Pan-Cancer Analysis Predicts FOXS1 as a Key Target in Prognosis and Tumor Immunotherapy

FOXS1 acts as an oncogene and induces EMT through FAK/PI3K/AKT pathway by upregulating HILPDA in prostate cancer

Prostate cancer (PCa) is a widespread global health concern characterized by elevated rates of occurrence, and there is a need for novel therapeutic targets to enhance patient outcomes. FOXS1 is closely linked to different cancers, but its function in PCa is still unknown. The expression of FOXS1, its prognostic role, clinical significance in PCa, and the potential mechanism by which FOXS1 affects PCa progression were investigated through bioinformatics analysis utilizing public data. The levels of FOXS1 and HILPDA were evaluated in clinical PCa samples using various methods, such as western blotting, immunohistochemistry, and qRT-PCR. To examine the function and molecular mechanisms of FOXS1 in PCa, a combination of experimental techniques including CCK-8 assay, flow cytometry, wound-healing assay, Transwell assay, and Co-IP assay were employed. The FOXS1 expression levels were significantly raised in PCa, correlating strongly with tumor aggressiveness and an unfavorable prognosis. Regulating FOXS1 expression, whether upregulating or downregulating it, correspondingly enhanced or inhibited the growth, migration, and invasion capabilities of PCa cells. Mechanistically, we detected a direct interaction between FOXS1 and HILPDA, resulting in the pathway activation of FAK/PI3K/AKT and facilitation EMT in PCa cells. FOXS1 collaborates with HILPDA to initiate EMT, thereby facilitating the PCa progression through the FAK/PI3K/AKT pathway activation.

FOXS1 is increased in liver fibrosis and regulates TGFβ responsiveness and proliferation pathways in human hepatic stellate cells

Liver fibrosis commences with liver injury stimulating transforming growth factor beta (TGFβ) activation of hepatic stellate cells (HSCs), causing scarring and irreversible damage. TGFβ induces expression of the transcription factor Forkhead box S1 (FOXS1) in hepatocytes and may have a role in the pathogenesis of hepatocellular carcinoma (HCC). To date, no studies have determined how it affects HSCs. We analyzed human livers with cirrhosis, HCC, and a murine fibrosis model and found that FOXS1 expression is significantly higher in fibrotic livers but not in HCC. Next, we treated human LX2 HSC cells with TGFβ to activate fibrotic pathways, and FOXS1 mRNA was significantly increased. To study TGFβ-FOXS1 signaling, we developed human LX2 FOXS1 CRISPR KO and scrambled control HSCs. To determine differentially expressed gene transcripts controlled by TGFβ-FOXS1, we performed RNA-seq in the FOXS1 KO and control cells and over 400 gene responses were attenuated in the FOXS1 KO HSCs with TGFβ-activation. To validate the RNA-seq findings, we used our state-of-the-art PamGene PamStation kinase activity technology that measures hundreds of signaling pathways nonselectively in real time. Using our RNA-seq data, kinase activity data, and descriptive measurements, we found that FOXS1 controls pathways mediating TGFβ responsiveness, protein translation, and proliferation. Our study is the first to identify that FOXS1 may serve as a biomarker for liver fibrosis and HSC activation, which may help with early detection of hepatic fibrosis or treatment options for end-stage liver disease.

Glioblastoma-Associated Mesenchymal Stem/Stromal Cells and Cancer-Associated Fibroblasts: Partners in Crime?

Tumor-associated mesenchymal stem/stromal cells (TA-MSCs) have been recognized as attractive therapeutic targets in several cancer types, due to their ability to enhance tumor growth and angiogenesis and their contribution to an immunosuppressive tumor microenvironment (TME). In glioblastoma (GB), mesenchymal stem cells (MSCs) seem to be recruited to the tumor site, where they differentiate into glioblastoma-associated mesenchymal stem/stromal cells (GA-MSCs) under the influence of tumor cells and the TME. GA-MSCs are reported to exert important protumoral functions, such as promoting tumor growth and invasion, increasing angiogenesis, stimulating glioblastoma stem cell (GSC) proliferation and stemness, mediating resistance to therapy and contributing to an immunosuppressive TME. Moreover, they could act as precursor cells for cancer-associated fibroblasts (CAFs), which have recently been identified in GB. In this review, we provide an overview of the different functions exerted by GA-MSCs and CAFs and the current knowledge on the relationship between these cell types. Increasing our understanding of the interactions and signaling pathways in relevant models might contribute to future regimens targeting GA-MSCs and GB-associated CAFs to inhibit tumor growth and render the TME less immunosuppressive.

SPP1, a potential therapeutic target and biomarker for lung cancer: functional insights through computational studies

NIH reported 128 different types of cancer of which lung cancer is the leading cause of mortality. Globally, it is estimated that on average one in every seventeen hospitalized patients was deceased. There are plenty of studies that have been reported on lung cancer draggability and therapeutics, but yet a protein that plays a central specific to cure the disease remains unclear. So, this study is designed to identify the possible therapeutic targets and biomarkers that can be used for the potential treatment of lung cancers. In order to identify differentially expressed genes, 39 microarray datasets of lung cancer patients were obtained from various demographic regions of the GEO database available at NCBI. After annotating statistically, 6229 up-regulated genes and 10324 down-regulated genes were found. Out of 17 up-regulated genes and significant genes, we selected SPP1 (osteopontin) through virtual screening studies. We found functional interactions with the other cancer-associated genes such as VEGF, FGA, JUN, EGFR, and TGFB1. For the virtual screening studies,198 biological compounds were retrieved from the ACNPD database and docked with SPP1 protein (PDBID: 3DSF). In the results, two highly potential compounds secoisolariciresinol diglucoside (-12.9 kcal/mol), and Hesperidin (-12.0 kcal/mol) showed the highest binding affinity. The stability of the complex was accessed by 100 ns simulation in an SPC water model. From the functional insights obtained through these computational studies, we report that SPP1 could be a potential biomarker and successive therapeutic protein target for lung cancer treatment.

Pan-cancer analyses reveal multi-omic signatures and clinical implementations of the forkhead-box gene family

BACKGROUND

Forkhead box (FOX) proteins belong to one of the largest transcription factor families and play crucial roles in the initiation and progression of cancer. Prior research has linked several FOX genes, such as FOXA1 and FOXM1, to the crucial process of carcinogenesis. However, the overall picture of FOX gene family across human cancers is far from clear.

METHODS

To investigate the broad molecular signatures of the FOX gene family, we conducted study on multi-omics data (including genomics, epigenomics and transcriptomics) from over 11,000 patients with 33 different types of human cancers.

RESULTS

Pan-cancer analysis reveals that FOX gene mutations were found in 17.4% of tumor patients with a substantial cancer type-dependent pattern. Additionally, high expression heterogeneity of FOX genes across cancer types was discovered, which can be partially attributed to the genomic or epigenomic alteration. Co-expression network analysis reveals that FOX genes may exert functions by regulating the expression of both their own and target genes. For a clinical standpoint, we provided 103 FOX gene-drug target-drug predictions and found FOX gene expression have potential survival predictive value. All of the results have been included in the FOX2Cancer database, which is freely accessible at http://hainmu-biobigdata.com/FOX2Cancer.

CONCLUSION

Our findings may provide a better understanding of roles FOX genes played in the development of tumors, and help to offer new avenues for uncovering tumorigenesis and unprecedented therapeutic targets.

Differential regulation of TNFα and IL-6 expression contributes to immune evasion in prostate cancer

BACKGROUND

The role of the inflammatory milieu in prostate cancer progression is not well understood. Differences in inflammatory signaling between localized and metastatic disease may point to opportunities for early intervention.

METHODS

We modeled PCa disease progression by analyzing RNA-seq of localized vs. metastatic patient samples, followed by CIBERSORTx to assess their immune cell populations. The VHA CDW registry of PCa patients was analyzed for anti-TNF clinical outcomes.

RESULTS

We observed statistically significant opposing patterns of IL-6 and TNFα expression between localized and metastatic disease. IL-6 was robustly expressed in localized disease and downregulated in metastatic disease. The reverse was observed with TNFα expression. Metastatic disease was also characterized by downregulation of adhesion molecule E-selectin, matrix metalloproteinase ADAMTS-4 and a shift to M2 macrophages whereas localized disease demonstrated a preponderance of M1 macrophages. Treatment with anti-TNF agents was associated with earlier stage disease at diagnosis.

CONCLUSIONS

Our data points to clearly different inflammatory contexts between localized and metastatic prostate cancer. Primary localized disease demonstrates local inflammation and adaptive immunity, whereas metastases are characterized by immune cold microenvironments and a shift towards resolution of inflammation and tissue repair. Therapies that interfere with these inflammatory networks may offer opportunities for early intervention in monotherapy or in combination with immunotherapies and anti-angiogenic approaches.

A novel inflammatory response-related signature predicts the prognosis of cutaneous melanoma and the effect of antitumor drugs

Cutaneous melanoma (CM) is a skin cancer that is highly metastatic and aggressive, with a dismal prognosis. This is the first study to use inflammatory response-related genes to build a model and evaluate their predictive significance in CM. This study used public databases to download CM patients' mRNA expression profiles and clinical data to create multigene prognostic markers in the UCSC cohort. We compared overall survival (OS) between high- and low-risk groups using the Kaplan-Meier curve and determined independent predictors using Cox analysis. We also used enrichment analysis to assess immune cell infiltration fraction and immune pathway-related activity using KEGG enrichment analysis. Furthermore, we detected prognostic genes' mRNA and protein expression in CM and normal skin tissues using qRT-PCR and immunohistochemistry. Finally, we developed a 5-gene predictive model that showed that patients in the high-risk group had a considerably shorter OS than those in the low-risk group. The analysis of the receiver operating characteristic (ROC) curve proved the model's predictive ability. We also conducted a drug sensitivity analysis and discovered that the expression levels of prognostic genes were substantially linked with cancer cell sensitivity to antitumor medicines. The findings show that the model we developed, which consists of five inflammatory response-related genes, can be used to forecast the prognosis and immunological state of CM, giving personalized and precision medicine a new goal and direction.