Background Although breast cancer (BC) treatment has entered the era of precision therapy, the prognosis is good in the case of comprehensive multimodal treatment such as neoadjuvant, endocrine, and targeted therapy. However, due to its high heterogeneity, some patients still cannot benefit from conventional treatment and have poor survival prognoses. Amino acids and their metabolites affect tumor development, alter the tumor microenvironment, play an increasingly obvious role in immune response and regulation of immune cell function, and are involved in acquired and innate immune regulation; therefore, amino acid metabolism is receiving increasing attention. Methods Based on public datasets, we carried out a comprehensive transcriptome and single-cell sequencing investigation. Then we used 2.5 Weighted Co-Expression Network Analysis (WGCNA) and Cox to evaluate glutamine metabolism-related genes (GRGs) in BC and constructed a prognostic model for BC patients. Finally, the expression and function of the signature key gene SNX3 were examined by in vitro experiments. Results In this study, we constituted a risk signature to predict overall survival (OS) in BC patients by glutamine-related genes. According to our risk signature, BC patients can obtain a Prognostic Risk Signature (PRS), and the response to immunotherapy can be further stratified according to PRS. Compared with traditional clinicopathological features, PRS demonstrated robust prognostic power and accurate survival prediction. In addition, altered pathways and mutational patterns were analyzed in PRS subgroups. Our study sheds some light on the immune status of BC. In in vitro experiments, the knockdown of SNX3, an essential gene in the signature, resulted in a dramatic reduction in proliferation, invasion, and migration of MDA-MB-231 and MCF-7 cell lines. Conclusion We established a brand-new PRS consisting of genes associated with glutamine metabolism. It expands unique ideas for the diagnosis, treatment, and prognosis of BC.

/pdf/integrating-single-cell-rna-seq-and-bulk-rna-seq-to-2zi89i6p.pdf

Integrating single-cell RNA-seq and bulk RNA-seq to construct prognostic signatures to explore the role of glutamine metabolism in breast cancer

Background Despite tremendous advances in cancer research, breast cancer (BC) remains a major health concern and is the most common cancer affecting women worldwide. Breast cancer is a highly heterogeneous cancer with potentially aggressive and complex biology, and precision treatment for specific subtypes may improve survival in breast cancer patients. Sphingolipids are important components of lipids that play a key role in the growth and death of tumor cells and are increasingly the subject of new anti-cancer therapies. Key enzymes and intermediates of sphingolipid metabolism (SM) play an important role in regulating tumor cells and further influencing clinical prognosis. Methods We downloaded BC data from the TCGA database and GEO database, on which we performed in depth single-cell sequencing analysis (scRNA-seq), weighted co-expression network analysis, and transcriptome differential expression analysis. Then seven sphingolipid-related genes (SRGs) were identified using Cox regression, least absolute shrinkage, and selection operator (Lasso) regression analysis to construct a prognostic model for BC patients. Finally, the expression and function of the key gene PGK1 in the model were verified by in vitro experiments. Results This prognostic model allows for the classification of BC patients into high-risk and low-risk groups, with a statistically significant difference in survival time between the two groups. The model is also able to show high prediction accuracy in both internal and external validation sets. After further analysis of the immune microenvironment and immunotherapy, it was found that this risk grouping could be used as a guide for the immunotherapy of BC. The proliferation, migration, and invasive ability of MDA-MB-231 and MCF-7 cell lines were dramatically reduced after knocking down the key gene PGK1 in the model through cellular experiments. Conclusion This study suggests that prognostic features based on genes related to SM are associated with clinical outcomes, tumor progression, and immune alterations in BC patients. Our findings may provide insights for the development of new strategies for early intervention and prognostic prediction in BC.

/pdf/exploring-the-role-of-sphingolipid-related-genes-in-clinical-11w1eki5.pdf

Exploring the role of sphingolipid-related genes in clinical outcomes of breast cancer

The solute carrier (SLC) monocarboxylate transporter 1 (MCT1; SLC16A1) represents a promising target for the treatment of cancer; however, the MCT1 modulator landscape is underexplored with only roughly 100 reported compounds. To expand the knowledge about MCT1 modulation, we synthesized a library of 16 indole-based molecules and subjected these to a comprehensive biological assessment platform. All compounds showed functional inhibitory activities against MCT1 at low nanomolar concentrations and great antiproliferative activities against the MCT1-expressing cancer cell lines A-549 and MCF-7, while the compounds were selective over MCT4 (SLC16A4). Lead compound 24 demonstrated a greater potency than the reference compound, and molecular docking revealed strong binding affinities to MCT1. Compound 24 led to cancer cell cycle arrest as well as apoptosis, and it showed to sensitize these cancer cells toward an antineoplastic agent. Strikingly, compound 24 had also significant inhibitory power against the multidrug transporter ABCB1 and showed to reverse ABCB1-mediated multidrug resistance (MDR).

https://pubs.acs.org/doi/pdf/10.1021/acs.jmedchem.2c01612

Indole Derivatives as New Structural Class of Potent and Antiproliferative Inhibitors of Monocarboxylate Transporter 1 (MCT1; SLC16A1)

Skin cutaneous melanoma (SKCM) is a common cancer of which mortality is increasing continuously. Our study conducted a series of analyses on the clinical significance of Serine/threonine kinase 17B (STK17B) in SKCM to provide a new biomarker for diagnosis and treatment. The RNA-sequence data were obtained from The Cancer Genome Atlas and Genotype-Tissue Expression databases. The data of 468 SKCM patients were divided into STK17B high- and low-expression groups and analyzed by Bioconductor package to identify the differential expressed genes. The R package of “clusterProfiler” was used for Gene Ontology, Kyoto Encyclopedia of Genes and Genomes, and Gene-Set Enrichment Analysis analyses. A protein-protein interaction network and immune infiltration landscape were respectively constructed via STRING database and ssGSEA. STK17B had lower expression in SKCM than normal tissues. Besides, STK17B expression was significantly related to some clinicopathological characteristics in SKCM patients including T stage, Breslow depth, radiation therapy, melanoma Clark level, and pathologic stage. The Kaplan-Meier curve analyses revealed that the low expression of STK17B was correlated with poor overall survival and disease-specific survival. We constructed nomograms to predict the 1-, 3-, and 5-year survival of SKCM patients. The function enrichment analyses showed STK17B-related differential expressed genes were enriched in cellular differentiation and immune-related progress. STK17B expression level were positively correlated with infiltrating level of immune cells. In this study, we found that STK17B, which played an important role in immune infiltration, could be a new biomarker for diagnosis and prognosis in SKCM patients.

https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0263311&type=printable

Prognostic and immune-related value of STK17B in skin cutaneous melanoma

Background: Clear-cell renal cell carcinoma (ccRCC) is the most common malignant kidney cancer. However, the tumor microenvironment and crosstalk involved in metabolic reprogramming in ccRCC are not well-understood. Methods: We used The Cancer Genome Atlas to obtain ccRCC transcriptome data and clinical information. The E-MTAB-1980 cohort was used for external validation. The GENECARDS database contains the first 100 solute carrier (SLC)-related genes. The predictive value of SLC-related genes for ccRCC prognosis and treatment was assessed using univariate Cox regression analysis. An SLC-related predictive signature was developed through Lasso regression analysis and used to determine the risk profiles of patients with ccRCC. Patients in each cohort were separated into high- and low-risk groups based on their risk scores. The clinical importance of the signature was assessed through survival, immune microenvironment, drug sensitivity, and nomogram analyses using R software. Results: SLC25A23, SLC25A42, SLC5A1, SLC3A1, SLC25A37, SLC5A6, SLCO5A1, and SCP2 comprised the signatures of the eight SLC-related genes. Patients with ccRCC were separated into high- and low-risk groups based on the risk value in the training and validation cohorts; the high-risk group had a significantly worse prognosis (p < 0.001). The risk score was an independent predictive indicator of ccRCC in the two cohorts according to univariate and multivariate Cox regression (p < 0.05). Analysis of the immune microenvironment showed that immune cell infiltration and immune checkpoint gene expression differed between the two groups (p < 0.05). Drug sensitivity analysis showed that compared to the low-risk group, the high-risk group was more sensitive to sunitinib, nilotinib, JNK-inhibitor-VIII, dasatinib, bosutinib, and bortezomib (p < 0.001). Survival analysis and receiver operating characteristic curves were validated using the E-MTAB-1980 cohort. Conclusions: SLC-related genes have predictive relevance in ccRCC and play roles in the immunological milieu. Our results provide insight into metabolic reprogramming in ccRCC and identify promising treatment targets for ccRCC.

https://www.techscience.com/or/v31n2/52295/pdf

Solute carrier-related signature for assessing prognosis and immunity in patients with clear-cell renal cell carcinoma

Cancer is one of the serious diseases that endanger human health and bring a heavy burden to world economic development. Although the current targeted therapy and immunotherapy have achieved initial results, the emergence of drug resistance shows that the existing research is far from enough. In recent years, the tumor microenvironment has been found to be an important condition for tumor development and has profound research value. The SLC16 family is a group of monocarboxylic acid transporters involved in cancer metabolism and the formation of the tumor microenvironment. However, there have been no generalized cancer studies in the SLC16 family. In this study, we conducted a pan-cancer analysis of the SLC16 family. The results showed that multiple members of the SLC16 family could be used as prognostic indicators for many tumors, and were associated with immune invasion and tumor stem cells. Therefore, the SLC16 family has extensive exploration value in the future.

https://www.tandfonline.com/doi/pdf/10.1080/19336950.2021.1965422

A pan-cancer analysis revealed the role of the SLC16 family in cancer.

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A pan-cancer analysis revealed the role of the SLC16 family in cancer.