidic Chip Technique in Evaluating Materials of Health Food

We aimed to explore the optimization and application of a bionic system of dynamic co-culture with hepatocytes and renal cells based on the microfluidic chip technique in evaluating emodin, which might replace the conventionally cytological evaluation technique of health food. After optimal experiments, the improved bionic system was composed of human hepatocellular carcinoma cells (HepG2), human renal glomerular endothelial cells (HRGECs), rat tail collagen type I, and gelatin with optimized concentrations (1.3 mg/mL + 7.5%). The applicability of the bionic system indicated that the growth stability was appropriate (CV: 7.36%), and the cell viability of that gradually decreased with the increasing of emodin concentration from 0−100 μM, which statistic significances were at 50 and 100 μM (p < 0.05), and the stained results of dead/live cells also showed the same trend. The LDH level appeared rising trend after decline between 0 μM and 100 μM emodi, and the level of that at 100 μM emodin was significantly higher than that at 25 μM and 50 μM emodin, respectively. The BUN level continuously and significantly declined with the increasing of emodin concentration (p < 0.05). Our research realized the application of this optimized bionic system in evaluating emodin, and provided a useful platform and reference for further in vitro alternative research with regard to evaluating the efficacies of health food in the future.

Identification of Prognostic Factors in Cholangiocarcinoma Based on Integrated ceRNA Network Analysis

This study is aimed at screening prognostic biomarkers in cholangiocarcinoma (CHOL) based on competitive endogenous RNA (ceRNA) regulatory network analysis. Microarray data for lncRNAs, mRNA, and miRNAs were downloaded from the GEO and TCGA databases. Differentially expressed RNAs (DERs) were identified in CHOL and normal liver tissue samples. WGCNA was used to identify disease-related gene modules. By integrating the information from the starBase and DIANA-LncBasev2 databases, we constructed a ceRNA network. Survival analysis was performed, and a prognostic gene-based prognostic score (PS) model was generated. The correlation between gene expression and immune cell infiltration or immune-related feature genes was analyzed using TIMER. Finally, real-time quantitative PCR (RT-qPCR) was used to verify the expression of the 10 DERs with independent prognosis. A large cohort of DERs was identified in the CHOL and control samples. The ceRNA network consisted of 6 lncRNAs, 2 miRNAs, 90 mRNAs, and 98 nodes. Ten genes were identified as prognosis-related genes, and a ten-gene signature PS model was constructed, which exhibited a good prognosis predictive ability for risk assessment of CHOL patients (AUC value = 0.975). Four genes, ELF4, AGXT, ABCG2, and LDHD, were associated with immune cell infiltration and closely correlated with immune-related feature genes (CD14, CD163, CD33, etc.) in CHOL. Additionally, the consistency rate of the RT-qPCR results and bioinformatics analysis was 80%, implying a relatively high reliability of the bioinformatic analysis results. Our findings suggest that the ten-signature gene PS model has significant prognostic predictive value for patients with CHOL. These four immune-related DERs are involved in the progression of CHOL and may be useful prognostic biomarkers for CHOLs.

A novel lactate metabolism-related signature predicts prognosis and tumor immune microenvironment of breast cancer

Background: Lactate, an intermediate product of glycolysis, has become an essential regulator of tumor maintenance, development, and metastasis. Lactate can drive tumors by changing the microenvironment of tumor cells. Because of lactate's important role in cancer, we aim to find a novel prognostic signature based on lactate metabolism-related genes (LMRGs) of breast cancer (BC). Methods: RNA-sequencing data and clinical information of BC were enrolled from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database. We obtained LMRGs from the Molecular Signature Database v7.4 and articles, and then we compared candidate genes with TCGA data to get differential genes. Univariate analysis and most minor absolute shrinkage and selector operator (LASSO) Cox regression were employed to filter prognostic genes. A novel lactate metabolism-related risk signature was constructed using a multivariate Cox regression analysis. The signature was validated by time-dependent ROC curve analyses and Kaplan-Meier analyses in TCGA and GEO cohorts. Then, we further investigated in depth the function of the model's immune microenvironment. Results: We constructed a 3-LMRG-based risk signature. Kaplan-Meier curves confirmed that high-risk score subgroups had a worse prognosis in TCGA and GEO cohorts. Then a nomogram to predict the probability of survival for BC was constructed. We also performed Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway function analysis. The function analysis showed that the lactate metabolism-related signature was significantly related to immune response. A significant correlation was observed between prognostic LMRGs and tumor mutation burden, checkpoints, and immune cell infiltration. An mRNA-miRNA network was built to identify an miR-203a-3p/LDHD/LYRM7 regulatory axis in BC. Conclusion: In conclusion, we constructed a novel 3-LMRG signature and nomogram that can be used to predict the prognosis of BC patients. In addition, the signature is closely related to the immune microenvironment, which may provide new insight into future anticancer therapies.

The Association between Early Changes in Neutrophil-Lymphocyte Ratio and Survival in Patients Treated with Immunotherapy

Dynamic changes in the blood-based biomarkers could be used as a prognostic biomarker in patients treated with immune checkpoint inhibitors (ICIs), although the data are limited. We evaluated the association between the neutrophil−lymphocyte ratio (NLR) and early NLR changes with survival in ICI-treated patients. We retrospectively evaluated the data of 231 patients with advanced-stage cancer. We recorded baseline clinical characteristics, baseline NLR and fourth-week NLR changes, and survival data. A compound prognostic score, the NLR2-CEL score, was developed with the following parameters: baseline NLR (<5 vs. ≥5), ECOG status (0 vs. ≥1), Charlson Comorbidity Index (CCI, <9 vs. ≥9), LDH (N vs. ≥ULN), and fourth-week NLR change (10% or over NLR increase). In the multivariable analyses, higher NLR (HR: 1.743, p = 0.002), 10% or over NLR increase in the fourth week of treatment (HR: 1.807, p = 0.001), higher ECOG performance score (HR: 1.552, p = 0.006), higher LDH levels (HR: 1.454, p = 0.017), and higher CCI (HR: 1.400, p = 0.041) were associated with decreased OS. Compared to patients with the lowest scores, patients in the highest score group had significantly lower OS (HR: 7.967, 95% CI: 3.531−17.979, p < 0.001) and PFS. The composite score had moderate success for survival prediction, with an AUC of 0.702 (95% CI: 0.626−0.779, p < 0.001). We observed significantly lower survival in patients with higher baseline NLR values and increased NLR values under treatment.

Radix Actinidia chinensis Suppresses Renal Cell Carcinoma Progression: Network Pharmacology Prediction and In Vivo Experimental Validation

Background

Renal cell carcinoma (RCC) is a frequent disease with limited curative methods. This study is aimed at investigating the role and mechanism of Radix Actinidia chinensis (RAC) on RCC.

Methods

The ingredients, target, and crucial pathways of RAC in RCC therapy were analyzed by network pharmacology. Then, an RCC animal model was established by subcutaneously injecting A498 cell suspension to BALB/c nude mice. After 1 week, the mice in the RAC-L/M/H groups were administered with RAC at 5, 10, and 20 mg/kg/d, respectively. The histopathology of the tumor was evaluated. The contents of tumor inflammatory cytokines and serum oxidative stress factors were detected by ELISA. The apoptosis of tumor tissues was assessed by TUNEL staining. The expressions of apoptosis-, proliferate-, autophagy-, and MAPK-related proteins were measured.

Results

There were 13 active ingredients, and 20 RCC-relevant targets were selected from RAC; KEGG pathway indicated that these targets were enriched in the PI3K/AKT/mTOR and MAPK pathway. In in vivo experiments, RAC not only obviously damaged tumor cells and decreased the release of inflammatory cytokines and oxidative stress factors but also enhanced the apoptosis of the tumor cell in RCC mice. Besides, the expressions of apoptosis-, proliferate-, autophagy-, PI3K/AKT/mTOR path-, and MAPK path-related proteins were all affected by RAC.

Conclusion

RAC attenuated RCC by regulating inflammation response, oxidative stress, apoptosis, proliferation, and autophagy, and its effects were partly linked to the PI3K/AKT/mTOR and MAPK pathway, which indicated that RAC may be a candidate drug for RCC.

Lactate Dehydrogenase A or B Knockdown Reduces Lactate Production and Inhibits Breast Cancer Cell Motility in vitro

Background: Lactate dehydrogenase (LDH) plays an important role in cancer pathogenesis and enhanced expression/activity of this enzyme has been correlated with poor prognosis. In this study we determined the expression profile of LDH-A and B in normal as well as in endocrine-resistant and -responsive breast cancer cells and the effect of their knockdown on LDH activity, lactate production, proliferation and cell motility.

Methods: Knockdown experiments were performed using siRNA and shRNA. The expression profile of LDH and signaling molecules was determined using PCR and western blotting. Intracellular LDH activity and extracellular lactate levels were measured by a biochemical assay. Cell motility was determined using wound healing, while proliferation was determined using MTT assay.

Results: LDH-A was expressed in all of the tested cell lines, while LDH-B was specifically expressed only in normal and endocrine-resistant breast cancer cells. This was correlated with significantly enhanced LDH activity and lactate production in endocrine resistant breast cancer cells when compared to normal or endocrine responsive cancer cells. LDH-A or -B knockdown significantly reduced LDH activity and lactate production, which led to reduced cell motility. Exogenous lactate supplementation enhanced cell motility co-incident with enhanced phosphorylation of ERK1/2 and reduced E-cadherin expression. Also, LDH-A or -B knockdown reduced ERK 1/2 phosphorylation.

Conclusion: Enhanced cell motility in endocrine resistant breast cancer cells is at least in part mediated by enhanced extracellular lactate levels, and LDH inhibition might be a promising therapeutic target to inhibit cancer cell motility.

The Value of Lactate Dehydrogenase in Predicting Rhabdomyolysis-Induced Acute Renal Failure; a Narrative Review

Introduction

Determining the diagnostic value of available biomarkers in predicting rhabdomyolysis-induced acute kidney injury (AKI) is a priority. This study aimed to review the current evidence about the value of lactate dehydrogenase (LDH) in this regard.

Methods

In this narrative review, the papers in PubMed, Embase, and web of science were studied. The keywords prognosis, prognoses, prognostic, LDH, rhabdomyolysis, emergency patients, and acute kidney failure or AKI had been selected from MeSH medical dictionary. Related papers written in English and published from November 2007 to December 2020 were selected.

Results

Finally, 14 articles were accepted for analysis. Among the selected articles, four were randomized clinical trials, seven were cross-sectional, and three were case-control studies. The results of the present review showed that abuse of illegal drugs is the most common cause of rhabdomyolysis. AKI is the most serious complication of rhabdomyolysis reported in the studies. These studies have shown a three-fold increase in AKI following drug-induced rhabdomyolysis. The review of the included articles shows that high LDH can predicts AKI, especially in critical and emergency situations such as rhabdomyolysis where there is a risk of death if diagnosed late. These studies show that LDH increases in the presence of renal failure and tissue damage.

Conclusion

Serum LDH is an appropriate and cost-effective prognostic indicator that can be used for risk classification of patients at risk for rhabdomyolysis-induced AKI.

Cancer-testis antigen lactate dehydrogenase C4 in hepatocellular carcinoma: a promising biomarker for early diagnosis, efficacy evaluation and prognosis prediction

Expressions and clinical implications of cancer-testis antigen (CTA) lactate dehydrogenase (LDH)-C4 in hepatocellular carcinoma (HCC) have not been fully elucidated. Herein, expressions of LDHC mRNA in the serum and serum-derived exosomes of early-stage HCC patients were determined using qRT-PCR, and the expression of LDH-C4 protein in HCC tissues was detected using high-throughput tissue microarray analysis. It was found that positive rates of LDHC mRNA expressions in the serum and serum exosomes of HCC patients were 68% and 60%, respectively. The AUCs of serum and exosomal LDHC in differentiating HCC patients from healthy controls were 0.8382 and 0.9451, respectively. The serum and exosomal LDHC levels in HCC patients in the treatment group were higher than the levels in the preliminary diagnosis group, but lower than those in the recurrence group. Survival analysis showed that the expression of LDH-C4 was negatively correlated with the prognosis of HCC. The Cox regression analysis showed that an LDH-C4 level was an independent risk factor for the prognosis of HCC patients. Therefore, serum and exosomal LDHC can be used as a biomarker for early diagnosis, efficacy evaluation and recurrence prediction of HCC. Moreover, LDH-C4 can be used as an important reference indicator for monitoring the prognosis of HCC.

Expression of CREPT is associated with poor prognosis of patients with renal cell carcinoma

Cell-cycle-associated and expression-elevated protein in tumor (CREPT) functions as a cell cycle modulator that enhances the transcription of cyclin D1 by interacting with RNA polymerase II. CREPT has been identified to be overexpressed in various human cancer types; however, the expression and significance of CREPT in renal cell carcinoma (RCC) has remained largely elusive. In the present study, increased expression of CREPT was identified in 46.7% RCC tissues compared with adjacent normal tissue (31.1%; P=0.032) using immunohistochemistry. Furthermore, overexpression of CREPT was significantly associated with the Tumor-Node-Metastasis stage (χ²=11.967, P=0.001) and Fuhrman grade (χ²=15.453, P<0.001). In addition, increased expression of CREPT was associated with poor overall survival (P=0.021) and disease-free survival (P=0.015) of patients according to Kaplan-Meier analysis. Cellular function assays demonstrated that knockdown of CREPT in the 786-O and 769P RCC cell lines suppressed their proliferative, colony formation, migratory and invasive capacity and led to cell cycle arrest in the G1 phase. In addition, the western blotting analysis demonstrated that CREPT may control the cell cycle through downregulation of cyclin D1 and c-myc. Collectively, the overexpression of CREPT was indicated to be a negative prognostic factor for RCC, and CREPT may serve as a novel therapeutic target for the treatment of RCC.

Lactate Dehydrogenases as Metabolic Links between Tumor and Stroma in the Tumor Microenvironment

Cancer is a metabolic disease in which abnormally proliferating cancer cells rewire metabolic pathways in the tumor microenvironment (TME). Molecular reprogramming in the TME helps cancer cells to fulfill elevated metabolic demands for bioenergetics and cellular biosynthesis. One of the ways through which cancer cell achieve this is by regulating the expression of metabolic enzymes. Lactate dehydrogenase (LDH) is the primary metabolic enzyme that converts pyruvate to lactate and vice versa. LDH also plays a significant role in regulating nutrient exchange between tumor and stroma. Thus, targeting human lactate dehydrogenase for treating advanced carcinomas may be of benefit. LDHA and LDHB, two isoenzymes of LDH, participate in tumor stroma metabolic interaction and exchange of metabolic fuel and thus could serve as potential anticancer drug targets. This article reviews recent research discussing the roles of lactate dehydrogenase in cancer metabolism. As molecular regulation of LDHA and LDHB in different cancer remains obscure, we also review signaling pathways regulating LDHA and LDHB expression. We highlight on the role of small molecule inhibitors in targeting LDH activity and we emphasize the development of safer and more effective LDH inhibitors. We trust that this review will also generate interest in designing combination therapies based on LDH inhibition, with LDHA being targeted in tumors and LDHB in stromal cells for better treatment outcome.

Overexpression of COL5A1 promotes tumor progression and metastasis and correlates with poor survival of patients with clear cell renal cell carcinoma

Background and aims

COL5A1 has been identified to be involved in metastasis of clear cell renal cell carcinoma (ccRCC) by bioinformatic analysis. This study aimed to investigate COL5A1 expression and its clinical significance in ccRCC. The function of COL5A1 in ccRCC was further investigated.

Methods

COL5A1 expression was examined in 256 ccRCC tissues and paired adjacent normal renal tissues by immunohistochemistry and real-time quantitative PCR. The clinical significance of COL5A1 expression was evaluated. Downregulation of COL5A1 was achieved using siRNA. The effects of COL5A1 silencing on cell proliferation, apoptosis, migration, invasion in vitro, and tumor growth in vivo were investigated.

Results

COL5A1 expression was upregulated in the majority of the ccRCC tissues at both protein and mRNA levels. COL5A1 expression was significantly correlated with tumor diameter, tumor stage, tumor grade, distant metastasis, recurrence, necrosis, and sarcomatoid (all P<0.05). COL5A1 expression was also significantly associated with overall survival of ccRCC patients (HR 1.876; P=0.027) and recurrence-free survival of localized ccRCC patients (HR 4.751; P<0.001). The accuracy of TNM, University of California Los Angeles Integrated Staging System, and Mayo clinic stage, size, grade, and necrosis prognostic models was improved when COL5A1 expression was added.

Conclusion

COL5A1 knockdown significantly inhibited cell proliferation, induced cell apoptosis, inhibited cell migration and invasion in vitro, and inhibited tumor growth in vivo. Therefore, COL5A1 may be a novel prognostic biomarker and a promising therapeutic target for ccRCC.