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Most infants born with very low birth weight (VLBW, birth weight 1500 g) show spontaneous catch-up growth in postnatal life. The reasons for the absence of catch-up growth are not entirely understood. We performed a comprehensive investigation of 52 children born with VLBW. Ten children had a history of an external cause that explained the VLBW and five refused genetic evaluation. Twenty-three cases were initially evaluated by a candidate gene approach. Patients with a negative result in the candidate gene approach (n = 14) or without clinical suspicion (n = 14) were assessed by chromosome microarray analysis (CMA) and/or whole-exome sequencing (WES). A genetic condition was identified in 19 of 37 (51.4%) patients without an external cause, nine by candidate gene approach, and 10 by a genomic approach (CMA/WES). Silver-Russell syndrome was the most frequent diagnosis (n = 5) and the remaining patients were diagnosed with other rare monogenic conditions. Almost all patients with a positive genetic diagnosis exhibited syndromic features (94.4%). However, microcephaly, neurodevelopmental disorders, major malformation, or facial dysmorphism were also frequently observed in children with an external cause. In conclusion, a significant proportion of children born with VLBW with persistent short stature have a genetic/epigenetic condition.

Patients with non-small cell lung cancer (NSCLC) with epidermal growth factor receptor (EGFR) mutations exhibit an unfavorable response to PD-1 inhibitor through unclear mechanisms. Hypothesizing that EGFR mutations alter tumor-immune interactions, we compare tumor-infiltrating lymphocytes between EGFR mutant (EGFR-MT) and wild type (EGFR-WT) tumors through single-cell transcriptomic analysis. We find that B cells, CXCL13-producing follicular helper CD4+ T (TFH)-like cells, and tissue-resident memory CD8+ T (TRM)-like cells decreased in EGFR-MT tumors. The NOTCH-RBPJ regulatory network, which is vital for persistence of TRM state, is perturbed, and the interactions between TFH and B cells through the CXCL13-CXCR5 axis disappear in EGFR-MT tumors. Notably, the proportion of TRM-like cells is predictive for anti-PD-1 response in NSCLC. Our findings suggest that the impairment of TFH-B-TRM cooperation in tertiary lymphoid structure formation, accompanied by the dysregulation of TRM homeostasis and the loss of TFH-B crosstalk, underlies unfavorable anti-PD-1 response in EGFR-MT lung tumors., EGFR mutant lung tumours do not respond favourably to immunotherapy. Here, using single cell sequencing, the authors find that tissue resident memory CD8+ T like cells are reduced in the immune landscape of EGFR mutant tumours in comparison to wild type tumours and the presence of these cells may predict response to immunotherapy.

ObjectiveDysfunctional resolution of intestinal inflammation and altered mucosal healing are essential features in the pathogenesis of inflammatory bowel disease (IBD). Intestinal macrophages are vital in the process of inflammation resolution, but the mechanisms underlying their mucosal healing capacity remain elusive.DesignWe investigated the role of the prostaglandin E2 (PGE2) receptor PTGER4 on the differentiation of intestinal macrophages in patients with IBD and mouse models of intestinal inflammation. We studied mucosal healing and intestinal epithelial barrier regeneration in Csf1r-iCre Ptger4fl/fl mice during dextran sulfate sodium (DSS)-induced colitis. The effect of PTGER4+ macrophage secreted molecules was investigated on epithelial organoid differentiation.ResultsHere, we describe a subset of PTGER4-expressing intestinal macrophages with mucosal healing properties both in humans and mice. Csf1r-iCre Ptger4fl/fl mice showed defective mucosal healing and epithelial barrier regeneration in a model of DSS colitis. Mechanistically, an increased mucosal level of PGE2 triggers chemokine (C-X-C motif) ligand 1 (CXCL1) secretion in monocyte-derived PTGER4+ macrophages via mitogen-activated protein kinases (MAPKs). CXCL1 drives epithelial cell differentiation and proliferation from regenerating crypts during colitis. Specific therapeutic targeting of macrophages with liposomes loaded with an MAPK agonist augmented the production of CXCL1 in vivo in conditional macrophage PTGER4-deficient mice, restoring their defective epithelial regeneration and favouring mucosal healing.ConclusionPTGER4+ intestinal macrophages are essential for supporting the intestinal stem cell niche and regeneration of the injured epithelium. Our results pave the way for the development of a new class of therapeutic targets to promote macrophage healing functions and favour remission in patients with IBD.

Background The diagnostic yield of whole-exome sequencing (WES) varies from 30%–50% among patients with mild to severe neurodevelopmental delay (NDD)/intellectual disability (ID). Routine retrospective reanalysis of undiagnosed patients has increased the total diagnostic yield by 10–15%. Here, we performed proband-only WES of 1065 patients with NDD/ID and applied a prospective, daily reanalysis automated pipeline to patients without clinically significant variants to facilitate diagnoses. Methods The study included 1065 consecutive patients from 1056 nonconsanguineous unrelated families from 10 multimedical centers in South Korea between April 2018 and August 2021. WES data were analyzed daily using automatically updated databases with variant classification and symptom similarity scoring systems. Results At the initial analysis, 402 patients from 1056 unrelated families (38.0%, 402/1,056 families) had a positive genetic diagnosis. Daily prospective, automated reanalysis resulted in the identification of 34 additional diagnostic variants in 31 patients (3%), which increased our molecular diagnostic yield to 41% (433/1056 families). Among these 31 patients, 26 were diagnosed with 23 different diseases that were newly discovered after 2019. The time interval between the first analysis and the molecular diagnosis by reanalysis was 1.2 ± 0.9 years, which was shorter in the patients enrolled during the latter part of the study period. Conclusion Daily updated databases and reanalysis systems enhance the diagnostic performance in patients with NDD/ID, contributing to the rapid diagnosis of undiagnosed patients by applying the latest molecular genetic information.

Dysfunctional resolution of intestinal inflammation and altered mucosal healing are essential features in the pathogenesis of inflammatory bowel disease (IBD). Intestinal macrophages are vital in the process of inflammation resolution, but the mechanisms underlying their mucosal healing capacity remain elusive.We investigated the role of the prostaglandin EHere, we describe a subset of PTGER4-expressing intestinal macrophages with mucosal healing properties both in humans and mice. Csf1r-iCre Ptger4PTGER4

Gene set enrichment analysis (GSEA) is a popular tool to identify underlying biological processes in clinical samples using their gene expression phenotypes. GSEA measures the enrichment of annotated gene sets that represent biological processes for differentially expressed genes (DEGs) in clinical samples. GSEA may be suboptimal for functional gene sets, however, because DEGs from the expression dataset may not be functional genes per se but dysregulated genes perturbed by bona fide functional genes. To overcome this shortcoming, we developed network-based GSEA (NGSEA), which measures the enrichment score of functional gene sets using the expression difference of not only individual genes but also their neighbors in the functional network. We found that NGSEA outperformed GSEA in identifying pathway gene sets for matched gene expression phenotypes. We also observed that NGSEA substantially improved the ability to retrieve known anti-cancer drugs from patient-derived gene expression data using drug-target gene sets compared with another method, Connectivity Map. We also repurposed FDA-approved drugs using NGSEA and experimentally validated budesonide as a chemical with anti-cancer effects for colorectal cancer. We, therefore, expect that NGSEA will facilitate both pathway interpretation of gene expression phenotypes and anti-cancer drug repositioning. NGSEA is freely available at www.inetbio.org/ngsea.

Identifying genes that are capable of inducing tumorigenesis has been a major challenge in cancer research. In many cases, such genes frequently show somatic mutations in tumor samples; thus various computational methods for predicting cancer genes have been developed based on "significantly mutated genes." However, this approach is intrinsically limited by the fact that there are many cancer genes infrequently mutated in cancer genomes. Therefore, we recently developed MUFFINN (Mutations For Functional Impact on Network Neighbors), a method for cancer gene prediction based not only on mutation occurrences in each gene but also those of neighbors in functional networks. This enables the identification of cancer genes with infrequent mutation occurrence. We demonstrated that MUFFINN could retrieve known cancer genes more efficiently than gene-based methods and predicted cancer genes with low mutation occurrences in tumor samples. Users can freely access a web server ( http://www.inetbio.org/muffinn ) and run predictions with either public or private data of cancer somatic mutations. For given information of mutation occurrence profiles, the MUFFINN server returns lists of candidate cancer genes by four distinct predictions with different combinations between gene networks and scoring algorithms. Stand-alone software is also available, which allows MUFFINN to be run on local machines with a custom gene network. Here, we present an overall guideline for using the MUFFINN web server and stand-alone software for the discovery of novel cancer genes.

Identifying genes that are capable of inducing tumorigenesis has been a major challenge in cancer research. In many cases, such genes frequently show somatic mutations in tumor samples; thus various computational methods for predicting cancer genes have been developed based on "significantly mutated genes." However, this approach is intrinsically limited by the fact that there are many cancer genes infrequently mutated in cancer genomes. Therefore, we recently developed MUFFINN (Mutations For Functional Impact on Network Neighbors), a method for cancer gene prediction based not only on mutation occurrences in each gene but also those of neighbors in functional networks. This enables the identification of cancer genes with infrequent mutation occurrence. We demonstrated that MUFFINN could retrieve known cancer genes more efficiently than gene-based methods and predicted cancer genes with low mutation occurrences in tumor samples. Users can freely access a web server ( http://www.inetbio.org/muffinn ) and run predictions with either public or private data of cancer somatic mutations. For given information of mutation occurrence profiles, the MUFFINN server returns lists of candidate cancer genes by four distinct predictions with different combinations between gene networks and scoring algorithms. Stand-alone software is also available, which allows MUFFINN to be run on local machines with a custom gene network. Here, we present an overall guideline for using the MUFFINN web server and stand-alone software for the discovery of novel cancer genes.

Summary Disorders of the biliary epithelium, known as cholangiopathies, cause severe and irreversible liver diseases. The limited accessibility of bile duct precludes modeling of several cholangiocyte-mediated diseases. Therefore, novel approaches for obtaining functional cholangiocytes with high purity are needed. Previous work has shown that the combination of Hnf1β and Foxa3 could directly convert mouse fibroblasts into bipotential hepatic stem cell-like cells, termed iHepSCs. However, the efficiency of converting fibroblasts into iHepSCs is low, and these iHepSCs exhibit extremely low differentiation potential into cholangiocytes, thus hindering the translation of iHepSCs to the clinic. Here, we describe that the expression of Hnf1α and Foxa3 dramatically facilitates the robust generation of iHepSCs. Notably, prolonged in vitro culture of Hnf1α- and Foxa3-derived iHepSCs induces a Notch signaling-mediated secondary conversion into cholangiocyte progenitor-like cells that display dramatically enhanced differentiation capacity into mature cholangiocytes. Our study provides a robust two-step approach for obtaining cholangiocyte progenitor-like cells using defined factors., Graphical Abstract, Highlights • Hnf1α and Foxa3 (1a3) induce robust generation of iHepSCs from fibroblasts • 1a3-derived iHepSCs are transcriptionally closer to LEPCs than 1b3-iHepSCs • Prolonged culture induces Notch-mediated secondary conversion into iCPCs • This study provides the robust two-step approach for obtaining iCPCs, In this article, Han and colleagues revisited the roles of HepSC-specific factors and found that Hnf1α and Foxa3 facilitate the robust conversion into iHepSCs displaying a relatively closer transcriptional pattern with LEPCs. The prolonged in vitro culture of iHepSCs induces Notch-mediated secondary conversion into iCPCs, which could efficiently be differentiated into mature cholangiocytes.

The viral vector-mediated overexpression of the defined transcription factors, Brn4/Pou3f4, Sox2, Klf4, and c-Myc (BSKM), could induce the direct conversion of somatic fibroblasts into induced neural stem cells (iNSCs). However, viral vectors may be randomly integrated into the host genome thereby increasing the risk for undesired genotoxicity, mutagenesis, and tumor formation. Here we describe the generation of integration-free iNSCs from mouse fibroblasts by non-viral episomal vectors containing BSKM. The episomal vector-derived iNSCs (e-iNSCs) closely resemble control NSCs, and iNSCs generated by retrovirus (r-iNSCs) in morphology, gene expression profile, epigenetic status, and self-renewal capacity. The e-iNSCs are functionally mature, as they could differentiate into all the neuronal cell types both in vitro and in vivo. Our study provides a novel concept for generating functional iNSCs using a non-viral, non-integrating, plasmid-based system that could facilitate their biomedical applicability.

Spermatogonial stem cells (SSCs) can spontaneously dedifferentiate into embryonic stem cell (ESC)-like cells, which are designated as multipotent SSCs (mSSCs), without ectopic expression of reprogramming factors. Interestingly, SSCs express key pluripotency genes such as Oct4, Sox2, Klf4 and Myc. Therefore, molecular dissection of mSSC reprogramming may provide clues about novel endogenous reprogramming or pluripotency regulatory factors. Our comparative transcriptome analysis of mSSCs and induced pluripotent stem cells (iPSCs) suggests that they have similar pluripotency states but are reprogrammed via different transcriptional pathways. We identified 53 genes as putative pluripotency regulatory factors using an integrated systems biology approach. We demonstrated a selected candidate, Positive cofactor 4 (Pc4), can enhance the efficiency of somatic cell reprogramming by promoting and maintaining transcriptional activity of the key reprograming factors. These results suggest that Pc4 has an important role in inducing spontaneous somatic cell reprogramming via up-regulation of key pluripotency genes.

The reconstruction of transcriptional regulatory networks (TRNs) is a long-standing challenge in human genetics. Numerous computational methods have been developed to infer regulatory interactions between human transcriptional factors (TFs) and target genes from high-throughput data and their performance evaluation requires gold-standard interactions. Here we present a database of literature-curated human TF-target interactions, TRRUST (transcriptional regulatory relationships unravelled by sentence-based text-mining, http://www.grnpedia.org/trrust), which currently contains 8,015 interactions between 748 TF genes and 1,975 non-TF genes. A sentence-based text-mining approach was employed for efficient manual curation of regulatory interactions from approximately 20 million Medline abstracts. To the best of our knowledge, TRRUST is the largest publicly available database of literature-curated human TF-target interactions to date. TRRUST also has several useful features: i) information about the mode-of-regulation; ii) tests for target modularity of a query TF; iii) tests for TF cooperativity of a query target; iv) inferences about cooperating TFs of a query TF; and v) prioritizing associated pathways and diseases with a query TF. We observed high enrichment of TF-target pairs in TRRUST for top-scored interactions inferred from high-throughput data, which suggests that TRRUST provides a reliable benchmark for the computational reconstruction of human TRNs.