The overexpression of DNA repair genes in invasive ductal and lobular breast carcinomas: Insights on individual variations and precision medicine

Mohamed, Ruwaa I.; Bargal, Salma A.; Mekawy, Asmaa S; El-Shiekh, Iman; Tunçbağ, Nurcan; Ahmed, Alaa S.; Badr, Eman; Elserafy, Menattallah

doi:10.1371/journal.pone.0247837

Cited by 7 publications

(5 citation statements)

References 121 publications

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“…As previously mentioned, hyperglycemia is suggested to have a profound impact on cancer progression. We have also previously observed an upregulation in 36 DDR genes in ductal and lobular breast carcinomas in comparison to normal breast cells [70]. Therefore, we expected that the increase in the expression levels of DDR genes would be specific to the breast cancer cell line (MDA-MB-231).…”

Section: Discussionmentioning

confidence: 84%

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High Glucose Increases DNA Damage and Elevates the Expression of Multiple DDR Genes

Rahmoon

Elghaish

Ibrahim

et al. 2023

Genes

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The DNA Damage Response (DDR) pathways sense DNA damage and coordinate robust DNA repair and bypass mechanisms. A series of repair proteins are recruited depending on the type of breaks and lesions to ensure overall survival. An increase in glucose levels was shown to induce genome instability, yet the links between DDR and glucose are still not well investigated. In this study, we aimed to identify dysregulation in the transcriptome of normal and cancerous breast cell lines upon changing glucose levels. We first performed bioinformatics analysis using a microarray dataset containing the triple-negative breast cancer (TNBC) MDA-MB-231 and the normal human mammary epithelium MCF10A cell lines grown in high glucose (HG) or in the presence of the glycolysis inhibitor 2-deoxyglucose (2DG). Interestingly, multiple DDR genes were significantly upregulated in both cell lines grown in HG. In the wet lab, we remarkably found that HG results in severe DNA damage to TNBC cells as observed using the comet assay. In addition, several DDR genes were confirmed to be upregulated using qPCR analysis in the same cell line. Our results propose a strong need for DDR pathways in the presence of HG to oppose the severe DNA damage induced in cells.

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Section: Discussionmentioning

confidence: 84%

“…In addition, increasing the number of clones analyzed in the microarray analysis would produce better results. Performing RNA-Sequencing could even produce more solid results [70]. However, overall, both the bioinformatics analysis and the wet lab data greatly support an elevation in DDR genes in the presence of high glucose.…”

Section: Discussionmentioning

confidence: 99%

High Glucose Increases DNA Damage and Elevates the Expression of Multiple DDR Genes

Rahmoon

Elghaish

Ibrahim

et al. 2023

Genes

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“…However, other studies reported the overexpression of some of the genes. This could be owed to biological differences between the patients' samples analyzed in this study and previous studies [71]. Analysis of cell lines versus a cohort of patients can also result in output variability [72].…”

Section: Plos Onementioning

confidence: 83%

A feature selection-based framework to identify biomarkers for cancer diagnosis: A focus on lung adenocarcinoma

et al. 2022

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Lung cancer (LC) represents most of the cancer incidences in the world. There are many types of LC, but Lung Adenocarcinoma (LUAD) is the most common type. Although RNA-seq and microarray data provide a vast amount of gene expression data, most of the genes are insignificant to clinical diagnosis. Feature selection (FS) techniques overcome the high dimensionality and sparsity issues of the large-scale data. We propose a framework that applies an ensemble of feature selection techniques to identify genes highly correlated to LUAD. Utilizing LUAD RNA-seq data from the Cancer Genome Atlas (TCGA), we employed mutual information (MI) and recursive feature elimination (RFE) feature selection techniques along with support vector machine (SVM) classification model. We have also utilized Random Forest (RF) as an embedded FS technique. The results were integrated and candidate biomarker genes across all techniques were identified. The proposed framework has identified 12 potential biomarkers that are highly correlated with different LC types, especially LUAD. A predictive model has been trained utilizing the identified biomarker expression profiling and performance of 97.99% was achieved. In addition, upon performing differential gene expression analysis, we could find that all 12 genes were significantly differentially expressed between normal and LUAD tissues, and strongly correlated with LUAD according to previous reports. We here propose that using multiple feature selection methods effectively reduces the number of identified biomarkers and directly affects their biological relevance.

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“…(2022) found that increased CGA expression was significantly associated with a poor prognosis in patients with breast cancer. H2BC4 was overexpressed in breast cancer (Mohamed et al ., 2021). MSI1 was a negative prognostic indicator of breast cancer patient survival, and was indicative of tumor cells with stem cell-like characteristics (Wang et al ., 2010).…”

Section: Disease Gene Discoverymentioning

confidence: 99%

PathExpSurv: Pathway Expansion for Explainable Survival Analysis and Disease Gene Discovery

Hou

Leng

et al. 2022

Preprint

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In the field of biology and medicine, the interpretability and accuracy are both important when designing predictive models. The interpretability of many machine learning models such as neural networks is still a challenge. Recently, many researchers utilized prior information such as biological pathways to develop bioinformatics methods based on neural networks, so that the prior information can provide some insights and interpretability for the models. However, the prior biological knowledge may be incomplete and there still exists some unknown information to be explored. We proposed a novel method, named PathExpSurv, to gain an insight into the black-box model of neural network for cancer survival analysis. We demonstrated that PathExpSurv could not only incorporate the known prior information into the model, but also explore the unknown possible expansion to the existing pathways. We performed downstream analyses based on the expanded pathways and successfully identified some key genes associated with the diseases and original pathways.

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The overexpression of DNA repair genes in invasive ductal and lobular breast carcinomas: Insights on individual variations and precision medicine

Cited by 7 publications

References 121 publications

High Glucose Increases DNA Damage and Elevates the Expression of Multiple DDR Genes

High Glucose Increases DNA Damage and Elevates the Expression of Multiple DDR Genes

A feature selection-based framework to identify biomarkers for cancer diagnosis: A focus on lung adenocarcinoma

PathExpSurv: Pathway Expansion for Explainable Survival Analysis and Disease Gene Discovery

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