Construction of a prognostic signature for serous ovarian cancer based on lactate metabolism-related genes.

The key biochemical feature of malignant tumor is the conversion of energy metabolism from oxidative phosphorylation to glycolysis, which provides sufficient capacity and raw materials for tumor cell rapid growth. Our study aims to construct a prognostic signature for ovarian cancer based on lactate metabolism-related genes (LMRGs). Data of ovarian cancer and non-diseased ovarian data were downloaded from TCGA and the GTEx database, respectively. LMRGs were obtained from GeneCards and MSigDB databases, and the differentially expressed LMRGs were identified using limma and DESeq2 R packages. Cox regression analysis and LASSO were performed to determine the LMRGs associated with OS and develop the prognostic signature. Then, clinical significance of the prognostic signature in ovarian cancer was assessed. A total of 485 differentially expressed LMRGs in ovarian tissue were selected for subsequent analysis, of which 324 were up-regulated and 161 were down regulated. We found that 22 LMRGs were most significantly associated with OS by using the univariate regression analysis. The prognostic scoring model was consisted of 12 LMRGs (SLCO1B3, ERBB4, SLC28A1, PDSS1, BDH1, AIFM1, TSFM, PPARGC1A, HGF, FGFR1, ABCC8, TH). Kaplan-Meier survival analysis indicated that poorer overall survival (OS) in the high-risk group patients (P<0.0001). This prognostic signature could be an independent prognostic indicator after adjusting to other clinical factors. The calibration curves of nomogram for the signature at 1, 2, and 3 years and the ROC curve demonstrated good agreement between the predicted and observed survival rates of ovarian cancer patients. Furthermore, the high-risk group patients have much lower expression level of immune checkpoint-TDO2 compared with the low-risk group (P=0.024). We established a prognostic signature based on LMRGs for ovarian cancer, and highlighted emerging evidence indicating that this prognostic signature is a promising approach for predicting ovarian cancer prognosis and guiding clinical therapy.

Xiang J ，Su R ，Wu S ，Zhou L ... -  《Frontiers in Oncology》

Establishment and validation of a prognostic signature for pancreatic ductal adenocarcinoma based on lactate metabolism-related genes.

Background: Pancreatic ductal adenocarcinoma (PDAC) is one of the most aggressive and lethal malignancy with poor prognosis. To improve patient outcomes, it is necessary to gain a better understanding of the oncogenesis and progression of this disease. Metabolic reprogramming, particularly the regulation of lactate metabolism, is known to have a significant impact on tumor microenvironment and could provide valuable insights for the management of PDAC patients. In this study, we aimed to investigate the prognostic potential of lactate metabolism-related genes (LMRGs). Methods: Transcriptomic data of patients with PDAC along with the clinical outcomes were retrieved from The Cancer Genome Atlas database, and the expression data in normal pancreas from Genotype-Tissue Expression dataset were adopted as the normal control. By using Cox and LASSO regression models, we identified key genes that are differentially expressed in cancerous tissues and related to prognosis. To determine the prognostic value of LMRGs in PDAC, we evaluated their clinical significance and model performance using both the area under the receiver operator characteristic curve (AUC) and calibration curves. In addition, we evaluated the drug sensitivity prediction and immune infiltration by using oncoPredict algorithm, single sample gene set enrichment analysis and Tumor Immune Estimation Resource. Results: A total of 123 LMRGs were identified through differential gene screening analysis, among which 7 LMRGs were identified to comprise a LMRGs signature that independently predict overall survival of these PDAC patient. The AUC values for the LMRGs signature were 0.786, 0.820, 0.837, and 0.816 for predicting 1-, 2-, 3- and 5-year overall survival respectively. Furthermore, this prognostic signature was used to stratify patients into high-risk and low-risk groups, with the former having worse clinical outcomes. This observation was further validated through analysis of the International Cancer Genome Consortium database. In addition, lower sensitivity to gemcitabine and infiltration of immune effector cells were observed in the cancer tissue of patients in the high-risk group. Conclusion: In conclusion, our data suggests that a genomic signature comprised of these LMRGs may be a novel predictor of overall clinical outcomes and present therapeutic potential for PDAC patients.

Huang X ，Zhao C ，Han Y ，Li S ... -  《Frontiers in Molecular Biosciences》

A lactate metabolism-related signature predicting patient prognosis and immune microenvironment in ovarian cancer.

Zhu L ，Lin Z ，Wang K ，Gu J ，Chen X ，Chen R ，Wang L ，Cheng X ... -  《Frontiers in Endocrinology》

Lactate metabolism-related genes to predict the clinical outcome and molecular characteristics of endometrial cancer.

Metabolic reprogramming is one of hallmarks of cancer progression and is of great importance for the tumor microenvironment (TME). As an abundant metabolite, lactate has been found to play a critical role in cancer development and immunosuppression of TME. However, the potential role of lactate metabolism-related genes in endometrial cancer (EC) remains obscure. RNA sequencing data and clinical information of EC were obtained from The Cancer Genome Atlas (TCGA) database. Lactate metabolism-related genes (LMRGs) WERE from Molecular Signature Database v7.4 and then compared the candidate genes from TCGA to obtain final genes. Univariate analysis and Least Absolute Shrinkage and Selection Operator (LASSO) Cox regression were performed to screen prognostic genes. A lactate metabolism-related risk profile was constructed using multivariate Cox regression analysis. The signature was validated by time-dependent ROC curve analysis and Kaplan-Meier analysis. The relationship between the risk score and age, grade, stage, tumor microenvironmental characteristics, and drug sensitivity was as well explored by correlation analyses. Gene ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway functional analysis between the high and low-risk groups were performed. CCK8, EdU, and clone formation assays were applied to detect the proliferation ability of EC cells, Transwell assay was performed to detect the migration ability of EC cells, and intracellular lactate and glucose content was used to asses lactate metabolism. We constructed a risk signature based on 18 LMRGs. Kaplan-Meier curves confirmed that the high-risk group had poorer prognosis compared to the low-risk group. A nomogram was then constructed to predict the probability of EC survival. We also performed GO enrichment analysis and KEGG pathway functional analysis between the high and low-risk groups, and the outcome revealed that the features were significantly associated with energy metabolism. There was a significant correspondence between LMRGs and tumor mutational load, checkpoints and immune cell infiltration. C1, C2, and C4 were the most infiltrated in the high-risk group. The high-risk group showed increased dendritic cell activation, while the low-risk group showed increased plasma cells and Treg cells. Drug sensitivity analysis showed LMRGs risk was more resistant to Scr kinase inhibitors. We further proved that one of the lactate metabolism related genes, TIMM50 could promote EC cell proliferation, migration and lactate metabolism. In conclusion, we have established an effective prognostic signature based on LMRG expression patterns, which may greatly facilitate the assessment of prognosis, molecular features and treatment modalities in EC patients and may be useful in the future translation to clinical applications. TIMM50 was identified as a novel molecule that mediates lactate metabolism in vitro and in vivo, maybe a promising target for EC prognosis.

Shi R ，Li H ，Wei S ，Yu Z ，Zhang J ，Zhang Q ，Zhou T ，Yao Y ，Zhang Q ，Zhang T ，Wang H ... -  《BMC CANCER》

A Novel Lactate Metabolism-Related Gene Signature for Predicting Clinical Outcome and Tumor Microenvironment in Hepatocellular Carcinoma.

Hepatocellular carcinoma (HCC) is the main subtype of primary liver cancer with high malignancy and poor prognosis. Metabolic reprogramming is a hallmark of cancer and has great importance on the tumor microenvironment (TME). As an abundant metabolite, lactate plays a crucial role in cancer progression and the immunosuppressive TME. Nonetheless, the potential roles of lactate in HCC remain unclear. In this study, we downloaded transcriptomic data of HCC patients with corresponding clinical information from the TCGA and ICGC portals. The TCGA-HCC dataset used as the training cohort, while the ICGC-LIRI-JP dataset was served as an external validation cohort. Cox regression analysis and the LASSO regression model were combined to construct the lactate metabolism-related gene signature (LMRGS). Then, we assessed the clinical significance of LMRGS in HCC. Besides, enriched molecular functions, tumor mutation burden (TMB), infiltrating immune cells, and immune checkpoint were comprehensively analyzed in different LMRGS subgroups. In total, 66 differentially expressed lactate metabolism-related genes (LMRGs) were screened. The functions of LMRGs were mainly enriched in mitochondrial activity and metabolic processes. The LMRGS comprised of six key LMRGs (FKTN, PDSS1, PET117, PUS1, RARS1, and RNASEH1) had significant clinical value for independently predicting the prognosis of HCC patients. The overall survival and median survival of patients in the LMRGS-high group were significantly shorter than in the LMRGS-low group. In addition, there were differences in TMB between the two LMRGS subgroups. The probability of genetic mutations was higher in the LMRGS-high group. Most importantly, the LMRGS reflected the TME characteristics. In the LMRGS-high group, the immune microenvironment presented a suppressed state, accompanied by more inhibitory immune cell infiltration, including follicular helper T cells and regulatory T cells. Additionally, the expression of inhibitory checkpoint molecules was much higher in the LMRGS-high group. Our study suggested that the LMRGS was a robust biomarker to predict the clinical outcomes and evaluate the TME of patients with HCC.

Li Y ，Mo H ，Wu S ，Liu X ，Tu K ... -  《Frontiers in Cell and Developmental Biology》