Identification of Lactate-Related Gene Signature for Prediction of Progression and Immunotherapeutic Response in Skin Cutaneous Melanoma

Xie, Yalin; Zhang, Jie; Li, Mengna; Li, Qian; Zheng, Yue; Wei, Lai

doi:10.3389/fonc.2022.818868

Cited by 10 publications

(10 citation statements)

References 69 publications

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“…The effect of hypoxia on prognosis, treatment guidance, and immune infiltration assessment has been reported in many tumors, such as cervical cancer, head and neck squamous cell carcinoma, and BC (34)(35)(36). Simultaneously, lactate metabolism was related to the outcomes and immune microenvironment in skin cutaneous melanoma, kidney renal clear cell carcinoma, and BC (37)(38)(39). In BC, prognostic models have been developed solely using lactate metabolism-related genes (LMRGs) or hypoxia-related genes [HRGs] (39)(40)(41).…”

Section: Introductionmentioning

confidence: 99%

A novel hypoxia- and lactate metabolism-related signature to predict prognosis and immunotherapy responses for breast cancer by integrating machine learning and bioinformatic analyses

Hao²,

Wu³

et al. 2022

Front. Immunol.

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BackgroundBreast cancer is the most common cancer worldwide. Hypoxia and lactate metabolism are hallmarks of cancer. This study aimed to construct a novel hypoxia- and lactate metabolism-related gene signature to predict the survival, immune microenvironment, and treatment response of breast cancer patients.MethodsRNA-seq and clinical data of breast cancer from The Cancer Genome Atlas database and Gene Expression Omnibus were downloaded. Hypoxia- and lactate metabolism-related genes were collected from publicly available data sources. The differentially expressed genes were identified using the “edgeR” R package. Univariate Cox regression, random survival forest (RSF), and stepwise multivariate Cox regression analyses were performed to construct the hypoxia-lactate metabolism-related prognostic model (HLMRPM). Further analyses, including functional enrichment, ESTIMATE, CIBERSORTx, Immune Cell Abundance Identifier (ImmuCellAI), TIDE, immunophenoscore (IPS), pRRophetic, and CellMiner, were performed to analyze immune status and treatment responses.ResultsWe identified 181 differentially expressed hypoxia-lactate metabolism-related genes (HLMRGs), 24 of which were valuable prognostic genes. Using RSF and stepwise multivariate Cox regression analysis, five HLMRGs were included to establish the HLMRPM. According to the medium-risk score, patients were divided into high- and low-risk groups. Patients in the high-risk group had a worse prognosis than those in the low-risk group (P < 0.05). A nomogram was further built to predict overall survival (OS). Functional enrichment analyses showed that the low-risk group was enriched with immune-related pathways, such as antigen processing and presentation and cytokine-cytokine receptor interaction, whereas the high-risk group was enriched in mTOR and Wnt signaling pathways. CIBERSORTx and ImmuCellAI showed that the low-risk group had abundant anti-tumor immune cells, whereas in the high-risk group, immunosuppressive cells were dominant. Independent immunotherapy datasets (IMvigor210 and GSE78220), TIDE, IPS and pRRophetic analyses revealed that the low-risk group responded better to common immunotherapy and chemotherapy drugs.ConclusionsWe constructed a novel prognostic signature combining lactate metabolism and hypoxia to predict OS, immune status, and treatment response of patients with breast cancer, providing a viewpoint for individualized treatment.

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Section: Introductionmentioning

confidence: 99%

A novel hypoxia- and lactate metabolism-related signature to predict prognosis and immunotherapy responses for breast cancer by integrating machine learning and bioinformatic analyses

Hao²,

Wu³

et al. 2022

Front. Immunol.

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“…Recent studies suggest the role of lactate metabolism-related genes in predicting tumor progression and response to immunotherapy. Xie et al demonstrated that the enhanced expression of four lactate risk-related genes, SLC25A3 , HPDL , NDUFA13 , and NARS2 , was correlated with poor prognosis in patients with skin cutaneous melanoma (SKCM), while patients with risk-related gene expression may benefit more from immune checkpoint inhibitor (ICI) therapy ( Xie et al, 2022 ). Sun et al established a lactate-related prognostic signature (LRPS) for the prognosis of patients with kidney renal clear cell carcinoma (KIRC) based on lactate metabolism-related genes and confirmed that LRPS might be effective in predicting the prognosis of patients with KIRC and that patients with low FPB1 and HDAH expression but high TYMP expression had a poor prognosis ( Sun et al, 2022 ).…”

Section: Discussionmentioning

confidence: 99%

Characterization of Lactate Metabolism Score in Breast and Thyroid Cancers to Assist Immunotherapy via Large-Scale Transcriptomic Data Analysis

Wang

Chen

et al. 2022

Front. Pharmacol.

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Breast cancer (BC) and thyroid cancer (TC) have the highest rate of incidence, especially in women. Previous studies have revealed that lactate provides energetic and anabolic support to cancer cells, thus serving as an important oncometabolite with both extracellular and intracellular signaling functions. However, the correlation of lactate metabolism scores with thyroid and breast cancer immune characteristics remains to be systematically analyzed. To investigate the role of lactate at the transcriptome level and its correlation with the clinical outcome of BC and TC, transcriptome data of 1,217 patients with breast cancer (BC) and 568 patients with thyroid cancer (TC) were collected from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) datasets with their corresponding clinical and somatic mutation data. The lactate metabolism score was calculated based on a single-sample gene set enrichment analysis (ssGSEA). The results showed that lactate metabolism-related genes and lactate metabolism scores was significantly associated with the survival of patients with BRCA and THCA. Notably, the lactate metabolism scores were strongly correlated with human leukocyte antigen (HLA) expression, tumor-infiltrating lymphocyte (TIL) infiltration, and interferon (IFN) response in BC and TC. Furthermore, the lactate metabolism score was an independent prognostic factor and could serve as a reliable predictor of overall survival, clinical characteristics, and immune cell infiltration, with the potential to be applied in immunotherapy or precise chemotherapy of BC and TC.

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“…In BC, lactate is correlated with resistance to PI3K inhibitors ( Hillis and TOKER, 2020 ). In several cancers, lactate is essential in predicting prognosis, tumor microenvironment, and immune response ( Mai et al, 2022 ; Sun et al, 2022 ; Xie et al, 2022 ). However, the prognostic value of lactate in BC remains largely unknown.…”

Section: Discussionmentioning

confidence: 99%

“…Research has shown the critical value of lactate and lncRNAs in cancer classification, prognosis, and immunotherapy ( Sun et al, 2022 ; Xie et al, 2022 ; Xu et al, 2022 ). However, lactate-related lncRNAs have not been well studied in BC.…”

Section: Introductionmentioning

confidence: 99%

A lactate-related LncRNA model for predicting prognosis, immune landscape and therapeutic response in breast cancer

Jia

Zhang²,

Li³

et al. 2022

Front. Genet.

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Breast cancer (BC) has the highest incidence rate of all cancers globally, with high heterogeneity. Increasing evidence shows that lactate and long non-coding RNA (lncRNA) play a critical role in tumor occurrence, maintenance, therapeutic response, and immune microenvironment. We aimed to construct a lactate-related lncRNAs prognostic signature (LRLPS) for BC patients to predict prognosis, tumor microenvironment, and treatment responses. The BC data download from the Cancer Genome Atlas (TCGA) database was the entire cohort, and it was randomly assigned to the training and test cohorts at a 1:1 ratio. Difference analysis and Pearson correlation analysis identified 196 differentially expressed lactate-related lncRNAs (LRLs). The univariate Cox regression analysis, least absolute shrinkage and selection operator (LASSO), and multivariate Cox regression analysis were used to construct the LRLPS, which consisted of 7 LRLs. Patients could be assigned into high-risk and low-risk groups based on the medium-risk sore in the training cohort. Then, we performed the Kaplan–Meier survival analysis, time-dependent receiver operating characteristic (ROC) curves, and univariate and multivariate analyses. The results indicated that the prognosis prediction ability of the LRLPS was excellent, robust, and independent. Furthermore, a nomogram was constructed based on the LRLPS risk score and clinical factors to predict the 3-, 5-, and 10-year survival probability. The GO/KEGG and GSEA indicated that immune-related pathways differed between the two-risk group. CIBERSORT, ESTIMATE, Tumor Immune Dysfunction and Exclusion (TIDE), and Immunophenoscore (IPS) showed that low-risk patients had higher levels of immune infiltration and better immunotherapeutic response. The pRRophetic and CellMiner databases indicated that many common chemotherapeutic drugs were more effective for low-risk patients. In conclusion, we developed a novel LRLPS for BC that could predict the prognosis, immune landscape, and treatment response.

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Identification of Lactate-Related Gene Signature for Prediction of Progression and Immunotherapeutic Response in Skin Cutaneous Melanoma

Cited by 10 publications

References 69 publications

A novel hypoxia- and lactate metabolism-related signature to predict prognosis and immunotherapy responses for breast cancer by integrating machine learning and bioinformatic analyses

A novel hypoxia- and lactate metabolism-related signature to predict prognosis and immunotherapy responses for breast cancer by integrating machine learning and bioinformatic analyses

Characterization of Lactate Metabolism Score in Breast and Thyroid Cancers to Assist Immunotherapy via Large-Scale Transcriptomic Data Analysis

A lactate-related LncRNA model for predicting prognosis, immune landscape and therapeutic response in breast cancer

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