Identification of novel lactate metabolism signatures and molecular subtypes for prognosis in hepatocellular carcinoma

Abstract

Background: Evidence has shown that lactate, an immune signaling molecule, is associated with hepatocellular carcinoma (HCC) progression and immune suppression. Therefore, identifying lactate metabolism-related molecules is a promising therapeutic strategy to inhibit the development of HCC and overcome chemotherapy resistance. Long noncoding RNAs (lncRNAs) are related to tumorigenesis and metastasis. Hence, verifying the molecular subtypes of lncRNAs related to lactate metabolism will play a critical role in managing HCC.Methods: Based on HCC data in The Cancer Genome Atlas (TCGA), lactate metabolic pathway-related genes were enriched by gene collection and enrichment analysis (GSEA). Lactate metabolism-related lncRNAs (LM_lncRNAs) were identified by correlation analysis, HCC molecular subtypes were determined using nonnegative matrix factorization (NMF) clustering, and the response of the three subtypes to chemotherapeutics was further evaluated using the Genomic Tumor Sensitive Cell Line (GDSC) dataset. LM_lncRNAs were examined via Lasso-Cox regression analysis to determine prognosis for patients. A Nomagram plot was used to predict patient survival time.Results: Three molecular subtypes of HCC were identified. The survival rate of patients with C1 subtype was higher than that of those with C2 and C3. Additionally, patients with C3 subtype have higher levels of immune cell infiltration and high expression of genes related to immune checkpoints. The GDSC results indicated that patients with C3 subtypes were more sensitive to chemotherapy drugs such as sorafenib and sunitinib. The prognostic risk assessment model consisted of six risk factors (AC034229.4, AC131009.1, MYOSLID, AC008667.1, AC012073.1, AC068025.1) and two protective factors (LINC00402 and AC103858.1). Based on Kaplan-Meier analysis, low-risk HCC patients had a high survival rate, and the receiver operating characteristic curve (ROC), calibration curve, and C-index confirmed good prediction ability.Conclusion: In this study, the molecular subtyping method and prediction model of lactate metabolism-related lncRNAs (LM_lncRNAs) were constructed for the prognosis of HCC patients. This work demonstrated the potential targets of LM_lncRNAs and provided a novel perspective and therapeutic paradigm for future clinical translation.

Identification and functional analysis of lactic acid metabolism-related differentially expressed genes in hepatocellular carcinoma

“…It has been reported that the simultaneous inhibition of lactate metabolism related gene ODC1 and PKM2 exerts synergistic effects against HCC cells ( Zeng et al, 2020 ). Recently, a prediction model of lactic acid metabolism-related lncRNAs was constructed and used to predict the clinical outcomes and assess the TME in patients with HCC ( Guan et al, 2022 ). Therefore, it is necessary to understand the functions and mechanisms of LAMRGs in the development of HCC.…”

“…In recent years, the inhibition of lactic acid metabolism has proven to be a potential therapeutic approach for cancer ( Doherty and Cleveland, 2013 ; Zeng et al, 2020 ). Previous studies have shown that lactic acid metabolism-related genes (LAMRGs) and lncRNAs play critical role in HCC ( Li et al, 2021 ; Guan et al, 2022 ). However, the clinical significance and underlying mechanisms of lactic acid metabolism related differentially expressed genes (LAMRDEGs) in HCC remain poorly understood.…”

Development and Validation of a Novel Nomogram Integrated with Hypoxic and Lactate Metabolic Characteristics for Prognosis Prediction in Hepatocellular Carcinoma

“… 17 , 45 Prognostic models based on HRGs or LRGs have been constructed for HCC. 46 , 47 However, no research has been published on a HLPM for HCC, which integrated with the characteristics of both hypoxia and lactate metabolism. Given the heterogeneity of HCC and the strong relationship between hypoxia and lactate metabolism, it remains necessary to construct prognostic models of HLRGs for predicting survival, immune landscape and treatment responses of patients with HCC.…”

Development and Validation of a Novel Prognosis Model Based on a Panel of Three Immunogenic Cell Death-Related Genes for Non-Cirrhotic Hepatocellular Carcinoma

“…The IC50 values of common chemotherapy drugs, small-molecule drugs, or targeted drugs against HCC were analyzed in the high-risk and low-risk groups. [37][38][39][40] The IC50 values of vinblastine, axitinib, GDC-0449, methotrexate, and docetaxel against tumors in the high-risk group were significantly higher than those against tumors in the low-risk group (Figure 6a-e, p < 0.05). In contrast, the IC50 values of bleomycin, cisplatin, doxorubicin, epothilone B, gemcitabine, mitomycin C, obatoclax, mesylate, and sorafenib against tumors in the high-risk group were lower than those against tumors in the low-risk group, indicating that these prognostic-related genes may influence the therapeutic efficacy of drugs against HCC (Figure 6f-m, p < 0.05).…”