Flexible ordering of antibody class switch and V(D)J joining during B-cell ontogeny.

V(D)J joining is mediated by RAG recombinase during early B-lymphocyte development in the bone marrow (BM). Activation-induced deaminase initiates isotype switching in mature B cells of secondary lymphoid structures. Previous studies questioned the strict ontological partitioning of these processes. We show that pro-B cells undergo robust switching to a subset of immunoglobulin H (IgH) isotypes. Chromatin studies reveal that in pro-B cells, the spatial organization of the Igh locus may restrict switching to this subset of isotypes. We demonstrate that in the BM, V(D)J joining and switching are interchangeably inducible, providing an explanation for the hyper-IgE phenotype of Omenn syndrome.

53BP1 Contributes to Igh Locus Chromatin Topology during Class Switch Recombination.

In B lymphocytes, Ig class switch recombination (CSR) is induced by activation-induced cytidine deaminase, which initiates a cascade of events leading to DNA double-strand break formation in switch (S) regions. Resolution of DNA double-strand breaks proceeds through formation of S-S synaptic complexes. S-S synapsis is mediated by a chromatin loop that spans the C region domain of the Igh locus. S-S junctions are joined via a nonhomologous end joining DNA repair process. CSR occurs via an intrachromosomal looping out and deletion mechanism that is 53BP1 dependent. However, the mechanism by which 53BP1 facilitates deletional CSR and inhibits inversional switching events remains unknown. We report a novel architectural role for 53BP1 in Igh chromatin looping in mouse B cells. Long-range interactions between the Eµ and 3'Eα enhancers are significantly diminished in the absence of 53BP1. In contrast, germline transcript promoter:3'Eα looping interactions are unaffected by 53BP1 deficiency. Furthermore, 53BP1 chromatin occupancy at sites in the Igh locus is B cell specific, is correlated with histone H4 lysine 20 marks, and is subject to chromatin spreading. Thus, 53BP1 is required for three-dimensional organization of the Igh locus and provides a plausible explanation for the link with 53BP1 enforcement of deletional CSR.

Analysis of aggregated cell-cell statistical distances within pathways unveils therapeutic-resistance mechanisms in circulating tumor cells.

MOTIVATION: As 'omics' biotechnologies accelerate the capability to contrast a myriad of molecular measurements from a single cell, they also exacerbate current analytical limitations for detecting meaningful single-cell dysregulations. Moreover, mRNA expression alone lacks functional interpretation, limiting opportunities for translation of single-cell transcriptomic insights to precision medicine. Lastly, most single-cell RNA-sequencing analytic approaches are not designed to investigate small populations of cells such as circulating tumor cells shed from solid tumors and isolated from patient blood samples. RESULTS: In response to these characteristics and limitations in current single-cell RNA-sequencing methodology, we introduce an analytic framework that models transcriptome dynamics through the analysis of aggregated cell-cell statistical distances within biomolecular pathways. Cell-cell statistical distances are calculated from pathway mRNA fold changes between two cells. Within an elaborate case study of circulating tumor cells derived from prostate cancer patients, we develop analytic methods of aggregated distances to identify five differentially expressed pathways associated to therapeutic resistance. Our aggregation analyses perform comparably with Gene Set Enrichment Analysis and better than differentially expressed genes followed by gene set enrichment. However, these methods were not designed to inform on differential pathway expression for a single cell. As such, our framework culminates with the novel aggregation method, cell-centric statistics (CCS). CCS quantifies the effect size and significance of differentially expressed pathways for a single cell of interest. Improved rose plots of differentially expressed pathways in each cell highlight the utility of CCS for therapeutic decision-making. AVAILABILITY AND IMPLEMENTATION: http://www.lussierlab.org/publications/CCS/ CONTACT: yves@email.arizona.edu or piegorsch@math.arizona.edu SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Constraints contributed by chromatin looping limit recombination targeting during Ig class switch recombination.

Engagement of promoters with distal elements in long-range looping interactions has been implicated in regulation of Ig class switch recombination (CSR). The principles determining the spatial and regulatory relationships among Igh transcriptional elements remain poorly defined. We examined the chromosome conformation of C region (CH) loci that are targeted for CSR in a cytokine-dependent fashion in mature B lymphocytes. Germline transcription (GLT) of the γ1 and ε CH loci is controlled by two transcription factors, IL-4-inducible STAT6 and LPS-activated NF-κB. We showed that although STAT6 deficiency triggered loss of GLT, deletion of NF-κB p50 abolished both GLT and γ1 locus:enhancer looping. Thus, chromatin looping between CH loci and Igh enhancers is independent of GLT production and STAT6, whereas the establishment and maintenance of these chromatin contacts requires NF-κB p50. Comparative analysis of the endogenous γ1 locus and a knock-in heterologous promoter in mice identified the promoter per se as the interactive looping element and showed that transcription elongation is dispensable for promoter/enhancer interactions. Interposition of the LPS-responsive heterologous promoter between the LPS-inducible γ3 and γ2b loci altered GLT expression and essentially abolished direct IgG2b switching while maintaining a sequential µâ†’γ3→γ2b format. Our study provides evidence that promoter/enhancer looping interactions can introduce negative constraints on distal promoters and affect their ability to engage in germline transcription and determine CSR targeting.

kMEn: Analyzing noisy and bidirectional transcriptional pathway responses in single subjects.

MOTIVATION: Understanding dynamic, patient-level transcriptomic response to therapy is an important step forward for precision medicine. However, conventional transcriptome analysis aims to discover cohort-level change, lacking the capacity to unveil patient-specific response to therapy. To address this gap, we previously developed two N-of-1-pathways methods, Wilcoxon and Mahalanobis distance, to detect unidirectionally responsive transcripts within a pathway using a pair of samples from a single subject. Yet, these methods cannot recognize bidirectionally (up and down) responsive pathways. Further, our previous approaches have not been assessed in presence of background noise and are not designed to identify differentially expressed mRNAs between two samples of a patient taken in different contexts (e.g. cancer vs non cancer), which we termed responsive transcripts (RTs). METHODS: We propose a new N-of-1-pathways method, k-Means Enrichment (kMEn), that detects bidirectionally responsive pathways, despite background noise, using a pair of transcriptomes from a single patient. kMEn identifies transcripts responsive to the stimulus through k-means clustering and then tests for an over-representation of the responsive genes within each pathway. The pathways identified by kMEn are mechanistically interpretable pathways significantly responding to a stimulus. RESULTS: In ∼9000 simulations varying six parameters, superior performance of kMEn over previous single-subject methods is evident by: (i) improved precision-recall at various levels of bidirectional response and (ii) lower rates of false positives (1-specificity) when more than 10% of genes in the genome are differentially expressed (background noise). In a clinical proof-of-concept, personal treatment-specific pathways identified by kMEn correlate with therapeutic response (p-value<0.01). CONCLUSION: Through improved single-subject transcriptome dynamics of bidirectionally-regulated signals, kMEn provides a novel approach to identify mechanism-level biomarkers.

Dynamic changes of RNA-sequencing expression for precision medicine: N-of-1-pathways Mahalanobis distance within pathways of single subjects predicts breast cancer survival.

MOTIVATION: The conventional approach to personalized medicine relies on molecular data analytics across multiple patients. The path to precision medicine lies with molecular data analytics that can discover interpretable single-subject signals (N-of-1). We developed a global framework, N-of-1-pathways, for a mechanistic-anchored approach to single-subject gene expression data analysis. We previously employed a metric that could prioritize the statistical significance of a deregulated pathway in single subjects, however, it lacked in quantitative interpretability (e.g. the equivalent to a gene expression fold-change). RESULTS: In this study, we extend our previous approach with the application of statistical Mahalanobis distance (MD) to quantify personal pathway-level deregulation. We demonstrate that this approach, N-of-1-pathways Paired Samples MD (N-OF-1-PATHWAYS-MD), detects deregulated pathways (empirical simulations), while not inflating false-positive rate using a study with biological replicates. Finally, we establish that N-OF-1-PATHWAYS-MD scores are, biologically significant, clinically relevant and are predictive of breast cancer survival (P < 0.05, n = 80 invasive carcinoma; TCGA RNA-sequences). CONCLUSION: N-of-1-pathways MD provides a practical approach towards precision medicine. The method generates the magnitude and the biological significance of personal deregulated pathways results derived solely from the patient's transcriptome. These pathways offer the opportunities for deriving clinically actionable decisions that have the potential to complement the clinical interpretability of personal polymorphisms obtained from DNA acquired or inherited polymorphisms and mutations. In addition, it offers an opportunity for applicability to diseases in which DNA changes may not be relevant, and thus expand the 'interpretable 'omics' of single subjects (e.g. personalome). AVAILABILITY AND IMPLEMENTATION: http://www.lussierlab.net/publications/N-of-1-pathways.

eQTL networks unveil enriched mRNA master integrators downstream of complex disease-associated SNPs.

The causal and interplay mechanisms of Single Nucleotide Polymorphisms (SNPs) associated with complex diseases (complex disease SNPs) investigated in genome-wide association studies (GWAS) at the transcriptional level (mRNA) are poorly understood despite recent advancements such as discoveries reported in the Encyclopedia of DNA Elements (ENCODE) and Genotype-Tissue Expression (GTex). Protein interaction network analyses have successfully improved our understanding of both single gene diseases (Mendelian diseases) and complex diseases. Whether the mRNAs downstream of complex disease genes are central or peripheral in the genetic information flow relating DNA to mRNA remains unclear and may be disease-specific. Using expression Quantitative Trait Loci (eQTL) that provide DNA to mRNA associations and network centrality metrics, we hypothesize that we can unveil the systems properties of information flow between SNPs and the transcriptomes of complex diseases. We compare different conditions such as naïve SNP assignments and stringent linkage disequilibrium (LD) free assignments for transcripts to remove confounders from LD. Additionally, we compare the results from eQTL networks between lymphoblastoid cell lines and liver tissue. Empirical permutation resampling (p<0.001) and theoretic Mann-Whitney U test (p<10(-30)) statistics indicate that mRNAs corresponding to complex disease SNPs via eQTL associations are likely to be regulated by a larger number of SNPs than expected. We name this novel property mRNA hubness in eQTL networks, and further term mRNAs with high hubness as master integrators. mRNA master integrators receive and coordinate the perturbation signals from large numbers of polymorphisms and respond to the personal genetic architecture integratively. This genetic signal integration contrasts with the mechanism underlying some Mendelian diseases, where a genetic polymorphism affecting a single protein hub produces a divergent signal that affects a large number of downstream proteins. Indeed, we verify that this property is independent of the hubness in protein networks for which these mRNAs are transcribed. Our findings provide novel insights into the pleiotropy of mRNAs targeted by complex disease polymorphisms and the architecture of the information flow between the genetic polymorphisms and transcriptomes of complex diseases.

Clinical Validation of Mathematically Derived Early Tumor Dynamics for Solid Tumors in Response to Durvalumab.

PURPOSE: Early prediction of response to immunotherapy may help guide patient management by identifying resistance to treatment and allowing adaptation of therapies. This analysis evaluated a mathematical model of response to immunotherapy that provides patient-specific prediction of outcome using the initial change in tumor size/burden from baseline to the first follow-up visit on standard imaging scans. METHODS: We applied the model to 600 patients with advanced solid tumors who received durvalumab in Study 1108, a phase I/II trial, and compared outcome prediction performance versus size-based criteria with RECIST version 1.1 best overall response (BOR), baseline circulating tumor (ct)DNA level, and other clinical/pathologic predictors of immunotherapy response. RESULTS: In multiple solid tumors, the mathematical parameter representing net tumor growth rate at the first on-treatment computed tomography (CT) scan assessed around 6 weeks after starting durvalumab (α1) had a concordance index to predict overall survival (OS) of 0.66-0.77 on multivariate analyses. This measurement of early tumor dynamics significantly improved multivariate OS models that included standard RECIST v1.1 criteria, baseline ctDNA levels, and other clinical/pathologic factors in predicting OS. Furthermore, α1 was assessed consistently at the first on-treatment CT scan, whereas all traditional RECIST BOR groups were confirmed only after this time. CONCLUSION: These results support further exploring α1 as an integral biomarker of response to immunotherapy. This biomarker may be predictive of further benefit and can be assessed before RECIST response groups can be assigned, potentially providing an opportunity to personalize oncologic management.

Clinical and molecular features of acquired resistance to immunotherapy in non-small cell lung cancer.

Although immunotherapy with PD-(L)1 blockade is routine for lung cancer, little is known about acquired resistance. Among 1,201 patients with non-small cell lung cancer (NSCLC) treated with PD-(L)1 blockade, acquired resistance is common, occurring in >60% of initial responders. Acquired resistance shows differential expression of inflammation and interferon (IFN) signaling. Relapsed tumors can be separated by upregulated or stable expression of IFNγ response genes. Upregulation of IFNγ response genes is associated with putative routes of resistance characterized by signatures of persistent IFN signaling, immune dysfunction, and mutations in antigen presentation genes which can be recapitulated in multiple murine models of acquired resistance to PD-(L)1 blockade after in vitro IFNγ treatment. Acquired resistance to PD-(L)1 blockade in NSCLC is associated with an ongoing, but altered IFN response. The persistently inflamed, rather than excluded or deserted, tumor microenvironment of acquired resistance may inform therapeutic strategies to effectively reprogram and reverse acquired resistance.

A Randomized Phase II Study of MEDI0680 in Combination with Durvalumab versus Nivolumab Monotherapy in Patients with Advanced or Metastatic Clear-cell Renal Cell Carcinoma.

PURPOSE: MEDI0680 is a humanized anti-programmed cell death-1 (PD-1) antibody, and durvalumab is an anti-PD-L1 antibody. Combining treatment using these antibodies may improve efficacy versus blockade of PD-1 alone. This phase II study evaluated antitumor activity and safety of MEDI0680 plus durvalumab versus nivolumab monotherapy in immunotherapy-naïve patients with advanced clear-cell renal cell carcinoma who received at least one prior line of antiangiogenic therapy. PATIENTS AND METHODS: Patients received either MEDI0680 (20 mg/kg) with durvalumab (750 mg) or nivolumab (240 mg), all intravenous, every 2 weeks. The primary endpoint was investigator-assessed objective response rate (ORR). Secondary endpoints included best overall response, progression-free survival (PFS), safety, overall survival (OS), and immunogenicity. Exploratory endpoints included changes in circulating tumor DNA (ctDNA), baseline tumor mutational burden, and tumor-infiltrated immune cell profiles. RESULTS: Sixty-three patients were randomized (combination, n = 42; nivolumab, n = 21). ORR was 16.7% [7/42; 95% confidence interval (CI), 7.0-31.4] with combination treatment and 23.8% (5/21; 95% CI, 8.2-47.2) with nivolumab. Median PFS was 3.6 months in both arms; median OS was not reached in either arm. Because of adverse events, 23.8% of patients discontinued MEDI0680 and durvalumab and 14.3% of patients discontinued nivolumab. In the combination arm, reduction in ctDNA fraction was associated with longer PFS. ctDNA mutational analysis did not demonstrate an association with response in either arm. Tumor-infiltrated immune profiles showed an association between immune cell activation and response in the combination arm. CONCLUSIONS: MEDI0680 combined with durvalumab was safe and tolerable; however, it did not improve efficacy versus nivolumab monotherapy.

Design and Efficacy of a Monovalent Bispecific PD-1/CTLA4 Antibody That Enhances CTLA4 Blockade on PD-1+ Activated T Cells.

The clinical benefit of PD-1 blockade can be improved by combination with CTLA4 inhibition but is commensurate with significant immune-related adverse events suboptimally limiting the doses of anti-CTLA4 mAb that can be used. MEDI5752 is a monovalent bispecific antibody designed to suppress the PD-1 pathway and provide modulated CTLA4 inhibition favoring enhanced blockade on PD-1+ activated T cells. We show that MEDI5752 preferentially saturates CTLA4 on PD-1+ T cells versus PD-1- T cells, reducing the dose required to elicit IL2 secretion. Unlike conventional PD-1/CTLA4 mAbs, MEDI5752 leads to the rapid internalization and degradation of PD-1. Moreover, we show that MEDI5752 preferentially localizes and accumulates in tumors providing enhanced activity when compared with a combination of mAbs targeting PD-1 and CTLA4 in vivo. Following treatment with MEDI5752, robust partial responses were observed in two patients with advanced solid tumors. MEDI5752 represents a novel immunotherapy engineered to preferentially inhibit CTLA4 on PD-1+ T cells. SIGNIFICANCE: The unique characteristics of MEDI5752 represent a novel immunotherapy engineered to direct CTLA4 inhibition to PD-1+ T cells with the potential for differentiated activity when compared with current conventional mAb combination strategies targeting PD-1 and CTLA4. This molecule therefore represents a step forward in the rational design of cancer immunotherapy.See related commentary by Burton and Tawbi, p. 1008.This article is highlighted in the In This Issue feature, p. 995.

Tetrameric and homodimeric camelid IgGs originate from the same IgH locus.

In addition to producing conventional tetrameric IgGs, camelids have the particularity of producing a functional homodimeric IgG type lacking L (light) chains and only made up of two H (heavy) chains. This nonconventional IgG type is characterized by variable and constant regions referred to as V(H)H and C(H)H, respectively, and which differ from conventional V(H) and C(H) counterparts. Although the structural properties of homodimeric IgGs have been well investigated, the genetic bases involved in their generation are still largely unknown. In this study, we characterized the organization of genes coding for the H chains of tetrameric and homodimeric IgGs by constructing an alpaca (Lama pacos) genomic cosmid library. We showed that a single IgH locus in alpaca chromosome 4 contains all of the genetic elements required for the generation of the two types of Igs. The alpaca IgH locus is composed of a V region that contains both V(H)H and V(H) genes followed by a unique D(H)-J(H) cluster and C region genes, which include both C(H)H and C(H) genes. Although this general gene organization greatly resembles that of other typical mammalian V(n)-D(n)-J(n)-C(n) translocon IgH loci, the intermixed gene organization within the alpaca V and C regions reveals a new type of translocon IgH locus. Furthermore, analyses of cDNA coding for the membrane forms of IgG and IgM present in alpaca peripheral blood B cells are most consistent with the notion that the development of a B cell bearing homodimeric IgG passes through an IgM(+) stage, similar to the case for conventional IgG.

Single-domain antibodies recognize selectively small oligomeric forms of amyloid beta, prevent Abeta-induced neurotoxicity and inhibit fibril formation.

Neurotoxic oligomers of amyloid beta (Abeta) peptide have been incriminated in the pathogenesis of Alzheimer's disease. Further exploration of this issue has been hampered to this date by the fact that all previously described anti-Abeta antibodies are unable to discriminate between the different conformations of the peptide (oligomers, protofibrils and fibrils). Here, we describe the generation of novel camelid single-chain binding domains (VHHs) that recognizes specifically low molecular-weight (MW) oligomers. Three VHH specific for Abeta were obtained from an immunized alpaca phage display library. Two were able to recognize selectively intraneuronal Abeta oligomers; furthermore, one of them, V31-1, prevented Abeta-induced neurotoxicity and inhibited fibril formation. This study confirms that VHHs may recognize non-conventional epitopes and illustrates their potential for the immunodiagnostic of diseases due to protein accumulation.

Anti-PD-1 monoclonal antibody MEDI0680 in a phase I study of patients with advanced solid malignancies.

BACKGROUND: The safety, efficacy, pharmacokinetics, and pharmacodynamics of the anti-programmed cell death-1 antibody MEDI0680 were evaluated in a phase I, multicenter, dose-escalation study in advanced solid malignancies. METHODS: MEDI0680 was administered intravenously once every 2 weeks (Q2W) or once every 3 weeks at 0.1, 0.5, 2.5, 10 or 20 mg/kg. Two cohorts received 20 mg/kg once a week for 2 or 4 weeks, then 20 mg/kg Q2W. All were treated for 12 months or until progression. The primary endpoint was safety. Secondary endpoints were efficacy and pharmacokinetics. Exploratory endpoints included pharmacodynamics. RESULTS: Fifty-eight patients were treated. Median age was 62.5 years and 81% were male. Most had kidney cancer (n = 36) or melanoma (n = 9). There were no dose-limiting toxicities. Treatment-related adverse events occurred in 83% and were grade ≥ 3 in 21%. Objective clinical responses occurred in 8/58 patients (14%): 5 with kidney cancer, including 1 with a complete response, and 3 with melanoma. The relationship between dose and serum levels was predictable and linear, with apparent receptor saturation at 10 mg/kg Q2W and all 20 mg/kg cohorts. CONCLUSIONS: MEDI0680 induced peripheral T-cell proliferation and increased plasma IFNγ and associated chemokines regardless of clinical response. CD8+ T-cell tumor infiltration and tumoral gene expression of IFNG, CD8A, CXCL9, and granzyme K (GZMK) were also increased following MEDI0680 administration. TRIAL REGISTRATION: NCT02013804 ; date of registration December 12, 2013.

Correction to: 33rd Annual Meeting & Pre-Conference Programs of the Society for Immunotherapy of Cancer (SITC 2018).

After publication of this supplement [1, 2], it was brought to our attention that due to an error authors were missing in the following abstracts. This has now been included in this correction.

Convergent downstream candidate mechanisms of independent intergenic polymorphisms between co-classified diseases implicate epistasis among noncoding elements.

Eighty percent of DNA outside protein coding regions was shown biochemically functional by the ENCODE project, enabling studies of their interactions. Studies have since explored how convergent downstream mechanisms arise from independent genetic risks of one complex disease. However, the cross-talk and epistasis between intergenic risks associated with distinct complex diseases have not been comprehensively characterized. Our recent integrative genomic analysis unveiled downstream biological effectors of disease-specific polymorphisms buried in intergenic regions, and we then validated their genetic synergy and antagonism in distinct GWAS. We extend this approach to characterize convergent downstream candidate mechanisms of distinct intergenic SNPs across distinct diseases within the same clinical classification. We construct a multipartite network consisting of 467 diseases organized in 15 classes, 2,358 disease-associated SNPs, 6,301 SNPassociated mRNAs by eQTL, and mRNA annotations to 4,538 Gene Ontology mechanisms. Functional similarity between two SNPs (similar SNP pairs) is imputed using a nested information theoretic distance model for which p-values are assigned by conservative scale-free permutation of network edges without replacement (node degrees constant). At FDR≤5%, we prioritized 3,870 intergenic SNP pairs associated, among which 755 are associated with distinct diseases sharing the same disease class, implicating 167 intergenic SNPs, 14 classes, 230 mRNAs, and 134 GO terms. Co-classified SNP pairs were more likely to be prioritized as compared to those of distinct classes confirming a noncoding genetic underpinning to clinical classification (odds ratio ∼3.8; p≤10-25). The prioritized pairs were also enriched in regions bound to the same/interacting transcription factors and/or interacting in long-range chromatin interactions suggestive of epistasis (odds ratio ∼ 2,500; p≤10-25). This prioritized network implicates complex epistasis between intergenic polymorphisms of co-classified diseases and offers a roadmap for a novel therapeutic paradigm: repositioning medications that target proteins within downstream mechanisms of intergenic disease-associated SNPs. Supplementary information and software: http://lussiergroup.org/publications/disease_class.

N-of-1-pathways MixEnrich: advancing precision medicine via single-subject analysis in discovering dynamic changes of transcriptomes.

BACKGROUND: Transcriptome analytic tools are commonly used across patient cohorts to develop drugs and predict clinical outcomes. However, as precision medicine pursues more accurate and individualized treatment decisions, these methods are not designed to address single-patient transcriptome analyses. We previously developed and validated the N-of-1-pathways framework using two methods, Wilcoxon and Mahalanobis Distance (MD), for personal transcriptome analysis derived from a pair of samples of a single patient. Although, both methods uncover concordantly dysregulated pathways, they are not designed to detect dysregulated pathways with up- and down-regulated genes (bidirectional dysregulation) that are ubiquitous in biological systems. RESULTS: We developed N-of-1-pathways MixEnrich, a mixture model followed by a gene set enrichment test, to uncover bidirectional and concordantly dysregulated pathways one patient at a time. We assess its accuracy in a comprehensive simulation study and in a RNA-Seq data analysis of head and neck squamous cell carcinomas (HNSCCs). In presence of bidirectionally dysregulated genes in the pathway or in presence of high background noise, MixEnrich substantially outperforms previous single-subject transcriptome analysis methods, both in the simulation study and the HNSCCs data analysis (ROC Curves; higher true positive rates; lower false positive rates). Bidirectional and concordant dysregulated pathways uncovered by MixEnrich in each patient largely overlapped with the quasi-gold standard compared to other single-subject and cohort-based transcriptome analyses. CONCLUSION: The greater performance of MixEnrich presents an advantage over previous methods to meet the promise of providing accurate personal transcriptome analysis to support precision medicine at point of care.

A genome-by-environment interaction classifier for precision medicine: personal transcriptome response to rhinovirus identifies children prone to asthma exacerbations.

OBJECTIVE: To introduce a disease prognosis framework enabled by a robust classification scheme derived from patient-specific transcriptomic response to stimulation. MATERIALS AND METHODS: Within an illustrative case study to predict asthma exacerbation, we designed a stimulation assay that reveals individualized transcriptomic response to human rhinovirus. Gene expression from peripheral blood mononuclear cells was quantified from 23 pediatric asthmatic patients and stimulated in vitro with human rhinovirus. Responses were obtained via the single-subject gene set testing methodology "N-of-1-pathways." The classifier was trained on a related independent training dataset (n = 19). Novel visualizations of personal transcriptomic responses are provided. RESULTS: Of the 23 pediatric asthmatic patients, 12 experienced recurrent exacerbations. Our classifier, using individualized responses and trained on an independent dataset, obtained 74% accuracy (area under the receiver operating curve of 71%; 2-sided P = .039). Conventional classifiers using messenger RNA (mRNA) expression within the viral-exposed samples were unsuccessful (all patients predicted to have recurrent exacerbations; accuracy of 52%). DISCUSSION: Prognosis based on single time point, static mRNA expression alone neglects the importance of dynamic genome-by-environment interplay in phenotypic presentation. Individualized transcriptomic response quantified at the pathway (gene sets) level reveals interpretable signals related to clinical outcomes. CONCLUSION: The proposed framework provides an innovative approach to precision medicine. We show that quantifying personal pathway-level transcriptomic response to a disease-relevant environmental challenge predicts disease progression. This genome-by-environment interaction assay offers a noninvasive opportunity to translate omics data to clinical practice by improving the ability to predict disease exacerbation and increasing the potential to produce more effective treatment decisions.

hMSH2 expression is driven by AP1-dependent regulation through phorbol-ester exposure.

Mammalian mismatch repair (MMR) plays a prominent role in genomic stability and toxicity induced by some DNA damaging agents. Advance in the appreciation of regulation mechanisms of the key MMR protein hMSH2 would certainly lead to valuable information on its role and to a better understanding of MMR system dysfunctions with respect to their consequences in cells. We have previously reported that, in myeloid leukemic U937 cell line, the expression of hMSH2 MMR protein is regulated by protein kinase C (PKC) activity. Here we show that the increase of protein level following PKC activation by phorbol ester (TPA) treatment parallels that of hMSH2 mRNA. Our results support the view that the hMSH2 gene is prone to transcriptional regulation upon TPA induction, and that AP-1 is a factor implicated in the transactivation. When losing the AP-1-dependent hMSH2 promoter activity, either by mutating the AP-1 binding sites of the hMSH2 promoter or by using a dominant negative c-Jun factor, the hMSH2 overexpression induced by TPA is abolished both in vitro and in vivo. Thus the control of hMSH2 expression by PKC appears to be dependent, at least partially, on an up-regulation mediated by AP-1 transactivation.

Integrative genomics analyses unveil downstream biological effectors of disease-specific polymorphisms buried in intergenic regions.

Functionally altered biological mechanisms arising from disease-associated polymorphisms, remain difficult to characterize when those variants are intergenic, or, fall between genes. We sought to identify shared downstream mechanisms by which inter- and intragenic single nucleotide polymorphisms (SNPs) contribute to a specific physiopathology. Using computational modeling of 2 million pairs of disease-associated SNPs drawn from genome wide association studies (GWAS), integrated with expression Quantitative Trait Loci (eQTL) and Gene Ontology functional annotations, we predicted 3,870 inter-intra and inter-intra SNP pairs with convergent biological mechanisms (FDR<0.05). These prioritized SNP pairs with overlapping mRNA targets or similar functional annotations were more likely to be associated with the same disease than unrelated pathologies (OR>12). We additionally confirmed synergistic and antagonistic genetic interactions for a subset of prioritized SNP pairs in independent studies of Alzheimer's disease (entropy p=0.046), bladder cancer (entropy p=0.039), and rheumatoid arthritis (PheWAS case-control p<10-4). Using ENCODE datasets, we further statistically validated that the biological mechanisms shared within prioritized SNP pairs are frequently governed by matching transcription factor binding sites and long-range chromatin interactions. These results provide a "roadmap" of disease mechanisms emerging from GWAS and further identify candidate therapeutic targets among downstream effectors of intergenic SNPs.