Human lung cancer harbors spatially organized stem-immunity hubs associated with response to immunotherapy

The organization of immune cells in human tumors is not well understood. Immunogenic tumors harbor spatially localized multicellular 'immunity hubs' defined by expression of the T cell-attracting chemokines CXCL10/CXCL11 and abundant T cells. Here, we examined immunity hubs in human pre-immunotherapy lung cancer specimens and found an association with beneficial response to PD-1 blockade. Critically, we discovered the stem-immunity hub, a subtype of immunity hub strongly associated with favorable PD-1-blockade outcome. This hub is distinct from mature tertiary lymphoid structures and is enriched for stem-like TCF7+PD-1+CD8+ T cells, activated CCR7+LAMP3+ dendritic cells and CCL19+ fibroblasts as well as chemokines that organize these cells. Within the stem-immunity hub, we find preferential interactions between CXCL10+ macrophages and TCF7-CD8+ T cells as well as between mature regulatory dendritic cells and TCF7+CD4+ and regulatory T cells. These results provide a picture of the spatial organization of the human intratumoral immune response and its relevance to patient immunotherapy outcomes.

Adipocytes regulate fibroblast function, and their loss contributes to fibroblast dysfunction in inflammatory diseases

Fibroblasts play critical roles in tissue homeostasis, but in pathologic states can drive fibrosis, inflammation, and tissue destruction. In the joint synovium, fibroblasts provide homeostatic maintenance and lubrication. Little is known about what regulates the homeostatic functions of fibroblasts in healthy conditions. We performed RNA sequencing of healthy human synovial tissue and identified a fibroblast gene expression program characterized by enhanced fatty acid metabolism and lipid transport. We found that fat-conditioned media reproduces key aspects of the lipid-related gene signature in cultured fibroblasts. Fractionation and mass spectrometry identified cortisol in driving the healthy fibroblast phenotype, confirmed using glucocorticoid receptor gene ( NR3C1 ) deleted cells. Depletion of synovial adipocytes in mice resulted in loss of the healthy fibroblast phenotype and revealed adipocytes as a major contributor to active cortisol generation via Hsd11 β 1 expression. Cortisol signaling in fibroblasts mitigated matrix remodeling induced by TNFα- and TGFβ, while stimulation with these cytokines repressed cortisol signaling and adipogenesis. Together, these findings demonstrate the importance of adipocytes and cortisol signaling in driving the healthy synovial fibroblast state that is lost in disease.

Spatial analysis of human lung cancer reveals organized immune hubs enriched for stem-like CD8 T cells and associated with immunotherapy response

The organization of immune cells in human tumors is not well understood. Immunogenic tumors harbor spatially-localized multicellular 'immunity hubs' defined by expression of the T cell-attracting chemokines CXCL10/CXCL11 and abundant T cells. Here, we examined immunity hubs in human pre-immunotherapy lung cancer specimens, and found that they were associated with beneficial responses to PD-1-blockade. Immunity hubs were enriched for many interferon-stimulated genes, T cells in multiple differentiation states, and CXCL9/10/11 + macrophages that preferentially interact with CD8 T cells. Critically, we discovered the stem-immunity hub, a subtype of immunity hub strongly associated with favorable PD-1-blockade outcomes, distinct from mature tertiary lymphoid structures, and enriched for stem-like TCF7+PD-1+ CD8 T cells and activated CCR7 + LAMP3 + dendritic cells, as well as chemokines that organize these cells. These results elucidate the spatial organization of the human intratumoral immune response and its relevance to patient immunotherapy outcomes.

Cross-tissue, single-cell stromal atlas identifies shared pathological fibroblast phenotypes in four chronic inflammatory diseases

BACKGROUND

Pro-inflammatory fibroblasts are critical for pathogenesis in rheumatoid arthritis, inflammatory bowel disease, interstitial lung disease, and Sjögren's syndrome and represent a novel therapeutic target for chronic inflammatory disease. However, the heterogeneity of fibroblast phenotypes, exacerbated by the lack of a common cross-tissue taxonomy, has limited our understanding of which pathways are shared by multiple diseases.

METHODS

We profiled fibroblasts derived from inflamed and non-inflamed synovium, intestine, lungs, and salivary glands from affected individuals with single-cell RNA sequencing. We integrated all fibroblasts into a multi-tissue atlas to characterize shared and tissue-specific phenotypes.

FINDINGS

Two shared clusters, CXCL10+CCL19+ immune-interacting and SPARC+COL3A1+ vascular-interacting fibroblasts, were expanded in all inflamed tissues and mapped to dermal analogs in a public atopic dermatitis atlas. We confirmed these human pro-inflammatory fibroblasts in animal models of lung, joint, and intestinal inflammation.

CONCLUSIONS

This work represents a thorough investigation into fibroblasts across organ systems, individual donors, and disease states that reveals shared pathogenic activation states across four chronic inflammatory diseases.

FUNDING

Grant from F. Hoffmann-La Roche (Roche) AG.

A framework for employing longitudinally collected multicenter electronic health records to stratify heterogeneous patient populations on disease history

OBJECTIVE

To facilitate patient disease subset and risk factor identification by constructing a pipeline which is generalizable, provides easily interpretable results, and allows replication by overcoming electronic health records (EHRs) batch effects.

MATERIAL AND METHODS

We used 1872 billing codes in EHRs of 102 880 patients from 12 healthcare systems. Using tools borrowed from single-cell omics, we mitigated center-specific batch effects and performed clustering to identify patients with highly similar medical history patterns across the various centers. Our visualization method (PheSpec) depicts the phenotypic profile of clusters, applies a novel filtering of noninformative codes (Ranked Scope Pervasion), and indicates the most distinguishing features.

RESULTS

We observed 114 clinically meaningful profiles, for example, linking prostate hyperplasia with cancer and diabetes with cardiovascular problems and grouping pediatric developmental disorders. Our framework identified disease subsets, exemplified by 6 "other headache" clusters, where phenotypic profiles suggested different underlying mechanisms: migraine, convulsion, injury, eye problems, joint pain, and pituitary gland disorders. Phenotypic patterns replicated well, with high correlations of ≥0.75 to an average of 6 (2-8) of the 12 different cohorts, demonstrating the consistency with which our method discovers disease history profiles.

DISCUSSION

Costly clinical research ventures should be based on solid hypotheses. We repurpose methods from single-cell omics to build these hypotheses from observational EHR data, distilling useful information from complex data.

CONCLUSION

We establish a generalizable pipeline for the identification and replication of clinically meaningful (sub)phenotypes from widely available high-dimensional billing codes. This approach overcomes datatype problems and produces comprehensive visualizations of validation-ready phenotypes.

Maternal oxytocin administration modulates gene expression in the brains of perinatal mice

OBJECTIVES

Oxytocin (OXT) is widely used to facilitate labor. However, little is known about the effects of perinatal OXT exposure on the developing brain. We investigated the effects of maternal OXT administration on gene expression in perinatal mouse brains.

METHODS

Pregnant C57BL/6 mice were treated with saline or OXT at term (n=6-7/group). Dams and pups were euthanized on gestational day (GD) 18.5 after delivery by C-section. Another set of dams was treated with saline or OXT (n=6-7/group) and allowed to deliver naturally; pups were euthanized on postnatal day 9 (PND9). Perinatal/neonatal brain gene expression was determined using Illumina BeadChip Arrays and real time quantitative PCR. Differential gene expression analyses were performed. In addition, the effect of OXT on neurite outgrowth was assessed using PC12 cells.

RESULTS

Distinct and sex-specific gene expression patterns were identified in offspring brains following maternal OXT administration at term. The microarray data showed that female GD18.5 brains exhibited more differential changes in gene expression compared to male GD18.5 brains. Specifically, Cnot4 and Frmd4a were significantly reduced by OXT exposure in male and female GD18.5 brains, whereas Mtap1b, Srsf11, and Syn2 were significantly reduced only in female GD18.5 brains. No significant microarray differences were observed in PND9 brains. By quantitative PCR, OXT exposure reduced Oxtr expression in female and male brains on GD18.5 and PND9, respectively. PC12 cell differentiation assays revealed that OXT induced neurite outgrowth.

CONCLUSIONS

Prenatal OXT exposure induces sex-specific differential regulation of several nervous system-related genes and pathways with important neural functions in perinatal brains.

Multimodal platform for assessing drug distribution and response in clinical trials

BACKGROUND

Response to targeted therapy varies between patients for largely unknown reasons. Here, we developed and applied an integrative platform using mass spectrometry imaging (MSI), phosphoproteomics, and multiplexed tissue imaging for mapping drug distribution, target engagement, and adaptive response to gain insights into heterogeneous response to therapy.

METHODS

Patient-derived xenograft (PDX) lines of glioblastoma were treated with adavosertib, a Wee1 inhibitor, and tissue drug distribution was measured with MALDI-MSI. Phosphoproteomics was measured in the same tumors to identify biomarkers of drug target engagement and cellular adaptive response. Multiplexed tissue imaging was performed on sister sections to evaluate spatial co-localization of drug and cellular response. The integrated platform was then applied on clinical specimens from glioblastoma patients enrolled in the phase 1 clinical trial.

RESULTS

PDX tumors exposed to different doses of adavosertib revealed intra- and inter-tumoral heterogeneity of drug distribution and integration of the heterogeneous drug distribution with phosphoproteomics and multiplexed tissue imaging revealed new markers of molecular response to adavosertib. Analysis of paired clinical specimens from patients enrolled in the phase 1 clinical trial informed the translational potential of the identified biomarkers in studying patient's response to adavosertib.

CONCLUSIONS

The multimodal platform identified a signature of drug efficacy and patient-specific adaptive responses applicable to preclinical and clinical drug development. The information generated by the approach may inform mechanisms of success and failure in future early phase clinical trials, providing information for optimizing clinical trial design and guiding future application into clinical practice.

Maximizing statistical power to detect differentially abundant cell states with scPOST

To estimate a study design's power to detect differential abundance, we require a framework that simulates many multi-sample single-cell datasets. However, current simulation methods are challenging for large-scale power analyses because they are computationally resource intensive and do not support easy simulation of multi-sample datasets. Current methods also lack modeling of important inter-sample variation, such as the variation in the frequency of cell states between samples that is observed in single-cell data. Thus, we developed single-cell POwer Simulation Tool (scPOST) to address these limitations and help investigators quickly simulate multi-sample single-cell datasets. Users may explore a range of effect sizes and study design choices (such as increasing the number of samples or cells per sample) to determine their effect on power, and thus choose the optimal study design for their planned experiments.

IL-1-driven stromal-neutrophil interactions define a subset of patients with inflammatory bowel disease that does not respond to therapies

Current inflammatory bowel disease (IBD) therapies are ineffective in a high proportion of patients. Combining bulk and single-cell transcriptomics, quantitative histopathology and in situ localization across three cohorts of patients with IBD (total n = 376), we identify coexpressed gene modules within the heterogeneous tissular inflammatory response in IBD that map to distinct histopathological and cellular features (pathotypes). One of these pathotypes is defined by high neutrophil infiltration, activation of fibroblasts and vascular remodeling at sites of deep ulceration. Activated fibroblasts in the ulcer bed display neutrophil-chemoattractant properties that are IL-1R, but not TNF, dependent. Pathotype-associated neutrophil and fibroblast signatures are increased in nonresponders to several therapies across four independent cohorts (total n = 343). The identification of distinct, localized, tissular pathotypes will aid precision targeting of current therapeutics and provides a biological rationale for IL-1 signaling blockade in ulcerating disease.

Efficient and precise single-cell reference atlas mapping with Symphony

Recent advances in single-cell technologies and integration algorithms make it possible to construct comprehensive reference atlases encompassing many donors, studies, disease states, and sequencing platforms. Much like mapping sequencing reads to a reference genome, it is essential to be able to map query cells onto complex, multimillion-cell reference atlases to rapidly identify relevant cell states and phenotypes. We present Symphony ( https://github.com/immunogenomics/symphony ), an algorithm for building large-scale, integrated reference atlases in a convenient, portable format that enables efficient query mapping within seconds. Symphony localizes query cells within a stable low-dimensional reference embedding, facilitating reproducible downstream transfer of reference-defined annotations to the query. We demonstrate the power of Symphony in multiple real-world datasets, including (1) mapping a multi-donor, multi-species query to predict pancreatic cell types, (2) localizing query cells along a developmental trajectory of fetal liver hematopoiesis, and (3) inferring surface protein expression with a multimodal CITE-seq atlas of memory T cells.

IFN-γ and TNF-α drive a CXCL10+ CCL2+ macrophage phenotype expanded in severe COVID-19 lungs and inflammatory diseases with tissue inflammation

BACKGROUND

Immunosuppressive and anti-cytokine treatment may have a protective effect for patients with COVID-19. Understanding the immune cell states shared between COVID-19 and other inflammatory diseases with established therapies may help nominate immunomodulatory therapies.

METHODS

To identify cellular phenotypes that may be shared across tissues affected by disparate inflammatory diseases, we developed a meta-analysis and integration pipeline that models and removes the effects of technology, tissue of origin, and donor that confound cell-type identification. Using this approach, we integrated > 300,000 single-cell transcriptomic profiles from COVID-19-affected lungs and tissues from healthy subjects and patients with five inflammatory diseases: rheumatoid arthritis (RA), Crohn's disease (CD), ulcerative colitis (UC), systemic lupus erythematosus (SLE), and interstitial lung disease. We tested the association of shared immune states with severe/inflamed status compared to healthy control using mixed-effects modeling. To define environmental factors within these tissues that shape shared macrophage phenotypes, we stimulated human blood-derived macrophages with defined combinations of inflammatory factors, emphasizing in particular antiviral interferons IFN-beta (IFN-β) and IFN-gamma (IFN-γ), and pro-inflammatory cytokines such as TNF.

RESULTS

We built an immune cell reference consisting of > 300,000 single-cell profiles from 125 healthy or disease-affected donors from COVID-19 and five inflammatory diseases. We observed a CXCL10+ CCL2+ inflammatory macrophage state that is shared and strikingly abundant in severe COVID-19 bronchoalveolar lavage samples, inflamed RA synovium, inflamed CD ileum, and UC colon. These cells exhibited a distinct arrangement of pro-inflammatory and interferon response genes, including elevated levels of CXCL10, CXCL9, CCL2, CCL3, GBP1, STAT1, and IL1B. Further, we found this macrophage phenotype is induced upon co-stimulation by IFN-γ and TNF-α.

CONCLUSIONS

Our integrative analysis identified immune cell states shared across inflamed tissues affected by inflammatory diseases and COVID-19. Our study supports a key role for IFN-γ together with TNF-α in driving an abundant inflammatory macrophage phenotype in severe COVID-19-affected lungs, as well as inflamed RA synovium, CD ileum, and UC colon, which may be targeted by existing immunomodulatory therapies.

IFN- γ and TNF- α drive a CXCL10 + CCL2 + macrophage phenotype expanded in severe COVID-19 and other diseases with tissue inflammation

Immunosuppressive and anti-cytokine treatment may have a protective effect for patients with COVID-19. Understanding the immune cell states shared between COVID-19 and other inflammatory diseases with established therapies may help nominate immunomodulatory therapies. Using an integrative strategy, we built a reference by meta-analyzing > 300,000 immune cells from COVID-19 and 5 inflammatory diseases including rheumatoid arthritis (RA), Crohn's disease (CD), ulcerative colitis (UC), lupus, and interstitial lung disease. Our cross-disease analysis revealed that an FCN1 + inflammatory macrophage state is common to COVID-19 bronchoalveolar lavage samples, RA synovium, CD ileum, and UC colon. We also observed that a CXCL10 + CCL2 + inflammatory macrophage state is abundant in severe COVID-19, inflamed CD and RA, and expresses inflammatory genes such as GBP1, STAT1 , and IL1B . We found that the CXCL10 + CCL2 + macrophages are transcriptionally similar to blood-derived macrophages stimulated with TNF- α and IFN- γ ex vivo . Our findings suggest that IFN- γ , alongside TNF- α , might be a key driver of this abundant inflammatory macrophage phenotype in severe COVID-19 and other inflammatory diseases, which may be targeted by existing immunomodulatory therapies.

Notch signalling drives synovial fibroblast identity and arthritis pathology

The synovium is a mesenchymal tissue composed mainly of fibroblasts with a lining and sublining that surrounds the joints. In rheumatoid arthritis (RA), the synovial tissue undergoes marked hyperplasia, becomes inflamed and invasive and destroys the joint^1,2. Recently, we and others found that a subset of fibroblasts located in the sublining undergoes major expansion in RA and is linked to disease activity^3,4,5. However, the molecular mechanism by which these fibroblasts differentiate and expand in RA remains unknown. Here, we identified a critical role for NOTCH3 signaling in the differentiation of perivascular and sublining CD90(THY1)+ fibroblasts. Using single cell RNA-sequencing and synovial tissue organoids, we found that NOTCH3 signaling drives both transcriptional and spatial gradients in fibroblasts emanating from vascular endothelial cells outward. In active RA, NOTCH3 and NOTCH target genes are markedly upregulated in synovial fibroblasts. Importantly, genetic deletion of Notch3 or monoclonal antibody-blockade of NOTCH3 signaling attenuates inflammation and prevents joint damage in inflammatory arthritis. Our results indicate that synovial fibroblasts exhibit positional identity regulated by endothelium-derived Notch signaling and that this stromal crosstalk pathway underlies inflammation and pathology in inflammatory arthritis.

Fast, sensitive and accurate integration of single-cell data with Harmony

The emerging diversity of single-cell RNA-seq datasets allows for the full transcriptional characterization of cell types across a wide variety of biological and clinical conditions. However, it is challenging to analyze them together, particularly when datasets are assayed with different technologies, because biological and technical differences are interspersed. We present Harmony (https://github.com/immunogenomics/harmony), an algorithm that projects cells into a shared embedding in which cells group by cell type rather than dataset-specific conditions. Harmony simultaneously accounts for multiple experimental and biological factors. In six analyses, we demonstrate the superior performance of Harmony to previously published algorithms while requiring fewer computational resources. Harmony enables the integration of ~106 cells on a personal computer. We apply Harmony to peripheral blood mononuclear cells from datasets with large experimental differences, five studies of pancreatic islet cells, mouse embryogenesis datasets and the integration of scRNA-seq with spatial transcriptomics data.

Mixed-effects association of single cells identifies an expanded effector CD4+ T cell subset in rheumatoid arthritis

High-dimensional single-cell analyses have improved the ability to resolve complex mixtures of cells from human disease samples; however, identifying disease-associated cell types or cell states in patient samples remains challenging because of technical and interindividual variation. Here, we present mixed-effects modeling of associations of single cells (MASC), a reverse single-cell association strategy for testing whether case-control status influences the membership of single cells in any of multiple cellular subsets while accounting for technical confounders and biological variation. Applying MASC to mass cytometry analyses of CD4⁺ T cells from the blood of rheumatoid arthritis (RA) patients and controls revealed a significantly expanded population of CD4⁺ T cells, identified as CD27^- HLA-DR⁺ effector memory cells, in RA patients (odds ratio, 1.7; P = 1.1 × 10^-3). The frequency of CD27^- HLA-DR⁺ cells was similarly elevated in blood samples from a second RA patient cohort, and CD27^- HLA-DR⁺ cell frequency decreased in RA patients who responded to immunosuppressive therapy. Mass cytometry and flow cytometry analyses indicated that CD27^- HLA-DR⁺ cells were associated with RA (meta-analysis P = 2.3 × 10^-4). Compared to peripheral blood, synovial fluid and synovial tissue samples from RA patients contained about fivefold higher frequencies of CD27^- HLA-DR⁺ cells, which comprised ~10% of synovial CD4⁺ T cells. CD27^- HLA-DR⁺ cells expressed a distinctive effector memory transcriptomic program with T helper 1 (T_H1)- and cytotoxicity-associated features and produced abundant interferon-γ (IFN-γ) and granzyme A protein upon stimulation. We propose that MASC is a broadly applicable method to identify disease-associated cell populations in high-dimensional single-cell data.

Distinct fibroblast subsets drive inflammation and damage in arthritis

The identification of lymphocyte subsets with non-overlapping effector functions has been pivotal to the development of targeted therapies in immune-mediated inflammatory diseases (IMIDs)1,2. However, it remains unclear whether fibroblast subclasses with non-overlapping functions also exist and are responsible for the wide variety of tissue-driven processes observed in IMIDs, such as inflammation and damage3-5. Here we identify and describe the biology of distinct subsets of fibroblasts responsible for mediating either inflammation or tissue damage in arthritis. We show that deletion of fibroblast activation protein-α (FAPα)+ fibroblasts suppressed both inflammation and bone erosions in mouse models of resolving and persistent arthritis. Single-cell transcriptional analysis identified two distinct fibroblast subsets within the FAPα+ population: FAPα+THY1+ immune effector fibroblasts located in the synovial sub-lining, and FAPα+THY1- destructive fibroblasts restricted to the synovial lining layer. When adoptively transferred into the joint, FAPα+THY1- fibroblasts selectively mediate bone and cartilage damage with little effect on inflammation, whereas transfer of FAPα+ THY1+ fibroblasts resulted in a more severe and persistent inflammatory arthritis, with minimal effect on bone and cartilage. Our findings describing anatomically discrete, functionally distinct fibroblast subsets with non-overlapping functions have important implications for cell-based therapies aimed at modulating inflammation and tissue damage.

Lymphocyte innateness defined by transcriptional states reflects a balance between proliferation and effector functions

How innate T cells (ITC), including invariant natural killer T (iNKT) cells, mucosal-associated invariant T (MAIT) cells, and γδ T cells, maintain a poised effector state has been unclear. Here we address this question using low-input and single-cell RNA-seq of human lymphocyte populations. Unbiased transcriptomic analyses uncover a continuous ‘innateness gradient’, with adaptive T cells at one end, followed by MAIT, iNKT, γδ T and natural killer cells at the other end. Single-cell RNA-seq reveals four broad states of innateness, and heterogeneity within canonical innate and adaptive populations. Transcriptional and functional data show that innateness is characterized by pre-formed mRNA encoding effector functions, but impaired proliferation marked by decreased baseline expression of ribosomal genes. Together, our data shed new light on the poised state of ITC, in which innateness is defined by a transcriptionally-orchestrated trade-off between rapid cell growth and rapid effector function.

Innate T cells (ITC) contain many subsets and are poised to promptly respond to antigens and pathogens, but how this poised state is maintained is still unclear. Here the authors perform single-cell RNA-seq to align the various ITC subsets along an ‘innateness gradient’ that is associated with changes in proliferation and effector functions.

Abstract 3423: Determining neoadjuvant cisplatin-based chemosensitivity in muscle invasive bladder cancer through differential gene and miRNA expression analysis

Background: Muscle invasive bladder cancer (MIBC) neoadjuvant responders as opposed to nonresponders demonstrated significantly improved 5-year cancer specific survival and reduced nodal positivity rates. Identification of chemo responsive cohorts would not only facilitate targeted delivery of chemotherapy to those most likely to benefit, but also avoid morbidity and delayed surgical intervention in patients unlikely to derive benefit. We evaluated the role of gene and miRNA expression profiles in initial TURBT (transurethral resection of bladder tumor) specimens of patients before undergoing neoadjuvant chemotherapy and subsequent radical cystectomy. Pathological response at time of cystectomy was used to classify initial TURBT specimens as responders (pT0) versus non-responders (≥pT2). Differential expression of gene and miRNA between the two groups may help stratify patients being considered for neoadjuvant chemotherapy.

Methods: TURBT specimens from patients with MIBC were preserved in FFPE tissue blocks before patients subsequently received cisplatin-based neoadjuvant chemotherapy. A total of 13 pT0 and 17 ≥pT2 patients were selected and matched for age, gender and tumor stage. RNA was extracted from FFPE blocks using an Ambion total nucleic acid isolation kit. mRNA was sequenced using Illumina TruSeq RNA Access Library and NextSeq technology. Gene counts were assessed by ht-seq counts and differential expression using DESeq2. Pathway analysis was performed using GAGE. Differential expression of 754 miRNAs was analyzed using the TaqMan openarray miRNA panel.

Results: In responders, a gene-set enrichment analysis revealed significant upregulation of genes in the hsa00190 pathway (implicated in oxidative phosphorylation), hsa03040(spliceosome function). In non-responders, there was significant upregulation of genes in the hsa04510 pathway (focal adhesion), hsa04512 (ECM-receptor interaction), hsa04310(Wnt signaling), hsa04350(TGF-beta signaling) and hsa04010 (MAPK signaling). For the miRNA analysis, significant upregulation of miR-23a, miR-27a, miR-135b, miR-145, miR-422a was seen in responders, and miR-93, miR-107, miR-339-3p, miR-532 in non-responders. Using a random forest classification, a significant proportion of non-responders were correctly identified compared to responders.

Conclusion: Gene and miRNA expression in initial MIBC TURBT specimens may be used as an aid in predicting neoadjuvant non-responders. Increasing the sample size is needed to further validate our findings and may lead to a successful chemotherapy prediction model.

Citation Format: Neal Murphy*, Paras Shah*, Annette Lee, Thomas Bradley, Manish Vira, Ilya Korsunsky, Andrew Shih, Oksana Yaskiv, Zachary Kozel, Anthony Liew, Houman Khalili, Xinhua Zhu. Determining neoadjuvant cisplatin-based chemosensitivity in muscle invasive bladder cancer through differential gene and miRNA expression analysis [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 3423.

Persons with Chronic Spinal Cord Injury Have Decreased Natural Killer Cell and Increased Toll-Like Receptor/Inflammatory Gene Expression

Infections are the leading cause of death for individuals with traumatic spinal cord injury (SCI). Along with increased infection rates, inflammation is often also observed in persons with chronic SCI. Together, immunological changes post-SCI are also poised to impede neurological recovery and mediate common medical consequences of SCI, including atherogenesis and neuropathic pain. The molecular mechanisms contributing to increased infection susceptibility and inflammation in persons living with SCI are poorly understood. Here, we used tools of functional genomics to perform a pilot study to compare whole-blood gene expression in individuals with chronic SCI (≥1 year from initial injury; N = 31) and uninjured individuals (N = 26). We identified 1815 differentially expressed genes in all SCI participants and 2226 differentially expressed genes in persons with SCI rostral to thoracic level 5, compared to uninjured participants. This included marked downregulation of natural killer cell genes and upregulation of the proinflammatory Toll-like receptor signaling pathway. These data provide novel mechanistic insights into the causes underlying the symptoms of immune dysfunction in individuals living with SCI.

Abstract P2-07-09: Integrative analysis of miRNA and mRNA expression in metastatic versus non-metastatic triple negative breast cancer

Background: Triple Negative Breast Cancer (TNBC) is a subset of breast cancer that is difficult to treat clinically and is characterized by being estrogen receptor (ER) negative, progesterone receptor (PR) negative, and does not overexpress human epidermal growth factor receptor 2 (HER2). Patients with TNBC tend to have a worse prognosis than other breast cancer subtypes.

Methods: We obtained fifteen TNBC sample FFPE tissue blocks with corresponding plasma samples. All samples were from primary tumors; seven samples having metastasized, four samples that had not metastasized and four samples with unknown metastatic status. The total RNA was isolated from FFPE blocks using the RecoverAll Total Nucleic Acid Isolation Protocol. miRNA from plasma was isolated using Ambion's mirVANA kit. The plasma and tissue miRNAs were evaluated using the QuantStudio qPCR platform, capturing ˜750 miRNAs. The mRNA was processed using the TruSeq RNA Access kit and sequenced on the Illumina NextSeq platform. Analysis of the miRNA and mRNA individually was performed using limma and DESeq2 packages, respectively. Gene enrichment analysis of the mRNA expression was done using the GAGE package on KEGG pathways while the integrative analysis was done with sparse Canonical Correlation Analysis (sCCA) using the PMA pacakge.

Results: Analysis of plasma miRNA had four miRNAs with a significant difference in raw p-value (p < 0.05) between metastatic and non-metastatic TNBC; miRNA 708, 483-3p, 518f, and 766; in the tissue there were fifteen miRNA with p < 0.05, with one miR-872 still having significance after adjusting for multiple testing. mRNA had 33 genes being significant after multiple testing correction with several immune KEGG pathways being downregulated in metastatic samples (adjusted p < 0.05). The integrative analysis revealed five microRNA (miR-216, miR-127, miR-370, miR-382, and miR-487b) and 312 gene modules enriched in integrin (Fisher p < 10^-5) and extracellular matrix (Fisher p < 10^-6) signaling.

Conclusions: One of the circulating plasma miRNAs, miR483-3p, has been found to promote tumorigenesis, while miR581f and miR766 have not been reported in cancer to date. Further investigation into these miRNA could provide a feasible biomarker. The downregulation of immune pathways observed within the metastatic TNBC subjects implies immune evasion is of particular importance for metastasis and a targeted immunotherapy may be a viable treatment option. The integrative analysis of the miRNA and mRNA showed an enrichment in pathways previously linked to increased proliferation and chemoresistance, with an increased signal compared to either miRNA or mRNA alone.

Citation Format: Shih AJ, Korsunsky I, Guttadauria B, Bhuiya T, Liew A, Khalili H, Gregersen PK, Lee AT. Integrative analysis of miRNA and mRNA expression in metastatic versus non-metastatic triple negative breast cancer [abstract]. In: Proceedings of the 2017 San Antonio Breast Cancer Symposium; 2017 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2018;78(4 Suppl):Abstract nr P2-07-09.

Novel Method for High-Throughput Full-Length IGHV-D-J Sequencing of the Immune Repertoire from Bulk B-Cells with Single-Cell Resolution

Efficient and accurate high-throughput DNA sequencing of the adaptive immune receptor repertoire (AIRR) is necessary to study immune diversity in healthy subjects and disease-related conditions. The high complexity and diversity of the AIRR coupled with the limited amount of starting material, which can compromise identification of the full biological diversity makes such sequencing particularly challenging. AIRR sequencing protocols often fail to fully capture the sampled AIRR diversity, especially for samples containing restricted numbers of B lymphocytes. Here, we describe a library preparation method for immunoglobulin sequencing that results in an exhaustive full-length repertoire where virtually every sampled B-cell is sequenced. This maximizes the likelihood of identifying and quantifying the entire IGHV-D-J repertoire of a sample, including the detection of rearrangements present in only one cell in the starting population. The methodology establishes the importance of circumventing genetic material dilution in the preamplification phases and incorporates the use of certain described concepts: (1) balancing the starting material amount and depth of sequencing, (2) avoiding IGHV gene-specific amplification, and (3) using Unique Molecular Identifier. Together, this methodology is highly efficient, in particular for detecting rare rearrangements in the sampled population and when only a limited amount of starting material is available.

Two microRNA signatures for malignancy and immune infiltration predict overall survival in advanced epithelial ovarian cancer

MicroRNAs have been established as key regulators of tumor gene expression and as prime biomarker candidates for clinical phenotypes in epithelial ovarian cancer (EOC). We analyzed the coexpression and regulatory structure of microRNAs and their co-localized gene targets in primary tumor tissue of 20 patients with advanced EOC in order to construct a regulatory signature for clinical prognosis. We performed an integrative analysis to identify two prognostic microRNA/mRNA coexpression modules, each enriched for consistent biological functions. One module, enriched for malignancy-related functions, was found to be upregulated in malignant versus benign samples. The second module, enriched for immune-related functions, was strongly correlated with imputed intratumoral immune infiltrates of T cells, natural killer cells, cytotoxic lymphocytes, and macrophages. We validated the prognostic relevance of the immunological module microRNAs in the publicly available The Cancer Genome Atlas data set. These findings provide novel functional roles for microRNAs in the progression of advanced EOC and possible prognostic signatures for survival.

Identification of molecular biomarkers of cisplatin-based chemosensitivity in patients undergoing neoadjuvant chemotherapy for muscle-invasive bladder cancer

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Background: Although survival benefit of cisplatin-based neoadjuvant chemotherapy for muscle-invasive bladder cancer (MIBC) has been demonstrated, a significant proportion of patients do not respond. Identification of chemoresponsive cohorts would avoid morbidity and delayed surgical intervention in patients unlikely to derive benefit. We evaluate the role of miRNA and mRNA expression profiles in initial TURBT specimens of patients who receive neoadjuvant chemotherapy prior to undergoing radical cystectomy. Differences in expression patterns between complete responders (pT0) and nonresponders (pT2 ≤ ) at time of cystectomy may help stratify patients being considered for neoadjuvant chemotherapy. Methods: FFPE tissue was isolated from initial TURBT specimens of patients with clinically localized MIBC treated with cisplatin-based neoadjuvant chemotherapy. Tissue from 9 patients with T2 ≤ disease was compared with specimen from 10 pT0 patients at time of cystectomy specimen. Differential expression of 754 miRNAs and mRNA was analyzed utilizing real time quantitative polymerase chain reaction. miRNA expression profiles were compared between complete responder and nonresponder groups. mRNA in tumor specimen was sequenced from both groups with 76 base pair paired-end reads using NextSeq technology. KEGG Pathway analyses helped identify differential gene expression between complete responders and nonresponders. Results: Significant upregulation of miRNA 1203, miRNA 1304, and miRNA 580 was observed nonresponders versus complete responders. KEGG pathway analysis revealed significant upregulation of the hsa03430 pathway, implicated in DNA mismatch repair, the hsa03420 pathway, implicated in nucleotide excision repair, and the hsa03410 pathway, involved in base excision repair, among pT0 patients. Conclusions: Differential miRNA and mRNA expression within the initial tumor specimen of patients with complete pathologic regression versus progression indicates a possible role in determining-neoadjuvant chemo-sensitivity.

BioNetGen 2.2: advances in rule-based modeling

: BioNetGen is an open-source software package for rule-based modeling of complex biochemical systems. Version 2.2 of the software introduces numerous new features for both model specification and simulation. Here, we report on these additions, discussing how they facilitate the construction, simulation and analysis of larger and more complex models than previously possible.

AVAILABILITY AND IMPLEMENTATION

Stable BioNetGen releases (Linux, Mac OS/X and Windows), with documentation, are available at http://bionetgen.org Source code is available at http://github.com/RuleWorld/bionetgen CONTACT: bionetgen.help@gmail.comSupplementary information: Supplementary data are available at Bioinformatics online.

Systems biology of cancer: a challenging expedition for clinical and quantitative biologists

A systems-biology approach to complex disease (such as cancer) is now complementing traditional experience-based approaches, which have typically been invasive and expensive. The rapid progress in biomedical knowledge is enabling the targeting of disease with therapies that are precise, proactive, preventive, and personalized. In this paper, we summarize and classify models of systems biology and model checking tools, which have been used to great success in computational biology and related fields. We demonstrate how these models and tools have been used to study some of the twelve biochemical pathways implicated in but not unique to pancreatic cancer, and conclude that the resulting mechanistic models will need to be further enhanced by various abstraction techniques to interpret phenomenological models of cancer progression.