MethNet: a robust approach to identify regulatory hubs and their distal targets from cancer data.

Aberrations in the capacity of DNA/chromatin modifiers and transcription factors to bind non-coding regions can lead to changes in gene regulation and impact disease phenotypes. However, identifying distal regulatory elements and connecting them with their target genes remains challenging. Here, we present MethNet, a pipeline that integrates large-scale DNA methylation and gene expression data across multiple cancers, to uncover cis regulatory elements (CREs) in a 1 Mb region around every promoter in the genome. MethNet identifies clusters of highly ranked CREs, referred to as 'hubs', which contribute to the regulation of multiple genes and significantly affect patient survival. Promoter-capture Hi-C confirmed that highly ranked associations involve physical interactions between CREs and their gene targets, and CRISPR interference based single-cell RNA Perturb-seq validated the functional impact of CREs. Thus, MethNet-identified CREs represent a valuable resource for unraveling complex mechanisms underlying gene expression, and for prioritizing the verification of predicted non-coding disease hotspots.

Cellular dynamics in pig-to-human kidney xenotransplantation.

BACKGROUND: Xenotransplantation of genetically engineered porcine organs has the potential to address the challenge of organ donor shortage. Two cases of porcine-to-human kidney xenotransplantation were performed, yet the physiological effects on the xenografts and the recipients' immune responses remain largely uncharacterized. METHODS: We performed single-cell RNA sequencing (scRNA-seq) and longitudinal RNA-seq analyses of the porcine kidneys to dissect xenotransplantation-associated cellular dynamics and xenograft-recipient interactions. We additionally performed longitudinal scRNA-seq of the peripheral blood mononuclear cells (PBMCs) to detect recipient immune responses across time. FINDINGS: Although no hyperacute rejection signals were detected, scRNA-seq analyses of the xenografts found evidence of endothelial cell and immune response activation, indicating early signs of antibody-mediated rejection. Tracing the cells' species origin, we found human immune cell infiltration in both xenografts. Human transcripts in the longitudinal bulk RNA-seq revealed that human immune cell infiltration and the activation of interferon-gamma-induced chemokine expression occurred by 12 and 48 h post-xenotransplantation, respectively. Concordantly, longitudinal scRNA-seq of PBMCs also revealed two phases of the recipients' immune responses at 12 and 48-53 h. Lastly, we observed global expression signatures of xenotransplantation-associated kidney tissue damage in the xenografts. Surprisingly, we detected a rapid increase of proliferative cells in both xenografts, indicating the activation of the porcine tissue repair program. CONCLUSIONS: Longitudinal and single-cell transcriptomic analyses of porcine kidneys and the recipient's PBMCs revealed time-resolved cellular dynamics of xenograft-recipient interactions during xenotransplantation. These cues can be leveraged for designing gene edits and immunosuppression regimens to optimize xenotransplantation outcomes. FUNDING: This work was supported by NIH RM1HG009491 and DP5OD033430.

Inflammation in the tumor-adjacent lung as a predictor of clinical outcome in lung adenocarcinoma.

Approximately 30% of early-stage lung adenocarcinoma patients present with disease progression after successful surgical resection. Despite efforts of mapping the genetic landscape, there has been limited success in discovering predictive biomarkers of disease outcomes. Here we performed a systematic multi-omic assessment of 143 tumors and matched tumor-adjacent, histologically-normal lung tissue with long-term patient follow-up. Through histologic, mutational, and transcriptomic profiling of tumor and adjacent-normal tissue, we identified an inflammatory gene signature in tumor-adjacent tissue as the strongest clinical predictor of disease progression. Single-cell transcriptomic analysis demonstrated the progression-associated inflammatory signature was expressed in both immune and non-immune cells, and cell type-specific profiling in monocytes further improved outcome predictions. Additional analyses of tumor-adjacent transcriptomic data from The Cancer Genome Atlas validated the association of the inflammatory signature with worse outcomes across cancers. Collectively, our study suggests that molecular profiling of tumor-adjacent tissue can identify patients at high risk for disease progression.

MethNet: a robust approach to identify regulatory hubs and their distal targets in cancer.

Aberrations in the capacity of DNA/chromatin modifiers and transcription factors to bind non-coding regions can lead to changes in gene regulation and impact disease phenotypes. However, identifying distal regulatory elements and connecting them with their target genes remains challenging. Here, we present MethNet, a pipeline that integrates large-scale DNA methylation and gene expression data across multiple cancers, to uncover novel cis regulatory elements (CREs) in a 1Mb region around every promoter in the genome. MethNet identifies clusters of highly ranked CREs, referred to as 'hubs', which contribute to the regulation of multiple genes and significantly affect patient survival. Promoter-capture Hi-C confirmed that highly ranked associations involve physical interactions between CREs and their gene targets, and CRISPRi based scRNA Perturb-seq validated the functional impact of CREs. Thus, MethNet-identified CREs represent a valuable resource for unraveling complex mechanisms underlying gene expression, and for prioritizing the verification of predicted non-coding disease hotspots.

Ontogeny and Vulnerabilities of Drug-Tolerant Persisters in HER2+ Breast Cancer.

Resistance to targeted therapies is an important clinical problem in HER2-positive (HER2+) breast cancer. "Drug-tolerant persisters" (DTP), a subpopulation of cancer cells that survive via reversible, nongenetic mechanisms, are implicated in resistance to tyrosine kinase inhibitors (TKI) in other malignancies, but DTPs following HER2 TKI exposure have not been well characterized. We found that HER2 TKIs evoke DTPs with a luminal-like or a mesenchymal-like transcriptome. Lentiviral barcoding/single-cell RNA sequencing reveals that HER2+ breast cancer cells cycle stochastically through a "pre-DTP" state, characterized by a G0-like expression signature and enriched for diapause and/or senescence genes. Trajectory analysis/cell sorting shows that pre-DTPs preferentially yield DTPs upon HER2 TKI exposure. Cells with similar transcriptomes are present in HER2+ breast tumors and are associated with poor TKI response. Finally, biochemical experiments indicate that luminal-like DTPs survive via estrogen receptor-dependent induction of SGK3, leading to rewiring of the PI3K/AKT/mTORC1 pathway to enable AKT-independent mTORC1 activation. SIGNIFICANCE: DTPs are implicated in resistance to anticancer therapies, but their ontogeny and vulnerabilities remain unclear. We find that HER2 TKI-DTPs emerge from stochastically arising primed cells ("pre-DTPs") that engage either of two distinct transcriptional programs upon TKI exposure. Our results provide new insights into DTP ontogeny and potential therapeutic vulnerabilities. This article is highlighted in the In This Issue feature, p. 873.

Microbial signatures in the lower airways of mechanically ventilated COVID-19 patients associated with poor clinical outcome.

Respiratory failure is associated with increased mortality in COVID-19 patients. There are no validated lower airway biomarkers to predict clinical outcome. We investigated whether bacterial respiratory infections were associated with poor clinical outcome of COVID-19 in a prospective, observational cohort of 589 critically ill adults, all of whom required mechanical ventilation. For a subset of 142 patients who underwent bronchoscopy, we quantified SARS-CoV-2 viral load, analysed the lower respiratory tract microbiome using metagenomics and metatranscriptomics and profiled the host immune response. Acquisition of a hospital-acquired respiratory pathogen was not associated with fatal outcome. Poor clinical outcome was associated with lower airway enrichment with an oral commensal (Mycoplasma salivarium). Increased SARS-CoV-2 abundance, low anti-SARS-CoV-2 antibody response and a distinct host transcriptome profile of the lower airways were most predictive of mortality. Our data provide evidence that secondary respiratory infections do not drive mortality in COVID-19 and clinical management strategies should prioritize reducing viral replication and maximizing host responses to SARS-CoV-2.

Microbial signatures in the lower airways of mechanically ventilated COVID19 patients associated with poor clinical outcome.

Mortality among patients with COVID-19 and respiratory failure is high and there are no known lower airway biomarkers that predict clinical outcome. We investigated whether bacterial respiratory infections and viral load were associated with poor clinical outcome and host immune tone. We obtained bacterial and fungal culture data from 589 critically ill subjects with COVID-19 requiring mechanical ventilation. On a subset of the subjects that underwent bronchoscopy, we also quantified SARS-CoV-2 viral load, analyzed the microbiome of the lower airways by metagenome and metatranscriptome analyses and profiled the host immune response. We found that isolation of a hospital-acquired respiratory pathogen was not associated with fatal outcome. However, poor clinical outcome was associated with enrichment of the lower airway microbiota with an oral commensal ( Mycoplasma salivarium ), while high SARS-CoV-2 viral burden, poor anti-SARS-CoV-2 antibody response, together with a unique host transcriptome profile of the lower airways were most predictive of mortality. Collectively, these data support the hypothesis that 1) the extent of viral infectivity drives mortality in severe COVID-19, and therefore 2) clinical management strategies targeting viral replication and host responses to SARS-CoV-2 should be prioritized.

Microbial signatures in the lower airways of mechanically ventilated COVID19 patients associated with poor clinical outcome.

Mortality among patients with COVID-19 and respiratory failure is high and there are no known lower airway biomarkers that predict clinical outcome. We investigated whether bacterial respiratory infections and viral load were associated with poor clinical outcome and host immune tone. We obtained bacterial and fungal culture data from 589 critically ill subjects with COVID-19 requiring mechanical ventilation. On a subset of the subjects that underwent bronchoscopy, we also quantified SARS-CoV-2 viral load, analyzed the microbiome of the lower airways by metagenome and metatranscriptome analyses and profiled the host immune response. We found that isolation of a hospital-acquired respiratory pathogen was not associated with fatal outcome. However, poor clinical outcome was associated with enrichment of the lower airway microbiota with an oral commensal ( Mycoplasma salivarium ), while high SARS-CoV-2 viral burden, poor anti-SARS-CoV-2 antibody response, together with a unique host transcriptome profile of the lower airways were most predictive of mortality. Collectively, these data support the hypothesis that 1) the extent of viral infectivity drives mortality in severe COVID-19, and therefore 2) clinical management strategies targeting viral replication and host responses to SARS-CoV-2 should be prioritized.

Serial single-cell profiling analysis of metastatic TNBC during Nab-paclitaxel and pembrolizumab treatment.

PURPOSE: Immunotherapy has recently been shown to improve outcomes for advanced PD-L1-positive triple-negative breast cancer (TNBC) in the Impassion130 trial, leading to FDA approval of the first immune checkpoint inhibitor in combination with taxane chemotherapy. To further develop predictive biomarkers and improve therapeutic efficacy of the combination, interrogation of the tumor immune microenvironment before therapy as well as during each component of treatment is crucial. Here we use single-cell RNA sequencing (scRNA-seq) on tumor biopsies to assess immune cell changes from two patients with advanced TNBC treated in a prospective trial at predefined serial time points, before treatment, on taxane chemotherapy and on chemo-immunotherapy. METHODS: Both patients (one responder and one progressor) received the trial therapy, in cycle 1 nab-paclitaxel given as single agent, in cycle 2 nab-paclitaxel in combination with pembrolizumab. Tumor core biopsies were obtained at baseline, 3 weeks (after cycle 1, chemotherapy alone) and 6 weeks (after cycle 2, chemo-immunotherapy). Single-cell RNA sequencing (scRNA-seq) of both cancer cells and infiltrating immune cells isolated were performed from fresh tumor core biopsy specimens by 10 × chromium sequencing. RESULTS: ScRNA-seq analysis showed significant baseline heterogeneity of tumor-infiltrating immune cell populations between the two patients as well as modulation of the tumor microenvironment by chemotherapy and immunotherapy. In the responding patient there was a population of PD-1high-expressing T cells which significantly decreased after nab-paclitaxel plus pembrolizumab treatment as well as a presence of tissue-resident memory T cells (TRM). In contrast, tumors from the patient with rapid disease progression showed a prevalent and persistent myeloid compartment. CONCLUSIONS: Our study provides a deep cellular analysis of on-treatment changes during chemo-immunotherapy for advanced TNBC, demonstrating not only feasibility of single-cell analyses on serial tumor biopsies but also the heterogeneity of TNBC and differences in on-treatment changes in responder versus progressor.

Lower Airway Dysbiosis Affects Lung Cancer Progression.

In lung cancer, enrichment of the lower airway microbiota with oral commensals commonly occurs, and ex vivo models support that some of these bacteria can trigger host transcriptomic signatures associated with carcinogenesis. Here, we show that this lower airway dysbiotic signature was more prevalent in the stage IIIB-IV tumor-node-metastasis lung cancer group and is associated with poor prognosis, as shown by decreased survival among subjects with early-stage disease (I-IIIA) and worse tumor progression as measured by RECIST scores among subjects with stage IIIB-IV disease. In addition, this lower airway microbiota signature was associated with upregulation of the IL17, PI3K, MAPK, and ERK pathways in airway transcriptome, and we identified Veillonella parvula as the most abundant taxon driving this association. In a KP lung cancer model, lower airway dysbiosis with V. parvula led to decreased survival, increased tumor burden, IL17 inflammatory phenotype, and activation of checkpoint inhibitor markers. SIGNIFICANCE: Multiple lines of investigation have shown that the gut microbiota affects host immune response to immunotherapy in cancer. Here, we support that the local airway microbiota modulates the host immune tone in lung cancer, affecting tumor progression and prognosis.See related commentary by Zitvogel and Kroemer, p. 224.This article is highlighted in the In This Issue feature, p. 211.

Sequencing identifies multiple early introductions of SARS-CoV-2 to the New York City region.

Effective public response to a pandemic relies upon accurate measurement of the extent and dynamics of an outbreak. Viral genome sequencing has emerged as a powerful approach to link seemingly unrelated cases, and large-scale sequencing surveillance can inform on critical epidemiological parameters. Here, we report the analysis of 864 SARS-CoV-2 sequences from cases in the New York City metropolitan area during the COVID-19 outbreak in spring 2020. The majority of cases had no recent travel history or known exposure, and genetically linked cases were spread throughout the region. Comparison to global viral sequences showed that early transmission was most linked to cases from Europe. Our data are consistent with numerous seeds from multiple sources and a prolonged period of unrecognized community spreading. This work highlights the complementary role of genomic surveillance in addition to traditional epidemiological indicators.

Evidence for Environmental-Human Microbiota Transfer at a Manufacturing Facility with Novel Work-related Respiratory Disease.

Rationale: Workers' exposure to metalworking fluid (MWF) has been associated with respiratory disease.Objectives: As part of a public health investigation of a manufacturing facility, we performed a cross-sectional study using paired environmental and human sampling to evaluate the cross-pollination of microbes between the environment and the host and possible effects on lung pathology present among workers.Methods: Workplace environmental microbiota were evaluated in air and MWF samples. Human microbiota were evaluated in lung tissue samples from workers with respiratory symptoms found to have lymphocytic bronchiolitis and alveolar ductitis with B-cell follicles and emphysema, in lung tissue samples from control subjects, and in skin, nasal, and oral samples from 302 workers from different areas of the facility. In vitro effects of MWF exposure on murine B cells were assessed.Measurements and Main Results: An increased similarity of microbial composition was found between MWF samples and lung tissue samples of case workers compared with control subjects. Among workers in different locations within the facility, those that worked in the machine shop area had skin, nasal, and oral microbiota more closely related to the microbiota present in the MWF samples. Lung samples from four index cases and skin and nasal samples from workers in the machine shop area were enriched with Pseudomonas, the dominant taxa in MWF. Exposure to used MWF stimulated murine B-cell proliferation in vitro, a hallmark cell subtype found in the pathology of index cases.Conclusions: Evaluation of a manufacturing facility with a cluster of workers with respiratory disease supports cross-pollination of microbes from MWF to humans and suggests the potential for exposure to these microbes to be a health hazard.

Sequencing identifies multiple early introductions of SARS-CoV-2 to the New York City Region.

Effective public response to a pandemic relies upon accurate measurement of the extent and dynamics of an outbreak. Viral genome sequencing has emerged as a powerful approach to link seemingly unrelated cases, and large-scale sequencing surveillance can inform on critical epidemiological parameters. Here, we report the analysis of 864 SARS-CoV-2 sequences from cases in the New York City metropolitan area during the COVID-19 outbreak in Spring 2020. The majority of cases had no recent travel history or known exposure, and genetically linked cases were spread throughout the region. Comparison to global viral sequences showed that early transmission was most linked to cases from Europe. Our data are consistent with numerous seeds from multiple sources and a prolonged period of unrecognized community spreading. This work highlights the complementary role of genomic surveillance in addition to traditional epidemiological indicators.

Airway Microbiota Is Associated with Upregulation of the PI3K Pathway in Lung Cancer.

RATIONALE: In lung cancer, upregulation of the PI3K (phosphoinositide 3-kinase) pathway is an early event that contributes to cell proliferation, survival, and tissue invasion. Upregulation of this pathway was recently described as associated with enrichment of the lower airways with bacteria identified as oral commensals. OBJECTIVES: We hypothesize that host-microbe interactions in the lower airways of subjects with lung cancer affect known cancer pathways. METHODS: Airway brushings were collected prospectively from subjects with lung nodules at time of diagnostic bronchoscopy, including 39 subjects with final lung cancer diagnoses and 36 subjects with noncancer diagnoses. In addition, samples from 10 healthy control subjects were included. 16S ribosomal RNA gene amplicon sequencing and paired transcriptome sequencing were performed on all airway samples. In addition, an in vitro model with airway epithelial cells exposed to bacteria/bacterial products was performed. MEASUREMENTS AND MAIN RESULTS: The composition of the lower airway transcriptome in the patients with cancer was significantly different from the control subjects, which included up-regulation of ERK (extracellular signal-regulated kinase) and PI3K signaling pathways. The lower airways of patients with lung cancer were enriched for oral taxa (Streptococcus and Veillonella), which was associated with up-regulation of the ERK and PI3K signaling pathways. In vitro exposure of airway epithelial cells to Veillonella, Prevotella, and Streptococcus led to upregulation of these same signaling pathways. CONCLUSIONS: The data presented here show that several transcriptomic signatures previously identified as relevant to lung cancer pathogenesis are associated with enrichment of the lower airway microbiota with oral commensals.

Discovery of 7-aminofuro[2,3-c]pyridine inhibitors of TAK1: optimization of kinase selectivity and pharmacokinetics.

The kinase selectivity and pharmacokinetic optimization of a series of 7-aminofuro[2,3-c]pyridine inhibitors of TAK1 is described. The intersection of insights from molecular modeling, computational prediction of metabolic sites, and in vitro metabolite identification studies resulted in a simple and unique solution to both of these problems. These efforts culminated in the discovery of compound 13a, a potent, relatively selective inhibitor of TAK1 with good pharmacokinetic properties in mice, which was active in an in vivo model of ovarian cancer.

Discovery and optimization of 7-aminofuro[2,3-c]pyridine inhibitors of TAK1.

The discovery and potency optimization of a series of 7-aminofuro[2,3-c]pyridine inhibitors of TAK1 is described. Micromolar hits taken from high-throughput screening were optimized for biochemical and cellular mechanistic potency to ~10nM, as exemplified by compound 12az. Application of structure-based drug design aided by co-crystal structures of TAK1 with inhibitors significantly shortened the number of iterations required for the optimization.