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1.
Front Immunol ; 15: 1363834, 2024.
Artigo em Inglês | MEDLINE | ID: mdl-38633247

RESUMO

Background: Hyaluronan-mediated motility receptor (HMMR) is overexpressed in multiple carcinomas and influences the development and treatment of several cancers. However, its role in hepatocellular carcinoma (HCC) remains unclear. Methods: The "limma" and "GSVA" packages in R were used to perform differential expression analysis and to assess the activity of signalling pathways, respectively. InferCNV was used to infer copy number variation (CNV) for each hepatocyte and "CellChat" was used to analyse intercellular communication networks. Recursive partitioning analysis (RPA) was used to re-stage HCC patients. The IC50 values of various drugs were evaluated using the "pRRophetic" package. In addition, quantitative reverse transcription polymerase chain reaction (qRT-PCR) was performed to confirm HMMR expression in an HCC tissue microarray. Flow cytometry (FCM) and cloning, Edu and wound healing assays were used to explore the capacity of HMMR to regulate HCC tumour. Results: Multiple cohort studies and qRT-PCR demonstrated that HMMR was overexpressed in HCC tissue compared with normal tissue. In addition, HMMR had excellent diagnostic performance. HMMR knockdown inhibited the proliferation and migration of HCC cells in vitro. Moreover, high HMMR expression was associated with "G2M checkpoint" and "E2F targets" in bulk RNA and scRNA-seq, and FCM confirmed that HMMR could regulate the cell cycle. In addition, HMMR was involved in the regulation of the tumour immune microenvironment via immune cell infiltration and intercellular interactions. Furthermore, HMMR was positively associated with genomic heterogeneity with patients with high HMMR expression potentially benefitting more from immunotherapy. Moreover, HMMR was associated with poor prognosis in patients with HCC and the re-staging by recursive partitioning analysis (RPA) gave a good prognosis prediction value and could guide chemotherapy and targeted therapy. Conclusion: The results of the present study show that HMMR could play a role in the diagnosis, prognosis, and treatments of patients with HCC based on bulk RNA-seq and scRAN-seq analyses and is a promising molecular marker for HCC.


Assuntos
Carcinoma Hepatocelular , Receptores de Hialuronatos , Neoplasias Hepáticas , Humanos , Carcinoma Hepatocelular/genética , Variações do Número de Cópias de DNA , Proteínas da Matriz Extracelular/genética , Proteínas da Matriz Extracelular/metabolismo , Receptores de Hialuronatos/genética , Receptores de Hialuronatos/metabolismo , Análise da Expressão Gênica de Célula Única , Microambiente Tumoral/genética
2.
Sci Rep ; 14(1): 2189, 2024 01 25.
Artigo em Inglês | MEDLINE | ID: mdl-38273010

RESUMO

α-Enolase (ENO1) is a crucial molecular target for tumor therapy and has emerged as a research hotspot in recent decades. Here, we aimed to explore the role of ENO1 in bladder cancer (BLCA) and then construct a signature to predict the prognosis and treatment response of BLCA. Firstly, we found ENO1 was highly expressed in BLCA tissues, as verified by IHC, and was associated with poor prognosis. The analysis of the tumor immune microenvironment by bulk RNA-seq and scRNA-seq showed that ENO1 was associated with CD8+ T-cell exhaustion. Additionally, the results in vitro showed that ENO1 could promote the proliferation and invasion of BLCA cells. Then, the analysis of epithelial cells (ECs) revealed that ENO1 might promote BLCA progression by metabolism, the cell cycle and some carcinogenic pathways. A total of 249 hub genes were obtained from differentially expressed genes between ENO1-related ECs, and we used LASSO analysis to construct a novel signature that not only accurately predicted the prognosis of BLCA patients but also predicted the response to treatment for BLCA. Finally, we constructed a nomogram to better guide clinical application. In conclusion, through multi-omics analysis, we found that ENO1 was overexpressed in bladder cancer and associated with poor prognosis, CD8+ T-cell exhaustion and epithelial heterogeneity. Moreover, the prognosis and treatment of patients can be well predicted by constructing an epithelial-related prognostic signature.


Assuntos
Multiômica , Neoplasias da Bexiga Urinária , Humanos , Prognóstico , Neoplasias da Bexiga Urinária/genética , Nomogramas , Bexiga Urinária , Microambiente Tumoral/genética , Proteínas de Ligação a DNA/genética , Fosfopiruvato Hidratase/genética , Biomarcadores Tumorais/genética , Proteínas Supressoras de Tumor/genética
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