Contributions of the Microbiome-Derived Metabolome for Risk Assessment and Prognostication of Pancreatic Cancer

BACKGROUND

Increasing evidence implicates microbiome involvement in the development and progression of pancreatic ductal adenocarcinoma (PDAC). Studies suggest that reflux of gut or oral microbiota can lead to colonization in the pancreas, resulting in dysbiosis that culminates in release of microbial toxins and metabolites that potentiate an inflammatory response and increase susceptibility to PDAC. Moreover, microbe-derived metabolites can exert direct effector functions on precursors and cancer cells, as well as other cell types, to either promote or attenuate tumor development and modulate treatment response.

CONTENT

The occurrence of microbial metabolites in biofluids thereby enables risk assessment and prognostication of PDAC, as well as having potential for design of interception strategies. In this review, we first highlight the relevance of the microbiome for progression of precancerous lesions in the pancreas and, using liquid chromatography-mass spectrometry, provide supporting evidence that microbe-derived metabolites manifest in pancreatic cystic fluid and are associated with malignant progression of intraductal papillary mucinous neoplasm(s). We secondly summarize the biomarker potential of microbe-derived metabolite signatures for (a) identifying individuals at high risk of developing or harboring PDAC and (b) predicting response to treatment and disease outcomes.

SUMMARY

The microbiome-derived metabolome holds considerable promise for risk assessment and prognostication of PDAC.

Modulating a prebiotic food source influences inflammation and immune-regulating gut microbes and metabolites: insights from the BE GONE trial

BACKGROUND

Accessible prebiotic foods hold strong potential to jointly target gut health and metabolic health in high-risk patients. The BE GONE trial targeted the gut microbiota of obese surveillance patients with a history of colorectal neoplasia through a straightforward bean intervention.

METHODS

This low-risk, non-invasive dietary intervention trial was conducted at MD Anderson Cancer Center (Houston, TX, USA). Following a 4-week equilibration, patients were randomized to continue their usual diet without beans (control) or to add a daily cup of study beans to their usual diet (intervention) with immediate crossover at 8-weeks. Stool and fasting blood were collected every 4 weeks to assess the primary outcome of intra and inter-individual changes in the gut microbiome and in circulating markers and metabolites within 8 weeks. This study was registered on ClinicalTrials.gov as NCT02843425, recruitment is complete and long-term follow-up continues.

FINDINGS

Of the 55 patients randomized by intervention sequence, 87% completed the 16-week trial, demonstrating an increase on-intervention in diversity [n = 48; linear mixed effect and 95% CI for inverse Simpson index: 0.16 (0.02, 0.30); p = 0.02] and shifts in multiple bacteria indicative of prebiotic efficacy, including increased Faecalibacterium, Eubacterium and Bifidobacterium (all p < 0.05). The circulating metabolome showed parallel shifts in nutrient and microbiome-derived metabolites, including increased pipecolic acid and decreased indole (all p < 0.002) that regressed upon returning to the usual diet. No significant changes were observed in circulating lipoproteins within 8 weeks; however, proteomic biomarkers of intestinal and systemic inflammatory response, fibroblast-growth factor-19 increased, and interleukin-10 receptor-α decreased (p = 0.01).

INTERPRETATION

These findings underscore the prebiotic and potential therapeutic role of beans to enhance the gut microbiome and to regulate host markers associated with metabolic obesity and colorectal cancer, while further emphasizing the need for consistent and sustainable dietary adjustments in high-risk patients.

FUNDING

This study was funded by the American Cancer Society.

Blood-based Proteomic Signatures Associated With MEN1-related Duodenopancreatic Neuroendocrine Tumor Progression

PURPOSE

Patients with multiple endocrine neoplasia type 1 (MEN1) are predisposed to develop duodenopancreatic neuroendocrine tumors (dpNETs), and metastatic dpNET is the primary cause of disease-related mortality. Presently, there is a paucity of prognostic factors that can reliably identify patients with MEN1-related dpNETS who are at high risk of distant metastasis. In the current study, we aimed to establish novel circulating molecular protein signatures associated with disease progression.

EXPERIMENTAL DESIGN

Mass spectrometry-based proteomic profiling was conducted on plasmas procured through an international collaboration between MD Anderson Cancer Center, the National Institutes of Health, and the University Medical Center Utrecht from a cohort of 56 patients with MEN1 [14 with distant metastasis dpNETs (cases) and 42 with either indolent dpNETs or no dpNETs (controls)]. Findings were compared to proteomic profiles generated from serially collected plasmas from a mouse model of Men1-pancreatic neuroendocrine tumors (Men1fl/flPdx1-CreTg) and control mice (Men1fl/fl).

RESULTS

A total of 187 proteins were found to be elevated in MEN1 patients with distant metastasis compared to controls, including 9 proteins previously associated with pancreatic cancer and other neuronal proteins. Analyses of mouse plasmas revealed 196 proteins enriched for transcriptional targets of oncogenic MYCN, YAP1, POU5F1, and SMAD that were associated with disease progression in Men1fl/flPdx1-CreTg mice. Cross-species intersection revealed 19 proteins positively associated with disease progression in both human patients and in Men1fl/flPdx1-CreTg mice.

CONCLUSIONS

Our integrated analyses identified novel circulating protein markers associated with disease progression in MEN1-related dpNET.

Exercise Training Reduces the Inflammatory Response and Promotes Intestinal Mucosa-Associated Immunity in Lynch Syndrome

PURPOSE

Lynch syndrome (LS) is a hereditary condition with a high lifetime risk of colorectal and endometrial cancers. Exercise is a non-pharmacologic intervention to reduce cancer risk, though its impact on patients with LS has not been prospectively studied. Here, we evaluated the impact of a 12-month aerobic exercise cycling intervention in the biology of the immune system in LS carriers.

PATIENTS AND METHODS

To address this, we enrolled 21 patients with LS onto a non-randomized, sequential intervention assignation, clinical trial to assess the effect of a 12-month exercise program that included cycling classes 3 times weekly for 45 minutes versus usual care with a one-time exercise counseling session as control. We analyzed the effects of exercise on cardiorespiratory fitness, circulating, and colorectal-tissue biomarkers using metabolomics, gene expression by bulk mRNA sequencing, and spatial transcriptomics by NanoString GeoMx.

RESULTS

We observed a significant increase in oxygen consumption (VO2peak) as a primary outcome of the exercise and a decrease in inflammatory markers (prostaglandin E) in colon and blood as the secondary outcomes in the exercise versus usual care group. Gene expression profiling and spatial transcriptomics on available colon biopsies revealed an increase in the colonic mucosa levels of natural killer and CD8+ T cells in the exercise group that were further confirmed by IHC studies.

CONCLUSIONS

Together these data have important implications for cancer interception in LS, and document for the first-time biological effects of exercise in the immune system of a target organ in patients at-risk for cancer.

Mortality Benefit of a Blood-Based Biomarker Panel for Lung Cancer on the Basis of the Prostate, Lung, Colorectal, and Ovarian Cohort

PURPOSE

To investigate the utility of integrating a panel of circulating protein biomarkers in combination with a risk model on the basis of subject characteristics to identify individuals at high risk of harboring a lethal lung cancer.

METHODS

Data from an established logistic regression model that combines four-marker protein panel (4MP) together with the Prostate, Lung, Colorectal, and Ovarian (PLCO) risk model (PLCOm2012) assayed in prediagnostic sera from 552 lung cancer cases and 2,193 noncases from the PLCO cohort were used in this study. Of the 552 lung cancer cases, 387 (70%) died of lung cancer. Cumulative incidence of lung cancer death and subdistributional and cause-specific hazard ratios (HRs) were calculated on the basis of 4MP + PLCOm2012 risk scores at a predefined 1.0% and 1.7% 6-year risk thresholds, which correspond to the current and former US Preventive Services Task Force screening criteria, respectively.

RESULTS

When considering cases diagnosed within 1 year of blood draw and all noncases, the area under receiver operation characteristics curve estimate of the 4MP + PLCOm2012 model for risk prediction of lung cancer death was 0.88 (95% CI, 0.86 to 0.90). The cumulative incidence of lung cancer death was statistically significantly higher in individuals with 4MP + PLCOm2012 scores above the 1.0% 6-year risk threshold (modified χ2, 166.27; P < .0001). Corresponding subdistributional and lung cancer death-specific HRs for test-positive cases were 9.88 (95% CI, 6.44 to 15.18) and 10.65 (95% CI, 6.93 to 16.37), respectively.

CONCLUSION

The blood-based biomarker panel in combination with PLCOm2012 identifies individuals at high risk of a lethal lung cancer.

A blood-based metabolomic signature predictive of risk for pancreatic cancer

Emerging evidence implicates microbiome involvement in the development of pancreatic cancer (PaCa). Here, we investigate whether increases in circulating microbial-related metabolites associate with PaCa risk by applying metabolomics profiling to 172 sera collected within 5 years prior to PaCa diagnosis and 863 matched non-subject sera from participants in the Prostate, Lung, Colorectal, and Ovarian (PLCO) cohort. We develop a three-marker microbial-related metabolite panel to assess 5-year risk of PaCa. The addition of five non-microbial metabolites further improves 5-year risk prediction of PaCa. The combined metabolite panel complements CA19-9, and individuals with a combined metabolite panel + CA19-9 score in the top 2.5th percentile have absolute 5-year risk estimates of >13%. The risk prediction model based on circulating microbial and non-microbial metabolites provides a potential tool to identify individuals at high risk of PaCa that would benefit from surveillance and/or from potential cancer interception strategies.

Integrated spatial transcriptomics and lipidomics of precursor lesions of pancreatic cancer identifies enrichment of long chain sulfatide biosynthesis as an early metabolic alteration

Background

The development of diverse spatial profiling technologies has provided an unprecedented insight into molecular mechanisms driving cancer pathogenesis. Here, we conducted the first integrated cross-species assessment of spatial transcriptomics and spatial metabolomics alterations associated with progression of intraductal papillary mucinous neoplasms (IPMN), bona fide cystic precursors of pancreatic ductal adenocarcinoma (PDAC).

Methods

Matrix Assisted Laster Desorption/Ionization (MALDI) mass spectrometry (MS)-based spatial imaging and Visium spatial transcriptomics (ST) (10X Genomics) was performed on human resected IPMN tissues (N= 23) as well as pancreata from a mutant Kras;Gnas mouse model of IPMN. Findings were further compared with lipidomic analyses of cystic fluid from 89 patients with histologically confirmed IPMNs, as well as single-cell and bulk transcriptomic data of PDAC and normal tissues.

Results

MALDI-MS analyses of IPMN tissues revealed long-chain hydroxylated sulfatides, particularly the C24:0(OH) and C24:1(OH) species, to be selectively enriched in the IPMN and PDAC neoplastic epithelium. Integrated ST analyses confirmed that the cognate transcripts engaged in sulfatide biosynthesis, including UGT8, Gal3St1 , and FA2H , were co-localized with areas of sulfatide enrichment. Lipidomic analyses of cystic fluid identified several sulfatide species, including the C24:0(OH) and C24:1(OH) species, to be significantly elevated in patients with IPMN/PDAC compared to those with low-grade IPMN. Targeting of sulfatide metabolism via the selective galactosylceramide synthase inhibitor, UGT8-IN-1, resulted in ceramide-induced lethal mitophagy and subsequent cancer cell death in vitro , and attenuated tumor growth of mutant Kras;Gnas allografts. Transcript levels of UGT8 and FA2H were also selectively enriched in PDAC transcriptomic datasets compared to non-cancerous areas, and elevated tumoral UGT8 was prognostic for poor overall survival.

Conclusion

Enhanced sulfatide metabolism is an early metabolic alteration in cystic pre-cancerous lesions of the pancreas that persists through invasive neoplasia. Targeting sulfatide biosynthesis might represent an actionable vulnerability for cancer interception.

Kynureninase Upregulation Is a Prominent Feature of NFR2-Activated Cancers and Is Associated with Tumor Immunosuppression and Poor Prognosis

The nuclear factor erythroid 2-related factor 2 (NRF2) pathway is frequently activated in various cancer types. Aberrant activation of NRF2 in cancer is attributed to gain-of-function mutations in the NRF2-encoding gene NFE2L2 or a loss of function of its suppressor, Kelch-like ECH-associated protein 1 (KEAP1). NRF2 activation exerts pro-tumoral effects in part by altering cancer cell metabolism. Previously, we reported a novel mechanism of NRF2 tumoral immune suppression through the selective upregulation of the tryptophan-metabolizing enzyme kynureninase (KYNU) in lung adenocarcinoma. In the current study, we explored the relevance of NRF2-mediated KYNU upregulation across multiple cancer types. Specifically, using a gene expression dataset for 9801 tumors representing 32 cancer types from The Cancer Genome Atlas (TCGA), we demonstrated that elevated KYNU parallels increased gene-based signatures of NRF2-activation and that elevated tumoral KYNU mRNA expression is strongly associated with an immunosuppressive tumor microenvironment, marked by high expression of gene-based signatures of Tregs as well as the immune checkpoint blockade-related genes CD274 (PDL-1), PDCD1 (PD-1), and CTLA4, regardless of the cancer type. Cox proportional hazard models further revealed that increased tumoral KYNU gene expression was prognostic for poor overall survival in several cancer types, including thymoma, acute myeloid leukemia, low-grade glioma, kidney renal papillary cell carcinoma, stomach adenocarcinoma, and pancreatic ductal adenocarcinoma (PDAC). Using PDAC as a model system, we confirmed that siRNA-mediated knockdown of NRF2 reduced KYNU mRNA expression, whereas activation of NFE2L2 (the coding gene for NRF2) through either small-molecule agonists or siRNA-mediated knockdown of KEAP1 upregulated KYNU in PDAC cells. Metabolomic analyses of the conditioned medium from PDAC cell lines revealed elevated levels of KYNU-derived anthranilate, confirming that KYNU was enzymatically functional. Collectively, our study highlights the activation of the NRF2-KYNU axis as a multi-cancer phenomenon and supports the relevance of tumoral KYNU as a marker of tumor immunosuppression and as a prognostic marker for poor overall survival.

c-MYC-Driven Polyamine Metabolism in Ovarian Cancer: From Pathogenesis to Early Detection and Therapy

c-MYC and its paralogues MYCN and MYCL are among the most frequently amplified and/or overexpressed oncoproteins in ovarian cancer. c-MYC plays a key role in promoting ovarian cancer initiation and progression. The polyamine pathway is a bona fide target of c-MYC signaling, and polyamine metabolism is strongly intertwined with ovarian malignancy. Targeting of the polyamine pathway via small molecule inhibitors has garnered considerable attention as a therapeutic strategy for ovarian cancer. Herein, we discuss the involvement of c-MYC signaling and that of its paralogues in promoting ovarian cancer tumorigenesis. We highlight the potential of targeting c-MYC-driven polyamine metabolism for the treatment of ovarian cancers and the utility of polyamine signatures in biofluids for early detection applications.

Abstract P077: A blood-based lipid biomarker panel for personalized risk assessment of breast cancer

Background: The metabolic syndrome characterized in part by obesity, hyperinsulinemia, and insulin resistance is associated with increased risk of breast cancer. However there remains a need to establish a circulating biomarker metabolic profile indicative of increased risk of breast cancer. In the current study, we performed a comprehensive metabolomics screen to identify biomarkers indicative of increased risk of breast cancer. Methods: Unbiased metabolomics profiling was conducted on an initial Development Set of plasmas collected from 353 newly diagnosed breast cancer cases and 141 controls. A deep learning neural network with 3 layers each containing 32 nodes based on 11 individual lipids corresponding to discrete lipid subclasses was built for risk prediction of breast cancer. The model was validated in an independent Test Set consisting of 79 breast cancer cases and 163 controls. Using a nested case: control matched design, we evaluated the performance of the model among body mass index (BMI) strata (≥ 30 or &lt;30kg/m2). Results: An 11-marker lipid biomarker panel encompassing lipid subclasses with known pro-inflammatory and tumor promoting roles yielded an AUC of 0.75 (95% CI: 0.70-0.79) for distinguishing breast cancer cases from controls in the Development Set. Predictive performance of the lipid panel was comparable when stratifying cases into hormone-receptor (HR) positive, HER2-positive/HR negative, and triple-negative breast cancer subtypes. The biomarker panel had an AUC of 0.74 (95% CI: 0.68-0.81) in the independent Test Set. The predictive performance of the panel was most pronounced among obese subjects (BMI ≥ 30) with an AUC of 0.81 (95% CI: 0.71-0.91) in the Test Set. Conclusions: The lipid-based biomarker panel has utility for identifying women with ‘metabolic obesity’ who are at increased risk of breast cancer and would benefit from tailored screening.

Citation Format: Johannes F. Fahrmann, Ehsan Irajizad, Jody Vykoukal, Angelica Gutierrez Barrera, Jennifer B. Dennison, Ranran Wu, Banu Arun, Abenaa Brewster, Samir Hanash. A blood-based lipid biomarker panel for personalized risk assessment of breast cancer. [abstract]. In: Proceedings of the AACR Special Conference: Precision Prevention, Early Detection, and Interception of Cancer; 2022 Nov 17-19; Austin, TX. Philadelphia (PA): AACR; Can Prev Res 2023;16(1 Suppl): Abstract nr P077.

Abstract P076: Contribution of the microbiome to a metabolomic signature predictive of risk for pancreatic cancer

Purpose: Emerging evidence implicates the microbiome in the development of pancreatic cancer. We investigated whether increased levels of microbial-related metabolites in circulation are associated with pancreatic cancer risk. Methods: We applied metabolomics profiling to sera from the Prostate, Lung, Colorectal and Ovarian (PLCO) Cohort to quantify and build a model based on 14 microbial-related metabolites. The study involved samples collected from 172 subjects within five years prior to diagnosis and 863 matched controls. Data from five PLCO centers were used for training and from two centers for validation and model selection. The model was subsequently tested using samples from three independent centers. The contributions of non-microbial-associated metabolites as well as CA19-9 was also assessed. Results: A 3-marker microbial-related metabolite panel yielded in the PLCO testing set an AUC of 0.64 (95% CI: 0.53-0.76) for 5-year probability of pancreatic cancer. Five additional non-microbial metabolites were identified that when combined with the microbiome panel yielded an AUC of 0.79 (95% CI: 0.71-0.88) for 5-year probability of pancreatic cancer in the PLCO testing set. The combined metabolite panel and CA19-9 yielded an AUC of 0.86 (95% CI: 0.77-0.95) for 2-year probability of pancreatic cancer in the PLCO testing set, which was improved compared to CA19-9 alone (AUC: 0.70 (95% CI: 0.57-0.82), p&lt; 0.001). Conclusion: We developed a metabolite panel derived in part from the microbiome for risk assessment of pancreatic cancer, which has relevance to prevention and early detection.

Citation Format: Johannes F. Fahrmann, Ehsan Irajizad, Ana Kenney, Tiffany Tang, Jody Vykoukal, Ranran Wu, Jennifer B. Dennison, Marta Sans Escofet, James P. Long, Maureen Loftus, John A. Chabot, Michael D. Kluger, Fay Kastrinos, Lauren Brais, Ana Babic, Kunal Jajoo, Linda S. Lee, Thomas E. Clancy, Kimmie Ng, Andrea Bullock, Jeanine M. Genkinger, Anirban Maitra, Kim-Anh Do, Bin Yu, Brian M. Wolpin, Samir Hanash. Contribution of the microbiome to a metabolomic signature predictive of risk for pancreatic cancer. [abstract]. In: Proceedings of the AACR Special Conference: Precision Prevention, Early Detection, and Interception of Cancer; 2022 Nov 17-19; Austin, TX. Philadelphia (PA): AACR; Can Prev Res 2023;16(1 Suppl): Abstract nr P076.

Abstract P013: Impact of blood-based biomarkers for predicting lung cancer mortality in the PLCO cohort

Purpose: To investigate the utility of integrating a panel of circulating protein biomarkers in combination with a risk model based on subject characteristics for identifying individuals at high risk of harboring a lethal lung cancer. Methods: Data for a 4-marker protein panel (4MP) (consisting of the precursor form of surfactant protein B, cancer antigen 125, carcinoembryonic antigen, and cytokeratin-19 fragment) previously assayed in pre-diagnostic sera from 552 lung cancer cases and 2,193 non-cases from the Prostate Lung Colorectal and Ovarian (PLCO) cohort as well as a scores from a logistic regression model that combined the 4MP with the PLCOm2012 risk model were used for this study. Of the 552 lung cancer cases, 387 (70%) died from lung cancer. Cumulative incidence of lung cancer death as well as sub-distributional and cause-specific hazard ratios were calculated based on 4MP+PLCOm2012 risk scores at a pre-defined 1.0%/6-year risk threshold, which corresponds to current US Preventive Services Task Force screening criteria. For hazard modeling, stage at the time of clinical diagnosis and treatment modality were considered as co-variables. Results: When considering cases diagnosed within 1 year of blood draw and all non-cases, the performance estimate of the 4MP+PLCOm2012 model for risk prediction of lung cancer death was 0.88 (95% CI: 0.86-0.90). Among cases only, at the 1.0%/6-year risk threshold the cumulative incidence of lung cancer death was statistically significantly higher in ‘test positive’ cases compared to ‘test negative’ cases (Chi-square test: 5.42, P: 0.02). The adjusted sub distributional hazard ratio for ‘test positive’ cases was 1.67 (95% CI: 1.02-2.74). The adjusted lung-cancer death-specific hazard ratio for ‘test positive’ cases was 2.02 (95% CI: 1.28-3.17). Conclusions and Relevance: The blood-based biomarker panel in combination with PLCOm2012 identifies individuals at high risk of a lethal lung cancer.

Citation Format: Ehsan Irajizad, Johannes F. Fahrmann, Jody V. Vykoukal, Jennifer B. Dennison, James P. Long, Kim-Anh Do, Edwin J. Ostrin, Sam Hanash. Impact of blood-based biomarkers for predicting lung cancer mortality in the PLCO cohort. [abstract]. In: Proceedings of the AACR Special Conference: Precision Prevention, Early Detection, and Interception of Cancer; 2022 Nov 17-19; Austin, TX. Philadelphia (PA): AACR; Can Prev Res 2023;16(1 Suppl): Abstract nr P013.

A polyamine-centric, blood-based metabolite panel predictive of poor response to CAR-T cell therapy in large B cell lymphoma

Anti-CD19 chimeric antigen receptor (CAR) T cell therapy for relapsed or refractory (r/r) large B cell lymphoma (LBCL) results in durable response in only a subset of patients. MYC overexpression in LBCL tumors is associated with poor response to treatment. We tested whether an MYC-driven polyamine signature, as a liquid biopsy, is predictive of response to anti-CD19 CAR-T therapy in patients with r/r LBCL. Elevated plasma acetylated polyamines were associated with non-durable response. Concordantly, increased expression of spermidine synthase, a key enzyme that regulates levels of acetylated spermidine, was prognostic for survival in r/r LBCL. A broad metabolite screen identified additional markers that resulted in a 6-marker panel (6MetP) consisting of acetylspermidine, diacetylspermidine, and lysophospholipids, which was validated in an independent set from another institution as predictive of non-durable response to CAR-T therapy. A polyamine centric metabolomics liquid biopsy panel has predictive value for response to CAR-T therapy in r/r LBCL.

A Blood-Based Metabolite Panel for Distinguishing Ovarian Cancer from Benign Pelvic Masses

PURPOSE

To assess the contributions of circulating metabolites for improving upon the performance of the risk of ovarian malignancy algorithm (ROMA) for risk prediction of ovarian cancer among women with ovarian cysts.

EXPERIMENTAL DESIGN

Metabolomic profiling was performed on an initial set of sera from 101 serous and nonserous ovarian cancer cases and 134 individuals with benign pelvic masses (BPM). Using a deep learning model, a panel consisting of seven cancer-related metabolites [diacetylspermine, diacetylspermidine, N-(3-acetamidopropyl)pyrrolidin-2-one, N-acetylneuraminate, N-acetyl-mannosamine, N-acetyl-lactosamine, and hydroxyisobutyric acid] was developed for distinguishing early-stage ovarian cancer from BPM. The performance of the metabolite panel was evaluated in an independent set of sera from 118 ovarian cancer cases and 56 subjects with BPM. The contributions of the panel for improving upon the performance of ROMA were further assessed.

RESULTS

A 7-marker metabolite panel (7MetP) developed in the training set yielded an AUC of 0.86 [95% confidence interval (CI): 0.76-0.95] for early-stage ovarian cancer in the independent test set. The 7MetP+ROMA model had an AUC of 0.93 (95% CI: 0.84-0.98) for early-stage ovarian cancer in the test set, which was improved compared with ROMA alone [0.91 (95% CI: 0.84-0.98); likelihood ratio test P: 0.03]. In the entire specimen set, the combined 7MetP+ROMA model yielded a higher positive predictive value (0.68 vs. 0.52; one-sided P < 0.001) with improved specificity (0.89 vs. 0.78; one-sided P < 0.001) for early-stage ovarian cancer compared with ROMA alone.

CONCLUSIONS

A blood-based metabolite panel was developed that demonstrates independent predictive ability and complements ROMA for distinguishing early-stage ovarian cancer from benign disease to better inform clinical decision making.

Novel UHRF1-MYC Axis in Acute Lymphoblastic Leukemia

Ubiquitin-like, containing PHD and RING finger domain, (UHRF) family members are overexpressed putative oncogenes in several cancer types. We evaluated the protein abundance of UHRF family members in acute leukemia. A marked overexpression of UHRF1 protein was observed in ALL compared with AML. An analysis of human leukemia transcriptomic datasets revealed concordant overexpression of UHRF1 in B-Cell and T-Cell ALL compared with CLL, AML, and CML. In-vitro studies demonstrated reduced cell viability with siRNA-mediated knockdown of UHRF1 in both B-ALL and T-ALL, associated with reduced c-Myc protein expression. Mechanistic studies indicated that UHRF1 directly interacts with c-Myc, enabling ALL expansion via the CDK4/6-phosphoRb axis. Our findings highlight a previously unknown role of UHRF1 in regulating c-Myc protein expression and implicate UHRF1 as a potential therapeutic target in ALL.

A Comprehensive Search of Non-Canonical Proteins in Non-Small Cell Lung Cancer and Their Impact on the Immune Response

There is substantial interest in mining neoantigens for cancer applications. Non-canonical proteins resulting from frameshift mutations have been identified as neoantigens in cancer. We investigated the landscape of non-canonical proteins in non-small cell lung cancer (NSCLC) and their induced immune response in the form of autoantibodies. A database of cryptoproteins was computationally constructed and comprised all alternate open reading frames (altORFs) and ORFs identified in pseudogenes, noncoding RNAs, and untranslated regions of mRNAs that did not align with known canonical proteins. Proteomic profiles of seventeen lung adenocarcinoma (LUAD) cell lines were searched to evaluate the occurrence of cryptoproteins. To assess the immunogenicity, immunoglobulin (Ig)-bound cryptoproteins in plasmas were profiled by mass spectrometry. The specimen set consisted of plasmas from 30 newly diagnosed NSCLC cases, pre-diagnostic plasmas from 51 NSCLC cases, and 102 control plasmas. An analysis of LUAD cell lines identified 420 cryptoproteins. Plasma Ig-bound analyses revealed 90 cryptoproteins uniquely found in cases and 14 cryptoproteins that had a fold-change >2 compared to controls. In pre-diagnostic samples, 17 Ig-bound cryptoproteins yielded an odds ratio ≥2. Eight Ig-bound cryptoproteins were elevated in both pre-diagnostic and newly diagnosed cases compared to controls. Cryptoproteins represent a class of neoantigens that induce an autoantibody response in NSCLC.

Application of Artificial Intelligence to Plasma Metabolomics Profiles to Predict Response to Neoadjuvant Chemotherapy in Triple-Negative Breast Cancer

There is a need to identify biomarkers predictive of response to neoadjuvant chemotherapy (NACT) in triple-negative breast cancer (TNBC). We previously obtained evidence that a polyamine signature in the blood is associated with TNBC development and progression. In this study, we evaluated whether plasma polyamines and other metabolites may identify TNBC patients who are less likely to respond to NACT. Pre-treatment plasma levels of acetylated polyamines were elevated in TNBC patients that had moderate to extensive tumor burden (RCB-II/III) following NACT compared to those that achieved a complete pathological response (pCR/RCB-0) or had minimal residual disease (RCB-I). We further applied artificial intelligence to comprehensive metabolic profiles to identify additional metabolites associated with treatment response. Using a deep learning model (DLM), a metabolite panel consisting of two polyamines as well as nine additional metabolites was developed for improved prediction of RCB-II/III. The DLM has potential clinical value for identifying TNBC patients who are unlikely to respond to NACT and who may benefit from other treatment modalities.

Mutational Activation of the NRF2 Pathway Upregulates Kynureninase Resulting in Tumor Immunosuppression and Poor Outcome in Lung Adenocarcinoma

Activation of the NRF2 pathway through gain-of-function mutations or loss-of-function of its suppressor KEAP1 is a frequent finding in lung cancer. NRF2 activation has been reported to alter the tumor microenvironment. Here, we demonstrated that NRF2 alters tryptophan metabolism through the kynurenine pathway that is associated with a tumor-promoting, immune suppressed microenvironment. Specifically, proteomic profiles of 47 lung adenocarcinoma (LUAD) cell lines (11 KEAP1 mutant and 36 KEAP1 wild-type) revealed the tryptophan-kynurenine enzyme kynureninase (KYNU) as a top overexpressed protein associated with activated NRF2. The siRNA-mediated knockdown of NFE2L2, the gene encoding for NRF2, or activation of the NRF2 pathway through siRNA-mediated knockdown of KEAP1 or via chemical induction with the NRF2-activator CDDO-Me confirmed that NRF2 is a regulator of KYNU expression in LUAD. Metabolomic analyses confirmed KYNU to be enzymatically functional. Analysis of multiple independent gene expression datasets of LUAD, as well as a LUAD tumor microarray demonstrated that elevated KYNU was associated with immunosuppression, including potent induction of T-regulatory cells, increased levels of PD1 and PD-L1, and resulted in poorer survival. Our findings indicate a novel mechanism of NRF2 tumoral immunosuppression through upregulation of KYNU.

Blood-Based Biomarker Panel for Personalized Lung Cancer Risk Assessment

PURPOSE

To investigate whether a panel of circulating protein biomarkers would improve risk assessment for lung cancer screening in combination with a risk model on the basis of participant characteristics.

METHODS

A blinded validation study was performed using prostate lung colorectal ovarian (PLCO) Cancer Screening Trial data and biospecimens to evaluate the performance of a four-marker protein panel (4MP) consisting of the precursor form of surfactant protein B, cancer antigen 125, carcinoembryonic antigen, and cytokeratin-19 fragment in combination with a lung cancer risk prediction model (PLCO_m2012) compared with current US Preventive Services Task Force (USPSTF) screening criteria. The 4MP was assayed in 1,299 sera collected preceding lung cancer diagnosis and 8,709 noncase sera.

RESULTS

The 4MP alone yielded an area under the receiver operating characteristic curve of 0.79 (95% CI, 0.77 to 0.82) for case sera collected within 1-year preceding diagnosis and 0.74 (95% CI, 0.72 to 0.76) among the entire specimen set. The combined 4MP + PLCO_m2012 model yielded an area under the receiver operating characteristic curve of 0.85 (95% CI, 0.82 to 0.88) for case sera collected within 1 year preceding diagnosis. The benefit of the 4MP in the combined model resulted from improvement in sensitivity at high specificity. Compared with the USPSTF2021 criteria, the combined 4MP + PLCO_m2012 model exhibited statistically significant improvements in sensitivity and specificity. Among PLCO participants with ≥ 10 smoking pack-years, the 4MP + PLCO_m2012 model would have identified for annual screening 9.2% more lung cancer cases and would have reduced referral by 13.7% among noncases compared with USPSTF2021 criteria.

CONCLUSION

A blood-based biomarker panel in combination with PLCO_m2012 significantly improves lung cancer risk assessment for lung cancer screening.

CES2 sustains HNF4α expression to promote pancreatic adenocarcinoma progression through an epoxide hydrolase-dependent regulatory loop

Objective

Intra-tumoral expression of the serine hydrolase carboxylesterase 2 (CES2) contributes to the activation of the pro-drug irinotecan in pancreatic ductal adenocarcinoma (PDAC). Given other potential roles of CES2, we assessed its regulation, downstream effects, and contribution to tumor development in PDAC.

Methods

Association between the mRNA expression of CES2 in pancreatic tumors and overall survival was assessed using The Cancer Genome Atlas. Cell viability, clonogenic, and anchorage-independent growth assays as well as an orthotopic mouse model of PDAC were used to evaluate the biological relevance of CES2 in pancreatic cancer. CES2-driven metabolic changes were determined by untargeted and targeted metabolomic analyses.

Results

Elevated tumoral CES2 mRNA expression was a statistically significant predictor of poor overall survival in PDAC patients. Knockdown of CES2 in PDAC cells reduced cell viability, clonogenic capacity, and anchorage-independent growth in vitro and attenuated tumor growth in an orthotopic mouse model of PDAC. Mechanistically, CES2 was found to promote the catabolism of phospholipids resulting in HNF4α activation through a soluble epoxide hydrolase (sEH)-dependent pathway. Targeting of CES2 via siRNA or small molecule inhibitors attenuated HNF4α protein expression and reduced gene expression of classical/progenitor markers and increased basal-like markers. Targeting of the CES2-sEH-HNF4α axis using small molecule inhibitors of CES2 or sEH reduced cell viability.

Conclusions

We establish a novel regulatory loop between CES2 and HNF4α to sustain the progenitor subtype and promote PDAC progression and highlight the potential utility of CES2 or sEH inhibitors for the treatment of PDAC as part of non-irinotecan-containing regimens.

A Blood-based Polyamine Signature Associated With MEN1 Duodenopancreatic Neuroendocrine Tumor Progression

CONTEXT

Duodenopancreatic neuroendocrine tumors (dpNETs) frequently occur in patients with multiple endocrine neoplasia type 1 (MEN1), and metastatic dpNET is the primary cause of disease-related mortality. There is a need for biomarkers that can identify patients with MEN1-related dpNETs that are at high risk of developing distant metastasis. Polyamines have tumor-promoting roles in several cancer types.

OBJECTIVE

We hypothesized that MEN1-dpNET-related disease progression is associated with elevated levels of circulating polyamines.

METHODS

Through an international collaboration between The University of Texas MD Anderson Cancer Center, the National Institutes of Health, and the University Medical Center Utrecht, plasma polyamine levels were assessed using mass spectrometry in 84 patients with MEN1 (20 with distant metastatic dpNETs [patients] and 64 with either indolent dpNETs or no dpNETs [controls]). A mouse model of MEN1-pNET, Men1fl/flPdx1-CreTg, was used to test time-dependent changes in plasma polyamines associated with disease progression.

RESULTS

A 3-marker plasma polyamine signature (3MP: N-acetylputrescine, acetylspermidine, and diacetylspermidine) distinguished patients with metastatic dpNETs from controls in an initial set of plasmas from the 3 participating centers. The fixed 3MP yielded an area under the curve of 0.84 (95% CI, 0.62-1.00) with 66.7% sensitivity at 95% specificity for distinguishing patients from controls in an independent test set from MDACC. In Men1fl/flPdx1-CreTg mice, the 3MP was elevated early and remained high during disease progression.

CONCLUSION

Our findings provide a basis for prospective testing of blood-based polyamines as a potential means for monitoring patients with MEN1 for harboring or developing aggressive disease.

SRGN-Triggered Aggressive and Immunosuppressive Phenotype in a Subset of TTF-1-Negative Lung Adenocarcinomas

BACKGROUND

About 20% of lung adenocarcinoma (LUAD) is negative for the lineage-specific oncogene Thyroid transcription factor 1 (TTF-1) and exhibits worse clinical outcome with a low frequency of actionable genomic alterations. To identify molecular features associated with TTF-1-negative LUAD, we compared the transcriptomic and proteomic profiles of LUAD cell lines. SRGN, a chondroitin sulfate proteoglycan Serglycin, was identified as a markedly overexpressed gene in TTF-1-negative LUAD. We therefore investigated the roles and regulation of SRGN in TTF-1-negative LUAD.

METHODS

Proteomic and metabolomic analyses of 41 LUAD cell lines were done using mass spectrometry. The function of SRGN was investigated in 3 TTF-1-negative and 4 TTF-1-positive LUAD cell lines and in a syngeneic mouse model (n = 5 to 8 mice per group). Expression of SRGN in was evaluated in 94 and 105 surgically resected LUAD tumor specimens using immunohistochemistry. All statistical tests were two-sided.

RESULTS

SRGN was markedly overexpressed at mRNA and protein levels in TTF-1-negative LUAD cell lines (P < .001 for both mRNA and protein levels). Expression of SRGN in LUAD tumor tissue was associated with poor outcome (hazard ratio = 4.22, 95% confidential interval = 1.12 to 15.86; likelihood ratio test, P = .03), and with higher expression of Programmed cell death 1 ligand 1 (PD-L1) in tumor cells and higher infiltration of Programmed cell death protein 1 (PD-1)-positive lymphocytes. SRGN regulated expression of PD-L1, as well as proinflammatory cytokines including Interleukin-6 (IL-6), Interleukin-8 (IL-8), and C-X-C motif chemokine 1 (CXCL1) in LUAD cell lines, and increased migratory and invasive properties of LUAD cells and fibroblasts, and enhanced angiogenesis. SRGN was induced by DNA de-methylation resulting from Nicotinamide N-methyltransferase (NNMT)-mediated impairment of methionine metabolism.

CONCLUSION

Our findings suggest that SRGN plays a pivotal role in tumor-stromal interaction and reprogramming into an aggressive and immunosuppressive tumor microenvironment in TTF-1-negative LUAD.

Plasma Based Protein Signatures Associated with Small Cell Lung Cancer

Small-cell-lung cancer (SCLC) is associated with overexpression of oncogenes including Myc family genes and YAP1 and inactivation of tumor suppressor genes. We performed in-depth proteomic profiling of plasmas collected from 15 individuals with newly diagnosed early stage SCLC and from 15 individuals before the diagnosis of SCLC and compared findings with plasma proteomic profiles of 30 matched controls to determine the occurrence of signatures that reflect disease pathogenesis. A total of 272 proteins were elevated (area under the receiver operating characteristic curve (AUC) ≥ 0.60) among newly diagnosed cases compared to matched controls of which 31 proteins were also elevated (AUC ≥ 0.60) in case plasmas collected within one year prior to diagnosis. Ingenuity Pathway analyses of SCLC-associated proteins revealed enrichment of signatures of oncogenic MYC and YAP1. Intersection of proteins elevated in case plasmas with proteomic profiles of conditioned medium from 17 SCLC cell lines yielded 52 overlapping proteins characterized by YAP1-associated signatures of cytoskeletal re-arrangement and epithelial-to-mesenchymal transition. Among samples collected more than one year prior to diagnosis there was a predominance of inflammatory markers. Our integrated analyses identified novel circulating protein features in early stage SCLC associated with oncogenic drivers.

A Deep Learning Approach to Re-create Raw Full-Field Digital Mammograms for Breast Density and Texture Analysis

Purpose

To develop a computational approach to re-create rarely stored for-processing (raw) digital mammograms from routinely stored for-presentation (processed) mammograms.

Materials and Methods

In this retrospective study, pairs of raw and processed mammograms collected in 884 women (mean age, 57 years ± 10 [standard deviation]; 3713 mammograms) from October 5, 2017, to August 1, 2018, were examined. Mammograms were split 3088 for training and 625 for testing. A deep learning approach based on a U-Net convolutional network and kernel regression was developed to estimate the raw images. The estimated raw images were compared with the originals by four image error and similarity metrics, breast density calculations, and 29 widely used texture features.

Results

In the testing dataset, the estimated raw images had small normalized mean absolute error (0.022 ± 0.015), scaled mean absolute error (0.134 ± 0.078) and mean absolute percentage error (0.115 ± 0.059), and a high structural similarity index (0.986 ± 0.007) for the breast portion compared with the original raw images. The estimated and original raw images had a strong correlation in breast density percentage (Pearson r = 0.946) and a strong agreement in breast density grade (Cohen κ = 0.875). The estimated images had satisfactory correlations with the originals in 23 texture features (Pearson r ≥ 0.503 or Spearman ρ ≥ 0.705) and were well complemented by processed images for the other six features.

Conclusion

This deep learning approach performed well in re-creating raw mammograms with strong agreement in four image evaluation metrics, breast density, and the majority of 29 widely used texture features.Keywords: Mammography, Breast, Supervised Learning, Convolutional Neural Network (CNN), Deep learning algorithms, Machine Learning AlgorithmsSee also the commentary by Chan in this issue.Supplemental material is available for this article.©RSNA, 2021.

Lead-Time Trajectory of CA19-9 as an Anchor Marker for Pancreatic Cancer Early Detection

BACKGROUND & AIMS

There is substantial interest in liquid biopsy approaches for cancer early detection among subjects at risk, using multi-marker panels. CA19-9 is an established circulating biomarker for pancreatic cancer; however, its relevance for pancreatic cancer early detection or for monitoring subjects at risk has not been established.

METHODS

CA19-9 levels were assessed in blinded sera from 175 subjects collected up to 5 years before diagnosis of pancreatic cancer and from 875 matched controls from the Prostate, Lung, Colorectal and Ovarian (PLCO) Cancer Screening Trial. For comparison of performance, CA19-9 was assayed in blinded independent sets of samples collected at diagnosis from 129 subjects with resectable pancreatic cancer and 275 controls (100 healthy subjects; 50 with chronic pancreatitis; and 125 with noncancerous pancreatic cysts). The complementary value of 2 additional protein markers, TIMP1 and LRG1, was determined.

RESULTS

In the PLCO cohort, levels of CA19-9 increased exponentially starting at 2 years before diagnosis with sensitivities reaching 60% at 99% specificity within 0 to 6 months before diagnosis for all cases and 50% at 99% specificity for cases diagnosed with early-stage disease. Performance was comparable for distinguishing newly diagnosed cases with resectable pancreatic cancer from healthy controls (64% sensitivity at 99% specificity). Comparison of resectable pancreatic cancer cases to subjects with chronic pancreatitis yielded 46% sensitivity at 99% specificity and for subjects with noncancerous cysts, 30% sensitivity at 99% specificity. For prediagnostic cases below cutoff value for CA19-9, the combination with LRG1 and TIMP1 yielded an increment of 13.2% in sensitivity at 99% specificity (P = .031) in identifying cases diagnosed within 1 year of blood collection.

CONCLUSION

CA19-9 can serve as an anchor marker for pancreatic cancer early detection applications.

A MYC-Driven Plasma Polyamine Signature for Early Detection of Ovarian Cancer

MYC is an oncogenic driver in the pathogenesis of ovarian cancer. We previously demonstrated that MYC regulates polyamine metabolism in triple-negative breast cancer (TNBC) and that a plasma polyamine signature is associated with TNBC development and progression. We hypothesized that a similar plasma polyamine signature may associate with ovarian cancer (OvCa) development. Using mass spectrometry, four polyamines were quantified in plasma from 116 OvCa cases and 143 controls (71 healthy controls + 72 subjects with benign pelvic masses) (Test Set). Findings were validated in an independent plasma set from 61 early-stage OvCa cases and 71 healthy controls (Validation Set). Complementarity of polyamines with CA125 was also evaluated. Receiver operating characteristic area under the curve (AUC) of individual polyamines for distinguishing cases from healthy controls ranged from 0.74-0.88. A polyamine signature consisting of diacetylspermine + N-(3-acetamidopropyl)pyrrolidin-2-one in combination with CA125 developed in the Test Set yielded improvement in sensitivity at >99% specificity relative to CA125 alone (73.7% vs 62.2%; McNemar exact test 2-sided P: 0.019) in the validation set and captured 30.4% of cases that were missed with CA125 alone. Our findings reveal a MYC-driven plasma polyamine signature associated with OvCa that complemented CA125 in detecting early-stage ovarian cancer.

Association Between Plasma Diacetylspermine and Tumor Spermine Synthase With Outcome in Triple-Negative Breast Cancer

BACKGROUND

MYC is an oncogenic driver of development and progression in triple-negative breast cancer (TNBC). Ornithine decarboxylase, the rate-limiting enzyme in polyamine metabolism, is a transcriptional target of MYC. We therefore hypothesized that a plasma polyamine signature may be predictive of TNBC development and progression.

METHODS

Using liquid chromatography mass spectrometry, polyamine levels were determined in plasma samples from newly diagnosed patients with TNBC (n = 87) and cancer-free controls (n = 115). Findings were validated in plasma samples from an independent prospective cohort of 54 TNBC, 55 estrogen receptor negative (ER-) and progesterone receptor negative (PR-) and HER2 positive (HER2+), and 73 ER+ case patients, and 30 cancer-free control subjects. Gene expression data and clinical data for 921 and 2359 breast cancer tumors were obtained from The Cancer Genome Atlas repository and the Oncomine database, respectively. Relationships between plasma diacetylspermine (DAS) and tumor spermine synthase (SMS) mRNA expression with metastasis-free survival and overall survival were determined using Cox proportional hazard models; Fisher exact tests were used to assess risk of distant metastasis in relation to tumor SMS mRNA expression.

RESULTS

An increase in plasma DAS, a catabolic product of spermine mediated through SMS, was observed in the TNBC subtype of breast cancer. Plasma levels of DAS in TNBC associated with increased risk of metastasis (plasma DAS value ≥ 1.16, hazard ratio = 3.06, 95% confidence interval [CI] = 1.15 to 8.13, two-sided P = .03). SMS mRNA expression in TNBC tumor tissue was also found to be predictive of poor overall survival (top 25th percentile hazard ratio = 2.06, 95% CI = 1.04 to 4.08, one-sided P = .04) and increased risk of distant metastasis in TNBC (comparison of lowest SMS quartile [reference] to highest SMS quartile relative risk = 1.90, 95% CI = 0.97 to 4.06, one-sided Fisher exact test P=.03).

CONCLUSIONS

Metabolomic profiling identified plasma DAS as a predictive marker for TNBC progression and metastasis.

CES2 Expression in Pancreatic Adenocarcinoma Is Predictive of Response to Irinotecan and Is Associated With Type 2 Diabetes

PURPOSE

The combination chemotherapy of fluorouracil, leucovorin, irinotecan, and oxaliplatin (FOLFIRINOX) has provided clinically meaningful improvement for pancreatic ductal adenocarcinoma (PDAC). We previously uncovered a role for the serine hydrolase carboxylesterase 2 (CES2) in mediating intratumoral activation of the prodrug irinotecan, a constituent of FOLFIRINOX. We aimed to further test the predictive value of CES2 for response to irinotecan using patient-derived xenograft (PDX) models and to elucidate the determinants of CES2 expression and response to FOLFIRINOX treatment among patients with PDAC.

METHODS

PDXs were engrafted subcutaneously into nude mice and treated for 4 weeks with either saline control or irinotecan. CES2 and hepatocyte nuclear factor 4 alpha (HNF4A) expression in PDAC tissues was evaluated by immunohistochemical and Western blot analysis. Kaplan-Meier and Cox regression analyses were applied to assess the association between overall survival and hemoglobin A1C (HbA1C) levels in patients who underwent neoadjuvant FOLFIRINOX treatment.

RESULTS

High CES2 activity in PDAC PDXs was associated with increased sensitivity to irinotecan. Integrated gene expression, proteomic analyses, and in vitro genetic experiments revealed that nuclear receptor HNF4A, which is upregulated in diabetes, is the upstream transcriptional regulator of CES2 expression. Elevated CES2 protein expression in PDAC tissues was positively associated with a history of type 2 diabetes (odds ratio, 4.84; P = .02). High HbA1C levels were associated with longer overall survival in patients who received neoadjuvant FOLFIRINOX treatment (P = .04).

CONCLUSION

To our knowledge, we provide, for the first time, evidence that CES2 expression is associated with a history of type 2 diabetes in PDAC and that elevated HbA1C, by predicting tumor CES2 expression, may represent a novel marker for stratifying patients most likely to respond to FOLFIRINOX therapy.

Validation of 4-marker protein panel for the early detection of lung cancer using PLCO samples

9024

Background: We have previously demonstrated that a protein panel consisting of ProSFTPB, CEA, CA125 and CYFRA21.1 may improve lung cancer risk assessment and has potential to define eligibility for computed tomography screening. Herein, we aimed to validate the classifier performance of the 4-marker protein panel using pre-diagnostic serum samples from the PLCO cohort. We additionally explored the additive value of diacetylspermine (DAS) with the 4-marker protein panel for identifying lung cancer cases. Methods: ProSFTPB, CEA, CA125 and CYFRA21.1 levels were measured in baseline sera of 537 lung cancer cases (76 SCLC/461 NSCLC) diagnosed within 6 years of baseline blood draw and 3772 cancer-free controls using bead-based immunoassays. DAS was measured using ultrahigh performance liquid chromatography mass spectrometry. Samples were analyzed in a double-blinded randomized fashion. Results: Overall classification performance (receiver operating characteristic area under the curve (ROAUC)) of the 4-marker panel for delineating lung cases diagnosed within 1 year and 1 to 2 years of baseline blood draw from cancer-free controls was 0.78 (95% CI: 0.74-0.82) and 0.73 (95% CI: 0.68-0.78), respectively. Classification performances of the 4-marker panel amongst lung cancer cases diagnosed within 1 year of baseline blood draw stratified into adenocarcinoma, squamous cell carcinoma and small cell lung cancer subtypes yielded ROAUCS of 0.78 (95% CI: 0.72-0.85), 0.76 (95% CI: 0.69-0.83) and 0.79 (95% CI: 0.68-0.90), respectively. Sub-analyses adjusting for smoking status yielded comparable ROAUC point estimates. Comparison of the 4-marker performance amongst non-NLST and NLST eligible lung cancer patients diagnosed within 1 year of baseline blood draw in comparison to matched cancer-free controls resulted in ROAUCs of 0.71 (95% CI: 0.63-0.79) and 0.74 (95% CI: 0.69-0.80), respectively. Analyses evaluating the additive classifier performance of serum DAS with that of the 4-marker protein panel revealed statistically significant improvement (McNemar Exact Test 2-sided p < 0.05) in sensitivity at high specificity derived from youden index for SCLC and squamous cell carcinoma cases diagnosed within 2 years from baseline blood draw, respectively, in comparison to the 4-marker protein panel alone. Conclusions: We have validated the performance of the 4-marker panel for early detection of lung cancer in the PLCO pre-diagnostic cohort. We further demonstrate that DAS can complement the 4-marker protein panel and identify more SCLC and squamous cell carcinoma cases.

Repair or Observation of Resin Margin Defects: Clinical Trial After Five Years

OBJECTIVE

To assess the effectiveness of repair/resealing of stained composite margins as an alternative to controlled observation without treatment in a randomized clinical trial after five years.

METHODS AND MATERIALS

Each patient recruited had from one to three composite restorations with visible margin discoloration. Initially, the characteristics of each defect were recorded with direct vision through a surgical microscope at 20× magnification. Clinical evaluation was done by two independent examiners using modified USPHS criteria for color, margin discoloration, and margin adaptation. Each restoration was then randomly assigned to a control or treatment group. Control restorations were observed yearly for the presence of recurrent caries; treatment restorations were resealed by exposing the margin with a ¼ round bur, removing all interfacial stain, acid etching, placing an adhesive bonding agent, and a flowable composite to restore margin integrity. There were 152 patients recruited, with 360 restorations (180 control and 180 treatment).

RESULTS

At five years, 104 patients were recalled (68%) with 271 restorations (76%): 136 untreated control and 135 resealed restorations. At that time, 61 restorations had been lost or replaced for nonrelated reasons. Clinical evaluation of the remaining 210 restorations determined penetrating discoloration (control = 81%, resealed = 46%) and margin crevice formation (control = 21%, resealed = 11%). Recurrent caries was diagnosed cumulatively in only six control and five treatment restorations (<5%). Microscopically, 49 control restorations (49%) and 36 resealed restorations (33%) had crevice formation. Discoloration was distributed as follows: 9% vs 47% with no discoloration, 30% vs 33% in the composite, 49% vs 18% in the interface, and 12% vs 2% in tooth structure.

CONCLUSIONS

Resealing of restorations with margin discoloration reduced the occurrence of penetrating stain from 81% in controls to 46% in resealed margins and crevicing from 21% to 11% after five years. Both controlled observation and resealing of margins resulted in a similar very low incidence (<6%) of recurrent caries.

A Plasma-Derived Protein-Metabolite Multiplexed Panel for Early-Stage Pancreatic Cancer

BACKGROUND

We applied a training and testing approach to develop and validate a plasma metabolite panel for the detection of early-stage pancreatic ductal adenocarcinoma (PDAC) alone and in combination with a previously validated protein panel for early-stage PDAC.

METHODS

A comprehensive metabolomics platform was initially applied to plasmas collected from 20 PDAC cases and 80 controls. Candidate markers were filtered based on a second independent cohort that included nine invasive intraductal papillary mucinous neoplasm cases and 51 benign pancreatic cysts. Blinded validation of the resulting metabolite panel was performed in an independent test cohort consisting of 39 resectable PDAC cases and 82 matched healthy controls. The additive value of combining the metabolite panel with a previously validated protein panel was evaluated.

RESULTS

Five metabolites (acetylspermidine, diacetylspermine, an indole-derivative, and two lysophosphatidylcholines) were selected as a panel based on filtering criteria. A combination rule was developed for distinguishing between PDAC and healthy controls using the Training Set. In the blinded validation study with early-stage PDAC samples and controls, the five metabolites yielded areas under the curve (AUCs) ranging from 0.726 to 0.842, and the combined metabolite model yielded an AUC of 0.892 (95% confidence interval [CI] = 0.828 to 0.956). Performance was further statistically significantly improved by combining the metabolite panel with a previously validated protein marker panel consisting of CA 19-9, LRG1, and TIMP1 (AUC = 0.924, 95% CI = 0.864 to 0.983, comparison DeLong test one-sided P= .02).

CONCLUSIONS

A metabolite panel in combination with CA19-9, TIMP1, and LRG1 exhibited substantially improved performance in the detection of early-stage PDAC compared with a protein panel alone.

Gingival Health of Porcelain Laminate Veneered Teeth: A Retrospective Assessment

STATEMENT OF PROBLEM

The long-term effect of the presence of porcelain laminate veneers (PLVs) on the health of the surrounding gingival issues is not available in the restorative literature.

PURPOSE

To assess the long-term effect of PLVs on the health of the surrounding gingival tissues. A secondary aim was to correlate gingival crevicular fluid (GCF) scores with clinical parameters used for gingival health assessment in teeth treated with PLVs.

METHODS AND MATERIALS

Patients who received PLVs placed at the Graduate Restorative Clinic within a seven- to 14-year period were recalled for clinical evaluations. Periodontal measurements including gingival index (GI), periodontal pocket depth (PPD), gingival recession (GR), and clinical attachment level (CAL) were measured using a standard probe and indices. Gingival Crevicular Fluid (GCF) was measured with a Periotron machine (Periotron 8000, Oraflow Inc), using Periopaper (Periopaper Gingival Fluid Collection Strip, Oraflow Inc.) for fluid collection. Photographs of any observed clinical defect were taken. Data were tabulated using Excel 2010 (Microsoft Corp). Statistical analysis for all descriptive statistics was performed using SPSS 21 (SPSS Software, IBM Corp.) and Stata SE 13 (Stata Software, StataCorp). Repeated-measures analysis of variance (ANOVA) was done to test for statistical significance of the mean pocket depths between the restored and unrestored surfaces of the veneered teeth. The significance level for all tests was p<0.05. Pearson's correlation coefficient was performed for testing statistical significance between GCF and GI and between GCF and PPD.

RESULTS

The frequency distribution of the GI included 47 PLVs (43%) with normal gingiva, 16 (15%) with mild inflammation, and 46 (42%) with moderate inflammation and bleeding on probing. The average PPD on the facial surface of the maxillary and mandibular PLVs was 2.17 mm and 2.16 mm, respectively. On the lingual surface, the average PPD was 2.10 mm for maxillary and 2.22 mm for mandibular PLVs. Gingival recession was seen in 27% of the evaluated PLVs. The repeated-measures ANOVA revealed p≥0.136, showing no statistical difference in the mean pocket depths between restored facial and unrestored lingual surfaces of the veneered teeth. A moderate correlation (r=0.407) was found between GCF and GI, which was significant at p<0.001. No correlation (r=0.124) was found between GCF and PPD, which was not significant at p=0.197.

CONCLUSIONS

Gingival response to the evaluated PLVs was in the satisfactory range, with overall GI scores ranging between normal and moderate inflammation, pocket depths ranging from 1 to 2 mm, and recession present in 27% of the evaluated PLVs. No statistically significant difference was found between the mean pocket depths of the restored and unrestored surfaces of veneered teeth (p≥0.136). A moderate correlation was found between GCF and GI.

Targeting metabolic vulnerabilities of cancer: Small molecule inhibitors in clinic

BACKGROUND

Altered cell metabolism is an established hallmark of cancer. Advancement in our understanding of dysregulated cellular metabolism has aided drastically in identifying metabolic vulnerabilities that can be exploited therapeutically. Indeed, this knowledge has led to the development of a multitude of agents targeting various aspects of tumor metabolism.

RECENT FINDINGS

The intent of this review is to provide insight into small molecule inhibitors that target tumor metabolism and that are currently being explored in active clinical trials as either preventive, stand-alone, or adjuvant therapies for various malignancies. For each inhibitor, we outline the mechanism (s) of action, preclinical/clinical findings, and limitations. Sections are divided into three aspects based on the primary target of the small molecule inhibitor (s): those that impact (1) cancer cells directly, (2) immune cells present in the tumor microenvironment, or (3) both cancer cells and immune cells. We highlight small molecule targeting of metabolic pathways including de novo fatty acid synthesis, NAD+ biosynthesis, 2-hydroxyglutarate biosynthesis, polyamine metabolism, the kynurenine pathway, as well as glutamine and arginine metabolism.

CONCLUSIONS

Use of small molecule inhibitors aimed at exploiting tumor metabolic vulnerabilities continues to be an active area of research. Identifying metabolic dependencies specific to cancer cells and/or constituents of the tumor microenvironment is a viable area of therapeutic intervention that holds considerable clinical potential.

Abstract 1447: Aberrant tryptophan catabolism marked by high kynureninase expression contributes to immunosuppression and poor outcome in lung adenocarcinoma

Low tryptophan levels promote tumor immune evasion by suppressing immune function. Elucidation of the immunomodulatory effects of altered tryptophan catabolism has relevance to cancer immunotherapy. Previous studies have largely focused on the role of the rate-limiting enzyme indoleamine 2,3-dioxygenase 1 (IDO1) and tryptophan depletion in the microenvironment. However, IDO1 levels are highly heterogeneous in different cancers, and numerous other downstream tryptophan catabolites have also been shown to have immunomodulatory activity. We surveyed the proteomes of 123 cancer cell lines for regulators of tryptophan metabolism which revealed overexpression of kynureninase (KYNU) in KEAP1 mutant lung adenocarcinomas. Functional analysis indicated that KYNU expression is regulated through nuclear factor, erythroid 2-like (Nrf2) activation. KYNU-high cell lines exhibited increased secretion of KYNU-derived anthranilate/3-hydroxyanthranilate. Ex-vivo studies using isolated PBMCs demonstrated that 3-hydroxyanthranilate reduced CD8+ T-cell viability. KYNU mRNA expression in three independent datasets of lung adenocarcinomas and additionally KYNU protein expression in lung adenocarcinoma tissue microarrays revealed that high KYNU expression predicts poor survival and disease recurrence. Our findings indicate that KYNU promotes immune suppression and is an independent prognostic marker for lung adenocarcinoma.

Citation Format: Edwin J. Ostrin, Johannes F. Fahrmann, Ichidai Tanaka, Muge Celiktas, Clemente Aguilar, Mitzi Aguilar, Jennifer B. Dennison, Eunice Murage, Satyendra C. Tripathi, Oliver Delgado, Hong Wang, Jaime Rodriguez-Canales, Carmen Behrens, Ignacio I. Wistuba, Ayumu Taguchi, Samir M. Hanash. Aberrant tryptophan catabolism marked by high kynureninase expression contributes to immunosuppression and poor outcome in lung adenocarcinoma [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 1447.

Chlorinated adenosine analogue induces AMPK and autophagy in chronic lymphocytic leukaemia cells during therapy

8-chloro-adenosine (8-Cl-Ado) is currently in phase-I clinical trials for acute myeloid leukaemia and chronic lymphocytic leukaemia (CLL). Previously, we demonstrated that treatment with 8-Cl-Ado leads to diminished ATP levels. We hypothesized that AMP-activated protein kinase (AMPK) signalling would be initiated in these cells, leading to induction of autophagy. AMPK activation and induction of autophagy were demonstrated during preclinical incubations in CLL cells with the analogues. Importantly, we extended similar observations in CLL lymphocytes during an 8-Cl-Ado phase-I trial. In conclusion, 8-Cl-Ado treatment induces autophagy in CLL lymphocytes in vitro as well as in vivo during clinical trial.

Role of CPS1 in Cell Growth, Metabolism and Prognosis in LKB1-Inactivated Lung Adenocarcinoma

Background

Liver kinase B1 ( LKB1 ) is a tumor suppressor in lung adenocarcinoma (LADC). We investigated the proteomic profiles of 45 LADC cell lines with and without LKB1 inactivation. Carbamoyl phosphate synthetase 1 (CPS1), the first rate-limiting mitochondrial enzyme in the urea cycle, was distinctively overexpressed in LKB1-inactivated LADC cell lines. We therefore assessed the role of CPS1 and its clinical relevance in LKB1-inactivated LADC.

Methods

Mass spectrometric profiling of proteome and metabolome and function of CPS1 were analyzed in LADC cell lines. CPS1 and LKB1 expression in tumors from 305 LADC and 160 lung squamous cell carcinoma patients was evaluated by immunohistochemistry. Kaplan-Meier and Cox regression analyses were applied to assess the association between overall survival and CPS1 and LKB1 expression. All statistical tests were two-sided.

Results

CPS1 knockdown reduced cell growth, decreased metabolite levels associated with nucleic acid biosynthesis pathway, and contributed an additive effect when combined with gemcitabine, pemetrexed, or CHK1 inhibitor AZD7762. Tissue microarray analysis revealed that CPS1 was expressed in 65.7% of LKB1-negative LADC, and only 5.0% of LKB1-positive LADC. CPS1 expression showed statistically significant association with poor overall survival in LADC (hazard ratio = 3.03, 95% confidence interval = 1.74 to 5.25, P < .001).

Conclusions

Our findings suggest functional relevance of CPS1 in LKB1-inactivated LADC and association with worse outcome of LADC. CPS1 is a promising therapeutic target in combination with other chemotherapy agents, as well as a prognostic biomarker, enabling a personalized approach to treatment of LADC.

Abstract 2775: CPS1 as a therapeutic target and prognostic indicator in LKB1-inactivated lung adenocarcinoma

Liver Kinase B1 (LKB1), encoded by STK11, is a tumor suppressor and somatically mutated in approximately 20% of lung adenocarcinoma. Aside from the effects of LKB1 inactivation on tumor initiation, LKB1-mutant cancers are biologically distinct from cancer with functional LKB1, and the loss of LKB1 uniquely confers invasive and metastatic properties in genetically engineered mouse models of cancer. While various pathways, including energy metabolism, cell polarity, and cell growth, are regulated by LKB1 and can play a pleiotropic role in cancer initiation and progression, no therapies are currently available for clinical use that specifically target LKB1 inactivation. Therefore, elucidation of the functional mechanisms associated with LKB1 inactivation has translational relevance.

We analyzed proteomic profiles of 45 lung adenocarcinoma cell lines with and without LKB1 inactivation to identify molecular features associated with LKB1 inactivation. Carbamoyl phosphate synthase 1 (CPS1) was identified as a markedly overexpressed protein in LKB1-inactivated lung adenocarcinoma cell lines. CPS1 is the first rate-limiting mitochondrial enzyme in the urea cycle, and plays an intricate role in arginine and pyrimidine metabolism. CPS1 knockdown reduced cell growth, decreased levels of metabolites associated with nucleic acid biosynthesis pathway, and contributed an additive effect when combined with conventional chemotherapy agents including gemcitabine, pemetrexed, or CHK1 inhibitor AZD7762. Tissue microarray analysis using 305 lung adenocarcinoma tumors revealed that CPS1 was expressed in 65.7% of LKB1-negative and only 5.0% of LKB1-positive lung adenocarcinomas. In addition, CPS1 expression was significantly and independently associated with poor overall survival of lung adenocarcinoma patients (P &lt; 0.0001, HR = 3.03, 95% CI 1.74-5.25). Concordant with the results of tissue microarray, analysis of the Cancer Genome Atlas (TCGA) dataset consisting 403 lung adenocarcinomas revealed that high CPS1 mRNA expression was significantly associated with worse overall survival and is an independent prognostic indicator of lung adenocarcinoma (P = 0.005, HR = 2.31, 95% CI 1.28-4.16). Our findings suggest functional relevance of CPS1 and its association with worse outcome in LKB1-inactivated lung adenocarcinoma. Therefore, CPS1 is a promising therapeutic target in combination with other chemotherapy agents, as well as a prognostic biomarker, enabling us to personalize the treatment of LKB1-inactivated lung adenocarcinoma.

Citation Format: Muge Celiktas, Ichidai Tanaka, Satyendra Chandra Tripathi, Johannes F. Fahrmann, Clemente Aguilar-Bonavides, Pamela Villalobos, Oliver Delgado, Dilsher Dhillon, Jennifer B. Dennison, Edwin J. Ostrin, Hong Wang, Carmen Behrens, Kim-Anh Do, Adi F. Gazdar, Samir M. Hanash, Ayumu Taguchi. CPS1 as a therapeutic target and prognostic indicator in LKB1-inactivated lung adenocarcinoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 2775. doi:10.1158/1538-7445.AM2017-2775

Abstract 3170: MCAM modulates small cell lung cancer chemoresistance via PI3k/Akt/Sox2 signaling pathway

Despite favorable responses to initial therapy SCLC relapse occurs within a year exhibiting a multidrug resistant phenotype. Due to limited accessibility of patient tissues for research purpose, SCLC patient derived xenografts (PDXs) have provided the best opportunity to address this limitation. We sought to identify novel mechanisms involved in SCLC chemoresistance. Through in-depth proteomic profiling, we identified MCAM as a markedly upregulated surface receptor in chemoresistant SCLC cell lines that exhibited a mesenchymal phenotype and in chemoresistant PDXs compared to matched treatment-naïve tumors. MCAM is a cell membrane protein whose expression has been implicated in multiple human cancers. MCAM expression is also detected in lung adenocarcinoma; however, its expression and role in SCLC is still not been explored. MCAM knockdown in chemoresistant cells reduced cell proliferation and decreased the IC50 inhibitory concentration of chemotherapeutic drugs. MCAM was found to modulate sensitivity of SCLC cells to chemotherapeutic drugs through up-regulation of MRP1/ABCC1 expression and of the PI3K/AKT pathway in a SOX2 dependent manner. Metabolomic profiling revealed that MCAM can modulate glutamic acid and lactate production in chemoresistant cells with a distinct metabolic phenotype sustaining low oxidative phosphorylation. MCAM may serve as a novel therapeutic target to overcome chemoresistance in SCLC.

Citation Format: Satyendra C. Tripathi, Johannes F. Fahrmann, Muge Celiktas, Mitzi Aguilar, Kieren D. Marini, Mohit K. Jolly, Hiroyuki Katayama, Hong Wang, Eunice N. Murage, Jennifer B. Dennison, D. Neil Watkins, Herbert Levine, Edwin J. Ostrin, Ayumu Taguchi, Samir M. Hanash. MCAM modulates small cell lung cancer chemoresistance via PI3k/Akt/Sox2 signaling pathway [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 3170. doi:10.1158/1538-7445.AM2017-3170

MCAM Mediates Chemoresistance in Small-Cell Lung Cancer via the PI3K/AKT/SOX2 Signaling Pathway

Despite favorable responses to initial therapy, small-cell lung cancer (SCLC) relapse occurs within a year and exhibits resistance to multiple drugs. Because of limited accessibility of patient tissues for research purposes, SCLC patient-derived xenografts (PDX) have provided the best opportunity to address this limitation. Here, we sought to identify novel mechanisms involved in SCLC chemoresistance. Through in-depth proteomic profiling, we identified MCAM as a markedly upregulated surface receptor in chemoresistant SCLC cell lines and in chemoresistant PDX compared with matched treatment-naïve tumors. MCAM depletion in chemoresistant cells reduced cell proliferation and reduced the IC₅₀ inhibitory concentration of chemotherapeutic drugs in vitro This MCAM-mediated sensitization to chemotherapy occurred via SOX2-dependent upregulation of mitochondrial 37S ribosomal protein 1/ATP-binding cassette subfamily C member 1 (MRP1/ABCC1) and the PI3/AKT pathway. Metabolomic profiling revealed that MCAM modulated lactate production in chemoresistant cells that exhibit a distinct metabolic phenotype characterized by low oxidative phosphorylation. Our results suggest that MCAM may serve as a novel therapeutic target to overcome chemoresistance in SCLC. Cancer Res; 77(16); 4414-25. ©2017 AACR.

A murine preclinical syngeneic transplantation model for breast cancer precision medicine

We previously demonstrated that altered activity of lysophosphatidic acid in murine mammary glands promotes tumorigenesis. We have now established and characterized a heterogeneous collection of mouse-derived syngeneic transplants (MDSTs) as preclinical platforms for the assessment of personalized pharmacological therapies. Detailed molecular and phenotypic analyses revealed that MDSTs are the most heterogeneous group of genetically engineered mouse models (GEMMs) of breast cancer yet observed. Response of MDSTs to trametinib, a mitogen-activated protein kinase (MAPK) kinase inhibitor, correlated with RAS/MAPK signaling activity, as expected from studies in xenografts and clinical trials providing validation of the utility of the model. Sensitivity of MDSTs to talazoparib, a poly(adenosine 5'-diphosphate-ribose) polymerase (PARP) inhibitor, was predicted by PARP1 protein levels and by a new PARP sensitivity predictor (PSP) score developed from integrated analysis of drug sensitivity data of human cell lines. PSP score-based classification of The Cancer Genome Atlas breast cancer suggested that a subset of patients with limited therapeutic options would be expected to benefit from PARP-targeted drugs. These results indicate that MDSTs are useful models for studies of targeted therapies, and propose novel potential biomarkers for identification of breast cancer patients likely to benefit from personalized pharmacological treatments.

High Intratumoral Stromal Content Defines Reactive Breast Cancer as a Low-risk Breast Cancer Subtype

PURPOSE

The current study evaluated associative effects of breast cancer cells with the tumor microenvironment and its influence on tumor behavior.

EXPERIMENTAL DESIGN

Formalin-fixed, paraffin-embedded tissue and matched protein lysates were evaluated from two independent breast cancer patient datasets (TCGA and MD Anderson). Reverse-phase protein arrays (RPPA) were utilized to create a proteomics signature to define breast tumor subtypes. Expression patterns of cell lines and normal breast tissues were utilized to determine markers that were differentially expressed in stroma and cancer cells. Protein localization and stromal contents were evaluated for matched cases by imaging.

RESULTS

A subtype of breast cancers designated "Reactive," previously identified by RPPA that was not predicted by mRNA profiling, was extensively characterized. These tumors were primarily estrogen receptor (ER)-positive/human EGF receptor (HER)2-negative, low-risk cancers as determined by enrichment of low-grade nuclei, lobular or tubular histopathology, and the luminal A subtype by PAM50. Reactive breast cancers contained high numbers of stromal cells and the highest extracellular matrix content typically without infiltration of immune cells. For ER-positive/HER2-negative cancers, the Reactive classification predicted favorable clinical outcomes in the TCGA cohort (HR, 0.36; P < 0.05).

CONCLUSIONS

A protein stromal signature in breast cancers is associated with a highly differentiated phenotype. The stromal compartment content and proteins are an extended phenotype not predicted by mRNA expression that could be utilized to subclassify ER-positive/HER2-negative breast cancers. Clin Cancer Res; 22(20); 5068-78. ©2016 AACR.

Characterization of the role Rab25 in energy metabolism and cancer using extracellular flux analysis and material balance

Rab25, by altering trafficking of critical cellular resources, influences cell metabolism and survival during stress conditions. Overall, perturbations in the vesicular trafficking machinery change cellular bioenergetics that can be directly measured in real time as Oxygen Consumption Rate, OCR (mitochondrial respiration) and Extracellular Acidification Rate, ECAR (glycolysis) by an extracellular flux analyzer (XF96, Seahorse Biosciences, MA). Additionally, overall turnover of glucose, lactate, as well as glutamine and glutamate can be measured biochemically using the YSI2900 Biochemistry Analyzer (YSI Incorporated, Life Sciences, OH). A combination of these two methods allows a precise and quantitative approach to interrogate the role of Rab25 as well as other Rab GTPases in central carbon energy metabolism.

Functional annotation of rare gene aberration drivers of pancreatic cancer

As we enter the era of precision medicine, characterization of cancer genomes will directly influence therapeutic decisions in the clinic. Here we describe a platform enabling functionalization of rare gene mutations through their high-throughput construction, molecular barcoding and delivery to cancer models for in vivo tumour driver screens. We apply these technologies to identify oncogenic drivers of pancreatic ductal adenocarcinoma (PDAC). This approach reveals oncogenic activity for rare gene aberrations in genes including NAD Kinase (NADK), which regulates NADP(H) homeostasis and cellular redox state. We further validate mutant NADK, whose expression provides gain-of-function enzymatic activity leading to a reduction in cellular reactive oxygen species and tumorigenesis, and show that depletion of wild-type NADK in PDAC cell lines attenuates cancer cell growth in vitro and in vivo. These data indicate that annotating rare aberrations can reveal important cancer signalling pathways representing additional therapeutic targets.

The beneficial effects of a gas-permeable flask for expansion of Tumor-Infiltrating lymphocytes as reflected in their mitochondrial function and respiration capacity

Adoptive transfer of autologous ex vivo expanded tumor-infiltrating lymphocytes (TIL) is a highly successful cell therapy approach in the treatment of late-stage melanoma. Notwithstanding the success of this therapy, only very few centers worldwide can provide it. To make this therapy broadly available, one of the major obstacles to overcome is the complexity of culturing the TIL. Recently, major efforts have been deployed to resolve this issue. The use of the Gas-permeable flask (G-Rex) during the REP has been one application that has facilitated this process. Here we show that the use of this new device is able to rescue poor TIL growth and maintain clonal diversity while supporting an improved mitochondrial function.

Abstract P1-08-01: Signaling consequences and rational therapeutic combinations with glutaminase inhibitor, CB-839, in basal breast cancer

Purpose: Proliferation rates of basal breast cancers are dependent on glutamine metabolism as previously demonstrated by glutamine withdrawal or glutaminase inhibition by CB-839 in cell line models. Early and late adaptive signaling and metabolic responses to glutamine stress may enable cells to proliferate or evade cell death. We hypothesized that inhibition of these pathways would be synergistic in combination with glutaminase inhibition by CB-839.

Methods: Protein signaling responses in HCC1806 cells (basal A breast cancer) were quantified using reverse phase protein arrays (RPPA) at early (4 h) and late (24 h) time points in response to low glucose or low glutamine concentrations as well as treatment with CB-839, a selective glutaminase inhibitor. Signaling pathways evaluated included mTORC1/2, PI3K/AKT, MAPK, and AMPK. ADP and ATP were quantified by ion exchange chromatography. Drug combinations predicted by RPPA were evaluated at therapeutically relevant concentrations using proliferation or apoptosis assays after 72 h of continuous treatment.

Results: In agreement with previous reports of glutamine withdrawal, low glutamine and glutaminase inhibition resulted in inhibition of proliferation and early inhibition of mTORC1 signaling including pmTOR, pP70S6K, p4EBP1, and pS6. In contrast, for cells incubated in low glucose, proliferation and mTOR signaling were maintained at early time points despite robust pAMPK/pACC signaling and increased ADP/ATP ratios (2-orders of magnitude higher than baseline); mTOR signaling was only inhibited after 24 h when ATP concentrations were reduced. Bioenergetic stress as detected by pAMPK and pACC was not observed with glutaminase inhibition – ATP concentrations were increased by CB-839 treatment. Importantly, 2-deoxyglucose, a compound used to reduce ATP levels and activate AMPK signaling, was antagonistic in combination with CB-839. In contrast, hydroxychloroquine, an inhibitor of autophagy activated by mTOR inhibition, was synergistic with CB-839.

Consistent with mTORC1-mediated negative feedback loops, CB-839 treatment also increased AKT and ERK signaling. Combinations of CB-839 with AKT or MEK inhibitors (AZD5363 and GSK1120212B) were at synergistic and additive, respectively, for cell proliferation. The MEK inhibitor in combination with CB-839 resulted in supra-additive effects using apoptosis as an endpoint.

Conclusion: Glutaminase inhibition by CB-839 acutely inhibited mTORC1 signaling independently of AMPK signaling in HCC1806 cells. MEK and AKT signaling increased, likely in response to negative feedback loops with mTORC1. Combinatorial approaches with CB-839 targeting these compensation pathways resulted in increased responses supporting further preclinical and clinical studies.

Citation Format: Jennifer B Dennison, Zhenlin Ju, Mills B Gordon. Signaling consequences and rational therapeutic combinations with glutaminase inhibitor, CB-839, in basal breast cancer [abstract]. In: Proceedings of the Thirty-Seventh Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2014 Dec 9-13; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2015;75(9 Suppl):Abstract nr P1-08-01.

Quinoline 3-sulfonamides inhibit lactate dehydrogenase A and reverse aerobic glycolysis in cancer cells

Background

Most normal cells in the presence of oxygen utilize glucose for mitochondrial oxidative phosphorylation. In contrast, many cancer cells rapidly convert glucose to lactate in the cytosol, a process termed aerobic glycolysis. This glycolytic phenotype is enabled by lactate dehydrogenase (LDH), which catalyzes the inter-conversion of pyruvate and lactate. The purpose of this study was to identify and characterize potent and selective inhibitors of LDHA.

Methods

High throughput screening and lead optimization were used to generate inhibitors of LDHA enzymatic activity. Effects of these inhibitors on metabolism were evaluated using cell-based lactate production, oxygen consumption, and ¹³C NMR spectroscopy assays. Changes in comprehensive metabolic profile, cell proliferation, and apoptosis were assessed upon compound treatment.

Results

3-((3-carbamoyl-7-(3,5-dimethylisoxazol-4-yl)-6-methoxyquinolin-4-yl) amino) benzoic acid was identified as an NADH-competitive LDHA inhibitor. Lead optimization yielded molecules with LDHA inhibitory potencies as low as 2 nM and 10 to 80-fold selectivity over LDHB. Molecules in this family rapidly and profoundly inhibited lactate production rates in multiple cancer cell lines including hepatocellular and breast carcinomas. Consistent with selective inhibition of LDHA, the most sensitive breast cancer cell lines to lactate inhibition in hypoxic conditions were cells with low expression of LDHB. Our inhibitors increased rates of oxygen consumption in hepatocellular carcinoma cells at doses up to 3 microM, while higher concentrations directly inhibited mitochondrial function. Analysis of more than 500 metabolites upon LDHA inhibition in Snu398 cells revealed that intracellular concentrations of glycolysis and citric acid cycle intermediates were increased, consistent with enhanced Krebs cycle activity and blockage of cytosolic glycolysis. Treatment with these compounds also potentiated PKM2 activity and promoted apoptosis in Snu398 cells.

Conclusions

Rapid chemical inhibition of LDHA by these quinoline 3-sulfonamids led to profound metabolic alterations and impaired cell survival in carcinoma cells making it a compelling strategy for treating solid tumors that rely on aerobic glycolysis for survival.

The relative contributions of CYP3A4 and CYP3A5 to the metabolism of vinorelbine

Vinorelbine is a semisynthetic vinca alkaloid used in the treatment of advanced breast and non-small cell lung cancers. Vincristine, a related vinca alkaloid, is 9-fold more efficiently metabolized by CYP3A5 than by CYP3A4 in vitro. This study quantified the relative contribution of CYP3A4 and CYP3A5 to the metabolism of vinorelbine in vitro using cDNA-expressed human cytochrome P450s (P450s) and human liver microsomes (HLMs). CYP3A4 and CYP3A5 were identified as the P450s capable of oxidizing vinorelbine using a panel of human enzymes and selective P450 inhibitors in HLMs. For CYP3A4 coexpressed with cytochrome b5 (CYP3A4+b5) and CYP3A5+b5, the Michaelis-Menten constants for vinorelbine were 2.6 and 3.6 μM, respectively, but the Vmax of 1.4 pmol/min/pmol was common to both enzymes. In HLMs, the intrinsic clearance of vinorelbine metabolism was highly correlated with CYP3A4 activity, and there was no significant difference in intrinsic clearance between CYP3A5 high and low expressers. When radiolabeled vinorelbine substrate was used, there were clear qualitative differences in metabolite formation fingerprints between CYP3A4+b5 and CYP3A5+b5 as determined by NMR and mass spectrometry analysis. One major metabolite (M2), a didehydro-vinorelbine, was present in both recombinant and microsomal systems but was more abundant in CYP3A4+b5 incubations. We conclude that despite the equivalent efficiency of recombinant CYP3A4 and CYP3A5 in vinorelbine metabolism the polymorphic expression of CYP3A5, as shown by the kinetics with HLMs, may have a minimal effect on systemic clearance of vinorelbine.

Lactate dehydrogenase B: a metabolic marker of response to neoadjuvant chemotherapy in breast cancer

PURPOSE

Although breast cancers are known to be molecularly heterogeneous, their metabolic phenotype is less well-understood and may predict response to chemotherapy. This study aimed to evaluate metabolic genes as individual predictive biomarkers in breast cancer.

EXPERIMENTAL DESIGN

mRNA microarray data from breast cancer cell lines were used to identify bimodal genes-those with highest potential for robust high/low classification in clinical assays. Metabolic function was evaluated in vitro for the highest scoring metabolic gene, lactate dehydrogenase B (LDHB). Its expression was associated with neoadjuvant chemotherapy response and relapse within clinical and PAM50-derived subtypes.

RESULTS

LDHB was highly expressed in cell lines with glycolytic, basal-like phenotypes. Stable knockdown of LDHB in cell lines reduced glycolytic dependence, linking LDHB expression directly to metabolic function. Using patient datasets, LDHB was highly expressed in basal-like cancers and could predict basal-like subtype within clinical groups [OR = 21 for hormone receptor (HR)-positive/HER2-negative; OR = 10 for triple-negative]. Furthermore, high LDHB predicted pathologic complete response (pCR) to neoadjuvant chemotherapy for both HR-positive/HER2-negative (OR = 4.1, P < 0.001) and triple-negative (OR = 3.0, P = 0.003) cancers. For triple-negative tumors without pCR, high LDHB posttreatment also identified proliferative tumors with increased risk of recurrence (HR = 2.2, P = 0.006).

CONCLUSIONS

Expression of LDHB predicted response to neoadjuvant chemotherapy within clinical subtypes independently of standard prognostic markers and PAM50 subtyping. These observations support prospective clinical evaluation of LDHB as a predictive marker of response for patients with breast cancer receiving neoadjuvant chemotherapy.

Abstract 1702: Metabolic heterogeneity of HER2-positive breast cancers

Breast cancers are at least five molecularly distinct diseases with reported metabolic differences. Basal-like breast cancers are typically more glycolytic as compared to luminal-like breast cancers. However, HER2-positive breast tumors have variable FDG-PET maximum uptake values. We hypothesized that HER2-positive breast cancer cell lines would reflect the metabolic heterogeneity reported in breast cancer tumors. In the current study, a panel of HER2-positive breast cancer cell lines (N = 8) was profiled by their metabolic properties. To evaluate glycolytic dependency for ATP production, ATP-synthase dependent oxygen consumption rates were normalized to extracellular acidification rates using the Seahorse Bioscience XF analyzer. The glycolytic dependency was highly variable (12-fold range); ER-negative lines including AU565 and HCC1954 were the most glycolytic. Consistent with these results, HER2-positive/ER-negative cell lines produced more lactate compared to HER2-positive/ER-positive cell lines (1.5 versus 1.2 lactate produced/glucose consumed, p = 0.02). The glycolytic phenotypes of HER2-positive/ER-negative breast cancer cell lines were similar to that of basal-like breast cancer cell lines. For the HER2-positive lines, the highest rates of glutamine consumption were in ER-positive lines BT474 and HCC1419. Differential expression of mitochondrial glutaminase 2 (GLS2, p = 0.02), but not cytosolic glutaminase (GLS) or glutamine synthetase (GLUL), may contribute to higher rates of glutamine consumption by HER2-positive/ER-positive breast cancers. Consistent with higher rates of mitochondrial respiration, ER-positive/HER2-positive cells were also associated with higher expression of carbonic anhydrase 12 (CA12) and lower expression of the lactate transporter MCT1 (SLC16A1). Metabolic heterogeneity of HER2-positive cells was only evident in normoxic conditions. Per the “Pasteur effect,” all cell lines cultured under hypoxia (1% O2) were equally glycolytic (average = 1.8 lactate production/glucose consumption ratio) with correspondingly reduced rates of glutamine uptake. We conclude that the heterogeneity observed in FDG-PET may be influenced by fundamental metabolic differences between HER2-positive breast cancers, in particular, for well-oxygenated regions of the tumor.

Citation Format: Jennifer B. Dennison, Gordon B. Mills. Metabolic heterogeneity of HER2-positive breast cancers. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 1702. doi:10.1158/1538-7445.AM2013-1702