Background Stonin1 (STON1) is an endocytic protein but its role in cancer remains unclear. Here, we investigated the immune role of STON1 in kidney renal clear cell carcinoma (KIRC). Methods We undertook bioinformatics analyses of the expression and clinical significance of STON1 in KIRC through a series of public databases, and the role of STON1 in the tumor microenvironment and the predictive value for immunotherapy and targeted treatment in KIRC were identified with R packages. STON1 expression was validated in clinical KIRC tissues as well as in KIRC and normal renal tubular epithelial cells. Results Through public databases, STON1 mRNA was found to be significantly downregulated in KIRC compared with normal controls, and decreased STON1 was related to grade, TNM stage, distant metastasis and status of KIRC patients. Compared with normal controls, STON1 was found to be downregulated in KIRC tissues and cell lines. Furthermore, OncoLnc, Kaplan–Meier, and GEPIA2 analyses also suggested that KIRC patients with high STON1 expression had better overall survival. The high STON1 group with enriched immune cells had a more favorable prognosis than the low STON1 group with decreased immune cells. Single sample Gene Set Enrichment Analysis and Gene Set Variation Analysis indicated that STON1 creates an immune non-inflamed phenotype in KIRC. Moreover, STON1 was positively associated with mismatch repair proteins and negatively correlated with tumor mutational burden. Furthermore, Single sample Gene Set Enrichment Analysis algorithm and Pearson analysis found that the low STON1 group was more sensitive to immune checkpoint blockage whereas the high STON1 group was relatively suitable for targeted treatment. Conclusions Decreased STON1 expression in KIRC leads to clinical progression and poor survival. Mechanically, low STON1 expression is associated with an aberrant tumor immune microenvironment. Low STON1 is likely to be a favorable indicator for immunotherapy response but adverse indicator for targeted therapeutics in KIRC.

Background Triple-negative breast cancer (TNBC) is the most heterogenous and aggressive subtype of breast cancer. Chemotherapy remains the standard treatment option for patients with TNBC owing to the unavailability of acceptable targets and biomarkers in clinical practice. Novel biomarkers and targets for patient stratification and treatment of TNBC are urgently needed. It has been reported that the overexpression of DNA damage-inducible transcript 4 gene (DDIT4) is associated with resistance to neoadjuvant chemotherapy and poor prognosis in patients with TNBC. In this study, we aimed to identify novel biomarkers and therapeutic targets using RNA sequencing (RNA-seq) and data mining using data from public databases. Methods RNA sequencing (RNA-Seq) was performed to detect the different gene expression patterns in the human TNBC cell line HS578T treated with docetaxel or doxorubicin. Sequencing data were further analyzed by the R package “edgeR” and “clusterProfiler” to identify the profile of differentially expressed genes (DEGs) and annotate gene functions. The prognostic and predictive value of DDIT4 expression in patients with TNBC was further validated by published online data resources, including TIMER, UALCAN, Kaplan–Meier plotter, and LinkedOmics, and GeneMANIA and GSCALite were used to investigate the functional networks and hub genes related to DDIT4, respectively. Results Through the integrative analyses of RNA-Seq data and public datasets, we observed the overexpression of DDIT4 in TNBC tissues and found that patients with DDIT4 overexpression showed poor survival outcomes. Notably, immune infiltration analysis showed that the levels of DDIT4 expression correlated negatively with the abundance of tumor-infiltrating immune cells and immune biomarker expression, but correlated positively with immune checkpoint molecules. Furthermore, DDIT4 and its hub genes (ADM, ENO1, PLOD1, and CEBPB) involved in the activation of apoptosis, cell cycle, and EMT pathways. Eventually, we found ADM, ENO1, PLOD1, and CEBPB showed poor overall survival in BC patients. Conclusion In this study, we found that DDIT4 expression is associated with the progression, therapeutic efficacy, and immune microenvironment of patients with TNBC, and DDIT4 would be as a potential prognostic biomarker and therapeutic target. These findings will help to identify potential molecular targets and improve therapeutic strategies against TNBC.

Background Triple-negative breast cancer (TNBC) is the most heterogenous and aggressive subtype of breast cancer. Chemotherapy remains the standard treatment option for patients with TNBC owing to the unavailability of acceptable targets and biomarkers in clinical practice. Novel biomarkers and targets for patient stratification and treatment of TNBC are urgently needed. In this study, we aimed to identify novel biomarkers and therapeutic targets using RNA sequencing (RNA-seq) and data mining using data from public databases. Methods RNA-sequencing (RNA-Seq) was performed to detect the different gene expression patterns in the human TNBC cell line HS578T treated with docetaxel or doxorubicin. Raw data were analyzed using the R package “edgeR” to identify the profile of differentially expressed genes (DEGs) and functionally annotated through R package “clusterProfiler.” The prognostic and predictive value of DNA damage-inducible transcript 4 gene (DDIT4) expression in patients with TNBC was further studied using published online data resources, including TIMER, UALCAN, and Kaplan-Meier Plotter. LinkedOmics and GeneMANIA were used to investigate the genes and functional networks related to DDIT4. GSCALite was used to analyze the pathway activities of DDIT4 and its hub genes. Results Through the integrative analyses of RNA-Seq data and public datasets, we observed the overexpression of DDIT4 in TNBC tissues(p<0.01) and found that patients with DDIT4 overexpression showed poor survival outcomes (p<0.05). Notably, immune infiltration analysis showed that the levels of DDIT4 expression correlated negatively with the abundance of tumor-infiltrating immune cells and immune biomarker expression (p<0.05), but correlated positively with immune checkpoint molecules (p<0.01). Furthermore, DDIT4 and its hub genes (ADM, ENO1, PLOD1, and CEBPB) involved in the activation of Apoptosis, Cell Cycle and EMT pathways. Eventually, we found ADM, ENO1, PLOD1 and CEBPB showed poor overall survival in BC patients (p<0.01). Conclusion In this study, we found that DDIT4 expression is associated with the progression, therapeutic efficacy, and immune microenvironment of patients with TNBC, and DDIT4 would be as a potential prognostic biomarker and therapeutic target. These findings will help to identify potential new molecular targets and improve therapeutic strategies against TNBC.