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Supplementary Methods; Supplementary Figures S1-S9; Supplementary Tables S1-S7

Baseline (screening) vs treatment cycle 2 (P=.06; paired t test). For patient 5, baseline data were not available.

Purpose:Assess safety and efficacy of nivolumab plus nab-paclitaxel and gemcitabine in patients with locally advanced/metastatic pancreatic cancer in a two-part, open-label, phase I trial.Patients and Methods:Fifty chemotherapy-naive patients received nab-paclitaxel 125 mg/m2 plus gemcitabine 1,000 mg/m2 (days 1, 8, and 15) and nivolumab 3 mg/kg (days 1 and 15) in 28-day cycles. The primary endpoints were dose-limiting toxicities (DLTs; part 1) and grade 3/4 treatment-emergent adverse events (TEAEs) or treatment discontinuation due to TEAEs (parts 1/2). Secondary efficacy endpoints were progression-free survival (PFS), overall survival (OS), and response. Assessment of programmed cell death-ligand 1 (PD-L1) expression was an exploratory endpoint; additional biomarkers were assessed post hoc.Results:One DLT (hepatitis) was reported in part 1 among six DLT-evaluable patients; 48 of 50 patients experienced grade 3/4 TEAEs and 18 discontinued treatment due to TEAEs. One grade 5 TEAE (respiratory failure) was reported. Median [95% confidence interval (CI)] PFS/OS was 5.5 (3.25–7.20 months)/9.9 (6.74–12.16 months) months, respectively [median follow-up for OS, 13.6 months (95% CI, 12.06–23.49 months)]. Overall response rate (95% CI) was 18% (8.6%–31.4%). Median PFS/OS was 5.5/9.7 months (PD-L1 + CD8+/CD4+ cells increased significantly from baseline to cycle 3; median peak on-treatment Ki67+ CD8+ T-cell values were higher in responders than in nonresponders.Conclusions:The safety profile of nivolumab plus nab-paclitaxel and gemcitabine at standard doses in advanced pancreatic cancer was manageable, with no unexpected safety signals. Overall, the clinical results of this study do not support further investigation.

Percentage lymphocyte subset Ki67+. All patient visits are binned by treatment cycle. Data at baseline and treatment cycle 3 were compared using the Wilcoxon signed rank test. All available data are illustrated; however, statistical comparisons were performed only for data available at both baseline and treatment cycle 3 (n=29).

T-Cell Tumor Infiltration in Tissue-Matched Baseline (screening) and On-Treatment Metastatic Tumors (arm B parts 1 and 2)

Investigator-assessed PFS and OS in patients with PD-L1 expression cutoff of 1% (A, B) or 5% (C, D). HR, hazard ratio; mo, months; OS, overall survival; PD-L1, programmed cell death ligand-1; PFS, progression-free survival.

Patients were enrolled in Arm B Part 1 after the safety oversight committee deemed Arm A Part 1 safe. DRC, data review committee; LAPC, locally advanced pancreatic cancer; MPC, metastatic pancreatic cancer; RP2D, recommended Part 2 dose.

Concentrations of CXCL10 (A) and sIL2Rα (B) at baseline and peak on-treatment values. Investigator-assessed PFS in patients with high or low serum cytokines CXCL10 (C) and sIL2Rα (D). CXCL10, interferon gamma-induced protein 10; mo, months; NE, not estimable; NR, nonresponder; PFS, progression-free survival; R, responder; sIL2Rα, soluble form of interleukin 2 receptor alpha; Tx, treatment.

Data Tables

In the TRANSCEND NHL 001 study, 53% of patients with relapsed/refractory large B-cell lymphoma (LBCL) treated with lisocabtagene maraleucel (liso-cel) achieved a complete response (CR). To determine characteristics of patients who did and did not achieve a CR, we examined the tumor biology and microenvironment from lymph node tumor biopsies. LBCL biopsies from liso-cel–treated patients were taken pretreatment and ∼11 days posttreatment for RNA sequencing (RNA-seq) and multiplex immunofluorescence (mIF). We analyzed gene expression data from pretreatment biopsies (N = 78) to identify gene sets enriched in patients who achieved a CR to those with progressive disease. Pretreatment biopsies from month-3 CR patients displayed higher expression levels of T-cell and stroma-associated genes, and lower expression of cell-cycle genes. To interpret whether LBCL samples were “follicular lymphoma (FL)–like,” we constructed an independent gene expression signature and found that patients with a higher “FL-like” gene expression score had longer progression-free survival (PFS). Cell of origin was not associated with response or PFS, but double-hit gene expression was associated with shorter PFS. The day 11 posttreatment samples (RNA-seq, N = 73; mIF, N = 53) had higher levels of chimeric antigen receptor (CAR) T-cell densities and CAR gene expression, general immune infiltration, and immune activation in patients with CR. Further, the majority of T cells in the day 11 samples were endogenous. Gene expression signatures in liso-cel–treated patients with LBCL can inform the development of combination therapies and next-generation CAR T-cell therapies.

OBJECTIVE Prior research has found a positive association between the quality or adjustment of an individual's intimate relationship, such as marriage, and their physical health. However, it is possible that this association may be due, at least in part, to confounding variables (i.e., variables that are causally associated both with relationship adjustment and health and could account for their covariation), including genetically influenced confounds. This study was conducted using a genetically informative sample of twins to examine the association between intimate relationship adjustment and self-rated health, accounting for unmeasured genetic and environmental confounds. METHOD A Swedish sample of 539 monozygotic and dizygotic twins (321 male twin pairs and 218 female twin pairs) and their spouse or long-term partner completed self-report measures of relationship adjustment and health. RESULTS Relationship adjustment was positively associated with self-rated health in male and female twins. For male twins, nonshared environmental influences largely accounted for the association between relationship adjustment and health; for female twins, this association was generally explained by shared and nonshared environmental influences. For male twins, results obtained from partners' reports of relationship adjustment were largely consistent with those obtained from twins' reports. CONCLUSIONS Results suggest that the association between relationship adjustment and self-rated health remains after accounting for shared genetic influences, and that nonshared environmental influences, such as partners' characteristics, account for the association between relationship adjustment and self-rated health in men. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Purpose: Assess safety and efficacy of nivolumab plus nab-paclitaxel and gemcitabine in patients with locally advanced/metastatic pancreatic cancer in a two-part, open-label, phase I trial. Patients and Methods: Fifty chemotherapy-naive patients received nab-paclitaxel 125 mg/m2 plus gemcitabine 1,000 mg/m2 (days 1, 8, and 15) and nivolumab 3 mg/kg (days 1 and 15) in 28-day cycles. The primary endpoints were dose-limiting toxicities (DLTs; part 1) and grade 3/4 treatment-emergent adverse events (TEAEs) or treatment discontinuation due to TEAEs (parts 1/2). Secondary efficacy endpoints were progression-free survival (PFS), overall survival (OS), and response. Assessment of programmed cell death-ligand 1 (PD-L1) expression was an exploratory endpoint; additional biomarkers were assessed post hoc. Results: One DLT (hepatitis) was reported in part 1 among six DLT-evaluable patients; 48 of 50 patients experienced grade 3/4 TEAEs and 18 discontinued treatment due to TEAEs. One grade 5 TEAE (respiratory failure) was reported. Median [95% confidence interval (CI)] PFS/OS was 5.5 (3.25–7.20 months)/9.9 (6.74–12.16 months) months, respectively [median follow-up for OS, 13.6 months (95% CI, 12.06–23.49 months)]. Overall response rate (95% CI) was 18% (8.6%–31.4%). Median PFS/OS was 5.5/9.7 months (PD-L1 Conclusions: The safety profile of nivolumab plus nab-paclitaxel and gemcitabine at standard doses in advanced pancreatic cancer was manageable, with no unexpected safety signals. Overall, the clinical results of this study do not support further investigation.

Introduction The newly diagnosed pancreatic ductal adenocarcinoma (PDAC) population has a high unmet need for effective treatments, with median survival of < 1 year. The phase 3 APACT (Adjuvant Pancreatic Adenocarcinoma Clinical Trial) evaluated the use of adjuvant nab-paclitaxel plus gemcitabine vs. gemcitabine in 866 patients with surgically resected PDAC. We explored the tumor microenvironment (TME) of >500 baseline resected APACT tumors to identify TME features that are associated with adverse outcomes. Methods Biopsy analyses included RNA-seq, DNA-seq, and multiplexed immunohistochemistry (mIHC). We quantified, for 533 patient biopsies, via mIHC the spatial arrangement of 7 immune cell types and 2 checkpoint markers relative to tumor and nontumor regions, and pairwise colocalization relative to each other. We identified combinations of biomarkers that correlate significantly with molecular signatures, predefined patient subsets, and overall survival (OS). Hazard ratios (HR) and p-values were computed via a Cox proportional hazards regression model which included resection and lymph node status as covariates. Significantly differentially-expressed transcripts were associated with biomarkers derived from the mIHC via unpaired t-test. Results Higher densities of CD8+ T cells within tumor regions correlated with longer OS (hazard ratio HR=0.76; p=0.03), and higher overall densities of CD163+ macrophages correlated with shorter OS (HR=1.44; p=0.006). We furthermore identified a patient subset (n=72) with a combination of higher CD8+ T cell and lower CD163+ macrophage densities that had a strikingly significant decreased HR of 0.46 (p=0.009). Moreover, patients with a high degree of spatial colocalization between CD8+ T cells and dual-positive CMAF+CD163+ M2-like macrophages observed a significant increased HR of 1.51 (p=0.0006), a biomarker only surpassed by nodal status in significance of correlation with OS (HR=1.9; p=0.00015). While this cellular colocalization was computed to be independent of cell densities, we found that the association of this colocalized pair of cell types with shorter OS was most significant for patients with lower overall CD8+ T cell densities (HR=1.84; p=0.0004). We further identified differentially regulated transcripts associated with this interaction and found specific putative ligand-receptor pairs that were also associated with lower OS. Conclusion A combination of greater infiltration of CD8+ cytotoxic T cells and lower infiltration of macrophages is associated with longer OS in the APACT trial. Moreover, the spatial colocalization between CD8+ T cells and CMAF+ M2 macrophages is associated with shorter OS. These findings were observed across both treatment arms of the study. Future investigation of this apparent interaction, and associated differentially expressed transcripts, may inform management of patients with pancreatic adenocarcinoma and increase effectiveness of PDAC therapies. Citation Format: David J. Reiss, Andrew Browne, Brian Fox, Alexander V. Ratushnyy, Maria Wang, Andrew V. Biankin, Thomas Lila. Spatial arrangements of immune cells of the pancreatic ductal adenocarcinoma tumor microenvironment correlated with outcomes in the phase 3 APACT trial [abstract]. In: Proceedings of the AACR Special Conference on Pancreatic Cancer; 2022 Sep 13-16; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2022;82(22 Suppl):Abstract nr C085.

Background The tumor microenvironment (TME) is increasingly appreciated as an important determinant of cancer outcome, including in multiple myeloma (MM). However, most myeloma microenvironment studies have been based on bone marrow (BM) aspirates, which often do not fully reflect the cellular content of BM tissue itself. To address this limitation in myeloma research, we systematically characterized the whole bone marrow (WBM) microenvironment during premalignant, baseline, on treatment, and post-treatment phases. Methods and findings Between 2004 and 2019, 998 BM samples were taken from 436 patients with newly diagnosed MM (NDMM) at the University of Arkansas for Medical Sciences in Little Rock, Arkansas, United States of America. These patients were 61% male and 39% female, 89% White, 8% Black, and 3% other/refused, with a mean age of 58 years. Using WBM and matched cluster of differentiation (CD)138-selected tumor gene expression to control for tumor burden, we identified a subgroup of patients with an adverse TME associated with 17 fewer months of progression-free survival (PFS) (95% confidence interval [CI] 5–29, 49–69 versus 70–82 months, χ2 p = 0.001) and 15 fewer months of overall survival (OS; 95% CI –1 to 31, 92–120 versus 113–129 months, χ2 p = 0.036). Using immunohistochemistry-validated computational tools that identify distinct cell types from bulk gene expression, we showed that the adverse outcome was correlated with elevated CD8+ T cell and reduced granulocytic cell proportions. This microenvironment develops during the progression of premalignant to malignant disease and becomes less prevalent after therapy, in which it is associated with improved outcomes. In patients with quantified International Staging System (ISS) stage and 70-gene Prognostic Risk Score (GEP-70) scores, taking the microenvironment into consideration would have identified an additional 40 out of 290 patients (14%, premutation p = 0.001) with significantly worse outcomes (PFS, 95% CI 6–36, 49–73 versus 74–90 months) who were not identified by existing clinical (ISS stage III) and tumor (GEP-70) criteria as high risk. The main limitations of this study are that it relies on computationally identified cell types and that patients were treated with thalidomide rather than current therapies. Conclusions In this study, we observe that granulocyte signatures in the MM TME contribute to a more accurate prognosis. This implies that future researchers and clinicians treating patients should quantify TME components, in particular monocytes and granulocytes, which are often ignored in microenvironment studies., Author summary Why was this study done? The cells around a tumor, also known as the tumor microenvironment (TME), can help a tumor grow by suppressing the immune system or fight a tumor by mounting an immune response. Most studies of multiple myeloma (MM) have focused on the tumor itself, rather than the bone marrow (BM) TME in which the tumor is growing. We hypothesized that the MM TME held clues that could help us better treat patients. What did the researchers do and find? We used a gene-expression–based computational technique to determine which cell types were present in patient BM. Patients with BM lacking a family of innate immune cells called granulocytes presented with worse outcomes compared to other patients. As MM progresses from a predisease to a cancerous state, the percentage of granulocytes decreases; the patients with the fewest granulocytes had more serious diseases. What do these findings mean? If granulocytes help myeloma patients respond to therapy, then addressing the decline in granulocytes may improve MM treatment. Patients with MM and few granulocytes in their BM should be watched for worse outcomes.

The success of Mycobacterium tuberculosis (Mtb) is largely due to its ability to withstand multiple stresses encountered in the host. Here, we present a data-driven model that captures the dynamic interplay of environmental cues and genome-encoded regulatory programs in Mtb. The model captures the genome-wide distribution of cis-acting gene regulatory elements and the conditional influences of transcription factors at those elements to elicit environment-specific responses. Analysis of transcriptional responses that may be essential for Mtb to survive acidic stress within the maturing macrophage, identified regulatory control by the MtrAB two-component signal system. Using genome-wide transcriptomics as well as imaging studies, we have characterized the MtrAB circuit by tunable CRISPRi knockdown in both Mtb and the non-pathogenic organism, M. smegmatis (Msm). These experiments validated the essentiality of MtrA in Mtb, but not Msm. We identified that MtrA regulates multiple enzymes that cleave cell wall peptidoglycan and is required for efficient cell division. Moreover, our results suggest that peptidoglycan cleavage, regulated by MtrA, is necessary for Mtb to survive intracellular stress. Further, we present MtrA as an attractive drug target, as even weak repression of mtrA results in loss of Mtb viability and completely clears the bacteria with low-dose isoniazid or rifampicin treatment.

Despite recent advancements in the treatment of multiple myeloma (MM), nearly all patients ultimately relapse and many become refractory to their previous therapies. Although many therapies exist with diverse mechanisms of action, it is not yet clear how the differences in MM biology across patients impacts the likelihood of success for existing therapies and those in the pipeline. Therefore, we not only need the ability to predict which patients are at high risk for disease progression, but also a means to understand the mechanisms underlying their risk. We hypothesized that knowledge of the biological networks that give rise to MM, specifically the transcriptional regulatory network (TRN) and the mechanisms by which mutations impact gene regulation, would enable improved predictions of disease progression and actionable insights for treatment. Here we present a method to infer TRNs from multi-omics data and apply it to the generation of a MM TRN that links chromosomal abnormalities and somatic mutations to downstream effects on gene expression via perturbation of transcriptional regulators. We find that 141 genetic programs underlie the disease and that the activity profile of these programs fall into one of 25 distinct transcriptional states. These transcriptional signatures prove to be more predictive of outcomes than do mutations and reveal plausible mechanisms for relapse, including the establishment of an immuno-suppressive microenvironment. Moreover, we observe subtype-specific vulnerabilities to interventions with existing drugs and motivate the development of new targeted therapies that appear especially promising for relapsed refractory MM.

Background Mechanistic models, when combined with pertinent data, can improve our knowledge regarding important molecular and cellular mechanisms found in cancer. These models make the prediction of tissue-level response to drug treatment possible, which can lead to new therapies and improved patient outcomes. Here we present a data-driven multiscale modeling framework to study molecular interactions between cancer, stromal, and immune cells found in the tumor microenvironment. We also develop methods to use molecular data available in The Cancer Genome Atlas to generate sample-specific models of cancer. Results By combining published models of different cells relevant to pancreatic ductal adenocarcinoma (PDAC), we built an agent-based model of the multicellular pancreatic tumor microenvironment, formally describing cell type–specific molecular interactions and cytokine-mediated cell-cell communications. We used an ensemble-based modeling approach to systematically explore how variations in the tumor microenvironment affect the viability of cancer cells. The results suggest that the autocrine loop involving EGF signaling is a key interaction modulator between pancreatic cancer and stellate cells. EGF is also found to be associated with previously described subtypes of PDAC. Moreover, the model allows a systematic exploration of the effect of possible therapeutic perturbations; our simulations suggest that reducing bFGF secretion by stellate cells will have, on average, a positive impact on cancer apoptosis. Conclusions The developed framework allows model-driven hypotheses to be generated regarding therapeutically relevant PDAC states with potential molecular and cellular drivers indicating specific intervention strategies.

Assess safety and efficacy of nivolumab plusFifty chemotherapy-naive patients receivedOne DLT (hepatitis) was reported in part 1 among six DLT-evaluable patients; 48 of 50 patients experienced grade 3/4 TEAEs and 18 discontinued treatment due to TEAEs. One grade 5 TEAE (respiratory failure) was reported. Median [95% confidence interval (CI)] PFS/OS was 5.5 (3.25-7.20 months)/9.9 (6.74-12.16 months) months, respectively [median follow-up for OS, 13.6 months (95% CI, 12.06-23.49 months)]. Overall response rate (95% CI) was 18% (8.6%-31.4%). Median PFS/OS was 5.5/9.7 months (PD-L15%) and 6.8/11.6 months (PD-L1 ≥5%), respectively. Proportion of peripheral Ki67The safety profile of nivolumab plus

[This corrects the article DOI: 10.1371/journal.pone.0141881.].

(Abridged) We describe here the most ambitious survey currently planned in the optical, the Large Synoptic Survey Telescope (LSST). A vast array of science will be enabled by a single wide-deep-fast sky survey, and LSST will have unique survey capability in the faint time domain. The LSST design is driven by four main science themes: probing dark energy and dark matter, taking an inventory of the Solar System, exploring the transient optical sky, and mapping the Milky Way. LSST will be a wide-field ground-based system sited at Cerro Pach\'{o}n in northern Chile. The telescope will have an 8.4 m (6.5 m effective) primary mirror, a 9.6 deg$^2$ field of view, and a 3.2 Gigapixel camera. The standard observing sequence will consist of pairs of 15-second exposures in a given field, with two such visits in each pointing in a given night. With these repeats, the LSST system is capable of imaging about 10,000 square degrees of sky in a single filter in three nights. The typical 5$\sigma$ point-source depth in a single visit in $r$ will be $\sim 24.5$ (AB). The project is in the construction phase and will begin regular survey operations by 2022. The survey area will be contained within 30,000 deg$^2$ with $\delta, Comment: 57 pages, 32 color figures, version with high-resolution figures available from https://www.lsst.org/overview

Pancreatic ductal adenocarcinoma (PDAC) remains a difficult disease to treat, with few therapies available that target specific patient subgroups. Translational studies in pancreatic cancer can be technically challenging due to biopsy specimen characteristics including low tumor cellularity and dense fibrotic stroma. Resected primary pancreatic tumors obtained during the phase 3 APACT clinical trial (NCT01964430 adjuvant nab-paclitaxel + gemcitabine versus gemcitabine monotherapy n = 866) are a unique resource for characterizing molecular and immune subtypes among PDAC tumors and their association with treatment outcomes in the adjuvant chemotherapy setting. Tumor-infiltrating immune cells were assessed in serial sections of 453 tumors by dual-chromogen immuno-histochemical (IHC) staining (CD4 CD8 CD20 CD163 CMAF CD56 FoxP3 PD-1 PD-L1). Image alignment, segmentation, and spatial localization of stained cells relative to a pan-cytokeratin staining-based tumor epithelial mask was performed using a commercial analysis platform. Expression profiles were obtained for 515 macrodissected tumor biopsy regions by RNA-seq. Transcriptional subtypes were assigned based on schema previously reported by Moffit and Bailey, and molecular pathway correlates were characterized using gene set enrichment analysis. Based on immunochemical staining, higher intratumoral CD8+ or lower CD163+ cell densities were associated with modestly longer disease-free or overall survival in patients treated with nab-paclitaxel plus gemcitabine. The combination of both high CD8+ and low CD163+ cell density was notably associated with longer overall survival compared to other subjects treated with the combination regimen (mOS>55months versus 36 months HR=0.46 p= Citation Format: Thomas Lila, Andrew Biankin, Andrew Browne, David J. Reiss, Brian Lu, Daniel Pierce, Alexander Ratushny, Kao-tai Tsai, Sneh Lata, Sitharthan Kamalakaran, Tomas Babak, Brian Fox, Sam Danziger, Konstantinos Mavrommatis, Matthew W. B. Trotter, David Chang, Fadi Towfic. Multi-omic Profiling of primary pancreatic adenocarcinomas obtained from the APACT adjuvant trial of nab-paclitaxel + gemcitabine vs gemcitabine [abstract]. In: Proceedings of the AACR Virtual Special Conference on Pancreatic Cancer; 2020 Sep 29-30. Philadelphia (PA): AACR; Cancer Res 2020;80(22 Suppl):Abstract nr PO-008.

Managing trade‐offs through gene regulation is believed to confer resilience to a microbial community in a fluctuating resource environment. To investigate this hypothesis, we imposed a fluctuating environment that required the sulfate‐reducer Desulfovibrio vulgaris to undergo repeated ecologically relevant shifts between retaining metabolic independence (active capacity for sulfate respiration) and becoming metabolically specialized to a mutualistic association with the hydrogen‐consuming Methanococcus maripaludis. Strikingly, the microbial community became progressively less proficient at restoring the environmentally relevant physiological state after each perturbation and most cultures collapsed within 3–7 shifts. Counterintuitively, the collapse phenomenon was prevented by a single regulatory mutation. We have characterized the mechanism for collapse by conducting RNA‐seq analysis, proteomics, microcalorimetry, and single‐cell transcriptome analysis. We demonstrate that the collapse was caused by conditional gene regulation, which drove precipitous decline in intracellular abundance of essential transcripts and proteins, imposing greater energetic burden of regulation to restore function in a fluctuating environment.

This is an unannotated bibliography of writings through 2016 primarily about the Federal Home Loan Bank System (FHLBS), but it also includes materials regarding the savings and loan (S&L) industry. While it is comprehensive, it is not exhaustive, with a focus on work published by government agencies, economists, legal and policy scholars, private sector analysts and think tanks. The bibliography also includes other materials about the housing finance market in the 19th and early 20th Century. These materials provide some context for the operations of the FHLBS and the S&L industry. This bibliography will be posted on Wikipedia so that others can make additions to it. The text of this page and the attached downloadable document are available for modification and reuse under the terms of the Creative Commons Attribution-Sharealike 3.0 Unported License and the GNU Free Documentation License (unversioned, with no invariant sections, front-cover texts, or back-cover texts).

Introduction: It is strikingly difficult to develop successful treatments for PDAC; even with curative resection, most patients die from early occult metastases. Prior studies identified the presence of tumor-infiltrating lymphocytes (TILs) in primary PDAC tumors as having prognostic significance in the PDAC adjuvant setting, sharpening the questions of what fraction of patients have immune-infiltrated tumors and what therapeutic strategies should be pursued in these patients vs. the non-infiltrated group. The phase 3 APACT trial evaluated the use of adjuvant nab-paclitaxel plus gemcitabine vs. gemcitabine in 866 patients with PDAC who had undergone primary tumor resection, with the primary endpoint of disease-free survival evaluated by independent review. We extended studies of the tumor microenvironment of PDAC to a large set of resected APACT primary tumors in an effort to further refine features of tumor or immune infiltrate that influence disease progression and to determine if chemotherapy regimen–specific predictive signatures are identifiable. Tissue analyses for a large subset of APACT samples included RNA-seq, DNA-seq, multiplexed immunohistochemistry (IHC), and proteomics. Methods: We imaged and quantified markers for tumor cells, 7 different immune cells, and 2 immune checkpoint markers using bright-field chromogenic multiplexed IHC from pretreatment samples for more than 500 APACT primary tumor samples. We computationally defined the tumor, tumor margin, and distal stromal (> 150 μm from tumor boundary) regions, and quantified densities and distributions of immune cells in these regions. As part of an initial analysis of more than 400 samples, we applied both unsupervised clustering and supervised classification to these IHC measurements to identify patient subgroups with similar spatial arrangements of immune cells relative to tumor regions. Results: The preliminary analysis of normalized cell densities across all 3 tissue regions revealed 3 patient subgroups: one in which immune cells are mixed within the tumor regions; a second where immune cells approach the tumor boundary but are depleted within the tumor; and a third in which immune cells are depleted in both tumor and its margin, remaining at high densities only in the distal stromal regions. Within these latter subgroups, CD20+, CD4+, and CD8+ cells were more prevalently depleted from tumor and/or margin, whereas CD163+ and CD163+CMAF+ cells showed less of this arrangement. Nearly 85% of patients fell in the second or third patient group. Conclusions: We are pursuing analyses of these data in conjunction with upcoming molecular and genetic profiling data to further elucidate the association of the immune cell populations and these subgroups with clinical outcomes. These data will provide an unprecedented opportunity for exploratory analysis and discovery of immune, molecular, and genetic biomarkers for PDAC patient stratification. Citation Format: David J. Reiss, Thomas Lila, Suzana Couto, Sitharthan Kamalakaran, Yan Ren, Doug Bowman, Amber Ortiz, Maria Wang, Clifton Drew, Kao-Tai Tsai, Mathieu Marella, Brian Fox, Garth McGrath, Matthew Trotter, Fadi Towfic, Ian Cushman, Alexander Ratushny, Brian Lu, Daniel Pierce, Jim Cassidy. Spatial organization of pancreatic ductal adenocarcinoma (PDAC)–associated immune cells from the Adjuvant Pancreatic Adenocarcinoma Clinical Trial (APACT) study [abstract]. In: Proceedings of the AACR Special Conference on Pancreatic Cancer: Advances in Science and Clinical Care; 2019 Sept 6-9; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2019;79(24 Suppl):Abstract nr A43.

Immune cell infiltration of tumors can be an important component for determining patient outcomes, e.g. by inferring immune cell presence by deconvolving gene expression data drawn from a heterogenous mix of cell types. One particularly powerful family of deconvolution techniques uses signature matrices of genes that uniquely identify each cell type as determined from cell type purified gene expression data. Many methods of this type have been recently published, often including new signature matrices appropriate for a single purpose, such as investigating a specific type of tumor. The package ADAPTS helps users make the most of this expanding knowledge base by introducing a framework for cell type deconvolution. ADAPTS implements modular tools for customizing signature matrices for new tissue types by adding custom cell types or building new matrices de novo, including from single cell RNAseq data. It includes a common interface to several popular deconvolution algorithms that use a signature matrix to estimate the proportion of cell types present in heterogenous samples. ADAPTS also implements a novel method for clustering cell types into groups that are hard to distinguish by deconvolution and then re-splitting those clusters using hierarchical deconvolution. We demonstrate that the techniques implemented in ADAPTS improve the ability to reconstruct the cell types present in a single cell RNAseq data set in a blind predictive analysis. ADAPTS is currently available for use in R on CRAN and GitHub.

Background: The availability of chimeric antigen receptor (CAR)-modified T cells (CAR T) has profoundly increased therapeutic options for patients (pts) with B cell malignancies, including DLBCL. Liso-cel is an investigational, anti-CD19, defined composition, 4-1BB, CAR T cell product administered at a target dose of CD4+ and CD8+ CAR T cells. To understand tumor microenvironmental (TME) factors affecting short-term and durable responses in pts with R/R DLBCL who received liso-cel in the TRANSCEND NHL 001 study, we conducted multiplexed IF analyses of 111 DLBCL biopsies for 83 pts obtained at baseline (n=58) and approximately 11 days (D11) (n=53; 28 paired) after liso-cel infusion (NCT02631044). Methods: We employed three 5-plex IF panels, consisting of antibodies detecting (1) B cell (CD19, CD20) and T cell lineage (CD4, CD8, EGFR) markers, (2) immunosuppressive markers (CD163, FoxP3, CD73, IDO1, PD-L1), and (3) functional markers (CD3, Ki67, GZMB, PD-1, EGFR). Liso-cel expresses a truncated EGFR (EGFRt), and fluorescent anti-EGFR was used to identify CAR T cells within the tumor biopsies. We also performed bulk tumor RNA profiling for an overlapping subset of 50 baseline biopsies and 37 D11 biopsies (11 paired). We investigated the association of differences in marker densities for pts with best overall response (BOR) of complete response (CR), and progressive disease (PD). Baseline and D11 biopsy findings were correlated with early responses at ~1 month (M1) posttreatment (PD n=16; CR n=42) and durable responses at ~9 months (M9) posttreatment (PD n=76; CR n=32; 55 pts evaluated at both M1 and M9). We investigated how baseline and D11 densities, with spatial distinction between tumoral and peritumoral regions, correlated with early and durable responses. All comparisons describe differences in median densities, and have statistical significance reported with uncorrected P values assessed via the (unpaired) Wilcoxon-Mann-Whitney nonparametric test. Results: Signals in baseline biopsies that correlated with early (M1) response differed from those that correlated with durable (M9) CR. A 21% higher baseline presence of PD-1+ T cells was associated with pts who achieved early CR at M1 vs pts who had PD at M1 (P=0.007). Pts with durable CR at M9 had 39% lower baseline levels of CD163+ macrophages (P=0.019) and 270% higher levels of CD73+ cells (P=0.028) than those with PD at M9. On-treatment (D11) tumors of pts with both early and durable CR had 28% higher levels of EGFRt+ (CAR T) CD8+ T cells (P=0.022), and 810% higher EGFRt- (non-CAR T) CD4+ (but notably, not CD8+; P=0.28) T cells (P=0.009). We also investigated changes in marker densities between baseline and on-treatment (D11) biopsies, and found that pts with durable CR at M9 had decreased on-treatment B cell densities (P=0.029), and increased densities of CD8+ GZMB+, Ki67+, and/or PD-1+ CAR (P=0.001) as well as non-CAR T (P=0.017) cells. Pts with durable CR also had a 29% increase in tumor-associated CD163+ macrophages at D11 relative to baseline (P=0.033). While the accessibility of spatial arrangements and multilabeled cells from IF enables a more nuanced picture of the TME, many of the general trends described above are concordant with those observed in bulk tumor RNA sequencing. Lower baseline expression of CD163 (P=0.021) and higher expression of CD73 (P=0.054) were seen in pts with durable CR. Additionally, elevated on-treatment (D11) expression of CD3E, CD4, and liso-cel (P Conclusions: Overall, these data suggest that increased infiltration of tumor-specific CAR T cells upon initial treatment with liso-cel helped establish an active immune response, and that recruitment of additional functional endogenous (particularly CD4+) T cells correlated with durable response. Higher numbers of activated/functional T cells and lower numbers of macrophages prior to treatment also correlated with durable response to liso-cel. Thus, tumors in responders may already have had a baseline TME in which T cells could infiltrate and respond to antigen. This may have promoted the success of CAR T cell entry into tumors and the subsequent recruitment and activation of endogenous lymphocytes that support their function. Disclosures Reiss: Celgene Corporation: Employment, Equity Ownership. Do:Juno Therapeutics, a Celgene Company: Employment, Equity Ownership. Kuo:Juno Therapeutics, a Celgene Company: Employment, Equity Ownership. Gray:Celgene Corporation: Employment, Equity Ownership. Olson:Celgene Corporation: Employment, Equity Ownership. Lee:Celgene Corporation: Employment, Equity Ownership. Young:Celgene Corporation: Employment, Equity Ownership. Srinivasan:Juno Therapeutics, a Celgene Company: Employment, Equity Ownership. Gray:Celgene: Employment, Equity Ownership. Fox:Celgene Corporation: Employment, Equity Ownership. Couto:Celgene Corporation: Employment, Equity Ownership. Dubovsky:Celgene: Employment. Schmitz:Celgene Corporation: Employment, Equity Ownership. Newhall:Celgene Corporation: Employment, Equity Ownership.

This study investigated the differences between adolescents` own perceptions of their psychopathology and perceptions by clinically depressed parents of their adolescents` psychopathology. The study also examined parental characteristics that accounted for discrepancies between parents and adolescents. The clinical sample consisted of 61 adolescents and their parents who were diagnosed with a major depressive disorder. The adolescents and parents evaluated the adolescents` psychopathology in separate interviews with the Child Behavior Checklist (CBCL) and the Youth Self- Report (YSR). Parents reported on current depressive symptoms and parenting practices using questionnaires. The results revealed that parent-adolescent discrepancies were greater in regard to affective and anxiety problems compared to oppositional defiant and conduct problems. Parental rejection was associated with differences in scores for affective problems after controlling for parents` current depressive symptoms and adolescents` age and gender. The findings highlight the importance of considering adolescents` affective and anxiety problems when treating depressed parents. Furthermore, the findings suggest that parental rejection may play a pivotal role when interpreting the discrepancy concerning adolescents` affective problems.

Methanogens catalyze the critical methane-producing step (called methanogenesis) in the anaerobic decomposition of organic matter. Here, we present the first predictive model of global gene regulation of methanogenesis in a hydrogenotrophic methanogen, Methanococcus maripaludis. We generated a comprehensive list of genes (protein-coding and noncoding) for M. maripaludis through integrated analysis of the transcriptome structure and a newly constructed Peptide Atlas. The environment and gene-regulatory influence network (EGRIN) model of the strain was constructed from a compendium of transcriptome data that was collected over 58 different steady-state and time-course experiments that were performed in chemostats or batch cultures under a spectrum of environmental perturbations that modulated methanogenesis. Analyses of the EGRIN model have revealed novel components of methanogenesis that included at least three additional protein-coding genes of previously unknown function as well as one noncoding RNA. We discovered that at least five regulatory mechanisms act in a combinatorial scheme to intercoordinate key steps of methanogenesis with different processes such as motility, ATP biosynthesis, and carbon assimilation. Through a combination of genetic and environmental perturbation experiments we have validated the EGRIN-predicted role of two novel transcription factors in the regulation of phosphate-dependent repression of formate dehydrogenase—a key enzyme in the methanogenesis pathway. The EGRIN model demonstrates regulatory affiliations within methanogenesis as well as between methanogenesis and other cellular functions.

SummaryWe developed the transcription factor (TF)-target gene database and the Systems Genetics Network Analysis (SYGNAL) pipeline to decipher transcriptional regulatory networks from multi-omic and clinical patient data, and we applied these tools to 422 patients with glioblastoma multiforme (GBM). The resulting gbmSYGNAL network predicted 112 somatically mutated genes or pathways that act through 74 TFs and 37 microRNAs (miRNAs) (67 not previously associated with GBM) to dysregulate 237 distinct co-regulated gene modules associated with patient survival or oncogenic processes. The regulatory predictions were associated to cancer phenotypes using CRISPR-Cas9 and small RNA perturbation studies and also demonstrated GBM specificity. Two pairwise combinations (ETV6-NFKB1 and romidepsin-miR-486-3p) predicted by the gbmSYGNAL network had synergistic anti-proliferative effects. Finally, the network revealed that mutations in NF1 and PIK3CA modulate IRF1-mediated regulation of MHC class I antigen processing and presentation genes to increase tumor lymphocyte infiltration and worsen prognosis. Importantly, SYGNAL is widely applicable for integrating genomic and transcriptomic measurements from other human cohorts.

Mycobacterium tuberculosis (MTB) is a highly successful pathogen that infects over a billion people. As with most organisms, MTB adapts to stress by modifying its transcriptional profile. Remodeling of the transcriptome requires both altering the transcription rate and clearing away the existing mRNA through degradation, a process that can be directly regulated in response to stress. To understand better how MTB adapts to the harsh environs of the human host, we performed a global survey of the decay rates of MTB mRNA transcripts. Decay rates were measured for 2139 of the ∼4000 MTB genes, which displayed an average half-life of 9.5 min. This is nearly twice the average mRNA half-life of other prokaryotic organisms where these measurements have been made. The transcriptome was further stabilized in response to lowered temperature and hypoxic stress. The generally stable transcriptome described here, and the additional stabilization in response to physiologically relevant stresses, has far-ranging implications for how this pathogen is able to adapt in its human host.

Assembly of genes into operons is generally viewed as an important process during the continual adaptation of microbes to changing environmental challenges. However, the genome reorganization events that drive this process are also the roots of instability for existing operons. We have determined that there exists a statistically significant trend that correlates the proportion of genes encoded in operons in archaea to their phylogenetic lineage. We have further characterized how microbes deal with operon instability by mapping and comparing transcriptome architectures of four phylogenetically diverse extremophiles that span the range of operon stabilities observed across archaeal lineages: a photoheterotrophic halophile (Halobacterium salinarum NRC-1), a hydrogenotrophic methanogen (Methanococcus maripaludis S2), an acidophilic and aerobic thermophile (Sulfolobus solfataricus P2), and an anaerobic hyperthermophile (Pyrococcus furiosus DSM 3638). We demonstrate how the evolution of transcriptional elements (promoters and terminators) generates new operons, restores the coordinated regulation of translocated, inverted, and newly acquired genes, and introduces completely novel regulation for even some of the most conserved operonic genes such as those encoding subunits of the ribosome. The inverse correlation (r = –0.92) between the proportion of operons with such internally located transcriptional elements and the fraction of conserved operons in each of the four archaea reveals an unprecedented view into varying stages of operon evolution. Importantly, our integrated analysis has revealed that organisms adapted to higher growth temperatures have lower tolerance for genome reorganization events that disrupt operon structures.

Introduction The multiple myeloma (MM) tumor microenvironment (TME) strongly influences patient outcomes as evidenced by the success of immunomodulatory therapies. To develop precision immunotherapeutic approaches, it is essential to identify and enumerate TME cell types and understand their dynamics. Methods We estimated the population of immune and other non-tumor cell types during the course of MM treatment at a single institution using gene expression of paired CD138-selected bone marrow aspirates and whole bone marrow (WBM) core biopsies from 867 samples of 436 newly diagnosed MM patients collected at 5 time points: pre-treatment (N=354), post-induction (N=245), post-transplant (N=83), post-consolidation (N=51), and post-maintenance (N=134). Expression profiles from the aspirates were used to infer the transcriptome contribution of immune and stromal cells in the WBM array data. Unsupervised clustering of these non-tumor gene expression profiles across all time points was performed using the R package ConsensusClusterPlus with Bayesian Information Criterion (BIC) to select the number of clusters. Individual cell types in these TMEs were estimated using the DCQ algorithm and a gene expression signature matrix based on the published LM22 leukocyte matrix (Newman et al., 2015) augmented with 5 bone marrow- and myeloma-specific cell types. Results Our deconvolution approach accurately estimated percent tumor cells in the paired samples compared to estimates from microscopy and flow cytometry (PCC = 0.63, RMSE = 9.99%). TME clusters built on gene expression data from all 867 samples resulted in 5 unsupervised clusters covering 91% of samples. While the fraction of patients in each cluster changed during treatment, no new TME clusters emerged as treatment progressed. These clusters were associated with progression free survival (PFS) (p-Val = 0.020) and overall survival (OS) (p-Val = 0.067) when measured in pre-transplant samples. The most striking outcomes were represented by Cluster 5 (N = 106) characterized by a low innate to adaptive cell ratio and shortened patient survival (Figure 1, 2). This cluster had worse outcomes than others (estimated mean PFS = 58 months compared to 71+ months for other clusters, p-Val = 0.002; estimate mean OS = 105 months compared with 113+ months for other clusters, p-Val = 0.040). Compared to other immune clusters, the adaptive-skewed TME of Cluster 5 is characterized by low granulocyte populations and high antigen-presenting, CD8 T, and B cell populations. As might be expected, this cluster was also significantly enriched for ISS3 and GEP70 high risk patients, as well as Del1p, Del1q, t12;14, and t14:16. Importantly, this TME persisted even when the induction therapy significantly reduced the tumor load (Table 1). At post-induction, outcomes for the 69 / 245 patients in Cluster 5 remain significantly worse (estimate mean PFS = 56 months compared to 71+ months for other clusters, p-Val = 0.004; estimate mean OS = 100 months compared to 121+ months for other clusters, p-Val = 0.002). The analysis of on-treatment samples showed that the number of patients in Cluster 5 decreases from 30% before treatment to 12% after transplant, and of the 63 patients for whom we have both pre-treatment and post-transplant samples, 18/20 of the Cluster 5 patients moved into other immune clusters; 13 into Cluster 4. The non-5 clusters (with better PFS and OS overall) had higher amounts of granulocytes and lower amounts of CD8 T cells. Some clusters (1 and 4) had increased natural killer (NK) cells and decreased dendritic cells, while other clusters (2 and 3) had increased adipocytes and increases in M2 macrophages (Cluster 2) or NK cells (Cluster 3). Taken together, the gain of granulocytes and adipocytes was associated with improved outcome, while increases in the adaptive immune compartment was associated with poorer outcome. Conclusions We identified distinct clusters of patient TMEs from bulk transcriptome profiles by computationally estimating the CD138- fraction of TMEs. Our findings identified differential immune and stromal compositions in patient clusters with opposing clinical outcomes and tracked membership in those clusters during treatment. Adding this layer of TME to the analysis of myeloma patient baseline and on-treatment samples enables us to formulate biological hypotheses and may eventually guide therapeutic interventions to improve outcomes for patients. Disclosures Danziger: Celgene Corporation: Employment, Equity Ownership. McConnell:Celgene Corporation: Employment. Gockley:Celgene Corporation: Employment. Young:Celgene Corporation: Employment, Equity Ownership. Schmitz:Celgene Corporation: Employment, Equity Ownership. Reiss:Celgene Corporation: Employment, Equity Ownership. Davies:MMRF: Honoraria; Celgene: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Amgen: Consultancy, Membership on an entity's Board of Directors or advisory committees; TRM Oncology: Honoraria; Abbvie: Consultancy; ASH: Honoraria; Takeda: Consultancy, Membership on an entity's Board of Directors or advisory committees; Janssen: Consultancy, Honoraria. Copeland:Celgene Corporation: Employment, Equity Ownership. Fox:Celgene Corporation: Employment, Equity Ownership. Fitch:Celgene Corporation: Employment, Equity Ownership. Newhall:Celgene Corporation: Employment, Equity Ownership. Barlogie:Celgene: Consultancy, Research Funding; Dana Farber Cancer Institute: Other: travel stipend; Multiple Myeloma Research Foundation: Other: travel stipend; International Workshop on Waldenström's Macroglobulinemia: Other: travel stipend; Millenium: Consultancy, Research Funding; European School of Haematology- International Conference on Multiple Myeloma: Other: travel stipend; ComtecMed- World Congress on Controversies in Hematology: Other: travel stipend; Myeloma Health, LLC: Patents & Royalties: : Co-inventor of patents and patent applications related to use of GEP in cancer medicine licensed to Myeloma Health, LLC. Trotter:Celgene Research SL (Spain), part of Celgene Corporation: Employment, Equity Ownership. Hershberg:Celgene Corporation: Employment, Equity Ownership, Patents & Royalties. Dervan:Celgene Corporation: Employment, Equity Ownership. Ratushny:Celgene Corporation: Employment, Equity Ownership. Morgan:Takeda: Consultancy, Honoraria; Bristol-Myers Squibb: Consultancy, Honoraria; Celgene: Consultancy, Honoraria, Research Funding; Janssen: Research Funding.

Introduction The multistep progression of multiple myeloma from a normal plasma cell to a system with the features of invasive cancer provides a unique opportunity to understand the co-evolution of the malignant clone within its microenvironment. Understanding these changes is becoming increasingly important as we attempt to design early intervention strategies and to precisely leverage emerging immunotherapeutic modalities to prevent and treat disease progression. In this work, we used mass cytometry (CyTOF) to generate a high-resolution map of the BM microenvironment and how it changes during the transition from health through pre-malignancy to disease. This approach allows us to both understand microenvironmental patterns that correlate with rapid disease progression as well as to generate new hypotheses about permissive and protective immune-phenotypes that might reveal novel immunologic drug targets. Methods To understand the immunologic characteristics of monoclonal gammopathy of undetermined significance (MGUS), smoldering multiple myeloma (SMM), newly diagnosed multiple myeloma (NDMM) and relapsed-refractory multiple myeloma (RRMM), we profiled BM aspirates from 79 patients using mass cytometry by time of flight (CyTOF). Furthermore, we compared the BM compartment of pre-malignant, malignant, and relapsed disease states to the BM of healthy donors using a 37-marker pan-immune panel. In this panel, we used antibodies against several immune lineages, tumor antigens, and functional surface markers, including co-stimulatory and co-inhibitory receptors. Cell clusters defined by Citrus analysis of CyTOF data were combined into an evolutionarily optimized decision tree by evtree to identify cluster interactions that strongly partition patient samples. Results During MGUS, when the tumor plasma cells are Conclusions Immune dysregulation is thought to be a major contributor to the progression and outcome of patients with MGUS, SMM, and MM. Using CyTOF, we have begun to benchmark the content of the immune microenvironment across the myeloma continuum. Based on this cross-sectional analysis we hypothesize that it is important to further interrogate whether the losses in the CD4 memory and effector populations we described correlate with outcomes after therapy with either CAR T or T cell engager trials that are currently ongoing, and whether reconstituting these cell types could provide a meaningful treatment strategy. Disclosures Young: Celgene Corporation: Employment, Equity Ownership. Danziger:Celgene Corporation: Employment, Equity Ownership. Fitch:Celgene Corporation: Employment, Equity Ownership. Schmitz:Celgene Corporation: Employment, Equity Ownership. Gockley:Celgene Corporation: Employment. McConnell:Celgene Corporation: Employment. Reiss:Celgene Corporation: Employment, Equity Ownership. Copeland:Celgene Corporation: Employment, Equity Ownership. Newhall:Celgene Corporation: Employment, Equity Ownership. Hershberg:Celgene Corporation: Employment, Equity Ownership, Patents & Royalties. Foy:Celgene Corporation: Employment, Equity Ownership. Ratushny:Celgene Corporation: Employment, Equity Ownership. Dervan:Celgene Corporation: Employment, Equity Ownership. Morgan:Takeda: Consultancy, Honoraria; Janssen: Research Funding; Celgene: Consultancy, Honoraria, Research Funding; Bristol-Myers Squibb: Consultancy, Honoraria.