Integrative lactylation and tumor microenvironment signature as prognostic and therapeutic biomarkers in skin cutaneous melanoma.
The incidence of skin cutaneous melanoma (SKCM), one of the most aggressive and lethal skin tumors, is increasing worldwide. However, for advanced SKCM, we still lack an accurate and valid way to predict its prognosis, as well as novel theories to guide the planning of treatment options for SKCM patients. Lactylation (LAC), a novel post-translational modification of histones, has been shown to promote tumor growth and inhibit the antitumor response of the tumor microenvironment (TME) in a variety of ways. We hope that this study will provide new ideas for treatment options for SKCM patients, as well as research on the molecular mechanisms of SKCM pathogenesis and development.
At the level of the RNA sequencing set (TCGA, GTEx), we used differential expression analysis, LASSO regression analysis, and multifactor Cox regression analysis to screen for prognosis-related genes and calculate the corresponding LAC scores. The content of TME cells in the tumor tissue was calculated using the CIBERSORT algorithm, and the TME score was calculated based on its results. Finally, the LAC-TME classifier was established and further analyzed based on the two scores, including the construction of a prognostic model, analysis of clinicopathological characteristics, and correlation analysis of tumor mutation burden (TMB) and immunotherapy. Based on single-cell RNA sequencing data, this study analyzed the cellular composition in SKCM tissues and explored the role of LAC scores in intercellular communication. To validate the functionality of the pivotal gene CLPB in the model, cellular experiments were ultimately executed.
We screened a total of six prognosis-related genes (NDUFA10, NDUFA13, CLPB, RRM2B, HPDL, NARS2) and 7 TME cells with good prognosis. According to Kaplan-Meier survival analysis, we found that the LAClow/TMEhigh group had the highest overall survival (OS) and the LAChigh/TMElow group had the lowest OS (p value < 0.05). In further analysis of immune infiltration, tumor microenvironment (TME), functional enrichment, tumor mutational load and immunotherapy, we found that immunotherapy was more appropriate in the LAClow/TMEhigh group. Moreover, the cellular assays exhibited substantial reductions in proliferation, migration, and invasive potentials of melanoma cells in both A375 and A2058 cell lines upon CLPB knockdown.
The prognostic model using the combined LAC score and TME score was able to predict the prognosis of SKCM patients more consistently, and the LAC-TME classifier was able to significantly differentiate the prognosis of SKCM patients across multiple clinicopathological features. The LAC-TME classifier has an important role in the development of immunotherapy regimens for SKCM patients.
Zhu Y
,Song B
,Yang Z
,Peng Y
,Cui Z
,Chen L
,Song B
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Development of an IFNγ response-related signature for predicting the survival of cutaneous melanoma.
The tumor microenvironment (TME) plays a critical role in tumorigenesis, development, and therapeutic efficacy. Major advances have been achieved in the treatment of various cancers through immunotherapy. Nevertheless, only a minority of patients have positive responses to immunotherapy, which is partly due to conditions of the immunosuppressive microenvironment. Therefore, it is essential to identify prognostic biomarkers that reflect heterogeneous landscapes of the TME.
Based upon the ESTIMATE algorithm, we evaluated the infiltrating levels of immune and stromal components derived from patients afflicted by various types of cancer from The Cancer Genome Atlas database (TCGA). According to respective patient immune and stromal scores, we categorized cases into high- and low-scoring subgroups for each cancer type to explore associations between TME and patient prognosis. Gene Set Enrichment Analyses (GSEA) were conducted and genes enriched in IFNγ response signaling pathway were selected to facilitate establishment of a risk model for predicting overall survival (OS). Furthermore, we investigated the associations between the prognostic signature and tumor immune infiltration landscape by using CIBERSORT algorithm and TIMER database.
Among the cancers assessed, the immune scores for skin cutaneous melanoma (SKCM) were the most significantly correlated with patients' survival time (P < .0001). We identified and validated a five-IFNγ response-related gene signature (UBE2L6, PARP14, IFIH1, IRF2, and GBP4), which was closely correlated with the prognosis for SKCM afflicted patients. Multivariate Cox regression analysis indicated that this risk model was an independent prognostic factor for SKCM. Tumor-infiltrating lymphocytes and specific immune checkpoint molecules had notably differential levels of expression in high- compared to low-risk samples.
In this study, we established a novel five-IFNγ response-related gene signature that provided a better and increasingly comprehensive understanding of tumor immune landscape, and which demonstrated good performance in predicting outcomes for patients afflicted by SKCM.
Hu B
,Wei Q
,Li X
,Ju M
,Wang L
,Zhou C
,Chen L
,Li Z
,Wei M
,He M
,Zhao L
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《Cancer Medicine》