The NER-related gene GTF2H5 predicts survival in high-grade serous ovarian cancer patients

Regulation of nucleotide excision repair by wild-type HRAS signaling in head and neck cancer

Head and neck squamous cell carcinoma (HNSCC) is characterized by a high rate of locoregional or distant relapse among patients. It is well established that resistance to chemotherapeutic drugs has an important role in the emergence of the recurrent and/or metastatic type of this malignancy which is associated with poor prognosis. Therefore, understanding the molecular basis of chemoresistance in head and neck cancer is required for the development of effective therapeutic strategies. Activating mutations in the HRAS gene are driver events in human cancer. Although numerous studies have demonstrated that oncogenic HRAS mutations promote chemoresistance in HNSCC, the molecular profile of HNSCC tumors that overexpress wild-type HRAS (wtHRASov) and their response to chemotherapy is poorly investigated. To gain deeper insights into the characteristics of wtHRASov tumors, we conducted a gene expression analysis using transcriptome data from The Cancer Genome Atlas (TCGA). This analysis revealed a distinct signature of overexpressed nucleotide excision repair (NER) genes in wtHRASov tumors, which are associated with chemoresistance. We further explored the role of these NER components in response to genotoxic stress, utilizing a diverse panel of HNSCC cell lines and patient-derived xenografts. Our findings indicate that in a specific cluster of head and neck tumors, ERK/cJun signaling activation is strongly reliant on HRAS activity. Inhibiting HRAS in these tumors results in a significant downregulation of the NER signature components, re-sensitizing cancer cells to platinum-based chemotherapy.

GTF2H5 Identified as a crucial synthetic lethal target to counteract chemoresistance in colorectal cancer

BACKGROUND

Synthetic lethality (SL) emerges as a novel concept being explored to combat cancer progression and resistance to conventional therapy. Despite the efficacy of chemotherapy in select cases of colorectal cancer (CRC), a substantial proportion of patients encounter challenges, leading to an adverse prognosis of CRC patients. CRC-related SL genes offer a potential avenue for identifying therapeutic targets.

METHODS

CRC-related SL genes were obtained from the SynLethDB database. The bulk RNA sequencing data, mutation data, and clinical information for treated and untreated CRC patients were enrolled from the UCSC and GEO databases. The Tumor Immunology Single Cell Center database served as the repository for collecting and analyzing single-cell RNA sequencing data. The synergistic killing effect of SL genes and chemotherapeutic drugs on resistant cells was experimentally verified.

RESULTS

In the present study, pivotal SL genes associated with chemoresistance identified by using WGCNA and CRC patients categorized into two groups based on these genes. Variations between the groups were most pronounced in pathways associated with extracellular matrix remodeling. Further by integrating mutation data, five potential SL genes were discerned, which were highly expressed in the presence of TP53 or KRAS mutations, leading to a severely poor prognosis. Subsequent time series analysis revealed that the expression of GTF2H5 was gradually elevated at different stages of the transition from sensitive to resistant in CRC cells. Finally, it was preliminarily verified by experiments that GTF2H5 may play a key role in driving the drug-resistant transition within CRC cells.

CONCLUSIONS

The identification of SL genes that collaboratively interact with chemotherapeutic agents could provide new insights into solving the issue of chemotherapy resistance in CRC patients. And GTF2H5 wields a fundamental influence in inducing chemoresistance in CRC, which provided a potential therapeutic target for CRC.

Imputation strategies for low-coverage whole-genome sequencing data and their effects on genomic prediction and genome-wide association studies in pigs

The uncertainty resulting from missing genotypes in low-coverage whole-genome sequencing (LCWGS) data complicates genotype imputation. The aim of this study is to find out an optimal strategy for accurately imputing LCWGS data and assess its effectiveness for genomic prediction (GP) and genome-wide association study (GWAS) on economically important traits of Large White pigs. The LCWGS data of 1 423 Large White pigs were imputed using three different strategies: (1) using the high-coverage whole-genome sequencing (HCWGS) of 30 key progenitors as the reference panel (Ref_LG); (2) mixing HCWGS of key progenitors with LCWGS (Mix_HLG) and (3) self-imputation in LCWGS (Within_LG). Additionally, to compare the imputation effects of LCWGS, we also imputed SNP chip data of 1 423 Large White pigs to the whole-genome sequencing level using the reference panel consisting of key progenitors (Ref_SNP). To evaluate effects of the imputed sequencing data, we compared the accuracies of GP and statistical power of GWAS for four reproductive traits based on the chip data, sequencing data imputed from chip data and LCWGS data using an optimal strategy. The average imputation accuracies of the Within_LG, Ref_LG and Mix_HLG were 0.9893, 0.9899 and 0.9875, respectively, which were higher than that of the Ref_SNP (0.8522). Using the imputed sequencing data from LCWGS with the Ref_LG imputation strategy, the accuracies of GP for four traits improved by approximately 0.31-1.04% compared to the chip data, and by 0.7-1.05% compared to the imputed sequencing data from chip data. Furthermore, by using the sequence data imputed from LCWGS with the Ref_LG, 18 candidate genes were identified to be associated with the four reproductive traits of interest in Large White pigs: total number of piglets born - EPC2, MBD5, ORC4 and ACVR2A; number of piglets born healthy - IKBKE; total litter weight of piglets born alive - HSPA13 and CPA1; gestation length - GTF2H5, ITGAV, NFE2L2, CALCRL, ITGA4, STAT1, HOXD10, MSTN, COL5A2 and STAT4. With the exception of EPC2, ORC4, ACVR2A and MSTN, others represent novel candidates. Our findings can provide a reference for the application of LCWGS data in livestock and poultry.

Personalized Driver Gene Prediction Using Graph Convolutional Networks with Conditional Random Fields

Cancer is a complex and evolutionary disease mainly driven by the accumulation of genetic variations in genes. Identifying cancer driver genes is important. However, most related studies have focused on the population level. Cancer is a disease with high heterogeneity. Thus, the discovery of driver genes at the individual level is becoming more valuable but is a great challenge. Although there have been some computational methods proposed to tackle this challenge, few can cover all patient samples well, and there is still room for performance improvement. In this study, to identify individual-level driver genes more efficiently, we propose the PDGCN method. PDGCN integrates multiple types of data features, including mutation, expression, methylation, copy number data, and system-level gene features, along with network structural features extracted using Node2vec in order to construct a sample-gene interaction network. Prediction is performed using a graphical convolutional neural network model with a conditional random field layer, which is able to better combine the network structural features with biological attribute features. Experiments on the ACC (Adrenocortical Cancer) and KICH (Kidney Chromophobe) datasets from TCGA (The Cancer Genome Atlas) demonstrated that the method performs better compared to other similar methods. It can identify not only frequently mutated driver genes, but also rare candidate driver genes and novel biomarker genes. The results of the survival and enrichment analyses of these detected genes demonstrate that the method can identify important driver genes at the individual level.

DNA Damage Responses, the Trump Card of Stem Cells in the Survival Game

Stem cells, as a group of undifferentiated cells, are enriched with self-renewal and high proliferative capacity, which have attracted the attention of many researchers as a promising approach in the treatment of many diseases over the past years. However, from the cellular and molecular point of view, the DNA repair system is one of the biggest challenges in achieving therapeutic goals through stem cell technology. DNA repair mechanisms are an advantage for stem cells that are constantly multiplying to deal with various types of DNA damage. However, this mechanism can be considered a trump card in the game of cell survival and treatment resistance in cancer stem cells, which can hinder the curability of various types of cancer. Therefore, getting a deep insight into the DNA repair system can bring researchers one step closer to achieving major therapeutic goals. The remarkable thing about the DNA repair system is that this system is not only under the control of genetic factors, but also under the control of epigenetic factors. Therefore, it is necessary to investigate the role of the DNA repair system in maintaining the survival of cancer stem cells from both aspects.

Domatinostat Targets the FOXM1-Survivin Axis to Reduce the Viability of Ovarian Cancer Cells Alone and in Combination with Chemotherapeutic Agents

The deregulation of the FOXM1 transcription factor is a key molecular alteration in ovarian cancer, contributing to the development and progression of ovarian cancer via activation of the target genes. As such, FOXM1 is a highly attractive therapeutic target in the treatment of ovarian cancer, but there has been no clinically tested FOXM1 inhibitor to date. We investigated in this study the effects of domatinostat, a class I-selective HDAC inhibitor currently in the clinical stage of development as a cancer therapeutic, on the expression of FOXM1 and viability of ovarian cancer cells. Cell viability, as well as protein and mRNA expression of FOXM1 and its transcriptional target survivin, was examined after domatinostat treatment of TOV21G and SKOV3 ovarian cancer cell lines in the absence or presence of cisplatin and paclitaxel. The effect of FOXM1 knockdown on survivin expression and those of genetic and pharmacological inhibition of survivin alone or in combination with the chemotherapeutic agents on cell viability were also examined. Domatinostat reduced the protein and mRNA expression of FOXM1 and survivin and also the viability of ovarian cancer cells alone and in combination with cisplatin or paclitaxel at clinically relevant concentrations. Knockdown experiments showed survivin expression was dependent on FOXM1 in ovarian cancer cells. Survivin inhibition was sufficient to reduce the viability of ovarian cancer cells alone and in combination with the chemotherapeutic agents. Our findings suggest that domatinostat, which effectively targets the FOXM1-survivin axis required for the viability of ovarian cancer cells, is a promising option for the treatment of ovarian cancer.

Genomic testing in high-grade serous ovarian cancer: current options and future development

Understanding the genomic complexity of high-grade serous ovarian cancer is now essential in guiding patient management, particularly in the first-line setting. Our knowledge in this area has expanded rapidly in recent years, with biomarkers developing in parallel to agents designed to exploit cancer-associated genetic aberrations. In this review we will take stock of the current landscape of genetic testing and look towards the future with developments that aim to refine personalized treatment paradigms and track treatment resistance in real time.

Application of RNA processing factors for predicting clinical outcomes in colon cancer

Background: Colon cancer is the fifth most common cause of cancer-related death worldwide, and despite significant advances in related treatment, the prognosis of colon cancer patients remains poor.

Objective: This study performs systematic bioinformatics analysis of prognostic-associated RNA processing factor genes in colon cancer using the Cancer Related Genome Atlas database to explore their role in colon carcinogenesis and prognosis and excavate potential therapeutic targets.

Methods: Data sets of colon cancer patients were obtained from GEO and TCGA databases. Univariate cox analysis was performed on the GSE39582 training set to identify prognosis-associated RNA processing factor genes and constructed a muticox model. The predictive performance of the model was validated by Correlation curve analysis. Similar results were obtained for the test dataset. Functional analyses were performed to explore the underlying mechanisms of colon carcinogenesis and prognosis.

Results: A constructed muticox model consisting of βi and prognosis-related RNA processing factor gene expression levels (Expi) was established to evaluate the risk score of each patient. The subgroup with a higher risk score had lower overall survival (OS), higher risk factor, and mortality. We found that the risk score, age, gender, and TNM Stage were strongly associated with OS, and the 13-gene signature as an independent prognostic factor for colon cancer. The model has good accuracy in predicting patient survival and is superior to traditional pathological staging.

Conclusion: This study proposes 13 RNA processing factor genes as a prognostic factor for colon cancer patients, which can independently predict the clinical outcome by risk score. The gene expression profile in this model is closely related to the immune status and prognosis of colon cancer patients. The interaction of the 13 RNA processing factor genes with the immune system during colon carcinogenesis provides new ideas for the molecular mechanisms and targeted therapies for colon cancer.

Analysis of Omics Data Reveals Nucleotide Excision Repair-Related Genes Signature in Highly-Grade Serous Ovarian Cancer to Predict Prognosis

Most of the high-grade serous ovarian cancers (HGSOC) are accompanied by P53 mutations, which are related to the nucleotide excision repair (NER) pathway. This study aims to construct a risk signature based on NER-related genes that could effectively predict the prognosis for advanced patients with HGSOC. In our study, we found that two clusters of HGSOC with significantly different overall survival (OS) were identified by consensus clustering and principal component analysis (PCA). Then, a 7-gene risk signature (DDB2, POLR2D, CCNH, XPC, ERCC2, ERCC4, and RPA2) for OS prediction was developed subsequently based on TCGA cohort, and the risk score-based signature was identified as an independent prognostic indicator for HGSOC. According to the risk score, HGSOC patients were divided into high-risk group and low-risk group, in which the distinct OS and the predictive power were also successfully verified in the GEO validation sets. Then we constructed a nomogram, including the risk signature and clinical-related risk factors (age and treatment response) that predicted an individual’s risk of OS, which can be validated by assessing calibration curves. Furthermore, GSEA showed that the genes in the high-risk group were significantly enriched in cancer-related pathways, such as “MAPK signaling pathway”, “mTOR signaling pathway”, “VEGF signaling pathway” and so on. In conclusion, our study has developed a robust NER-related genes-based molecular signature for prognosis prediction, and the nomogram could be used as a convenient tool for OS evaluation and guidance of therapeutic strategies in advanced patients with HGSOC.

DNA transposons mediate duplications via transposition-independent and -dependent mechanisms in metazoans

Despite long being considered as "junk", transposable elements (TEs) are now accepted as catalysts of evolution. One example is Mutator-like elements (MULEs, one type of terminal inverted repeat DNA TEs, or TIR TEs) capturing sequences as Pack-MULEs in plants. However, their origination mechanism remains perplexing, and whether TIR TEs mediate duplication in animals is almost unexplored. Here we identify 370 Pack-TIRs in 100 animal reference genomes and one Pack-TIR (Ssk-FB4) family in fly populations. We find that single-copy Pack-TIRs are mostly generated via transposition-independent gap filling, and multicopy Pack-TIRs are likely generated by transposition after replication fork switching. We show that a proportion of Pack-TIRs are transcribed and often form chimeras with hosts. We also find that Ssk-FB4s represent a young protein family, as supported by proteomics and signatures of positive selection. Thus, TIR TEs catalyze new gene structures and new genes in animals via both transposition-independent and -dependent mechanisms.

Research Progress in Prognostic Factors and Biomarkers of Ovarian Cancer

Ovarian cancer is a serious threat to women's health; its early diagnosis rate is low and prone to metastasis and recurrence. The current conventional treatment for ovarian cancer is a combination of platinum and paclitaxel chemotherapy based on surgery. The recurrence and progression of ovarian cancer with poor prognosis is a major challenge in treatment. With rapid advances in technology, understanding of the molecular pathways involved in ovarian cancer recurrence and progression has increased, biomarker-guided treatment options can greatly improve the prognosis of patients. This review systematically discusses and summarizes existing and new information on prognostic factors and biomarkers of ovarian cancer, which is expected to improve the clinical management of patients and lead to effective personalized treatment.

Overexpression of Galectin10 Predicts a Better Prognosis in Human Ovarian Cancer

To explore the prognosis of Galectins (LGALS) expression on patients with ovarian cancer, the prognosis of LGALS members in ovarian cancer was retrieved and analyzed by using 'Kaplan-Meier plotter' database. The relation of LGALS to overall survival (OS) was evaluated according to histological subtypes, clinical stages and pathological grade. Quantitative real-time polymerase chain reaction and western blot were used to detect the mRNA and protein expression of LGALS in ovarian cancer and normal ovarian cells. Immunohistochemistry was applied to evaluate the different expression of LGALS between cancer and normal tissues. In total patients with ovarian cancer, LGALS4, LGALS8, LGALS10 and LGALS13 mRNA levels were related to a better OS, and LGALS1 to a worse OS. LGALS1 predicted a worse OS in women with serous, stages III+IV or grade II ovarian cancer. LGALS4 predicted a better OS in patients with endometrioid, stages I+II or grade III ovarian cancer. LGALS10 predicted a longer OS in females with serous, all stages, or grade III cancer. LGALS8 overexpression was related to a better OS in all stages. Notably, mRNA and protein expressions of LGALS4, LGALS10 and LGALS13 were decreased in cancer cells than those in normal cells (P<0.05). Additionally, the immunostaining score of LGALS8, LGALS10 and LGALS13 expression were lower but LGALS1 was higher in caner tissues than those in normal tissues (P<0.001). In conclusion, LGALS10 possibly is a valuable biomarker for predicting a favorable prognosis in patients with ovarian cancer, especially with serous, all stages and grade III cancer.

Genetic Parameters and Genome-Wide Association Studies of Eight Longevity Traits Representing Either Full or Partial Lifespan in Chinese Holsteins

Due to the complexity of longevity trait in dairy cattle, two groups of trait definitions are widely used to measure longevity, either covering the full lifespan or representing only a part of it to achieve an early selection. Usually, only one group of longevity definition is used in breeding program for one population, and genetic studies on the comparisons of two groups of trait definitions are scarce. Based on the data of eight traits well representing the both groups of trait definitions, the current study investigated genetic parameters and genetic architectures of longevity in Holsteins. Heritabilities and correlations of eight longevity traits were estimated using single-trait and multi-trait animal models, with the data from 103,479 cows. Among the cows with phenotypes, 2,630 cows were genotyped with the 150K-SNP panel. A single-trait fixed and random Circuitous Probability Unification model was performed to detect candidate genes for eight longevity traits. Generally, all eight longevity traits had low heritabilities, ranging from 0.038 for total productive life and herd life to 0.090 for days from the first calving to the end of first lactation or culling. High genetic correlations were observed among the traits within the same definition group: from 0.946 to 0.997 for three traits reflecting full lifespan and from 0.666 to 0.997 for five traits reflecting partial productive life. Genetic correlations between two groups of traits ranged from 0.648 to 0.963, and increased gradually with the extension of lactations number regarding the partial productive life traits. A total of 55 SNPs located on 25 chromosomes were found genome-wide significantly associated with longevity, in which 12 SNPs were associated with more than one trait, even across traits of different definition groups. This is the first study to investigate the genetic architecture of longevity representing both full and the partial lifespan simultaneously, which will assist the selection of an appropriate trait definition for genetic improvement of longevity. Because of high genetic correlations with the full lifespan traits and higher heritability, the partial productive life trait measured as the days from the first calving to the end of the third lactation or culling could be a good alternative for early selection on longevity. The candidate genes identified by this study, such as RPRM, GRIA3, GTF2H5, CA5A, CACNA2D1, FGF10, and DNAJA3, could be used to pinpoint causative mutations for longevity and further benefit the genomic improvement of longevity in dairy cattle.

TTDA inhibited apoptosis by regulating the p53-Bax/Bcl2 axis in glioma

The trichothiodystrophy group A protein (TTDA) functions in nucleotide excision repair and basal transcription. TTDA plays a role in cancers and serves as a prognostic and predictive factor in high-grade serous ovarian cancer; however, its role in human glioma remains unknown. Here, we found that TTDA was overexpressed in glioma tissues. In vitro experiments revealed that TTDA overexpression inhibited apoptosis of glioma cells and promoted cell growth, whereas knockdown of TTDA had the opposite effect. Increased TTDA expression significantly decreased the Bax/Bcl2 ratio and the level of cleaved-caspase3. TTDA interacted with the p53 gene at the -1959 bp and -1530 bp region and regulated its transcription, leading to inhibition of the p53-Bax/Bcl2 mitochondrial apoptosis pathway in glioma cells. These results indicate that TTDA is an upstream regulator of p53-mediated apoptosis and acts as an oncogene, suggesting its value as a potential molecular target for the diagnosis and treatment of glioma.

Identification of a Prognostic Signature Associated With DNA Repair Genes in Ovarian Cancer

Introduction: Ovarian cancer is a highly malignant cancer with a poor prognosis. At present, there is no accurate strategy for predicting the prognosis of ovarian cancer. A prognosis prediction signature associated with DNA repair genes in ovarian cancer was explored in this study.

Methods: Gene expression profiles of ovarian cancer were downloaded from the GEO, UCSC, and TCGA databases. Cluster analysis, univariate analysis, and stepwise regression were used to identify DNA repair genes as potential targets and a prognostic signature for ovarian cancer survival prediction. The top genes were evaluated by immunohistochemical staining of ovarian cancer tissues, and external data were used to assess the signature.

Results: A total of 28 DNA repair genes were identified as being significantly associated with overall survival (OS) among patients with ovarian cancer. The results showed that high expression of XPC and RECQL and low expression of DMC1 were associated with poor prognosis in ovarian cancer patients. The prognostic signature combining 14 DNA repair genes was able to separate ovarian cancer samples associated with different OS times and showed robust performance for predicting survival (Training set: p < 0.0001, AUC = 0.759; Testing set: p < 0.0001, AUC = 0.76).

Conclusion: Our study identified 28 DNA repair genes related to the prognosis of ovarian cancer. Using some of these potential biomarkers, we constructed a prognostic signature to effectively stratify ovarian cancer patients with different OS rates, which may also serve as a potential therapeutic target in ovarian cancer.

DNA damage response and repair in ovarian cancer: Potential targets for therapeutic strategies

Ovarian cancer is among the most lethal gynecologic malignancies with a poor survival prognosis. The current therapeutic strategies involve surgery and chemotherapy. Research is now focused on novel agents especially those targeting DNA damage response (DDR) pathways. Understanding the DDR process in ovarian cancer necessitates having a detailed knowledge on a series of signaling mediators at the cellular and molecular levels. The complexity of the DDR process in ovarian cancer and how this process works in metastatic conditions is comprehensively reviewed. For evaluating the efficacy of therapeutic agents targeting DNA damage in ovarian cancer, we will discuss the components of this system including DDR sensors, DDR transducers, DDR mediators, and DDR effectors. The constituent pathways include DNA repair machinery, cell cycle checkpoints, and apoptotic pathways. We also will assess the potential of active mediators involved in the DDR process such as therapeutic and prognostic candidates that may facilitate future studies.

The prognostic values of insulin-like growth factor binding protein in breast cancer

Insulin-like growth factor binding proteins (IGFBPs) are a family of proteins binding to insulin-like growth factors, generally consisting 6 high-affinity IGFBPs, namely IGFBP1 through IGFBP6. IGFBP family members have been indicated to be involved in the development and progression of tumors and may be useful prognostic biomarkers in various malignancies. However, the prognostic role of individual IGFBPs, especially at the mRNA level in breast cancer patients remains elusive.We accessed the prognostic roles of IGFBPs family (IGFBP1-6) in breast cancer through the "Kaplan-Meier plotter" online database and OncoLnc database.Our results showed that the high expression of IGFBP1 mRNA was associated with favorable relapsed free survival (RFS) in all breast cancer patients. The high expression of IGFBP2 mRNA was associated with favorable overall survival (OS) and RFS in all breast cancer patients. The high expression of IGFBP3 mRNA was significantly correlated to worsen RFS in all breast cancer patients. The high expression of IGFBP4 mRNA was associated with favorable OS, RFS, distant metastasis-free survival, and post-progression survival in all breast cancer patients.Our results indicated that expression of IGFBPs mRNA may have prognostic values in breast cancer patients, and have a benefit for developing tools to predict the prognosis more accurately.

Integrated analysis of microfibrillar-associated proteins reveals MFAP4 as a novel biomarker in human cancers

Aim: The potential functions and underlying mechanism of microfibrillar-associated proteins (MFAPs) are explored in human cancers. Materials & methods: Here, we examined the expression profiles, prognostic values, epigenetic and genetic alterations of MFAPs in human cancers from public omics repository. Results: Among MFAPs family, MFAP4 was frequently downregulated in the most human cancers and high mRNA expression of MFAP4 significantly correlated with better overall survival in breast cancer. DNA hypermethylation in the promoter of MFAP4 decreased its mRNA expression. MFAP4 strongly associated with pathway in impairment and alteration of the elastic fibers. Conclusion: This integrated analysis provides new insights into MFAPs in human cancers and indicates that MFAP4 could be used as novel biomarker for developing therapies against human cancers.

Distinct prognostic values of mRNA expression of glutathione peroxidases in non-small cell lung cancer

Introduction

Glutathione peroxidases (GPxs) constitutes an enzyme family which has the ability to reduce free hydrogen peroxide to water and lipid hydroperoxides to their corresponding alcohols, and its main biological roles are to protect organisms from oxidative stress-induced damage. GPxs include eight members in different tissues of the body, and they play essential roles in carcinogenesis. However, the prognostic value of individual GPx in non-small cell lung cancer (NSCLC) remains elusive.

Materials and methods

In the current study, we investigated the prognostic value of GPxs in NSCLC patients through the “Kaplan–Meier plotter” database, wherein updated gene expression data and survival information from a total of 1,926 NSCLC patients are included.

Results

High expression of GPx1 mRNA was correlated with worse overall survival (OS) in adenocarcinoma patients. High expression of GPx2 mRNA was correlated with worse OS for all NSCLC patients. In contrast, high expression of GPx3 mRNA was associated with better OS for all NSCLC patients. High expression of GPx4 mRNA was significantly correlated with worsening adenocarcinoma in these patients. GPx5 mRNA high expression correlated with worsening OS for all NSCLC patients.

Discussion

The current findings of prognostic values of individual mRNA expression of GPxs in NSCLC patients indicate some GPxs may have prognostic value in NSCLC patients, and this needs further study.

Prognostic values of aquaporins mRNA expression in human ovarian cancer

Aquaporins (AQPs), a family of transmembrane channel, are composed of 13 identified members (AQP0-12). Accumulating evidences reported that AQPs were correlated with various biological roles and represented a prognostic predictor in various cancer types. However, the prognostic value of AQPs expression in ovarian cancer remains unclear. Using 'Kaplan-Meier plotter' (KM plotter) online database, we explored the predictive prognostic value of individual AQPs members' mRNA expression to overall survival (OS) in different clinical data, such as histology, pathological grades, clinical stages, TP53 status, and applied chemotherapy in ovarian cancer patients. Our results revealed that higher AQP0, AQP1, and AQP4 mRNA expression were correlated with poor OS, whereas higher AQP3, AQP5, AQP6, AQP8, AQP10, and AQP11 showed better OS in ovarian cancer patients. Moreover, AQP4 and AQP8 showed poor OS in TP53-mutated ovarian cancer patients and AQP1 presented unfavorable OS in both TP53 mutated and wild ovarian cancer patients. Additionally, AQP3, AQP6, and AQP11 mRNA expression were correlated with better OS, whereas AQP0 and AQP1 showed poor OS in all ovarian cancer patients treated with Platin, Taxol, and Taxol + Platin chemotherapy. AQP5, AQP8, and AQP10 were associated with improved OS, however, AQP4 predicted unfavorable OS in all patients treated with Platin chemotherapy. Our results suggest that individual AQPs, except AQP2 and AQP9, are associated with unique prognostic significance and may thus act as new predictive prognostic indicators and potential drug therapeutic target in ovarian cancer.

Prognostic roles of Notch receptor mRNA expression in human ovarian cancer

Aberrant activation of Notch signaling pathway has been correlated with high grade ovarian carcinoma and carcinogenesis. However, the predictive and prognostic values of Notch signaling pathway in ovarian cancer patients remains unclear. We utilize “The Kaplan-Meier plotter” (KM plotter) background database to access the prognostic values including overall survival (OS), progression-free survival (PFS), as well as post-progression survival (PPS) of four Notch receptor mRNA expression in ovarian cancer patients. Notch1 mRNA high expression was not correlated with OS, PFS and PPS for all ovarian cancer patients, but significantly correlated with poor PFS in TP53 wild type and favorite PFS in TP53 mutation type ovarian cancer patients. Notch2 mRNA high expression was significantly correlated with poor PFS for all ovarian cancer patients, especially in grade II patients. Notch3 mRNA high expression was significantly correlated with favorite PFS for all ovarian cancer patients. Notch4 mRNA high expression was significantly correlated with favorite OS, but not PFS and PPS for all ovarian cancer patients. The results strongly support that there are distinct prognostic values of four Notch receptor mRNA expression in ovarian cancer patients.

DNA Methylation of miR-7 is a Mechanism Involved in Platinum Response through MAFG Overexpression in Cancer Cells

One of the major limitations associated with platinum use is the resistance that almost invariably develops in different tumor types. In the current study, we sought to identify epigenetically regulated microRNAs as novel biomarkers of platinum resistance in lung and ovarian cancers, the ones with highest ratios of associated chemo-resistance.

Methods: We combined transcriptomic data from microRNA and mRNA under the influence of an epigenetic reactivation treatment in a panel of four paired cisplatin -sensitive and -resistant cell lines, followed by real-time expression and epigenetic validations for accurate candidate selection in 19 human cancer cell lines. To identify specific candidate genes under miRNA regulation, we assembled “in silico” miRNAs and mRNAs sequences by using ten different algorithms followed by qRT-PCR validation. Functional assays of site-directed mutagenesis and luciferase activity, miRNAs precursor overexpression, silencing by antago-miR and cell viability were performed to confirm their specificity in gene regulation. Results were further explored in 187 primary samples obtained from ovarian tumors and controls.

Results: We identified 4 candidates, miR-7, miR-132, miR-335 and miR-148a, which deregulation seems to be a common event in the development of resistance to cisplatin in both tumor types. miR-7 presented specific methylation in resistant cell lines, and was associated with poorer prognosis in ovarian cancer patients. Our experimental results strongly support the direct regulation of MAFG through miR-7 and their involvement in the development of CDDP resistance in human tumor cells.

Conclusion: The basal methylation status of miR-7 before treatment may be a potential clinical epigenetic biomarker, predictor of the chemotherapy outcome to CDDP in ovarian cancer patients. To the best of our knowledge, this is the first report linking the regulation of MAFG by miRNA-7 and its role in chemotherapy response to CDDP. Furthermore, this data highlights the possible role of MAFG as a novel therapeutic target for platinum resistant tumors.

Decreased expression of ALDH5A1 predicts prognosis in patients with ovarian cancer

Aldehyde dehydrogenase 5 family, member A1 (ALDH5A1) belongs to the superfamily of aldehyde dehydrogenases (ALDHs). However, the prognostic value of ALDH5A1 in ovarian cancer remains unclear. The aim of this study was to explore the relationship between ALDH5A1 and the prognosis of patients with ovarian cancer (OC). We compared the expression of ALDH5A1 in OC to that innormal controls, using GSE40595 profiling data. Tissue microarray analysis was conducted for192 OC patients, 14 adjacent normal ovary tissues, and 2 normal ovary tissues. Using the "Kaplan-Meier plotter" (KM plotter) database, updated gene expression data and survival information of a total of 1583 OC patients were used to evaluate the prognostic value of ALDH5A1 in OC patients. We found that ALDH5A1 mRNA expression was downregulated in OC patients compared with that innormal tissues. In survival analyses, we found that ALDH5A1 was positively linked to prognosis in patients with OC, particularly in those with serous ovarian cancer (SOC). In addition, high Ctranscription activity of ALDH5A1 was correlated with better overall survival in SOC patients expressing mutatedTP53, but not in those expressing wild-type TP53. In pathological grades II/III, a high mRNA level of ALDH5A1 was associated with improved overall survival. The positive association between ALDH5A1 and prognosis was found not only in early stages(I and II), but also in advanced stages (III and IV) of SOC patients. results indicate that ALDH5A1 is an excellent predictive factor of OC and may play crucial roles in OC progression.

Prognostic values of four Notch receptor mRNA expression in gastric cancer

Notch ligands and receptors are frequently deregulated in several human malignancies including gastric cancer. The activation of Notch signaling has been reported to contribute to gastric carcinogenesis and progression. However, the prognostic roles of individual Notch receptors in gastric cancer patients remain elusive. In the current study, we accessed the prognostic roles of four Notch receptors, Notch 1-4, in gastric cancer patients through "The Kaplan-Meier plotter" (KM plotter) database, in which updated gene expression data and survival information include a total of 876 gastric cancer patients. All four Notch receptors' high mRNA expression was found to be correlated to worsen overall survival (OS) for all gastric cancer patients followed for 20 years. We further accessed the prognostic roles of individual Notch receptors in different clinicopathological features using Lauren classification, pathological grades, clinical grades, HER2 status and different choices of treatments of gastric cancer patients. These results indicate that there are critical prognostic values of the four Notch receptors in gastric cancer. This information will be useful for better understanding of the heterogeneity and complexity in the molecular biology of gastric cancer and to develop tools to more accurately predict their prognosis.

Prognostic values of aldehyde dehydrogenase 1 isoenzymes in ovarian cancer

Aldehyde dehydrogenase 1 (ALDH1) activity has been used as a functional stem cell marker to isolate cancer stem cells in different cancer types, including ovarian cancer. However, which ALDH1’s isoenzymes are contributing to ALDH1 activity in ovarian cancer remains elusive. In addition, the prognostic value of an individual ALDH1 isoenzyme in ovarian cancer is not clear. Thus, we accessed the prognostic value of ALDH1 isoenzymes in ovarian cancer patients through the “Kaplan–Meier plotter” online database, which can be used to determine the effect of the genes on ovarian cancer prognosis. We found that high mRNA expression of five ALDH1 isoenzymes, such as ALDH1A1, ALDH1A2, ALDH1A3, ALDH1B1, and ALDH1L1, was not correlated with overall survival (OS) for all 1,306 ovarian cancer patients. In addition, all five of the ALDH1 isoenzymes’ high mRNA expression was found to be uncorrelated with OS in serous cancer or endometrioid cancer patients. However, ALDH1A3’s high mRNA expression is associated with worse OS in grade II ovarian cancer patients, hazard ratio (HR) 1.53 (1.14–2.07), P=0.005. ALDH1A2’s high mRNA expression is significantly associated with worse OS in TP53 wild-type ovarian cancer patients, HR 2.86 (1.56–5.08), P=0.00036. In addition, ALDH1A3’s high mRNA expression is significantly associated with better OS in TP53 wild-type ovarian cancer patients, HR 0.56 (0.32–1.00), P=0.04. Our results indicate that although ALDH1 isoenzyme mRNA might not be a prognostic marker for overall ovarian cancer patients, some isoenzymes, such as ALDH1A2 and ALDH1A3, might be a good prognostic marker for some types of ovarian cancer patients.

Distinct prognostic values of four-Notch-receptor mRNA expression in ovarian cancer

Notch signaling pathway includes ligands and Notch receptors, which are frequently deregulated in several human malignancies including ovarian cancer. Aberrant activation of Notch signaling has been linked to ovarian carcinogenesis and progression. In the current study, we used the "Kaplan-Meier plotter" (KM plotter) database, in which updated gene expression data and survival information from a total of 1306 ovarian cancer patients were used to access the prognostic value of four Notch receptors in ovarian cancer patients. Hazard ratio (HR), 95 % confidence intervals, and log-rank P were calculated. Notch1 messenger RNA (mRNA) high expression was not found to be correlated to overall survival (OS) for all ovarian cancer, as well as in serous and endometrioid cancer patients followed for 20 years. However, Notch1 mRNA high expression is significantly associated with worsen OS in TP53 wild-type ovarian cancer patients, while it is significantly associated with better OS in TP53 mutation-type ovarian cancer patients. Notch2 mRNA high expression was found to be significantly correlated to worsen OS for all ovarian cancer patients, as well as in grade II ovarian cancer patients. Notch3 mRNA high expression was found to be significantly correlated to better OS for all ovarian cancer patients, but not in serous cancer patients and endometrioid cancer patients. Notch4 mRNA high expression was not found to be significantly correlated to OS for all ovarian cancer patients, serous cancer patients, and endometrioid cancer patients. These results indicate that there are distinct prognostic values of four Notch receptors in ovarian cancer. This information will be useful for better understanding of the heterogeneity and complexity in the molecular biology of ovarian cancer and for developing tools to more accurately predict their prognosis. Based on our results, Notch1 could be a potential drug target of TP53 wild-type ovarian cancer and Notch2 could be a potential drug target of ovarian cancer.