A steady dysfunctional state caused by chronic antigen stimulation in the tumor microenvironment (TME) is known as CD8⁺ T cell exhaustion. Exhausted-like CD8⁺ T cells (CD8⁺ Tex) displayed decreased effector and proliferative capabilities, elevated co-inhibitory receptor generation, decreased cytotoxicity, and changes in metabolism and transcription. TME induces T cell exhaustion through long-term antigen stimulation, upregulation of immune checkpoints, recruitment of immunosuppressive cells, and secretion of immunosuppressive cytokines. CD8⁺ Tex may be both the reflection of cancer progression and the reason for poor cancer control. The successful outcome of the current cancer immunotherapies, which include immune checkpoint blockade and adoptive cell treatment, depends on CD8⁺ Tex. In this review, we are interested in the intercellular signaling network of immune cells interacting with CD8⁺ Tex. These findings provide a unique and detailed perspective, which is helpful in changing this completely unpopular state of hypofunction and intensifying the effect of immunotherapy.

Background: Clinically relevant postoperative pancreatic fistula (CR-POPF) is a common and troublesome complication after pancreatoduodenectomy (PD). We conducted a systematic review and meta-analysis to identify the risk factors of CR-POPF after PD. Methods: We searched PubMed, EMBASE, and Cochrane Library databases for studies related to risk factors of CR-POPF after PD. Odds ratios (ORs) with corresponding 95% confidence intervals (CIs) were extracted from the included studies, then a meta-analysis was conducted. If necessary, sensitivity analysis would be performed by changing the effect model or excluding 1 study at a time. Publication bias was assessed by funnel plot and Begg test and Egger test. Results: A total of 27 studies with 24,740 patients were included, and CR-POPF occurred in 3843 patients (incidence = 17%, 95% CI: 16%–19%). Male (OR = 1.56, 95% CI: 1.42–1.70), body mass index >25 kg/m² (OR = 1.98, 95% CI: 1.23–3.18), pancreatic duct diameter <3 mm (OR = 1.87, 95% CI: 1.66–2.12), soft pancreatic texture (OR = 3.49, 95% CI: 2.61–4.67), and blood transfusion (OR = 3.10, 95% CI: 2.01–4.77) can significantly increase the risk of CR-POPF. Pancreatic adenocarcinoma (OR = 0.54, 95% CI: 0.47–0.61), vascular resection (OR = 0.57, 95% CI: 0.39–0.83), and preoperative chemoradiotherapy (OR = 0.68, 95% CI: 0.57–0.81) can significantly decrease the factor of CR-POPF. Diabetes mellitus was not statistically associated with CR-POPF (OR = 0.66, 95% CI: 0.40–1.08). However, the analysis of body mass index, pancreatic texture, and diabetes mellitus had a high heterogeneity, then sensitivity analysis was performed, and the result after sensitivity analysis showed diabetes mellitus can significantly decrease the risk of CR-POPF. There was no significant publication bias in this meta-analysis. Conclusions: The current review assessed the effects of different factors on CR-POPF. This can provide a basis for the prevention and management of CR-POPF. Effective interventions targeting the above risk factors should be investigated in future studies for decreasing the occurrence of CR-POPF.

Melanoma is a malignant tumor of melanocytes and is often considered immunogenic cancer. Toll-like receptor-related genes are expressed differently in most types of cancer, depending on the immune microenvironment inside cancer, and the key function of Toll-like receptors (TLRs) for melanoma has not been fully elucidated. Based on multi-omics data from TCGA and GEO databases, we first performed pan-cancer analysis on TLR, including CNV, SNV, and mRNA changes in TLR-related genes in multiple human cancers, as well as patient prognosis characterization. Then, we divided melanoma patients into three subgroups (clusters 1, 2, and 3) according to the expression of the TLR pathway, and explored the correlation between TLR pathway and melanoma prognosis, immune infiltration, metabolic reprogramming, and oncogene expression characteristics. Finally, through univariate Cox regression analysis and LASSO algorithm, we selected six TLR-related genes to construct a survival prognostic model, divided melanoma patients into the training set, internal validation set 1, internal validation set 2, and external validation set for multiple validations, and discussed the correlation between model genes and clinical features of melanoma patients. In conclusion, we constructed a prognostic survival model based on TLR-related genes that precisely and independently demonstrated the potential to assess the prognosis and immune traits of melanoma patients, which is critical for patients’ survival.

Background: Necroptosis is crucial for organismal development and pathogenesis. To date, the role of necroptosis in skin cutaneous melanoma (SKCM) is yet unveiled. In addition, the part of melanin pigmentation was largely neglected in the bioinformatic analysis. In this study, we aimed to construct a novel prognostic model based on necroptosis-related genes and analysis the pigmentation phenotype of patients to provide clinically actionable information for SKCM patients. Methods: We downloaded the SKCM data from the TCGA and GEO databases in this study and identified the differently expressed and prognostic necroptosis-related genes. Patients’ pigmentation phenotype was evaluated by the GSVA method. Then, using Lasso and Cox regression analysis, a novel prognostic model was constructed based on the intersected genes. The risk score was calculated and the patients were divided into two groups. The survival differences between the two groups were compared using Kaplan-Meier analysis. The ROC analysis was performed and the area under curves was calculated to evaluate the prediction performances of the model. Then, the GO, KEGG and GSEA analyses were performed to elucidate the underlying mechanisms. Differences in the tumor microenvironment, patients’ response to immune checkpoint inhibitors (ICIs) and pigmentation phenotype were analyzed. In order to validate the mRNA expression levels of the selected genes, quantitative real-time PCR (qRT-PCR) was performed. Results: Altogether, a novel prognostic model based on four genes (BOK, CD14, CYLD and FASLG) was constructed, and patients were classified into high and low-risk groups based on the median risk score. Low-risk group patients showed better survival status. The model showed high accuracy in the training and the validation cohort. Pathway and functional enrichment analysis indicated that immune-related pathways were differently activated in the two groups. In addition, immune cells infiltration patterns and sensitivity of ICIs showed a significant difference between patients from two risk groups. The pigmentation score was positively related to the risk score in pigmentation phenotype analysis. Conclusion: In conclusion, this study established a novel prognostic model based on necroptosis-related genes and revealed the possible connections between necroptosis and melanin pigmentation. It is expected to provide a reference for clinical treatment.