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Heart failure (HF) describes a heterogenous complex spectrum of pathological conditions that results in structural and functional remodeling leading to subsequent impairment of cardiac function, including either systolic dysfunction, diastolic dysfunction, or both. Several factors chronically lead to HF, including cardiac volume and pressure overload that may result from hypertension, valvular lesions, acute, or chronic ischemic injuries. Major forms of HF include hypertrophic, dilated, and restrictive cardiomyopathy. The severity of cardiomyopathy can be impacted by other comorbidities such as diabetes or obesity and external stress factors. Age is another major contributor, and the number of patients with HF is rising worldwide in part due to an increase in the aged population. HF can occur with reduced ejection fraction (HF with reduced ejection fraction), that is, the overall cardiac function is compromised, and typically the left ventricular ejection fraction is lower than 40%. In some cases of HF, the ejection fraction is preserved (HF with preserved ejection fraction). Animal models play a critical role in facilitating the understanding of molecular mechanisms of how hearts fail. This review aims to summarize and describe the strengths, limitations, and outcomes of both small and large animal models of HF with reduced ejection fraction that are currently used in basic and translational research. The driving defect is a failure of the heart to adequately supply the tissues with blood due to impaired filling or pumping. An accurate model of HF with reduced ejection fraction would encompass the symptoms (fatigue, dyspnea, exercise intolerance, and edema) along with the pathology (collagen fibrosis, ventricular hypertrophy) and ultimately exhibit a decrease in cardiac output. Although countless experimental studies have been published, no model completely recapitulates the full human disease. Therefore, it is critical to evaluate the strength and weakness of each animal model to allow better selection of what animal models to use to address the scientific question proposed.
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Cardiomiopatias , Insuficiência Cardíaca , Disfunção Ventricular Esquerda , Idoso , Animais , Humanos , Modelos Animais , Volume Sistólico , Função Ventricular EsquerdaRESUMO
CMV infection is a significant complication after solid organ transplantation. We used single cell TCR αß sequencing to determine how memory inflation impacts clonality and diversity of the CMV-responsive CD8 and CD4 T cell repertoire in the first year after transplantation in human subjects. We observed CD8 T cell inflation but no changes in clonal diversity, indicating homeostatic stability in clones. In contrast, the CD4 repertoire was diverse and stable over time, with no evidence of CMV-responsive CD4 T cell expansion. We identified shared CDR3 TCR motifs among patients but no public CMV-specific TCRs. Temporal changes in clonality in response to transplantation and in the absence of detectable viral reactivation suggest changes in the repertoire immediately after transplantation followed by an expansion with stable clonal competition that may mediate protection.
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Linfócitos T CD4-Positivos/imunologia , Linfócitos T CD8-Positivos/imunologia , Infecções por Citomegalovirus/imunologia , Citomegalovirus/fisiologia , Rejeição de Enxerto/imunologia , Transplante de Coração , Transplante de Rim , Adulto , Idoso , Antígenos Virais/imunologia , Proliferação de Células , Células Clonais , Feminino , Variação Genética , Humanos , Memória Imunológica , Masculino , Pessoa de Meia-Idade , Receptores de Antígenos de Linfócitos T alfa-beta/genética , Transplante Homólogo , Ativação Viral/imunologiaRESUMO
The mammalian heart undergoes complex structural and functional remodeling to compensate for stresses such as pressure overload. While studies suggest that, at best, the adult mammalian heart is capable of very limited regeneration arising from the proliferation of existing cardiomyocytes, how myocardial stress affects endogenous cardiac regeneration or repair is unknown. To define the relationship between left ventricular afterload and cardiac repair, we induced left ventricle pressure overload in adult mice by constriction of the ascending aorta (AAC). One week following AAC, we normalized ventricular afterload in a subset of animals through removal of the aortic constriction (de-AAC). Subsequent monitoring of cardiomyocyte cell cycle activity via thymidine analog labeling revealed that an acute increase in ventricular afterload induced cardiomyocyte proliferation. Intriguingly, a release in ventricular overload (de-AAC) further increases cardiomyocyte proliferation. Following both AAC and de-AAC, thymidine analog-positive cardiomyocytes exhibited characteristics of newly generated cardiomyocytes, including single diploid nuclei and reduced cell size as compared to age-matched, sham-operated adult mouse myocytes. Notably, those smaller cardiomyocytes frequently resided alongside one another, consistent with local stimulation of cellular proliferation. Collectively, our data demonstrate that adult cardiomyocyte proliferation can be locally stimulated by an acute increase or decrease of ventricular pressure, and this mode of stimulation can be harnessed to promote cardiac repair.
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Ventrículos do Coração/metabolismo , Ventrículos do Coração/patologia , Pressão Ventricular , Remodelação Ventricular , Animais , Biomarcadores , Cardiomegalia/etiologia , Cardiomegalia/metabolismo , Cardiomegalia/patologia , Cardiomegalia/fisiopatologia , Proliferação de Células , Modelos Animais de Doenças , Ecocardiografia , Imunofluorescência , Expressão Gênica , Hipertrofia Ventricular Esquerda/etiologia , Hipertrofia Ventricular Esquerda/metabolismo , Hipertrofia Ventricular Esquerda/patologia , Camundongos , Miócitos Cardíacos/metabolismo , Miócitos Cardíacos/patologia , Estresse OxidativoRESUMO
BACKGROUND: Hospitalizations account for almost one-third of the US $4.1 trillion health care cost in the United States. A substantial portion of these hospitalizations are attributed to readmissions, which led to the establishment of the Hospital Readmissions Reduction Program (HRRP) in 2012. The HRRP reduces payments to hospitals with excess readmissions. In 2018, >US $700 million was withheld; this is expected to exceed US $1 billion by 2022. More importantly, there is nothing more physically and emotionally taxing for readmitted patients and demoralizing for hospital physicians, nurses, and administrators. Given this high uncertainty of proper home recovery, intelligent monitoring is needed to predict the outcome of discharged patients to reduce readmissions. Physical activity (PA) is one of the major determinants for overall clinical outcomes in diabetes, hypertension, hyperlipidemia, heart failure, cancer, and mental health issues. These are the exact comorbidities that increase readmission rates, underlining the importance of PA in assessing the recovery of patients by quantitative measurement beyond the questionnaire and survey methods. OBJECTIVE: This study aims to develop a remote, low-cost, and cloud-based machine learning (ML) platform to enable the precision health monitoring of PA, which may fundamentally alter the delivery of home health care. To validate this technology, we conducted a clinical trial to test the ability of our platform to predict clinical outcomes in discharged patients. METHODS: Our platform consists of a wearable device, which includes an accelerometer and a Bluetooth sensor, and an iPhone connected to our cloud-based ML interface to analyze PA remotely and predict clinical outcomes. This system was deployed at a skilled nursing facility where we collected >17,000 person-day data points over 2 years, generating a solid training database. We used these data to train our extreme gradient boosting (XGBoost)-based ML environment to conduct a clinical trial, Activity Assessment of Patients Discharged from Hospital-I, to test the hypothesis that a comprehensive profile of PA would predict clinical outcome. We developed an advanced data-driven analytic platform that predicts the clinical outcome based on accurate measurements of PA. Artificial intelligence or an ML algorithm was used to analyze the data to predict short-term health outcome. RESULTS: We enrolled 52 patients discharged from Stanford Hospital. Our data demonstrated a robust predictive system to forecast health outcome in the enrolled patients based on their PA data. We achieved precise prediction of the patients' clinical outcomes with a sensitivity of 87%, a specificity of 79%, and an accuracy of 85%. CONCLUSIONS: To date, there are no reliable clinical data, using a wearable device, regarding monitoring discharged patients to predict their recovery. We conducted a clinical trial to assess outcome data rigorously to be used reliably for remote home care by patients, health care professionals, and caretakers.
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The JAK2 V617F somatic variant is a well-known driver of myeloproliferative neoplasms (MPN) associated with an increased risk for athero-thrombotic cardiovascular disease. Recent studies have demonstrated its role in the development of thoracic aortic aneurysm (TAA). However, limited clinical information and level of JAK2 V617F burden have been provided for a comprehensive evaluation of potential confounders. A retrospective genotype-first study was conducted to identify carriers of the JAK2 V617F variant from an internal exome sequencing database in Yale DNA Diagnostics Lab. Additionally, the overall incidence of somatic variants in the JAK2 gene across various tissue types in the healthy population was carried out based on reanalysis of SomaMutDB and data from the UK Biobank (UKBB) cohort to compare our dataset to the population prevalence of the variant. In our database of 12,439 exomes, 594 (4.8%) were found to have a thoracic aortic aneurysm (TAA), and 12 (0.049%) were found to have a JAK2 V617F variant. Among the 12 JAK2 V617F variant carriers, five had a TAA (42%), among whom four had an ascending TAA and one had a descending TAA, with a variant allele fraction ranging from 11.2% to 20%. Among these five patients, 60% were female, and average age at diagnosis was 70 (49-79). The mean ascending aneurysm size was 5.05 cm (range 4.6-5.5 cm), and four patients had undergone surgical aortic replacement or repair. UKBB data revealed a positive correlation between the JAK2 V617F somatic variant and aortic valve disease (effect size 0.0086, p = 0.85) and TAA (effect size = 0.004, p = 0.92), although not statistically significant. An unexpectedly high prevalence of TAA in our dataset (5/594, 0.84%) is greater than the prevalence reported before for the general population, supporting its association with TAA. JAK2 V617F may contribute a meaningful proportion of otherwise unexplained aneurysm patients. Additionally, it may imply a potential JAK2-specific disease mechanism in the developmental of TAA, which suggests a possible target of therapy that warrants further investigation.
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Aneurisma da Aorta Torácica , Janus Quinase 2 , Humanos , Janus Quinase 2/genética , Aneurisma da Aorta Torácica/genética , Aneurisma da Aorta Torácica/epidemiologia , Aneurisma da Aorta Torácica/patologia , Feminino , Masculino , Idoso , Pessoa de Meia-Idade , Estudos Retrospectivos , Sequenciamento do Exoma , MutaçãoRESUMO
Physiological variability in pancreatic cell type gene regulation and the impact on diabetes risk is poorly understood. In this study we mapped gene regulation in pancreatic cell types using single cell multiomic (joint RNA-seq and ATAC-seq) profiling in 28 non-diabetic donors in combination with single cell data from 35 non-diabetic donors in the Human Pancreas Analysis Program. We identified widespread associations with age, sex, BMI, and HbA1c, where gene regulatory responses were highly cell type- and phenotype-specific. In beta cells, donor age associated with hypoxia, apoptosis, unfolded protein response, and external signal-dependent transcriptional regulators, while HbA1c associated with inflammatory responses and gender with chromatin organization. We identified 10.8K loci where genetic variants were QTLs for cis regulatory element (cRE) accessibility, including 20% with lineage- or cell type-specific effects which disrupted distinct transcription factor motifs. Type 2 diabetes and glycemic trait associated variants were enriched in both phenotype- and QTL-associated beta cell cREs, whereas type 1 diabetes showed limited enrichment. Variants at 226 diabetes and glycemic trait loci were QTLs in beta and other cell types, including 40 that were statistically colocalized, and annotating target genes of colocalized QTLs revealed genes with putatively novel roles in disease. Our findings reveal diverse responses of pancreatic cell types to phenotype and genotype in physiology, and identify pathways, networks, and genes through which physiology impacts diabetes risk.
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Type 2 diabetes (T2D) and prediabetes are classically defined by the level of fasting glucose or surrogates such as hemoglobin HbA1c. This classification does not take into account the heterogeneity in the pathophysiology of glucose dysregulation, the identification of which could inform targeted approaches to diabetes treatment and prevention and/or predict clinical outcomes. We performed gold-standard metabolic tests in a cohort of individuals with early glucose dysregulation and quantified four distinct metabolic subphenotypes known to contribute to glucose dysregulation and T2D: muscle insulin resistance, ß-cell dysfunction, impaired incretin action, and hepatic insulin resistance. We revealed substantial inter-individual heterogeneity, with 34% of individuals exhibiting dominance or co-dominance in muscle and/or liver IR, and 40% exhibiting dominance or co-dominance in ß-cell and/or incretin deficiency. Further, with a frequently-sampled oral glucose tolerance test (OGTT), we developed a novel machine learning framework to predict metabolic subphenotypes using features from the dynamic patterns of the glucose time-series ("shape of the glucose curve"). The glucose time-series features identified insulin resistance, ß-cell deficiency, and incretin defect with auROCs of 95%, 89%, and 88%, respectively. These figures are superior to currently-used estimates. The prediction of muscle insulin resistance and ß-cell deficiency were validated using an independent cohort. We then tested the ability of glucose curves generated by a continuous glucose monitor (CGM) worn during at-home OGTTs to predict insulin resistance and ß-cell deficiency, yielding auROC of 88% and 84%, respectively. We thus demonstrate that the prediabetic state is characterized by metabolic heterogeneity, which can be defined by the shape of the glucose curve during standardized OGTT, performed in a clinical research unit or at-home setting using CGM. The use of at-home CGM to identify muscle insulin resistance and ß-cell deficiency constitutes a practical and scalable method by which to risk stratify individuals with early glucose dysregulation and inform targeted treatment to prevent T2D.
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The coding variant (p.Arg192His) in the transcription factor PAX4 is associated with an altered risk for type 2 diabetes (T2D) in East Asian populations. In mice, Pax4 is essential for beta cell formation but its role on human beta cell development and/or function is unknown. Participants carrying the PAX4 p.His192 allele exhibited decreased pancreatic beta cell function compared to homozygotes for the p.192Arg allele in a cross-sectional study in which we carried out an intravenous glucose tolerance test and an oral glucose tolerance test. In a pedigree of a patient with young onset diabetes, several members carry a newly identified p.Tyr186X allele. In the human beta cell model, EndoC-ßH1, PAX4 knockdown led to impaired insulin secretion, reduced total insulin content, and altered hormone gene expression. Deletion of PAX4 in human induced pluripotent stem cell (hiPSC)-derived islet-like cells resulted in derepression of alpha cell gene expression. In vitro differentiation of hiPSCs carrying PAX4 p.His192 and p.X186 risk alleles exhibited increased polyhormonal endocrine cell formation and reduced insulin content that can be reversed with gene correction. Together, we demonstrate the role of PAX4 in human endocrine cell development, beta cell function, and its contribution to T2D-risk.
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Diabetes Mellitus Tipo 2 , Células Secretoras de Glucagon , Células-Tronco Pluripotentes Induzidas , Células Secretoras de Insulina , Humanos , Camundongos , Animais , Proteínas de Homeodomínio/genética , Diabetes Mellitus Tipo 2/genética , Diabetes Mellitus Tipo 2/metabolismo , Estudos Transversais , Fatores de Transcrição Box Pareados/genética , Fatores de Transcrição Box Pareados/metabolismo , Células-Tronco Pluripotentes Induzidas/metabolismo , Insulina/metabolismo , Células Secretoras de Insulina/metabolismo , Células Secretoras de Glucagon/metabolismoRESUMO
BACKGROUND: Prognosis in pulmonary arterial hypertension (PAH) is closely related to indexes of right ventricular function. A better understanding of their relationship may provide important implications for risk stratification in PAH. RESEARCH QUESTION: Can clinical network graphs inform risk stratification in PAH? STUDY DESIGN AND METHODS: The study cohort consisted of 231 patients with PAH followed up for a median of 7.1 years. An undirected, correlation network was used to visualize the relationship between clinical features in PAH. This network was enriched for right heart parameters and included N-terminal pro-hormone B-type natriuretic peptide (NT-proBNP), comprehensive echocardiographic parameters, and hemodynamics, as well as 6-min walk distance (6MWD), vital signs, laboratory data, and diffusing capacity for carbon monoxide (Dlco). Connectivity was assessed by using eigenvector and betweenness centrality to reflect global and regional connectivity, respectively. Cox proportional hazards regression was used to model event-free survival for the combined end point of death or lung transplantation. RESULTS: A network of closely intertwined features centered around NT-proBNP with 6MWD emerging as a secondary hub were identified. Less connected nodes included Dlco, systolic BP, albumin, and sodium. Over the follow-up period, death or transplantation occurred in 92 patients (39.8%). A strong prognostic model was achieved with a Harrell's C-index of 0.81 (0.77-0.85) when combining central right heart features (NT-proBNP and right ventricular end-systolic remodeling index) with 6MWD and less connected nodes (Dlco, systolic BP, albumin, sodium, sex, connective tissue disease etiology, and prostanoid therapy). When added to the baseline risk model, serial change in NT-proBNP significantly improved outcome prediction at 5 years (increase in C-statistic of 0.071 ± 0.024; P = .003). INTERPRETATION: NT-proBNP emerged as a central hub in the intertwined PAH network. Connectivity analysis provides explainability for feature selection and combination in outcome models.
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Hipertensão Arterial Pulmonar , Albuminas , Biomarcadores , Hipertensão Pulmonar Primária Familiar , Humanos , Peptídeo Natriurético Encefálico , Fragmentos de Peptídeos , Prognóstico , Medição de Risco , Sódio , Remodelação VentricularRESUMO
OBJECTIVE: Identifying the transcripts which mediate genetic association signals for type 2 diabetes (T2D) is critical to understand disease mechanisms. Studies in pancreatic islets support the transcription factor ZMIZ1 as a transcript underlying a T2D GWAS signal, but how it influences T2D risk is unknown. METHODS: ß-Cell-specific Zmiz1 knockout (Zmiz1ßKO) mice were generated and phenotypically characterised. Glucose homeostasis was assessed in Zmiz1ßKO mice and their control littermates on chow diet (CD) and high fat diet (HFD). Islet morphology and function were examined by immunohistochemistry and in vitro islet function was assessed by dynamic insulin secretion assay. Transcript and protein expression were assessed by RNA sequencing and Western blotting. In islets isolated from genotyped human donors, we assessed glucose-dependent insulin secretion and islet insulin content by static incubation assay. RESULTS: Male and female Zmiz1ßKO mice were glucose intolerant with impaired insulin secretion, compared with control littermates. Transcriptomic profiling of Zmiz1ßKO islets identified over 500 differentially expressed genes including those involved in ß-cell function and maturity, which we confirmed at the protein level. Upon HFD, Zmiz1ßKO mice fail to expand ß-cell mass and become severely diabetic. Human islets from carriers of the ZMIZ1-linked T2D-risk alleles have reduced islet insulin content and glucose-stimulated insulin secretion. CONCLUSIONS: ß-Cell Zmiz1 is required for normal glucose homeostasis. Genetic variation at the ZMIZ1 locus may influence T2D-risk by reducing islet mass expansion upon metabolic stress and the ability to maintain a mature ß-cell state.
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Diabetes Mellitus Tipo 2 , Células Secretoras de Insulina , Fatores de Transcrição , Animais , Feminino , Humanos , Masculino , Camundongos , Diabetes Mellitus Tipo 2/genética , Diabetes Mellitus Tipo 2/metabolismo , Glucose/metabolismo , Insulina/metabolismo , Células Secretoras de Insulina/metabolismo , Fatores de Transcrição/metabolismo , Camundongos Knockout , Dieta HiperlipídicaRESUMO
The eye is highly susceptible to inflammation-mediated tissue damage evoked during bacterial infection. However, mechanisms regulating inflammation to protect the eye remain elusive. Here, we used integrated metabolomics and transcriptomics to show that the immunomodulatory metabolite itaconate and immune-responsive gene 1 (Irg1) are induced in bacterial (Staphylococcus aureus)-infected mouse eyes, bone-marrow-derived macrophages (BMDMs), and Müller glia. Itaconate levels are also elevated in the vitreous of patients with bacterial endophthalmitis. Irg1 deficiency in mice led to increased ocular pathology. Conversely, intraocular administration of itaconate protects both Irg1-/- and wild-type mice from bacterial endophthalmitis by reducing inflammation, bacterial burden, and preserving retinal architecture and visual function. Notably, itaconate exerts synergistic effects with antibiotics. The protective, anti-inflammatory effects of itaconate are mediated via activation of NRF2/HO-1 signaling and inhibition of NLRP3 inflammasome. Collectively, our study demonstrates the Irg1/itaconate axis is a regulator of intraocular inflammation and provides evidence for using itaconate, along with antibiotics, to treat bacterial infections.
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Inflamassomos/efeitos dos fármacos , Inflamação/tratamento farmacológico , Infecções Estafilocócicas/tratamento farmacológico , Succinatos/farmacologia , Transcriptoma/efeitos dos fármacos , Animais , Infecções Oculares Bacterianas/metabolismo , Inflamassomos/metabolismo , Inflamação/metabolismo , Macrófagos/efeitos dos fármacos , Metabolômica/métodos , Camundongos Endogâmicos C57BL , Camundongos Transgênicos , Fator 2 Relacionado a NF-E2/efeitos dos fármacos , Fator 2 Relacionado a NF-E2/genética , Transdução de Sinais/efeitos dos fármacos , Infecções Estafilocócicas/metabolismo , Staphylococcus aureus/genética , Transcriptoma/imunologiaRESUMO
Previously, we reported that Zika virus (ZIKV) causes ocular complications such as chorioretinal atrophy, by infecting cells lining the blood-retinal barrier, including the retinal pigment epithelium (RPE). To understand the molecular basis of ZIKV-induced retinal pathology, we performed a meta-analysis of transcriptome profiles of ZIKV-infected human primary RPE and other cell types infected with either ZIKV or other related flaviviruses (Japanese encephalitis, West Nile, and Dengue). This led to identification of a unique ZIKV infection signature comprising 43 genes (35 upregulated and 8 downregulated). The major biological processes perturbed include SH3/SH2 adaptor activity, lipid and ceramide metabolism, and embryonic organ development. Further, a comparative analysis of some differentially regulated genes (ABCG1, SH2B3, SIX4, and TNFSF13B) revealed that ZIKV induced their expression relatively more than dengue virus did in RPE. Importantly, the pharmacological inhibition of ABCG1, a membrane transporter of cholesterol, resulted in reduced ZIKV infectivity. Interestingly, the ZIKV infection signature revealed the downregulation of ALDH5A1 and CHML, genes implicated in neurological (cognitive impairment, expressive language deficit, and mild ataxia) and ophthalmic (choroideremia) disorders, respectively. Collectively, our study revealed that ZIKV induces differential gene expression in RPE cells, and the identified genes/pathways (e.g., ABCG1) could potentially contribute to ZIKV-associated ocular pathologies.
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Epitélio Pigmentado da Retina/metabolismo , Transcriptoma/genética , Infecção por Zika virus/genética , Zika virus/genética , Membro 1 da Subfamília G de Transportadores de Cassetes de Ligação de ATP/genética , Proteínas Adaptadoras de Transdução de Sinal , Fator Ativador de Células B/genética , Dengue/genética , Dengue/patologia , Dengue/virologia , Vírus da Dengue/patogenicidade , Vírus da Encefalite Japonesa (Subgrupo)/patogenicidade , Infecções por Flavivirus/genética , Infecções por Flavivirus/patologia , Infecções por Flavivirus/virologia , Regulação da Expressão Gênica/genética , Proteínas de Homeodomínio/genética , Humanos , Peptídeos e Proteínas de Sinalização Intracelular , Cultura Primária de Células , Proteínas/genética , Epitélio Pigmentado da Retina/patologia , Epitélio Pigmentado da Retina/virologia , Transativadores/genética , Replicação Viral/genética , Febre do Nilo Ocidental/genética , Febre do Nilo Ocidental/patologia , Febre do Nilo Ocidental/virologia , Vírus do Nilo Ocidental/patogenicidade , Zika virus/patogenicidade , Infecção por Zika virus/patologia , Infecção por Zika virus/virologiaRESUMO
BACKGROUND: Next Generation Sequencing (NGS) is playing a key role in therapeutic decision making for the cancer prognosis and treatment. The NGS technologies are producing a massive amount of sequencing datasets. Often, these datasets are published from the isolated and different sequencing facilities. Consequently, the process of sharing and aggregating multisite sequencing datasets are thwarted by issues such as the need to discover relevant data from different sources, built scalable repositories, the automation of data linkage, the volume of the data, efficient querying mechanism, and information rich intuitive visualisation. RESULTS: We present an approach to link and query different sequencing datasets (TCGA, COSMIC, REACTOME, KEGG and GO) to indicate risks for four cancer types - Ovarian Serous Cystadenocarcinoma (OV), Uterine Corpus Endometrial Carcinoma (UCEC), Uterine Carcinosarcoma (UCS), Cervical Squamous Cell Carcinoma and Endocervical Adenocarcinoma (CESC) - covering the 16 healthy tissue-specific genes from Illumina Human Body Map 2.0. The differentially expressed genes from Illumina Human Body Map 2.0 are analysed together with the gene expressions reported in COSMIC and TCGA repositories leading to the discover of potential biomarkers for a tissue-specific cancer. CONCLUSION: We analyse the tissue expression of genes, copy number variation (CNV), somatic mutation, and promoter methylation to identify associated pathways and find novel biomarkers. We discovered twenty (20) mutated genes and three (3) potential pathways causing promoter changes in different gynaecological cancer types. We propose a data-interlinked platform called BIOOPENER that glues together heterogeneous cancer and biomedical repositories. The key approach is to find correspondences (or data links) among genetic, cellular and molecular features across isolated cancer datasets giving insight into cancer progression from normal to diseased tissues. The proposed BIOOPENER platform enriches mutations by filling in missing links from TCGA, COSMIC, REACTOME, KEGG and GO datasets and provides an interlinking mechanism to understand cancer progression from normal to diseased tissues with pathway components, which in turn helped to map mutations, associated phenotypes, pathways, and mechanism.