A Molecular Characterization of the Allelic Expression of the BRCA1 Founder Δ9-12 Pathogenic Variant and Its Potential Clinical Relevance in Hereditary Cancer.

Hereditary breast and ovarian cancer (HBOC) syndrome is a genetic condition that increases the risk of breast cancer by 80% and that of ovarian cancer by 40%. The most common pathogenic variants (PVs) causing HBOC occur in the BRCA1 gene, with more than 3850 reported mutations in the gene sequence. The prevalence of specific PVs in BRCA1 has increased across populations due to the effect of founder mutations. Therefore, when a founder mutation is identified, it becomes key to improving cancer risk characterization and effective screening protocols. The only founder mutation described in the Mexican population is the deletion of exons 9 to 12 of BRCA1 (BRCA1Δ9-12), and its description focuses on the gene sequence, but no transcription profiles have been generated for individuals who carry this gene. In this study, we describe the transcription profiles of cancer patients and healthy individuals who were heterozygous for PV BRCA1Δ9-12 by analyzing the differential expression of both alleles compared with the homozygous BRCA1 control group using RT-qPCR, and we describe the isoforms produced by the BRCA1 wild-type and BRCA1Δ9-12 alleles using nanopore long-sequencing. Using the Kruskal-Wallis test, our results showed a similar transcript expression of the wild-type allele between the healthy heterozygous group and the homozygous BRCA1 control group. An association between the recurrence and increased expression of both alleles in HBOC patients was also observed. An analysis of the sequences indicated four wild-type isoforms with diagnostic potential for discerning individuals who carry the PV BRCA1Δ9-12 and identifying which of them has developed cancer.

Underlying Mechanisms of the Protective Effects of Lifestyle Factors in the Prevention of Age-Related Diseases.

The rise in life expectancy has significantly increased the occurrence of age-related chronic diseases, leading to escalating expenses for both society and individuals. Among the main factors influencing health and lifespan, lifestyle takes a forefront position. Specifically, nutrition, mental activity, and physical exercise influence the molecular and functional mechanisms that contribute to the prevention of major age-related diseases. Gaining deeper insights into the mechanisms that drive the positive effects of healthy lifestyles is valuable for creating interventions to prevent or postpone the development of chronic degenerative diseases. This review summarizes the main mechanisms that underlie the positive effect of lifestyle factors in counteracting the major age-related diseases involving brain health, musculoskeletal function, cancer, frailty, and cardiovascular diseases, among others. This knowledge will help to identify high-risk populations for targeted intervention trials and discover new biomarkers associated with healthy aging.

Association of SLC12A1 and GLUR4 Ion Transporters with Neoadjuvant Chemoresistance in Luminal Locally Advanced Breast Cancer.

Chemoresistance to standard neoadjuvant treatment commonly occurs in locally advanced breast cancer, particularly in the luminal subtype, which is hormone receptor-positive and represents the most common subtype of breast cancer associated with the worst outcomes. Identifying the genes associated with chemoresistance is crucial for understanding the underlying mechanisms and discovering effective treatments. In this study, we aimed to identify genes linked to neoadjuvant chemotherapy resistance in 62 retrospectively included patients with luminal breast cancer. Whole RNA sequencing of 12 patient biopsies revealed 269 differentially expressed genes in chemoresistant patients. We further validated eight highly correlated genes associated with resistance. Among these, solute carrier family 12 member 1 (SLC12A1) and glutamate ionotropic AMPA type subunit 4 (GRIA4), both implicated in ion transport, showed the strongest association with chemoresistance. Notably, SLC12A1 expression was downregulated, while protein levels of glutamate receptor 4 (GLUR4), encoded by GRIA4, were elevated in patients with a worse prognosis. Our results suggest a potential link between SLC12A1 gene expression and GLUR4 protein levels with chemoresistance in luminal breast cancer. In particular, GLUR4 protein could serve as a potential target for drug intervention to overcome chemoresistance.

Genomic Profile in a Non-Seminoma Testicular Germ-Cell Tumor Cohort Reveals a Potential Biomarker of Sensitivity to Platinum-Based Therapy.

Despite having a favorable response to platinum-based chemotherapies, ~15% of Testicular Germ-Cell Tumor (TGCT) patients are platinum-resistant. Mortality rates among Latin American countries have remained constant over time, which makes the study of this population of particular interest. To gain insight into this phenomenon, we conducted whole-exome sequencing, microarray-based comparative genomic hybridization, and copy number analysis of 32 tumors from a Mexican cohort, of which 18 were platinum-sensitive and 14 were platinum-resistant. We incorporated analyses of mutational burden, driver mutations, and SNV and CNV signatures. DNA breakpoints in genes were also investigated and might represent an interesting research opportunity. We observed that sensitivity to chemotherapy does not seem to be explained by any of the mutations detected. Instead, we uncovered CNVs, particularly amplifications on segment 2q11.1 as a novel variant with chemosensitivity biomarker potential. Our data shed light into understanding platinum resistance in a Latin-origin population.

Proteasome inhibition alters mitotic progression through the upregulation of centromeric α-Satellite RNAs.

Cell cycle progression requires control of the abundance of several proteins and RNAs over space and time to properly transit from one phase to the next and to ensure faithful genomic inheritance in daughter cells. The proteasome, the main protein degradation system of the cell, facilitates the establishment of a proteome specific to each phase of the cell cycle. Its activity also strongly influences transcription. Here, we detected the upregulation of repetitive RNAs upon proteasome inhibition in human cancer cells using RNA-seq. The effect of proteasome inhibition on centromeres was remarkable, especially on α-Satellite RNAs. We showed that α-Satellite RNAs fluctuate along the cell cycle and interact with members of the cohesin ring, suggesting that these transcripts may take part in the regulation of mitotic progression. Next, we forced exogenous overexpression and used gapmer oligonucleotide targeting to demonstrate that α-Sat RNAs have regulatory roles in mitosis. Finally, we explored the transcriptional regulation of α-Satellite DNA. Through in silico analyses, we detected the presence of CCAAT transcription factor-binding motifs within α-Satellite centromeric arrays. Using high-resolution three-dimensional immuno-FISH and ChIP-qPCR, we showed an association between the α-Satellite upregulation and the recruitment of the transcription factor NFY-A to the centromere upon MG132-induced proteasome inhibition. Together, our results show that the proteasome controls α-Satellite RNAs associated with the regulation of mitosis.

Transcriptome Analysis Identifies GATA3-AS1 as a Long Noncoding RNA Associated with Resistance to Neoadjuvant Chemotherapy in Locally Advanced Breast Cancer Patients.

Breast cancer is one of the leading causes of mortality in women worldwide, and neoadjuvant chemotherapy has emerged as an option for the management of locally advanced breast cancer. Extensive efforts have been made to identify new molecular markers to predict the response to neoadjuvant chemotherapy. Transcripts that do not encode proteins, termed long noncoding RNAs (lncRNAs), have been shown to display abnormal expression profiles in different types of cancer, but their role as biomarkers in response to neoadjuvant chemotherapy has not been extensively studied. Herein, lncRNA expression was profiled using RNA sequencing in biopsies from patients who subsequently showed either response or no response to treatment. GATA3-AS1 was overexpressed in the nonresponder group and was the most stable feature when performing selection in multiple random forest models. GATA3-AS1 was experimentally validated by quantitative RT-PCR in an extended group of 68 patients. Expression analysis confirmed that GATA3-AS1 is overexpressed primarily in patients who were nonresponsive to neoadjuvant chemotherapy, with a sensitivity of 92.9% and a specificity of 75.0%. The statistical model was based on luminal B-like patients and adjusted by menopausal status and phenotype (odds ratio, 37.49; 95% CI, 6.74-208.42; P = 0.001); GATA3-AS1 was established as an independent predictor of response. Thus, lncRNA GATA3-AS1 is proposed as a potential predictive biomarker of nonresponse to neoadjuvant chemotherapy.

Magnetically-stimulated transformations in nanostructure of lipid mesophases: Effect of structure of iron oxide nanoparticles.

Nanostructured lipid-based liquid crystalline (LLC) systems can display different drug release rates and also be stimuli-responsive, rendering them the potential to serve as 'on-demand' drug delivery systems. In this study, a magnetically-responsive cubic phase nanocomposite was engineered by doping iron oxide nanoparticles (IONPs) into a phytantriol (PHYT)-based lipid that exhibits transformation in nanostructure under external alternating magnetic field (AMF). The effects of IONP surface hydrophilicity/hydrophobicity, size and concentration were determined in dispersed systems, and the effect of hydration state of the system was also assessed. Time-resolved small angle X-ray scattering (SAXS) was used to probe the impact of these variables on the transformation of nanostructure with and without the application of AMF. The inclusion of both hydrophobic and hydrophilic IONPs reduced the temperature of the phase transition from the inverted bicontinuous cubic (V2) phase to inverted hexagonal (H2) phase and imparted magnetic-responsiveness to the systems. The size of the IONPs played an important role in governing the phase reversibility of the dispersed systems, while the concentration of the IONPs had more impact on the phase behaviour of the bulk systems. These successfully demonstrated a completely reversible magneto-responsive phase transition in the nanostructured LLC systems through optimising the selection of IONPs.

De Novo Pathway-Based Classification of Breast Cancer Subtypes.

Breast cancer is a heterogeneous disease for which various clinically relevant subtypes have been reported. These subtypes are characterized by molecular differences which direct treatment selection. The state of the art for breast cancer subtyping utilizes histochemistry or gene expression to measure a few selected markers. However, classification based on molecular pathways (rather than individual markers) is a more robust way to classify breast cancer samples into known subtypes.Here, we present PathClass, a web application that allows its users to predict breast cancer subtypes using various traditional as well as advanced methods. This includes methods based on classical gene expression panels as well as de novo pathway-based predictors. Users can predict labels for datasets in the Gene Expression Omnibus or upload their own expression profiling data.Availability: https://pathclass.compbio.sdu.dk/ .

A functional genetic screen identifies the Mediator complex as essential for SSX2-induced senescence.

The senescence response to oncogenes is believed to be a barrier to oncogenic transformation in premalignant lesions, and describing the mechanisms by which tumor cells evade this response is important for early diagnosis and treatment. The male germ cell-associated protein SSX2 is ectopically expressed in many types of cancer and is functionally involved in regulating chromatin structure and supporting cell proliferation. Similar to many well-characterized oncogenes, SSX2 has the ability to induce senescence in cells. In this study, we performed a functional genetic screen to identify proteins implicated in SSX2-induced senescence and identified several subunits of the Mediator complex, which is central in regulating RNA polymerase-mediated transcription. Further experiments showed that reduced levels of MED1, MED4, and MED14 perturbed the development of senescence in SSX2-expressing cells. In contrast, knockdown of MED1 did not prevent development of B-Raf- and Epirubicin-induced senescence, suggesting that Mediator may be specifically linked to the cellular functions of SSX2 that may lead to development of senescence or be central in a SSX2-specific senescence response. Indeed, immunostaining of melanoma tumors, which often express SSX proteins, exhibited altered levels of MED1 compared to benign nevi. Similarly, RNA-seq analysis suggested that MED1, MED4, and MED14 were downregulated in some tumors, while upregulated in others. In conclusion, our study reveals the Mediator complex as essential for SSX2-induced senescence and suggests that changes in Mediator activity could be instrumental for tumorigenesis.

The epigenetic factor BORIS (CTCFL) controls the androgen receptor regulatory network in ovarian cancer.

The identification of prognostic biomarkers is a priority for patients suffering from high-grade serous ovarian cancer (SOC), which accounts for >70% of ovarian cancer (OC) deaths. Meanwhile, borderline ovarian cancer (BOC) is a low malignancy tumor and usually patients undergo surgery with low probabilities of recurrence. However, SOC remains the most lethal neoplasm due to the lack of biomarkers for early diagnosis and prognosis. In this regard, BORIS (CTCFL), a CTCF paralog, is a promising cancer biomarker that is overexpressed and controls transcription in several cancer types, mainly in OC. Studies suggest that BORIS has an important function in OC by altering gene expression, but the effect and extent to which BORIS influences transcription in OC from a genome-wide perspective is unclear. Here, we sought to identify BORIS target genes in an OC cell line (OVCAR3) with potential biomarker use in OC tumor samples. To achieve this, we performed in vitro knockout and knockdown experiments of BORIS in OVCAR3 cell line followed by expression microarrays and bioinformatics network enrichment analysis to identify relevant BORIS target genes. In addition, ex vivo expression data analysis of 373 ovarian cancer patients were evaluated to identify the expression patterns of BORIS target genes. In vitro, we uncovered 130 differentially expressed genes and obtained the BORIS-associated regulatory network, in which the androgen receptor (AR) acts as a major transcription factor. Also, FN1, FAM129A, and CD97 genes, which are related to chemoresistance and metastases in OC, were identified. In SOC patients, we observed that malignancy is associated with high levels of BORIS expression while BOC patients show lower levels. Our study suggests that BORIS acts as a main regulator, and has the potential to be used as a prognostic biomarker and to yield novel drug targets among the genes BORIS controls in SOC patients.

Orthologous proteins of experimental de- and remyelination are differentially regulated in the CSF proteome of multiple sclerosis subtypes.

OBJECTIVE: Here, we applied a multi-omics approach (i) to examine molecular pathways related to de- and remyelination in multiple sclerosis (MS) lesions; and (ii) to translate these findings to the CSF proteome in order to identify molecules that are differentially expressed among MS subtypes. METHODS: To relate differentially expressed genes in MS lesions to de- and remyelination, we compared transcriptome of MS lesions to transcriptome of cuprizone (CPZ)-induced de- and remyelination. Protein products of the overlapping orthologous genes were measured within the CSF by quantitative proteomics, parallel reaction monitoring (PRM). Differentially regulated proteins were correlated with molecular markers of inflammation by using MesoScale multiplex immunoassay. Expression kinetics of differentially regulated orthologous genes and proteins were examined in the CPZ model. RESULTS: In the demyelinated and remyelinated corpus callosum, we detected 1239 differentially expressed genes; 91 orthologues were also differentially expressed in MS lesions. Pathway analysis of these orthologues suggested that the TYROBP (DAP12)-TREM2 pathway, TNF-receptor 1, CYBA and the proteasome subunit PSMB9 were related to de- and remyelination. We designed 129 peptides representing 51 orthologous proteins, measured them by PRM in 97 individual CSF, and compared their levels between relapsing (n = 40) and progressive MS (n = 57). Four proteins were differentially regulated among relapsing and progressive MS: tyrosine protein kinase receptor UFO (UFO), TIMP-1, apolipoprotein C-II (APOC2), and beta-2-microglobulin (B2M). The orthologous genes/proteins in the mouse brain peaked during acute remyelination. UFO, TIMP-1 and B2M levels correlated inversely with inflammation in the CSF (IL-6, MCP-1/CCL2, TARC/CCL17). APOC2 showed positive correlation with IL-2, IL-16 and eotaxin-3/CCL26. CONCLUSIONS: Pathology-based multi-omics identified four CSF markers that were differentially expressed in MS subtypes. Upregulated TIMP-1, UFO and B2M orthologues in relapsing MS were associated with reduced inflammation and reflected reparatory processes, in contrast to the upregulated orthologue APOC2 in progressive MS that reflected changes in lipid metabolism associated with increased inflammation.

CTCF-KDM4A complex correlates with histone modifications that negatively regulate CHD5 gene expression in cancer cell lines.

Histone demethylase KDM4A is involved in H3K9me3 and H3K36me3 demethylation, which are epigenetic modifications associated with gene silencing and RNA Polymerase II elongation, respectively. KDM4A is abnormally expressed in cancer, affecting the expression of multiple targets, such as the CHD5 gene. This enzyme localizes at the first intron of CHD5, and the dissociation of KDM4A increases gene expression. In vitro assays showed that KDM4A-mediated demethylation is enhanced in the presence of CTCF, suggesting that CTCF could increase its enzymatic activity in vivo, however the specific mechanism by which CTCF and KDM4A might be involved in the CHD5 gene repression is poorly understood. Here, we show that CTCF and KDM4A form a protein complex, which is recruited into the first intron of CHD5. This is related to a decrease in H3K36me3/2 histone marks and is associated with its transcriptional downregulation. Depletion of CTCF or KDM4A by siRNA, triggered the reactivation of CHD5 expression, suggesting that both proteins are involved in the negative regulation of this gene. Furthermore, the knockout of KDM4A restored the CHD5 expression and H3K36me3 and H3K36me2 histone marks. Such mechanism acts independently of CHD5 promoter DNA methylation. Our findings support a novel mechanism of epigenetic repression at the gene body that does not involve promoter silencing.

De novo pathway-based biomarker identification.

Gene expression profiles have been extensively discussed as an aid to guide the therapy by predicting disease outcome for the patients suffering from complex diseases, such as cancer. However, prediction models built upon single-gene (SG) features show poor stability and performance on independent datasets. Attempts to mitigate these drawbacks have led to the development of network-based approaches that integrate pathway information to produce meta-gene (MG) features. Also, MG approaches have only dealt with the two-class problem of good versus poor outcome prediction. Stratifying patients based on their molecular subtypes can provide a detailed view of the disease and lead to more personalized therapies. We propose and discuss a novel MG approach based on de novo pathways, which for the first time have been used as features in a multi-class setting to predict cancer subtypes. Comprehensive evaluation in a large cohort of breast cancer samples from The Cancer Genome Atlas (TCGA) revealed that MGs are considerably more stable than SG models, while also providing valuable insight into the cancer hallmarks that drive them. In addition, when tested on an independent benchmark non-TCGA dataset, MG features consistently outperformed SG models. We provide an easy-to-use web service at http://pathclass.compbio.sdu.dk where users can upload their own gene expression datasets from breast cancer studies and obtain the subtype predictions from all the classifiers.

Elucidation of Altered Pathways in Tumor-Initiating Cells of Triple-Negative Breast Cancer: A Useful Cell Model System for Drug Screening.

A limited number of cancer cells within a tumor are thought to have self-renewing and tumor-initiating capabilities that produce the remaining cancer cells in a heterogeneous tumor mass. Elucidation of central pathways preferentially used by tumor-initiating cells/cancer stem cells (CSCs) may allow their exploitation as potential cancer therapy targets. We used single cell cloning to isolate and characterize four isogenic cell clones from a triple-negative breast cancer cell line; two exhibited mesenchymal-like and two epithelial-like characteristics. Within these pairs, one, but not the other, resulted in tumors in immunodeficient NOD/Shi-scid/IL-2 Rγ null mice and efficiently formed mammospheres. Quantitative proteomics and phosphoproteomics were used to map signaling pathways associated with the tumor-initiating ability. Signaling associated with apoptosis was suppressed in tumor-initiating versus nontumorigenic counterparts with pro-apoptotic proteins, such as Bcl2-associated agonist of cell death (BAD), FAS-associated death domain protein (FADD), and myeloid differentiation primary response protein (MYD88), downregulated in tumor-initiating epithelial-like cells. Functional studies confirmed significantly lower apoptosis in tumor-initiating versus nontumorigenic cells. Moreover, central pathways, including ß-catenin and nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB)-related signaling, exhibited increased activation in the tumor-initiating cells. To evaluate the CSC model as a tool for drug screening, we assessed the effect of separately blocking NF-κB and Wnt/ß-catenin signaling and found markedly reduced mammosphere formation, particularly for tumor-initiating cells. Similar reduction was also observed using patient-derived primary cancer cells. Furthermore, blocking NF-κB signaling in mice transplanted with tumor-initiating cells significantly reduced tumor outgrowth. Our study demonstrates that suppressed apoptosis, activation of pathways associated with cell viability, and CSCs are the major differences between tumor-initiating and nontumorigenic cells independent of their epithelial-like/mesenchymal-like phenotype. These altered pathways may provide targets for future drug development to eliminate CSCs, and the cell model may be a useful tool in such drug screenings. Stem Cells 2017;35:1898-1912.

Elucidation of epithelial-mesenchymal transition-related pathways in a triple-negative breast cancer cell line model by multi-omics interactome analysis.

In life sciences, and particularly biomedical research, linking aberrant pathways exhibiting phenotype-specific alterations to the underlying physical condition or disease is an ongoing challenge. Computationally, a key approach for pathway identification is data enrichment, combined with generation of biological networks. This allows identification of intrinsic patterns in the data and their linkage to a specific context such as cellular compartments, diseases or functions. Identification of aberrant pathways by traditional approaches is often limited to biological networks based on either gene expression, protein expression or post-translational modifications. To overcome single omics analysis, we developed a set of computational methods that allow a combined analysis of data collections from multiple omics fields utilizing hybrid interactome networks. We apply these methods to data obtained from a triple-negative breast cancer cell line model, combining data sets of gene and protein expression as well as protein phosphorylation. We focus on alterations associated with the phenotypical differences arising from epithelial-mesenchymal transition in two breast cancer cell lines exhibiting epithelial-like and mesenchymal-like morphology, respectively. Here we identified altered protein signaling activity in a complex biologically relevant network, related to focal adhesion and migration of breast cancer cells. We found dysregulated functional network modules revealing altered phosphorylation-dependent activity in concordance with the phenotypic traits and migrating potential of the tested model. In addition, we identified Ser267 on zyxin, a protein coupled to actin filament polymerization, as a potential in vivo phosphorylation target of cyclin-dependent kinase 1.

Efficient key pathway mining: combining networks and OMICS data.

Systems biology has emerged over the last decade. Driven by the advances in sophisticated measurement technology the research community generated huge molecular biology data sets. These comprise rather static data on the interplay of biological entities, for instance protein-protein interaction network data, as well as quite dynamic data collected for studying the behavior of individual cells or tissues in accordance with changing environmental conditions, such as DNA microarrays or RNA sequencing. Here we bring the two different data types together in order to gain higher level knowledge. We introduce a significantly improved version of the KeyPathwayMiner software framework. Given a biological network modelled as a graph and a set of expression studies, KeyPathwayMiner efficiently finds and visualizes connected sub-networks where most components are expressed in most cases. It finds all maximal connected sub-networks where all nodes but k exceptions are expressed in all experimental studies but at most l exceptions. We demonstrate the power of the new approach by comparing it to similar approaches with gene expression data previously used to study Huntington's disease. In addition, we demonstrate KeyPathwayMiner's flexibility and applicability to non-array data by analyzing genome-scale DNA methylation profiles from colorectal tumor cancer patients. KeyPathwayMiner release 2 is available as a Cytoscape plugin and online at http://keypathwayminer.mpi-inf.mpg.de.