Data-driven characterization of molecular phenotypes across heterogeneous sample collections

Existing large gene expression data repositories hold enormous potential to elucidate disease mechanisms, characterize changes in cellular pathways, and to stratify patients based on molecular profiles. To achieve this goal, integrative resources and tools are needed that allow comparison of results across datasets and data types. We propose an intuitive approach for data-driven stratifications of molecular profiles and benchmark our methodology using the dimensionality reduction algorithm t-distributed stochastic neighbor embedding (t-SNE) with multi-study and multi-platform data on hematological malignancies. Our approach enables assessing the contribution of biological versus technical variation to sample clustering, direct incorporation of additional datasets to the same low dimensional representation, comparison of molecular disease subtypes identified from separate t-SNE representations, and characterization of the obtained clusters based on pathway databases and additional data. In this manner, we performed an integrative analysis across multi-omics acute myeloid leukemia studies. Our approach indicated new molecular subtypes with differential survival and drug responsiveness among samples lacking fusion genes, including a novel myelodysplastic syndrome-like cluster and a cluster characterized with CEBPA mutations and differential activity of the S-adenosylmethionine-dependent DNA methylation pathway. In summary, integration across multiple studies can help to identify novel molecular disease subtypes and generate insight into disease biology.Peer reviewe

Hemap: An nteractive online resource for characterizing molecular phenotypes across hematologic malignancies

Large collections of genome-wide data can facilitate the characterization of disease states and subtypes, permitting pan-cancer analysis of molecular phenotypes and evaluation of disease contexts for new therapeutic approaches. We analyzed 9,544 transcriptomes from over 30 hematologic malignancies, normal blood cell types and cell lines, and show that the disease types can be stratified in a data-driven manner. We utilized the obtained molecular clustering for discovery of cluster-specific pathway activity, new biomarkers and in silico drug target prioritization through integration with drug target databases. Using known vulnerabilities and available drug screens in benchmarking, we highlight the importance of integrating the molecular phenotype context and drug target expression for in silico prediction of drug responsiveness. Our analysis implicates BCL2 expression level as important indicator of venetoclax responsiveness and provides a rationale for its targeting in specific leukemia subtypes and multiple myeloma, links several polycomb group proteins that could be targeted by small molecules (SFMBT1, CBX7 and EZH1) with CLL, and supports CDK6 as disease-specific target in AML. Through integration with proteomics data, we characterized target protein expression for pre-B leukemia immunotherapy candidates, including DPEP1. These molecular data can be explored using our freely available interactive resource, Hemap, for expediting therapeutic innovations in hematologic malignancies

Ageing-associated changes in the human DNA methylome: genomic locations and effects on gene expression

Background Changes in DNA methylation are among the mechanisms contributing to the ageing process. We sought to identify ageing-associated DNA methylation changes at single-CpG-site resolution in blood leukocytes and to ensure that the observed changes were not due to differences in the proportions of leukocytes. The association between DNA methylation changes and gene expression levels was also investigated in the same individuals. Results We identified 8540 high-confidence ageing-associated CpG sites, 46% of which were hypermethylated in nonagenarians. The hypermethylation-associated genes belonged to a common category: they were predicted to be regulated by a common group of transcription factors and were enriched in a related set of GO terms and canonical pathways. Conversely, for the hypomethylation-associated genes only a limited set of GO terms and canonical pathways were identified. Among the 8540 CpG sites associated with ageing, methylation level of 377 sites was also associated with gene expression levels. These genes were enriched in GO terms and canonical pathways associated with immune system functions, particularly phagocytosis. Conclusions We find that certain ageing-associated immune-system impairments may be mediated via changes in DNA methylation. The results also imply that ageing-associated hypo- and hypermethylation are distinct processes: hypermethylation could be caused by programmed changes, whereas hypomethylation could be the result of environmental and stochastic processes.BioMed Central open aces

Comparison of machine learning methods in the early identification of vasculitides, myositides and glomerulonephritides

Background: Rare disease diagnoses are often delayed by years, including multiple doctor visits, and potential imprecise or incorrect diagnoses before receiving the correct one. Machine learning could solve this problem by flagging potential patients that doctors should examine more closely. Methods: Making the prediction situation as close as possible to real situation, we tested different masking sizes. In the masking phase, data was removed, and it was applied to all data points following the first rare disease diagnosis, including the day when the diagnosis was received, and in addition applied to selected number of days before initial diagnosis. Performance of machine learning models were compared with positive predictive value (PPV), negative predictive value (NPV), prevalence PPV (pPPV), prevalence NPV (pNPV), accuracy (ACC) and area under the receiver operation characteristics curve (AUC). Results: XGBoost had PPVs over 90 % in all masking settings, and InceptionVasGloMyotides had most of the PPVs over 90 %, but not as consistently. When the prevalence of the diseases was considered XGBoost achieved highest value of 8.8 % in binary classification with 30 days masking and InceptionVasGloMyotides achieved the best value of 6 % in the binary classification as well, but with 2160 days and 4320 days masking. ACC were varying between 89 % and 98 % with XGBoost and InceptionVasGloMyotides having variation between 79 % and 94 %. AUC on the other hand varied between 72.6 % and 94.5 % with InceptionVasGloMyotides and for XGBoost it varied between 69.9 % and 96.4 %. Conclusions: XGBoost and InceptionVasGloMyotides could successfully predict rare diseases for patients at least 30 days prior to initial rare disease diagnose. In addition, we managed to build performative custom deep learning model.Peer reviewe

CYP2C19 loss-of-function alleles and use of omeprazole or esomeprazole increase the risk of cardiovascular outcomes in patients using clopidogrel

Our aim was to investigate in a real-life prospective patient cohort how CYP2C19 loss-of- function ( LOF) variants and CYP2C19 inhibitor omeprazole or esomeprazole influence the incidence of cardiovascular events in patients using clopidogrel. Data based simultaneously on these factors are conflicting and sparse. A cohort of prospective patients (n = 1972) with acute coronary syndrome (n = 1302) or symptomatic chronic coronary disease (n = 656) was followed for 365 days after hospitalization with information on purchased prescription drugs, hospital discharge, death, and genotype for CYP2C19*2, CYP2C19*3, and CYP2C19*8 LOF variants. The primary study outcome measurement was cardiovascular death or recurring myocardial infarction or stroke. Altogether, 608 patients (30.8%) carried CYP2C19 LOF alleles. During the 365-day follow-up 252 patients (12.8%) had an ischemic vascular event. Cardiovascular events were significantly more frequent in carriers of CYP2C19 LOF alleles ( 14.8%, 95% confidence interval [CI], 11.7-17.8) than in non-carriers (10.8%, 95% CI, 9.0-12.6, p = 0.0159). Omeprazole or esomeprazole use was similar among LOF allele carriers (n = 131, 21.5%) and non-carriers (n = 250, 18.3%, p = 0.185). Cardiovascular events were significantly more common in a composite group consisting of all CYP2C19 LOF carriers regardless of proton pump inhibitor use status and non- carriers using omeprazole or esomeprazole than in non-carriers not using omeprazole or esomeprazole (14.8%, 95% CI, 12.2-17.3 vs. 9.9%, 95% CI, 8.0-11.9, p = 0.00173). We observed significantly more cardiovascular events in carriers of CYP2C19 LOF variants and in non- carriers using omeprazole or esomeprazole. For optimal patient care, both genetics and concomitant medication should be considered.Peer reviewe

Laminin α5 substrates promote survival, network formation and functional development of human pluripotent stem cell-derived neurons in vi

Laminins are one of the major protein groups in the extracellular matrix (ECM) and specific laminin isoforms are crucial for neuronal functions in the central nervous system in vivo. In the present study, we compared recombinant human laminin isoforms (LN211, LN332, LN411, LN511, and LN521) and laminin isoform fragment (LN511-E8) in in vitro cultures of human pluripotent stem cell (hPSC)-derived neurons. We showed that laminin substrates containing the α5-chain are important for neuronal attachment, viability and network formation, as detected by phase contrast imaging, viability staining, and immunocytochemistry. Gene expression analysis showed that the molecular mechanisms involved in the preference of hPSC-derived neurons for specific laminin isoforms could be related to ECM remodeling and cell adhesion. Importantly, the microelectrode array analysis revealed the widest distribution of electrophysiologically active neurons on laminin α5 substrates, indicating most efficient development of neuronal network functionality. This study shows that specific laminin α5 substrates provide a controlled in vitro culture environment for hPSC-derived neurons. These substrates can be utilized not only to enhance the production of functional hPSC-derived neurons for in vitro applications like disease modeling, toxicological studies, and drug discovery, but also for the production of clinical grade hPSC-derived cells for regenerative medicine applications

Ageing-associated changes in the human DNA methylome: genomic locations and effects on gene expression

Background Changes in DNA methylation are among the mechanisms contributing to the ageing process. We sought to identify ageing-associated DNA methylation changes at single-CpG-site resolution in blood leukocytes and to ensure that the observed changes were not due to differences in the proportions of leukocytes. The association between DNA methylation changes and gene expression levels was also investigated in the same individuals. Results We identified 8540 high-confidence ageing-associated CpG sites, 46% of which were hypermethylated in nonagenarians. The hypermethylation-associated genes belonged to a common category: they were predicted to be regulated by a common group of transcription factors and were enriched in a related set of GO terms and canonical pathways. Conversely, for the hypomethylation-associated genes only a limited set of GO terms and canonical pathways were identified. Among the 8540 CpG sites associated with ageing, methylation level of 377 sites was also associated with gene expression levels. These genes were enriched in GO terms and canonical pathways associated with immune system functions, particularly phagocytosis. Conclusions We find that certain ageing-associated immune-system impairments may be mediated via changes in DNA methylation. The results also imply that ageing-associated hypo- and hypermethylation are distinct processes: hypermethylation could be caused by programmed changes, whereas hypomethylation could be the result of environmental and stochastic processes.BioMed Central open aces

Hemap : An Interactive Online Resource for Characterizing Molecular Phenotypes across Hematologic Malignancies

Large collections of genome-wide data can facilitate the characterization of disease states and subtypes, permitting pan-cancer analysis of molecular phenotypes and evaluation of disease context for new therapeutic approaches. We analyzed 9,544 transcriptomes from more than 30 hematologic malignancies, normal blood cell types, and cell lines, and showed that disease types could be stratified in a data-driven manner. We then identified cluster-specific pathway activity, new biomarkers, and in silico drug target prioritization through interrogation of drug target databases. Using known vulnerabilities and available drug screens, we highlighted the importance of integrating molecular phenotype with drug target expression for in silico prediction of drug responsiveness. Our analysis implicated BCL2 expression level as an important indicator of venetoclax responsiveness and provided a rationale for its targeting in specific leukemia subtypes and multiple myeloma, linked several polycomb group proteins that could be targeted by small molecules (SFMBT1, CBX7, and EZH1) with chronic lymphocytic leukemia, and supported CDK6 as a disease-specific target in acute myeloid leukemia. Through integration with proteomics data, we characterized target protein expression for pre-B leukemia immunotherapy candidates, including DPEP1. These molecular data can be explored using our publicly available interactive resource, Hemap, for expediting therapeutic innovations in hematologic malignancies.Peer reviewe

Whole-exome sequencing identifies germline mutation in TP53 and ATRX in a child with genomically aberrant AT/RT and her mother with anaplastic astrocytoma

Brain tumors typically arise sporadically and do not affect several family members simultaneously. In the present study, we describe clinical and genetic data from two patients, a mother and her daughter, with familial brain tumors. Exome sequencing revealed a germline missense mutation in the TP53 and ATRX genes in both cases, and a somatic copy-neutral loss of heterozygosity (LOH) in TP53 in both atypical teratoid/rhabdoid tumor (AT/RT) and astrocytoma tumors. ATRX mutation was associated with the loss of ATRX protein expression. In the astrocytoma case, R132C missense mutation was found in the known hotspot site in isocitrate dehydrogenase 1 (IDH1) and LOH was detected in TP53. The mother carried few other somatic alterations, suggesting that the IDH1 mutation and LOH in TP53 were sufficient to drive tumor development. The genome in the AT/RT tumor was atypically aneuploid: Most chromosomes had experienced copy-neutral LOH or whole-chromosome gains. Only Chromosome 18 had normal diploid status. INI1/hSNF5/SMARCB1 was homozygously deleted in the AT/RT tumor. This report provides further information about tumor development in a predisposed genetic background and describes two special Li–Fraumeni cases with a familial brain tumor.</jats:p

Integrated clinical, whole-genome, and transcriptome analysis of multisampled lethal metastatic prostate cancer

We report the first combined analysis of whole-genome sequence, detailed clinical history, and transcriptome sequence of multiple prostate cancer metastases in a single patient (A21). Whole-genome and transcriptome sequence was obtained from nine anatomically separate metastases, and targeted DNA sequencing was performed in cancerous and noncancerous foci within the primary tumor specimen removed 5 yr before death. Transcriptome analysis revealed increased expression of androgen receptor (AR)-regulated genes in liver metastases that harbored an AR p.L702H mutation, suggesting a dominant effect by the mutation despite being present in only one of an estimated 16 copies per cell. The metastases harbored several alterations to the PI3K/AKT pathway, including a clonal truncal mutation in PIK3CG and present in all metastatic sites studied. The list of truncal genomic alterations shared by all metastases included homozygous deletion of TP53, hemizygous deletion of RB1 and CHD1, and amplification of FGFR1. If the patient were treated today, given this knowledge, the use of second-generation androgen-directed therapies, cessation of glucocorticoid administration, and therapeutic inhibition of the PI3K/AKT pathway or FGFR1 receptor could provide personalized benefit. Three previously unreported truncal clonal missense mutations (ABCC4 p.R891L, ALDH9A1 p.W89R, and ASNA1 p.P75R) were expressed at the RNA level and assessed as druggable. The truncal status of mutations may be critical for effective actionability and merit further study. Our findings suggest that a large set of deeply analyzed cases could serve as a powerful guide to more effective prostate cancer basic science and personalized cancer medicine clinical trials