Individualization of cancer management requires prognostic markers and therapy-predictive markers. Prognostic markers assess risk of disease progression independent of therapy, whereas therapypredictive markers identify patients whose disease is sensitive or resistant to treatment. We show that an experimentally derived IFN-related DNA damage resistance signature (IRDS) is associated with resistance to chemotherapy and/or radiation across different cancer cell lines. The IRDS genes STAT1, ISG15, and IFIT1 all mediate experimental resistance. Clinical analyses reveal that IRDS(؉) and IRDS(؊) states exist among common human cancers. In breast cancer, a seven-gene-pair classifier predicts for efficacy of adjuvant chemotherapy and for local-regional control after radiation. By providing information on treatment sensitivity or resistance, the IRDS improves outcome prediction when combined with standard markers, risk groups, or other genomic classifiers.

Clinical exome sequencing (CES) has a reported diagnostic yield of 20% to 30% for most clinical indications. The ongoing discovery of novel geneedisease and variantedisease associations are expected to increase the diagnostic yield of CES. Performing systematic reanalysis of previously nondiagnostic CES samples represents a significant challenge for clinical laboratories. Here, we present the results of a novel automated reanalysis methodology applied to 300 CES samples initially analyzed between June 2014 and September 2016. Application of our reanalysis methodology reduced reanalysis variant analysis burden by >93% and correctly captured 70 of 70 previously identified diagnostic variants among 60 samples with previously identified diagnoses. Notably, reanalysis of 240 initially nondiagnostic samples using information available on July 1, 2017, revealed 38 novel diagnoses, representing a 15.8% increase in diagnostic yield. Modeling monthly iterative reanalysis of 240 nondiagnostic samples revealed a diagnostic rate of 0.57% of samples per month. Modeling the workload required for monthly iterative reanalysis of nondiagnostic samples revealed a variant analysis burden of approximately 5 variants/month for proband-only and approximately 0.5 variants/month for trio samples. Approximately 45% of samples required evaluation during each monthly interval, and 61.3% of samples were reevaluated across three consecutive reanalyses. In sum, automated reanalysis methods can facilitate efficient reevaluation of nondiagnostic samples using up-to-date literature and can provide significant value to clinical laboratories. (J Mol Diagn 2019, 21: 38e48; https://doi.

Self-organizing neural organoids represent a promising in vitro platform with which to model human development and disease1–5. However, organoids lack the connectivity that exists in vivo, which limits maturation and makes integration with other circuits that control behaviour impossible. Here we show that human stem cell-derived cortical organoids transplanted into the somatosensory cortex of newborn athymic rats develop mature cell types that integrate into sensory and motivation-related circuits. MRI reveals post-transplantation organoid growth across multiple stem cell lines and animals, whereas single-nucleus profiling shows progression of corticogenesis and the emergence of activity-dependent transcriptional programs. Indeed, transplanted cortical neurons display more complex morphological, synaptic and intrinsic membrane properties than their in vitro counterparts, which enables the discovery of defects in neurons derived from individuals with Timothy syndrome. Anatomical and functional tracings show that transplanted organoids receive thalamocortical and corticocortical inputs, and in vivo recordings of neural activity demonstrate that these inputs can produce sensory responses in human cells. Finally, cortical organoids extend axons throughout the rat brain and their optogenetic activation can drive reward-seeking behaviour. Thus, transplanted human cortical neurons mature and engage host circuits that control behaviour. We anticipate that this approach will be useful for detecting circuit-level phenotypes in patient-derived cells that cannot otherwise be uncovered.

Rhinovirus (RV) is the most prevalent human respiratory virus and is responsible for at least half of all common colds. RV infections may result in a broad spectrum of effects that range from asymptomatic infections to severe lower respiratory illnesses. The basis for inter-individual variation in the response to RV infection is not well understood. In this study, we explored whether host genetic variation is associated with variation in gene expression response to RV infections between individuals. To do so, we obtained genome-wide genotype and gene expression data in uninfected and RV-infected peripheral blood mononuclear cells (PBMCs) from 98 individuals. We mapped local and distant genetic variation that is associated with inter-individual differences in gene expression levels (eQTLs) in both uninfected and RV-infected cells. We focused specifically on response eQTLs (reQTLs), namely, genetic associations with inter-individual variation in gene expression response to RV infection. We identified local reQTLs for 38 genes, including genes with known functions in viral response (UBA7, OAS1, IRF5) and genes that have been associated with immune and RV-related diseases (e.g., ITGA2, MSR1, GSTM3). The putative regulatory regions of genes with reQTLs were enriched for binding sites of virus-activated STAT2, highlighting the role of condition-specific transcription factors in genotype-by-environment interactions. Overall, we suggest that the 38 loci associated with inter-individual variation in gene expression response to RV-infection represent promising candidates for affecting immune and RV-related respiratory diseases.

Summary It is a long-held paradigm that cell fusion reprograms gene expression, but the extent of reprogramming and whether it is affected by the cell types employed remain unknown. We recently showed that the silencing of somatic genes is attributable to either trans-acting cellular environment or cis-acting chromatin context. Here, we examine how trans- versus cis-silenced genes in a somatic cell type behave in fusions to another somatic cell type or to embryonic stem cells (ESCs). We demonstrate that while reprogramming of trans-silenced somatic genes occurs in both types of fusions, reprogramming of cis-silenced somatic genes occurs only in somatic-ESC fusions. Importantly, ESCs reprogram somatic genome in two distinct phases: trans-reprogramming occurs rapidly independent of DNA replication, whereas cis-reprogramming occurs with slow kinetics requiring DNA replication. We also show that pluripotency genes Oct4 and Nanog are cis-silenced in somatic cells. We conclude that cis-reprogramming capacity is a fundamental feature distinguishing ESCs from somatic cells.