Amino acid metabolism in tumor biology and therapy.

Amino acid metabolism plays important roles in tumor biology and tumor therapy. Accumulating evidence has shown that amino acids contribute to tumorigenesis and tumor immunity by acting as nutrients, signaling molecules, and could also regulate gene transcription and epigenetic modification. Therefore, targeting amino acid metabolism will provide new ideas for tumor treatment and become an important therapeutic approach after surgery, radiotherapy, and chemotherapy. In this review, we systematically summarize the recent progress of amino acid metabolism in malignancy and their interaction with signal pathways as well as their effect on tumor microenvironment and epigenetic modification. Collectively, we also highlight the potential therapeutic application and future expectation.

Pathogenesis and therapeutic strategies for cancer-related depression.

Depression is a common co-morbidity among cancer cases, which has a detrimental influence on cancer treatment and prognosis. Recent advancements in the neurobiology of depression and cancer pathophysiology have revealed several shared biobehavioral mechanisms and introduced new therapeutic strategies. In this review, we summarize the biological mechanisms driving cancer-related depression, including psychosocial factors, immuno-inflammatory processes, chronic stress, dysbiosis of gut microbiota, and medically-induced factors. Interventions used for cancer-related depression may include psychosocial therapies, pharmacological therapies, immunotherapies, psychobiological medications, and dietary strategies. This review could inspire the elucidation of possible co-occurring mechanisms and complex interactions between cancer and depression, provide an opportunity to propose faster and more effective therapies for cancer-related depression, and well as new strategies for cancer in the future.

Siglec-G Suppresses CD8+ T Cells Responses through Metabolic Rewiring and Can be Targeted to Enhance Tumor Immunotherapy.

CD8+ T cells play a critical role in cancer immune-surveillance and pathogen elimination. However, their effector function can be severely impaired by inhibitory receptors such as programmed death-1 (PD-1) and T cell immunoglobulin domain and mucin domain-3 (Tim-3). Here Siglec-G is identified as a coinhibitory receptor that limits CD8+ T cell function. Siglec-G is highly expressed on tumor-infiltrating T cells and is enriched in the exhausted T cell subset. Ablation of Siglec-G enhances the efficacy of adoptively transferred T cells and chimeric antigen receptor (CAR) T cells in suppressing solid tumors growth. Mechanistically, sialoglycan ligands, such as CD24 on tumor cells, activate the Siglec-G-SHP2 axis in CD8+ T cells, impairing metabolic reprogramming from oxidative phosphorylation to glycolysis, which dampens cytotoxic T lymphocyte (CTL) activation, expansion, and cytotoxicity. These findings discover a critical role for Siglec-G in inhibiting CD8+ T cell responses, suggesting its potential therapeutic effect in adoptive T cell therapy and tumor immunotherapy.

Integrating single-cell and bulk transcriptomic analyses to develop a cancer-associated fibroblast-derived biomarker for predicting prognosis and therapeutic response in breast cancer.

Background: Cancer-associated fibroblasts (CAFs) contribute to the progression and treatment of breast cancer (BRCA); however, risk signatures and molecular targets based on CAFs are limited. This study aims to identify novel CAF-related biomarkers to develop a risk signature for predicting the prognosis and therapeutic response of patients with BRCA. Methods: CAF-related genes (CAFRGs) and a risk signature based on these genes were comprehensively analyzed using publicly available bulk and single-cell transcriptomic datasets. Modular genes identified from bulk sequencing data were intersected with CAF marker genes identified from single-cell analysis to obtain reliable CAFRGs. Signature CAFRGs were screened via Cox regression and least absolute shrinkage and selection operator (LASSO) analyses. Multiple patient cohorts were used to validate the prognosis and therapeutic responsiveness of high-risk patients stratified based on the CAFRG-based signature. In addition, the relationship between the CAFRG-based signature and clinicopathological factors, tumor immune landscape, functional pathways, chemotherapy sensitivity and immunotherapy sensitivity was examined. External datasets were used and sample experiments were performed to examine the expression pattern of MFAP4, a key CAFRG, in BRCA. Results: Integrated analyses of single-cell and bulk transcriptomic data as well as prognostic screening revealed a total of 43 prognostic CAFRGs; of which, 14 genes (TLN2, SGCE, SDC1, SAV1, RUNX1, PDLIM4, OSMR, NT5E, MFAP4, IGFBP6, CTSO, COL12A1, CCDC8 and C1S) were identified as signature CAFRGs. The CAFRG-based risk signature exhibited favorable efficiency and accuracy in predicting survival outcomes and clinicopathological progression in multiple BRCA cohorts. Functional enrichment analysis suggested the involvement of the immune system, and the immune infiltration landscape significantly differed between the risk groups. Patients with high CAF-related risk scores (CAFRSs) exhibited tumor immunosuppression, enhanced cancer hallmarks and hyposensitivity to chemotherapy and immunotherapy. Five compounds were identified as promising therapeutic agents for high-CAFRS BRCA. External datasets and sample experiments validated the downregulation of MFAP4 and its strong correlation with CAFs in BRCA. Conclusions: A novel CAF-derived gene signature with favorable predictive performance was developed in this study. This signature may be used to assess prognosis and guide individualized treatment for patients with BRCA.