A novel signature model based on mitochondrial-related genes for predicting survival of colon adenocarcinoma

Characterization of mitochondrial metabolism related molecular subtypes and immune infiltration in colorectal adenocarcinoma

Colorectal adenocarcinoma (COAD) is the most common subtype of colorectal cancer. Due to the imperfect prognosis of COAD, related prognostic factors and possible mechanisms need to be further investigated. During tumor development, mitochondria help tumor cells survive in a variety of ways, so that further screening of mitochondrial metabolism related targets has positive implications for COAD. We screened the mitochondrial metabolism-related genes (MMRG) associated with the COAD prognosis and explored the MMRG-related molecular subtype characteristics of by unsupervised consensus clustering analysis. Using ESTIMATE and ssGSEA algorithms, we evaluated the immunoinfiltration characteristic landscape of different molecular subtypes defined by MMRG. Combining the expression profiles of differentially expressed genes associated with the MMRG subgroup and the survival characteristics of COAD, we constructed an MMRG prognostic model using LASSO-univariate Cox analysis and successfully validated its impact on independently predicting risk stratification of COAD. The potential clinical value of the MMRG score was subsequently evaluated by subgroup immunoinfiltration characteristics and drug susceptibility prediction analysis. We also offer SEC11A as a new potential target for COAD by single-cell sequencing analysis. The effect of SEC11A on the proliferation, invasion abilities and mitochondrial dysfunction of COAD cells was confirmed through in vitro experiments. Our study provides new insights into the role of MMRG and new target for COAD potential intervention.

Expression and prognostic impact of VDAC3 in colorectal adenocarcinoma

Background

Colorectal adenocarcinoma (COAD) is a malignant tumor with high mortality and low 5-year survival rate. Voltage-dependent anion channel 3 (VDAC3) is the least understood isoform of voltage-dependent anion-selective channels in the mitochondrial outer membrane. In this thesis, we aimed to investigate the prognostic value of VDAC3 and provide new insights into colon adenocarcinoma.

Methods

We utilized The Cancer Genome Atlas (TCGA) database, Gene Expression Omnibus (GEO) database, Human Protein Atlas online database, and the University of ALabama at Birmingham CANcer data analysis Portal (UALCAN) database to analyze VDAC3 expression in COAD and assess patient survival rates. Univariate and multivariate Cox regression analyses were employed to evaluate VDAC3's prognostic significance for COAD. Gene set variation analysis (GSVA) was utilized to explore COAD-related signaling pathways associated with VDAC3. Additionally, we predicted the relationship between VDAC3 expression and anticancer drug sensitivity using the CellMiner database.

Results

In the TCGA database, VDAC3 demonstrated elevated expression levels in COAD, which was further validated by findings from the GEO database. Survival analysis conducted using Kaplan-Meier (K-M) curves highlighted that the patients with decreased VDAC3 expression exhibited significantly shorter overall survival durations. VDAC3 expression demonstrated correlation with COAD pathological stage. VDAC3 gene mutation was linked to COAD outcomes. Cox regression analysis showed that VDAC3 was an independent predictor. In addition, GSVA analysis showed that VDAC3 was closely related to mitochondria-related biological processes and involved in the occurrence and development of mitochondria-related diseases. Finally, analysis of the CellMiner database predicted that VDAC3 expression was positively correlated with chelerythrine and cladribine, but negatively correlated with Ergenyl.

Conclusions

Our study suggests that VDAC3 may be a potential biomarker for early diagnosis, prognosis, and treatment of COAD.

Mitochondrial-related genes as prognostic and metastatic markers in breast cancer: insights from comprehensive analysis and clinical models

Background

Breast cancer (BC) constitutes a significant peril to global women's health. Contemporary research progressively suggests that mitochondrial dysfunction plays a pivotal role in both the inception and advancement of BC. However, investigations delving into the correlation between mitochondrial-related genes (MRGs) and the prognosis and metastasis of BC are still infrequent.

Methods

Utilizing data from the TCGA database, we employed the "limma" R package for differential expression analysis. Subsequently, both univariate and multivariate Cox regression analyses were executed, alongside LASSO Cox regression analysis, to pinpoint prognostic MRGs and to further develop the prognostic model. External validation (GSE88770 merged GSE425680) and internal validation were further conducted. Our investigation delved into a broad spectrum of analyses that included functional enrichment, metabolic and immune characteristics, immunotherapy response prediction, intratumor heterogeneity (ITH), mutation, tumor mutational burden (TMB), microsatellite instability (MSI), cellular stemness, single-cell, and drug sensitivity analysis. We validated the protein and mRNA expressions of prognostic MRGs in tissues and cell lines through immunohistochemistry and qRT-PCR. Moreover, leveraging the GSE102484 dataset, we conducted differential gene expression analysis to identify MRGs related to metastasis, subsequently developing metastasis models via 10 distinct machine-learning algorithms and then selecting the best-performing model. The division between training and validation cohorts was set at 70% and 30%, respectively.

Results

A prognostic model was constructed by 9 prognostic MRGs, which were DCTPP1, FEZ1, KMO, NME3, CCR7, ISOC2, STAR, COMTD1, and ESR2. Patients within the high-risk group experienced more adverse outcomes than their counterparts in the low-risk group. The ROC curves and constructed nomogram showed that the model exhibited an excellent ability to predict overall survival (OS) for patients and the risk score was identified as an independent prognostic factor. The functional enrichment analysis showed a strong correlation between metabolic progression and MRGs. Additional research revealed that the discrepancies in outcomes between the two risk categories may be attributed to a variety of metabolic and immune characteristics, as well as differences in intratumor heterogeneity (ITH), tumor mutational burden (TMB), and cancer stemness indices. ITH, TIDE, and IPS analyses suggested that patients possessing a low-risk score may exhibit enhanced responsiveness to immunotherapy. Additionally, distant metastasis models were established by PDK4, NRF1, DCAF8, CHPT1, MARS2 and NAMPT. Among these, the XGBoost model showed the best predicting ability.

Conclusion

In conclusion, MRGs significantly influence the prognosis and metastasis of BC. The development of dual clinical prediction models offers crucial insights for tailored and precise therapeutic strategies, and paves the way for exploring new avenues in understanding the pathogenesis of BC.

Guidelines for mitochondrial RNA analysis

Mitochondria are the energy-producing organelles of mammalian cells with critical involvement in metabolism and signaling. Studying their regulation in pathological conditions may lead to the discovery of novel drugs to treat, for instance, cardiovascular or neurological diseases, which affect high-energy-consuming cells such as cardiomyocytes, hepatocytes, or neurons. Mitochondria possess both protein-coding and noncoding RNAs, such as microRNAs, long noncoding RNAs, circular RNAs, and piwi-interacting RNAs, encoded by the mitochondria or the nuclear genome. Mitochondrial RNAs are involved in anterograde-retrograde communication between the nucleus and mitochondria and play an important role in physiological and pathological conditions. Despite accumulating evidence on the presence and biogenesis of mitochondrial RNAs, their study continues to pose significant challenges. Currently, there are no standardized protocols and guidelines to conduct deep functional characterization and expression profiling of mitochondrial RNAs. To overcome major obstacles in this emerging field, the EU-CardioRNA and AtheroNET COST Action networks summarize currently available techniques and emphasize critical points that may constitute sources of variability and explain discrepancies between published results. Standardized methods and adherence to guidelines to quantify and study mitochondrial RNAs in normal and disease states will improve research outputs, their reproducibility, and translation potential to clinical application.

Downregulation of HIGD1B induces mitochondria-mediated apoptosis in gastric cancer cells by inactivating Akt and ERK pathways

Gastric cancer (GC) is one of the most common malignancies worldwide. Hypoxia-inducible domain (HIGD) family members (e.g., HIGD1A) have been linked to tumor progression. However, the role of HIGD1B (another HIGD family member) in GC has yet to be fully understood. Based on data from TCGA_GC, GSE65801, and GSE65801 data sets, HIGD1B levels were evaluated in normal and GC tissues. Next, HIGD1B levels were validated by reverse transcription-quantitative PCR and western blot analysis analyses. Meanwhile, patients with GC in the TCGA_GC cohort were grouped into high- and low-HIGD1B level groups, and overall survival, functional enrichment, and immune infiltration were analyzed. Additionally, gain- and loss-of-function experiments were performed to determine the function of HIGD1B in GC cells. Compared to normal controls, HIGD1B mRNA levels were significantly elevated in GC tissues. Moreover, high HIGD1B levels may be an independent indicator of poor prognosis in patients with GC. Additionally, high HIGD1B levels were correlated with high stromal and ESTIMATE scores and elevated expression of immune checkpoints in patients with GC. Functional analyses showed that HIGD1B deficiency notably suppressed GC cell proliferation, migration, and invasion. Moreover, HIGD1B deficiency significantly induced mitochondria-mediated apoptosis in GC cells by inactivating Akt and ERK pathways. Collectively, HIGD1B may predict the prognosis of patients with GC and may function as an oncogene in GC. These findings suggest that HIGD1B may serve as a prognostic biomarker and potential therapeutic target in GC.

A Comprehensive Prognostic Model for Colon Adenocarcinoma Depending on Nuclear-Mitochondrial-Related Genes

Background: Colon adenocarcinoma (COAD) has increasing incidence and is one of the most common malignant tumors. The mitochondria involved in cell energy metabolism, oxygen free radical generation, and cell apoptosis play important roles in tumorigenesis and progression. The relationship between mitochondrial genes and COAD remains largely unknown. Methods: COAD data including 512 samples were set out from the UCSC Xena database. The nuclear mitochondrial-related genes (NMRGs)-related risk prognostic model and prognostic nomogram were constructed, and NMRGs-related gene mutation and the immune environment were analyzed using bioinformatics methods. Then, a liver metastasis model of colorectal cancer was constructed and protein expression was detected using Western blot assay. Results: A prognostic model for COAD was constructed. Comparing the prognostic model dataset and the validation dataset showed considerable correlation in both risk grouping and prognosis. Based on the risk score (RS) model, the samples of the prognostic dataset were divided into high risk group and low risk group. Moreover, pathologic N and T stage and tumor recurrence in the two risk groups were significantly different. The four prognostic factors, including age and pathologic T stage in the nomogram survival model also showed excellent predictive performance. An optimal combination of nine differentially expressed NMRGs was finally obtained, including LARS2, PARS2, ETHE1, LRPPRC, TMEM70, AARS2, ACAD9, VARS2, and ATP8A2. The high-RS group had more inflamed immune features, including T and CD4+ memory cell activation. Besides, mitochondria-associated LRPPRC and LARS2 expression levels were increased in vivo xenograft construction and liver metastases assays. Conclusion: This study established a comprehensive prognostic model for COAD, incorporating nine genes associated with nuclear-mitochondrial functions. This model demonstrates superior predictive performance across four prognostic factors: age, pathological T stage, tumor recurrence, and overall prognosis. It is anticipated to be an effective model for enhancing the prognosis and treatment of COAD.

Inhibition of TRAP1 Accelerates the DNA Damage Response, Activation of the Heat Shock Response and Metabolic Reprogramming in Colon Cancer Cells

BACKGROUND

Colorectal cancer (CRC) is one of the major causes of cancer-related mortality worldwide. The tumor microenvironment plays a significant role in CRC development, progression and metastasis. Oxidative stress in the colon is a major etiological factor impacting tumor progression. Tumor necrosis factor receptor-associated protein 1 (TRAP1) is a mitochondrial member of the heat shock protein 90 (HSP90) family that is involved in modulating apoptosis in colon cancer cells under oxidative stress. We undertook this study to provide mechanistic insight into the role of TRAP1 under oxidative stress in colon cells.

METHODS

We first assessed the The Cancer Genome Atlas (TCGA) CRC gene expression dataset to evaluate the expression of TRAP1 and its association with oxidative stress and disease progression. We then treated colon HCT116 cells with hydrogen peroxide to induce oxidative stress and with the TRAP1 inhibitor gamitrinib-triphenylphosphonium (GTPP) to inhibit TRAP1. We examined the cellular proteomic landscape using liquid chromatography tandem mass spectrometry (LC-MS/MS) in this context compared to controls. We further examined the impact of treatment on DNA damage and cell survival.

RESULTS

TRAP1 expression under oxidative stress is associated with the disease outcomes of colorectal cancer. TRAP1 inhibition under oxidative stress induced metabolic reprogramming and heat shock factor 1 (HSF1)-dependent transactivation. In addition, we also observed enhanced induction of DNA damage and cell death in the cells under oxidative stress and TRAP1 inhibition in comparison to single treatments and the nontreatment control.

CONCLUSIONS

These findings provide new insights into TRAP1-driven metabolic reprogramming in response to oxidative stress.

The anoikis-related gene signature predicts survival accurately in colon adenocarcinoma

Colon adenocarcinoma (COAD) is a serious public health problem, the third most common cancer and the second most deadly cancer in the world. About 9.4% of cancer-related deaths in 2020 were due to COAD. Anoikis is a specialized form of programmed cell death that plays an important role in tumor invasion and metastasis. The presence of anti-anoikis factors is associated with tumor aggressiveness and drug resistance. Various bioinformatic methods, such as differential expression analysis, and functional annotation analysis, machine learning, were used in this study. RNA-sequencing and clinical data from COAD patients were obtained from the Gene expression omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases. Construction of a prognostic nomogram for predicting overall survival (OS) using multivariate analysis and Lasso-Cox regression. Immunohistochemistry (IHC) was our method of validating the expression of seven genes that are linked to anoikis in COAD. We identified seven anoikis-related genes as predictors of COAD survival and prognosis, and confirmed their accuracy in predicting colon adenocarcinoma prognosis by KM survival curves and ROC curves. A seven-gene risk score consisting of NAT1, CDC25C, ATP2A3, MMP3, EEF1A2, PBK, and TIMP1 showed strong prognostic value. Meanwhile, we made a nomogram to predict the survival rate of COAD patients. The immune infiltration assay showed T cells. CD4 memory. Rest and macrophages. M0 has a higher proportion in COAD, and 11 genes related to tumor immunity are important. GDSC2-based drug susceptibility analysis showed that 6 out of 198 drugs were significant in COAD. Anoikis-related genes have potential value in predicting the prognosis of COAD and provide clues for developing new therapeutic strategies for COAD. Immune infiltration and drug susceptibility results provide important clues for finding new personalized treatment options for COAD. These findings also suggest possible mechanisms that may affect prognosis. These results are the starting point for planning individualized treatment and managing patient outcomes.