A novel method to guide biomarker combinations to optimize the sensitivity.

Logistic regression has demonstrated its utility in classifying binary labeled datasets through the maximum likelihood approach. However, in numerous biological and clinical contexts, the aim is often to determine coefficients that yield the highest sensitivity at the pre-specified specificity or vice versa. Therefore, the application of logistic regression is limited in such settings. To this end, we have developed an improved regression framework, SMAGS, for binary classification that, for a given specificity, finds the linear decision rule that yields the maximum sensitivity. Furthermore, we employed the method for feature selection to find the features that are satisfying the sensitivity maximization goal. We compared our method with normal logistic regression by applying it to real clinical data as well as synthetic data. In the real application data (colorectal cancer dataset), we found 14% improvement of sensitivity at 98.5% specificity. Availability and implementation: Software is made available in Python ( https://github.com/smahmoodghasemi/SMAGS ).

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.

Protein biomarkers and alternatively methylated cell-free DNA detect early stage pancreatic cancer.

OBJECTIVE: Pancreatic ductal adenocarcinoma (PDAC) is commonly diagnosed at an advanced stage. Liquid biopsy approaches may facilitate detection of early stage PDAC when curative treatments can be employed. DESIGN: To assess circulating marker discrimination in training, testing and validation patient cohorts (total n=426 patients), plasma markers were measured among PDAC cases and patients with chronic pancreatitis, colorectal cancer (CRC), and healthy controls. Using CA19-9 as an anchor marker, measurements were made of two protein markers (TIMP1, LRG1) and cell-free DNA (cfDNA) pancreas-specific methylation at 9 loci encompassing 61 CpG sites. RESULTS: Comparative methylome analysis identified nine loci that were differentially methylated in exocrine pancreas DNA. In the training set (n=124 patients), cfDNA methylation markers distinguished PDAC from healthy and CRC controls. In the testing set of 86 early stage PDAC and 86 matched healthy controls, CA19-9 had an area under the receiver operating characteristic curve (AUC) of 0.88 (95% CI 0.83 to 0.94), which was increased by adding TIMP1 (AUC 0.92; 95% CI 0.88 to 0.96; p=0.06), LRG1 (AUC 0.92; 95% CI 0.88 to 0.96; p=0.02) or exocrine pancreas-specific cfDNA methylation markers at nine loci (AUC 0.92; 95% CI 0.88 to 0.96; p=0.02). In the validation set of 40 early stage PDAC and 40 matched healthy controls, a combined panel including CA19-9, TIMP1 and a 9-loci cfDNA methylation panel had greater discrimination (AUC 0.86, 95% CI 0.77 to 0.95) than CA19-9 alone (AUC 0.82; 95% CI 0.72 to 0.92). CONCLUSION: A combined panel of circulating markers including proteins and methylated cfDNA increased discrimination compared with CA19-9 alone for early stage 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.

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.

A Nasal Inflammatory Cytokine Signature Is Associated with Early Graft-versus-Host Disease of the Lung after Allogeneic Hematopoietic Cell Transplantation: Proof of Concept.

Respiratory inflammation in bronchiolitis obliterans syndrome (BOS) after hematopoietic cell transplantation (HCT) is poorly understood. Clinical criteria for early-stage BOS (stage 0p) often capture HCT recipients without BOS. Measuring respiratory tract inflammation may help identify BOS, particularly early BOS. We conducted a prospective observational study in HCT recipients with new-onset BOS (n = 14), BOS stage 0p (n = 10), and recipients without lung impairment with (n = 3) or without (n = 8) chronic graft-versus-host disease and measured nasal inflammation using nasosorption at enrollment and then every 3 mo for 1 y. We divided BOS stage 0p into impairment that did not return to baseline values (preBOS, n = 6), or transient impairment (n = 4). We tested eluted nasal mucosal lining fluid from nasosorption matrices for inflammatory chemokines and cytokines using multiplex magnetic bead immunoassays. We analyzed between-group differences using the Kruskal-Wallis method, adjusting for multiple comparisons. We found increased nasal inflammation in preBOS and therefore directly compared patients with preBOS to those with transient impairment, as this would be of greatest diagnostic relevance. After adjusting for multiple corrections, we found significant increases in growth factors (FGF2, TGF-α, GM-CSF, VEGF), macrophage activation (CCL4, TNF-α, IL-6), neutrophil activation (CXCL2, IL-8), T cell activation (CD40 ligand, IL-2, IL-12p70, IL-15), type 2 inflammation (eotaxin, IL-4, IL-13), type 17 inflammation (IL-17A), dendritic maturation (FLT3 ligand, IL-7), and counterregulatory molecules (PD-L1, IL-1 receptor antagonist, IL-10) in preBOS patients compared to transient impairment. These differences waned over time. In conclusion, a transient multifaceted nasal inflammatory response is associated with preBOS. Our findings require validation in larger longitudinal cohorts.

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.

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.

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.

A unified mediation analysis framework for integrative cancer proteogenomics with clinical outcomes.

MOTIVATION: Multilevel molecular profiling of tumors and the integrative analysis with clinical outcomes have enabled a deeper characterization of cancer treatment. Mediation analysis has emerged as a promising statistical tool to identify and quantify the intermediate mechanisms by which a gene affects an outcome. However, existing methods lack a unified approach to handle various types of outcome variables, making them unsuitable for high-throughput molecular profiling data with highly interconnected variables. RESULTS: We develop a general mediation analysis framework for proteogenomic data that include multiple exposures, multivariate mediators on various scales of effects as appropriate for continuous, binary and survival outcomes. Our estimation method avoids imposing constraints on model parameters such as the rare disease assumption, while accommodating multiple exposures and high-dimensional mediators. We compare our approach to other methods in extensive simulation studies at a range of sample sizes, disease prevalence and number of false mediators. Using kidney renal clear cell carcinoma proteogenomic data, we identify genes that are mediated by proteins and the underlying mechanisms on various survival outcomes that capture short- and long-term disease-specific clinical characteristics. AVAILABILITY AND IMPLEMENTATION: Software is made available in an R package (https://github.com/longjp/mediateR). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

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.

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.

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.

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 (PLCOm2012) 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 + PLCOm2012 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 + PLCOm2012 model exhibited statistically significant improvements in sensitivity and specificity. Among PLCO participants with ≥ 10 smoking pack-years, the 4MP + PLCOm2012 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 PLCOm2012 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.

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.