Abstract 2837: NR2F1 is a barrier to early dissemination of pre-malignant mammary cells

Cancer cells disseminate during very early and sometimes asymptomatic stages of tumor progression. Granted that biological barriers to tumorigenesis exist, there must also be limiting steps to early dissemination, all of which remain largely unknown. We report that the orphan nuclear receptor NR2F1/COUP-TF1 serves as a barrier to early dissemination. High-resolution intravital imaging revealed that loss of function of NR2F1 in HER2+ early cancer cells increased in vivo dissemination without accelerating mammary tumor formation. NR2F1 expression was positively regulated by the tumor suppressive MMK3/6-p38-MAPK pathway and downregulated by HER2 and Wnt4 oncogenic signaling. NR2F1 downregulation by HER2 in early cancer cells led to decreased E-cadherin expression and β-catenin membrane localization, disorganized laminin 5 deposition, and increased expression of CK14, TWIST1, ZEB1 and PRRX1. Our findings reveal the existence of an inhibitory mechanism of dissemination regulated by NR2F1 downstream of HER2 signaling.

Citation Format: Maria Soledad Sosa, Carolina Rodriguez-Tirado, Nupura Kale, Maria Carlini, Nitisha Shrivastava, Bassem Khalil, Javier Bravo-Cordero, Melissa Alexander, Jiayi Ji. NR2F1 is a barrier to early dissemination of pre-malignant mammary cells [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 2837.

[Heat stress induces neuronal apoptosis by up-regulating endoplasmic reticulum stress pathway]

OBJECTIVE

To explore the role of endoplasmic reticulum stress in heat stress-induced apoptosis of human neuroblastoma SH-SY5Y cells.

OBJECTIVE

SH-SY5Y cells were incubated at 43 ℃ for 2 h followed by further culture at 37 ℃ for 0, 3 h, or 6 h. With the cells cultured at 37 ℃ as the control, the cells exposed to heat stress were examined for morphological changes under optical microscope and changes in cell viability using CCK-8 assay. Flow cytometry was performed for detecting apoptosis of the cells following heat stress, and intracellular Ca²⁺ level in the cells was determined using flow cytometry and immunofluorescence confocal microscopy. The mRNA expression levels of caspase-12, BIP and XBP-1 in the cells were detected using qRT-PCR, and the protein expressions of caspase-12, BIP, P-JNK, JNK and XBP-1 were examined using Western blotting. The effect of pretreatment with 4-PBA on cell apoptosis following heat stress was analyzed with Western blotting.

OBJECTIVE

SH-SY5Y cells showed obvious cell shrinkage immediately after the exposure to heat stress, followed then by gradual cell stretching over time. The cell viability decreased significantly after heat stress (P=0.001), and the intracellular Ca²⁺ level increased significantly at 0 h and gradually recovered the normal level at 3 and 6 h. Heat stress induced significant increase in the protein expression of cleaved caspase-3 and time-dependent increase of caspase-12 (P=0.002) and BIP (P=0.008) expression at both the protein and mRNA levels. The expression of P-JNK/JNK protein increased significantly at 0 h (P=0.003) followed by gradual decrease; the expression levels of XBP-1 protein and mRNA gradually decreased after heat stress (P=0.005, P=0.002). Pretreatment with 4-PBA significantly reduced the expression level of cleaved caspase-3 in SH-SY5Y cells following heat stress.

OBJECTIVE

Heat stress induces apoptosis of SH-SY5Y cells by triggering endoplasmic reticulum stress and the imbalance of intracellular calcium ion homeostasis.

POS0788 CIRCULATING EXOSOMES PROMOTE LUPUS NEPHRITIS IN MRL-LPR MICE

Background:

Systemic Lupus Erythematosus (SLE) is a prototypic autoimmune disease that characterized by the loss of self-tolerance and the production of autoantibodies (autoAbs) [1, 2]. Lupus nephritis (LN), the severe organ-threatening manifestations of SLE, could cause massive damage to patients[3, 4]. Currently, some exosomal microRNAs (miRNAs) are considered as potential biomarkers in SLE. However, the role of exosomal miRNAs in Lupus Nephritis (LN) remains unclear.

Objectives:

The purpose of this study was to investigate molecular mechanism of plasma exosomal miRNAs in the development of Lupus Nephritis.

Methods:

Circulating exosomes were isolated from plasma of patients with LN, SLE without LN (NLN). Plasma exosomes were authenticated by Western Blot, Nanosight Tracking Analysis (NTA) and transmission electron microscopy (TEM). Fluorescence microscopy of co-cultured plasma exosomes and podocytes demonstrated that exosomes were uptaken into podocytes. Moreover, cell apoptosis and the inflammation factors was assessed using Western Blot. We analyzed the expression profiles of miRNAs in LN and NLN exosomes and the expression profiles of mRNAs of podocytes stimulated with LN and NLN exosomes with the help of next generation sequencing (NGS).

Results:

We demonstrate that exosomes derived from LN plasma could be taken by neighboring podocytes and promote the apoptosis of podocytes and the expression of inflammation factors. In addition, the sequencing found that miRNAs were differentially expressed in LN and NLN exosomes and mRNAs were differentially expressed in podocytes stimulated with LN and NLN exosomes.

Conclusion:

LN plasma exosomes have a potency to stimulate the apoptosis of podocytes and the expression of inflammation factors. Moreover, differentially expressed miRNAs in exosomes play a potential role in the development of LN.

References:

[1]T. Colasanti, A. Maselli, F. Conti, M. Sanchez, C. Alessandri, C. Barbati, D. Vacirca, A. Tinari, F. Chiarotti, A. Giovannetti, F. Franconi, G. Valesini, W. Malorni, M. Pierdominici, E. Ortona, Autoantibodies to estrogen receptor α interfere with T lymphocyte homeostasis and are associated with disease activity in systemic lupus erythematosus, Arthritis and rheumatism, 64 (2012) 778-787.

[2]H.A. Al-Shobaili, A.A. Al Robaee, A.A. Alzolibani, Z. Rasheed, Antibodies against 4-hydroxy-2-nonenal modified epitopes recognized chromatin and its oxidized forms: role of chromatin, oxidized forms of chromatin and 4-hydroxy-2-nonenal modified epitopes in the etiopathogenesis of SLE, Disease markers, 33 (2012) 19-34.

[3]A. Kaul, C. Gordon, M.K. Crow, Z. Touma, M.B. Urowitz, R. van Vollenhoven, G. Ruiz-Irastorza, G. Hughes, Systemic lupus erythematosus, Nat Rev Dis Primers, 2 (2016) 16039.

[4]M.G. Tektonidou, A. Dasgupta, M.M. Ward, Risk of End-Stage Renal Disease in Patients With Lupus Nephritis, 1971-2015: A Systematic Review and Bayesian Meta-Analysis, Arthritis & rheumatology (Hoboken, N.J.), 68 (2016) 1432-1441.

Disclosure of Interests:

None declared

OP0073 SINGLE-CELL TRANSCRIPTOMICS UNCOVERS DEFECTIVE BONE MARROW EARLY B CELL DEVELOPMENT IN A SUBSET OF LUPUS PATIENTS ASSOCIATED WITH AGGRAVATED INFLAMMATION

Background:

Systemic lupus erythematosus (SLE) is a systemic autoimmune disease that occurs when the body’s immune system attacks own tissues and organs. B cells play a central role in SLE pathogenesis by producing autoantibodies as well as antibody-independent functions. Peripheral B cell abnormality is well known in lupus patients such as expansions of plasmablasts and atypical memory B cells, which are associated with active diseases. However, little is known about the B cell development in the bone marrow of lupus patients.

Objectives:

We conduct this survey to explore the disorder of the B cell development in the bone marrow of lupus patients.

Methods:

In this study, we have performed the scRNASeq to profile the bone marrow B cell compartment in lupus patients and healthy donors.

Results:

We identified that in a subset of lupus patients, the early B cells (proB and preB cells) were strongly decreased, which were confirmed by flow cytometry in an expanded cohort. Furthermore, bone marrow B cells from these patients showed a strong proinflammatory signature revealed by pathway analysis. Interestingly, BCR repertoire analysis showed that the IGHV-4-34 was highly enriched in these patients, indicating an enhanced B cell tolerance defect. Finally, a panel of proinflammatory cytokines (TNF-a, IL-1a, IL-12p70, IFN-g, et al.) were strongly increased in the bone marrow plasma of these patients compared with early B normal patients and healthy donors, confirming a localized proinflammatory microenvironment.

Conclusion:

Altogether, the current study has revealed that a defective early B cell development in lupus patients is associated with a more severe B cell tolerance defect and aggravated inflammation, which may shed new light on developing novel therapies by targeting relevant pathways.

References:

[1]Min Wang, Hua Chen, Jia Qiu, et al. Antagonizing miR-7 suppresses B cell hyperresponsiveness and inhibits lupus development. J Autoimmun 2020.

[2]A M Jacobi, D M Goldenberg, F Hiepe, et al. Differential effects of epratuzumab on peripheral blood B cells of patients with systemic lupus erythematosus versus normal controls. Ann Rheum Dis, 2008.

Acknowledgements:

This work was funded by Special project of clinical medicine of Nantong University (Grant/Award number: 2019LQ001), National Natural Science Foundation of China (Grant/Award number: 81671616, 81871278 and 82071838).

Disclosure of Interests:

None declared

POS0787 BERBERINE MODULATE LUPUS SYNDROME VIA THE REGULATION OF GUT MICROBIOTA IN MRL/LPR MICE

Background:

Intestinal flora disorder and immune abnormalities have been reported in systemic lupus erythematosus (SLE) patients1,2. Berberine (BBR) showed significant effects in regulating the intestinal flora, repairing gut barriers and regulating immune cells3,4. While few reports mentioned the abnormal gut microbiota and metabolites in Chinese SLE patients.

Objectives:

Our investigation tried to illustrate the relationship between gut microbiota, intestinal metabolites and disease activity in Chinese SLE patients. And the effect of BBR to intestinal dysbacteriosis, multiple organ damages and over-activated immune system in MRL/Lpr mice.

Methods:

16S high-throughput (16S rRNA) sequence, qRT-PCR and gas chromatography technology were used to determine the gut microbiota and metabolites in 104 SLE patients from Affiliated Hospital of Nantong University, China. BBR was orally treated to the MRL/Lpr mice in low, medium and high doses. After 6 weeks treatment, mice were sacrificed. Serum, faeces and organs were collected for further studies.

Results:

Chinese SLE patients showed higher abundance of Bacteroidetes and lower abundance of Firmcutes. The results of qRT-PCR showed high Firmcutes/Bacteroidetes (F/B) ratio of SLE patients. The F/B ratio was negative correlated with SLE disease activity index (SLEDA) score. Almost all the tested short-chain fatty acids (SCFAs) found statistically significant results in SLE and LN (lupus nephritis) patients, especially the propanoic acid and butyric. BBR altered the relative abundance of Bacteroides and Verrucomicrobia and the butyric acid content in colon of MRL/Lpr mice. The increase of tight junction protein also indicated the gut barrier was repaired by BBR. Treg and Tfr cells in spleen and mesenteric lymph node (MLN) were increased. These results revealed a positive therapeutic effect of berberine on SLE from gut microbiota to immune status.

Conclusion:

Our study highlights current status of intestinal dysbacteriosis in Chinese patients with SLE and differences in intestinal metabolites among patients with different disease states. The regulation of intestinal flora and the repairment of gut barrier by intestinal metabolites in BBR treated mice seemed to be the factor that directed the immune responses and disease outcomes. The ultimate goal of our study was to determine the beneficial effects of regulating the gut microbiota on the treatment of SLE. The application of berberine is a relatively safe and convenient way. In the coming investigations, we plan to focus on the study of berberine and its metabolites on intestinal function and systemic immunity.

References:

[1]Guo, M. et al. Alteration in gut microbiota is associated with dysregulation of cytokines and glucocorticoid therapy in systemic lupus erythematosus. Gut microbes11, 1758-1773, doi:10.1080/19490976.2020.1768644 (2020).

[2]Mu, Q. et al. Control of lupus nephritis by changes of gut microbiota. Microbiome5, 73, doi:10.1186/s40168-017-0300-8 (2017).

[3]Habtemariam, S. Berberine pharmacology and the gut microbiota: A hidden therapeutic link. Pharmacological research155, 104722, doi:10.1016/j.phrs.2020.104722 (2020).

[4]Cui, H. et al. Berberine Regulates Treg/Th17 Balance to Treat Ulcerative Colitis Through Modulating the Gut Microbiota in the Colon. Frontiers in pharmacology9, 571, doi:10.3389/fphar.2018.00571 (2018).

Figure 1.

Disclosure of Interests:

None declared

POS0761 INVESTIGATION ON THE EFFECT AND MECHANISM OF ABNORMALLY ACTIVATED CD8+ T CELLS FROM BONE MARROW ON HEMATOPOIETIC STEM CELLS IN PATIENTS WITH SYSTEMIC LUPUS ERYTHEMATOSUS

Background:

SLE is an autoimmune disease characterized by the abnormal function of lymphocytes. The impairment of hematopoietic function of bone marrow participates in its pathogenesis, in which T cells play an important role. However, study on bone marrow T cells in SLE patients is very limited.

Objectives:

This study aims to characterize the phenotype and molecular characteristics of abnormally activated CD8+T cells in bone marrow of SLE patients and explore the mechanism of hematopoietic stem cells (HSCs) reduction caused by the abnormally activated CD8+T cells in bone marrow of patients with SLE.

Methods:

A total of 8 SLE patients and 5 age- and sex-matched controls were recruited in our study. Among them, 3 SLE patients and 4 donors were collected bone marrow and peripheral blood samples for Single-cell RNA sequencing (scRNA-seq) and functional studies. BM and peripheral T cell subsets were measured by flow cytometry. Plasma cytokines and secreted immunoglobulins were detected by Luminex. Disease activity of SLE patients was measured using the SLE Disease Activity Index (SLEDAI). All analyses were performed using R language and Flowjo 9.

Results:

In the present study, SLE patients had increased CD8+T%αβT cells and decreased CD4+T%αβT cells in bone marrow of SLE, compared to healthy controls. A large number of CD38+HLADR+CD8+T cells existed in the bone marrow and peripheral blood of SLE patients. Those patients also showed reduced number of HSCs, and with a downward trend of the numbers of peripheral red blood cells, white blood cells, neutrophils, hemoglobin, and platelets. By scRNA-seq, the CD38+HLADR+CD8+T cells contained high levels of GZMK, GZMA, PRF1, IFNG, and TNF in the bone marrow of SLE patients. the CD38+HLADR+CD8+T cells exhibited significant relationship with HSCs, white blood cells, neutrophils, and platelets.

Conclusion:

These findings demonstrated that the abnormally activated CD8+T cells in bone marrow can reduce the number of HSCs by the expression of killer molecules, which contributes to the impairment of hematopoietic function and the development of SLE. This project focuses on the specific bone marrow T cell subset in SLE. The completement of this project provides information for exploring the mechanism of hematopoiesis involvement.

References:

[1]Anderson E, Shah B, Davidson A, Furie R. Lessons learned from bone marrow failure in systemic lupus erythematosus: Case reports and review of the literature. Semin Arthritis Rheum. 2018;48(1):90-104.

[2]Sun LY, Zhou KX, Feng XB, Zhang HY, Ding XQ, Jin O, Lu LW, Lau CS, Hou YY, Fan LM. Abnormal surface markers expression on bone marrow CD34+cells and correlation with disease activity in patients with systemic lupus erythematosus. Clin Rheumatol. 2007;26(12):2073-2079.

Acknowledgements:

We want to thank Lu Meng, Teng Li, Wei Zhou, and Jiaxin Guo for their assistance with this study.

Disclosure of Interests:

None declared

AB0066 MECHANISMS OF TOTAL SAPONINS OF PANAX JAPONICUS MITIGATES COLLAGEN-INDUCED ARTHRITIS

Background:

Total saponins of Panax japonicus (TSPJ) are extracted from Panax japonicus (T.Nees) C.A.Mey and have achieved a good therapeutic effect in the treatment of rheumatoid arthritis (RA). Unfortunately, the mechanism of TSPJ acting on RA is not clear.

Objectives:

To investigate the potential mechanisms and key targets of TSPJ on RA.

Methods:

The raw data were downloaded from the Gene Expression Omnibus (GEO) database, and the RStudio3.6.1 software was used to identify differentially expressed genes (DEGs). The potential targets of active compounds from TSPJ were predicted by the Pharmmapper and SwissTargetPrediction databases. Based on the overlapping genes, we used Cytoscape 3.7.2 software to construct a protein-protein interactions (PPI) network and to determine the mechanisms of the treatment by Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis. Collagen-induced arthritis (CIA) model was established and treated with different doses of TSPJ. Arthritis index (AI) and histology score were used to evaluate the symptoms of CIA. The levels of vascular endothelial growth factor (VEGF), hypoxia-inducible factor 1 (HIF-1), IL-1β, and IL-17A tested by enzyme linked immunosorbent assay and real time-quantitative Polymerase Chain Reaction.

Results:

A total of 2670 DEGs and 371 TSPJ targets were obtained, including 52 overlapping genes. 41 genes had protein interactions that are used to build the PPI network. The results of the KEGG enrichment analysis included VEGF and HIF-1 signaling pathway. Seven negative correlation genes and 16 positive correlation genes were obtained by correlational analysis of DEGs in VEGF and HIF-1 signaling pathway. SRC proto-oncogene, nonreceptor tyrosine kinase (SRC), and the signal transducer and the activator of transcription 3 (STAT 3) had a higher value of degree in PPI and showed a significant correlation in the pathways; they were regarded as key targets. Compared with the CIA model group, TSPJ significantly decreased the AI and histology scores. Moreover, the expression of VEGF-A, HIF-1α, IL-1β, and IL-17A in serum or spleens significantly reduced in a dose-dependent.

Conclusion:

Present study show that SRC and STAT 3 may be the key targets of TSPJ acting on the VEGF and HIF-1 signaling pathways, thus inhibiting angiogenesis and improving RA.

Disclosure of Interests:

None declared

POS0785 CHANGING EXPRESSION PROFILES OF LONG NONCODING RNAS, MIRNAS, MRNAS AND CIRCULAR RNAS IN LABIAL SALIVARY GLANDS OF PRIMARY SJÖGREN’S SYNDROME (PSS)

Background:

Primary Sjögren’s syndrome (pSS) is a relatively common autoimmune disease characterized by oral and ocular dryness. An increasing number of studies have revealed that long non-coding RNA (lncRNA), miRNA, mRNA and circular RNA (circRNA) contributes to the pathogenesis of autoimmune diseases.

Objectives:

To explore lncRNA, miRNA, mRNA and circRNA expression profiles in labial salivary glands (LSGs) in pSS patients and their biological functions in the regulation of pSS.

Methods:

The expression of 75,550 lncRNAs, 2,318 miRNA, 20,292 mRNAs and 6,877 circRNAs were determined in the LSG of six pSS patients and six healthy controls using microarray experiments. Validation was performed in pSS patients and controls using real-time PCR. LncRNA-mRNA co-expression and gene-pathway networks were constructed using bioinformatics software.

Results:

A total of 599 lncRNAs (upregulated: 279, downregulated: 320), 78 miRNAs (upregulated: 26, downregulated: 52), 615 mRNAs (upregulated: 590, downregulated: 25) and 160 mRNAs (upregulated: 110, downregulated: 50) were differentially expressed in the LSGs of pSS patients. Five of these lncRNAs were validated using real-time PCR. lncRNA HCP5, lncRNA SNHG5, lncRNA IFI44L, lncRNA CMPK2 were significantly upregulated and lncRNA TTYH1 were downregulated in pSS. GO and KEGG biological pathway analysis were performed to predict the functions of differentially expressed lncRNAs and co-expressed potential targeting genes. Subsequently, a ceRNA (lncRNA-miRNA-mRNA) network including 2320 ceRNA pairs was constructed based on predicted miRNAs shared by lncRNAs and mRNAs.

Conclusion:

The expression profile provided a systematic perspective on the potential functions of lncRNAs miRNAs, mRNAs and circRNAs in the pathogenesis of pSS. Therefore, this study will aid in the development of new diagnostic biomarkers and drug therapies.

References:

[1]Le Dantec C, Varin MM, Brooks WH, Pers JO, Youinou P, Renaudineau Y. Epigenetics and Sjogren’s syndrome.Curr Pharm Biotechnol. 2012 Aug;13(10):2046-53.

Disclosure of Interests:

None declared

Effect of first-line pembrolizumab treatment in individuals with advanced non-small cell lung cancer and poor performance status

e18796

Background: There is limited evidence supporting the optimal use of immune checkpoint inhibitors (ICIs) in NSCLC patients with poor performance status (PS), as clinical trials exclude these patients. In this study, we use real-world oncology data to determine the impact of first line pembrolizumab vs. no treatment in high PD(L)-1 expressing cancers in individuals with advanced NSCLC and ECOG PS ≥2. Methods: We performed a retrospective cohort study of patients with advanced NSCLC with ECOG PS ≥2 between 09/01/2014 and 02/18/2020, using the nationwide Flatiron Health electronic health record (EHR)-derived de-identified database. Patients were included if they were PD(L)-1 high (≥50%) and had clinical and treatment information recorded within 90 days of diagnosis. Real-world overall survival (rwOS) was defined as time from diagnosis to death (censored at last EHR activity). Median rwOS was estimated using weighted Kaplan-Meier methods. A marginal Cox structural model with inverse probability of treatment weighting was used to adjust for selection bias and estimate the effectiveness of pembrolizumab. The inverse probability weights were estimated using an ensemble machine learning technique, Super Learner, based on age, gender, race, practice type and smoking history. Adjusted hazard ratios (aHR) were estimated using weighted Cox proportional hazards models. Stratified analysis was conducted by ECOG PS (2 vs >2). Results: 217 (16%) individuals with advanced NSCLC and high PD(L)-1 expression received no treatment, compared to 546 (39%) individuals who received 1L pembrolizumab. The no-treatment group had a lower proportion of ECOG 2 compared to the pembrolizumab group (Table). Median rwOS in the no-treatment group was 2.4 months, compared to 7.1 months in the pembrolizumab group (p<0.001). In unadjusted survival analyses in the entire cohort and in cohorts stratified by ECOG status, treatment with pembrolizumab was associated with a significantly lower risk of death (hazard ratio [HR]: 0.38, 95% Confidence Interval [CI]: 0.31-0.45). In adjusted analyses, individuals treated with pembrolizumab had improved survival (HR: 0.40, 95% CI: 0.35-0.45). Conclusions: Our analysis of real-world clinical oncology data demonstrated that 1L treatment with pembrolizumab was associated with significantly improved rwOS among individuals with ECOG ≥ 2. [Table: see text]

Proteogenomic and metabolomic characterization of human glioblastoma

Glioblastoma (GBM) is the most aggressive nervous system cancer. Understanding its molecular pathogenesis is crucial to improving diagnosis and treatment. Integrated analysis of genomic, proteomic, post-translational modification and metabolomic data on 99 treatment-naive GBMs provides insights to GBM biology. We identify key phosphorylation events (e.g., phosphorylated PTPN11 and PLCG1) as potential switches mediating oncogenic pathway activation, as well as potential targets for EGFR-, TP53-, and RB1-altered tumors. Immune subtypes with distinct immune cell types are discovered using bulk omics methodologies, validated by snRNA-seq, and correlated with specific expression and histone acetylation patterns. Histone H2B acetylation in classical-like and immune-low GBM is driven largely by BRDs, CREBBP, and EP300. Integrated metabolomic and proteomic data identify specific lipid distributions across subtypes and distinct global metabolic changes in IDH-mutated tumors. This work highlights biological relationships that could contribute to stratification of GBM patients for more effective treatment.

Quantile Regression Forests to Identify Determinants of Neighborhood Stroke Prevalence in 500 Cities in the USA: Implications for Neighborhoods with High Prevalence

Stroke exerts a massive burden on the US health and economy. Place-based evidence is increasingly recognized as a critical part of stroke management, but identifying the key determinants of neighborhood stroke prevalence and the underlying effect mechanisms is a topic that has been treated sparingly in the literature. We aim to fill in the research gaps with a study focusing on urban health. We develop and apply analytical approaches to address two challenges. First, domain expertise on drivers of neighborhood-level stroke outcomes is limited. Second, commonly used linear regression methods may provide incomplete and biased conclusions. We created a new neighborhood health data set at census tract level by pooling information from multiple sources. We developed and applied a machine learning-based quantile regression method to uncover crucial neighborhood characteristics for neighborhood stroke outcomes among vulnerable neighborhoods burdened with high prevalence of stroke. Neighborhoods with a larger share of non-Hispanic blacks, older adults, or people with insufficient sleep tended to have a higher prevalence of stroke, whereas neighborhoods with a higher socio-economic status in terms of income and education had a lower prevalence of stroke. The effects of five major determinants varied geographically and were significantly stronger among neighborhoods with high prevalence of stroke. Highly flexible machine learning identifies true drivers of neighborhood cardiovascular health outcomes from wide-ranging information in an agnostic and reproducible way. The identified major determinants and the effect mechanisms can provide important avenues for prioritizing and allocating resources to develop optimal community-level interventions for stroke prevention.

Evaluating the Impact of New York's Executive Order on Face Mask Use on COVID-19 Cases and Mortality: a Comparative Interrupted Times Series Study

BACKGROUND

On April 17, 2020, the State of New York (NY) implemented an Executive Order that requires all people in NY to wear a face mask or covering in public settings where social distancing cannot be maintained. Although the Centers for Disease Control and Prevention recommended face mask use by the general public, there is a lack of evidence on the effect of face mask policies on the spread of COVID-19 at the state level.

OBJECTIVE

To assess the impact of the Executive Order on face mask use on COVID-19 cases and mortality in NY.

DESIGN

A comparative interrupted time series analysis was used to assess the impact of the Executive Order in NY with Massachusetts (MA) as a comparison state.

PARTICIPANTS

We analyzed data on COVID-19 in NY and MA from March 25 to May 6, 2020.

INTERVENTION

The Executive Order on face mask use in NY.

MAIN MEASURES

Daily numbers of COVID-19 confirmed cases and deaths.

KEY RESULTS

The average daily number of confirmed cases in NY decreased from 8549 to 5085 after the Executive Order took effect, with a trend change of 341 (95% CI, 187-496) cases per day. The average daily number of deaths decreased from 521 to 384 during the same two time periods, with a trend change of 52 (95% CI, 44-60) deaths per day. Compared to MA, the decreasing trend in NY was significantly greater for both daily numbers of confirmed cases (P = 0.003) and deaths (P < 0.001).

CONCLUSIONS

The Executive Order on face mask use in NY led to a significant decrease in both daily numbers of COVID-19 confirmed cases and deaths. Findings from this study provide important evidence to support state-level policies that require face mask use by the general public.

Proteogenomic insights into the biology and treatment of HPV-negative head and neck squamous cell carcinoma

We present a proteogenomic study of 108 human papilloma virus (HPV)-negative head and neck squamous cell carcinomas (HNSCCs). Proteomic analysis systematically catalogs HNSCC-associated proteins and phosphosites, prioritizes copy number drivers, and highlights an oncogenic role for RNA processing genes. Proteomic investigation of mutual exclusivity between FAT1 truncating mutations and 11q13.3 amplifications reveals dysregulated actin dynamics as a common functional consequence. Phosphoproteomics characterizes two modes of EGFR activation, suggesting a new strategy to stratify HNSCCs based on EGFR ligand abundance for effective treatment with inhibitory EGFR monoclonal antibodies. Widespread deletion of immune modulatory genes accounts for low immune infiltration in immune-cold tumors, whereas concordant upregulation of multiple immune checkpoint proteins may underlie resistance to anti-programmed cell death protein 1 monotherapy in immune-hot tumors. Multi-omic analysis identifies three molecular subtypes with high potential for treatment with CDK inhibitors, anti-EGFR antibody therapy, and immunotherapy, respectively. Altogether, proteogenomics provides a systematic framework to inform HNSCC biology and treatment.

Genome-Wide Identification and Characterization of Calcium-Dependent Protein Kinase (CDPK) and CDPK-Related Kinase (CRK) Gene Families in Medicago truncatula

Calcium-dependent protein kinase (CDPK or CPK) and CDPK-related kinase (CRK) play an important role in plant growth, development, and adaptation to environmental stresses. However, their gene families had been yet inadequately investigated in Medicago truncatula. In this study, six MtCRK genes were computationally identified, they were classified into five groups with MtCDPKs based on phylogenetic relationships. Six pairs of segmental duplications were observed in MtCDPK and MtCRK genes and the Ka/Ks ratio, an indicator of selection pressure, was below 0.310, indicating that these gene pairs underwent strong purifying selection. Cis-acting elements of morphogenesis, multiple hormone responses, and abiotic stresses were predicted in the promoter region. The spatial expression of MtCDPKs and MtCRKs displays diversity. The expression of MtCDPKs and MtCRKs could be regulated by various stresses. MtCDPK4, 14, 16, 22, and MtCRK6 harbor both N-myristoylation site and palmitoylation site and were anchored on plasma membrane, while MtCDPK7, 9, and 15 contain no or only one N-acylation site and were distributed in cytosol and nucleus, suggesting that the N-terminal acylation sites play a key role in subcellular localization of MtCDPKs and MtCRKs. In summary, comprehensive characterization of MtCDPKs and MtCRKs provide a subset of candidate genes for further functional analysis and genetic improvement against drought, cold, salt and biotic stress.

Machine learning identifies novel blood protein predictors of penetrating and stricturing complications in newly diagnosed paediatric Crohn's disease

BACKGROUND

There is a need for improved risk stratification in Crohn's disease.

AIM

To identify novel blood protein biomarkers associated with future Crohn's disease complications METHODS: We performed a case-cohort study utilising a paediatric inception cohort, the Risk Stratification and Identification of Immunogenetic and Microbial Markers of Rapid Disease Progression in Children with Crohn's disease (RISK) study. All patients had inflammatory disease (B1) at baseline. Outcomes were development of stricturing (B2) or penetrating (B3) complications. We assayed 92 inflammation-related proteins in baseline plasma using a proximity extension assay (Olink Proteomics). An ensemble machine learning technique, random survival forests (RSF), selected variables predicting B2 and B3 complications. Selected analytes were compared to clinical variables and serology only models. We examined selected proteins in a single-cell sequencing cohort to analyse differential cell expression in blood and ileum.

RESULTS

We included 265 patients with mean age 11.6 years (standard deviation [SD] 3.2). Seventy-three and 34 patients, respectively, had B2 and B3 complications within mean 1123 (SD 477) days for B2 and 1251 (442) for B3. A model with 5 protein markers predicted B3 complications with an area under the curve (AUC) of 0.79 (95% confidence interval [CI] 0.76-0.82) compared to 0.69 (95% CI 0.66-0.72) for serologies and 0.74 (95% CI 0.71-0.77) for clinical variables. A model with 4 protein markers predicted B2 complications with an AUC of 0.68 (95% CI 0.65-0.71) compared to 0.62 (95% CI 0.59-0.65) for serologies and 0.52 (95% CI 0.50-0.55) for clinical variables. B2 analytes were highly expressed in ileal stromal cells while B3 analytes were prominent in peripheral blood and ileal T cells.

CONCLUSIONS

We identified novel blood proteomic markers, distinct for B2 and B3, associated with progression of paediatric Crohn's disease.

Epigenetic differences in the innate response after immune stimulation during zebrafish sex differentiation

Infections are able to trigger epigenetic modifications; however, epigenetic-mediating infections in the immune system in fish is currently unavailable. Within this purpose, zebrafish were immune-stimulated with three lipopolysaccharides (LPS) during sex differentiation. Methylation patterns of three immune genes were studied by a candidate gene approach together with gene expression analysis, and in adulthood, sex ratios were determined. It was shown that the entrance of LPS was through the gills and accumulated in the pronephros. Significant hypomethylation levels of CASP9 and a significant CpG site for IL1β after Pseudomonas aeruginosa LPS exposure were found. No methylation difference was observed for TNFα. Gene expression and correlation data differed among studied genes. Sex ratios showed a feminization in dose and LPS strain-dependent manner. Here, it is provided epigenetic regulatory mechanisms derived by innate response and the first evidence of possible epigenetic interactions between the immune and reproductive systems.

Integrated Proteogenomic Characterization across Major Histological Types of Pediatric Brain Cancer

We report a comprehensive proteogenomics analysis, including whole-genome sequencing, RNA sequencing, and proteomics and phosphoproteomics profiling, of 218 tumors across 7 histological types of childhood brain cancer: low-grade glioma (n = 93), ependymoma (32), high-grade glioma (25), medulloblastoma (22), ganglioglioma (18), craniopharyngioma (16), and atypical teratoid rhabdoid tumor (12). Proteomics data identify common biological themes that span histological boundaries, suggesting that treatments used for one histological type may be applied effectively to other tumors sharing similar proteomics features. Immune landscape characterization reveals diverse tumor microenvironments across and within diagnoses. Proteomics data further reveal functional effects of somatic mutations and copy number variations (CNVs) not evident in transcriptomics data. Kinase-substrate association and co-expression network analysis identify important biological mechanisms of tumorigenesis. This is the first large-scale proteogenomics analysis across traditional histological boundaries to uncover foundational pediatric brain tumor biology and inform rational treatment selection.

TBIO-19. INTEGRATED GENOMIC, PROTEOMIC AND PHOSPHOPROTEOMIC ANALYSIS OF SEVEN TYPES OF PEDIATRIC BRAIN CANCER

We performed a comprehensive proteogenomic analysis across seven childhood brain tumors for a deeper understanding of their functional biology. Whole genome sequencing, RNAseq, quantitative proteomic profiling and phosphoproteomics were performed on 219 fresh frozen tumor samples representing the histologic diagnoses of: low grade astrocytoma (93), ependymoma (32), high grade astrocytoma (26), medulloblastoma (22), ganglioglioma (18), craniopharyngioma (16) and atypical teratoid rhabdoid tumor (12). Unsupervised clustering analysis based on proteomics data reveals eight clusters with distinct protein profiles and pathway activities. While some clusters coincide with histologic diagnoses, a couple of clusters appear to be a mixture of different diagnoses, including one cluster consisting of “aggressive” tumors characterized by poor survival and high stemness scores. By integrating proteomic data with RNAseq and WGS data, we characterize the impact of mutations (H3K27M, BRAFV600E, BRAF fusion) and CNVs upon the proteome across various diagnoses. Multiomics based kinase-substrate association analysis and co-expression network analysis reveal targetable active kinase networks within these tumors. Proteomic data reveals unique biology associated with H3K27M mutation status in HGG and BRAF aberrations in LGG. Characterization of the tumor microenvironment through deconvolution analyses based on multi-omics data reveals 5 distinct tumor clusters associated with different populations of infiltrating immune cells and the relative activity of the immune system based upon the expression of pro-inflammation or immunosuppressive markers. This study reports the first large-scale deep comprehensive proteogenomic analysis crossing traditional histologic boundaries to uncover foundational pediatric brain tumor biology including functional insight that helps drive translational efforts.

Identifying and understanding determinants of high healthcare costs for breast cancer: a quantile regression machine learning approach

BACKGROUND

To identify and rank the importance of key determinants of high medical expenses among breast cancer patients and to understand the underlying effects of these determinants.

METHODS

The Oncology Care Model (OCM) developed by the Center for Medicare & Medicaid Innovation were used. The OCM data provided to Mount Sinai on 2938 breast-cancer episodes included both baseline periods and three performance periods between Jan 1, 2012 and Jan 1, 2018. We included 11 variables representing information on treatment, demography and socio-economics status, in addition to episode expenditures. OCM data were collected from participating practices and payers. We applied a principled variable selection algorithm using a flexible tree-based machine learning technique, Quantile Regression Forests.

RESULTS

We found that the use of chemotherapy drugs (versus hormonal therapy) and interval of days without chemotherapy predominantly affected medical expenses among high-cost breast cancer patients. The second-tier major determinants were comorbidities and age. Receipt of surgery or radiation, geographically adjusted relative cost and insurance type were also identified as important high-cost drivers. These factors had disproportionally larger effects upon the high-cost patients.

CONCLUSIONS

Data-driven machine learning methods provide insights into the underlying web of factors driving up the costs for breast cancer care management. Results from our study may help inform population health management initiatives and allow policymakers to develop tailored interventions to meet the needs of those high-cost patients and to avoid waste of scarce resource.

Machine learning to identify and understand key factors for provider-patient discussions about smoking

We sought to identify key determinants of the likelihood of provider-patient discussions about smoking and to understand the effects of these determinants. We used data on 3666 self-reported current smokers who talked to a health professional within a year of the time the survey was conducted using the 2017 National Health Interview Survey. We included wide-ranging information on 43 potential covariates across four domains, demographic and socio-economic status, behavior, health status and healthcare utilization. We exploited a principled nonparametric permutation based approach using Bayesian machine learning to identify and rank important determinants of discussions about smoking between health providers and patients. In the order of importance, frequency of doctor office visits, intensity of cigarette use, length of smoking history, chronic obstructive pulmonary disease, emphysema, marital status were major determinants of disparities in provider-patient discussions about smoking. There was a distinct interaction between intensity of cigarette use and length of smoking history. Our analysis may provide some insights into strategies for promoting discussions on smoking and facilitating smoking cessation. Health care resource usage, smoking intensity and duration and smoking-related conditions were key drivers. The "usual suspects", age, gender, race and ethnicity were less important, and gender, in particular, had little effect.

Tree-Based Machine Learning to Identify and Understand Major Determinants for Stroke at the Neighborhood Level

Background

Stroke is a major cardiovascular disease that causes significant health and economic burden in the United States. Neighborhood community‐based interventions have been shown to be both effective and cost‐effective in preventing cardiovascular disease. There is a dearth of robust studies identifying the key determinants of cardiovascular disease and the underlying effect mechanisms at the neighborhood level. We aim to contribute to the evidence base for neighborhood cardiovascular health research.

Methods and Results

We created a new neighborhood health data set at the census tract level by integrating 4 types of potential predictors, including unhealthy behaviors, prevention measures, sociodemographic factors, and environmental measures from multiple data sources. We used 4 tree‐based machine learning techniques to identify the most critical neighborhood‐level factors in predicting the neighborhood‐level prevalence of stroke, and compared their predictive performance for variable selection. We further quantified the effects of the identified determinants on stroke prevalence using a Bayesian linear regression model. Of the 5 most important predictors identified by our method, higher prevalence of low physical activity, larger share of older adults, higher percentage of non‐Hispanic Black people, and higher ozone levels were associated with higher prevalence of stroke at the neighborhood level. Higher median household income was linked to lower prevalence. The most important interaction term showed an exacerbated adverse effect of aging and low physical activity on the neighborhood‐level prevalence of stroke.

Conclusions

Tree‐based machine learning provides insights into underlying drivers of neighborhood cardiovascular health by discovering the most important determinants from a wide range of factors in an agnostic, data‐driven, and reproducible way. The identified major determinants and the interactive mechanism can be used to prioritize and allocate resources to optimize community‐level interventions for stroke prevention.

Estimation of causal effects of multiple treatments in observational studies with a binary outcome

There is a dearth of robust methods to estimate the causal effects of multiple treatments when the outcome is binary. This paper uses two unique sets of simulations to propose and evaluate the use of Bayesian additive regression trees in such settings. First, we compare Bayesian additive regression trees to several approaches that have been proposed for continuous outcomes, including inverse probability of treatment weighting, targeted maximum likelihood estimator, vector matching, and regression adjustment. Results suggest that under conditions of non-linearity and non-additivity of both the treatment assignment and outcome generating mechanisms, Bayesian additive regression trees, targeted maximum likelihood estimator, and inverse probability of treatment weighting using generalized boosted models provide better bias reduction and smaller root mean squared error. Bayesian additive regression trees and targeted maximum likelihood estimator provide more consistent 95% confidence interval coverage and better large-sample convergence property. Second, we supply Bayesian additive regression trees with a strategy to identify a common support region for retaining inferential units and for avoiding extrapolating over areas of the covariate space where common support does not exist. Bayesian additive regression trees retain more inferential units than the generalized propensity score-based strategy, and shows lower bias, compared to targeted maximum likelihood estimator or generalized boosted model, in a variety of scenarios differing by the degree of covariate overlap. A case study examining the effects of three surgical approaches for non-small cell lung cancer demonstrates the methods.

Factors associated with mammography use: A side-by-side comparison of results from two national surveys

BACKGROUND

Mammography use is affected by multiple factors that may change as public health interventions are implemented. We examined two nationally representative, population-based surveys to seek consensus and identify inconsistencies in factors associated with mammography use in the entirety of the US population, and by black and white subgroups.

METHODS

Self-reported mammography use in the past year was extracted for 12 639 and 169 116 women aged 40-74 years from the 2016 National Health Interview Survey (NHIS) and the 2016 Behavioral Risk Factor Surveillance System (BRFSS), respectively. We applied a random forest algorithm to identify the risk factors of mammography use and used a subset of them in multivariable survey logistic regressions to examine their associations with mammography use, reporting predictive margins and effect sizes.

RESULTS

The weighted prevalence of past year mammography use was comparable across surveys: 54.31% overall, 54.50% in white, and 61.57% in black in NHIS and 53.24% overall, 56.97% in white, and 62.11% in black in BRFSS. Overall, mammography use was positively associated with black race, older age, higher income, and having health insurance, while negatively associated with having three or more children at home and residing in the Western region of the US. Overweight and moderate obesity were significantly associated with increased mammography use among black women (NHIS), while severe obesity was significantly associated with decreased mammography use among white women (BRFSS).

CONCLUSION

We found higher mammography use among black women than white women, a change in the historical trend. We also identified high parity as a risk factor for mammography use, which suggests a potential subpopulation to target with interventions aimed at increasing mammography use.

Abstract 445: Integrated proteogenomic characterization across seven histological types of pediatric brain tumors

We performed a comprehensive proteogenomic analysis across seven major types of childhood brain tumors for a deeper understanding of their functional biology. Whole genome seq, RNAseq, quantitative proteomic and phosphoproteomic profiling were performed on 219 fresh frozen tumor samples representing the histologic diagnoses of: low grade astrocytoma (93), ependymoma (32), high grade astrocytoma (26), medulloblastoma (22), ganglioglioma (18), craniopharyngioma (16) and atypical teratoid rhabdoid tumor (12). Characterization of the tumor microenvironment through multi-omics based deconvolution analyses revealed 5 distinct tumor clusters associated with different populations of infiltrating immune cells: Cold-medullo, Cold-mixed, Epithelial, Neuronal and Hot. The two cold-tumor clusters have the lowest immune cell infiltration, one characterized by the enrichment of medulloblastoma tumors; while the other is a mixture of ependymoma, ATRT, HGG and medulloblastoma. The Epithelial group, on the other hand, was enriched in craniopharyngioma samples, an epithelium derived tumor. Interestingly, the RNA levels of PD-1 and CTLA4 were significantly upregulated in this Epithelial group, confirming that craniopharingioma could potentially benefit from anti PD-1 and/or CTLA-4 therapies as previously reported. LLG and ganglioglioma were allocated into two groups of Neuronal and Hot, the former characterized by the presence of neuronal cells, and the latter by the presence of macrophages, microglia, and dendritic cells. Adenosine producers (e.g., ENTPD1 and NT5E), which act as inhibitory immune checkpoint molecular, showed up-regulation in the Hot cluster based on both RNAseq and proteome data, suggesting patients in this group might benefit from adenosine reducing treatments. Among LGG tumors, there is a significant difference between microglial and macrophage polarization across BRAF statuses: BRAF-fusion promoted more pro-regenerative (immune suppressive) microglia than pro-inflammatory microglia, while BRAF-V600E promoted more pro-regenerative macrophages than pro-inflammatory macrophages, implying different immunosuppressive mechanisms in the BRAF-V600E and fusion tumors. This study reports the first large-scale deep comprehensive proteogenomic analysis crossing traditional histologic boundaries to uncover foundational pediatric brain tumor biology relating to tumor microenvironment. The incorporation of the proteomic and phosphoproteomic dimension into this large-scale multi-omic study adds functional insight that helps drive translational efforts.

Citation Format: Francesca Petralia, Nicole Tignor, Boris Reva, Pichai Raman, Shrabanti Chowdhury, Dmitry Rykunov, Azra Krek, Weiping Ma, Jiayi Ji, Xiaoyu Song, Yuankun Zhu, Jo Lynne Rokita, Antonio Colaprico, Anna Calinawan, Jeffrey R. Whiteaker, Richard G. Ivey, Zeynep Gumus, Selim Kalayci, Gonzalo L. Garcia, Seungyeul Yoo, Lizabeth Katsnelson, Ying Wang, Jacob J. Kennedy, Uliana J. Voytovich, Lei Zhao, Felipe Leprevost, Hui-Yin Chang, Krutika S. Gaonkar, Elizabeth M. Appert, Ximena Cuellar, Jena Lilly, Jun Zhu, Eric E. Schadt, Medhi Mesri, Emily Boja, Tara Hiltka, Henry Rodriguez, Li Ding, Antonio Iavarone, Maciej Wiznerowicz, Alexey I. Nesvizhskii, David Fenyo, Steven Gygi, Amanda Paulovich, Adam C. Resnick, Phillip B. Storm, Brian Rood, Pei Wang, Children's Brain Tumor Tissue Consortium and Clinical Proteomic Tumor Analysis Consortium. Integrated proteogenomic characterization across seven histological types of pediatric brain tumors [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 445.