Integrative analyses of triple negative dysregulated transcripts compared with non-triple negative tumors and their functional and molecular interactions

Exploring the therapeutic targets of stevioside in management of type 2 diabetes by network pharmacology and in-silico approach

AIMS

The main objective of the current study is to investigate the pathways and therapeutic targets linked to stevioside in the management of T2D using computational approaches.

METHODS

We collected RNA-seq datasets from NCBI, then employed GREIN to retrieve differentially expressed genes (DEGs). Computer-assisted techniques DAVID, STRING and NetworkAnalyst were used to explore common significant pathways and therapeutic targets associated with T2D and stevioside. Molecular docking and dynamics simulations were conducted to validate the interaction between stevioside and therapeutic targets.

RESULTS

Gene ontology and KEGG analysis revealed that prostaglandin synthesis, IL-17 signaling, inflammatory response, and interleukin signaling were potential pathways targeted by stevioside in T2D. Protein-protein interactions (PPI) analysis identified six common hub proteins (PPARG, PTGS2, CXCL8, CCL2, PTPRC, and EDN1). Molecular docking results showed best binding of stevioside to PPARG (-8 kcal/mol) and PTGS2 (-10.1 kcal/mol). Finally, 100 ns molecular dynamics demonstrated that the binding stability between stevioside and target protein (PPARG and PTGS2) falls within the acceptable range.

CONCLUSIONS

This study reveals that stevioside exhibits significant potential in controlling T2D by targeting key pathways and stably binding to PPARG and PTGS2. Further research is necessary to confirm and expand upon these significant computational results.

Unraveling Biomarker Signatures in Triple-Negative Breast Cancer: A Systematic Review for Targeted Approaches

Triple-negative breast cancer (TNBC) is one of the most aggressive subtypes of breast cancer, marked by poor outcomes and dismal prognosis. Due to the absence of targetable receptors, chemotherapy still represents the main therapeutic option. Therefore, current research is now focusing on understanding the specific molecular pathways implicated in TNBC, in order to identify novel biomarker signatures and develop targeted therapies able to improve its clinical management. With the aim of identifying novel molecular features characterizing TNBC, elucidating the mechanisms by which these molecular biomarkers are implicated in the tumor development and progression, and assessing the impact on cancerous cells following their inhibition or modulation, we conducted a literature search from the earliest works to December 2023 on PubMed, Scopus, and Web Of Science. A total of 146 studies were selected. The results obtained demonstrated that TNBC is characterized by a heterogeneous molecular profile. Several biomarkers have proven not only to be characteristic of TNBC but also to serve as potential effective therapeutic targets, holding the promise of a new era of personalized treatments able to improve its prognosis. The pre-clinical findings that have emerged from our systematic review set the stage for further investigation in forthcoming clinical trials.

Evaluation of Circ_0000977-Mediated Regulatory Network in Breast Cancer: A Potential Discriminative Biomarker for Triple-Negative Tumors

Previous investigations have revealed that circular RNAs (circRNAs) play pivotal roles in cancer development and progression by participating in several biological procedures, such as competing endogenous RNA (ceRNA) networks. Recently, circRNAs have been proposed as non-invasive, stable, and affordable cell-free biomarkers for cancer screening and test monitoring. Although, their clinical usefulness vastly remains to be evaluated in breast cancer (BC). Triple-negative breast cancer (TNBC), as the most challenging BC subtype, is an urgent requirement of identifying specific biomarkers and discovering the molecular mechanisms that lead to aggressive behaviors of tumor cells. The therapeutic strategies for TN patients have remained limited due to the impracticality of endocrine therapies and a remarkable portion of patients with TNBC experience recurrence, chemoresistance, and metastasis. TNBC Microarray expression profile analysis found that circ_0000977 is one of the most dysregulated circRNA in TNBC in comparison with non-TNBC. It could be a clue referring to the potential clinical utility of circ_0000977 in TNBC. The current study aims to assess the clinical implications and potential ceRNA regulatory network of circ_0000977 in TNBC. We confirmed circ_0000977 down-regulation in TNBC cell lines and tumors versus non-TNBC samples by real-time PCR. Subsequently, an assessment of the diagnostic value of circ_0000977 in plasma samples from triple-negative patients revealed a potential diagnostic cell-free biomarker in triple-negative BC. Finally, our integrative approach uncovered potential circ-0000977/miR-135b-5p/mRNAs regulatory network in TNBC. The inhibitory effect of miR-135b-5p on its downstream mRNAs was assessed by knocking down it in MDA-MB-231 cells. Functional and correlation analyses revealed APC and GATA3 could be regulated by circ_0000977/miR-135b-5p ceRNA axis, which presents valuable insight into circ-0000977-mediated gene silencing involved in the ceRNA network of TNBC. This study uncovered the potential clinical implication of circ_0000977 for the diagnosis and treatment of TNBC patients.

RBCK1 is an endogenous inhibitor for triple negative breast cancer via hippo/YAP axis

BACKGROUND

Triple negative breast cancer (TNBC) is one of the most lethal breast cancer subtypes. Due to a lack of effective therapeutic targets, chemotherapy is still the main medical treatment for TNBC patients. Thus, it is important and necessary to find new therapeutic targets for TNBC. Recent genomic studies implicated the Hippo / Yap signal is over activated in TNBC, manifesting it plays a key role in TNBC carcinogenesis and cancer progression. RBCK1 was firstly identified as an important component for linear ubiquitin assembly complex (LUBAC) and facilitates NFKB signaling in immune response. Further studies showed RBCK1 also facilitated luminal type breast cancer growth and endocrine resistance via trans-activation estrogen receptor alpha.

METHODS

RBCK1 and YAP protein expression levels were measured by western blotting, while the mRNA levels of YAP target genes were measured by RT-PCR. RNA sequencing data were analyzed by Ingenuity Pathway Analysis. Identification of Hippo signaling activity was accomplished with luciferase assays, RT-PCR and western blotting. Protein stability assays and ubiquitin assays were used to detect YAP protein degradation. Ubiquitin-based immunoprecipitation assays were used to detect the specific ubiquitination modification on the YAP protein.

RESULTS

In our current study, our data revealed an opposite function for RBCK1 in TNBC progression. RBCK1 over-expression inhibited TNBC cell progression in vitro and in vivo, while RBCK1 depletion promoted TNBC cell invasion. The whole genomic expression profiling showed that RBCK1 depletion activated Hippo/YAP axis. RBCK1 depletion increased YAP protein level and Hippo target gene expression in TNBC. The molecular biology studies confirmed that RBCK1 could bind to YAP protein and enhance the stability of YAP protein by promoting YAP K48-linked poly-ubiquitination at several YAP lysine sites (K76, K204 and K321).

CONCLUSION

Our study revealed the multi-faced RBCK1 function in different subtypes of breast cancer patients and a promising therapeutic target for TNBC treatment. Video abstract.

The role of FOXC1/FOXCUT/DANCR axis in triple negative breast cancer: a bioinformatics and experimental approach

BACKGROUND

Triple-negative breast cancer (TNBC) is the most challenging subtype of breast cancer and does not benefit from the existing targeted therapies. In the present study, we used bioinformatics and experimental approaches to assess the genes that are somehow involved in the epithelial-mesenchymal transition (EMT) pathway which may explain the invasive features of TNBC.

METHOD AND RESULTS

We analyzed five GEO datasets consisting of 657 breast tumors by GEO2R online software to achieve common differentially expressed genes (DEGs) between TNBC and non-TNBC tumors. The expression of the selected coding and non-coding genes was validated in 100 breast tumors, including fifty TNBC and fifty non-TNBC samples, using quantitative Real-Time PCR (qRT-PCR). The bioinformatics approach resulted in a final DEG list consisting of ten upregulated and seventeen downregulated genes (logFC ≥|1| and P < 0.05). Co-expression network construction indicated the FOXC1 transcription factor as a central hub node. Considering the notable role of FOXC1 in EMT, the expression levels of FOXC1-related lncRNAs, lnc-FOXCUT and lnc-DANCR, were also evaluated in the studied tumors. The results of qRT-PCR confirmed notable upregulation of FOXC1, lnc-FOXCUT, and lnc-DANCR in TNBC tissues compared to non-TNBC samples (P < 0.0001, P = 0.0005, and P = 0.0008, respectively). Moreover, ROC curve analysis revealed the potential biomarker role of FOXC1 in TNBC samples.

CONCLUSION

Present study suggested that the deregulation of FOXC1/lnc-FOXCUT/lnc-DANCR axis may contribute to the aggressive features of triple-negative breast tumors. Therefore, this axis may be considered as a new probable therapeutic target in the treatment of TNBC.

Overexpression of GABRP Gene in Triple Negative Breast Cancer: Molecular Mechanisms and Interpretation

Background: Triple-negative breast cancer (TNBC) is a heterogeneous disease that characterized by aggressiveness features with increased metastasis and poor clinical prognosis. However, the molecular mechanisms underlying this highly malignant phenotype are still poorly understood. It has been well documented that the dysregulation of neural genes is profoundly implicated in cancer development and metastasis. Objectives: In the present study, the expression level of GABA receptor π subunit (GABRP) as the most up-regulated gene in TNBC and a hub node in the co-expression network were investigated. Methods: In this study, the importance of GABRP as the most up-regulated gene in TNBC was discovered through integrative analysis of multiple microarray expression datasets, containing about 1000 samples. Furthermore, the co-expression network analysis was constructed based on the up-regulated genes. Quantitative Real‐time polymerase chain reaction (qRT-PCR) was used to evaluate of the GABRP expression in 50 TNBC compared to 33 non-TNBC tumors. Results: According to the bioinformatics analysis, GABRP occupies a key position in the co-expression network which is mainly enriched in the nervous systems development. The qRT-PCR results indicated that up-regulation of GABRP was highly concordant with integrative analysis findings. Moreover, the receiver operating characteristic (ROC) curve analysis revealed that GABRP can be a potential biomarker to distinguish TNBC from non-TNBC samples. Conclusions: Our study revealed that up-regulation of GABRP is among the most remarkable molecular signature in TNBC and may play a critical role in tumorigenesis. The results may provide a deeper insight into molecular mechanisms underlying the brain metastasis in TNBC tumors and propose the potential targets for therapeutic interventions.

Circular RNA-associated ceRNA network involved in HIF-1 signalling in triple-negative breast cancer: circ_0047303 as a potential key regulator

The aggressive and highly metastatic nature of triple‐negative breast cancer (TNBC) causes patients to suffer from the poor outcome. HIF‐1 signalling pathway is a prominent pathway that contributes to angiogenesis and metastasis progression in tumours. On the contrary, the undeniable importance of circular RNAs (circRNAs) as multifunctional non‐coding RNAs (ncRNAs) has been identified in breast cancer. These ncRNAs owing to their high stability and specificity have been becoming a hotspot in cancer researches. circRNAs act as competing endogenous RNAs (ceRNAs) and compete with mRNAs for shared miRNAs, thus modulate gene expression. Since the most dysregulated biological functions in TNBC are associated with cellular invasion, understanding the molecular pathogenesis of these processes is a crucial step towards the development of new treatment approaches. The purpose of this study is to undermine the circRNA‐associated ceRNA network involved in HIF‐1 signalling in TNBC using an integrative bioinformatics approach. In the next step, the novel circ_0047303‐mediated ceRNA regulatory axes have been extracted and validated across TNBC samples. We show that circ_0047303 has the highest degree in the circRNA‐associated ceRNA network and shows a significant up‐expression in TNBC. Moreover, our results suggest that circ_0047303 could mediate the upregulation of key angiogenesis‐related genes, including HIF‐1, EIF4E2 and VEGFA in TNBC through sponging the tumour‐suppressive miRNAs. The circ_0047303 could be a promising molecular biomarker and/or therapeutic target for TNBC.

Identifying Hub Genes, Key Pathways and Immune Cell Infiltration Characteristics in Pediatric and Adult Ulcerative Colitis by Integrated Bioinformatic Analysis

BACKGROUND AND AIMS

In the present study, we investigated the differentially expressed genes (DEGs), pathways and immune cell infiltration characteristics of pediatric and adult ulcerative colitis (UC).

METHODS

We conducted DEG analysis using the microarray dataset GSE87473 containing 19 pediatric and 87 adult UC samples downloaded from the Gene Expression Omnibus. Gene ontology and pathway enrichment analyses were conducted using Metascape. We constructed the protein-protein interaction (PPI) network and the drug-target interaction network of DEGs and identified hub modules and genes using Cytoscape and analyzed immune cell infiltration in pediatric and adult UC using CIBERSORT.

RESULTS

In total, 1700 DEGs were screened from the dataset. These genes were enriched mainly in inter-cellular items relating to cell junctions, cell adhesion, actin cytoskeleton and transmembrane receptor signaling pathways and intra-cellular items relating to the splicing, metabolism and localization of RNA. CDC42, POLR2A, RAC1, PIK3R1, MAPK1 and SRC were identified as hub DEGs. Immune cell infiltration analysis revealed higher proportions of naive B cells, resting memory T helper cells, regulatory T cells, monocytes, M0 macrophages and activated mast cells in pediatric UC, along with lower proportions of memory B cells, follicular helper T cells, γδ T cells, M2 macrophages, and activated dendritic cells.

CONCLUSIONS

Our study suggested that hub genes CDC42, POLR2A, RAC1, PIK3R1, MAPK1 and SRC and immune cells including B cells, T cells, monocytes, macrophages and mast cells play vital roles in the pathological differences between pediatric and adult UC and may serve as potential biomarkers in the diagnosis and treatment of UC.

Circular RNA hsa_circ_0044234 as distinct molecular signature of triple negative breast cancer: a potential regulator of GATA3

BACKGROUND

Circular RNAs (circRNAs) have been implicated in the initiation and development of breast cancer as functional non-coding RNAs (ncRNA). The roles of circRNAs as the competing endogenous RNAs (ceRNAs) to sponge microRNAs (miRNAs) have also been indicated. However, the functions of circRNAs in breast cancer have not been totally elucidated. This study aimed to explore the clinical implications and possible roles of circ_0044234 in carcinogenesis of the most problematic BC subtype, triple negative breast cancer (TNBC), which are in desperate need of biomarkers and targeted therapies.

METHODS

The importance of circ_0044234 as one of the most dysregulated circRNAs in TNBC was discovered through microarray expression profile analysis. Reverse transcription-quantitative polymerase chain reaction (RT-qPCR) was performed to confirm the downregulation of circ_0044234 in triple negative tumors and cell lines versus non-triple negative ones. The bioinformatics prediction revealed that circ_0044234 could act as an upstream sponge in the miR-135b/GATA3 axis, two of the most dysregulated transcripts in TNBC.

RESULTS

Our experimental investigation of circ_0044234 expressions in various BC subtypes as well as cell lines reveals that TNBC expresses circ_0044234 at a substantially lower level than non-TNBC. The ROC curve analysis indicates that it could be applied as a discriminative biomarker to identify TNBC from other BC subtypes. Moreover, circ_0044234 expression could be an independent prognostic biomarker in BC. Interestingly, a substantial inverse expression correlation was detected between circ_0044234 and miR-135b-5p as well as between miR-135b-5p and GATA3 in breast tumors.

CONCLUSIONS

The possible clinical usefulness of circ_0044234 as a promising distinct biomarker and upcoming therapeutic target for TNBC have been indicated in this research. Our comprehensive approach revealed the potential circ_0044234/miR135b-5p/GATA3 ceRNA axis in TNBC.

Immune checkpoint inhibitors: review of the existing evidence and challenges in breast cancer

Cancer initiation and progression are associated with immune system responses. Tumor cells use various tricks to scape of immune system, such as activating immune checkpoint pathways that induce immunosuppressive functions. Among the different immune checkpoint receptors, CTLA-4 and PD-1/PD-L1 are prominent therapeutic targets in different cancers. Although the US FDA has approved some immune checkpoint inhibitors for several cancers, concerning breast cancer still different clinical trials are looking for optimizing efficacy and decreasing immune-related adverse events. This review will discuss the existing body of knowledge with regard to cross-talk between immune system and tumor cells and then explore immune checkpoint-related signaling pathways in the context of breast tumors. Finally, we highlight the application of different immune checkpoint blockers in breast cancer patients.

Identification of dysregulated miRNAs-genes network in ovarian cancer: An integrative approach to uncover the molecular interactions and oncomechanisms

Background

Ovarian (OV) cancer is considered as one of the most deadly malignancies in women, since it is unfortunately diagnosed in advanced stages. Nowadays, the importance of bioinformatics tools and their frequent usage in tracking dysregulated cancer‐related genes and pathways have been highlighted in researches.

Aim

The aim of this study is to investigate dysregulated miRNAs‐genes network and its function in OV tumors based on the integration of microarray data through a system biology approach.

Methods

Two microarray data (GSE119056 and GSE4122) were analyzed to explore the differentially expressed miRNAs (DEmiRs) and genes among OV tumors and normal tissues. Then, through the help of TargetScan, miRmap, and miRTarBase databases, the dysregulated miRNA‐gene network in OV tumors was constructed by Cytoscape. In the next step, co‐expression and protein‐protein interaction networks were made using GEPIA and STRING databases. Moreover, the functional analysis of the hub genes was done by DAVID, KEGG, and Enrichr databases. Eventually, the regulatory network of TF‐miRNA‐gene was constructed.

Results

The potential dysregulated miRNAs‐genes network in OV tumors has been constructed, including 109 differentially expressed genes (DEGs), 25 DEmiRs, and 213 interactions. Two down‐regulated microRNAs, miR‐660‐3p and hsa‐miR‐4510, have the most interactions with up‐expressed oncogenic DEGs. CDK1, PLK1, CCNB1, CCNA2, and EZH2 are involved in protein module, which show significant overexpression in OV tumors according to The Cancer Genome Atlas (TCGA) data. EZH2 shows amplification in OV tumors with remarkable percentage. The transcription factors TFAP2C and GATA4 have the pivotal regulatory functions in oncotranscriptomic profile of OV tumors.

Conclusion

In current study, we have collected and integrated different data to uncover the complex molecular interactions and oncomechanisms in OV tumors. The DEmiRs‐DEGs and TF‐miRNA‐gene networks reveal the potential interactions that could be a significant piece of the OV onco‐puzzle.

Comparison of methods for the detection of outliers and associated biomarkers in mislabeled omics data

Background

Previous studies have reported that labeling errors are not uncommon in omics data. Potential outliers may severely undermine the correct classification of patients and the identification of reliable biomarkers for a particular disease. Three methods have been proposed to address the problem: sparse label-noise-robust logistic regression (Rlogreg), robust elastic net based on the least trimmed square (enetLTS), and Ensemble. Ensemble is an ensembled classification based on distinct feature selection and modeling strategies. The accuracy of biomarker selection and outlier detection of these methods needs to be evaluated and compared so that the appropriate method can be chosen.

Results

The accuracy of variable selection, outlier identification, and prediction of three methods (Ensemble, enetLTS, Rlogreg) were compared for simulated and an RNA-seq dataset. On simulated datasets, Ensemble had the highest variable selection accuracy, as measured by a comprehensive index, and lowest false discovery rate among the three methods. When the sample size was large and the proportion of outliers was ≤5%, the positive selection rate of Ensemble was similar to that of enetLTS. However, when the proportion of outliers was 10% or 15%, Ensemble missed some variables that affected the response variables.

Overall, enetLTS had the best outlier detection accuracy with false positive rates < 0.05 and high sensitivity, and enetLTS still performed well when the proportion of outliers was relatively large. With 1% or 2% outliers, Ensemble showed high outlier detection accuracy, but with higher proportions of outliers Ensemble missed many mislabeled samples. Rlogreg and Ensemble were less accurate in identifying outliers than enetLTS. The prediction accuracy of enetLTS was better than that of Rlogreg. Running Ensemble on a subset of data after removing the outliers identified by enetLTS improved the variable selection accuracy of Ensemble.

Conclusions

When the proportion of outliers is ≤5%, Ensemble can be used for variable selection. When the proportion of outliers is > 5%, Ensemble can be used for variable selection on a subset after removing outliers identified by enetLTS. For outlier identification, enetLTS is the recommended method. In practice, the proportion of outliers can be estimated according to the inaccuracy of the diagnostic methods used.

Identification of Key Differentially Expressed Transcription Factors in Glioblastoma

Glioblastoma (GBM) is the most frequent malignant brain tumor in adults. Our study focused on uncovering differentially expressed genes (DEGs) and their methylation in order to identify novel diagnostic biomarkers and potential treatment targets. Using GBM RNA-sequencing data from The Cancer Genome Atlas (TCGA) database, DEGs between GBM samples and paracancer tissue samples were analyzed. Enrichment analysis for DEGs and transcription factors (TFs) was performed. A total of 1029 upregulated genes and 1542 downregulated genes were identified, which were associated mainly with multiple tumor-related and immune-related pathways such as cell cycle, mitogen-activated protein kinase signaling pathway, leukocyte transendothelial migration, and autoimmune thyroid disease. These DEGs were enriched for 174 TFs, and six TFs were differentially expressed and identified as key TFs in GBM: HOXA3, EN1, ZIC1, and FOXD3 were upregulated, while HLF and EGR3 were downregulated. A total of 1978 DEGs were involved in the regulatory networks of the six key differentially expressed TFs. High expression of EN1 was associated with shorter overall survival, while high expression of EGR3 was associated with shorter recurrence-free survival. The six TFs were differentially methylated in GBM samples compared with paracancer tissues. Our study identifies numerous DEGs and their associated pathways as potential contributors to GBM, particularly the TFs EN1, EGR3, HOXA3, ZIC1, FOXD3, and HLF. The differential expression of these TFs may be unlikely driven by aberrant methylation. These TFs may be useful as diagnostic markers and treatment targets in GBM, and EN1 and EGR3 may have predictive prognostic value.

Unraveling the Genomic-Epigenomic Interaction Landscape in Triple Negative and Non-Triple Negative Breast Cancer

Background: The recent surge of next generation sequencing of breast cancer genomes has enabled development of comprehensive catalogues of somatic mutations and expanded the molecular classification of subtypes of breast cancer. However, somatic mutations and gene expression data have not been leveraged and integrated with epigenomic data to unravel the genomic-epigenomic interaction landscape of triple negative breast cancer (TNBC) and non-triple negative breast cancer (non-TNBC). Methods: We performed integrative data analysis combining somatic mutation, epigenomic and gene expression data from The Cancer Genome Atlas (TCGA) to unravel the possible oncogenic interactions between genomic and epigenomic variation in TNBC and non-TNBC. We hypothesized that within breast cancers, there are differences in somatic mutation, DNA methylation and gene expression signatures between TNBC and non-TNBC. We further hypothesized that genomic and epigenomic alterations affect gene regulatory networks and signaling pathways driving the two types of breast cancer. Results: The investigation revealed somatic mutated, epigenomic and gene expression signatures unique to TNBC and non-TNBC and signatures distinguishing the two types of breast cancer. In addition, the investigation revealed molecular networks and signaling pathways enriched for somatic mutations and epigenomic changes unique to each type of breast cancer. The most significant pathways for TNBC were: retinal biosynthesis, BAG2, LXR/RXR, EIF2 and P2Y purigenic receptor signaling pathways. The most significant pathways for non-TNBC were: UVB-induced MAPK, PCP, Apelin endothelial, Endoplasmatic reticulum stress and mechanisms of viral exit from host signaling Pathways. Conclusion: The investigation revealed integrated genomic, epigenomic and gene expression signatures and signing pathways unique to TNBC and non-TNBC, and a gene signature distinguishing the two types of breast cancer. The study demonstrates that integrative analysis of multi-omics data is a powerful approach for unravelling the genomic-epigenomic interaction landscape in TNBC and non-TNBC.