TNF-like ligand 1A is associated with progression and prognosis of human gastric cancer

Identification and characterization of ferroptosis-related genes in therapy-resistant gastric cancer

Therapy resistance in gastric cancer poses ongoing challenges, necessitating the identification of ferroptosis-related genes linked to overall survival for potential therapeutic insights. The purpose of the study was to identify ferroptosis-related genes contributing to therapy resistance in gastric cancer and explore their associations with overall survival. Differentially expressed ferroptosis-related genes were identified in therapy-resistant versus therapy-responsive gastric cancer patients. Hub genes were selected from these genes. Enrichment analysis focused on oxidative stress and ROS metabolism. Validation was conducted in a TCGA stomach adenocarcinoma dataset. A hub gene-based risk model (DUSP1/TNF/NOX4/LONP1) was constructed and assessed for overall survival prediction. Associations with the tumor immune microenvironment were examined using the ESTIMATE algorithm and correlation analysis. Ten hub genes were identified, enriched in oxidative stress and ROS metabolism. Validation confirmed their aberrant expressions in the TCGA dataset. The hub gene-based risk model effectively predicted overall survival. High G6PD/TNF expression and low NOX4/SREBF1/MAPK3/DUSP1/KRAS/SIRT3/LONP1 expression correlated with stromal and immune scores. KRAS/TNF/MAPK3 expression positively correlated with immune-related SREBF1/NOX4 expression. DUSP1/NOX4/SREBF1/TNF/KRAS expression was associated with immune cell infiltration. The hub gene-based risk model (DUSP1/TNF/NOX4/LONP1) shows promise as an overall survival predictor in gastric cancer. Ferroptosis-related hub genes represent potential therapeutic targets for overcoming therapy resistance in gastric cancer treatment.

Comprehensive pathway-related genes signature for prognosis and recurrence of ovarian cancer

Background

Ovarian cancer (OC) is a highly malignant disease with a poor prognosis and high recurrence rate. At present, there is no accurate strategy to predict the prognosis and recurrence of OC. The aim of this study was to identify gene-based signatures to predict OC prognosis and recurrence.

Methods

mRNA expression profiles and corresponding clinical information regarding OC were collected from The Cancer Genome Atlas (TCGA) database. Gene set enrichment analysis (GSEA) and LASSO analysis were performed, and Kaplan–Meier curves, time-dependent ROC curves, and nomograms were constructed using R software and GraphPad Prism7.

Results

We first identified several key signalling pathways that affected ovarian tumorigenesis by GSEA. We then established a nine-gene-based signature for overall survival (OS) and a five-gene-based-signature for relapse-free survival (RFS) using LASSO Cox regression analysis of the TCGA dataset and validated the prognostic value of these signatures in independent GEO datasets. We also confirmed that these signatures were independent risk factors for OS and RFS by multivariate Cox analysis. Time-dependent ROC analysis showed that the AUC values for OS and RFS were 0.640, 0.663, 0.758, and 0.891, and 0.638, 0.722, 0.813, and 0.972 at 1, 3, 5, and 10 years, respectively. The results of the nomogram analysis demonstrated that combining two signatures with the TNM staging system and tumour status yielded better predictive ability.

Conclusion

In conclusion, the two-gene-based signatures established in this study may serve as novel and independent prognostic indicators for OS and RFS.

The Development and Homing of Myeloid-Derived Suppressor Cells: From a Two-Stage Model to a Multistep Narrative

Myeloid-derived suppressor cells (MDSC) represent a heterogeneous population of immature myeloid cells. Under normal conditions, they differentiate into macrophages, dendritic cells, and granulocytes. Under pathological conditions, such as chronic inflammation, or cancer, they tend to maintain their immature state as immature myeloid cells that, within the tumor microenvironment, become suppressor cells and assist tumor escape from immune eradication. MDSC are comprised of two major subsets: monocytic MDSC (M-MDSC) and polymorphonuclear MDSC (PMN-MDSC). Monocytic myeloid cells give rise to monocytic cells, whereas PMN-MDSC share similarities with neutrophils. Based on their biological activities, a two-stage model that includes the mobilization of the periphery as myeloid cells and their activation within the tumor microenvironment converting them into suppressor cells was previously suggested by D. Gabrilovich. From the migratory viewpoint, we are suggesting a more complex setup. It starts with crosstalk between the tumor site and the hematopoietic stem and progenitor cells (HSPCs) at the bone marrow (BM) and secondary lymphatic organs, resulting in rapid myelopoiesis followed by mobilization to the blood. Although myelopoiesis is coordinated by several cytokines and transcription factors, mobilization is selectively directed by chemokine receptors and may differ between M-MDSC and PMN-MDSC. These myeloid cells may then undergo further expansion at these secondary lymphatic organs and then home to the tumor site. Finally, selective homing of T cell subsets has been associated with retention at the target organs directed by adhesion molecules or chemokine receptors. The possible relevance to myeloid cells is still speculative but is discussed.