Molecular mechanism of triple-negative breast cancer-associated BRCA1 and the identification of signaling pathways

LRG1 and SDR16C5 protein expressions differ according to HPV status in oropharyngeal squamous cell carcinoma

The increasing incidence of oropharyngeal squamous cell carcinoma (OPSCC) is primarily due to human papillomavirus, and understanding the tumor biology caused by the virus is crucial. Our goal was to investigate the proteins present in the serum of patients with OPSCC, which were not previously studied in OPSCC tissue. We examined the difference in expression of these proteins between HPV-positive and -negative tumors and their correlation with clinicopathological parameters and patient survival. The study included 157 formalin-fixed, paraffin-embedded tissue samples and clinicopathological data. Based on the protein levels in the sera of OPSCC patients, we selected 12 proteins and studied their expression in HPV-negative and HPV-positive OPSCC cell lines. LRG1, SDR16C5, PIP4K2C and MVD proteins were selected for immunohistochemical analysis in HPV-positive and -negative OPSCC tissue samples. These protein´s expression levels were compared with clinicopathological parameters and patient survival to investigate their clinical relevance. LRG1 expression was strong in HPV-negative whereas SDR16C5 expression was strong in HPV-positive tumors. Correlation was observed between LRG1, SDR16C5, and PIP4K2C expression and patient survival. High expression of PIP4K2C was found to be an independent prognostic factor for overall survival and expression correlated with HPV-positive tumor status. The data suggest the possible role of LRG1, SDR16C5 and PIP4K2C in OPSCC biology.

Differential whole-genome doubling based signatures for improvement on clinical outcomes and drug response in patients with breast cancer

Whole genome doublings (WGD), a hallmark of human cancer, is pervasive in breast cancer patients. However, the molecular mechanism of the complete impact of WGD on survival and treatment response in breast cancer remains unclear. To address this, we performed a comprehensive and systematic analysis of WGD, aiming to identify distinct genetic alterations linked to WGD and highlight its improvement on clinical outcomes and treatment response for breast cancer. A linear regression model along with weighted gene co-expression network analysis (WGCNA) was applied on The Cancer Genome Atlas (TCGA) dataset to identify critical genes related to WGD. Further Cox regression models with random selection were used to optimize the most useful prognostic markers in the TCGA dataset. The clinical implication of the risk model was further assessed through prognostic impact evaluation, tumor stratification, functional analysis, genomic feature difference analysis, drug response analysis, and multiple independent datasets for validation. Our findings revealed a high aneuploidy burden, chromosomal instability (CIN), copy number variation (CNV), and mutation burden in breast tumors exhibiting WGD events. Moreover, 247 key genes associated with WGD were identified from the distinct genomic patterns in the TCGA dataset. A risk model consisting of 22 genes was optimized from the key genes. High-risk breast cancer patients were more prone to WGD and exhibited greater genomic diversity compared to low-risk patients. Some oncogenic signaling pathways were enriched in the high-risk group, while primary immune deficiency pathways were enriched in the low-risk group. We also identified a risk gene, ANLN (anillin), which displayed a strong positive correlation with two crucial WGD genes, KIF18A and CCNE2. Tumors with high expression of ANLN were more prone to WGD events and displayed worse clinical survival outcomes. Furthermore, the expression levels of these risk genes were significantly associated with the sensitivities of BRCA cell lines to multiple drugs, providing valuable insights for targeted therapies. These findings will be helpful for further improvement on clinical outcomes and contribution to drug development in breast cancer.

Efficacy of metformin and electrical pulses in breast cancer MDA-MB-231 cells

Aim

Triple-negative breast cancer (TNBC) is a very aggressive subset of breast cancer, with limited treatment options, due to the lack of three commonly targeted receptors, which merits the need for novel treatments for TNBC. Towards this need, the use of metformin (Met), the most widely used type-2 diabetes drug worldwide, was explored as a repurposed anticancer agent. Cancer being a metabolic disease, the modulation of two crucial metabolites, glucose, and reactive oxygen species (ROS), is studied in MDA-MB-231 TNBC cells, using Met in the presence of electrical pulses (EP) to enhance the drug efficacy.

Methods

MDA-MB-231, human TNBC cells were treated with Met in the presence of EP, with various concentrations Met of 1 mmol/L, 2.5 mmol/L, 5 mmol/L, and 10 mmol/L. EP of 500 V/cm, 800 V/cm, and 1,000 V/cm (with a pulse width of 100 µs at 1 s intervals) were applied to TNBC and the impact of these two treatments was studied. Various assays, including cell viability, microscopic inspection, glucose, ROS, and wound healing assay, were performed to characterize the response of the cells to the combination treatment.

Results

Combining 1,000 V/cm with 5 mmol/L Met yielded cell viability as low as 42.6% at 24 h. The glucose level was reduced by 5.60-fold and the ROS levels were increased by 9.56-fold compared to the control, leading to apoptotic cell death.

Conclusions

The results indicate the enhanced anticancer effect of Met in the presence of electric pulses. The cell growth is inhibited by suppressing glucose levels and elevated ROS. This shows a synergistic interplay between electroporation, Met, glucose, and ROS metabolic alterations. The results show promises for combinational therapy in TNBC patients.

Integrative pathway analysis with gene expression, miRNA, methylation and copy number variation for breast cancer subtypes

Developments in biotechnologies enable multi-platform data collection for functional genomic units apart from the gene. Profiling of non-coding microRNAs (miRNAs) is a valuable tool for understanding the molecular profile of the cell, both for canonical functions and malignant behavior due to complex diseases. We propose a graphical mixed-effects statistical model incorporating miRNA-gene target relationships. We implement an integrative pathway analysis that leverages measurements of miRNA activity for joint analysis with multimodal observations of gene activity including gene expression, methylation, and copy number variation. We apply our analysis to a breast cancer dataset, and consider differential activity in signaling pathways across breast tumor subtypes. We offer discussion of specific signaling pathways and the effect of miRNA integration, as well as publish an interactive data visualization to give public access to the results of our analysis.

The current advances of lncRNAs in breast cancer immunobiology research

Breast cancer is the most frequently diagnosed malignancy and the leading cause of cancer-related death in women worldwide. Breast cancer development and progression are mainly associated with tumor-intrinsic alterations in diverse genes and signaling pathways and with tumor-extrinsic dysregulations linked to the tumor immune microenvironment. Significantly, abnormal expression of lncRNAs affects the tumor immune microenvironment characteristics and modulates the behavior of different cancer types, including breast cancer. In this review, we provide the current advances about the role of lncRNAs as tumor-intrinsic and tumor-extrinsic modulators of the antitumoral immune response and the immune microenvironment in breast cancer, as well as lncRNAs which are potential biomarkers of tumor immune microenvironment and clinicopathological characteristics in patients, suggesting that lncRNAs are potential targets for immunotherapy in breast cancer.

Targeting Triple Negative Breast Cancer With Oncolytic Adenoviruses

Breast cancer (BC) is the most common cancer globally, accounting for 685,000 deaths in 2020. Triple-negative breast cancers (TNBC) lack oestrogen (ER) and progesterone (PR) hormone receptor expression and HER2 overexpression. TNBC represent 10–15% of all BC with high incidence in women under 50-years old that have BRCA mutations, and have a dismal prognosis. African American and Hispanic women are at higher risk partly due to the common occurrence of BRCA mutations. The standard treatment for TNBC includes surgery, radiotherapy, and chemotherapy although, resistance to all standard-of-care therapies eventually develops. It is crucial to identify and develop more efficacious therapeutics with different mechanisms of action to improve on survival in these women. Recent findings with oncolytic adenoviruses (OAds) may generate a new strategy to improve on the outcomes for women afflicted by TNBC and other types of BC. OAds are genetically engineered to selectively lyse, eliminate and recruit the host antitumour immune responses, leaving normal cells unharmed. The most common modifications are deletions in the early gene products including the E1B55 KDa protein, specific regions of the E1A protein, or insertion of tumour-specific promoters. Clinical trials using OAds for various adenocarcinomas have not yet been sufficiently evaluated in BC patients. Preclinical studies demonstrated efficacy in BC cell lines, including TNBC cells, with promising novel adenoviral mutants. Here we review the results reported for the most promising OAds in preclinical studies and clinical trials administered alone and in combination with current standard of care or with novel therapeutics. Combinations of OAds with small molecule drugs targeting the epidermal growth factor receptor (EGFR), androgen receptor (AR), and DNA damage repair by the novel PARP inhibitors are currently under investigation with reported enhanced efficacy. The combination of the PARP-inhibitor Olaparib with OAds showed an impressive anti-tumour effect. The most promising findings to date are with OAds in combination with antibodies towards the immune checkpoints or expression of cytokines from the viral backbone. Although safety and efficacy have been demonstrated in numerous clinical trials and preclinical studies with cancer-selective OAds, further developments are needed to eliminate metastatic lesions, increase immune activation and intratumoural viral spread. We discuss shortcomings of the OAds and potential solutions for improving on patient outcomes.

Ontologies and Knowledge Graphs in Oncology Research

The complexity of cancer research stems from leaning on several biomedical disciplines for relevant sources of data, many of which are complex in their own right. A holistic view of cancer—which is critical for precision medicine approaches—hinges on integrating a variety of heterogeneous data sources under a cohesive knowledge model, a role which biomedical ontologies can fill. This study reviews the application of ontologies and knowledge graphs in cancer research. In total, our review encompasses 141 published works, which we categorized under 14 hierarchical categories according to their usage of ontologies and knowledge graphs. We also review the most commonly used ontologies and newly developed ones. Our review highlights the growing traction of ontologies in biomedical research in general, and cancer research in particular. Ontologies enable data accessibility, interoperability and integration, support data analysis, facilitate data interpretation and data mining, and more recently, with the emergence of the knowledge graph paradigm, support the application of Artificial Intelligence methods to unlock new knowledge from a holistic view of the available large volumes of heterogeneous data.

Methylation of Immune-Related Genes in Peripheral Blood Leukocytes and Breast Cancer

Abnormal DNA methylation contributes to breast cancer (BC). Immune-related genes play crucial roles in BC development and progression. This study aims to investigate the effect of methylation of immune-related genes in peripheral blood leukocytes (PBLs) on BC risk. GSE51032 and GSE104942 datasets were used to identify significantly differentially methylated CpG sites (DMCs) of immune-related genes. A case-control study was conducted using MethylTarget sequencing to validate the relationship between the methylation levels of the screened genes and BC risk. We also evaluated the association between methylation haplotypes of screened genes and BC risk. Moreover, we sorted the blood leukocytes into T cells, B cells, and monocytes to detect the difference of DNA methylation in different cell subtypes. A total of five DMCs were screened from GEO datasets, including cg01760846 (PSMC1), cg07141527 (SPPL3), cg15658543 (CARD11), cg21568368 (PSMB8), and cg24045276 (NCF2). In the case-control study, there were significant associations between methylation of the CpG sites in the five genes and BC risk. Methylation haplotype burdens of PSMC1, CARD11, and PSMB8 were associated with reduced BC risk. Moreover, there were heterogeneities in the methylation levels of the genes in different cell subtypes. In conclusion, methylation of PSMC1, SPPL3, CARD11, PSMB8, and NCF2 in PBLs were associated with BC risk. The five-gene methylation could be the potential biomarkers for predicting BC risk.

Screening differentially expressed genes between endometriosis and ovarian cancer to find new biomarkers for endometriosis

AIM

Endometriosis is one of the most common reproductive system diseases, but the mechanisms of disease progression are still unclear. Due to its high recurrence rate, searching for potential therapeutic biomarkers involved in the pathogenesis of endometriosis is an urgent issue.

METHODS

Due to the similarities between endometriosis and ovarian cancer, four endometriosis datasets and one ovarian cancer dataset were downloaded from Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were identified, followed by gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and protein-protein interaction (PPI) analyses. Then, we validated gene expression and performed survival analysis with ovarian serous cystadenocarcinoma (OV) datasets in TCGA/GTEx database, and searched for potential drugs in the Drug-Gene Interaction Database. Finally, we explored the miRNAs of key genes to find biomarkers associated with the recurrence of endometriosis.

RESULTS

In total, 104 DEGs were identified in the endometriosis datasets, and the main enriched GO functions included cell adhesion, extracellular exosome and actin binding. Fifty DEGs were identified between endometriosis and ovarian cancer datasets including 11 consistently regulated genes, and nine DEGs with significant expression in TCGA/GTEx. Only IGHM had both significant expression and an association with survival, three module DEGs and two significantly expressed DEGs had drug associations, and 10 DEGs had druggability.

CONCLUSIONS

ITGA7, ITGBL1 and SORBS1 may help us understand the invasive nature of endometriosis, and IGHM might be related to recurrence; moreover, these genes all may be potential therapeutic targets.KEY MESSAGEThis manuscript used a bioinformatics approach to find target genes for the treatment of endometriosis.This manuscript used a new approach to find target genes by drawing on common characteristics between ovarian cancer and endometriosis.We screened relevant therapeutic agents for target genes in the drug database, and performed histological validation of target genes with both expression and survival analysis difference in cancer databases.

STARD3: A Prospective Target for Cancer Therapy

Cancer is one of the major causes of death in developed countries and current therapies are based on surgery, chemotherapeutic agents, and radiation. To overcome side effects induced by chemo- and radiotherapy, in recent decades, targeted therapies have been proposed in second and even first lines. Targeted drugs act on the essential pathways involved in tumor induction, progression, and metastasis, basically all the hallmark of cancers. Among emerging pathways, the cholesterol metabolic pathway is a strong candidate for this purpose. Cancer cells have an accelerated metabolic rate and require a continuous supply of cholesterol for cell division and membrane renewal. Steroidogenic acute regulatory related lipid transfer (START) proteins are a family of proteins involved in the transfer of lipids and some of them are important in non-vesicular cholesterol transportation within the cell. The alteration of their expression levels is implicated in several diseases, including cancers. In this review, we report the latest discoveries on StAR-related lipid transfer protein domain 3 (STARD3), a member of the START family, which has a potential role in cancer, focusing on the structural and biochemical characteristics and mechanisms that regulate its activity. The role of the STARD3 protein as a molecular target for the development of cancer therapies is also discussed. As STARD3 is a key protein in the cholesterol movement in cancer cells, it is of interest to identify inhibitors able to block its activity.

Triple-negative breast cancer: understanding Wnt signaling in drug resistance

Triple-negative breast cancer (TNBC) is not as prevalent as hormone receptor or HER2-positive breast cancers and all receptor tests come back negative. More importantly, the heterogeneity and complexity of the TNBC on the molecular and clinical levels have limited the successful development of novel therapeutic strategies and led to intrinsic or developed resistance to chemotherapies and new therapeutic agents. Studies have demonstrated deregulation of Wnt/β-catenin signaling in tumorigenesis which plays decisive roles at the low survival rate of patients and facilitates resistance to currently existing therapies. This review summarizes mechanisms of Wnt/β-catenin signaling for resistance development in TNBC, the complex interaction between Wnt/β-catenin signaling, and the transactivated receptor tyrosine kinase (RTK) signaling pathways, lymphocytic infiltration, epithelial-mesenchymal transition (EMT), and induction of metastasis. Such associations and how these pathways interact in the development and progression of cancer have led to the careful analysis and development of new and effective combination therapies without generating significant toxicity and resistance.

CARD11 is a prognostic biomarker and correlated with immune infiltrates in uveal melanoma

Uveal melanoma (UVM), the most common primary intraocular malignancy, has a high mortality because of a high propensity to metastasize. Our study analyzed prognostic value and immune-related characteristics of CARD11 in UVM, hoping to provide a potential management and research direction. The RNA-sequence data of 80 UVM patients were downloaded from The Cancer Genome Atlas database and divided them into high- and low-expression groups. We analyzed the differentially expressed genes, enrichment analyses and the infiltration of immune cells using the R package and Gene-Set Enrichment Analysis. A clinical prediction nomogram and protein-protein interaction network were constructed and the first 8 genes were considered as the hub-genes. Finally, we constructed a competing endogenous RNA (ceRNA) network by Cytoscape and analyzed the statistical data via the R software. Here we found that CARD11 expression had notable correlation with UVM clinicopathological features, which was also an independent predictor for overall survival (OS). Intriguingly, CARD11 had a positively correlation to autophagy, cellular senescence and apoptosis. Infiltration of monocytes was significantly higher in low CARD11 expression group, and infiltration of T cells regulatory was lower in the same group. Functional enrichment analyses revealed that CARD11 was positively related to T cell activation pathways and cell adhesion molecules. The expressions of hub-genes were all increased in the high CARD11 expression group and the ceRNA network showed the interaction among mRNA, miRNA and lncRNA. These findings show that high CARD11 expression in UVM is associated with poor OS, indicating that CARD11 may serve as a potential biomarker for the diagnosis and prognosis of the UVM.

Identification prognosis-associated immune genes in colon adenocarcinoma

Colon adenocarcinoma (COAD) is one of the most prevalent malignant tumors worldwide. Immune genes (IGs) have a considerable correlation with tumor initiation and prognosis. The present paper aims to identify the prognosis value of IGs in COAD and conduct a prognosis model for clinical utility. Gene expression data of COAD were downloaded from The Cancer Genome Atlas (TCGA), screening and analyzing differentially expressed IGs by bioinformatics. Core genes were screened by univariate and multivariate Cox regression analyses. Survival analysis was appraised by the Kaplan–Meier method and the log-rank test. Gene Ontology, Kyoto Encyclopedia of Genes and Genomes, and Gene Set Enrichment Analysis (GSEA) were used to identify IGs’ relevant signal pathways. We predicted the overall survival (OS) by nomogram. Finally, a prognosis model was conducted based on 12 IGs (SLC10A2, CXCL3, NOX4, FABP4, ADIPOQ, IGKV1-33, IGLV6-57, INHBA, UCN, VIP, NGFR, and TRDC). The risk score was an independent prognostic factor, and a nomogram could accurately predict the OS of individual COAD patients. These results were validated in GSE39582, GSE12945, and GSE103479 cohorts. Functional enrichment analysis demonstrated that these IGs are mainly enriched in hormone secretion, hormone transport, lipid transport, cytokine–cytokine receptor interaction, and peroxisome proliferators-activated receptor signaling pathway. In summary, the risk score is an independent prognostic biomarker. We also excavated several IGs related to COAD’s survival and maybe potential biomarkers for COAD diagnosis and treatment.

TSPAN1, TMPRSS4, SDR16C5, and CTSE as Novel Panel for Pancreatic Cancer: A Bioinformatics Analysis and Experiments Validation

Pancreatic cancer is a lethal malignancy with a poor prognosis. This study aims to identify pancreatic cancer-related genes and develop a robust diagnostic model to detect this disease. Weighted gene co-expression network analysis (WGCNA) was used to determine potential hub genes for pancreatic cancer. Their mRNA and protein expression levels were validated through reverse transcription PCR (RT-PCR) and immunohistochemical (IHC). Diagnostic models were developed by eight machine learning algorithms and ten-fold cross-validation. Four hub genes (TSPAN1, TMPRSS4, SDR16C5, and CTSE) were identified based on bioinformatics. RT-PCR showed that the four hub genes were expressed at medium to high levels, IHC revealed that their protein expression levels were higher in pancreatic cancer tissues. For the panel of these four genes, eight models performed with 0.87-0.92 area under the curve value (AUC), 0.91-0.94 sensitivity, and 0.84-0.86 specificity in the validation cohort. In the external validation set, these models also showed good performance (0.86-0.98 AUC, 0.84-1.00 sensitivity, and 0.86-1.00 specificity). In conclusion, this study has identified four hub genes that might be closely related to pancreatic cancer: TSPAN1, TMPRSS4, SDR16C5, and CTSE. Four-gene panels might provide a theoretical basis for the diagnosis of pancreatic cancer.

The role of estrogen receptor beta in breast cancer

Breast cancer, a malignant tumor originating from mammary epithelial tissue, is the most common cancer among women worldwide. Challenges facing the diagnosis and treatment of breast cancer necessitate the search for new mechanisms and drugs to improve outcomes. Estrogen receptor (ER) is considered to be important for determining the diagnosis and treatment strategy. The discovery of the second estrogen receptor, ERβ, provides an opportunity to understand estrogen action. The emergence of ERβ can be traced back to 1996. Over the past 20 years, an increasing body of evidence has implicated the vital effect of ERβ in breast cancer. Although there is controversy among scholars, ERβ is generally thought to have antiproliferative effects in disease progression. This review summarizes available evidence regarding the involvement of ERβ in the clinical treatment and prognosis of breast cancer and describes signaling pathways associated with ERβ. We hope to highlight the potential of ERβ as a therapeutic target.

Mice lacking the epidermal retinol dehydrogenases SDR16C5 and SDR16C6 display accelerated hair growth and enlarged meibomian glands

Retinol dehydrogenases catalyze the rate-limiting step in the biosynthesis of retinoic acid, a bioactive lipid molecule that regulates the expression of hundreds of genes by binding to nuclear transcription factors, the retinoic acid receptors. Several enzymes exhibit retinol dehydrogenase activities in vitro; however, their physiological relevance for retinoic acid biosynthesis in vivo remains unclear. Here, we present evidence that two murine epidermal retinol dehydrogenases, short-chain dehydrogenase/reductase family 16C member 5 (SDR16C5) and SDR16C6, contribute to retinoic acid biosynthesis in living cells and are also essential for the oxidation of retinol to retinaldehyde in vivo Mice with targeted knockout of the more catalytically active SDR16C6 enzyme have no obvious phenotype, possibly due to functional redundancy, because Sdr16c5 and Sdr16c6 exhibit an overlapping expression pattern during later developmental stages and in adulthood. Mice that lack both enzymes are viable and fertile but display accelerated hair growth after shaving and also enlarged meibomian glands, consistent with a nearly 80% reduction in the retinol dehydrogenase activities of skin membrane fractions from the Sdr16c5/Sdr16c6 double-knockout mice. The up-regulation of hair-follicle stem cell genes is consistent with reduced retinoic acid signaling in the skin of the double-knockout mice. These results indicate that the retinol dehydrogenase activities of murine SDR16C5 and SDR16C6 enzymes are not critical for survival but are responsible for most of the retinol dehydrogenase activity in skin, essential for the regulation of the hair-follicle cycle, and required for the maintenance of both sebaceous and meibomian glands.