Characterization of Immunogenicity of Malignant Cells with Stemness in Intrahepatic Cholangiocarcinoma by Single-Cell RNA Sequencing

Integration of single-cell RNA-seq and bulk RNA-seq to construct liver hepatocellular carcinoma stem cell signatures to explore their impact on patient prognosis and treatment

BACKGROUND

Liver hepatocellular carcinoma (LIHC) is a prevalent form of primary liver cancer. Research has demonstrated the contribution of tumor stem cells in facilitating tumor recurrence, metastasis, and treatment resistance. Despite this, there remains a lack of established cancer stem cells (CSCs)-associated genes signatures for effectively predicting the prognosis and guiding the treatment strategies for patients diagnosed with LIHC.

METHODS

The single-cell RNA sequencing (scRNA-seq) and bulk RNA transcriptome data were obtained based on public datasets and computerized firstly using CytoTRACE package and One Class Linear Regression (OCLR) algorithm to evaluate stemness level, respectively. Then, we explored the association of stemness indicators (CytoTRACE score and stemness index, mRNAsi) with survival outcomes and clinical characteristics by combining clinical information and survival analyses. Subsequently, weighted co-expression network analysis (WGCNA) and Cox were applied to assess mRNAsi-related genes in bulk LIHC data and construct a prognostic model for LIHC patients. Single-sample gene-set enrichment analysis (ssGSEA), Cell-type Identification By Estimating Relative Subsets Of RNA Transcripts (CIBERSORT) and Tumor Immune Estimation Resource (TIMER) analysis were employed for immune infiltration assessment. Finally, the potential immunotherapeutic response was predicted by the Tumor Immune Dysfunction and Exclusion (TIDE), and the tumor mutation burden (TMB). Additionally, pRRophetic package was applied to evaluate the sensitivity of high and low-risk groups to common chemotherapeutic drugs.

RESULTS

A total of four genes (including STIP1, H2AFZ, BRIX1, and TUBB) associated with stemness score (CytoTRACE score and mRNAsi) were identified and constructed a risk model that could predict prognosis in LIHC patients. It was observed that high stemness cells occurred predominantly in the late stages of LIHC and that poor overall survival in LIHC patients was also associated with high mRNAsi scores. In addition, pathway analysis confirmed the biological uniqueness of the two risk groups. Personalized treatment predictions suggest that patients with a low risk benefited more from immunotherapy, while those with a high risk group may be conducive to chemotherapeutic drugs.

CONCLUSION

The current study developed a novel prognostic risk signature with genes related to CSCs, which provides novel ideas for the diagnosis, prognosis and treatment of LIHC.

CXCL6: A potential therapeutic target for inflammation and cancer

Chemokines were originally defined as cytokines that affect the movement of immune cells. In recent years, due to the increasing importance of immune cells in the tumor microenvironment (TME), the role of chemokines has changed from a single "chemotactic agent" to a key factor that can regulate TME and affect the tumor phenotype. CXCL6, also known as granulocyte chemoattractant protein-2 (GCP-2), can recruit neutrophils to complete non-specific immunity in the process of inflammation. Cancer-related genes and interleukin family can promote the abnormal secretion of CXCL6, which promotes tumor growth, metastasis, epithelial mesenchymal transformation (EMT) and angiogenesis in the TME. CXCL6 also has a role in promoting fibrosis and tissue damage repair. In this review, we focus on the regulatory network affecting CXCL6 expression, its role in the progress of inflammation and how it affects tumorigenesis and progression based on the TME, in an attempt to provide a potential target for the treatment of diseases such as inflammation and cancer.

Unraveling the heterogeneity of cholangiocarcinoma and identifying biomarkers and therapeutic strategies with single-cell sequencing technology

Cholangiocarcinoma (CCA) is a common malignant tumor of the biliary tract that carries a high burden of morbidity and a poor prognosis. Due to the lack of precise diagnostic methods, many patients are often diagnosed at advanced stages of the disease. The current treatment options available are of varying efficacy, underscoring the urgency for the discovery of more effective biomarkers for early diagnosis and improved treatment. Recently, single-cell sequencing (SCS) technology has gained popularity in cancer research. This technology has the ability to analyze tumor tissues at the single-cell level, thus providing insights into the genomics and epigenetics of tumor cells. It also serves as a practical approach to study the mechanisms of cancer progression and to explore therapeutic strategies. In this review, we aim to assess the heterogeneity of CCA using single-cell sequencing technology, with the ultimate goal of identifying possible biomarkers and potential treatment targets.

Revealing the Heterogeneity of the Tumor Ecosystem of Cholangiocarcinoma through Single-Cell Transcriptomics

The prognosis of cholangiocarcinoma remains poor. The heterogeneity of the tumor ecosystem of cholangiocarcinoma plays a critical role in tumorigenesis and therapeutic resistance, thereby affecting the clinical outcome of patients with cholangiocarcinoma. Recent progress in single-cell RNA sequencing (scRNA-seq) has enabled detailed characterization of intratumoral stromal and malignant cells, which has vastly improved our understanding of the heterogeneity of various cell components in the tumor ecosystem of cholangiocarcinoma. It also provides an unprecedented view of the phenotypical and functional diversity in tumor and stromal cells including infiltrating immune cells. This review focuses on examining tumor heterogeneity and the interaction between various cellular components in the tumor ecosystem of cholangiocarcinoma derived from an scRNA-seq dataset, discussing limitations in current studies, and proposing future directions along with potential clinical applications.

Multi-omics analysis of the oncogenic value of copper Metabolism-Related protein COMMD2 in human cancers

BACKGROUND

The copper metabolism MURR1 domain (COMMD) protein family is involved in tumorigenicity of malignant tumors. However, as the member of COMMD, the role of COMMD2 in human tumors remains unknown.

METHODS

We used The Cancer Genome Atlas (TCGA), Genotype Tissue Expression (GTEx), Human Protein Atlas (HPA) database, Cancer Cell Line Encyclopedia (CCLE) platform, univariate Cox regression analysis, Kaplan-Meier curve, cBioPortal, UALCAN database, Sangerbox online platform, GSCA database gene set enrichment analysis (GSEA), and GeneMANIA to analyze the expression of COMMD2, its prognostic values, genomic alteration patterns, and the correlation with tumor stemness, tumor mutational burden (TMB), microsatellite instability (MSI), and immune infiltrates, drug sensitivity, and gene function enrichment in pan-cancer. qRT-PCR, CCK-8, EdU, wound healing, and transwell migration assays were performed to confirm the function of COMMD2.

RESULTS

COMMD2 was strongly expressed in most cancer types. Elevated COMMD2 expression affects the prognosis, clinicopathological stage, and molecular or immune subtypes of various tumors. Moreover, promoter hypomethylation and mutations in the COMMD2 gene may be associated with its high expression and poor survival. Additionally, we discovered that COMMD2 expression was linked to tumor stemness, TMB, MSI, immune cell infiltration, immune-checkpoint inhibitors, and drug sensitivity in pan-cancer. Furthermore, the COMMD2 gene co-expression network is constructed with GSEA analysis, displaying significant interaction of COMMD2 with E2F targets, G2-M checkpoint, and mitotic spindle in bladder cancer (BLCA). Finally, RNA interference data showed suppression of COMMD2 prevented proliferation and migration of BLCA and uterine corpus endometrial carcinoma (UCEC) cells.

CONCLUSION

Our findings shed light on the COMMD2 functions in human cancers and demonstrate that it is a promising prognostic biomarker and therapeutic target in pan-cancer.