Risky decision-making in major depressive disorder: A three-level meta-analysis / Toma de decisiones arriesgadas en el trastorno depresivo mayor: un metanálisis de tres niveles

Background: Individuals with major depressive disorder (MDD) are usually observed making inappropriate risky decisions. However, whether and to what extent MDD is associated with impairments in risky decision-making remains unclear. We performed a three-level meta-analysis to explore the relationship between risky decision-making and MDD. Method: We searched the Web of Science, PubMed, Scopus, and PsycINFO databases up to February 7, 2023, and calculated Hedges' g to demonstrate the difference in risky decision-making between MDD patients and healthy controls (HCs). The moderating effect of sample and task characteristics were also revealed. Results: Across 73 effect sizes in 39 cross-sectional studies, MDD patients exhibited greater risk-seeking than HCs (Hedges' g = 0.187, p = .030). Furthermore, age (p = .068), region (p = .005), and task type (p < .001) were found to have moderating effects. Specifically, patients preferred risk-seeking over HCs as age increased. European patients showed significantly increased risk-seeking compared to American and Asian patients. Patients in the Iowa Gambling Task (IGT) exhibited a notable rise in risk-seeking compared to other tasks, along with an increased risk aversion in the Balloon Analogue Risk Task (BART). The multiple-moderator analysis showed that only task type had significant effects, which may be explained by a tentative framework of "operationalization-mechanism-measure" specificity. Conclusions: MDD patients generally exhibit higher risk-seeking than HCs. It implies that impaired risky decision-making might be a noteworthy symptom of depression, which should be placed more emphasis for clinical management and psycho-education.(AU)

Development of an immune-related prognostic biomarker for triple-negative breast cancer.

Purpose: Oncology studies employing digital dissection methodologies have provided some insight on the biological features of tumor microenvironment of Triple-negative breast cancer (TNBC), but molecular diagnostics rarely have therapeutic impact. We aimed to identify a novel prognostic biomarker to investigate immune characteristics of TNBC using transcriptomic features.Patients and Methods: We extracted whole transcriptome from breast cancer tissue of 30 TNBC patients and then used bioinformatics approaches to characterize the different immune cell contents in tumor tissue and para-cancerous tissue. We extract 2 indicators to describe the major differences in immune infiltration in the microenvironment between tumor tissue and para-cancerous tissue. We then combined the 2 indicators that represent the levels of increased and decreased infiltration in each sample to obtain the Immune Infiltration Score (IIS). Then we compared the tumor-infiltrating immune cell contents and immune infiltrating status in TNBC samples with CIBERSORT and ESTIMATE score to validate the IIS. Finally, 132 TNBC patients from the Cancer Genome Atlas program (TCGA) dataset was used to validate the predictive power of IIS.Results: 4 types of upregulated and 4 types of downregulated immune cells were identified in the tumor tissue samples of the TNBC patients. Then we developed a novel biomarker, IIS. Results showed that IIS score can clearly separate cancer and para-cancerous tissue. Using the same cutoff value of 0 in the TNBC-TCGA cohort, we show that those patients with a higher IIS had significantly higher PD-L1 expression and shorter progression-free survival time than those with a lower IIS value, indicating IIS score can be generalized to other TNBC datasets.Conclusion: we explored the immune infiltration landscape in 30 TNBC patients and provided IIS as a novel and reliable biomarker to evaluate the progression-free survival and prognosis of the TNBC patients.

Identification of Five Cytotoxicity-Related Genes Involved in the Progression of Triple-Negative Breast Cancer.

Background: Breast cancer is one of the deadly tumors in women, and its incidence continues to increase. This study aimed to identify novel therapeutic molecules using RNA sequencing (RNA-seq) data of breast cancer from our hospital. Methods: 30 pairs of human breast cancer tissue and matched normal tissue were collected and RNA sequenced in our hospital. Differentially expressed genes (DEGs) were calculated with raw data by the R package "edgeR", and functionally annotated using R package "clusterProfiler". Tumor-infiltrating immune cells (TIICs) were estimated using a website tool TIMER 2.0. Effects of key genes on therapeutic efficacy were analyzed using RNA-seq data and drug sensitivity data from two databases: the Cancer Cell Line Encyclopedia (CCLE) and the Cancer Therapeutics Response Portal (CTRP). Results: There were 2,953 DEGs between cancerous and matched normal tissue, as well as 975 DEGs between primary breast cancer and metastatic breast cancer. These genes were primarily enriched in PI3K-Akt signaling pathway, calcium signaling pathway, cAMP signaling pathway, and cell cycle. Notably, CD8+ T cell, M0 macrophage, M1 macrophage, regulatory T cell and follicular helper T cell were significantly elevated in cancerous tissue as compared with matched normal tissue. Eventually, we found five genes (GALNTL5, MLIP, HMCN2, LRRN4CL, and DUOX2) were markedly corelated with CD8+ T cell infiltration and cytotoxicity, and associated with therapeutic response. Conclusion: We found five key genes associated with tumor progression, CD8+ T cell and therapeutic efficacy. The findings would provide potential molecular targets for the treatment of breast cancer.

PRKDC is a prognostic marker for poor survival in gastric cancer patients and regulates DNA damage response.

A hallmark of gastric cancer is the high rate of genomic instability associated with deregulation of DNA damage repair pathways. DNA-Dependent Protein Kinase Catalytic Subunit (PRKDC) is a key component of the non-homologous end-joining (NHEJ) pathway. By reanalyzing transcriptome data of 80 pairs of gastric cancer tumors and the adjacent normal tissues from non-treated patients, we identified PRKDC as the top upregulated DNA damage repair genes in gastric cancer. High expression of PRKDC is associated with poor survival of gastric cancer patients, and genomic amplification of the gene is frequently observed across most gastric cancer subtypes. Knockdown of PRKDC in gastric cell lines resulted in reduced proliferation and cell cycle arrest. Furthermore, we showed that loss of PRKDC induced DNA damage and enhanced gastric cancer cell chemosensitivity to DNA-damaging reagents. Together, our results suggest that PRKDC is a prognostic marker of poor survival and is a putative target to overcome chemoresistance in gastric cancer.

Application whole exome sequencing for the clinical molecular diagnosis of patients with Duchenne muscular dystrophy; identification of four novel nonsense mutations in four unrelated Chinese DMD patients.

BACKGROUND: Duchenne muscular dystrophy (DMD) is the most common form of inherited muscular dystrophy. Germline mutations in dystrophin (DMD) gene cause DMD, with a X-linked recessive mode of inheritance. Patients with DMD are usually characterized by weakness of muscle, usually started since childhood and gradually the patient will unable to stand and walk. METHODS: In our present study, we identified four unrelated Chinese patients with DMD from four Chinese families. Whole exome sequencing was performed for genetic molecular analysis for these probands. RESULTS: Whole exome sequencing and confirmatory Sanger sequencing identified four novel nonsense mutations in these four unrelated Chinese patients, respectively. All these four mutations lead to the formation of a truncated DMD protein by formation of a premature stop codon. According to the variant interpretation guidelines of American College of Medical Genetics and Genomics (ACMG), these four novel nonsense mutations are categorized as "likely pathogenic" variants. CONCLUSION: Our present finding not only identified four novel loss-of-function mutations in dystrophin (DMD) gene but also strongly emphasized the significance of whole exome sequencing as the most efficient way of identifying the candidate genes and mutations which enables us for easy and rapid clinical diagnosis, follow-up, and management of DMD patients.