Potential Applications of Dual Haptoglobin Expression in the Reclassification and Treatment of Hepatocellular Carcinoma.

HCC is a malignancy characterized by high incidence and mortality rates. Traditional classifications of HCC primarily rely on tumor morphology, phenotype, and multicellular molecular levels, which may not accurately capture the cellular heterogeneity within the tumor. Current research on HCC using scRNA-seq is predominantly focused on immune and stromal cells. This study integrates scRNA-seq and bulk RNA-seq to spotlight HP as a critical gene. HP is highly expressed in HCC malignant cells and lowly expressed in T cells. Within malignant cells, elevated HP expression interacts with C3, promoting Th1-type responses via the C3/C3AR1 axis. In T cells, down-regulating HP expression favors the expression of Th1 cell-associated marker genes, potentially enhancing Th1-type responses. Consequently, we developed a "HP-promoted Th1 response reclassification" gene set, correlating higher activity scores with improved survival rates in HCC patients. Additionally, four predictive models for neoadjuvant treatment based on HP and C3 expression were established: 1) Low HP and C3 expression with high Th2 cell infiltration; 2) High HP and low C3 expression with high Th2 cell infiltration; 3) High HP and C3 expression with high Th1 cell infiltration; 4) Low HP and high C3 expression with high Th1 cell infiltration. In conclusion, the HP gene selected from the HCC malignant cell subgroup (Malignant_Sub 6) might serve as a potential ally against the tumor by promoting Th1-type immune responses. The establishment of the "HP-promoted Th1 response reclassification" gene set offers predictive insights for HCC patient survival prognosis and neoadjuvant treatment efficacy, providing directions for clinical treatments.

Anoikis resistance--protagonists of breast cancer cells survive and metastasize after ECM detachment.

Breast cancer exhibits the highest global incidence among all tumor types. Regardless of the type of breast cancer, metastasis is a crucial cause of poor prognosis. Anoikis, a form of apoptosis initiated by cell detachment from the native environment, is an outside-in process commencing with the disruption of cytosolic connectors such as integrin-ECM and cadherin-cell. This disruption subsequently leads to intracellular cytoskeletal and signaling pathway alterations, ultimately activating caspases and initiating programmed cell death. Development of an anoikis-resistant phenotype is a critical initial step in tumor metastasis. Breast cancer employs a series of stromal alterations to suppress anoikis in cancer cells. Comprehensive investigation of anoikis resistance mechanisms can inform strategies for preventing and regressing metastatic breast cancer. The present review first outlines the physiological mechanisms of anoikis, elucidating the alterations in signaling pathways, cytoskeleton, and protein targets that transpire from the outside in upon adhesion loss in normal breast cells. The specific anoikis resistance mechanisms induced by pathological changes in various spatial structures during breast cancer development are also discussed. Additionally, the genetic loci of targets altered in the development of anoikis resistance in breast cancer, are summarized. Finally, the micro-RNAs and targeted drugs reported in the literature concerning anoikis are compiled, with keratocin being the most functionally comprehensive. Video Abstract.

Transcriptomic characterization revealed that METTL7A inhibits melanoma progression via the p53 signaling pathway and immunomodulatory pathway.

METTL7A is a protein-coding gene expected to be associated with methylation, and its expression disorder is associated with a range of diseases. However, few research have been carried out to explore the relationship between METTL7A and tumor malignant phenotype as well as the involvement potential mechanism. We conducted our research via a combination of silico analysis and molecular biology techniques to investigate the biological function of METTL7A in the progression of cancer. Gene expression and clinical information were extracted from the TCGA database to explore expression variation and prognostic value of METTL7A. In vitro, CCK8, transwell, wound healing and colony formation assays were conducted to explore the biological functions of METT7A in cancer cell. GSEA was performed to explore the signaling pathway involved in METTL7A and validated via western blotting. In conclusion, METTL7A was downregulated in most cancer tissues and its low expression was associated with shorter overall survival. In melanoma, METTL7A downregulation was associated with poorer clinical staging, lower levels of TIL infiltration, higher IC50 levels of chemotherapeutic agents, and poorer immunotherapy outcomes. QPCR results confirm that METTL7A is down-regulated in melanoma cells. Cell function assays showed that METTL7A knockdown promoted proliferation, invasion, migration and clone formation of melanoma cells. Mechanistic studies showed that METTL7A inhibits tumorigenicity through the p53 signaling pathway. Meanwhile, METTL7A is also a potential immune regulatory factor.

CD3ζ as a novel predictive biomarker of PD-1 inhibitor resistance in melanoma.

Malignant melanoma is the most lethal form of skin cancer, and its incidence rates are increasing in Europe, America, and Oceania countries. Despite immune checkpoint inhibitors, such as PD-1 inhibitors, have been shown to have significant therapeutic effects on malignant melanoma, many patients are unresponsive to these treatments, even emerged resistance. There is an urgent need to discover novel biomarkers that might distinguish resistant patients from responders. In this study, we used a series of bioinformatics analyses and experimental validation. The GSE65041 was used for differential expression analysis. Kaplan-Meier was used to assess the prognostic value. ESTIMATE, ssGSEA, EPIC, TIMER, quanTiseq and MCPcounter for estimation of immune infiltration in the tumor microenvironment. We eventually identified that CD3ζ was significantly down-regulated in IHC PD-L1(-) melanoma patients. Low level of CD3ζ expression possessed a poor prognosis. CD3ζ low expression population is significantly associated with lower immune infiltration. In vivo experiment, CD3ζ expression was significantly down-regulated in mice melanoma after intradermally injected with B16-F10R cells. Compared to their wildtype counterparts, melanoma resistant mice treated with nivolumab showed significant reductions in tumor volume and weight when adding CD3ζ. In vitro experiment, the addition of CD3ζ increased nivolumab effection on inhibiting B16-F10R cell viability. Our findings indicated that CD3ζ could be a novel predictive biomarker of PD-1 inhibitor resistance in melanoma.

Sema4D silencing increases the sensitivity of nivolumab to B16-F10 resistant melanoma via inhibiting the PI3K/AKT signaling pathway.

Melanoma is a common skin tumor that causes a high rate of mortality, especially in Europe, North America and Oceania. Immunosuppressants such as anti-PD-1 have been used in the treatment of malignant melanoma, however, nearly 60% of patients do not respond to these treatments. Sema4D, also called CD100, is expressed in T cells and tumor tissues. Sema4D and its receptor, Plexin-B1, play crucial roles in the process of immune regulation, angiogenesis, and tumor progression. The role of Sema4D in melanoma with anti-PD-1 resistance is poorly understood. Through a combination of molecular biology techniques and in silico analysis, the role of Sema4D in improving anti-PD-L1 sensitivity in melanoma was explored. The results showed that the expression of Sema4D, Plexin-B1 and PD-L1 was significantly increased in B16-F10R cells. Sema4D knockdown synergizes with anti-PD-1 treatment, cell viability, cell invasion and migration were significantly decreased, while the apoptosis was increased, the growth of tumors on the mice was also inhibited. Mechanistically, bioinformatics analysis revealed that Sema4D is involved in the PI3K/AKT signaling pathway; the downregulation of p-PI3K/PI3K and p-AKT/AKT expression were observed in Sema4D knockdown, therefore, nivolumab resistance is related to Sema4D and Sema4D silencing can improve sensitivity to nivolumab via inhibition of the PI3K/AKT signaling pathway.

Vemurafenib inhibits immune escape biomarker BCL2A1 by targeting PI3K/AKT signaling pathway to suppress breast cancer.

Objectives: To investigate the role of immune escape encoding genes on the prognosis of BC, and to predict the novel targeting agents. Methods: Human immune genes and immune escape encoding genes were obtained from the IMMPORT database and the previous study. Sample information and clinical data on BC were obtained from the TCGA and GTEX databases. Obtaining differentially expressed protein data from cBioportal database. To construct a risk score model by lasso analysis, and nomogram was used to predict score core. GSCA, TIMER and CELLMINER databases were used for immune and drug susceptibility correlation analyses. Cell experiments were verified by MTT, Western blotting, and RT-qPCR. Results: We found prognostic models consisting of eleven immune escape related protein-coding genes with ROC curves that performed well in the ontology data (AUC for TCGA is 0.672) and the external data (AUC for GSE20685 is 0.663 and for GES42568 is 0.706). Five core prognostic models are related to survival (EIF4EBP1, BCL2A1, NDRG1, ERRFI1 and BRD4) were summarized, and a nomogram was constructed to validate a C-index of 0.695, which was superior to other prognostic models. Relevant drugs targeting core genes were identified based on drug sensitivity analysis, and found that Vemurafenib downregulates the PI3K-AKT pathway and BCL2A1 protein in BC, as confirmed by external data and cellular assays. Conclusions: Briefly, our work establishes and validates an 11-immune escape risk model, and five core prognostic factors that are mined deeply from this model, and elucidates in detail that Vemurafenib suppresses breast cancer by targeting the PI3K/AKT signaling pathway to inhibit the immune escape biomarker BCL2A1, confirms the validity of the prognostic model, and provides corresponding targeted agents to guide individualized treatment of BC patients.

Complex interaction and heterogeneity among cancer stem cells in head and neck squamous cell carcinoma revealed by single-cell sequencing.

Background: Cancer stem cells (CSCs) have been characterized to be responsible for multidrug resistance, metastasis, recurrence, and immunosuppressive in head and neck squamous cell carcinoma (HNSCC). However, the diversity of CSCs remains to be investigated. In this study, we aimed to determine the heterogeneity of CSCs and its effect on the formation of tumor microenvironment (TME). Methods: We depicted the landscape of HNSCC transcriptome profile by single-cell RNA-sequencing analysis of 20 HNSCC tissues from public databases, to reveal the Cell components, trajectory changes, signaling network, malignancy status and functional enrichment of CSCs within tumors. Results: Immune checkpoint molecules CD276, LILRB2, CD47 were significantly upregulated in CSCs, enabling host antitumor response to be weakened or damaged. Notably, naive CSCs were divided to 2 different types of cells with different functions, exhibiting functional diversity. In addition, CSCs underwent self-renewal and tumor metastasis activity through WNT and ncWNT signaling. Among them, Regulon regulators (IRF1_394g, IRF7_160g, NFKB1_12g, NFKB2_33g and STAT1_356g) were activated in subgroups 2 and 3, suggesting their pivotal roles in the inflammatory response process in tumors. Among all CSCs, naive CSCs appear to be the most malignant resulting in a worse prognosis. Conclusions: Our study reveals the major signal transduction and biological function of CSCs during HNSCC progression, highlighting the heterogeneity of CSCs and their underlying mechanisms in the formation of an immunosuppressive TME. Therefore, our study about heterogeneity of CSCs in HNSCC can bring new insights for the treatment of HNSCC.

Molecular profiling of core immune-escape genes highlights LCK as an immune-related prognostic biomarker in melanoma.

The tumor microenvironment is complicated and continuously evolving. This study was devoted to the identification of potential prognostic biomarkers based on the tumor microenvironment associated with immunotherapy for melanoma. This study integrates a couple of melanoma single cell and transcriptome sequencing datasets and performs a series of silico analyses as nicely as validation of molecular biology techniques. A core set of immune escape related genes was identified through Lawson et al. and the ImmPort portal. The differential proteins were identified through the cBioPortal database. Regression analysis was used to profile independent prognostic factors. Correlation with the level of immune cell infiltration was evaluated by multiple algorithms. The capacity of LCK to predict response was assessed in two independent immunotherapy cohorts. High LCK expression is associated with better prognosis, high levels of TILs and better clinical staging. Pathway analysis showed that high expression of LCK was significantly associated with activation of multiple tumor pathways as well as immune-related pathways. LCK expression tends to be higher in immunotherapy-responsive patients and those with lower IC50s treated with chemotherapeutic agents. RT-qPCR detected that LCK expression was significantly upregulated in melanoma cell lines. Single-cell transcriptome analysis showed that LCK was specifically highly expressed on T cells. CellChat analysis confirmed that LCK in C2 subpopulations and T cell subpopulations exerted immune promotion between cells by binding to CD8 receptors. In conclusion, LCK is a reliable biomarker for melanoma and will contribute to its immunotherapy.

Comprehensive analysis of chemokines family and related regulatory ceRNA network in lung adenocarcinoma.

Lung adenocarcinoma (LUAD) is one of the world's commonest malignancies with a high fatality rate. Chemokines not only regulate immune response but also participate in tumor development and metastasis and yet the mechanism of chemokines in LUAD remains unclear. In this study, transcriptional expression profiles, mutation data, and copy number variation data were downloaded from The Cancer Genome Atlas (TCGA). Risk gene protein expression was assessed by the Clinical Proteomic Tumor Analysis Consortium (CPTAC) and the Human Protein Atlas (HPA). Gene Expression Omnibus (GEO) data was used to validate the prognostic model. We summarized the genetic mutation variation landscape of chemokines. The risk prognosis model was developed based on differentially expressed chemokines, and patients in the high-risk score (RS) group had lower survival rates. Gene Set Enrichment Analysis (GSEA) revealed that high-RS patients were associated with metabolic transformation pathways, while low-RS patients were associated with immune-related pathways. Compared with the high-RS group, the low-RS group had higher immune/stromal/estimate scores calculated by the ESTIMATE package. The proportion of immune cells obtained using the CIBERSORT package was significantly different between the two groups. Most of the immune checkpoints were highly expressed in low-RS samples. Finally, we discovered that the lncRNA MIR17HG/AC009299.3/miR-21-5p/CCL20 regulatory network might be crucial in the pathogenesis of LUAD. In conclusion, we developed a risk signature and chemokine-related competing endogenous RNA (ceRNA) network.