A Model of Basement Membrane-Associated Gene Signature Predicts Liver Hepatocellular Carcinoma Response to Immune Checkpoint Inhibitors

DHX34 as a promising biomarker for prognosis, immunotherapy and chemotherapy in Pan-Cancer: A Comprehensive Analysis and Experimental Validation

Background: As a member of the DExD/H-box RNA helicase family, DHX34 has demonstrated a significant correlation with the development of multiple disorders. Nevertheless, a comprehensive investigation between DHX34 and pan-cancer remains unexplored. Methods: We analyzed the value of DHX34 in pan-cancer based on some databases, such as The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO), and The Human Protein Atlas (HPA) by use the R language as well as some online analysis tools, including STRING, TISIDB, TISCH2. And based on our samples we performed Western blot (WB), qPCR and immunohistochemical staining (IHC) experiments. Results: DHX34 was highly expressed in most tumors, including Liver Hepatocellular Carcinoma (LIHC), compared to corresponding normal tissues. Among cervical cancers, DHX34 mutation frequency was the highest. Intriguingly, a positive correlation was observed between DHX34 expression and Mutational Burden (TMB) across 12 tumor types, and Microsatellite Instability (MSI) across 10 tumor types. Remarkably, DHX34 exhibited a favorable diagnostic value in a multitude of tumors. High expression of DHX34 is associated with poor prognosis in tumors such as adrenocortical carcinoma (ACC), renal papillary cell carcinoma (KIRP), low-grade glioma (LGG), and LIHC. Correlation analysis indicated that DHX34 expression correlated with clinicopathological features in a variety of tumors. The Protein-Protein Interaction (PPI) network and GSCALite database suggested that DHX34 and its ten co-expression genes might promote cancer progression by regulating the cell cycle. Gene Set Enrichment Analysis (GSEA) results further showed that DHX34 was positively correlated with pathways such as cell cycle, mitosis, and gene transcription regulation. The TISIDB database showed that DHX34 expression was closely associated with immune infiltration. Based on the TISCH2 database, we found that DHX34 was expressed in a number of immune cells, with relatively high expression in monocyte macrophages in LIHC. Conclusions: In summary, our study found that DHX34 is highly expressed in pan-cancer and has diagnostic and prognostic value. Targeting DHX34 may improve the therapeutic efficacy of immunotherapy and chemotherapy in a multitude of tumors.

Prognostic biomarkers associated with immune checkpoint inhibitors in hepatocellular carcinoma

The treatment of hepatocellular carcinoma (HCC), particularly advanced HCC, has been a serious challenge. Immune checkpoint inhibitors (ICIs) are landmark drugs in the field of cancer therapy in recent years, which have changed the landscape of cancer treatment. In the field of HCC treatment, this class of drugs has shown good therapeutic prospects. For example, atezolizumab in combination with bevacizumab has been approved as first-line treatment for advanced HCC due to significant efficacy. However, sensitivity to ICI therapy varies widely among HCC patients. Therefore, there is an urgent need to search for determinants of resistance/sensitivity to ICIs and to screen biomarkers that can predict the efficacy of ICIs. This manuscript reviews the research progress of prognostic biomarkers associated with ICIs in HCC in order to provide a scientific basis for the development of clinically individualised precision medication regimens.

Decoding tumor heterogeneity in uveal melanoma: basement membrane genes as novel biomarkers and therapeutic targets revealed by multi-omics approaches for cancer immunotherapy

Background: Uveal melanoma (UVM) is a primary intraocular malignancy that poses a significant threat to patients' visual function and life. The basement membrane (BM) is critical for establishing and maintaining cell polarity, adult function, embryonic and organ morphogenesis, and many other biological processes. Some basement membrane protein genes have been proven to be prognostic biomarkers for various cancers. This research aimed to develop a novel risk assessment system based on BMRGs that would serve as a theoretical foundation for tailored and accurate treatment. Methods: We used gene expression profiles and clinical data from the TCGA-UVM cohort of 80 UVM patients as a training set. 56 UVM patients from the combined cohort of GSE84976 and GSE22138 were employed as an external validation dataset. Prognostic characteristics of basement membrane protein-related genes (BMRGs) were characterized by Lasso, stepwise multifactorial Cox. Multivariate analysis revealed BMRGs to be independent predictors of UVM. The TISCH database probes the crosstalk of BMEGs in the tumor microenvironment at the single-cell level. Finally, we investigated the function of ITGA5 in UVM using multiple experimental techniques, including CCK8, transwell, wound healing assay, and colony formation assay. Results: There are three genes in the prognostic risk model (ADAMTS10, ADAMTS14, and ITGA5). After validation, we determined that the model is quite reliable and accurately forecasts the prognosis of UVM patients. Immunotherapy is more likely to be beneficial for UVM patients in the high-risk group, whereas the survival advantage may be greater for UVM patients in the low-risk group. Knockdown of ITGA5 expression was shown to inhibit the proliferation, migration, and invasive ability of UVM cells in vitro experiments. Conclusion: The 3-BMRGs feature model we constructed has excellent predictive performance which plays a key role in the prognosis, informing the individualized treatment of UVM patients. It also provides a new perspective for assessing pre-immune efficacy.