Pancancer Analysis Revealed the Value of RAC2 in Immunotherapy and Cancer Stem Cell

RAC2 as a Tumor-Suppressive Biomarker Associated with T Cell Infiltration in Breast Cancer

Background: RAC2 is critical in regulating the homeostasis of hematopoietic stem cells. Nonetheless, its role in breast cancer (BC) remains unclear, necessitating further investigation. Methods: The expression of RAC2 in BC and healthy tissues was acquired from The Cancer Genome Atlas. Its validity was further assessed using datasets from the gene expression omnibus database. The Tumor Immune Single-cell Hub database was used to collect and analyze the single-cell RNA sequencing datasets of BC. The diagnostic relevance of RAC2 was evaluated using receiver operating characteristic curves. Further assessment was carried out via enrichment analyses; Gene Set Analysis, immune scoring, single-cell sequencing, and immunohistochemical analysis were conducted to confirm the relationship between RAC2 expression and immune infiltration. Results: RAC2 expression was notably heightened in BC (p < 0.001). It was observed that a better prognosis was linked to heightened expression of RAC2 (p < 0.01), with the diagnostic efficacy of the marker noted to be good (area under the curve = 0.858). We found a lower percentage of protumor immune cells and a greater proportion of antitumor immune cells in the high RAC2. Our analysis revealed alterations in gene expression and an enriched network of immune pathways influenced by RAC2. Notably, cytotoxic genes, chemokines, chemokine receptors, immunostimulators, and immunosuppressive molecules positively correlated with RAC2 expression. RAC2 expression reliably predicted how patients would respond to two different therapeutic approaches in BC. Conclusions: The RAC2 was found to be a key biomarker in BC in the current study, demonstrating considerable potential as a prognostic and diagnostic marker. These results highlight the RAC2 potential to improve precision medicine strategies and treatment outcomes for patients with BC.

A Neutrophil Extracellular Traps-Related Signature Predicts Clinical Outcomes and Identifies Immune Landscape in Ovarian Cancer

Ovarian cancer (OvCa) is the most lethal gynaecology malignancies worldwide. Neutrophil extracellular traps (NETs), net-like protein structures produced by activated neutrophils and DNA-histone complexes, have a central role in tumours, though haven't been fully explored in OvCa. We obtained transcriptome data from TCGA-OvCa database (n = 376) as training, ICGC-OvCa database (n = 111) as validation and GTEx database (n = 180) as controls. Through LASSO-COX Regression analysis, we identified an eight-gene signature among 87 NETs-related genes, which was significantly related to poor prognosis in both TCGA-OvCa and ICGC-OvCa cohorts (Log-rank p-value = 0.0003 and 0.0014). Next, we constructed and validated a prognostic nomogram, consist of NETs-related signature and clinical features (C-index = 0.82). We evaluated 22 typical immune cell infiltration through CIBERSORT analysis, which implied upregulation of memory CD4 + T cells, follicular helper T cells and neutrophils in high-risk group. Additionally, we predicted therapy sensitivity through TIDE algorithm, indicating that high NETs-riskscore exhibited more sensitivity towards Sorafenib and less sensitivity towards immunotherapy. We initially reported that RAC2 upregulation was associated with NETs formation and poor prognosis (p-value < 0.05) through IHC analysis of tissue microarrays (n = 125). Conclusively, NETs-related signature was reliable for OvCa prognosis prediction and therapy assessment. Especially, RAC2 was predominantly related to NETs formation, thus providing hints towards anti-tumour mechanism of NETs in OvCa.

A single-cell transcriptome atlas of Lueyang black-bone chicken skin

As the largest organ of the body, the skin participates in various physiological activities, such as barrier function, sensory function, and temperature regulation, thereby maintaining the balance between the body and the natural environment. To date, compositional and transcriptional profiles in chicken skin cells have not been reported. Here, we report detailed transcriptome analyses of cell populations present in the skin of a black-feather chicken and a white-feather chicken using single-cell RNA sequencing (scRNA-seq). By analyzing cluster-specific gene expression profiles, we identified 12 cell clusters, and their corresponding cell types were also characterized. Subsequently, we characterized the subpopulations of keratinocytes, myocytes, mesenchymal cells, fibroblasts, and melanocytes. It is worth noting that we have identified a subpopulation of keratinocytes involved in pigment granule capture and a subpopulation of melanocytes involved in pigment granule deposition, both of which have a higher cell abundance in black-feather chicken compared to white-feather chicken. Meanwhile, we also compared the cellular heterogeneity features of Lueyang black-bone chicken skin with different feather colors. In addition, we also screened out 12 genes those could be potential markers of melanocytes. Finally, we validated the specific expression of SGK1, WNT5A, CTSC, TYR, and LAPTM5 in black-feather chicken, which may be the key candidate genes determining the feather color differentiation of Lueyang black-bone chicken. In summary, this study first revealed the transcriptome characteristics of chicken skin cells via scRNA-seq technology. These datasets provide valuable information for the study of avian skin characteristics and have important implications for future poultry breeding.

A Novel Oncogenic Role of Disulfidptosis-related Gene SLC7A11 in Anti-tumor Immunotherapy Response to Human Cancers

BACKGROUND

The protein Solute Carrier Family 7 Member 11 (SLC7A11) plays a pivotal role in cellular redox homeostasis by suppressing disulfidptosis, which restricts tumor growth. Yet, its relevance in prognosis, immunity, and cancer treatment efficacy is not well understood.

METHODS

We conducted a comprehensive analysis of the expression of SLC7A11 across 33 cancer types, employing datasets from public databases. Methods, such as Cox regression and survival analyses assessed its prognostic significance, while functional enrichment explored the biological processes tied to SLC7A11. The association between SLC7A11 expression, immune cell infiltration, and immune-related gene expression was also scrutinized.

RESULTS

Notably, SLC7A11 expression was more pronounced in cancerous compared to normal samples and correlated with higher tumor grades. Increased SLC7A11 expression was linked to poor outcomes, particularly in liver hepatocellular carcinoma (LIHC). This protein's expression also showcased significant relationships with diverse molecular and immune subtypes. Additionally, a prognostic nomogram was devised, integrating SLC7A11 expression and clinical variables. High SLC7A11 levels corresponded with cell growth and senescence pathways in various cancers and with lipid and cholesterol metabolism in LIHC. Furthermore, potential therapeutic compounds for LIHC with high SLC7A11 were identified. Real-time PCR (qPCR) and Western blot were conducted to explore the expression of SLC7A11 in tumor tissues and cancer cell lines.

CONCLUSION

In summation, this study emphasizes the prognostic and immunological importance of SLC7A11, spotlighting its potential as a therapeutic target in LIHC.