Pan-Cancer Analysis Reveals SH3TC2 as an Oncogene for Colorectal Cancer and Promotes Tumorigenesis via the MAPK Pathway

Comprehensive analysis of MAPK genes in the prognosis, immune characteristics, and drug treatment of renal clear cell carcinoma using bioinformatic analysis and Mendelian randomization

Mitogen-activated protein kinase (MAPK) signalling is vitally important in tumour development and progression. This study is the first to comprehensively analyse the role of MAPK-family genes in the progression, prognosis, immune-cell infiltration, methylation, and potential therapeutic value drug candidates in ccRCC. We identified a novel prognostic panel of six MAPK-signature genes (MAP3K12, MAP3K1, MAP3K5, MAPK1, MAPK8, MAPK9), and introduced a robust MAPK-signature risk model for predicting ccRCC prognosis. Model construction, evaluation, and external validation using datasets from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database demonstrated its stability, as well as high sensitivity and specificity. Enrichment analysis suggested the participation of immune-mediated mechanism in MAPK dysregulation in ccRCC. Immune-infiltration analysis confirmed the relationship and revealed that the MAPK-signature risk model might stratify immunotherapy response in ccRCC, which was verified in drug sensitivity analysis and validated in external ccRCC immunotherapy dataset (GSE67501). Potential therapeutic drug predictions for key MAPKs using DSigDB, Network Analyst, CTD, and DGIdb were subsequently verified by molecular docking with AutoDock Vina and PyMol. Mendelian randomization further demonstrated the possibilities of the MAPK-signature genes as targets for therapeutic drugs in ccRCC. Methylation analysis using UALCAN and MethSurv revealed the participation of epigenetic modifications in dysregulation and survival difference of MAPK pathway in ccRCC. Among the key MAPKs, MAP3K12 exhibited the highest significance, indicating its independent prognostic value as single gene in ccRCC. Knockout and overexpression validation experiments in vitro and in vivo found that MAP3K12 acted as a promoter of tumour progression in RCC, suggesting a pivotal role for MAP3K12 in the proliferation, migration, and invasion of RCC cells. Our findings proposed the potential of MAPK-signature genes as biomarkers for prognosis and therapy response, as well as targets for therapeutic drugs in ccRCC.

Identification of MDK as a Hypoxia- and Epithelial-Mesenchymal Transition-Related Gene Biomarker of Glioblastoma Based on a Novel Risk Model and In Vitro Experiments

BACKGROUND

Tumor cells are commonly exposed to a hypoxic environment, which can easily induce the epithelial-mesenchymal transition (EMT) of tumor cells, further affecting tumor proliferation, invasion, metastasis, and drug resistance. However, the predictive role of hypoxia and EMT-related genes in glioblastoma (GBM) has not been investigated.

METHODS

Intersection genes were identified by weighted correlation network analysis (WGCNA) and differential expression analyses, and a risk model was further constructed by LASSO and Cox analyses. Clinical, immune infiltration, tumor mutation, drug treatment, and enrichment profiles were analyzed based on the risk model. The expression level of the MDK gene was tested using RT-PCR, immunohistochemistry, and immunofluorescence. CCK8 and EdU were employed to determine the GBM cells' capacity for proliferation while the migration and invasion ability were detected by a wound healing assay and transwell assay, respectively.

RESULTS

Based on the GBM data of the TCGA and GTEx databases, 58 intersection genes were identified, and a risk model was constructed. The model was verified in the CGGA cohort, and its accuracy was confirmed by the ROC curve (AUC = 0.807). After combining clinical subgroups, univariate and multivariate Cox regression analyses showed that risk score and age were independent risk factors for GBM patients. Furthermore, our subsequent analysis of immune infiltration, tumor mutation, and drug treatment showed that risk score and high- and low-risk groups were associated with multiple immune cells, mutated genes, and drugs. Enrichment analysis indicated that the differences between high- and low-risk groups were manifested in tumor-related pathways, including the PI3K-AKT and JAK-STAT pathways. Finally, in vivo experiments proved that the hypoxia environment promoted the expression of MDK, and MDK knockdown reduced the proliferation, migration, and EMT of GBM cells induced by hypoxia.

CONCLUSIONS

Our novel prognostic correlation model provided more potential treatment strategies for GBM patients.

A pan-cancer analysis of the MAPK family gene and their association with prognosis, tumor microenvironment, and therapeutic targets

The mitogen-activated protein kinases family of genes plays a crucial role in a wide range of inflammatory responses in the human body. The MAPK family of genes includes ERK, ERK5, JNK, P-38 mitogen-activated protein kinases. However, the correlation between MAPK family gene expression and pan-cancer prognosis, as well as the tumor microenvironment, has not been extensively studied. This study integrated multiple bioinformatics analysis methods to assess the expression and prognostic value of MAPK family genes, as well as their relationship with tumor microenvironment in patients with pan-cancer. The results showed that ERK, JNK, and P-38 MAPK expression were found to be significantly upregulated in rectum adenocarcinoma (READ), colon adenocarcinoma/rectum adenocarcinoma esophageal carcinoma (COADREAD), and kidney renal clear cell carcinoma (KIRC), and significantly downregulated in acute myeloid leukemia. And the results revealed good prognostic results for ERK, JNK, and P-38 MAPK in READ, COADREAD, and KIRC. We observed significant positive correlation between MAPK family gene expression and immune scores especially dendritic cells in READ, COADREAD, and KIRC. And we observed that the expression levels of MAPK family genes were significantly correlated with the expression of immune-related genes, such as CXCL1, CXCL2, CXCL8, CXCR1, CXCR2, CTLA-4, CD80, CD86, and CD28, suggesting their important role in regulating immune infiltrates and tumor progression. Therefore, our study suggested that MAPK family gene plays an important role in regulating immune infiltrates and tumor progression.

Resveratrol and 3,3'-Diindolylmethane Differentially Regulate Aryl Hydrocarbon Receptor and Estrogen Receptor Alpha Activity through Multiple Transcriptomic Targets in MCF-7 Human Breast Cancer Cells

Inhibitory crosstalk between estrogen receptor alpha (ERα) and aryl hydrocarbon receptor (AHR) regulates 17β-estradiol (E2)-dependent breast cancer cell signaling. ERα and AHR are transcription factors activated by E2 and 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD), respectively. Dietary ligands resveratrol (RES) and 3,3'diindolylmethane (DIM) also activate ERα while only DIM activates AHR and RES represses it. DIM and RES are reported to have anti-cancer and anti-inflammatory properties. Studies with genome-wide targets and AHR- and ERα-regulated genes after DIM and RES are unknown. We used chromatin immunoprecipitation with high-throughput sequencing and transcriptomics to study ERα as well as AHR coregulation in MCF-7 human breast cancer cells treated with DIM, RES, E2, or TCDD alone or E2+TCDD for 1 and 6 h, respectively. ERα bound sites after being DIM enriched for the AHR motif but not after E2 or RES while AHR bound sites after being DIM and E2+TCDD enriched for the ERE motif but not after TCDD. More than 90% of the differentially expressed genes closest to an AHR binding site after DIM or E2+TCDD also had an ERα site, and 60% of the coregulated genes between DIM and E2+TCDD were common. Collectively, our data show that RES and DIM differentially regulate multiple transcriptomic targets via ERα and ERα/AHR coactivity, respectively, which need to be considered to properly interpret their cellular and biological responses. These novel data also suggest that, when both receptors are activated, ERα dominates with preferential recruitment of AHR to ERα target genes.

Risk scoring based on DNA methylation-driven related DEGs for colorectal cancer prognosis with systematic insights

Colorectal cancer is a common malignant tumor of the digestive tract. Despite advances in diagnostic techniques and medications. Its prognosis remains challenging. DNA methylation-driven related circulating tumor cells have attracted enormous interest in diagnosing owing to their non-invasive nature and early recognition properties. However, the mechanism through which risk biomarkers act remains elusive. Here, we designed a risk model based on differentially expressed genes, DNA methylation, robust, and survival-related factors in the framework of Cox regression. The model has satisfactory performance and is independently verified by an external and isolated dataset in terms of C-index value, ROC, and tROC. The model was applied to Colorectal cancer patients who were subsequently divided into high- and low-risk groups. Functional annotations, genomic alterations, tumor immune environment, and drug sensitivity were analyzed. We observed that up-regulated genes are associated with epithelial cell differentiation and MAPK signaling pathways. The down-regulated genes are related to IL-7 signaling and apoptosis-induced DNA fragmentation. Interestingly, the immune system was inhibited in high-risk groups. High-frequency mutation genes tend to co-occur. High-risk score patients are related to copy number amplification events. To address the challenges, we suggested eleven and twenty-one drugs that are sensitive to low- and high-risk patients. Finally, an artificial neural network was provided to evaluate the immunotherapeutic efficiency. Taken together, the findings demonstrated that our risk score model is robust and reliable for evaluating the prognosis with novel diagnostic and treatment targets. It also yields benefits for the treatment and provides unique insights into developing therapeutic strategies.

Identification and validation of a novel prognostic signature based on mitochondria and oxidative stress related genes for glioblastoma

BACKGROUND

Mitochondria represent a major source of reactive oxygen species (ROS) in cells, and the direct increase in ROS content is the primary cause of oxidative stress, which plays an important role in tumor proliferation, invasion, angiogenesis, and treatment. However, the relationship between mitochondrial oxidative stress-related genes and glioblastoma (GBM) remains unclear. This study aimed to investigate the value of mitochondria and oxidative stress-related genes in the prognosis and therapeutic targets of GBM.

METHODS

We retrieved mitochondria and oxidative stress-related genes from several public databases. The LASSO regression and Cox analyses were utilized to build a risk model and the ROC curve was used to assess its performance. Then, we analyzed the correlation between the model and immunity and mutation. Furthermore, CCK8 and EdU assays were utilized to verify the proliferative capacity of GBM cells and flow cytometry was used to analyze apoptosis rates. Finally, the JC-1 assay and ATP levels were utilized to detect mitochondrial function, and the intracellular ROS levels were determined using MitoSOX and BODIPY 581/591 C11.

RESULTS

5 mitochondrial oxidative stress-related genes (CTSL, TXNRD2, NUDT1, STOX1, CYP2E1) were screened by differential expression analysis and Cox analysis and incorporated in a risk model which yielded a strong prediction accuracy (AUC value = 0.967). Furthermore, this model was strongly related to immune cell infiltration and mutation status and could identify potential targeted therapeutic drugs for GBM. Finally, we selected NUDT1 for further validation in vitro. The results showed that NUDT1 was elevated in GBM, and knockdown of NUDT1 inhibited the proliferation and induced apoptosis of GBM cells, while knockdown of NUDT1 damaged mitochondrial homeostasis and induced oxidative stress in GBM cells.

CONCLUSION

Our study was the first to propose a prognostic model of mitochondria and oxidative stress-related genes, which provided potential therapeutic strategies for GBM patients.

The role of lactate metabolism-related LncRNAs in the prognosis, mutation, and tumor microenvironment of papillary thyroid cancer

BACKGROUND

Lactate, a byproduct of glucose metabolism, is primarily utilized for gluconeogenesis and numerous cellular and organismal life processes. Interestingly, many studies have demonstrated a correlation between lactate metabolism and tumor development. However, the relationship between long non-coding RNAs (lncRNAs) and lactate metabolism in papillary thyroid cancer (PTC) remains to be explored.

METHODS

Lactate metabolism-related lncRNAs (LRLs) were obtained by differential expression and correlation analyses, and the risk model was further constructed by least absolute shrinkage and selection operator analysis (Lasso) and Cox analysis. Clinical, immune, tumor mutation, and enrichment analyses were performed based on the risk model. The expression level of six LRLs was tested using RT-PCR.

RESULTS

This study found several lncRNAs linked to lactate metabolism in both The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) datasets. Using Cox regression analysis, 303 lactate LRLs were found to be substantially associated with prognosis. Lasso was done on the TCGA cohort. Six LRLs were identified as independent predictive indicators for the development of a PTC prognostic risk model. The cohort was separated into two groups based on the median risk score (0.39717 -0.39771). Subsequently, Kaplan-Meier survival analysis and multivariate Cox regression analysis revealed that the high-risk group had a lower survival probability and that the risk score was an independent predictive factor of prognosis. In addition, a nomogram that can easily predict the 1-, 3-, and 5-year survival rates of PTC patients was established. Furthermore, the association between PTC prognostic factors and tumor microenvironment (TME), immune escape, as well as tumor somatic mutation status was investigated in high- and low-risk groups. Lastly, gene expression analysis was used to confirm the differential expression levels of the six LRLs.

CONCLUSION

In conclusion, we have constructed a prognostic model that can predict the prognosis, mutation status, and TME of PTC patients. The model may have great clinical significance in the comprehensive evaluation of PTC patients.

Hypoxia-Inducible Factor-2-Altered Urothelial Carcinoma: Clinical and Genomic Features

Background: Hypoxia is recognized as a key feature of cancer growth and is involved in various cellular processes, including proliferation, angiogenesis, and immune surveillance. Besides hypoxia-inducible factor 1-alpha (HIF-1α), which is the main mediator of hypoxia effects and can also be activated under normoxic conditions, little is known about its counterpart, HIF-2. This study focused on investigating the clinical and molecular landscape of HIF-2-altered urothelial carcinoma (UC). Methods: Publicly available next-generation sequencing (NGS) data from muscle-invasive UC cell lines and patient tumor samples from the MSK/TCGA 2020 cohort (n = 476) were interrogated for the level of expression (mRNA, protein) and presence of mutations, copy number variations, structural variants in the EPAS1 gene encoding HIF-2, and findings among various clinical (stage, grade, progression-free and overall survival) and molecular (tumor mutational burden, enriched gene expression) parameters were compared between altered and unaltered tumors. Results: 19% (7/37) of UC cell lines and 7% (27/380) of patients with muscle-invasive UC display high EPAS1 mRNA and protein expression or/and EPAS1 alterations. EPAS1-altered tumors are associated with higher stage, grade, and lymph node metastasis as well as with shorter PFS (14 vs. 51 months, q = 0.01) and OS (15 vs. 55 months, q = 0.01). EPAS1 mRNA expression is directly correlated with that of its target-genes, including VEGF, FLT1, KDR, DLL4, CDH5, ANGPT1 (q < 0.001). While there is a slightly higher tumor mutational burden in EPAS1-altered tumors (9.9 vs. 4.9 mut/Mb), they are enriched in and associated with genes promoting immune evasion, including ARID5B, SPINT1, AAK1, CLIC3, SORT1, SASH1, and FGFR3, respectively (q < 0.001). Conclusions: HIF-2-altered UC has an aggressive clinical and a distinct genomic and immunogenomic profile enriched in angiogenesis- and immune evasion-promoting genes.