LDHA: The Obstacle to T cell responses against tumor

Exploring the Key Amino Acid Residues Surrounding the Active Center of Lactate Dehydrogenase A for the Development of Ideal Inhibitors

Lactate dehydrogenase A (LDHA) primarily catalyzes the conversion between lactic acid and pyruvate, serving as a key enzyme in the aerobic glycolysis pathway of sugar in tumor cells. LDHA plays a crucial role in the occurrence, development, progression, invasion, metastasis, angiogenesis, and immune escape of tumors. Consequently, LDHA not only serves as a biomarker for tumor diagnosis and prognosis but also represents an ideal target for tumor therapy. Although LDHA inhibitors show great therapeutic potential, their development has proven to be challenging. In the development of LDHA inhibitors, the key active sites of LDHA are emphasized. Nevertheless, there is a relative lack of research on the amino acid residues around the active center of LDHA. Therefore, in this study, we investigated the amino acid residues around the active center of LDHA. Through structure comparison analysis, five key amino acid residues (Ala30, Met41, Lys131, Gln233, and Ala259) were identified. Subsequently, the effects of these five residues on the enzymatic properties of LDHA were investigated using site-directed mutagenesis. The results revealed that the catalytic activities of the five mutants varied to different degrees in both the reaction from lactic acid to pyruvate and pyruvate to lactic acid. Notably, the catalytic activities of LDHAM41G and LDHAK131I were improved, particularly in the case of LDHAK131I. The results of the molecular dynamics analysis of LDHAK131I explained the reasons for this phenomenon. Additionally, the optimum temperature of LDHAM41G and LDHAQ233M increased from 35 °C to 40 °C, whereas in the reverse reaction, the optimum temperature of LDHAM41G and LDHAK131I decreased from 70 °C to 60 °C. These findings indicate that Ala30, Met41, Lys131, Gln233, and Ala259 exert diverse effects on the catalytic activity and optimum temperature of LHDA. Therefore, these amino acid residues, in addition to the key catalytic site of the active center, play a crucial role. Considering these residues in the design and screening of LDHA inhibitors may lead to the development of more effective inhibitors.

Novel findings from arsenic‑lead combined exposure in mouse testicular TM4 Sertoli cells based on transcriptomics

Arsenic (As) and lead (Pb) exist widespread in daily life, and they are common harmful substances in the environment. As and Pb pollute the environment more often in combination than in isolation. The TM4 Sertoli cell line is one of the most common normal mouse testicular Sertoli cell lines. In vitro, we found that the type of combined action of As and Pb on TM4 Sertoli cells was additive action by using the isobologram analysis. To further investigate the combined toxicity of As and Pb, we performed mRNA and miRNA sequencing on TM4 Sertoli cells exposed to As alone (4 μM NaAsO2) and AsPb combined (4 μM NaAsO2 and 150 μM PbAc), respectively. Compared with the control group, 1391 differentially expressed genes (DEGs) and 6 differentially expressed miRNAs (DEMs) were identified in the As group. Compared with the control group, 2384 DEGs and 44 DEMs were identified in the AsPb group. Compared with the As group, 387 DEGs and 4 DEMs were identified in the AsPb group. Through data analysis, we discovered for the first time that As caused the dysfunction of cholesterol synthesis and energy metabolism, and disrupted cyclic adenosine monophosphate signaling pathway and wingless/integrated (Wnt) signaling pathway in TM4 Sertoli cells. In addition to affecting cholesterol synthesis and energy metabolism, AsPb combined exposure also up-regulated the antioxidant reaction level of TM4 Sertoli cells. Meanwhile, the Wnt signaling pathway of TM4 Sertoli cells was relatively normal when exposed to AsPb. In conclusion, at the transcription level, the combined action of AsPb is not merely additive effect, but involves synergistic and antagonistic effects. The new discovery of the joint toxic mechanism of As and Pb breaks the stereotype of the combined action and provides a good theoretical basis and research clue for future study of the combined-exposure of harmful materials.

Glycolytic enzymes in non-glycolytic web: functional analysis of the key players

To survive in the tumour microenvironment, cancer cells undergo rapid metabolic reprograming and adaptability. One of the key characteristics of cancer is increased glycolytic selectivity and decreased oxidative phosphorylation (OXPHOS). Apart from ATP synthesis, glycolysis is also responsible for NADH regeneration and macromolecular biosynthesis, such as amino acid biosynthesis and nucleotide biosynthesis. This allows cancer cells to survive and proliferate even in low-nutrient and oxygen conditions, making glycolytic enzymes a promising target for various anti-cancer agents. Oncogenic activation is also caused by the uncontrolled production and activity of glycolytic enzymes. Nevertheless, in addition to conventional glycolytic processes, some glycolytic enzymes are involved in non-canonical functions such as transcriptional regulation, autophagy, epigenetic changes, inflammation, various signaling cascades, redox regulation, oxidative stress, obesity and fatty acid metabolism, diabetes and neurodegenerative disorders, and hypoxia. The mechanisms underlying the non-canonical glycolytic enzyme activities are still not comprehensive. This review summarizes the current findings on the mechanisms fundamental to the non-glycolytic actions of glycolytic enzymes and their intermediates in maintaining the tumor microenvironment.

Elaboration and validation of a prognostic signature associated with disulfidoptosis in lung adenocarcinoma, consolidated with integration of single-cell RNA sequencing and bulk RNA sequencing techniques

Background

Lung adenocarcinoma (LUAD), the predominant subtype of non-small cell lung cancer (NSCLC), remains a pervasive global public health concern. Disulfidoptosis, a nascent form of regulated cell death (RCD), presents an emerging field of inquiry. Currently, investigations into disulfidoptosis are in their initial stages. Our undertaking sought to integrate single-cell RNA sequencing (scRNA-seq) in conjunction with traditional bulk RNA sequencing (bulk RNA-seq) methodologies, with the objective of delineating genes associated with disulfidoptosis and subsequently prognosticating the clinical outcomes of LUAD patients.

Methods

Initially, we conducted an in-depth examination of the cellular composition disparities existing between LUAD and normal samples using scRNA-seq data sourced from GSE149655. Simultaneously, we scrutinized the expression patterns of disulfidoptosis-associated gene sets across diverse cell types. Subsequently, leveraging the bulk RNA-seq data, we formulated disulfidoptosis-related prognostic risk signatures (DRPS) employing LASSO-Cox regression. This was accomplished by focusing on genes implicated in disulfidoptosis that exhibited differential expression within endothelial cells (ECs). Sequentially, the robustness and precision of the DRPS model were rigorously verified through both internal and external validation datasets. In parallel, we executed single-cell trajectory analysis to delve into the differentiation dynamics of ECs. Concluding our study, we undertook a comprehensive investigation encompassing various facets. These included comparative assessments of enrichment pathways, clinicopathological parameters, immune cell abundance, immune response-associated genes, impacts of immunotherapy, and drug predictions among distinct risk cohorts.

Results

The scrutiny of scRNA-seq data underscored discernible disparities in cellular composition between LUAD and normal samples. Furthermore, disulfidoptosis-associated genes exhibited marked discrepancies within endothelial cells (ECs). Consequently, we formulated the Disulfidoptosis-Related Prognostic Signature (DRPS) to facilitate prognostic prediction. The prognostic nomogram based on the risk score effectively demonstrated DRPS's robust capacity to prognosticate survival outcomes. This assertion was corroborated by rigorous assessments utilizing both internal and external validation sets, thus affirming the commendable predictive accuracy and enduring stability of DRPS. Functional enrichment analysis shed light on the significant correlation of DRPS with pathways intrinsic to the cell cycle. Subsequent analysis unveiled correlations between DRPS and gene mutations characteristic of LUAD, as well as indications of an immunosuppressive status. Through drug prediction, we explored potential therapeutic agents for low-risk patients. Concluding our investigation, qRT-PCR experiments confirmed the heightened expression levels of EPHX1, LDHA, SHC1, MYO6, and TLE1 in lung cancer cell lines.

Development of the prognostic value in lung adenocarcinoma based on anoikis-related genes and initial experimental validation

BACKGROUND

Lung adenocarcinoma (LUAD) is a highly aggressive cancer in advanced stages and has the highest cancer-related death across the world. Anoikis has emerged as a specific form of apoptotic cell death that may play a vital role in the formation and development of tumors.

METHODS

Based on The Cancer Genome Atlas dataset, we developed a novel anoikis-related genes (ARGs) signature in LUAD and evaluated the differences between low and high-risk groups in clinical characteristics, expression patterns, immune cell infiltration, and drug sensitivity, etc. According to multivariate Cox regression analysis, the risk score was identified as a significant independent prognostic factor. The possible biological pathways of ARGs' were assessed by Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses. The immune infiltration landscape and risk score of ARGs were analyzed by ESTIMATE and CIBERSORT analysis. A nomogram grounded on six key ARGs and clinicopathological features was provided. Moreover, experiment validation of the expression patterns of six hub ARGs in lung cancer cell lines was conducted.

RESULTS

We identified 53 survival-related LUAD anoikis-related differentially expressed genes and finally six hub anoikis genes (LDHA, SLC2A1, SERPINB5, ITGB4, BRCA2, and PIK3R1) were selected to construct an ARG model. The risk model could efficiently cluster the patients into low- and high-risk groups which could accurately predict clinical outcomes for LUAD patients. There is evidence that the prognostic risk score is a remarkable prognostic factor in determining overall survival. Different immune statuses and drug sensitivity between low- and high-risk groups were explored according to functional analysis. On the basis of risk scores and LUAD clinicopathological features, a novel nomogram was developed. Ultimately, all six key genes except for PIK3R1 were proved to be upregulated in LUAD tissues and cell lines by bioinformatics analysis and experimental validation.

CONCLUSIONS

The result of the present study suggest that ARGs could be carcinogenic to LUAD and could be used as an effective stratification factor to customize therapies and forecast the survival rate in LUAD patients.