Using Weighted Gene Co-Expression Network Analysis to Identify Increased MND1 Expression as a Predictor of Poor Breast Cancer Survival

Integrated pan-cancer analysis and experimental verification of the roles of meiotic nuclear divisions 1 in breast cancer

INTRODUCTION

The aberrant up-regulation of meiotic nuclear division 1 (MND1) in somatic cells is considered as one of the driving factors of oncogenesis, whereas its expression and role in breast invasive cancer (BRCA) remain unclear. Hence, this study embarked on a comprehensive evaluation of MND1 across various cancers and identified its roles in BRCA.

METHODS

Based on publicly available databases, including but not limited to UCSC Xena, TCGA, GTEx, GEO, STRING, GeneMANIA, and CancerSEA, we evaluated the expression patterns, genomic features, and biological functions of MND1 from a pan-cancer viewpoint and delved into the implications of MND1 in the prognosis and treatment of BRCA. Further molecular biology experiments were undertaken to identify the role of MND1 in proliferation, migration, and apoptosis in BRCA cells.

RESULTS

Elevated levels of MND1 were notably observed in a wide array of tumor types, especially in BRCA, COAD, HNSC, LIHC, LUAD, LUSC, STAD, and UCEC. Elevated MND1 expression was markedly associated with shortened OS in several tumors, including BRCA (HR = 1.52 [95%CI, 1.10-2.09], P = 0.011). The up-regulation of MND1 in BRCA was validated in external cohorts and clinical samples. Survival analyses demonstrated that elevated MND1 expression was associated with decreased survival for patients with BRCA. Co-expressed genes of MND1 were identified, and subsequent pathway analyses based on significantly associated genes indicated that MND1 plays key roles in DNA replication, cell cycle regulation, and DNA damage repair. The observed abnormal elevation and activation of MND1 led to increased proliferation and migration, along with decreased apoptosis in BRCA cells.

CONCLUSIONS

MND1 emerges as a promising biomarker for diagnostic and therapeutic targeting in various cancers, including BRCA. The abnormal up-regulation and activation of MND1 are linked to carcinogenesis and poor prognosis among BRCA patients, which may be attributed to its involvement in HR-dependent ALT, warranting further scrutiny.

Integrative Pan-Cancer Analysis Reveals the Oncogenic Role of MND1 and Validation of MND1's Role in Breast Cancer

Purpose

Meiotic nuclear division 1 (MND1) is a meiosis-specific protein that promotes lung adenocarcinoma progression. However, its expression and biological function across cancers remain largely unexplored.

Patients and Methods

The expression, prognostic significance, mutation status, and methylation profile of MND1 in various cancers were comprehensively analyzed using the TIMER, GTEX, Kaplan-Meier plotter, cBioPortal, and GSCA databases. Additionally, we constructed a PPI network, enrichment analysis and single-cell transcriptomic sequencing to elucidate the underlying mechanism of MND1. Furthermore, we investigated the association between MND1 expression and drug sensitivity using CellMiner. Moreover, we also explored the correlation between MND1 expression and immune infiltration. Finally, we validated the functional role of MND1 in breast cancer through IHC staining, CCK8, EdU, colony formation, and flow cytometry assays.

Results

MND1 has been reported to be highly expressed in Pan-cancer, High MND1 expression was significantly associated with poor prognosis in cancers. Additionally, MND1 mutation frequency is high in most cancers, and its expression correlates with methylation. Furthermore, MND1 expression significantly correlates with immune checkpoint blockade (ICB) markers, including PD-L1, PD-1, and CTLA-4. The PPI network reveals interactions between MND1 and PSMC3IP, BRCA1, and BRCA2. Enrichment analysis and single-cell sequencing indicate that MND1 positively correlates with cell cycle. ROC curve reveals favorable diagnostic efficacy of MND1 in breast cancer. In vitro, MND1 overexpression promotes breast cancer cell proliferation and increases the expression of key cell cycle regulators (CDK4, CDK6, and cyclin D3), accelerating the G1/S phase transition and leading to abnormal breast cancer cell proliferation. The immunohistochemical analysis revealed a robust expression of MND1 in breast cancer tissues, exhibiting a significant positive correlation with PD-L1 and FOXP3.

Conclusion

MND1 is an oncogene and may serve as a biomarker for cancer prognosis and immunotherapy. Targeting MND1 may be a potential tumor treatment strategy.

Mechanistic insights into FEN1-mediated drug sensitivity and risk signature in colon cancer: An integrative bioinformatics study

The overexpression of Flap endonuclease 1 (FEN1) has been implicated in drug resistance and prognosis across various cancer types. However, the precise role of FEN1 in colon cancer remains to be fully elucidated. In this study, we employed comprehensive datasets from The Cancer Genome Atlas, Gene Expression Omnibus, and Human Protein Atlas to examine FEN1 expression and assess its correlation with clinical pathology and prognosis in colon cancer. We utilized the pRRophetic algorithm to evaluate drug sensitivity and performed differential expression analysis to identify genes associated with FEN1-mediated drug sensitivity. Gene set enrichment analysis was conducted to further investigate these genes. Additionally, single-cell sequencing analysis was employed to explore the relationship between FEN1 expression and functional states. Cox regression analysis was implemented to construct a prognostic model, and a nomogram for prognosis was developed. Our analysis of The Cancer Genome Atlas and Gene Expression Omnibus datasets revealed a significant upregulation of FEN1 in colon cancer. However, while FEN1 expression showed no notable correlation with prognosis, it displayed associations with metastasis. Single-cell sequencing analysis further confirmed a positive correlation between FEN1 expression and colon cancer metastasis. Furthermore, we detected marked discrepancies in drug responsiveness between the High_FEN1 and Low_FEN1 groups, identifying 342 differentially expressed genes. Enrichment analysis showed significant suppression in processes related to DNA replication, spliceosome, and cell cycle pathways in the Low_FEN1 group, while the calcium signaling pathway, cAMP signaling pathway, and other pathways were activated. Of the 197 genes differentially expressed and strongly linked to FEN1 expression, 39 were significantly implicated in colon cancer prognosis. Finally, we constructed a risk signature consisting of 5 genes, which, when combined with drug treatment and pathological staging, significantly improved the prediction of colon cancer prognosis. This study offers novel insights into the interplay among FEN1 expression levels, colon cancer metastatic potential, and sensitivity to therapeutic agents. Furthermore, we successfully developed a multi-gene prognostic risk signature derived from FEN1.

FOXA1/MND1/TKT axis regulates gastric cancer progression and oxaliplatin sensitivity via PI3K/AKT signaling pathway

BACKGROUND

Drug resistance is a main factor affecting the chemotherapy efficacy of gastric cancer (GC), in which meiosis plays an important role. Therefore, it is urgent to explore the effect of meiosis related genes on chemotherapy resistance.

METHODS

The expression of meiotic nuclear divisions 1 (MND1) in GC was detected by using TCGA and clinical specimens. In vitro and in vivo assays were used to investigate the effects of MND1. The molecular mechanism was determined using luciferase reporter assay, CO-IP and mass spectrometry (MS).

RESULTS

Through bioinformatics, we found that MND1 was highly expressed in platinum-resistant samples. In vitro experiments showed that interference of MND1 significantly inhibited the progression of GC and increased the sensitivity to oxaliplatin. MND1 was significantly higher in 159 GC tissues in comparison with the matched adjacent normal tissues. In addition, overexpression of MND1 was associated with worse survival, advanced TNM stage, and lower pathological grade in patients with GC. Further investigation revealed that forkhead box protein A1 (FOXA1) directly binds to the promoter of MND1 to inhibit its transcription. CO-IP and MS assays showed that MND1 was coexpressed with transketolase (TKT). In addition,TKT activated the PI3K/AKT signaling axis and enhanced the glucose uptake and lactate production in GC cells.

CONCLUSIONS

Our results confirm that FOXA1 inhibits the expression of MND1, which can directly bind to TKT to promote GC progression and reduce oxaliplatin sensitivity through the PI3K/AKT signaling pathway.

Identification of SNP markers for canine mammary gland tumours in females based on a genome-wide association study - preliminary results

Introduction

The development of genetic research over recent decades has enabled the discovery of new genetic markers, such as single nucleotide polymorphisms (SNPs). This, as well as the full sequencing of the dog genome, has enabled genome-wide association studies (GWAS) to be used in the search for genetic causes of canine mammary tumours (CMTs).

Material and Methods

Genotypic data containing 175,000 SNPs, which had been obtained using the Illumina CanineHD BeadChip microarray technique, were available for analysis in this study. The data concerned 118 bitches, including 36 animals with CMT, representing various breeds and age groups. Statistical analysis was performed in two steps: quality control of genotyping data and genome-wide association analysis based on dominant, recessive, overdominant, codominant, and log-additive models with the single SNP effects.

Results

A total of 40 different SNPs significantly associated with CMT appearance were detected. Moreover, twelve SNPs showed statistical significance in more than one model. Of all the significant SNPs, two, namely BICF2G630136001 in the overdominant model and TIGRP2P107898_rs9044787 in the log-additive model, reached the 5-8 significance level. The other SNPs were significant to a 1-5 level.

Conclusion

In the group of SNPs indicated as significant in the GWAS analysis, several transpired to be localised within genes that may play an important role in CMT.

Identification of a novel survival predictor, CSF2RB, for female lung cancer in never smokers (LCNS) by a bioinformatics analysis

Lung cancer in never smokers (LCNS) has been considered as a separate disease and the 7th cause of cancer-related death worldwide. However, limited research has focused on "female" cohorts, which have presented a higher incidence rate. In this study, the microarray data of lung cancer tissues derived from 54 female lung cancer patients, consisting of 43 nonsmokers and 11 smokers, were selected from GSE2109 dataset. A total of 249 differentially expressed genes (DEGs) including 102 up- and 147 down-regulated genes were identified and further analyzed for gene ontology (GO) terms and Kyoto encyclopedia of genes and genomes (KEGG) pathway enrichment. By constructing protein-protein interaction (PPI) network and calculating key modules, 10 hub genes were screened out. The module analysis of the PPI network presented that the progression of female LCNS was significantly associated with immune response as chemokine activity and lipopolysaccharide response, and these biological processes (BP) might be mediated by chemokine signaling pathway and cytokine-cytokine receptor interaction. Then, survival analysis by Kaplan-Meier (K-M) Plotter online platform presented down-regulated gene colony stimulating factor 2 receptor beta common subunit (CSF2RB) of female LCNS might be involved in poor clinical outcome. Female LCNS with high expression of CSF2RB might be relevant with relative risk reduction of mortality, longer median survival time and higher 5-year survival rate, while female LCNS with low expression of CSF2RB might be implicated in a poor clinical outcome. In short, our results support CSF2RB to be a candidate survival predictor for female LCNS.

High Expression of DNTTIP1 Predicts Poor Prognosis in Clear Cell Renal Cell Carcinoma

Background

Invasion and metastasis led to poor prognosis and death of clear cell renal cell carcinoma (ccRCC) patients. The deoxynucleotidyl transferase terminal interacting protein 1 (DNTTIP1) was reported to promote multiple tumor progression. However, there is no research about DNTTIP1 in ccRCC.

Methods

Kaplan-Meier survival analysis, multivariate analysis demonstrated the prognostic indicator in overall survival (OS) and disease-free survival (DFS) of ccRCC with DNTTIP1 expression in the Cancer Genome Atlas Kidney Clear Cell Carcinoma (TCGA-KIRC). Receiver operator characteristic (ROC) curve analyzed diagnostic ability of DNTTIP1 in TCGA-KIRC and validation dataset. The quantitative real-time polymerase chain reaction (qRT-PCR) detected the DNTTIP1 expression in renal cancer tissues, and the Office of Cancer Clinical Proteomics Research (CPTAC) verified the protein expression of DNTTIP1. Moreover, nomogram predicted the role of DNTTIP1 in ccRCC patient. Single-sample Gene Set Enrichment Analysis (SsGSEA) and GSEA evaluated the pathogenesis role of DNTTIP1 in TCGA-KIRC.

Results

DNTTIP1 expression was higher in ccRCC tumor tissues. High expression of DNTTIP1 was associated with poor OS (HR = 1.618, P < 0.0001), and poor DFS (HR = 1.789, P < 0.0001). SsGSEA and GSEA showed DNTTIP1 was associated with hypoxia, epithelial-mesenchymal transition (EMT), angiogenesis, G2M checkpoint. DNTTIP1 had a positive correlation with EMT biomarkers in ccRCC, and might be an effective target for ccRCC.

Conclusion

This study provided that higher expression of DNTTIP1 predicted poor prognosis in ccRCC, and DNTTIP1 might be a novel detection biomarker and therapeutic target of tumor malignant in the future.

Meiotic nuclear divisions 1 promotes proliferation and metastasis in hepatocellular carcinoma and is a potential diagnostic and therapeutic target gene

Hepatocellular carcinoma is the cancer with the highest incidence among liver cancers and how to treat this cancer effectively is still a difficult problem we must face. We selected meiotic nuclear divisions 1 (MND1) as the study object by combining data from The Cancer Genome Atlas (TCGA) database with prognostic survival analysis. We validated the value of MND1 in evaluating the prognosis of hepatocellular carcinoma through a diagnostic and prognostic model. At the same time, cellular experiments were used to demonstrate the effect of MND1 on hepatocellular carcinoma proliferation and migration. We used short hairpin RNA (shRNA) to knock down MND1 in Hun7 and HCCLM3 cell lines. Through 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) and colony formation assays, we found that knocking down MND1 reduced the proliferation of cells. Through wound healing and Transwell assays, we found that knocking down MND1 reduced cell migration and invasion. Moreover, we found that MND1 can promote the proliferation, migration, and invasion of Hep3B cells by overexpressing MND1. Therefore, in general, MND1 is expected to be a gene that can effectively diagnose and treat hepatocellular carcinoma.

Validation of a Disease-Free Survival Prediction Model Using UBE2C and Clinical Indicators in Breast Cancer Patients

Objective

To explore the validation of a disease-free survival (DFS) model for predicting disease progression based on the combination of ubiquitin-conjugating enzyme E2 C (UBE2C) levels and clinical indicators in breast cancer patients.

Methods

We enrolled 121 patients with breast cancer, collected their baseline characteristics and follow-up data, and analyzed the UBE2C levels in tumor tissues. We studied the relationship between UBE2C expression in tumor tissues and disease progression events of patients. We used the Kaplan-Meier method for identifying the disease-free survival rate of patients, and the multivariate Cox regression analysis to study the risk factors affecting the prognosis of patients. We sought to develop and validate a model for predicting disease progression.

Results

We found that the level of expression of UBE2C could effectively distinguish the prognosis of patients. In the Receiver Operating Characteristic (ROC) curve analysis, the Area under the ROC Curve (AUC) = 0.826 (0.714-0.938) indicating that high levels of UBE2C was a high-risk factor for poor prognosis. After evaluating different models using the ROC curve, Concordance index (C-index), calibration curve, Net Reclassification Index (NRI), Integrated Discrimination Improvement Index (IDI), and other methods, we finally developed a model for the expression of Tumor-Node (TN) staging using Ki-67 and UBE2C, which had an AUC=0.870, 95% CI of 0.786-0.953. The traditional TN model had an AUC=0.717, and 95% CI of 0.581-0.853. Decision Curve Analysis (DCA) and Clinical Impact Curve (CIC) analysis indicated that the model had good clinical benefits and it was relatively simple to use.

Conclusion

We found that high levels of UBE2C was a high-risk factor for poor prognosis. The use of UBE2C in addition to other breast cancer-related indicators effectively predicted the possible disease progression, thus providing a reliable basis for clinical decision-making.