Citations

Abstract Background: Cholangiocarcinoma (CCA) is a lethal and heterogenous malignancy of the biliary tree characterized by perineural invasion. About 85% of CCA show activation of YAP signaling, which promotes proliferation, anti-apoptosis, and therapeutic resistance. YAP signaling is mediated by Src family kinases (SFK) by phosphorylation of YAP (pYAPy357). NXP900 is a first-in-class, highly selective, SFK inhibitor with a novel mechanism of action which locks SFK in its closed and inhibited conformation, in contrast to other Src inhibitors such as dasatinib. A phase 1a study of NXP900 in patients with advanced solid tumors was recently initiated. Here, we examined treatment responses of CCA to NXP900 in vitro and in vivo. Methods: Cell viability was determined in seven CCA cell lines by CellTiter-Glo. Cell death and apoptosis were assayed by PI/Hoechst and Caspase-Glo 3/7 assay. CalcuSyn software was used to determine synergistic drug effects. Immunoblot analysis, RT-PCR, and IF staining of YAP localization were used to evaluate YAP knockdown. Clones of human CCA cell lines resistant to NXP900 were generated through escalating exposure to NXP900 over 6 months. Five patient-derived xenograft (PDX) tumors were expanded into flanks of NOD/SCID mice. Tumor bearing mice were randomized 1:1 with 5 mice per arm and treated with vehicle or NXP900 (40 mg/kg) once daily for up to 4 weeks. To determine drivers of sensitivity and resistance, predicted sensitivity scores based on tumor growth were linked to multi-omics (RNA seq and [phospho-]proteomics) of our PDX models. Results: All cell lines were sensitive to NXP900 with IC50 values between 7nM-15µM; IC50’s of resistant clones were 1000 times higher. NXP900 induced more cell death compared to vehicle, which appeared to be through apoptosis. NXP900 inhibited pSrc, decreased pYAPy357, and upregulated inactive pYAPs127. Correspondingly, decreased YAP target gene (Cyr61, NUAK, and CTGF) levels and a nuclear-to-cytoplasmic translocation were observed. NXP900/GemCis combination therapy increased cell death demonstrated a synergistic effect (Combination Indices <1) at all concentrations. In our PDX models, treatment was associated with a significant decrease in tumor growth in 3 models (mean fold change 3.1 vs. 14.2; 1.0 vs. 7.6; 1.4 vs. 2.6). The major resistant signature was the TRK signaling network, involved in nerve growth factor binding activity, while drivers of sensitivity included the SRC network. Conclusion: NXP900 demonstrated therapeutic activity in vitro and in human PDX models. We are currently performing multi-omic approaches in NXP900 sensitive and resistant cell lines to unravel determinants of activity and resistance. Additional in vivo studies will be performed to determine effects of NXP900/GemCis and NXP900/anti-PDL-1 combination therapy. Citation Format: Hendrien Kuipers, Jennifer L. Tomlinson, Danielle M. Carlson, Amro M. Abdelrahman, Erik Jessen, Jack W. Sample, Nathan W. Werneburg, Hannah E. Stumpf, Mark J. Truty, Sumera I. Ilyas, Gregory J. Gores, Rory L. Smoot. Src family kinase inhibition demonstrates antitumor activity in vitro and in patient-derived xenograft models of human cholangiocarcinoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 614.

Abstract Introduction Cholangiocarcinoma (CCA) is a highly lethal, heterogenous biliary malignancy. Despite the development of targeted therapies, treatment success has been hindered by primary or acquired resistance. New therapeutic strategies are necessary to improve outcomes in these patients. NXP800 is a GCN2 small-molecule activator that phosphorylates eIF2a inducing selective ATF4 transcription which stimulates stress-induced genes leading to apoptosis. NXP800 has been previously validated in ovarian cancers with ARID1A mutations, well-known players in cholangiocarcinoma. We sought to determine the treatment efficacy of novel NXP800 in CCA utilizing patient derived xenograft (PDX) preclinical models. Methods In our preliminary studies, four human and two murine CCA cell lines were tested for cell viability using CellTiter-Glo to determine the maximal inhibitory concentration (IC50). Immunoblot analysis of HuCCT-1 cells incubated with 1 mM of NXP800 for 6 hours vs. vehicle was performed. We also evaluated response to GCN2 activation in multiple RNA sequenced PDX models. Xenografts were expanded into the flank of NOD/SCID mice and treatment begun when tumors averaged 120mm3. Tumor bearing mice were treated with NXP800 (35 mg/kg) or vehicle via oral gavage five days on, two days off, for 28 days. Tumor volume and animal weight were collected twice weekly. Predicted sensitive signatures were determined using multi-omics. Results IC50 dose response curves showed nanomolar activity in all six cell lines, ranging from 5-170 nM. Immunoblotting demonstrated an upregulation of phosphorylated eIF2a and in turn upregulation of ATF4 with treatment of NXP800 compared to vehicle. Five PDX tumors from patients with intrahepatic or distal CCA was established and validated by histologic analysis. Molecular characterization of the tumor identified tumor mutation and a total tumor mutational burden. RNA sequencing was completed and identified 21-gene signatures related to YAP activity, which were cross-referenced against our existing PDX model tumor bank. Treatment with NXP800 was associated with a statistically significant decrease in tumor size in three of five PDX models tested, which included an ARID1A, FGFR1, and ATM mutants. Preliminary multi-omics on the PDX models revealed that sensitivity mechanisms were centered around EGFR signaling. Conclusion The novel GCN2 kinase activator, NXP800, has nanomolar efficacy in both human and murine CCA cell lines in vitro. Additionally, NXP800 demonstrated therapeutic activity in multiple cholangiocarcinoma PDX models in vivo. We are opening a Phase 1b clinical trial investigating the effects of NXP800 use in patients with advanced CCA. Future studies determining the cellular effect of GCN2 activation utilizing NXP800 are being conducted. Citation Format: Danielle Marie Carlson, Hendrien Kuipers, Amro Abdelrahman, Erik Jessen, Joshua Roldan Kalil, Jack Sample, Jennifer Tomlinson, Mark Truty, Rory Smoot. A novel GCN2 kinase activator demonstrates therapeutic efficacy in preclinical PDX models of human cholangiocarcinoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 2098.

Abstract Background Cholangiocarcinoma (CCA) is a heterogeneous malignancy. Platinum-based chemotherapy (Gemcitabine and Cisplatin) has been the standard treatment for over a decade and is the base for the current immunotherapy combinations. Response rates are typically between 20-30%. Herein, we present outcomes of preclinical efficacy trials on CCA PDX models in correlation with baseline multiomics profiling of CCA patient-derived xenograft (PDX) models to identify molecular features associated with response. Methods Tumor samples from twenty-eight CCA PDX were used to isolate RNA and protein to be included in multiomics analysis (Phosphoproteomics, Proteomics, and Transcriptomics). A subset of PDX models were treated with various doses of Gemcitabine and Cisplatin. The Median Efficacy Index (MEI) was calculated as the ratio of the difference in median of delta in tumor volume at the last day of the study between the treatment and the control arms divided by the median of delta in tumor volume of the control at the last day of the treatment (positive= growth, negative=inhibition, and 0=no efficacy). A Hierarchical All-Against-All algorithm was utilized to compare multiomics features to the MEI and pathway analysis completed for identified molecular features. Results After conducting preclinical efficacy trials, the five tested CCA PDX models were classified into sensitive, moderately sensitive, and resistant models based on the MEI on each treatment arm. The top up-regulated genes were identified for Gemcitabine response (SRPK2, GLK2, and RIOK2) and Cisplatin response (NTRK1, PRPF4B, and SRPK2). The top up-regulated genes related to Gemcitabine resistance were NTRK1, PIP5K1C, and CSNK2A2, while those related to Cisplatin resistance were SRPK1, PRPF4B, and CSNK2A1. Conclusion Cholangiocarcinoma multiomics signatures can predict therapeutic response to standard-of-care chemotherapy in preclinical models. Novel mechanisms of Gemcitabine and Cisplatin resistance were identified related to NTRK1, SRPK1 and SRPK2. Resistant signatures will be challenged with the appropriate targeted therapies on the resistant CCA PDX models. Citation Format: Amro M. Abdelrahman, Danielle M. Carlson, Erik Jessen, Dong-Gi Mun, Isaac Lynch, Alessandro Fogliati, Stella Konadu Adjei Antwi, Aushinie Abeynayake, Akhilesh Pandey, Mark J. Truty, Gregory J. Gores, Rory L. Smoot. Pretreatment multiomics in conjunction with preclinical trials on patient-derived xenograft models of cholangiocarcinoma can identify chemotherapy response signatures [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6912.

Abstract The pathogenesis of primary sclerosing cholangitis (PSC) is unclear, although studies implicate IL-17A as an inflammatory mediator in this disease. However, a direct assessment of IL-17 signaling in PSC cholangiocytes is lacking. In this study we aimed to investigate the response of PSC extrahepatic cholangiocyte organoids (ECO) to IL-17A stimulation. Cholangiocytes obtained from PSC and non-PSC patients by endoscopic retrograde cholangiography (ERC) were cultured as ECO. The ECO were treated with vehicle or IL-17A and assessed by transcriptomics, secretome analysis, and genome sequencing (GS). Unsupervised clustering of all integrated scRNA-seq data identified 8 cholangiocyte clusters which did not differ between PSC and non-PSC ECO. However, PSC ECO cells demonstrated a robust response to IL-17 treatment, noted by an increased number of differentially expressed genes (DEG) by transcriptomics, and more abundant chemokine and cytokine expression and secretion. After rigorous filtering, GS identified candidate somatic variants shared among PSC ECO from unrelated individuals. However, no candidate rare variants in genes regulating the IL-17 pathway were identified, but rare variants regulating the MAPK signaling pathway were present in all PSC ECO. In conclusion, PSC and non-PSC patient derived ECO respond differently to IL-17 stimulation implicating this pathway in the pathogenesis of PSC.

Abstract Objective: Endometrial cancer (EC) is the most common gynecologic malignancy and serous histology is the second most common subtype. It is associated with poorer outcomes as recurrent disease tends to be resistant to chemotherapy. Given the dearth of proven targeted therapies in this setting and the tendency for serous ECs to have homologous recombination deficiency (HRD), this study aimed to test the synergy between poly (ADP-ribose) polymerase inhibitors (PARPis) and SN38, an active metabolite of DNA topoisomerase I, irinotecan. PARPis are currently FDA approved in ovarian cancer and have their greatest efficacy in tumors with HRD while topoisomerase inhibitors are a standard chemotherapy option for recurrent cancer. Methods: A genomic instability score (GIS) was derived from low-pass whole genome sequencing-based bioinformatics analysis according to three previously reported HRD metrics: telomeric allelic imbalance, large state transitions, and loss of heterozygosity. GIS was calculated for 34 patient derived xenograft (PDX) tumors, of which eight had serous histology. PARPi, rucaparib, and SN38 were used to treat EC PDX tumors in ex vivo 3D cell culture experiments using RealTime Glo for viability after 4-5 days of drug exposure. Synergy was assessed by calculating the combination index (CI) using Chou-Talalay method. Results: GIS ≥ 42 was noted in 62.5% (5/8) of serous EC PDX tumors and only 19.2% (5/26) of non-serous EC PDX tumors. Synergy (CI < 1.0) between rucaparib and SN38 was demonstrated in 85.7% (6/7) of serous EC PDX ex vivo 3D cell culture experiments, but only 62.5% (10/16) of non-serous EC PDX tumors. Conclusions: Most serous EC PDX tumors had a high GIS, consistent with HRD, when compared to a minority of non-serous histologies. Furthermore, combination therapy of rucaparib and SN38 had a synergistic effect in almost all serous EC PDX models, while still being effective in a majority of non-serous models. Additional PDX tumors need to be assessed to establish the predictive value of a GIS on synergy between rucaparib and SN38. Further in vivo studies are also needed to confirm these ex vivo findings of synergy. Ultimately, the hope is to generate preclinical data which justifies the use of PARPis in serous ECs as monotherapy or in combination with other anticancer therapies. Citation Format: Conway Xu, Xiaonan Hou, Erik Jessen, Chen Wang, S. John Weroha. Combination therapy with poly (ADP-ribose) polymerase inhibitor in endometrial cancer. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 5495.

Abstract Objectives Cirrhosis-like hepatocellular carcinoma (CL-HCC) is a rare hepatocellular malignancy characterized by multiple tumor nodules that clinically, radiologically, macroscopically, and microscopically mimic cirrhosis. We aimed to elucidate the molecular biology of CL-HCC and determine tumor nodule clonality. Methods We performed RNA sequencing on formalin-fixed, paraffin-embedded tissue from confirmed CL-HCC cases (n = 6), along with corresponding nonneoplastic hepatic tissue (n = 4) when available. Transcriptomes from our previous work on steatohepatitic hepatocellular carcinoma and The Cancer Genome Atlas (TCGA) were used for comparison purposes. Results Histologically, CL-HCC displayed innumerable nodules and extensive vascular invasion. Intratumoral nodule comparison indicated that the multiple nodules were all clonally related, not independent primaries. The unique histomorphologic appearance corresponded with a distinct transcriptome compared with other HCCs, including fibrolamellar HCC (n = 6), steatohepatitic HCC (n = 8), and conventional HCC in TCGA (n = 424). Tumor-normal gene expression analysis revealed consistent overexpression of several genes involved in degradation of tissue matrix. No recurrent translocations or point mutations were identified. CL-HCC showed a gene expression profile indicative of zone 2 hepatocytes. Conclusions CL-HCC’s distinctive clinicopathologic features correspond to a unique gene expression profile, increased expression of invasive markers, features of zone 2 hepatocytes, and features suggestive of intratumoral nodule monoclonality.

Abstract Background: Cholangiocarcinoma is an aggressive malignancy with limited systemic therapeutics. We have recently identified LCK, a non-receptor tyrosine kinase, as a potential therapeutic target in select subtypes of cholangiocarcinoma. Proteomic profiling in other cancer types has proven beneficial in predicting response to systemic therapies. Herein, we present proteomic profiling of cholangiocarcinoma can predict sensitivity to a novel LCK inhibitor in patient derived xenograft models. Methods: Proteins from 28 unique cholangiocarcinoma patient derived xenograft models (PDX) were isolated, labeled with tandem mass tags (TMT) and then analyzed by liquid chromatography and mass spectroscopy (LC/MS). Phosphopeptides were separately evaluated both by Immobilized Metal Affinity Chromatography and pY-enrichment techniques. Following normalization, the global proteome, serine/threonine phosphoproteome, and tyrosine phosphoproteome were analyzed and a proteomic signature was created for each tumor. These signatures were compared to PDX models with known response profiles to NTRC0652-0, an LCK inhibitor (1 resistant and 1 sensitive). The top 200 differentially abundant proteins (log2FC 2.6) were then utilized to develop a sensitive and a resistant signature. Correlation indices were then calculated across the 28 PDX model library. An additional predicted resistant and predicted sensitive model was expanded. Tumor bearing mice were randomized based on tumor volume to either treatment with NTRC (30mg/kg PO daily), n=5, or vehicle, n=4, (10% Kolliphor, 10% DMSO, 80% Water, 2 mol equivalents HCl). Tumors were measured weekly with calipers and then weighed at the end of the study. Results: In the top 200 differentially abundant proteins that represented the proteomic signature there was over representation of proteins with decreased abundance. There were only 12 proteins with higher abundance in the sensitive model as compared to the resistant. Utilizing the signature developed from the global proteomics data, nine tumors were predicted to be sensitive while 17 were predicted to be resistant to NTRC. PDX115 is a an intrahepatic CCA PDX known to contain an IDH1 mutation and was predicted to be resistant by modeling. The model was resistant to single agent NTRC with no demonstrable effect on tumor growth in vivo. PDX175 is a distal CCA PDX and was predicted to be sensitive by modeling. In vivo growth was inhibited by NTRC as compared to vehicle treated mice following two weeks of treatment (983% vs 435%, p=0.03). Additionally, final tumor weight was significantly lower in NTRC treated mice (0.651 g vs 0.317 g, p=0.04). Conclusion: Cholangiocarcinoma proteomic signatures can be used to predict therapeutic response to a novel LCK inhibitor in preclinical models. Whether or not this could be applied to other treatment modalities in cholangiocarcinoma remains to be determined. Citation Format: Ryan Watkins, Roberto Alva-Ruiz, Caitlin Conboy, Dong-Gi Mun, Erik Jessen, Diep Vu, Jos de Man, Rogier Buijsman, Akhilesh Pandey, Mitesh Borad, Gregory Gores, Rory Smoot. Proteomic profiling of cholangiocarcinoma predicts response to a novel small molecule inhibitor in preclinical models [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 3094.

Abstract Chronic lymphocytic leukemia (CLL) is characterized by multiple copy number abnormalities (CNVs) with prognostic value. Identifying these structural variations is central to defining CLL pathogenesis, risk stratification, and therapeutic approaches. Fluorescence in situ hybridization (FISH) is the clinical gold standard in detecting prognostic CNVs in CLL. However, next-generation sequencing (NGS) techniques have become more readily available for clinical genomic applications and can also be used to identify CNVs. Here we present bioinformatic methods to accurately identify CNVs in CLL using NGS data. We used the CNV-calling algorithm PatternCNV to detect clinically relevant CNVs: deletion 17p13 [del(17p)], deletion 11q23 [del(11q)], deletion 13q14 [del(13q)], and trisomy 12. PatternCNV was run on 2274 samples (1500 somatic and 774 germline samples) from six different sequencing batches, screened using a targeted sequencing panel that covers all exons of 59 recurrently CLL mutated genes and additional amplicons covering the minimal affected regions of relevant CNVs. To correct for potential batch effects, PatternCNV was initially run to quantify exon coverage behavior without the chromosomes containing recurrent CNV events, 11, 12, 13, and 17. Principal component analyses and correlation matrices were analyzed, grouping the samples into four distinct clusters that contain similar exon coverage patterns. Samples in each of the four clusters were then independently re-run through PatternCNV using all chromosomes. Visual analysis of CNV plots revealed a bias in normalization. To correct this, the log2ratios were corrected to center the log ratio on the median coverage. Sample noisiness was calculated from the difference in the median absolute deviation (DiffMAD) and samples with a DiffMAD score greater than 0.3 were excluded. All CNV analyses were blinded to clinical FISH results. The effectiveness of our CNV calling was evaluated in 522 CLL patients who had FISH conducted within three months of the sample date. We excluded samples with low tumor metrics identified by FISH (less than 20% of cells with either del(17p), del(11q), trisomy 12 or del(13q)). When we compared our CNV analyses with the FISH data, we found high concordance 99.6% for del(17p), 97.5% for del(11p), 99.1% for trisomy 12, and 93.7% for del(13q). N=46 total discordant pairs were identified, with the highest discordance for del(13q), N=28, followed by del(11q), N=12. These novel bioinformatic methods allow for accurate detection of CNVs across NGS sequencing batches. The high concordance in detecting CNVs between targeted NGS and the gold standard of FISH, suggest NGS is an accurate tool for calling CNVs in CLL. Further, NGS can infer clinically relevant CNVs in genomic locations not targeted by FISH. Citation Format: Chantal E. McCabe, Erik Jessen, Daniel R. O'Brien, Julia E. Wiedmeier-Nutor, Susan L. Slager, Esteban Braggio. Identifying copy number variations in chronic lymphocytic leukemia using targeted next generation sequencing [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 3352.

AbstractAltered energy metabolism and changes in glycolytic and oxidative phosphorylation pathways are hallmarks of all cancer cells. The expression of select genes associated with the production of various enzymes and proteins involved in glycolysis and oxidative phosphorylation were assessed in the clonal plasma cells derived from patients with newly diagnosed multiple myeloma (NDMM) enrolled in the Multiple Myeloma Research Foundation (MMRF) CoMMpass data set. A scoring system consisting of assigning a point for every gene where their fragments per kilobase of transcript per million (FPKM) was above the median yielded a minimum of 0 and a maximum of 12 for the set of genes in the glycolytic and oxidative phosphorylation pathways to create a total energy metabolism molecular signature (EMMS) score. This EMMS score was independently associated with worse progression free survival (PFS) and overall survival (OS) outcomes of patients with NDMM. A higher EMMS score was more likely to be present in clonal plasma cells derived from Multiple myeloma (MM) patients than those from patients with monoclonal gammopathy of undetermined significance (MGUS). This was functionally confirmed by the clonal plasma cells from MM patients having a higher rate of mitochondrial and glycolysis‐derived ATP formation than clonal plasma cells from MGUS patients. Thus, this study provides evidence for the effect of energy metabolism within clonal plasma cells on pathogenesis and outcomes of patients with MM. Exploiting the energy‐producing metabolic pathways within clonal plasma cells for diagnostic and therapeutic purposes in MM should be explored in the future.

Abstract Introduction: Multiple gene expression profile assays have successfully prognosticated the overall survival (OS) outcomes of patients with Newly Diagnosed Multiple Myeloma (NDMM) and are now available for use in clinical practice. The genes included in these profiles encompass several aspects of cancer biology broadly such as cell-cycle biology, energy metabolism, migration, adhesion, immune evasion etc. Since altered energy metabolism is one of the hallmarks of all cancer cells, our goal was to take a deep-dive into specific genes associated with intracellular central carbon energy metabolism (CCEM) pathways such as oxidative phosphorylation (OxPhos) as well as glycolysis and lactate fermentation (Glyco-Lac) in MM cells to determine their impact on the pathogenesis and prognosis of MM patients. Methods: Gene expression level data via RNA sequencing from the COMMPASS dataset (made available by the Multiple Myeloma Research Foundation (MMRF)) was utilized. The expression levels of all genes associated with the OxPhos (N = 118) and Glyco-Lac (N = 34) pathways were evaluated in CD138+ cells derived from patients with NDMM. Each gene was dichotomized into low and high expression groups -based on their expression level above and below the median fragments per kilobase of transcript per million (FPKM), respectively. The prognostic significance of dichotomizing each of the 152 genes in this NDMM cohort was evaluated by levels of their hazard ratios (HRs) for OS determined by the log-rank method. Genes from the OxPhos and Glyco-Lac pathways were selected based on their significant negative impact on OS, wide representation of their biologic activity throughout the pathway and high independence from each other. This resulted in the selection of 12 distinct genes of interest. A scoring system consisting of assigning a point for every gene where their FPKM was above the median yielded a minimum of 0 and a maximum of 12 for the set of genes in the OxPhos and Glyco-Lac pathways to create an energy metabolism score (EMS). Patients were then categorized into "low" (0-8) or "high" (9-12) EMS groups. In addition, patients were designated as having high-risk cytogenetics if they had any of the following: t(4;14), t(14;16), t(14;20), del17p, and Amp 1q. Survival analysis was performed using the Kaplan-Meier survival analysis and compared via the log-rank method. Finally, the distribution of the EMS score among patients within a spectrum of plasma cell disorders such as, monoclonal gammopathy of undetermined significance (MGUS), smoldering multiple myeloma and MM as well as normal plasma cells was assessed using a previously published transcriptome dataset (GSE6477). Results: A total of 766 patients were included in this study. The selected genes included in this scoring system and their biological relevance in the OxPhos and Glyco-Lac pathways are depicted in Figure A. The distribution of low and high EMS groups across ISS stage and cytogenetic risk are depicted in Figure B and C respectively. The median OS (mOS) and PFS for the high (N = 248) vs. low (N = 518) EMS groups was 55 vs. 94 months (HR: 2.41; (95%CI: 1.85-3.14); P <0.0001) (Figure D) and 24 vs. 42 months (HR: 1.74; (95%CI: 1.42-2.13); P <0.0001). Patients with ISS 2 stage disease categorized as having a high or low EMS score had a similar mOS to patients with ISS 3 and ISS 1 stage disease respectively (Figure E). Similarly, the mOS was similar among patients with standard risk and high-risk cytogenetics when categorized by low and high EMS (Figure F). Finally, the relative expression of most of the 12 select CCEM genes (Figure G) and the probability of a high EMS score increased among patients along the spectrum of plasma cell disorders (Normal plasma cell -> MGUS -> SMM -> MM) (Figure H). Conclusions: The expression levels of specific genes associated with the activity of intracellular CCEM pathways such as glycolysis, lactate fermentation and oxidative phosphorylation in plasma cells provides evidence for the impact of cellular energy metabolism on the pathogenesis and survival outcomes of MM. This provides an opportunity for developing future studies aimed at understanding the energy metabolism pathways of plasma cell malignancies in greater detail so as to exploit them for diagnostic and therapeutic purposes in MM. Figure 1 Figure 1. Disclosures Kumar: Novartis: Research Funding; Amgen: Consultancy, Research Funding; Beigene: Consultancy; Carsgen: Research Funding; Merck: Research Funding; Antengene: Consultancy, Honoraria; Janssen: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Astra-Zeneca: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Oncopeptides: Consultancy; Roche-Genentech: Consultancy, Research Funding; KITE: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Takeda: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Tenebio: Research Funding; Bluebird Bio: Consultancy; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; BMS: Consultancy, Research Funding; Abbvie: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Adaptive: Membership on an entity's Board of Directors or advisory committees, Research Funding; Sanofi: Research Funding. Dispenzieri: Alnylam: Research Funding; Sorrento Therapeutics: Consultancy; Oncopeptides: Consultancy; Pfizer: Research Funding; Takeda: Research Funding; Janssen: Consultancy, Research Funding. Kapoor: AbbVie: Research Funding; Takeda: Research Funding; Karyopharm: Consultancy; Cellectar: Consultancy; BeiGene: Consultancy; Pharmacyclics: Consultancy; Sanofi: Consultancy; Amgen: Research Funding; Ichnos Sciences: Research Funding; Regeneron Pharmaceuticals: Research Funding; Glaxo SmithKline: Research Funding; Karyopharm: Research Funding; Sanofi: Research Funding. Dingli: Apellis: Consultancy; Sanofi: Consultancy; Janssen: Consultancy; GSK: Consultancy; Novartis: Research Funding; Alexion: Consultancy. Lin: Gamida Cell: Consultancy; Takeda: Research Funding; Kite, a Gilead Company: Consultancy, Research Funding; Juno: Consultancy; Novartis: Consultancy; Legend: Consultancy; Janssen: Consultancy, Research Funding; Celgene: Consultancy, Research Funding; Bluebird Bio: Consultancy, Research Funding; Sorrento: Consultancy; Merck: Research Funding; Vineti: Consultancy. Gertz: Akcea Therapeutics, Ambry Genetics, Amgen Inc, Celgene Corporation, Janssen Biotech Inc, Karyopharm Therapeutics, Pfizer Inc (to Institution), Sanofi Genzyme: Honoraria; Aurora Biopharma: Other: Stock option; AbbVie Inc, Celgene Corporation: Other: Data Safetly & Monitoring; Ionis Pharmaceuticals: Other: Advisory Board; Akcea Therapeutics, Alnylam Pharmaceuticals Inc, Prothena: Consultancy. Fonseca: Aduro: Consultancy; Kite: Consultancy; Juno: Consultancy; Merck: Consultancy; Takeda: Consultancy; Caris Life Sciences: Membership on an entity's Board of Directors or advisory committees; Patent: Prognosticaton of myeloma via FISH: Patents & Royalties; AbbVie: Consultancy; Scientific Advisory Board: Adaptive Biotechnologies: Membership on an entity's Board of Directors or advisory committees; OncoTracker: Consultancy, Membership on an entity's Board of Directors or advisory committees; Mayo Clinic in Arizona: Current Employment; Amgen: Consultancy; BMS: Consultancy; Celgene: Consultancy; Bayer: Consultancy; Janssen: Consultancy; Novartis: Consultancy; Pharmacyclics: Consultancy; Sanofi: Consultancy; GSK: Consultancy.