Genenames.org: the HGNC and VGNC resources in 2017

Evaluation of the Immune Response within the Tumor Microenvironment in African American and Non-Hispanic White Patients with Non-Small Cell Lung Cancer

BACKGROUND

African Americans have higher incidence and mortality from lung cancer than non-Hispanic Whites, but investigations into differences in immune response have been minimal. Therefore, we compared components of the tumor microenvironment among African Americans and non-Hispanic Whites diagnosed with non-small cell lung cancer based on PDL1 or tertiary lymphoid structure (TLS) status to identify differences of translational relevance.

METHODS

Using a cohort of 280 patients with non-small cell lung cancer from the Inflammation, Health, Ancestry, and Lung Epidemiology study (non-Hispanic White: n = 155; African American: n = 125), we evaluated PDL1 tumor proportion score (<1% vs. ≥1%) and TLS status (presence/absence), comparing differences within the tumor microenvironment based on immune cell distribution and differential expression of genes.

RESULTS

Tumors from African Americans had a higher proportion of plasma cell signatures within the tumor microenvironment than non-Hispanic Whites. In addition, gene expression patterns in African American PDL1-positive samples suggest that these tumors contained greater numbers of γδ T cells and resting dendritic cells, along with fewer CD8+ T cells after adjusting for age, sex, pack-years, stage, and histology. Investigation of differential expression of B cell/plasma cell-related genes between the two patient populations revealed that two immunoglobulin genes (IGKV2-29 and IGLL5) were associated with decreased mortality risk in African Americans.

CONCLUSIONS

In the first known race-stratified analysis of tumor microenvironment components in lung cancer based on PDL1 expression or TLS status, differences within the immune cell composition and transcriptomic signature were identified that may have therapeutic implications.

IMPACT

Future investigation of racial variation within the tumor microenvironment may help direct the use of immunotherapy.

An open source knowledge graph ecosystem for the life sciences

Translational research requires data at multiple scales of biological organization. Advancements in sequencing and multi-omics technologies have increased the availability of these data, but researchers face significant integration challenges. Knowledge graphs (KGs) are used to model complex phenomena, and methods exist to construct them automatically. However, tackling complex biomedical integration problems requires flexibility in the way knowledge is modeled. Moreover, existing KG construction methods provide robust tooling at the cost of fixed or limited choices among knowledge representation models. PheKnowLator (Phenotype Knowledge Translator) is a semantic ecosystem for automating the FAIR (Findable, Accessible, Interoperable, and Reusable) construction of ontologically grounded KGs with fully customizable knowledge representation. The ecosystem includes KG construction resources (e.g., data preparation APIs), analysis tools (e.g., SPARQL endpoint resources and abstraction algorithms), and benchmarks (e.g., prebuilt KGs). We evaluated the ecosystem by systematically comparing it to existing open-source KG construction methods and by analyzing its computational performance when used to construct 12 different large-scale KGs. With flexible knowledge representation, PheKnowLator enables fully customizable KGs without compromising performance or usability.

Synovial fibroblast gene expression is associated with sensory nerve growth and pain in rheumatoid arthritis

It has been presumed that rheumatoid arthritis (RA) joint pain is related to inflammation in the synovium; however, recent studies reveal that pain scores in patients do not correlate with synovial inflammation. We developed a machine-learning approach (graph-based gene expression module identification or GbGMI) to identify an 815-gene expression module associated with pain in synovial biopsy samples from patients with established RA who had limited synovial inflammation at arthroplasty. We then validated this finding in an independent cohort of synovial biopsy samples from patients who had early untreated RA with little inflammation. Single-cell RNA sequencing analyses indicated that most of these 815 genes were most robustly expressed by lining layer synovial fibroblasts. Receptor-ligand interaction analysis predicted cross-talk between human lining layer fibroblasts and human dorsal root ganglion neurons expressing calcitonin gene-related peptide (CGRP+). Both RA synovial fibroblast culture supernatant and netrin-4, which is abundantly expressed by lining fibroblasts and was within the GbGMI-identified pain-associated gene module, increased the branching of pain-sensitive murine CGRP+ dorsal root ganglion neurons in vitro. Imaging of solvent-cleared synovial tissue with little inflammation from humans with RA revealed CGRP+ pain-sensing neurons encasing blood vessels growing into synovial hypertrophic papilla. Together, these findings support a model whereby synovial lining fibroblasts express genes associated with pain that enhance the growth of pain-sensing neurons into regions of synovial hypertrophy in RA.

A framework for identifying fertility gene targets for mammalian pest control

Fertility-targeted gene drives have been proposed as an ethical genetic approach for managing wild populations of vertebrate pests for public health and conservation benefit. This manuscript introduces a framework to identify and evaluate target gene suitability based on biological gene function, gene expression and results from mouse knockout models. This framework identified 16 genes essential for male fertility and 12 genes important for female fertility that may be feasible targets for mammalian gene drives and other non-drive genetic pest control technology. Further, a comparative genomics analysis demonstrates the conservation of the identified genes across several globally significant invasive mammals. In addition to providing important considerations for identifying candidate genes, our framework and the genes identified in this study may have utility in developing additional pest control tools such as wildlife contraceptives.

Emerging roles of the Protein Phosphatase 1 (PP1) in the context of viral infections

Protein Phosphatase 1 (PP1) is a major serine/threonine phosphatase in eukaryotes, participating in several cellular processes and metabolic pathways. Due to their low substrate specificity, PP1's catalytic subunits do not exist as free entities but instead bind to Regulatory Interactors of Protein Phosphatase One (RIPPO), which regulate PP1's substrate specificity and subcellular localization. Most RIPPOs bind to PP1 through combinations of short linear motifs (4-12 residues), forming highly specific PP1 holoenzymes. These PP1-binding motifs may, hence, represent attractive targets for the development of specific drugs that interfere with a subset of PP1 holoenzymes. Several viruses exploit the host cell protein (de)phosphorylation machinery to ensure efficient virus particle formation and propagation. While the role of many host cell kinases in viral life cycles has been extensively studied, the targeting of phosphatases by viral proteins has been studied in less detail. Here, we compile and review what is known concerning the role of PP1 in the context of viral infections and discuss how it may constitute a putative host-based target for the development of novel antiviral strategies.

Machine Learning Reveals Synovial Fibroblast Genes Associated with Pain Affect Sensory Nerve Growth in Rheumatoid Arthritis

It has been presumed that rheumatoid arthritis (RA) joint pain is related to inflammation in the synovium; however, recent studies reveal that pain scores in patients do not correlate with synovial inflammation. We identified a module of 815 genes associated with pain, using a novel machine learning approach, Graph-based Gene expression Module Identification (GbGMI), in samples from patients with longstanding RA, but limited synovial inflammation at arthroplasty, and validated this finding in an independent cohort of synovial biopsy samples from early, untreated RA patients. Single-cell RNA-seq analyses indicated these genes were most robustly expressed by lining layer fibroblasts and receptor-ligand interaction analysis predicted robust lining layer fibroblast crosstalk with pain sensitive CGRP+ dorsal root ganglion sensory neurons. Netrin-4, which is abundantly expressed by lining fibroblasts and associated with pain, significantly increased the branching of pain-sensitive CGRP+ neurons in vitro . We conclude GbGMI is a useful method for identifying a module of genes that associate with a clinical feature of interest. Using this approach, we find that Netrin-4 is produced by synovial fibroblasts in the absence of inflammation and can enhance the outgrowth of CGRP+ pain sensitive nerve fibers.

One Sentence Summary

Machine Learning reveals synovial fibroblast genes related to pain affect sensory nerve growth in Rheumatoid Arthritis addresses unmet clinical need.

Phosphoproteomics of patient-derived xenografts identifies targets and markers associated with sensitivity and resistance to EGFR blockade in colorectal cancer

Epidermal growth factor receptor (EGFR) is a well-exploited therapeutic target in metastatic colorectal cancer (mCRC). Unfortunately, not all patients benefit from current EGFR inhibitors. Mass spectrometry-based proteomics and phosphoproteomics were performed on 30 genomically and pharmacologically characterized mCRC patient-derived xenografts (PDXs) to investigate the molecular basis of response to EGFR blockade and identify alternative drug targets to overcome resistance. Both the tyrosine and global phosphoproteome as well as the proteome harbored distinctive response signatures. We found that increased pathway activity related to mitogen-activated protein kinase (MAPK) inhibition and abundant tyrosine phosphorylation of cell junction proteins, such as CXADR and CLDN1/3, in sensitive tumors, whereas epithelial-mesenchymal transition and increased MAPK and AKT signaling were more prevalent in resistant tumors. Furthermore, the ranking of kinase activities in single samples confirmed the driver activity of ERBB2, EGFR, and MET in cetuximab-resistant tumors. This analysis also revealed high kinase activity of several members of the Src and ephrin kinase family in 2 CRC PDX models with genomically unexplained resistance. Inhibition of these hyperactive kinases, alone or in combination with cetuximab, resulted in growth inhibition of ex vivo PDX-derived organoids and in vivo PDXs. Together, these findings highlight the potential value of phosphoproteomics to improve our understanding of anti-EGFR treatment and response prediction in mCRC and bring to the forefront alternative drug targets in cetuximab-resistant tumors.

Citrullination of actin-ligand and nuclear structural proteins, cytoskeleton reorganization and protein redistribution across cellular fractions are early events in ionomycin-induced NETosis

Neutrophil extracellular traps (NETs) are web-like structures of DNA coated with cytotoxic proteins and histones released by activated neutrophils through a process called NETosis. NETs release occurs through a sequence of highly organized events leading to chromatin expansion and rupture of nuclear and cellular membranes. In calcium ionophore-induced NETosis, the enzyme peptidylargine deiminase 4 (PAD4) mediates chromatin decondensation through histone citrullination, but the biochemical pathways involved in this process are not fully understood. Here we use live-imaging microscopy and proteomic studies of the neutrophil cellular fractions to investigate the early events in ionomycin-triggered NETosis. We found that before ionomycin-stimulated neutrophils release NETs, profound biochemical changes occur in and around their nucleus, such as, cytoskeleton reorganization, nuclear redistribution of actin-remodeling related proteins, and citrullination of actin-ligand and nuclear structural proteins. Ionomycin-stimulated neutrophils rapidly lose their characteristic polymorphic nucleus, and these changes are promptly communicated to the extracellular environment through the secretion of proteins related to immune response. Therefore, our findings revealed key biochemical mediators in the early process that subsequently culminates with nuclear and cell membranes rupture, and extracellular DNA release.

A framework for identifying fertility gene targets for mammalian pest control

Fertility-targeted gene drives have been proposed as an ethical genetic approach for managing wild populations of vertebrate pests for public health and conservation benefit.This manuscript introduces a framework to identify and evaluate target gene suitability based on biological gene function, gene expression, and results from mouse knockout models.This framework identified 16 genes essential for male fertility and 12 genes important for female fertility that may be feasible targets for mammalian gene drives and other non-drive genetic pest control technology. Further, a comparative genomics analysis demonstrates the conservation of the identified genes across several globally significant invasive mammals.In addition to providing important considerations for identifying candidate genes, our framework and the genes identified in this study may have utility in developing additional pest control tools such as wildlife contraceptives.

Multidimensional conservation analysis decodes the expression of conserved long noncoding RNAs

Although long noncoding RNAs (lncRNAs) experience weaker evolutionary constraints and exhibit lower sequence conservation than coding genes, they can still conserve their features in various aspects. Here, we used multiple approaches to systemically evaluate the conservation between human and mouse lncRNAs from various dimensions including sequences, promoter, global synteny, and local synteny, which led to the identification of 1,731 conserved lncRNAs with 427 high-confidence ones meeting multiple criteria. Conserved lncRNAs, compared with non-conserved ones, generally have longer gene bodies, more exons and transcripts, stronger connections with human diseases, and are more abundant and widespread across different tissues. Transcription factor (TF) profile analysis revealed a significant enrichment of TF types and numbers in the promoters of conserved lncRNAs. We further identified a set of TFs that preferentially bind to conserved lncRNAs and exert stronger regulation on conserved than non-conserved lncRNAs. Our study has reconciled some discrepant interpretations of lncRNA conservation and revealed a new set of transcriptional factors ruling the expression of conserved lncRNAs.

New insights in the genetic variant spectrum of SLC34A2 in pulmonary alveolar microlithiasis; a systematic review

Pulmonary alveolar microlithiasis (PAM) is a rare autosomal recessive lung disease caused by variants in the SLC34A2 gene encoding the sodium-dependent phosphate transport protein 2B, NaPi-2b. PAM is characterized by deposition of calcium phosphate crystals in the alveoli. Onset and clinical course vary considerably; some patients remain asymptomatic while others develop severe respiratory failure with a significant symptom burden and compromised survival. It is likely that PAM is under-reported due to lack of recognition, misdiagnosis, and mild clinical presentation. Most patients are genetically uncharacterized as the diagnostic confirmation of PAM has traditionally not included a genetic analysis. Genetic testing may in the future be the preferred tool for diagnostics instead of invasive methods. This systematic review aims to provide an overview of the growing knowledge of PAM genetics. Rare variants in SLC34A2 are found in almost all genetically tested patients. So far, 34 allelic variants have been identified in at least 68 patients. A majority of these are present in the homozygous state; however, a few are found in the compound heterozygous form. Most of the allelic variants involve only a single nucleotide. Half of the variants are either nonsense or frameshifts, resulting in premature termination of the protein or decay of the mRNA. There is currently no cure for PAM, and the only effective treatment is lung transplantation. Management is mainly symptomatic, but an improved understanding of the underlying pathophysiology will hopefully result in development of targeted treatment options. More standardized data on PAM patients, including a genetic diagnosis covering larger international populations, would support the design and implementation of clinical studies to the benefit of patients. Further genetic characterization and understanding of how the molecular changes influence disease phenotype will hopefully allow earlier diagnosis and treatment of the disease in the future.

SOX17 Enhancer Variants Disrupt Transcription Factor Binding And Enhancer Inactivity Drives Pulmonary Hypertension

BACKGROUND

Pulmonary arterial hypertension (PAH) is a rare disease characterized by remodeling of the pulmonary arteries, increased vascular resistance, and right-sided heart failure. Genome-wide association studies of idiopathic/heritable PAH established novel genetic risk variants, including conserved enhancers upstream of transcription factor (TF) SOX17 containing 2 independent signals. SOX17 is an important TF in embryonic development and in the homeostasis of pulmonary artery endothelial cells (hPAEC) in the adult. Rare pathogenic mutations in SOX17 cause heritable PAH. We hypothesized that PAH risk alleles in an enhancer region impair TF-binding upstream of SOX17, which in turn reduces SOX17 expression and contributes to disturbed endothelial cell function and PAH development.

METHODS

CRISPR manipulation and siRNA were used to modulate SOX17 expression. Electromobility shift assays were used to confirm in silico-predicted TF differential binding to the SOX17 variants. Functional assays in hPAECs were used to establish the biological consequences of SOX17 loss. In silico analysis with the connectivity map was used to predict compounds that rescue disturbed SOX17 signaling. Mice with deletion of the SOX17-signal 1 enhancer region (SOX17-4593/enhKO) were phenotyped in response to chronic hypoxia and SU5416/hypoxia.

RESULTS

CRISPR inhibition of SOX17-signal 2 and deletion of SOX17-signal 1 specifically decreased SOX17 expression. Electromobility shift assays demonstrated differential binding of hPAEC nuclear proteins to the risk and nonrisk alleles from both SOX17 signals. Candidate TFs HOXA5 and ROR-α were identified through in silico analysis and antibody electromobility shift assays. Analysis of the hPAEC transcriptomes revealed alteration of PAH-relevant pathways on SOX17 silencing, including extracellular matrix regulation. SOX17 silencing in hPAECs resulted in increased apoptosis, proliferation, and disturbance of barrier function. With the use of the connectivity map, compounds were identified that reversed the SOX17-dysfunction transcriptomic signatures in hPAECs. SOX17 enhancer knockout in mice reduced lung SOX17 expression, resulting in more severe pulmonary vascular leak and hypoxia or SU5416/hypoxia-induced pulmonary hypertension.

CONCLUSIONS

Common PAH risk variants upstream of the SOX17 promoter reduce endothelial SOX17 expression, at least in part, through differential binding of HOXA5 and ROR-α. Reduced SOX17 expression results in disturbed hPAEC function and PAH. Existing drug compounds can reverse the disturbed SOX17 pulmonary endothelial transcriptomic signature.

The VGNC: expanding standardized vertebrate gene nomenclature

The Vertebrate Gene Nomenclature Committee (VGNC) was established in 2016 as a sister project to the HUGO Gene Nomenclature Committee, to approve gene nomenclature in vertebrate species without an existing dedicated nomenclature committee. The VGNC aims to harmonize gene nomenclature across selected vertebrate species in line with human gene nomenclature, with orthologs assigned the same nomenclature where possible. This article presents an overview of the VGNC project and discussion of key findings resulting from this work to date. VGNC-approved nomenclature is accessible at https://vertebrate.genenames.org and is additionally displayed by the NCBI, Ensembl, and UniProt databases.

COVID-19Base v3: Update of the knowledgebase for drugs and biomedical entities linked to COVID-19

COVID-19 has taken a huge toll on our lives over the last 3 years. Global initiatives put forward by all stakeholders are still in place to combat this pandemic and help us learn lessons for future ones. While the vaccine rollout was not able to curb the spread of the disease for all strains, the research community is still trying to develop effective therapeutics for COVID-19. Although Paxlovid and remdesivir have been approved by the FDA against COVID-19, they are not free of side effects. Therefore, the search for a therapeutic solution with high efficacy continues in the research community. To support this effort, in this latest version (v3) of COVID-19Base, we have summarized the biomedical entities linked to COVID-19 that have been highlighted in the scientific literature after the vaccine rollout. Eight different topic-specific dictionaries, i.e., gene, miRNA, lncRNA, PDB entries, disease, alternative medicines registered under clinical trials, drugs, and the side effects of drugs, were used to build this knowledgebase. We have introduced a BLSTM-based deep-learning model to predict the drug-disease associations that outperforms the existing model for the same purpose proposed in the earlier version of COVID-19Base. For the very first time, we have incorporated disease-gene, disease-miRNA, disease-lncRNA, and drug-PDB associations covering the largest number of biomedical entities related to COVID-19. We have provided examples of and insights into different biomedical entities covered in COVID-19Base to support the research community by incorporating all of these entities under a single platform to provide evidence-based support from the literature. COVID-19Base v3 can be accessed from: https://covidbase-v3.vercel.app/. The GitHub repository for the source code and data dictionaries is available to the community from: https://github.com/91Abdullah/covidbasev3.0.

Transcriptional mapping of the macaque retina and RPE-choroid reveals conserved inter-tissue transcription drivers and signaling pathways

The macula and fovea comprise a highly sensitive visual detection tissue that is susceptible to common disease processes like age-related macular degeneration (AMD). Our understanding of the molecular determinants of high acuity vision remains unclear, as few model organisms possess a human-like fovea. We explore transcription factor networks and receptor-ligand interactions to elucidate tissue interactions in the macula and peripheral retina and concomitant changes in the underlying retinal pigment epithelium (RPE)/choroid. Poly-A selected, 100 bp paired-end RNA-sequencing (RNA-seq) was performed across the macular/foveal, perimacular, and temporal peripheral regions of the neural retina and RPE/choroid tissues of four adult Rhesus macaque eyes to characterize region- and tissue-specific gene expression. RNA-seq reads were mapped to both the macaque and human genomes for maximum alignment and analyzed for differential expression and Gene Ontology (GO) enrichment. Comparison of the neural retina and RPE/choroid tissues indicated distinct, contiguously changing gene expression profiles from fovea through perimacula to periphery. Top GO enrichment of differentially expressed genes in the RPE/choroid included cell junction organization and epithelial cell development. Expression of transcriptional regulators and various disease-associated genes show distinct location-specific preference and retina-RPE/choroid tissue-tissue interactions. Regional gene expression changes in the macaque retina and RPE/choroid is greater than that found in previously published transcriptome analysis of the human retina and RPE/choroid. Further, conservation of human macula-specific transcription factor profiles and gene expression in macaque tissues suggest a conservation of programs required for retina and RPE/choroid function and disease susceptibility.

A curated collection of human vaccination response signatures

Recent advances in high-throughput experiments and systems biology approaches have resulted in hundreds of publications identifying “immune signatures”. Unfortunately, these are often described within text, figures, or tables in a format not amenable to computational processing, thus severely hampering our ability to fully exploit this information. Here we present a data model to represent immune signatures, along with the Human Immunology Project Consortium (HIPC) Dashboard (www.hipc-dashboard.org), a web-enabled application to facilitate signature access and querying. The data model captures the biological response components (e.g., genes, proteins, cell types or metabolites) and metadata describing the context under which the signature was identified using standardized terms from established resources (e.g., HGNC, Protein Ontology, Cell Ontology). We have manually curated a collection of >600 immune signatures from >60 published studies profiling human vaccination responses for the current release. The system will aid in building a broader understanding of the human immune response to stimuli by enabling researchers to easily access and interrogate published immune signatures.

Follistatin-like 1 and its paralogs in heart development and cardiovascular disease

Cardiovascular diseases (CVDs) are a group of disorders affecting the heart and blood vessels and a leading cause of death worldwide. Thus, there is a need to identify new cardiokines that may protect the heart from damage as reported in GBD 2017 Causes of Death Collaborators (2018) (The Lancet 392:1736-1788). Follistatin-like 1 (FSTL1) is a cardiokine that is highly expressed in the heart and released to the serum after cardiac injury where it is associated with CVD and predicts poor outcome. The action of FSTL1 likely depends not only on the tissue source but also post-translation modifications that are target tissue- and cell-specific. Animal studies examining the effect of FSTL1 in various models of heart disease have exploded over the past 15 years and primarily report a protective effect spanning from inhibiting inflammation via transforming growth factor, preventing remodeling and fibrosis to promoting angiogenesis and hypertrophy. A better understanding of FSTL1 and its homologs is needed to determine whether this protein could be a useful novel biomarker to predict poor outcome and death and whether it has therapeutic potential. The aim of this review is to provide a comprehensive description of the literature for this family of proteins in order to better understand their role in normal physiology and CVD.

Role of EFNA1 SNP (rs12904) in Tumorigenesis and Metastasis of Colorectal Cancer: A Bioinformatic Analysis and HRM SNP Genotyping Verification

OBJECTIVE

Colorectal cancer is a prevalent disease with a poor prognosis and is known as a heterogeneous disease with many differences in clinical Symptoms and molecular profiles. The present study aimed to systematically evaluate the association of SNPs in miRNA binding sites of target genes that are involved in CRC angiogenesis, epithelial to mesenchymal transition, and cytoskeleton organization with tumorigenesis and metastasis of CRC.

METHODS

A case-control study was performed on 146 samples of CRC patients and 132 healthy samples. After that, the DNA of all samples was isolated by the salting-out method. Finally, the genotypes for EFNA1 SNP (rs12904) were identified by HRM (High-resolution melting analysis) method. In order to evaluate the results of genotyping, two samples from each genotype were sequenced using the sanger sequencing method.

RESULT

The frequency of AA genotype and the frequency of GG for rs12904 in satge4 and other stages are different from each other (P-value <0.0001) (P-value = 0.008). Also, the frequency of AA genotype in patients with different grades is different from each other (P-value = 0.035), while the frequency of AG   genotype and the frequency of GG   genotype is not significantly different in patients with different grades (P-value = 0.377) (P-value = 0.284).

CONCLUSION

Results of this study indicated that patients carrying the GA and GG genotypes reduced the risk of disease progression compared to the AA genotype. As a result, this polymorphism plays a key role in CRC pathogenesis and metastasis and could be used as a biomarker in molecular diagnosis and metastatic state prediction in the near future after further study of its signaling pathways and molecular mechanism.

BESFA: bioinformatics based evolutionary, structural & functional analysis of prostrate, Placenta, Ovary, Testis, and Embryo (POTE) paralogs

The POTE family comprises 14 paralogues and is primarily expressed in Prostrate, Placenta, Ovary, Testis, Embryo (POTE), and cancerous cells. The prospective function of the POTE protein family under physiological conditions is less understood. We systematically analyzed their cellular localization and molecular docking analysis to elucidate POTE proteins' structure, function, and Adaptive Divergence. Our results suggest that group three POTE paralogs (POTEE, POTEF, POTEI, POTEJ, and POTEKP (a pseudogene)) exhibits significant variation among other members could be because of their Adaptive Divergence. Furthermore, our molecular docking studies on POTE protein revealed the highest binding affinity with NCI-approved anticancer compounds. Additionally, POTEE, POTEF, POTEI, and POTEJ were subject to an explicit molecular dynamic simulation for 50ns. MM-GBSA and other essential electrostatics were calculated that showcased that only POTEE and POTEF have absolute binding affinities with minimum energy exploitation. Thus, this study’s outcomes are expected to drive cancer research to successful utilization of POTE genes family as a new biomarker, which could pave the way for the discovery of new therapies.

Immunodeficiency, autoimmunity, and increased risk of B cell malignancy in humans with TRAF3 mutations

Tumor necrosis factor receptor-associated factor 3 (TRAF3) is a central regulator of immunity. TRAF3 is often somatically mutated in B cell malignancies, but its role in human immunity is not defined. Here, in five unrelated families, we describe an immune dysregulation syndrome of recurrent bacterial infections, autoimmunity, systemic inflammation, B cell lymphoproliferation, and hypergammaglobulinemia. Affected individuals each had monoallelic mutations in TRAF3 that reduced TRAF3 expression. Immunophenotyping showed that patients' B cells were dysregulated, exhibiting increased nuclear factor-κB 2 activation, elevated mitochondrial respiration, and heightened inflammatory responses. Patients had mild CD4+ T cell lymphopenia, with a reduced proportion of naïve T cells but increased regulatory T cells and circulating T follicular helper cells. Guided by this clinical phenotype, targeted analyses demonstrated that common genetic variants, which also reduce TRAF3 expression, are associated with an increased risk of B cell malignancies, systemic lupus erythematosus, higher immunoglobulin levels, and bacterial infections in the wider population. Reduced TRAF3 conveys disease risks by driving B cell hyperactivity via intrinsic activation of multiple intracellular proinflammatory pathways and increased mitochondrial respiration, with a likely contribution from dysregulated T cell help. Thus, we define monogenic TRAF3 haploinsufficiency syndrome and demonstrate how common TRAF3 variants affect a range of human diseases.

Exploration of Target Spaces in the Human Genome for Protein and Peptide Drugs

After decades of development, protein and peptide drugs have now grown into a major drug class in the marketplace. Target identification and validation are crucial for the discovery of protein and peptide drugs, and bioinformatics prediction of targets based on the characteristics of known target proteins will help improve the efficiency and success rate of target selection. However, owing to the developmental history in the pharmaceutical industry, previous systematic exploration of the target spaces has mainly focused on traditional small-molecule drugs, while studies related to protein and peptide drugs are lacking. Here, we systematically explore the target spaces in the human genome specifically for protein and peptide drugs. Compared with other proteins, both successful protein and peptide drug targets have many special characteristics, and are also significantly different from those of small-molecule drugs in many aspects. Based on these features, we develop separate effective genome-wide target prediction models for protein and peptide drugs. Finally, a user-friendly web server, Predictor Of Protein and PeptIde drugs' therapeutic Targets (POPPIT) (http://poppit.ncpsb.org.cn/), is established, which provides not only target prediction specifically for protein and peptide drugs but also abundant annotations for predicted targets.

DES-Amyloidoses “Amyloidoses through the looking-glass”: A knowledgebase developed for exploring and linking information related to human amyloid-related diseases

More than 30 types of amyloids are linked to close to 50 diseases in humans, the most prominent being Alzheimer’s disease (AD). AD is brain-related local amyloidosis, while another amyloidosis, such as AA amyloidosis, tends to be more systemic. Therefore, we need to know more about the biological entities’ influencing these amyloidosis processes. However, there is currently no support system developed specifically to handle this extraordinarily complex and demanding task. To acquire a systematic view of amyloidosis and how this may be relevant to the brain and other organs, we needed a means to explore "amyloid network systems" that may underly processes that leads to an amyloid-related disease. In this regard, we developed the DES-Amyloidoses knowledgebase (KB) to obtain fast and relevant information regarding the biological network related to amyloid proteins/peptides and amyloid-related diseases. This KB contains information obtained through text and data mining of available scientific literature and other public repositories. The information compiled into the DES-Amyloidoses system based on 19 topic-specific dictionaries resulted in 796,409 associations between terms from these dictionaries. Users can explore this information through various options, including enriched concepts, enriched pairs, and semantic similarity. We show the usefulness of the KB using an example focused on inflammasome-amyloid associations. To our knowledge, this is the only KB dedicated to human amyloid-related diseases derived primarily through literature text mining and complemented by data mining that provides a novel way of exploring information relevant to amyloidoses.

Mitochondrial Ribosome Dysfunction in Human Alveolar Type II Cells in Emphysema

Pulmonary emphysema is characterized by airspace enlargement and the destruction of alveoli. Alveolar type II (ATII) cells are very abundant in mitochondria. OXPHOS complexes are composed of proteins encoded by the mitochondrial and nuclear genomes. Mitochondrial 12S and 16S rRNAs are required to assemble the small and large subunits of the mitoribosome, respectively. We aimed to determine the mechanism of mitoribosome dysfunction in ATII cells in emphysema. ATII cells were isolated from control nonsmokers and smokers, and emphysema patients. Mitochondrial transcription and translation were analyzed. We also determined the miRNA expression. Decreases in ND1 and UQCRC2 expression levels were found in ATII cells in emphysema. Moreover, nuclear NDUFS1 and SDHB levels increased, and mitochondrial transcribed ND1 protein expression decreased. These results suggest an impairment of the nuclear and mitochondrial stoichiometry in this disease. We also detected low levels of the mitoribosome structural protein MRPL48 in ATII cells in emphysema. Decreased 16S rRNA expression and increased 12S rRNA levels were observed. Moreover, we analyzed miR4485-3p levels in this disease. Our results suggest a negative feedback loop between miR-4485-3p and 16S rRNA. The obtained results provide molecular mechanisms of mitoribosome dysfunction in ATII cells in emphysema.

OncoboxPD: human 51 672 molecular pathways database with tools for activity calculating and visualization

OncoboxPD (Oncobox pathway databank) available at https://open.oncobox.com is the collection of 51 672 uniformly processed human molecular pathways. Superposition of all pathways formed interactome graph of protein–protein interactions and metabolic reactions containing 361 654 interactions and 64 095 molecular participants. Pathways are uniformly classified by biological processes, and each pathway node is algorithmically functionally annotated by specific activator/repressor role. This enables online calculation of statistically supported pathway activation levels (PALs) with the built-in bioinformatic tool using custom RNA/protein expression profiles. Each pathway can be visualized as static or dynamic graph, where vertices are molecules participating in a pathway and edges are interactions or reactions between them. Differentially expressed nodes in a pathway can be visualized in two-color mode with user-defined color scale. For every comparison, OncoboxPD also generates a graph summarizing top up- and downregulated pathways.

Impaired phosphate transport in SLC34A2 variants in patients with pulmonary alveolar microlithiasis

BACKGROUND

Variants in SLC34A2 encoding the sodium-dependent phosphate transport protein 2b (NaPi-IIb) cause the rare lung disease pulmonary alveolar microlithiasis (PAM). PAM is characterised by the deposition of calcium-phosphate concretions in the alveoli usually progressing over time. No effective treatment is available. So far, 30 allelic variants in patients have been reported but only a few have been functionally characterised. This study aimed to determine the impact of selected SLC34A2 variants on transporter expression and phosphate uptake in cellular studies.

METHODS

Two nonsense variants (c.910A > T and c.1456C > T), one frameshift (c.1328delT), and one in-frame deletion (c.1402_1404delACC) previously reported in patients with PAM were selected for investigation. Wild-type and mutant c-Myc-tagged human NaPi-IIb constructs were expressed in Xenopus laevis oocytes. The transport function was investigated with a 32Pi uptake assay. NaPi-IIb protein expression and localisation were determined with immunoblotting and immunohistochemistry, respectively.

RESULTS

Oocytes injected with the wild-type human NaPi-IIb construct had significant 32Pi transport compared to water-injected oocytes. In addition, the protein had a molecular weight as expected for the glycosylated form, and it was readily detectable in the oocyte membrane. Although the protein from the Thr468del construct was synthesised and expressed in the oocyte membrane, phosphate transport was similar to non-injected control oocytes. All other mutants were non-functional and not expressed in the membrane, consistent with the expected impact of the truncations caused by premature stop codons.

CONCLUSIONS

Of four analysed SLC34A2 variants, only the Thr468del showed similar protein expression as the wild-type cotransporter in the oocyte membrane. All mutant transporters were non-functional, supporting that dysfunction of NaPi-IIb underlies the pathology of PAM.

B4GALT5 high expression associated with poor prognosis of hepatocellular carcinoma

BACKGROUND

B4GALT5 is postulated to be an important protein in sugar metabolism that catalyzes the synthesis of lactosylceramide (LacCer). However, its role in hepatocellular carcinoma (HCC) remains unknown.

METHOD

We characterized the expression of B4GALT5 in HCC tissue compared to normal tissue, and explored its function of B4GALT5 in HCC by enrichment analysis based on its co-expressed gene set. Next, we checked whether B4GALT5 expression is correlated to immune infiltration level and clinical prognosis in hepatocellular carcinoma. Finally, we verified the expression of B4GALT5 using clinical samples evaluated by RT-PCR, and conducted in vitro experiments with B4GALT5-knockdown HCC cells to investigate the function of B4GALT5 in the HCC cell proliferation, migration and invasion.

RESULTS

We found B4GALT5 mRNA and protein expression levels were significantly high in HCC tissue compared to normal tissue. The enrichment analysis of the gene sets that co-expressed with B4GALT5 showed specificity in HCC-related pathways and functions. Also, the expression pattern of B4GALT5 was significantly related to the immune infiltration level, especially CD4+ T cell and macrophage cells. B4GALT5 higher mRNA expression was associated with poor overall survival (OS) in HCC patients. Furthermore, In vitro experiments showed that depletion of B4GALT5 significantly inhibited HCC cell proliferation, migration and invasion. This study revealed the function and its mediated pathways of B4GALT5 in HCC, indicating that B4GALT5 may serve as a prognostic biomarker of HCC.

Pulmonary surfactant protein B carried by HDL predicts incident CVD in patients with type 1 diabetes

Atherosclerotic CVD is the major cause of death in patients with type 1 diabetes mellitus (T1DM). Alterations in the HDL proteome have been shown to associate with prevalent CVD in T1DM. We therefore sought to determine which proteins carried by HDL might predict incident CVD in patients with T1DM. Using targeted MS/MS, we quantified 50 proteins in HDL from 181 T1DM subjects enrolled in the prospective Coronary Artery Calcification in Type 1 Diabetes study. We used Cox proportional regression analysis and a case-cohort design to test associations of HDL proteins with incident CVD (myocardial infarction, coronary artery bypass grafting, angioplasty, or death from coronary heart disease). We found that only one HDL protein-SFTPB (pulmonary surfactant protein B)-predicted incident CVD in all the models tested. In a fully adjusted model that controlled for lipids and other risk factors, the hazard ratio was 2.17 per SD increase of SFTPB (95% confidence interval, 1.12-4.21, P = 0.022). In addition, plasma fractionation demonstrated that SFTPB is nearly entirely bound to HDL. Although previous studies have shown that high plasma levels of SFTPB associate with prevalent atherosclerosis only in smokers, we found that SFTPB predicted incident CVD in T1DM independently of smoking status and a wide range of confounding factors, including HDL-C, LDL-C, and triglyceride levels. Because SFTPB is almost entirely bound to plasma HDL, our observations support the proposal that SFTPB carried by HDL is a marker-and perhaps mediator-of CVD risk in patients with T1DM.

Gene Expression-Based Signature Can Predict Sorafenib Response in Kidney Cancer

Sorafenib is a tyrosine kinase inhibitory drug with multiple molecular specificities that is approved for clinical use in second-line treatments of metastatic and advanced renal cell carcinomas (RCCs). However, only 10–40% of RCC patients respond on sorafenib-containing therapies, and personalization of its prescription may help in finding an adequate balance of clinical efficiency, cost-effectiveness, and side effects. We investigated whether expression levels of known molecular targets of sorafenib in RCC can serve as prognostic biomarker of treatment response. We used Illumina microarrays to profile RNA expression in pre-treatment formalin-fixed paraffin-embedded (FFPE) samples of 22 metastatic or advanced RCC cases with known responses on next-line sorafenib monotherapy. Among them, nine patients showed partial response (PR), three patients—stable disease (SD), and 10 patients—progressive disease (PD) according to Response Evaluation Criteria In Solid Tumors (RECIST) criteria. We then classified PR + SD patients as “responders” and PD patients as “poor responders”. We found that gene signature including eight sorafenib target genes was congruent with the drug response characteristics and enabled high-quality separation of the responders and poor responders [area under a receiver operating characteristic curve (AUC) 0.89]. We validated these findings on another set of 13 experimental annotated FFPE RCC samples (for 2 PR, 1 SD, and 10 PD patients) that were profiled by RNA sequencing and observed AUC 0.97 for 8-gene signature as the response classifier. We further validated these results in a series of qRT-PCR experiments on the third experimental set of 12 annotated RCC biosamples (for 4 PR, 3 SD, and 5 PD patients), where 8-gene signature showed AUC 0.83.

Silencing of lncRNA CHRM3-AS2 Expression Exerts Anti-Tumour Effects Against Glioma via Targeting microRNA-370-5p/KLF4

Objectives

Long non-coding RNAs (lncRNAs) are key regulators involved in the progression of glioma, and many functional lncRNAs are yet to be identified. This study aimed to explore the function of CHRM3-AS2, a rarely reported lncRNA, in glioma, as well as the underlying mechanisms involving miR-370-5p/KLF4.

Methods

Differentially expressed RNAs (DERs) were screened from two gene expression profiles of glioblastoma (GBM). Fluorescence in situ hybridisation was performed to determine the subcellular localisation of CHRM3-AS2. Cell viability, colony formation, apoptosis, migration, and invasion were evaluated using cell counting kit-8, colony counts, flow cytometry, wound healing, and Transwell assays, respectively. mRNA and protein expression of specific genes were measured using quantitative real-time polymerase chain reaction and western blotting, respectively. Dual luciferase reporter gene, RNA immunoprecipitation, and RNA pull-down assays were performed to identify the target relationships. A mouse xenograft model was established for in vivo validation.

Results

CHRM3-AS2 was screened as a prognosis-associated DER in GBM. CHRM3-AS2 expression was up-regulated in glioma cells, and CHRM3-AS2 was localised in the cytoplasm. Silencing of CHRM3-AS2 expression inhibited cell viability, colony formation, migration, and invasion and promoted apoptosis of U251 and SHG-44 cells. In addition, CHRM3-AS2 targeted miR-370-5p/KLF4 in glioma cells. The anti-tumour effect of CHRM3-AS2 silencing was weakened by miR-370-5p silencing or KLF4 overexpression. In vivo, silencing of CHRM3-AS2 expression inhibited tumour growth and Ki67 expression in mice. Overexpression of KLF4 also weakened the anti-tumour effect of CHRM3-AS2 silencing in mice.

Conclusions

Silencing of CHRM3-AS2 expression inhibited the malignant progression of glioma by regulating miR-370-5p/KLF4 expression.

A single-cell regulatory map of postnatal lung alveologenesis in humans and mice

Ex-utero regulation of the lungs' responses to breathing air and continued alveolar development shape adult respiratory health. Applying single-cell transposome hypersensitive site sequencing (scTHS-seq) to over 80,000 cells, we assembled the first regulatory atlas of postnatal human and mouse lung alveolar development. We defined regulatory modules and elucidated new mechanistic insights directing alveolar septation, including alveolar type 1 and myofibroblast cell signaling and differentiation, and a unique human matrix fibroblast population. Incorporating GWAS, we mapped lung function causal variants to myofibroblasts and identified a pathogenic regulatory unit linked to lineage marker FGF18, demonstrating the utility of chromatin accessibility data to uncover disease mechanism targets. Our regulatory map and analysis model provide valuable new resources to investigate age-dependent and species-specific control of critical developmental processes. Furthermore, these resources complement existing atlas efforts to advance our understanding of lung health and disease across the human lifespan.

The EurOPDX Data Portal: an open platform for patient-derived cancer xenograft data sharing and visualization

Background

Patient-derived xenografts (PDX) mice models play an important role in preclinical trials and personalized medicine. Sharing data on the models is highly valuable for numerous reasons – ethical, economical, research cross validation etc. The EurOPDX Consortium was established 8 years ago to share such information and avoid duplicating efforts in developing new PDX mice models and unify approaches to support preclinical research. EurOPDX Data Portal is the unified data sharing platform adopted by the Consortium.

Main body

In this paper we describe the main features of the EurOPDX Data Portal (https://dataportal.europdx.eu/), its architecture and possible utilization by researchers who look for PDX mice models for their research. The Portal offers a catalogue of European models accessible on a cooperative basis. The models are searchable by metadata, and a detailed view provides molecular profiles (gene expression, mutation, copy number alteration) and treatment studies. The Portal displays the data in multiple tools (PDX Finder, cBioPortal, and GenomeCruzer in future), which are populated from a common database displaying strictly mutually consistent views.

(Short) Conclusion

EurOPDX Data Portal is an entry point to the EurOPDX Research Infrastructure offering PDX mice models for collaborative research, (meta)data describing their features and deep molecular data analysis according to users’ interests.

The Novel Inducer of Innate Immunity HO53 Stimulates Autophagy in Human Airway Epithelial Cells

Aroylated phenylenediamines (APDs) are novel modulators of innate immunity with respect to enhancing the expression of antimicrobial peptides and maintaining epithelial barrier integrity. Here, we present a new study on induction of autophagy in human lung epithelial cells by the APD HO53. Interestingly, HO53 affected autophagy in a dose-dependent manner, demonstrated by increased microtubule-associated proteins 1A/1B light-chain 3B (LC3B) processing in mature polarized bronchial epithelial cells. The quantification of LC3B puncta showed increased autophagy flux and formation of autophagosomes visualized by transmission electron microscopy. The phenotypic changes indicated that autophagy induction was associated with activation of 5′ adenosine monophosphate-activated protein kinase (AMPK), nuclear translocation of transcription factor EB (TFEB), and changes in expression of autophagy-related genes. The kinetics of the explored signaling pathways indicated on activation of AMPK followed by the nuclear translocation of TFEB. Moreover, our data suggest that HO53 modulates epigenetic changes related to induction of autophagy manifested by transcriptional regulation of histone-modifying enzymes. These changes were reflected by decreased ubiquitination of histone 2B at the lysine 120 residue that is associated with autophagy induction. Taken together, HO53 modulates autophagy, a part of the host defense system, through a complex mechanism involving several pathways and epigenetic events.

Integrating genome-scale metabolic modelling and transfer learning for human gene regulatory network reconstruction

MOTIVATION

Gene regulation is responsible for controlling numerous physiological functions and dynamically responding to environmental fluctuations. Reconstructing the human network of gene regulatory interactions is thus paramount to understanding the cell functional organization across cell types, as well as to elucidating pathogenic processes and identifying molecular drug targets. Although significant effort has been devoted towards this direction, existing computational methods mainly rely on gene expression levels, possibly ignoring the information conveyed by mechanistic biochemical knowledge. Moreover, except for a few recent attempts, most of the existing approaches only consider the information of the organism under analysis, without exploiting the information of related model organisms.

RESULTS

We propose a novel method for the reconstruction of the human gene regulatory network, based on a transfer learning strategy that synergically exploits information from human and mouse, conveyed by gene-related metabolic features generated in silico from gene expression data. Specifically, we learn a predictive model from metabolic activity inferred via tissue-specific metabolic modelling of artificial gene knockouts. Our experiments show that the combination of our transfer learning approach with the constructed metabolic features provides a significant advantage in terms of reconstruction accuracy, as well as additional clues on the contribution of each constructed metabolic feature.

AVAILABILITY AND IMPLEMENTATION

The method, the datasets and all the results obtained in this study are available at: https://doi.org/10.6084/m9.figshare.c.5237687.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Investigating Deep Learning Based Breast Cancer Subtyping Using Pan-Cancer and Multi-Omic Data

Breast Cancer comprises multiple subtypes implicated in prognosis. Existing stratification methods rely on the expression quantification of small gene sets. Next Generation Sequencing promises large amounts of omic data in the next years. In this scenario, we explore the potential of machine learning and, particularly, deep learning for breast cancer subtyping. Due to the paucity of publicly available data, we leverage on pan-cancer and non-cancer data to design semi-supervised settings. We make use of multi-omic data, including microRNA expressions and copy number alterations, and we provide an in-depth investigation of several supervised and semi-supervised architectures. Obtained accuracy results show simpler models to perform at least as well as the deep semi-supervised approaches on our task over gene expression data. When multi-omic data types are combined together, performance of deep models shows little (if any) improvement in accuracy, indicating the need for further analysis on larger datasets of multi-omic data as and when they become available. From a biological perspective, our linear model mostly confirms known gene-subtype annotations. Conversely, deep approaches model non-linear relationships, which is reflected in a more varied and still unexplored set of representative omic features that may prove useful for breast cancer subtyping.

Lung Microenvironments and Disease Progression in Fibrotic Hypersensitivity Pneumonitis

Rationale: Fibrotic hypersensitivity pneumonitis (fHP) is an interstitial lung disease caused by sensitization to an inhaled allergen. Objectives: To identify the molecular determinants associated with progression of fibrosis. Methods: Nine fHP explant lungs and six unused donor lungs (as controls) were systematically sampled (4 samples/lung). According to microcomputed tomography measures, fHP cores were clustered into mild, moderate, and severe fibrosis groups. Gene expression profiles were assessed using weighted gene co-expression network analysis, xCell, gene ontology, and structure enrichment analysis. Gene expression of the prevailing molecular traits was also compared with idiopathic pulmonary fibrosis (IPF). The explant lung findings were evaluated in separate clinical fHP cohorts using tissue, BAL samples, and computed tomography scans. Measurements and Main Results: We found six molecular traits that associated with differential lung involvement. In fHP, extracellular matrix and antigen presentation/sensitization transcriptomic signatures characterized lung zones with only mild structural and histological changes, whereas signatures involved in honeycombing and B cells dominated the transcriptome in the most severely affected lung zones. With increasing disease severity, endothelial function was progressively lost, and progressive disruption in normal cellular homeostatic processes emerged. All six were also found in IPF, with largely similar associations with disease microenvironments. The molecular traits correlated with in vivo disease behavior in a separate clinical fHP cohort. Conclusions: We identified six molecular traits that characterize the morphological progression of fHP and associate with in vivo clinical behavior. Comparing IPF with fHP, the transcriptome landscape was determined considerably by local disease extent rather than by diagnosis alone.

The Genome of the "Sea Vomit" Didemnum vexillum

Tunicates are the sister group of vertebrates and thus occupy a key position for investigations into vertebrate innovations as well as into the consequences of the vertebrate-specific genome duplications. Nevertheless, tunicate genomes have not been studied extensively in the past, and comparative studies of tunicate genomes have remained scarce. The carpet sea squirt Didemnum vexillum, commonly known as "sea vomit", is a colonial tunicate considered an invasive species with substantial ecological and economical risk. We report the assembly of the D. vexillum genome using a hybrid approach that combines 28.5 Gb Illumina and 12.35 Gb of PacBio data. The new hybrid scaffolded assembly has a total size of 517.55 Mb that increases contig length about eightfold compared to previous, Illumina-only assembly. As a consequence of an unusually high genetic diversity of the colonies and the moderate length of the PacBio reads, presumably caused by the unusually acidic milieu of the tunic, the assembly is highly fragmented (L50 = 25,284, N50 = 6539). It is sufficient, however, for comprehensive annotations of both protein-coding genes and non-coding RNAs. Despite its shortcomings, the draft assembly of the "sea vomit" genome provides a valuable resource for comparative tunicate genomics and for the study of the specific properties of colonial ascidians.

Novel prostate cancer susceptibility gene SP6 predisposes patients to aggressive disease

Prostate cancer (PrCa) is one of the most common cancers in men, but little is known about factors affecting its clinical outcomes. Genome-wide association studies have identified more than 170 germline susceptibility loci, but most of them are not associated with aggressive disease. We performed a genome-wide analysis of 185,478 SNPs in Finnish samples (2738 cases, 2400 controls) from the international Collaborative Oncological Gene-Environment Study (iCOGS) to find underlying PrCa risk variants. We identified a total of 21 common, low-penetrance susceptibility loci, including 10 novel variants independently associated with PrCa risk. Novel risk loci were located in the 8q24 (CASC8 rs16902147, OR 1.86, padj = 3.53 × 10-8 and rs58809953, OR 1.71, padj = 4.00 × 10-6; intergenic rs79012498, OR 1.81, padj = 4.26 × 10-8), 17q21 (SP6 rs2074187, OR 1.66, padj = 3.75 × 10-5), 11q13 (rs12795301, OR 1.42, padj = 2.89 × 10-5) and 8p21 (rs995432, OR 1.38, padj = 3.00 × 10-11) regions. Here, we describe SP6, a transcription factor gene, as a new, potentially high-risk gene for PrCa. The intronic variant rs2074187 in SP6 was associated not only with overall susceptibility to PrCa (OR 1.66) but also with a higher odds ratio for aggressive PrCa (OR 1.89) and lower odds for non-aggressive PrCa (OR 1.43). Furthermore, the new intergenic variant rs79012498 at 8q24 conferred risk for aggressive PrCa. Our findings highlighted the power of a population-stratified approach to identify novel, clinically actionable germline PrCa risk loci and strongly suggested SP6 as a new PrCa candidate gene that may be involved in the pathogenesis of PrCa.

Labour classified by cervical dilatation & fetal membrane rupture demonstrates differential impact on RNA-seq data for human myometrium tissues

High throughput sequencing has previously identified differentially expressed genes (DEGs) and enriched signalling networks in human myometrium for term (≥37 weeks) gestation labour, when defined as a singular state of activity at comparison to the non-labouring state. However, transcriptome changes that occur during transition from early to established labour (defined as ≤3 and >3 cm cervical dilatation, respectively) and potentially altered by fetal membrane rupture (ROM), when adapting from onset to completion of childbirth, remained to be defined. In the present study, we assessed whether differences for these two clinically observable factors of labour are associated with different myometrial transcriptome profiles. Analysis of our tissue (‘bulk’) RNA-seq data (NCBI Gene Expression Omnibus: GSE80172) with classification of labour into four groups, each compared to the same non-labour group, identified more DEGs for early than established labour; ROM was the strongest up-regulator of DEGs. We propose that lower DEGs frequency for early labour and/or ROM negative myometrium was attributed to bulk RNA-seq limitations associated with tissue heterogeneity, as well as the possibility that processes other than gene transcription are of more importance at labour onset. Integrative analysis with future data from additional samples, which have at least equivalent refined clinical classification for labour status, and alternative omics approaches will help to explain what truly contributes to transcriptomic changes that are critical for labour onset. Lastly, we identified five DEGs common to all labour groupings; two of which (AREG and PER3) were validated by qPCR and not differentially expressed in placenta and choriodecidua.

SeekFusion - A Clinically Validated Fusion Transcript Detection Pipeline for PCR-Based Next-Generation Sequencing of RNA

Detecting gene fusions involving driver oncogenes is pivotal in clinical diagnosis and treatment of cancer patients. Recent developments in next-generation sequencing (NGS) technologies have enabled improved assays for bioinformatics-based gene fusions detection. In clinical applications, where a small number of fusions are clinically actionable, targeted polymerase chain reaction (PCR)-based NGS chemistries, such as the QIAseq RNAscan assay, aim to improve accuracy compared to standard RNA sequencing. Existing informatics methods for gene fusion detection in NGS-based RNA sequencing assays traditionally use a transcriptome-based spliced alignment approach or a de-novo assembly approach. Transcriptome-based spliced alignment methods face challenges with short read mapping yielding low quality alignments. De-novo assembly-based methods yield longer contigs from short reads that can be more sensitive for genomic rearrangements, but face performance and scalability challenges. Consequently, there exists a need for a method to efficiently and accurately detect fusions in targeted PCR-based NGS chemistries. We describe SeekFusion, a highly accurate and computationally efficient pipeline enabling identification of gene fusions from PCR-based NGS chemistries. Utilizing biological samples processed with the QIAseq RNAscan assay and in-silico simulated data we demonstrate that SeekFusion gene fusion detection accuracy outperforms popular existing methods such as STAR-Fusion, TOPHAT-Fusion and JAFFA-hybrid. We also present results from 4,484 patient samples tested for neurological tumors and sarcoma, encompassing details on some novel fusions identified.

A domain damage index to prioritizing the pathogenicity of missense variants

Prioritizing causal variants is one major challenge for the clinical application of sequencing data. Prompted by the observation that 74.3% of missense pathogenic variants locate in protein domains, we developed an approach named domain damage index (DDI). DDI identifies protein domains depleted of rare missense variations in the general population, which can be further used as a metric to prioritize variants. DDI is significantly correlated with phylogenetic conservation, variant-level metrics, and reported pathogenicity. DDI achieved great performance for distinguishing pathogenic variants from benign ones in three benchmark datasets. The combination of DDI with the other two best approaches improved the performance of each individual method considerably, suggesting DDI provides a powerful and complementary way of variant prioritization.

Interpretation of cancer mutations using a multiscale map of protein systems

A major goal of cancer research is to understand how mutations distributed across diverse genes affect common cellular systems, including multiprotein complexes and assemblies. Two challenges—how to comprehensively map such systems and how to identify which are under mutational selection—have hindered this understanding. Accordingly, we created a comprehensive map of cancer protein systems integrating both new and published multi-omic interaction data at multiple scales of analysis. We then developed a unified statistical model that pinpoints 395 specific systems under mutational selection across 13 cancer types. This map, called NeST (Nested Systems in Tumors), incorporates canonical processes and notable discoveries, including a PIK3CA-actomyosin complex that inhibits phosphatidylinositol 3-kinase signaling and recurrent mutations in collagen complexes that promote tumor proliferation. These systems can be used as clinical biomarkers and implicate a total of 548 genes in cancer evolution and progression. This work shows how disparate tumor mutations converge on protein assemblies at different scales.

Human cytomegalovirus expands a CD8+ T cell population with loss of BCL11B expression and gain of NK cell identity

[Figure: see text].

Talin rod domain-containing protein 1 (TLNRD1) is a novel actin-bundling protein which promotes filopodia formation

Talin is a mechanosensitive adapter protein that couples integrins to the cytoskeleton. Talin rod domain-containing protein 1 (TLNRD1) shares 22% homology with the talin R7R8 rod domains, and is highly conserved throughout vertebrate evolution, although little is known about its function. Here we show that TLNRD1 is an α-helical protein structurally homologous to talin R7R8. Like talin R7R8, TLNRD1 binds F-actin, but because it forms a novel antiparallel dimer, it also bundles F-actin. In addition, it binds the same LD motif-containing proteins, RIAM and KANK, as talin R7R8. In cells, TLNRD1 localizes to actin bundles as well as to filopodia. Increasing TLNRD1 expression enhances filopodia formation and cell migration on 2D substrates, while TLNRD1 down-regulation has the opposite effect. Together, our results suggest that TLNRD1 has retained the diverse interactions of talin R7R8, but has developed distinct functionality as an actin-bundling protein that promotes filopodia assembly.

SISTEMA: A large and standardized collection of transcriptome data sets for human pluripotent stem cell research

Human pluripotent stem cells have ushered in an exciting new era for disease modeling, drug discovery, and cell therapy development. Continued progress toward realizing the potential of human pluripotent stem cells will be facilitated by robust data sets and complementary resources that are easily accessed and interrogated by the stem cell community. In this context, we present SISTEMA, a quality-controlled curated gene expression database, built on a valuable catalog of human pluripotent stem cell lines, and their derivatives for which transcriptomic analyses have been generated using a single experimental pipeline. SISTEMA functions as a one-step resource that will assist the stem cell community to easily evaluate the expression level for genes of interest, while comparing them across different hPSC lines, cell types, pathological conditions, or after pharmacological treatments.

The status of causality in biological databases: data resources and data retrieval possibilities to support logical modeling

Causal molecular interactions represent key building blocks used in computational modeling, where they facilitate the assembly of regulatory networks. Logical regulatory networks can be used to predict biological and cellular behaviors by system perturbations and in silico simulations. Today, broad sets of causal interactions are available in a variety of biological knowledge resources. However, different visions, based on distinct biological interests, have led to the development of multiple ways to describe and annotate causal molecular interactions. It can therefore be challenging to efficiently explore various resources of causal interaction and maintain an overview of recorded contextual information that ensures valid use of the data. This review lists the different types of public resources with causal interactions, the different views on biological processes that they represent, the various data formats they use for data representation and storage, and the data exchange and conversion procedures that are available to extract and download these interactions. This may further raise awareness among the targeted audience, i.e. logical modelers and other scientists interested in molecular causal interactions, but also database managers and curators, about the abundance and variety of causal molecular interaction data, and the variety of tools and approaches to convert them into one interoperable resource.

DES-Tcell is a knowledgebase for exploring immunology-related literature

T-cells are a subtype of white blood cells circulating throughout the body, searching for infected and abnormal cells. They have multifaceted functions that include scanning for and directly killing cells infected with intracellular pathogens, eradicating abnormal cells, orchestrating immune response by activating and helping other immune cells, memorizing encountered pathogens, and providing long-lasting protection upon recurrent infections. However, T-cells are also involved in immune responses that result in organ transplant rejection, autoimmune diseases, and some allergic diseases. To support T-cell research, we developed the DES-Tcell knowledgebase (KB). This KB incorporates text- and data-mined information that can expedite retrieval and exploration of T-cell relevant information from the large volume of published T-cell-related research. This KB enables exploration of data through concepts from 15 topic-specific dictionaries, including immunology-related genes, mutations, pathogens, and pathways. We developed three case studies using DES-Tcell, one of which validates effective retrieval of known associations by DES-Tcell. The second and third case studies focuses on concepts that are common to Grave’s disease (GD) and Hashimoto’s thyroiditis (HT). Several reports have shown that up to 20% of GD patients treated with antithyroid medication develop HT, thus suggesting a possible conversion or shift from GD to HT disease. DES-Tcell found miR-4442 links to both GD and HT, and that miR-4442 possibly targets the autoimmune disease risk factor CD6, which provides potential new knowledge derived through the use of DES-Tcell. According to our understanding, DES-Tcell is the first KB dedicated to exploring T-cell-relevant information via literature-mining, data-mining, and topic-specific dictionaries.

A Curriculum for Genomic Education of Molecular Genetic Pathology Fellows: A Report of the Association for Molecular Pathology Training and Education Committee

Molecular genetic pathology (MGP) is a subspecialty of pathology and medical genetics and genomics. Genomic testing, which we define as that which generates large data sets and interrogates large segments of the genome in a single assay, is increasingly recognized as essential for optimal patient care through precision medicine. The most common genomic testing technologies in clinical laboratories are next-generation sequencing and microarray. It is essential to train in these methods and to consider the data generated in the context of the diagnosis, medical history, and other clinical findings of individual patients. Accordingly, updating the MGP fellowship curriculum to include genomics is timely, important, and challenging. At the completion of training, an MGP fellow should be capable of independently interpreting and signing out results of a wide range of genomic assays and, given the appropriate context and institutional support, of developing and validating new assays in compliance with applicable regulations. The Genomics Task Force of the MGP Program Directors, a working group of the Association for Molecular Pathology Training and Education Committee, has developed a genomics curriculum framework and recommendations specific to the MGP fellowship. These recommendations are presented for consideration and implementation by MGP fellowship programs with the understanding that MGP programs exist in a diversity of clinical practice environments with a spectrum of available resources.