Ovarian cancer-associated immune exhaustion involves SPP1+ T cell and NKT cell, symbolizing more malignant progression

Single-cell transcriptomics reveals the multidimensional dynamic heterogeneity from primary to metastatic gastric cancer

Reprogramming of the tumor microenvironment (TME) plays a critical role in gastric cancer (GC) progression and metastasis. However, the multidimensional features between primary tumors and organ-specific metastases remain poorly understood. In this study, we characterized the dynamic heterogeneity of GC from primary to metastatic stages. We identified seven major cell types and 27 immune and stromal subsets. Immune cells decreased, while immunosuppressive cells increased in ovarian and peritoneal metastases. A 30-gene signature for ovarian metastasis was validated in GC cohorts. Additionally, critical ligand-receptor interactions, including LGALS9-MET in liver metastasis and PVR-TIGIT in lymph node metastasis, were identified as potential therapeutic targets. Furthermore, CLOCK, a transcription factor, was associated with poor prognosis and influenced immune cell interactions and migration. Collectively, this study provides valuable insights into TME dynamics in GC and highlights potential avenues for targeted therapies.

SPP1 as a Prognostic and Immunotherapeutic Biomarker in Gliomas and Other Cancer Types: A Pan-Cancer Study

Background

Gliomas, including glioblastoma (GBM), present significant treatment challenges due to their poor prognosis and complex tumor microenvironment. This study investigates the role of Secreted Phosphoprotein 1 (SPP1) as a prognostic and immunotherapeutic biomarker in gliomas and other cancers through pan-cancer analysis.

Methods

A comprehensive pan-cancer analysis was conducted using datasets from UCSC TCGA Pan-Cancer, TCGA-GBM, UALCAN, and single-cell sequencing data from GEO and TISCH. The correlation of SPP1 expression with overall survival (OS), progression-free survival (PFS), immune cell infiltration, and immune checkpoint markers was analyzed. Functional validation was performed via SPP1 knockdown in glioma cell lines to evaluate effects on proliferation, invasion, and immune interactions.

Results

SPP1 was found to be overexpressed in 27 tumor types, with high expression correlating with poor OS, PFS, and increased immune cell infiltration, particularly with CD8+ T cells and macrophages. Single-cell analysis indicated SPP1 enrichment in macrophages interacting with malignant GBM cells. Knockdown of SPP1 significantly inhibited glioma cell proliferation, invasion, and promoted apoptosis.

Conclusion

The findings suggest that SPP1 is a promising target for immunotherapy, potentially improving outcomes for patients with gliomas and other cancers. Further research is warranted to explore SPP1-targeted therapies and their efficacy in clinical settings.

Identification of the biological functions and chemo-therapeutic responses of ITGB superfamily in ovarian cancer

BACKGROUND

Patients with ovarian cancer (OC) tend to face a poor prognosis due to a lack of typical symptoms and a high rate of recurrence and chemo-resistance. Therefore, identifying representative and reliable biomarkers for early diagnosis and prediction of chemo-therapeutic responses is vital for improving the prognosis of OC.

METHODS

Expression levels, IHC staining, and subcellular distribution of eight ITGBs were analyzed using The Cancer Genome Atlas (TCGA)-Ovarian Serous Cystadenocarcinoma (OV) database, GEO DataSets, and the HPA website. PrognoScan and Univariate Cox were used for prognostic analysis. TIDE database, TIMER database, and GSCA database were used to analyze the correlation between immune functions and ITGBs. Consensus clustering analysis was performed to subtype OC patients in the TCGA database. LASSO regression was used to construct the predictive model. The Cytoscape software was used for identifying hub genes. The 'pRRophetic' R package was applied to predict chemo-therapeutic responses of ITGBs.

RESULTS

ITGBs were upregulated in OC tissues except ITGB1 and ITGB3. High expression of ITGBs correlated with an unfavorable prognosis of OC except ITGB2. In OC, there was a strong correlation between immune responses and ITGB2, 6, and 7. In addition, the expression matrix of eight ITGBs divided the TCGA-OV database into two subgroups. Subgroup A showed upregulation of eight ITGBs. The predictive model distinguishes OC patients from favorable prognosis to poor prognosis. Chemo-therapeutic responses showed that ITGBs were able to predict responses of common chemo-therapeutic drugs for patients with OC.

CONCLUSIONS

This article provides evidence for predicting prognosis, immuno-, and chemo-therapeutic responses of ITGBs in OC and reveals related biological functions of ITGBs in OC.

In Silico Approach to Molecular Profiling of the Transition from Ovarian Epithelial Cells to Low-Grade Serous Ovarian Tumors for Targeted Therapeutic Insights

This paper aims to elucidate the differentially coexpressed genes, their potential mechanisms, and possible drug targets in low-grade invasive serous ovarian carcinoma (LGSC) in terms of the biologic continuity of normal, borderline, and malignant LGSC. We performed a bioinformatics analysis, integrating datasets generated using the GPL570 platform from different studies from the GEO database to identify changes in this transition, gene expression, drug targets, and their relationships with tumor microenvironmental characteristics. In the transition from ovarian epithelial cells to the serous borderline, the FGFR3 gene in the "Estrogen Response Late" pathway, the ITGB2 gene in the "Cell Adhesion Molecule", the CD74 gene in the "Regulation of Cell Migration", and the IGF1 gene in the "Xenobiotic Metabolism" pathway were upregulated in the transition from borderline to LGSC. The ERBB4 gene in "Proteoglycan in Cancer", the AR gene in "Pathways in Cancer" and "Estrogen Response Early" pathways, were upregulated in the transition from ovarian epithelial cells to LGSC. In addition, SPP1 and ITGB2 genes were correlated with macrophage infiltration in the LGSC group. This research provides a valuable framework for the development of personalized therapeutic approaches in the context of LGSC, with the aim of improving patient outcomes and quality of life. Furthermore, the main goal of the current study is a preliminary study designed to generate in silico inferences, and it is also important to note that subsequent in vitro and in vivo studies will be necessary to confirm the results before considering these results as fully reliable.