Gene Expression Profiling of Tricarboxylic Acid Cycle and One Carbon Metabolism Related Genes for Prognostic Risk Signature of Colon Carcinoma

Pathological characteristics of axons and alterations of proteomic and lipidomic profiles in midbrain dopaminergic neurodegeneration induced by WDR45-deficiency

BACKGROUND

Although WD repeat domain 45 (WDR45) mutations have been linked to β -propeller protein-associated neurodegeneration (BPAN), the precise molecular and cellular mechanisms behind this disease remain elusive. This study aims to shed light on the impacts of WDR45-deficiency on neurodegeneration, specifically axonal degeneration, within the midbrain dopaminergic (DAergic) system. We hope to better understand the disease process by examining pathological and molecular alterations, especially within the DAergic system.

METHODS

To investigate the impacts of WDR45 dysfunction on mouse behaviors and DAergic neurons, we developed a mouse model in which WDR45 was conditionally knocked out in the midbrain DAergic neurons (WDR45cKO). Through a longitudinal study, we assessed alterations in the mouse behaviors using open field, rotarod, Y-maze, and 3-chamber social approach tests. We utilized a combination of immunofluorescence staining and transmission electron microscopy to examine the pathological changes in DAergic neuron soma and axons. Additionally, we performed proteomic and lipidomic analyses of the striatum from young and aged mice to identify the molecules and processes potentially involved in the striatal pathology during aging. Further more, primary midbrain neuronal culture was employed to explore the molecular mechanisms leading to axonal degeneration.

RESULTS

Our study of WDR45cKO mice revealed a range of deficits, including impaired motor function, emotional instability, and memory loss, coinciding with the profound reduction of midbrain DAergic neurons. The neuronal loss, we observed massive axonal enlargements in the dorsal and ventral striatum. These enlargements were characterized by the accumulation of extensively fragmented tubular endoplasmic reticulum (ER), a hallmark of axonal degeneration. Proteomic analysis of the striatum showed that the differentially expressed proteins were enriched in metabolic processes. The carbohydrate metabolic and protein catabolic processes appeared earlier, and amino acid, lipid, and tricarboxylic acid metabolisms were increased during aging. Of note, we observed a tremendous increase in the expression of lysophosphatidylcholine acyltransferase 1 (Lpcat1) that regulates phospholipid metabolism, specifically in the conversion of lysophosphatidylcholine (LPC) to phosphatidylcholine (PC) in the presence of acyl-CoA. The lipidomic results consistently suggested that differential lipids were concentrated on PC and LPC. Axonal degeneration was effectively ameliorated by interfering Lpcat1 expression in primary cultured WDR45-deficient DAergic neurons, proving that Lpcat1 and its regulated lipid metabolism, especially PC and LPC metabolism, participate in controlling the axonal degeneration induced by WDR45 deficits.

CONCLUSIONS

In this study, we uncovered the molecular mechanisms underlying the contribution of WDR45 deficiency to axonal degeneration, which involves complex relationships between phospholipid metabolism, autophagy, and tubular ER. These findings greatly advance our understanding of the fundamental molecular mechanisms driving axonal degeneration and may provide a foundation for developing novel mechanistically based therapeutic interventions for BPAN and other neurodegenerative diseases.

Biomarker Identification and Risk Prediction Model Development for Differentiated Thyroid Carcinoma Lung Metastasis Based on Primary Lesion Proteomics

PURPOSE

The rising global high incidence of differentiated thyroid carcinoma (DTC) has led to a significant increase in patients presenting with lung metastasis of DTC (LMDTC). This population poses a significant challenge in clinical practice, necessitating the urgent development of effective risk stratification methods and predictive tools for lung metastasis.

EXPERIMENTAL DESIGN

Through proteomic analysis of large samples of primary lesion and dual validation employing parallel reaction monitoring and IHC, we identified eight hub proteins as potential biomarkers. By expanding the sample size and conducting statistical analysis on clinical features and hub protein expression, we constructed three risk prediction models.

RESULTS

This study identified eight hub proteins-SUCLG1/2, DLAT, IDH3B, ACSF2, ACO2, CYCS, and VDAC2-as potential biomarkers for predicting LMDTC risk. We developed and internally validated three risk prediction models incorporating both clinical characteristics and hub protein expression. Our findings demonstrated that the combined prediction model exhibited optimal predictive performance, with the highest discrimination (AUC: 0.986) and calibration (Brier score: 0.043). Application of the combined prediction model within a specific risk threshold (0-0.97) yielded maximal clinical benefit. Finally, we constructed a nomogram based on the combined prediction model.

CONCLUSIONS

As a large sample size study in LMDTC research, the identification of biomarkers through primary lesion proteomics and the development of risk prediction models integrating clinical features and hub protein biomarkers offer valuable insights for predicting LMDTC and establishing personalized treatment strategies.

p32 regulates glycometabolism and TCA cycle to inhibit ccRCC progression via copper-induced DLAT lipoylation oligomerization

A key player in mitochondrial respiration, p32, often referred to as C1QBP, is mostly found in the mitochondrial matrix. Previously, we showed that p32 interacts with DLAT in the mitochondria. Here, we found that p32 expression was reduced in ccRCC and suppressed progression and metastasis in ccRCC animal models. We observed that increasing p32 expression led to an increase in oxidative phosphorylation by interacting with DLAT, thus, regulating the activation of the pyruvate dehydrogenase complex (PDHc). Mechanistically, reduced p32 expression, in concert with DLAT, suppresses PDHc activity and the TCA cycle. Furthermore, our research discovered that p32 has a direct binding affinity for copper, facilitating the copper-induced oligomerization of lipo-DLAT specifically in ccRCC cells. This finding reveals an innovative function of the p32/DLAT/copper complex in regulating glycometabolism and the TCA cycle in ccRCC. Importantly, our research provides important new understandings of the underlying molecular processes causing the abnormal mitochondrial metabolism linked to this cancer.

ACO2 deficiency increases vulnerability to Parkinson's disease via dysregulating mitochondrial function and histone acetylation-mediated transcription of autophagy genes

Parkinson's disease (PD) is characterized by α-synuclein aggregation in dopaminergic (DA) neurons, which are sensitive to oxidative stress. Mitochondria aconitase 2 (ACO2) is an essential enzyme in the tricarboxylic acid cycle that orchestrates mitochondrial and autophagic functions to energy metabolism. Though widely linked to diseases, its relation to PD has not been fully clarified. Here we revealed that the peripheral ACO2 activity was significantly decreased in PD patients and associated with their onset age and disease durations. The knock-in mouse and Drosophila models with the A252T variant displayed aggravated motor deficits and DA neuron degeneration after 6-OHDA and rotenone-induction, and the ACO2 knockdown or blockade cells showed features of mitochondrial and autophagic dysfunction. Moreover, the transcription of autophagy-related genes LC3 and Atg5 was significantly downregulated via inhibited histone acetylation at the H3K9 and H4K5 sites. These data provided multi-dimensional evidences supporting the essential roles of ACO2, and as a potential early biomarker to be used in clinical trials for assessing the effects of antioxidants in PD. Moreover, ameliorating energy metabolism by targeting ACO2 could be considered as a potential therapeutic strategy for PD and other neurodegenerative disorders.

Development and experimental validation of a folate metabolism-related gene signature to predict the prognosis and immunotherapeutic sensitivity in bladder cancer

Folate metabolism is critical for the maintenance of genomic stability due to its regulatory ability to methylation, nucleotide metabolism, and reduction capabilities in cancer cells. However, the prognostic value of folate metabolism-related genes has not been clarified, especially in bladder cancer (BLCA). 91 folate metabolism-related genes were retrieved from the public database. TCGA-BLCA cohort, obtained from the Cancer Genome Atlas, was selected for training, while GSE13507, GSE31684, and GSE32894, downloaded from the Gene Expression Omnibus, and 35 BLCA samples collected from the local hospital were used for external validation. Through genomic difference detection, protein-protein interaction network analysis, LASSO regression, and Cox regression, a three-gene signature, including ATIC, INS, and MTHFD1L, was constructed. The signature was a reliable prognosis predictor across multiple independent cohorts (pooled hazard ratio = 2.79, 95% confidence interval = 1.79-4.33). The signature was associated with the BLCA malignant degree, which was validated in the local clinical samples (P < 0.01) and multiple cell lines (all P < 0.05). Additionally, the TIDE algorithm, GSE111636 cohort, and IMvigor210 cohort indicated that the signature was a promising tool to evaluate the immunotherapeutic response. Collectively, a folate metabolism-related gene signature was constructed to predict the prognosis and immunotherapeutic sensitivity in BLCA, which was verified in multiple large-scale cohorts, clinical samples, and cellular experiments, providing novel insights into the biological mechanisms.

Transcriptome profiling of A549 non-small cell lung cancer cells in response to Trichinella spiralis muscle larvae excretory/secretory products

Trichinella spiralis (T. spiralis) muscle-larva excretory/secretory products (ML-ESPs) is a complex array of proteins with antitumor activity. We previously demonstrated that ML-ESPs inhibit the proliferation of A549 non-small cell lung cancer (NSCLC) cell line. However, the mechanism of ML-ESPs against A549 cells, especially on the transcriptional level, remains unknow. In this study, we systematically investigated a global profile bioinformatics analysis of transcriptional response of A549 cells treated with ML-ESPs. And then, we further explored the transcriptional regulation of genes related to glucose metabolism in A549 cells by ML-ESPs. The results showed that ML-ESPs altered the expression of 2,860 genes (1,634 upregulated and 1,226 downregulated). GO and KEGG analysis demonstrated that differentially expressed genes (DEGs) were mainly associated with pathway in cancer and metabolic process. The downregulated genes interaction network of metabolic process is mainly associated with glucose metabolism. Furthermore, the expression of phosphofructokinase muscle (PFKM), phosphofructokinase liver (PFKL), enolase 2 (ENO2), lactate dehydrogenase B (LDHB), 6-phosphogluconolactonase (6PGL), ribulose-phosphate-3-epimerase (PRE), transketolase (TKT), transaldolase 1 (TALDO1), which genes mainly regulate glycolysis and pentose phosphate pathway (PPP), were suppressed by ML-ESPs. Interestingly, tricarboxylic acid cycle (TCA)-related genes, such as pyruvate dehydrogenase phosphatase 1 (PDP1), PDP2, aconitate hydratase 1 (ACO1) and oxoglutarate dehydrogenase (OGDH) were upregulated by ML-ESPs. In summary, the transcriptome profiling of A549 cells were significantly altered by ML-ESPs. And we also provide new insight into how ML-ESPs induced a transcriptional reprogramming of glucose metabolism-related genes in A549 cells.

A prognostic 15-gene model based on differentially expressed genes among metabolic subtypes in diffuse large B-cell lymphoma

The outcomes of patients with diffuse large B-cell lymphoma (DLBCL) vary widely, and about 40% of them could not be cured by the standard first-line treatment, R-CHOP, which could be due to the high heterogeneity of DLBCL. Here, we aim to construct a prognostic model based on the genetic signature of metabolic heterogeneity of DLBCL to explore therapeutic strategies for DLBCL patients. Clinical and transcriptomic data of one training and four validation cohorts of DLBCL were obtained from the GEO database. Metabolic subtypes were identified by PAM clustering of 1,916 metabolic genes in the 7 major metabolic pathways in the training cohort. DEGs among the metabolic clusters were then analyzed. In total, 108 prognosis-related DEGs were identified. Through univariable Cox and LASSO regression analyses, 15 DEGs were used to construct a risk score model. The overall survival (OS) and progression-free survival (PFS) of patients with high risk were significantly worse than those with low risk (OS: HR 2.86, 95%CI 2.04-4.01, p < 0.001; PFS: HR 2.42, 95% CI 1.77-3.31, p < 0.001). This model was also associated with OS in the four independent validation datasets (GSE10846: HR 1.65, p = 0.002; GSE53786: HR 2.05, p = 0.02; GSE87371: HR 1.85, p = 0.027; GSE23051: HR 6.16, p = 0.007) and PFS in the two validation datasets (GSE87371: HR 1.67, p = 0.033; GSE23051: HR 2.74, p = 0.049). Multivariable Cox analysis showed that in all datasets, the risk model could predict OS independent of clinical prognosis factors (p < 0.05). Compared with the high-risk group, patients in the low-risk group predictively respond to R-CHOP (p = 0.0042), PI3K inhibitor (p < 0.05), and proteasome inhibitor (p < 0.05). Therefore, in this study, we developed a signature model of 15 DEGs among 3 metabolic subtypes, which could predict survival and drug sensitivity in DLBCL patients.

Comprehensive analysis of the prognosis, tumor microenvironment, and immunotherapy response of SDHs in colon adenocarcinoma

Background

Succinate dehydrogenase (SDH), one of the key enzymes in the tricarboxylic acid cycle, is mainly found in the mitochondria. SDH consists of four subunits encoding SDHA, SDHB, SDHC, and SDHD. The biological function of SDH is significantly related to cancer progression. Colorectal cancer (CRC) is one of the most common malignant tumors globally, whose most common histological subtype is colon adenocarcinoma (COAD). However, the correlation between SDH factors and COAD remains unclear.

Methods

The data on pan-cancer was obtained from The Cancer Genome Atlas (TCGA) database. Kaplan-Meier survival analysis showed the prognostic ability of SDHs. The cBioPortal database reflected genetic variations of SDHs. The correlation analysis was conducted between SDHs and mitochondrial energy metabolism genes (MMGs) and the protein-protein interaction (PPI) network was built. Consequently, Univariate and Multivariate Cox Regression Analysis on SDHs and other clinical characteristics were conducted. A nomogram was established. The ssGSEA analysis visualized the association between SDHs and immune infiltration. Immunophenoscore (IPS) explored the correlation between SDHs and immunotherapy, and the correlation between SDHs and targeted therapy was investigated through Genomics of Drug Sensitivity in Cancer. Finally, qPCR and immunohistochemistry detected SDHs' expression.

Results

After assessing SDHs differential expression in pan-cancer, we found that SDHB, SDHC, and SDHD benefit COAD patients. The cBioPortal database demonstrated that SDHA was the top gene in mutation frequency rank. Correlation analysis mirrored a strong link between SDHs and MMGs. We formulated a nomogram and found that SDHB, SDHC, SDHD, and clinical characteristics correlated with COAD patients' survival. For T helper cells, Th2 cells, and Tem, SDHA, SDHB, SDHC, and SDHD were significantly enriched in the high expression group. Moreover, COAD patients with high SDHA expression were more suitable for immunotherapy. And COAD patients with different SDHs' expression have different sensitivity to targeted drugs. Further verifying the gene and protein expression levels of SDHs, we found that the tissues were consistent with the bioinformatics analysis.

Conclusions

Our study analyzed the expression and prognostic value of SDHs in COAD, explored the pathway mechanisms involved, and the immune cell correlations, indicating that SDHs might be biomarkers for COAD patients.

Metabolic reprogramming by miRNAs in the tumor microenvironment: Focused on immunometabolism

MicroRNAs (miRNAs) are emerging as a significant modulator of immunity, and their abnormal expression/activity has been linked to numerous human disorders, such as cancer. It is now known that miRNAs potentially modulate the production of several metabolic processes in tumor-associated immune cells and indirectly via different metabolic enzymes that affect tumor-associated signaling cascades. For instance, Let-7 has been identified as a crucial modulator for the long-lasting survival of CD8+ T cells (naive phenotypes) in cancer by altering their metabolism. Furthermore, in T cells, it has been found that enhancer of zeste homolog 2 (EZH2) expression is controlled via glycolytic metabolism through miRNAs in patients with ovarian cancer. On the other hand, immunometabolism has shown us that cellular metabolic reactions and processes not only generate ATP and biosynthetic intermediates but also modulate the immune system and inflammatory processes. Based on recent studies, new and encouraging approaches to cancer involving the modification of miRNAs in immune cell metabolism are currently being investigated, providing insight into promising targets for therapeutic strategies based on the pivotal role of immunometabolism in cancer. Throughout this overview, we explore and describe the significance of miRNAs in cancer and immune cell metabolism.

A novel fatty acid metabolism-related gene signature predicts the prognosis, tumor immune properties, and immunotherapy response of colon adenocarcinoma patients

Colon adenocarcinoma (COAD) has a high incidence and death rate. Despite the fact that change in fatty acid metabolism promotes tumor growth and metastasis to the greatest degree among metabolite profiles, a thorough investigation on the involvement of fatty acid metabolism-related genes (FAMRGs) in COAD has yet not been conducted. Here, the clinical data as well as the gene expression profiles were extracted from The Cancer Genome Atlas (TCGA) database. Based on the FAMRG expression data and clinical information, a FAMRG risk signature was developed using LASSO as well as multivariate and univariate Cox regression analyses. Then, the nomogram was used to create a customized prognostic prediction model, and the calibration and receiver operating characteristic curves were used to evaluate the nomogram's prediction performance and discriminative capability. Lastly, a number of studies were conducted to assess the influence of independent FAMRGs on COAD, including unsupervised cluster analysis, functional analysis, and drug sensitivity analysis. Three hundred and sixty-seven patients were included in this study, and a 12-FAMRG risk signature was discovered in the training cohort based on a detailed examination of the FAMRGs expression data and clinical information. After that, risk scores were computed to classify patients into low or high-risk groups, and the Kaplan-Meier curve analysis revealed that patients in the low-risk group exhibited an elevated overall survival (OS) rate. The FAMRG was shown to be substantially correlated with prognosis in multivariate Cox regression analysis and was validated using the validation dataset. Then, using the clinical variables and risk signature, we developed and validated a prediction nomogram for OS. Functional characterization showed a strong correlation between this signature and immune cell infiltration and immune modulation. Additionally, by evaluating the GDSC database, it was determined that the high-risk group exhibited medication resistance to many chemotherapeutic and targeted medicines, including VX.680, gemcitabine, doxorubicin, and paclitaxel. Overall, we have revealed the significance of a FAMRG risk signature for predicting the prognosis and response to immunotherapy in COAD, and our findings might contribute to an enhanced comprehension of metabolic pathways and the future development of innovative COAD therapeutic methods.

Performance of the Use of Genetic Information to Assess the Risk of Colorectal Cancer in the Basque Population

Although the genetic contribution to colorectal cancer (CRC) has been studied in various populations, studies on the applicability of available genetic information in the Basque population are scarce. In total, 835 CRC cases and 940 controls from the Basque population were genotyped and genome-wide association studies were carried out. Mendelian Randomization analyses were used to discover the effect of modifiable risk factors and microbiota on CRC. In total, 25 polygenic risk score models were evaluated to assess their performance in CRC risk calculation. Moreover, 492 inflammatory bowel disease cases were used to assess whether that genetic information would not confuse both conditions. Five suggestive (p < 5 × 10−6) loci were associated with CRC risk, where genes previously associated with CRC were located (e.g., ABCA12, ATIC or ERBB4). Moreover, the analyses of CRC locations detected additional genes consistent with the biology of CRC. The possible contribution of cholesterol, BMI, Firmicutes and Cyanobacteria to CRC risk was detected by Mendelian Randomization. Finally, although polygenic risk score models showed variable performance, the best model performed correctly regardless of the location and did not misclassify inflammatory bowel disease cases. Our results are consistent with CRC biology and genetic risk models and could be applied to assess CRC risk in the Basque population.

Value of Immunohistochemical Expression of Apelin, Succinate Dehydrogenase B, Chromogranin B, Human Epidermal Growth Factor Receptor-2, Contactin 4, and Succinyl-CoA Synthetase Subunit Beta in Differentiating Metastatic From Non-Metastatic Pheochromocytoma and Paraganglioma

OBJECTIVE

We aimed to retrospectively collect pathologically identified pheochromocytoma and paraganglioma (PPGL) tumor tissues from our center and investigate the expression of apelin and succinyl-CoA synthetase subunit beta (SUCLG2), human epidermal growth factor receptor-2 (HER2 or ERBB-2), contactin 4 (CNTN4), chromogranin B (CHGB), and succinate dehydrogenase B (SDHB) in metastatic and non-metastatic PPGLs, for exploring their roles in the diagnosis of metastatic PPGLs.

METHODS

A total of 369 patients with pathologically and surgically confirmed PPGLs at Xiangya Hospital, Central South University, between June 2010 and June 2020 were retrospectively included. Sixty patients-12 patients with metastatic PPGLs and 48 patients with non-metastatic PPGLs-were selected through propensity score matching (1:4) to reduce the effect of PPGL type, sex, and age. We observed and quantified the expression of apelin, SDHB, CHGB, ERBB-2, CNTN4, and SUCLG2 in paraffin-embedded samples using immunohistochemical staining.

RESULTS

No significant differences were observed between the metastatic group and non-metastatic group with respect to the expression of CNTN4 and SUCLG2. The expression of apelin, SDHB, CHGB, and ERBB-2 was significantly different between the two groups. The expression of apelin, SDHB, and CHGB was significantly lower in the metastatic group than that in the non-metastatic group (P < 0.001). ERBB-2 expression was significantly higher in the metastatic group than in the non-metastatic group (P = 0.042). Kaplan-Meier analysis revealed that patients with negative expression of apelin, SDHB, and CHGB showed significantly lower metastasis-free survival than those with positive expression. Multivariate Cox analysis revealed that SDHB and CHGB levels were independently associated with metastasis-free survival.

CONCLUSION

The expression levels of apelin, CHGB, SDHB, and ERBB-2 may be predictive biomarkers for the diagnosis of metastatic PPGLs. Patients with negative expression of apelin, CHGB, and SDHB should be subjected to frequent postoperative follow-up procedures.