S772 Risankizumab Therapy Induces Improvements in Endoscopic Endpoints in Patients With Moderate-To-Severe Crohn’s Disease: Results From the Phase 3 ADVANCE and MOTIVATE Studies
Cross-Cancer Genome-Wide Association Study of Endometrial Cancer and Epithelial Ovarian Cancer Identifies Genetic Risk Regions Associated with Risk of Both Cancers
Abstract Background: Accumulating evidence suggests a relationship between endometrial cancer and ovarian cancer. Independent genome-wide association studies (GWAS) for endometrial cancer and ovarian cancer have identified 16 and 27 risk regions, respectively, four of which overlap between the two cancers. We aimed to identify joint endometrial and ovarian cancer risk loci by performing a meta-analysis of GWAS summary statistics from these two cancers. Methods: Using LDScore regression, we explored the genetic correlation between endometrial cancer and ovarian cancer. To identify loci associated with the risk of both cancers, we implemented a pipeline of statistical genetic analyses (i.e., inverse-variance meta-analysis, colocalization, and M-values) and performed analyses stratified by subtype. Candidate target genes were then prioritized using functional genomic data. Results: Genetic correlation analysis revealed significant genetic correlation between the two cancers (rG = 0.43, P = 2.66 × 10−5). We found seven loci associated with risk for both cancers (PBonferroni < 2.4 × 10−9). In addition, four novel subgenome-wide regions at 7p22.2, 7q22.1, 9p12, and 11q13.3 were identified (P < 5 × 10−7). Promoter-associated HiChIP chromatin loops from immortalized endometrium and ovarian cell lines and expression quantitative trait loci data highlighted candidate target genes for further investigation. Conclusions: Using cross-cancer GWAS meta-analysis, we have identified several joint endometrial and ovarian cancer risk loci and candidate target genes for future functional analysis. Impact: Our research highlights the shared genetic relationship between endometrial cancer and ovarian cancer. Further studies in larger sample sets are required to confirm our findings.
Macrophage Inflammatory Protein (MIP)-1alpha (CCL3) Is a Downstream Target of FGFR3 and RAS Signaling in Multiple Myeloma.
Abstract The identification of the t(4;14) translocation in Multiple Myeloma (MM) provided the first indication that fibroblast growth factor 3 (FGFR3) could act as an oncogene. Several studies have assessed the potential of FGFR3 as a drug target and have shown that inhibition of FGFRs using tyrosine kinase inhibitors induces cell death of FGFR3 expressing MM cells. To clarify the signaling pathways implicated in FGFR3 dependent myeloma, we assessed gene expression changes associated with treatment of MM cell lines with three known small molecule FGFR inhibitors, PD173074, SU5402 and a third novel compound using Human U133_Plus2 arrays. In addition to describing the unique pharmacogenomic signals of each drug in myeloma, 845 differentially expressed genes, common to all three FGFR3 inhibitors, were identified. Cell cycle, DNA replication and ATP binding proteins were the most common (47%) functional classes of genes effected. Further validation and refinement of this gene list was conducted using FGFR3 siRNA inhibition and FGF ligand induction. 120 genes were altered between FGFR3 RNAi and scrambled control and 892 were induced by FGF ligand. Ten genes were commonly identified as significantly regulated by all 4 FGFR3 inhibitors and induced in the opposing direction by ligand. Of these macrophage inflammatory protein (MIP)-1alpha, and dual specific phosphatase 6 (DUSP6) were positively regulative while ANXA9, CR2, AL531683, ZNF589, AW274468, FRMD3, LTB and WDR42A were negatively regulated by FGFR3 signaling. Validating our findings, a feedback loop between FGFR/ERK/MAP kinase activation and DUSP6 has previously been described in the literature. MIP-1alpha however was the most significantly altered (12 fold) on array, and MIP-1alpha regulation in response to FGFR3 pathway stimulation was confirmed by flow cytometry and Western blot. Mining of publicly available array datasets on 174 MM patients significantly associated MIP1-alpha with FGFR3 expression (p=0.01). Of note down-regulation of MIP-1alpha was not observed following FGFR3 inhibition in MM cells with RAS mutations. Based on these, and previous findings, we hypothesized that MIP-1alpha was regulated by the FGFR3/ERK/MAP kinase pathway. Indeed, inhibition of ERK in FGFR inhibitor resistant cells with RAS mutations also led to down regulation of MIP-1alpha. Because of the recognized role of MIP1-alpha (CCL3) in survival and proliferation of MM cells and in MM bone disease, our observations raise the possibility that pharmacological inhibition of MIP-1 alpha may hold therapeutic promise in t(4;14) MM and may serve as a biomarker for successful FGFR3 or RAS signaling inhibition.
A multicenter, randomized, double-blind, placebo-controlled trial of thalidomide plus dexamethasone versus dexamethasone alone as initial therapy for newly diagnosed multiple myeloma
7517 Background: Thalidomide plus dexamethasone (Thal/Dex) yields superior response rates versus dexamethasone (Dex) but its impact as primary therapy for multiple myeloma (MM) is unknown. Methods: Patients (pts) with previously untreated, symptomatic MM were eligible and were randomized in this double-blind trial to Thal/Dex (Arm A) or placebo plus Dex (Arm B). Pts in Arm A received Thal 50 mg PO daily, escalated to 100 mg on day 15, and to 200 mg from day 1 of cycle 2; Dex 40 mg PO was given on days 1–4, 9–12, and 17–20. Pts in Arm B received placebo instead of Thal, and Dex as in Arm A. Cycles were 28 days long, repeated until progression or undue toxicity. The primary endpoint was time to progression (TTP) defined using EBMT criteria. All analyses were intent to treat. Planned sample size was 218 eligible pts in each arm. Full information for one-sided log rank test with significance level of 0.025 (allowing for 1interim analysis) to have 80% power to detect a 40% improvement in TTP (16.8 mo in Arm A vs. 12 mo in Arm B) would be achieved when 282 pts have progressed. A pre-planned interim analysis of the primary endpoint and safety was performed by an independent Data Monitoring Committee (DMC). P value < 0.0015 at this interim analysis would indicate that Arm A is superior to Arm B based on an alpha-spending function of the O’Brien-Fleming type. The DMC recommended release of results. Results: 470 pts were enrolled: 235 randomized to Thal/Dex and 235 to placebo/Dex. Median follow-up was 25 months. Median age was 65 yrs. TTP was significantly superior with Thal/Dex vs placebo/Dex, median TTP 17.4 months (95% CI: 8.1 months-NE) vs 6.4 months (95% CI: 5.6–7.4 months), respectively, P < 0.000065, crossing the upper boundary for superiority. DVT was higher with Thal/Dex vs placebo/Dex, 15.4% vs 4.3%, respectively. Median survival was not reached in either arm. Conclusions: Thal/Dex is significantly superior to Dex alone as first-line therapy for multiple myeloma. [Table: see text] [Table: see text]
Hippocampal changes in mice lacking an active prohormone convertase 2
AbstractProhormone convertase 2 (PC2) is essential for the biosynthesis of many neuropeptides, including several of them in hippocampus. In mouse brain, lacking an enzymatically active PC2 (PC2‐null) causes accumulation of many neuropeptides in their precursor or intermediate forms. Little is known about how a PC2‐null state may affect the function of the hippocampus. In this study, adult PC2‐null mice and their wildtype (WT) littermates were subjected to three analyses to determine possible changes associated with PC2‐null at physiological, behavioral, and molecular levels, respectively, under normal and stressed conditions. Electrophysiological recordings of hippocampal slices were performed to measure evoked field‐excitatory postsynaptic potentials (EPSP), long‐term potentiation (LTP), and paired‐pulse facilitation (PPF). Morris water maze (MWM) testing was conducted to examine behavioral changes that are indicative of hippocampal integrity. Quantitative mass spectrometry analysis was used to determine changes in the hippocampal proteome in response to a focal cerebral ischemic insult. We found that there were no significant differences in the threshold of evoked EPSPs between PC2‐null and WT animals. However, an increase in LTP in both triggering rate and amplitude was observed in PC2‐null mice, suggesting that PC2 may be involved in regulating synaptic strength. The PPF, on the other hand, showed a decrease in PC2‐null mice, suggesting a presynaptic mechanism. Consistent with changes in LTP, PC2‐null mice displayed decreased latencies in finding the escape platform in the MWM test. Further, after distal focal cerebral ischemia, the hippocampal proteomes incurred changes in both WT and PC2‐null mice, with a prominent change in proteins associated with neurotransmission, exocytosis, and transport processes seen in the PC2‐null but not WT mice. Taken together, our results suggest that PC2 is involved in regulating hippocampal synaptic plasticity, learning, and memory behaviors, as well as the hippocampal response to stresses originating in other regions of the brain.
A Single-Cell Transcriptional Analysis of Tumour Cells and the Immune Microenvironment during Disease Evolution in a Transgenic Mouse Model of Myeloma
Abstract Introduction: Multiple Myeloma (MM) is consistently preceded by pre-malignant asymptomatic monoclonal gammopathies (AMG). To date, our understanding of the pathogenesis of progression to MM remains incomplete. Genetic analyses of AMG cells compared to MM-derived plasma cells (PCs) have found few differences, suggesting that progression may be mediated in part by tumour-extrinsic mechanisms. To comprehensively examine the cellular and molecular complexities of MM pathogenesis, we performed an unbiased single cell RNA-sequencing (scRNA-seq) analysis of tumour cells as well as immune cells from the tumour microenvironment (TME) derived from transgenic mice transitioning from AMG to MM. Methods: We employed the Vk*MYC immune-competent mouse model of MM (C57BL/6/KaLwRij), which is a clinically and biologically faithful model of untreated disease that similarly progresses from AMG to MM with age. We established an age-based cohort of Vk*MYC mice to recapitulate a range of MM disease stages, generated single-cell suspensions from flushed bone marrow and subjected these cells to scRNA-seq profiling (10x Genomics). Results: Across 12 samples profiled to date, our scRNA-seq dataset contains 82,853 high-quality cells, expressing 17,922 genes. We employed dimensionality reduction and unsupervised graph-based clustering to visualize and group transcriptionally-similar cell populations, which revealed 42 clusters. Expression of known marker genes and computed correlation scores with bulk gene expression reference datasets enabled annotation of cell types, revealing both malignant cells and non-malignant immune cell populations. We first focused on single cell T/NK profiles in our data given the emerging utility of immune checkpoint inhibitors that target these populations. Although we did not observe numerical differences in the proportion of CD8+ T cells across disease stages, analysis of immune checkpoint receptor genes revealed increased expression of Pdcd1 (PD-1) and Lag3 in CD8+ T cells from mice with disease. Co-expression of LAG3 and PD-1 proteins was also confirmed using a Vk*MYC transplantable model, with a positive correlation between disease burden (%CD138+/B220- cells) and %PD1+LAG3+ CD8+ T cells by flow cytometry. Consistent with reports of PD-1 and LAG3 co-expression on non-functional exhausted T cells, CD8+ T cells from diseased mice demonstrated elevated T cell exhaustion scores in our scRNA-seq dataset. These observations suggest that T cell exhaustion may be mediated by multiple immune checkpoint receptors during disease evolution. Although combinatorial treatment with PD-1 and LAG3 antibodies failed to induce tumour regression in mice with established disease, the addition of cyclophosphamide (Cy) to these antibodies resulted in marked improvement in survival of the mice compared to Cy alone, presumably by promoting immunogenic cell death. Studies exploring the combination of LAG3 and PD-1 antibodies as a strategy to inhibit transition from AMG to MM in the Vk*MYC mice are ongoing and will be reported. We also performed subclustering analysis of 5,228 Sdc1+ (CD138) PCs in our scRNA-seq dataset revealing 11 distinct clusters, with evidence of inter- and intra-tumoural heterogeneity across all Vk*MYC mice. Differential gene expression analysis revealed a non-malignant PC (nPC) cluster as supported by lower Myc transgene and Ccnd2 expression. Moreover, this cluster was predominantly comprised of cells from age-matched control mice or mice with earlier disease. Single-cell chromosomal copy number analysis revealed loss of Chr5 in the majority of tumour cells from MM mice, but not in the nPC cluster. Loss of Chr5 was observed in tumor subclones from all AMG mice suggesting that it is an early and potentially unifying event in Vk*MYC mice during disease progression. Further, the data support the establishment of intratumoural heterogeneity early in disease evolution. Conclusions: Our approach of using scRNA-seq to characterize the pathogenesis of disease evolution in MM has enabled simultaneous measurement of intratumoural heterogeneity and immune cell phenotypes in the TME. In turn, this has provided insights into mechanisms that may contribute to transition from AMG to MM, including induction of T cell exhaustion and loss of mouse Chr5. Ongoing and future work aims to evaluate whether these mechanisms can be exploited therapeutically in pre-malignant AMG. Disclosures Sebag: Amgen Canada: Membership on an entity's Board of Directors or advisory committees; Janssen Inc.: Membership on an entity's Board of Directors or advisory committees; Celgene Canada: Membership on an entity's Board of Directors or advisory committees; Takeda Canada: Membership on an entity's Board of Directors or advisory committees. Pugh:Prosigna: Honoraria; N/A: Patents & Royalties: Hybrid-capture sequencing for determining immune cell clonality; N/A: Patents & Royalties: Combined hybrid-capture DNA sequencing for disease detection; Boehringer Ingelheim: Research Funding; Chrysalis Biomedical Advisors: Honoraria; Merck: Honoraria; DynaCare: Consultancy.
Diagnostic Evaluation of t[4;14] in Multiple Myeloma.
Abstract The t[4;14] simultaneously deregulates fibroblast growth factor receptor 3 (FGFR3) and MMSET in 15% of patients (pts) with Multiple Myeloma (MM). Although oncogenic, FGFR3 expression is lost in ~25% of t[4;14] pts on gene expression profiling while MMSET is always retained. The t[4;14] is highly associated with poor prognosis, furthermore FGFR3 kinase inhibitors are in Phase I trials, thus detection of t[4;14] pts is increasingly important. The Multiple Myeloma Research Consortium (MMRC) therefore evaluated 4 competing methodologies for the diagnostic detection of t[4;14]. Bone marrow (BM) samples were collected in uniform fashion from 85 pts. FGFR3 immunocytochemistry (ICC) and flow cytometry (FC) were performed at the retrieval site, while split samples were shipped to the MMRC tissue bank and processed under GLP conditions. Processed samples were analyzed by cIg-FISH and quantitative IgH-MMSET RT-PCR (QPCR) on unsorted BM and blood. Of 60 samples with sufficient plasma cells for analysis, 8 were FISH +ve [13.3%]. Low % BM plasma cells prevented successful FISH in 25% of samples reflecting large volume harvests and hemodilution. Analysis was conducted in a blinded fashion. With FISH as the gold standard for detection of t[4;14] the sensitivity and specificity of the other diagnostic tests are: BM QPCR is most sensitive (7 of 8 FISH positive detected) and specific (42/43 negatives correctly identified). QPCR on peripheral blood is ongoing. FC is more sensitive to the detection of FGFR3 protein than ICC. Correlation between FC and ICC was only 0.46. Interestingly, 6 of 7 evaluable pts here and 13/14 (92%) in an expanded analysis of FISH +ve patients also expressed the FGFR3 protein. Given the discrepancy between this finding and previously reported loss of FGFR3 expression in 25% of pts we further explored t[4;14] stability. Clonal selection/heterogeneity was determined by the % plasma cells in each pt. with an unbalanced translocation (loss of one der chromosome). In 42 t[4;14] pts, 13 (31%) had a balanced translocation(>75% of cells with a double fusion), 14 (33%) had an unbalanced translocation (>75% cells with only one signal), and 15 (36%) had a chimeric picture. This heterogeneous pattern is suggestive of an evolution towards an unbalanced translocation. Despite this survival did not differ between pts with balanced or unbalanced translocation. Conclusions: These results indicate that the t[4;14] is highly heterogeneous with respect to balanced versus unbalanced translocations, which likely evolve over time. For detection, cIg-FISH continues to be the gold standard diagnostic methodology but may be limited by low plasma cell numbers in dilute BM or during MM remission. QPCR and FC appear most sensitive and specific for presence of t[4;14] and FGFR3 protein expression respectively. Surprisingly (given prior evidence of loss of FGFR3 expression in 25% of pts) 92% of t[4;14] pts in this series expressed FGFR3 protein. # Analyzed % Positive Sensitivity Specificity FISH 60 13 - - QPCR 65 14 87.5 97.6 Flow 82 15 85.7 91 ICC 85 15 62.5 92
Genome-wide Analysis of Common Copy Number Variation and Epithelial Ovarian Cancer Risk
AbstractBackground:Germline DNA copy number variation (CNV) is a ubiquitous source of genetic variation and remains largely unexplored in association with epithelial ovarian cancer (EOC) risk.Methods:CNV was quantified in the DNA of approximately 3,500 cases and controls genotyped with the Illumina 610k and HumanOmni2.5M arrays. We performed a genome-wide association study of common (>1%) CNV regions (CNVRs) with EOC and high-grade serous (HGSOC) risk and, using The Cancer Genome Atlas (TCGA), performed in silico analyses of tumor-gene expression.Results:Three CNVRs were associated (P < 0.01) with EOC risk: two large (∼100 kb) regions within the 610k set and one small (<5 kb) region with the higher resolution 2.5M data. Large CNVRs included a duplication at LILRA6 (OR = 2.57; P = 0.001) and a deletion at CYP2A7 (OR = 1.90; P = 0.007) that were strongly associated with HGSOC risk (OR = 3.02; P = 8.98 × 10−5). Somatic CYP2A7 alterations correlated with EGLN2 expression in tumors (P = 2.94 × 10−47). An intronic ERBB4/HER4 deletion was associated with reduced EOC risk (OR = 0.33; P = 9.5 × 10−2), and somatic deletions correlated with ERBB4 downregulation (P = 7.05 × 10−5). Five CNVRs were associated with HGSOC, including two reduced-risk deletions: one at 1p36.33 (OR = 0.28; P = 0.001) that correlated with lower CDKIIA expression in TCGA tumors (P = 2.7 × 10−7), and another at 8p21.2 (OR = 0.52; P = 0.002) that was present somatically where it correlated with lower GNRH1 expression (P = 5.9 × 10−5).Conclusions:Though CNV appears to not contribute largely to EOC susceptibility, a number of low-to-common frequency variants may influence the risk of EOC and tumor-gene expression.Impact:Further research on CNV and EOC susceptibility is warranted, particularly with CNVs estimated from high-density arrays.
Integration of Population-Level Genotype Data with Functional Annotation Reveals Over-Representation of Long Noncoding RNAs at Ovarian Cancer Susceptibility Loci