Proteogenomic analysis of enriched HGSOC tumor epithelium identifies prognostic signatures and therapeutic vulnerabilities

We performed a deep proteogenomic analysis of bulk tumor and laser microdissection enriched tumor cell populations from high-grade serous ovarian cancer (HGSOC) tissue specimens spanning a broad spectrum of purity. We identified patients with longer progression-free survival had increased immune-related signatures and validated proteins correlating with tumor-infiltrating lymphocytes in 65 tumors from an independent cohort of HGSOC patients, as well as with overall survival in an additional 126 HGSOC patient cohort. We identified that homologous recombination deficient (HRD) tumors are enriched in pathways associated with metabolism and oxidative phosphorylation that we validated in independent patient cohorts. We further identified that polycomb complex protein BMI-1 is elevated in HR proficient (HRP) tumors, that elevated BMI-1 correlates with poor overall survival in HRP but not HRD HGSOC patients, and that HRP HGSOC cells are uniquely sensitive to BMI-1 inhibition.

Transcriptomic Profiling and Pathway Analysis of Mesenchymal Stem Cells Following Low Dose-Rate Radiation Exposure

Low dose-rate radiation exposure can occur in medical imaging, as background from environmental or industrial radiation, and is a hazard of space travel. In contrast with high dose-rate radiation exposure that can induce acute life-threatening syndromes, chronic low-dose radiation is associated with Chronic Radiation Syndrome (CRS), which can alter environmental sensitivity. Secondary effects of chronic low dose-rate radiation exposure include circulatory, digestive, cardiovascular, and neurological diseases, as well as cancer. Here, we investigated 1-2 Gy, 0.66 cGy/h, ⁶⁰Co radiation effects on primary human mesenchymal stem cells (hMSC). There was no significant induction of apoptosis or DNA damage, and cells continued to proliferate. Gene ontology (GO) analysis of transcriptome changes revealed alterations in pathways related to cellular metabolism (cholesterol, fatty acid, and glucose metabolism), extracellular matrix modification and cell adhesion/migration, and regulation of vasoconstriction and inflammation. Interestingly, there was increased hypoxia signaling and increased activation of pathways regulated by iron deficiency, but Nrf2 and related genes were reduced. The data were validated in hMSC and human lung microvascular endothelial cells using targeted qPCR and Western blotting. Notably absent in the GO analysis were alteration pathways for DNA damage response, cell cycle inhibition, senescence, and pro-inflammatory response that we previously observed for high dose-rate radiation exposure. Our findings suggest that cellular gene transcription response to low dose-rate ionizing radiation is fundamentally different compared to high-dose-rate exposure. We hypothesize that cellular response to hypoxia and iron deficiency are driving processes, upstream of the other pathway regulation.

APOE Is Associated With Serum Tau Following Uncomplicated Mild Traumatic Brain Injury

Background and Objectives

APOE e4 has been linked to poor outcome following traumatic brain injury (TBI); however, the mechanisms behind this relationship are unclear. Few studies have investigated the relationship between the APOE genotype and established brain related protein biomarkers following TBI. The purpose of this study was to examine this relationship in service members and veterans (SMVs) following TBI.

Methods

Participants were 209 SMVs [124 uncomplicated mild TBI (mTBI); 85 complicated mild, moderate, severe, or penetrating TBI (mod-sev TBI)] prospectively enrolled in the DVBIC-TBICoE 15-Year Longitudinal TBI Study. APOE genotyping was undertaken using non-fasting blood serum samples. Participants were divided into three groups: APOE e2+, APOE e3/e3, and APOE e4+.

Results

In participants with mTBI, those with the APOE e2 allele had significantly lower levels of tau than those with APOE e4 (p = 0.005, r = 0.43, medium-large effect size). Those with APOE e3/e3 trended toward having higher tau than those APOE e2+ (p = 0.076, r = 0.20, small-medium effect size) and lower tau than those with APOE e4+ (p = 0.062, r = 0.21, small-medium effect size). There were no significant differences in biomarkers based on APOE in the mod-sev TBI group.

Discussion

This study is the first to demonstrate APOE genotype is related to serum tau levels following a mTBI, extending prior findings to human serum following mTBI. In addition to higher serum tau levels in APOE e4 carriers, lower tau levels were observed in APOE e2 carriers, suggesting a possible protective effect.

Recruitment of MLL1 complex is essential for SETBP1 to induce myeloid transformation

Abnormal activation of SETBP1 due to overexpression or missense mutations occurs frequently in various myeloid neoplasms and associates with poor prognosis. Direct activation of Hoxa9/Hoxa10/Myb transcription by SETBP1 and its missense mutants is essential for their transforming capability; however, the underlying epigenetic mechanisms remain elusive. We found that both SETBP1 and its missense mutant SETBP1(D/N) directly interact with histone methyltransferase MLL1. Using a combination of ChIP-seq and RNA-seq analysis in primary hematopoietic stem and progenitor cells, we uncovered extensive overlap in their genomic occupancy and their cooperation in activating many oncogenic transcription factor genes including Hoxa9/Hoxa10/Myb and a large group of ribosomal protein genes. Genetic ablation of Mll1 as well as treatment with an inhibitor of the MLL1 complex OICR-9429 abrogated Setbp1/Setbp1(D/N)-induced transcriptional activation and transformation. Thus, the MLL1 complex plays a critical role in Setbp1-induced transcriptional activation and transformation and represents a promising target for treating myeloid neoplasms with SETBP1 activation.

Rare variant association study of veteran twin whole-genomes links severe depression with a nonsynonymous change in the neuronal gene BHLHE22

OBJECTIVES

Major Depressive Disorder (MDD) is a complex neuropsychiatric disease with known genetic associations, but without known links to rare variation in the human genome. Here we aim to identify rare genetic variants associated with MDD using deep whole-genome sequencing data in an independent population.

METHODS

We report the sequencing of 1,688 whole genomes in a large sample of male-male Veteran twins. Depression status was classified based on a structured diagnostic interview according to DSM-III-R diagnostic criteria. Searching only rare variants in genomic regions from recent GWAS on MDD, we used the optimised sequence kernel association test and Fisher's Exact test to fine map loci associated with severe depression.

RESULTS

Our analysis identified one gene associated with severe depression, basic helix loop helix e22 (P_Adjusted = 0.03) via SKAT-O test between unrelated severely depressed cases compared to unrelated non-depressed controls. The same gene BHLHE22 had a non-silent variant rs13279074 (P_Adjusted = 0.032) based on a single variant Fisher's Exact test between unrelated severely depressed cases compared to unrelated non-depressed controls.

CONCLUSION

The gene BHLHE22 shows compelling genetic evidence of directly impacting the severe depression phenotype. Together these results advance understanding of the genetic contribution to major depressive disorder in a new cohort and link a rare variant to severe forms of the disorder.

Peptide ancestry informative markers in uterine neoplasms from women of European, African, and Asian ancestry

Characterization of ancestry-linked peptide variants in disease-relevant patient tissues represents a foundational step to connect patient ancestry with disease pathogenesis. Nonsynonymous single-nucleotide polymorphisms encoding missense substitutions within tryptic peptides exhibiting high allele frequencies in European, African, and East Asian populations, termed peptide ancestry informative markers (pAIMs), were prioritized from 1000 genomes. In silico analysis identified that as few as 20 pAIMs can determine ancestry proportions similarly to >260K SNPs (R² = 0.99). Multiplexed proteomic analysis of >100 human endometrial cancer cell lines and uterine leiomyoma tissues combined resulted in the quantitation of 62 pAIMs that correlate with patient race and genotype-confirmed ancestry. Candidates include a D451E substitution in GC vitamin D-binding protein previously associated with altered vitamin D levels in African and European populations. pAIMs will support generalized proteoancestry assessment as well as efforts investigating the impact of ancestry on the human proteome and how this relates to the pathogenesis of uterine neoplasms.

Survival motor neuron deficiency slows myoblast fusion through reduced myomaker and myomixer expression

BACKGROUND

Spinal muscular atrophy is an inherited neurodegenerative disease caused by insufficient levels of the survival motor neuron (SMN) protein. Recently approved treatments aimed at increasing SMN protein levels have dramatically improved patient survival and have altered the disease landscape. While restoring SMN levels slows motor neuron loss, many patients continue to have smaller muscles and do not achieve normal motor milestones. While timing of treatment is important, it remains unclear why SMN restoration is insufficient to fully restore muscle size and function. We and others have shown that SMN-deficient muscle precursor cells fail to efficiently fuse into myotubes. However, the role of SMN in myoblast fusion is not known.

METHODS

In this study, we show that SMN-deficient myoblasts readily fuse with wild-type myoblasts, demonstrating fusion competency. Conditioned media from wild type differentiating myoblasts do not rescue the fusion deficit of SMN-deficient cells, suggesting that compromised fusion may primarily be a result of altered membrane dynamics at the cell surface. Transcriptome profiling of skeletal muscle from SMN-deficient mice revealed altered expression of cell surface fusion molecules. Finally, using cell and mouse models, we investigate if myoblast fusion can be rescued in SMN-deficient myoblast and improve the muscle pathology in SMA mice.

RESULTS

We found reduced expression of the muscle fusion proteins myomaker (P = 0.0060) and myomixer (P = 0.0051) in the muscle of SMA mice. Suppressing SMN expression in C2C12 myoblast cells reduces expression of myomaker (35% reduction; P < 0.0001) and myomixer, also known as myomerger and minion, (30% reduction; P < 0.0001) and restoring SMN levels only partially restores myomaker and myomixer expression. Ectopic expression of myomixer improves myofibre number (55% increase; P = 0.0006) and motor function (35% decrease in righting time; P = 0.0089) in SMA model mice and enhances motor function (82% decrease in righting time; P < 0.0001) and extends survival (28% increase; P < 0.01) when administered in combination with an antisense oligonucleotide that increases SMN protein levels.

CONCLUSIONS

Here, we identified reduced expression of muscle fusion proteins as a key factor in the fusion deficits of SMN-deficient myoblasts. This discovery provides a novel target to improve SMA muscle pathology and motor function, which in combination with SMN increasing therapy could enhance clinical outcomes for SMA patients.

Apolipoprotein E e4 is associated with worse self-reported neurobehavioral symptoms following uncomplicated mild traumatic brain injury in U.S. military service members

Past research has found a relationship between the apolipoprotein E (APOE) e4 allele and worse neurobehavioral functioning following mild traumatic brain injury (MTBI) in civilian populations. The purpose of this study was to examine this relationship in service members and veterans (SMVs) following MTBI. Participants were 151 SMVs (103 uncomplicated MTBI; 48 Injured Controls [IC]) prospectively enrolled in the DVBIC-TBICoE 15-Year Longitudinal TBI Study. Participants completed a battery of self-reported neurobehavioral symptom measures on average 76.2 months post-injury (SD = 31.8). APOE genotyping was undertaken using non-fasting blood samples. Participants were classified into four subgroups based on injury (MTBI vs. IC) and APOE e4 allele status (e4 present/absent). In the IC group, there were no significant differences across APOE e4 status subgroups for all measures. In the MTBI group, participants with the APOE e4 allele had significantly worse scores on measures of depression, pain, anxiety, grief, positive well-being, social participation, and resilience compared to those without the e4 allele (d = .44 to d = .69). When comparing the number of 'clinically elevated' neurobehavioral measures simultaneously, the MTBI/e4 present subgroup consistently had a higher number of elevated measures compared to the MTBI/e4 absent, IC/e4 present, and IC/e4 absent subgroups. The APOE e4 allele was associated with poorer neurobehavioral outcome in SMVs in the chronic phase of recovery following MTBI. APOE e4 could be incorporated into screening tools to predict SMVs at risk for poor long-term neurobehavioral outcome in an effort to provide early intervention to improve long-term clinical outcome.

Correction to: Large‑scale pathway specific polygenic risk and transcriptomic community network analysis identifies novel functional pathways in Parkinson disease

A correction to this paper has been published: https://doi.org/10.1007/s00401-021-02309-z

Tensin 1 (TNS1) is a modifier gene for low body mass index (BMI) in homozygous [F508del]CFTR patients

Cystic fibrosis (CF) is a life‐limiting autosomal recessive genetic disease caused by variants in the CFTR gene, most commonly by the [F508del] variant. Although CF is a classical Mendelian disease, genetic variants in several modifier genes have been associated with variation of the clinical phenotype for pulmonary and gastrointestinal function and urogenital development. We hypothesized that whole genome sequencing of a well‐phenotyped CF populations might identify novel variants in known, or hitherto unknown, modifier genes. Whole genome sequencing was performed on the Illumina HiSeq X platform for 98 clinically diagnosed cystic fibrosis patient samples from the Adult CF Clinic at the University of California San Diego (UCSD). We compared protein‐coding, non‐silent variants genome wide between CFTR [F508del] homozygotes vs CFTR compound heterozygotes. Based on a single variant score test, we found 3 SNPs in common variants (MAF >5%) that occurred at significantly different rates between homozygous [F508del]CFTR and compound heterozygous [F508del]CFTR patients. The 3 SNPs were all located in one gene on chromosome 2: Tensin 1 (TNS1: rs3796028; rs2571445: and rs918949). We observed significantly lower BMIs in homozygous [F508del]CFTR patients who were also homozygous for Tensin 1 rs918949 (T/T) (p = 0.023) or rs2571445 (G/G) (p = 0.02) variants. The Tensin 1 gene is thus a potential modifier gene for low BMI in CF patients homozygous for the [F508del]CFTR variant.

Personalized Single-Cell Proteogenomics to Distinguish Acute Myeloid Leukemia from Non-Malignant Clonal Hematopoiesis

Genetic mutations associated with acute myeloid leukemia (AML) also occur in age-related clonal hematopoiesis, often in the same individual. This makes confident assignment of detected variants to malignancy challenging. The issue is particularly crucial for AML post-treatment measurable residual disease monitoring, where results can be discordant between genetic sequencing and flow cytometry. We show here, that it is possible to distinguish AML from clonal hematopoiesis and to resolve the immunophenotypic identity of clonal architecture. To achieve this, we first design patient-specific DNA probes based on patient's whole-genome sequencing, and then use them for patient-personalized single-cell DNA sequencing with simultaneous single-cell antibody-oligonucleotide sequencing. Examples illustrate AML arising from DNMT3A and TET2 mutated clones as well as independently. The ability to personalize single-cell proteogenomic assessment for individual patients based on leukemia-specific genomic features has implications for ongoing AML precision medicine efforts.

Transcriptomic Analysis of Mouse Brain After Traumatic Brain Injury Reveals That the Angiotensin Receptor Blocker Candesartan Acts Through Novel Pathways

Traumatic brain injury (TBI) results in complex pathological reactions, where the initial lesion is followed by secondary inflammation and edema. Our laboratory and others have reported that angiotensin receptor blockers (ARBs) have efficacy in improving recovery from traumatic brain injury in mice. Treatment of mice with a subhypotensive dose of the ARB candesartan results in improved functional recovery, and reduced pathology (lesion volume, inflammation and gliosis). In order to gain a better understanding of the molecular mechanisms through which candesartan improves recovery after controlled cortical impact injury (CCI), we performed transcriptomic profiling on brain regions after injury and drug treatment. We examined RNA expression in the ipsilateral hippocampus, thalamus and hypothalamus at 3 or 29 days post injury (dpi) treated with either candesartan (0.1 mg/kg) or vehicle. RNA was isolated and analyzed by bulk mRNA-seq. Gene expression in injured and/or candesartan treated brain region was compared to that in sham vehicle treated mice in the same brain region to identify genes that were differentially expressed (DEGs) between groups. The most DEGs were expressed in the hippocampus at 3 dpi, and the number of DEGs reduced with distance and time from the lesion. Among pathways that were differentially expressed at 3 dpi after CCI, candesartan treatment altered genes involved in angiogenesis, interferon signaling, extracellular matrix regulation including integrins and chromosome maintenance and DNA replication. At 29 dpi, candesartan treatment reduced the expression of genes involved in the inflammatory response. Some changes in gene expression were confirmed in a separate cohort of animals by qPCR. Fewer DEGs were found in the thalamus, and only one in the hypothalamus at 3 dpi. Additionally, in the hippocampi of sham injured mice, 3 days of candesartan treatment led to the differential expression of 384 genes showing that candesartan in the absence of injury had a powerful impact on gene expression specifically in the hippocampus. Our results suggest that candesartan has broad actions in the brain after injury and affects different processes at acute and chronic times after injury. These data should assist in elucidating the beneficial effect of candesartan on recovery from TBI.

Large-scale pathway specific polygenic risk and transcriptomic community network analysis identifies novel functional pathways in Parkinson disease

Polygenic inheritance plays a central role in Parkinson disease (PD). A priority in elucidating PD etiology lies in defining the biological basis of genetic risk. Unraveling how risk leads to disruption will yield disease-modifying therapeutic targets that may be effective. Here, we utilized a high-throughput and hypothesis-free approach to determine biological processes underlying PD using the largest currently available cohorts of genetic and gene expression data from International Parkinson's Disease Genetics Consortium (IPDGC) and the Accelerating Medicines Partnership-Parkinson's disease initiative (AMP-PD), among other sources. We applied large-scale gene-set specific polygenic risk score (PRS) analyses to assess the role of common variation on PD risk focusing on publicly annotated gene sets representative of curated pathways. We nominated specific molecular sub-processes underlying protein misfolding and aggregation, post-translational protein modification, immune response, membrane and intracellular trafficking, lipid and vitamin metabolism, synaptic transmission, endosomal-lysosomal dysfunction, chromatin remodeling and apoptosis mediated by caspases among the main contributors to PD etiology. We assessed the impact of rare variation on PD risk in an independent cohort of whole-genome sequencing data and found evidence for a burden of rare damaging alleles in a range of processes, including neuronal transmission-related pathways and immune response. We explored enrichment linked to expression cell specificity patterns using single-cell gene expression data and demonstrated a significant risk pattern for dopaminergic neurons, serotonergic neurons, hypothalamic GABAergic neurons, and neural progenitors. Subsequently, we created a novel way of building de novo pathways by constructing a network expression community map using transcriptomic data derived from the blood of PD patients, which revealed functional enrichment in inflammatory signaling pathways, cell death machinery related processes, and dysregulation of mitochondrial homeostasis. Our analyses highlight several specific promising pathways and genes for functional prioritization and provide a cellular context in which such work should be done.

Abstract 5893: Comprehensive proteogenomic analysis and classification of lung adenocarcinoma

Lung adenocarcinoma is a highly lethal tumor that displays extensive molecular heterogeneity of which deep characterization may drive therapeutic development and improve clinical outcomes. Through the Applied Proteogenomics Organizational Learning and Outcomes (APOLLO) research network, we utilized five molecular profiling technologies (DNA whole genome sequencing, RNA sequencing, total and phospho-proteomics by mass spectrometry, and reverse phase protein arrays [RPPA]) to characterize a longitudinally-annotated cohort of 87 lung adenocarcinomas. Through whole genome sequencing, we identified molecular signatures from patterns of somatic SNVs, indels, and large structural alterations that stratified tumors into three groups associated with patient smoke exposures. We also identified TP53, EGFR, KRAS, and STK11 as recurrently mutated genes, which together represent 80% of the cohort, in addition to genes mutated in smaller cohort subsets (e.g. RBM10), fusion genes, and pathogenic germline variants. To characterize tumor proteomes, we quantified &gt;7,000 proteins and &gt;10,000 phosphopeptides by mass spectrometry and &gt;300 species by RPPA. Matched RNAs and proteins were typically positively correlated across samples (median ρ = 0.49). Through quantitative trait loci analyses, we identified genes whose RNA and protein expression levels were significantly modified by somatic mutations. We then classified tumors into RNA expression subtypes and found coordinated proteogenomic alterations and distinct clinical associations: terminal respiratory unit subtype – EGFR mutations and RNA/protein overexpression, acinar histology, non-smokers; proximal-proliferative subtype – STK11 mutations and RNA/protein underexpression, high smoking signature; proximal-inflammatory subtype – high tumor mutational burden. We also identified phospho-peptide signatures associated with these subtypes, including downregulation of CDK1/2 targets in terminal respiratory unit tumors. Protein co-expression network analysis discovered biologically-diverse pathway activities of the RNA expression subtypes. To interrogate somatic mutations in the context of molecular pathways, we projected DNA alterations onto known interaction networks and identified four subtypes with markedly distinct proteomic and microenvironment characteristics. Finally, several molecular characteristics were found to significantly predict patient outcomes, including RNA expression subtype classification against metastasis-free survival. Thus, our integrative, proteogenomic characterization of lung adenocarcinoma uncovered novel tumor biology and identified potential molecular markers for predicting patient outcomes. The views expressed in this abstract are solely of the authors and do not reflect the official policy of the Departments of Army/Navy/Air Force, Department of Defense, USUHS, HJF, or U.S. Government.

Citation Format: Anthony R. Soltis, Nicholas W. Bateman, Thomas P. Conrads, Clifton L. Dalgard, Hai Hu, Teri J. Franks, Jianfang Liu, Daoud Meerzaman, Emanuel F. Petricoin, Qingrong Chen, Chunhua Yan, Xijun Zhang, Clesson E. Turner, The APOLLO Research Network, Craig D. Shriver, Christopher A. Moskaluk, Robert F. Browning, Matthew D. Wilkerson. Comprehensive proteogenomic analysis and classification of lung adenocarcinoma [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 5893.

MutEnricher: a flexible toolset for somatic mutation enrichment analysis of tumor whole genomes

Background

Analysis of somatic mutations from tumor whole exomes has fueled discovery of novel cancer driver genes. However, ~ 98% of the genome is non-coding and includes regulatory elements whose normal cellular functions can be disrupted by mutation. Whole genome sequencing (WGS), on the other hand, allows for identification of non-coding somatic variation and expanded estimation of background mutation rates, yet fewer computational tools exist for specific interrogation of this space.

Results

We present MutEnricher, a flexible toolset for investigating somatic mutation enrichment in both coding and non-coding genomic regions from WGS data. MutEnricher contains two distinct modules for these purposes that provide customizable options for calculating sample- and feature-specific background mutation rates. Additionally, both MutEnricher modules calculate feature-level and local, or “hotspot,” somatic mutation enrichment statistics.

Conclusions

MutEnricher is a flexible software package for investigating somatic mutation enrichment that is implemented in Python, is freely available, can be efficiently parallelized, and is highly configurable to researcher's specific needs. MutEnricher is available online at https://github.com/asoltis/MutEnricher.

Hemophilia A Inhibitor Subjects Show Unique PBMC Gene Expression Profiles That Include Up-Regulated Innate Immune Modulators

Formation of pathological anti-FVIII antibodies, or "inhibitors," is the most serious complication of therapeutic FVIII infusions, affecting up to 1/3 of severe Hemophilia A (HA) patients. Inhibitor formation is a classical T-cell dependent adaptive immune response. As such, it requires help from the innate immune system. However, the roles of innate immune cells and mechanisms of inhibitor development vs. immune tolerance, achieved with or without Immune Tolerance Induction (ITI) therapy, are not well-understood. To address these questions, temporal transcriptomics profiling of FVIII-stimulated peripheral blood mononuclear cells (PBMCs) was carried out for HA subjects with and without a current or historic inhibitor using RNA-Seq. PBMCs were isolated from 40 subjects in the following groups: HA with an inhibitor that resolved either following ITI or spontaneously; HA with a current inhibitor; HA with no inhibitor history and non-HA controls. PBMCs were stimulated with 5 nM FVIII and RNA was isolated 4, 16, 24, and 48 h following stimulation. Time-series differential expression analysis was performed and distinct transcriptional signatures were identified for each group, providing clues as to cellular mechanisms leading to or accompanying their disparate anti-FVIII antibody responses. Subjects with a current inhibitor showed differential expression of 56 genes and a clustering analysis identified three major temporal profiles. Interestingly, gene ontology enrichments featured innate immune modulators, including NLRP3, TLR8, IL32, CLEC10A, and COLEC12. NLRP3 and TLR8 are associated with enhanced secretion of the pro-inflammatory cytokines IL-1β and TNFα, while IL32, which has several isoforms, has been associated with both inflammatory and regulatory immune processes. RNA-Seq results were validated by RT-qPCR, ELISAs, multiplex cytokine analysis, and flow cytometry. The inflammatory status of HA patients suffering from an ongoing inhibitor includes up-regulated innate immune modulators, which may act as ongoing danger signals that influence the responses to, and eventual outcomes of, ITI therapy.

Molecular Analysis of Clinically Defined Subsets of High-Grade Serous Ovarian Cancer

The diversity and heterogeneity within high-grade serous ovarian cancer (HGSC), which is the most lethal gynecologic malignancy, is not well understood. Here, we perform comprehensive multi-platform omics analyses, including integrated analysis, and immune monitoring on primary and metastatic sites from highly clinically annotated HGSC samples based on a laparoscopic triage algorithm from patients who underwent complete gross resection (R0) or received neoadjuvant chemotherapy (NACT) with excellent or poor response. We identify significant distinct molecular abnormalities and cellular changes and immune cell repertoire alterations between the groups, including a higher rate of NF1 copy number loss, and reduced chromothripsis-like patterns, higher levels of strong-binding neoantigens, and a higher number of infiltrated T cells in the R0 versus the NACT groups.

Gene therapy-emulating small molecule treatments in cystic fibrosis airway epithelial cells and patients

Background

Several small molecule corrector and potentiator drugs have recently been licensed for Cystic Fibrosis (CF) therapy. However, other aspects of the disease, especially inflammation, are less effectively treated by these drugs. We hypothesized that small molecule drugs could function either alone or as an adjuvant to licensed therapies to treat these aspects of the disease, perhaps emulating the effects of gene therapy in CF cells. The cardiac glycoside digitoxin, which has been shown to inhibit TNFα/NFκB signaling in CF lung epithelial cells, may serve as such a therapy.

Methods

IB3–1 CF lung epithelial cells were treated with different Vertex (VX) drugs, digitoxin, and various drug mixtures, and ELISA assays were used to assess suppression of baseline and TNFα-activated secretion of cytokines and chemokines. Transcriptional responses to these drugs were assessed by RNA-seq and compared with gene expression in AAV-[wildtype]CFTR-treated IB3–1 (S9) cells. We also compared in vitro gene expression signatures with in vivo data from biopsied nasal epithelial cells from digitoxin-treated CF patients.

Results

CF cells exposed to digitoxin exhibited significant suppression of both TNFα/NFκB signaling and downstream secretion of IL-8, IL-6 and GM-CSF, with or without co-treatment with VX drugs. No evidence of drug-drug interference was observed. RNA-seq analysis showed that gene therapy-treated CF lung cells induced changes in 3134 genes. Among these, 32.6% were altered by digitoxin treatment in the same direction. Shared functional gene ontology themes for genes suppressed by both digitoxin and gene therapy included inflammation (84 gene signature), and cell-cell interactions and fibrosis (49 gene signature), while genes elevated by both were enriched for epithelial differentiation (82 gene signature). A new analysis of mRNA data from digitoxin-treated CF patients showed consistent trends in expression for genes in these signatures.

Conclusions

Adjuvant gene therapy-emulating activities of digitoxin may contribute to enhancing the efficacy of currently licensed correctors and potentiators in CF patients.

FOXP3 protects conventional human T cells from premature restimulation-induced cell death

The adaptive immune response relies on specific apoptotic programs to maintain homeostasis. Conventional effector T cell (Tcon) expansion is constrained by both forkhead box P3 (FOXP3)⁺-regulatory T cells (Tregs) and restimulation-induced cell death (RICD), a propriocidal apoptosis pathway triggered by repeated stimulation through the T-cell receptor (TCR). Constitutive FOXP3 expression protects Tregs from RICD by suppressing SLAM-associated protein (SAP), a key adaptor protein that amplifies TCR signaling strength. The role of transient FOXP3 induction in activated human CD4 and CD8 Tcons remains unresolved, but its expression is inversely correlated with acquired RICD sensitivity. Here, we describe a novel role for FOXP3 in protecting human Tcons from premature RICD during expansion. Unlike FOXP3-mediated protection from RICD in Tregs, FOXP3 protects Tcons through a distinct mechanism requiring de novo transcription that does not require SAP suppression. Transcriptome profiling and functional analyses of expanding Tcons revealed that FOXP3 enhances expression of the SLAM family receptor CD48, which in turn sustains basal autophagy and suppresses pro-apoptotic p53 signaling. Both CD48 and FOXP3 expression reduced p53 accumulation upon TCR restimulation. Furthermore, silencing FOXP3 expression or blocking CD48 decreased the mitochondrial membrane potential in expanding Tcons with a concomitant reduction in basal autophagy. Our findings suggest that FOXP3 governs a distinct transcriptional program in early-stage effector Tcons that maintains RICD resistance via CD48-dependent protective autophagy and p53 suppression.

Acidification of Tumor at Stromal Boundaries Drives Transcriptome Alterations Associated with Aggressive Phenotypes

Acidosis is a fundamental feature of the tumor microenvironment, which directly regulates tumor cell invasion by affecting immune cell function, clonal cell evolution, and drug resistance. Despite the important association of tumor microenvironment acidosis with tumor cell invasion, relatively little is known regarding which areas within a tumor are acidic and how acidosis influences gene expression to promote invasion. Here, we injected a labeled pH-responsive peptide to mark acidic regions within tumors. Surprisingly, acidic regions were not restricted to hypoxic areas and overlapped with highly proliferative, invasive regions at the tumor-stroma interface, which were marked by increased expression of matrix metalloproteinases and degradation of the basement membrane. RNA-seq analysis of cells exposed to low pH conditions revealed a general rewiring of the transcriptome that involved RNA splicing and enriched for targets of RNA binding proteins with specificity for AU-rich motifs. Alternative splicing of Mena and CD44, which play important isoform-specific roles in metastasis and drug resistance, respectively, was sensitive to histone acetylation status. Strikingly, this program of alternative splicing was reversed in vitro and in vivo through neutralization experiments that mitigated acidic conditions. These findings highlight a previously underappreciated role for localized acidification of tumor microenvironment in the expression of an alternative splicing-dependent tumor invasion program. SIGNIFICANCE: This study expands our understanding of acidosis within the tumor microenvironment and indicates that acidosis induces potentially therapeutically actionable changes to alternative splicing.

Sleep Deprivation Alters the Pituitary Stress Transcriptome in Male and Female Mice

Poor sleep hygiene is a growing problem, with detrimental effects on many biological systems. The pituitary gland plays a crucial role in the regulation of sleep and the stress response, and its dysfunction leads to sleep-related disorders. However, the interaction between these critical functions remains unclear. Thus, we performed a comparative, whole-transcriptome, analysis to identify stress-induced genes and relevant pathways that may be affected by sleep deprivation. One day following 12 h of Paradoxical Sleep Deprivation (PSD), mice were restrained for 20 min. Gene expression changes in the pituitary were assessed via RNA-Seq and Gene Ontology in PSD and/or restrained groups compared to controls. We show that restraint triggers transcriptional responses involved in hormone secretion, the glucocorticoid response, and apoptosis in both sexes, with 285 differentially expressed genes in females and 93 in males. When PSD preceded restraint stress, the numbers of differentially expressed genes increased to 613 in females and 580 in males. The pituitary transcriptome of restraint+PSD animals was enriched for microglia and macrophage proliferation, cellular response to corticosteroids, and apoptosis, among others. Finally, we identify sex-specific differences in restraint-induced genes following PSD. These findings provide genetic targets to consider when studying sleep and the response to stress.

Abstract 2281: Flexible discovery of recurrent coding and non-coding mutations in tumor whole genomes

Analysis of somatic protein-coding mutations, particularly via tumor exome sequencing, has driven discovery of novel cancer genes in recent years. However, ~97% of the human genome is non-coding and not addressable by exome-targeting methods. Tumor whole genome sequencing, by contrast, allows for genome-wide discovery of somatic events and may identify novel non-coding driver mutations. In conjunction, flexible tools employing principled statistical methods are needed for discovery of recurrent somatic driver mutations from tumor whole genomes.

Here, we developed a computational toolset that addresses these needs and describe its application to a novel cohort of lung adenocarcinoma tumors generated by the APOLLO (Applied Proteogenomics OrganizationaL Learning and Outcomes) consortium. Our toolset flexibly computes feature-wise and hotspot somatic mutation enrichment statistics in both protein-coding and non-coding (e.g. promoters, enhancers) genomic regions. Additionally, we incorporated an affinity propagation-based clustering procedure that groups test regions by user-specified genomic covariates that can influence local mutation properties.

We applied our toolset to several TCGA datasets of tumor exome sequencing. We found strong agreement between our results and those of other tools: among the top 15 genes called at FDR &lt; 0.01 by MutSigCV, we observed a median overlap of 75.7% with genes ranked in the top 15 by our methods. We next applied our toolset to tumor whole genome sequencing data from our APOLLO lung adenocarcinoma cohort. During analysis, we simultaneously controlled for several genomic covariates, including GC/CpG content, replication timing, and proximal mRNA expression. Gene-centric analysis identified several significantly mutated genes, including KRAS, STK11, and TP53 (FDR &lt; 0.005). We examined matched mRNA-seq data from this cohort and found significant over-expression of KRAS mRNA in samples possessing a non-silent coding mutation in this gene (p &lt; 0.02). We additionally assessed somatic mutation enrichment in promoters, 3' UTRs, non-coding genes, and lung-specific enhancers. From these results, we found significant enrichment of somatic mutations in the body of the long non-coding RNA NEAT1. Among the tumors with somatic NEAT1 mutations, a single sample was hypermutated at this locus and corresponded with the lowest observed RNA expression for this lncRNA in our cohort (TPM of 12.2 vs. overall mean TPM of 84.2).

In conclusion, we developed a flexible toolset for interrogating both coding and non-coding landscapes from tumor whole genomes. We applied our methods to a novel cohort of lung adenocarcinoma tumors and identified recurrently mutated genes and non-coding regions, including the NEAT1 lncRNA.

Citation Format: Anthony R. Soltis, Coralie Viollet, Harvey B. Pollard, Christopher A. Moskaluk, Robert F. Browning, Clifton L. Dalgard, Craig D. Shriver, Matthew D. Wilkerson. Flexible discovery of recurrent coding and non-coding mutations in tumor whole genomes [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 2281.

Network-Based Interpretation of Diverse High-Throughput Datasets through the Omics Integrator Software Package

High-throughput, ‘omic’ methods provide sensitive measures of biological responses to perturbations. However, inherent biases in high-throughput assays make it difficult to interpret experiments in which more than one type of data is collected. In this work, we introduce Omics Integrator, a software package that takes a variety of ‘omic’ data as input and identifies putative underlying molecular pathways. The approach applies advanced network optimization algorithms to a network of thousands of molecular interactions to find high-confidence, interpretable subnetworks that best explain the data. These subnetworks connect changes observed in gene expression, protein abundance or other global assays to proteins that may not have been measured in the screens due to inherent bias or noise in measurement. This approach reveals unannotated molecular pathways that would not be detectable by searching pathway databases. Omics Integrator also provides an elegant framework to incorporate not only positive data, but also negative evidence. Incorporating negative evidence allows Omics Integrator to avoid unexpressed genes and avoid being biased toward highly-studied hub proteins, except when they are strongly implicated by the data. The software is comprised of two individual tools, Garnet and Forest, that can be run together or independently to allow a user to perform advanced integration of multiple types of high-throughput data as well as create condition-specific subnetworks of protein interactions that best connect the observed changes in various datasets. It is available at http://fraenkel.mit.edu/omicsintegrator and on GitHub at https://github.com/fraenkel-lab/OmicsIntegrator.

Robustness portraits of diverse biological networks conserved despite order-of-magnitude parameter uncertainty

MOTIVATION

Biological networks are robust to a wide variety of internal and external perturbations, yet fragile or sensitive to a small minority of perturbations. Due to this rare sensitivity of networks to certain perturbations, it is unclear how precisely biochemical parameters must be experimentally measured in order to accurately predict network function.

RESULTS

Here, we examined a model of cardiac β-adrenergic signaling and found that its robustness portrait, a global measure of steady-state network function, was well conserved even when all parameters were rounded to their nearest 1-2 orders of magnitude. In contrast, β-adrenergic network kinetics were more sensitive to parameter precision. This analysis was then extended to 10 additional networks, including Escherichia coli chemotaxis, stem cell differentiation and cytokine signaling, of which nine exhibited conserved robustness portraits despite the order-of-magnitude approximation of their biochemical parameters. Thus, both fragile and robust aspects of diverse biological networks are largely shaped by network topology and can be predicted despite order-of-magnitude uncertainty in biochemical parameters. These findings suggest an iterative strategy where order-of-magnitude models are used to prioritize experiments toward the fragile network elements that require precise measurements, efficiently driving model revision.

CONTACT

jsaucerman@virginia.edu

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Synergy between CaMKII substrates and β-adrenergic signaling in regulation of cardiac myocyte Ca(2+) handling

Cardiac excitation-contraction coupling is a highly coordinated process that is controlled by protein kinase signaling pathways, including Ca(2+)/calmodulin-dependent protein kinase II (CaMKII) and protein kinase A (PKA). Increased CaMKII expression and activity (as occurs during heart failure) destabilizes EC coupling and may lead to sudden cardiac death. To better understand mechanisms of cardiac CaMKII function, we integrated dynamic CaMKII-dependent regulation of key Ca(2+) handling targets with previously validated models of cardiac EC coupling, Ca(2+)/calmodulin-dependent activation of CaMKII, and β-adrenergic activation of PKA. Model predictions are validated against CaMKII-overexpression data from rabbit ventricular myocytes. The model demonstrates how overall changes to Ca(2+) handling during CaMKII overexpression are explained by interactions between individual CaMKII substrates. CaMKII and PKA activities during β-adrenergic stimulation may synergistically facilitate inotropic responses and contribute to a CaMKII-Ca(2+)-CaMKII feedback loop. CaMKII regulated early frequency-dependent acceleration of relaxation and EC coupling gain (which was highly sarcoplasmic reticulum Ca(2+) load-dependent). Additionally, the model identifies CaMKII-dependent ryanodine receptor hyperphosphorylation as a proarrhythmogenic trigger. In summary, we developed a detailed computational model of CaMKII and PKA signaling in cardiac myocytes that provides unique insights into their regulation of normal and pathological Ca(2+) handling.

Modeling cardiac β-adrenergic signaling with normalized-Hill differential equations: comparison with a biochemical model

Background

New approaches are needed for large-scale predictive modeling of cellular signaling networks. While mass action and enzyme kinetic approaches require extensive biochemical data, current logic-based approaches are used primarily for qualitative predictions and have lacked direct quantitative comparison with biochemical models.

Results

We developed a logic-based differential equation modeling approach for cell signaling networks based on normalized Hill activation/inhibition functions controlled by logical AND and OR operators to characterize signaling crosstalk. Using this approach, we modeled the cardiac β₁-adrenergic signaling network, including 36 reactions and 25 species. Direct comparison of this model to an extensively characterized and validated biochemical model of the same network revealed that the new model gave reasonably accurate predictions of key network properties, even with default parameters. Normalized Hill functions improved quantitative predictions of global functional relationships compared with prior logic-based approaches. Comprehensive sensitivity analysis revealed the significant role of PKA negative feedback on upstream signaling and the importance of phosphodiesterases as key negative regulators of the network. The model was then extended to incorporate recently identified protein interaction data involving integrin-mediated mechanotransduction.

Conclusions

The normalized-Hill differential equation modeling approach allows quantitative prediction of network functional relationships and dynamics, even in systems with limited biochemical data.