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.

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.

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.

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.

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 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.

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.

Caveolin-1-mediated sphingolipid oncometabolism underlies a metabolic vulnerability of prostate cancer.

Plasma and tumor caveolin-1 (Cav-1) are linked with disease progression in prostate cancer. Here we report that metabolomic profiling of longitudinal plasmas from a prospective cohort of 491 active surveillance (AS) participants indicates prominent elevations in plasma sphingolipids in AS progressors that, together with plasma Cav-1, yield a prognostic signature for disease progression. Mechanistic studies of the underlying tumor supportive onco-metabolism reveal coordinated activities through which Cav-1 enables rewiring of cancer cell lipid metabolism towards a program of 1) exogenous sphingolipid scavenging independent of cholesterol, 2) increased cancer cell catabolism of sphingomyelins to ceramide derivatives and 3) altered ceramide metabolism that results in increased glycosphingolipid synthesis and efflux of Cav-1-sphingolipid particles containing mitochondrial proteins and lipids. We also demonstrate, using a prostate cancer syngeneic RM-9 mouse model and established cell lines, that this Cav-1-sphingolipid program evidences a metabolic vulnerability that is targetable to induce lethal mitophagy as an anti-tumor therapy.

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.

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.

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.

PET of insulinoma using ¹8F-FBEM-EM3106B, a new GLP-1 analogue.

Derived from endocrine pancreatic beta cells, insulinomas express glucagon-like peptide-1 (GLP-1) receptor with high density and incidence. In this study, we labeled a novel GLP-1 analogue, EM3106B, with (18)F and performed PET imaging to visualize insulinoma tumors in an animal model. A GLP-1 analogue that contains multiple lactam bridges, EM3106B, was labeled with (18)F through a maleimide-based prosthetic group, N-2-(4-(18)F-fluorobenzamido)ethylmaleimide ((18)F-FBEM). The newly developed radiotracer was characterized by cell based receptor-binding assay, cell uptake and efflux assay. The stability in serum was evaluated by radio-HPLC analysis. In vivo PET imaging was performed in nude mice bearing subcutaneous INS-1 insulinoma tumors and MDA-MB-435 tumors of melanoma origin. Ex vivo biodistribution study was performed to confirm the PET imaging data. EM3106B showed high binding affinity (IC(50) = 1.38 nM) and high cell uptake (5.25 ± 0.61% after 120 min incubation). (18)F-FBEM conjugation of EM3106B resulted in high labeling yield (24.9 ± 2.4%) and high specific activity (>75 GBq/µmol at the end of bombardment). EM3106B specifically bound and was internalized by GLP-1R positive INS-1 cells. After intravenous injection of 3.7 MBq (100 µCi) of (18)F-FBEM-EM3106B, the INS-1 tumors were clearly visible with high contrast in relation to the contralateral background on PET images, and tumor uptake of (18)F-FBEM-EM3106B was determined to be 28.5 ± 4.7 and 25.4 ± 4.1% ID/g at 60 and 120 min, respectively. (18)F-FBEM-EM3106B showed low uptake in MB-MDA-435 tumors with low level of GLP-1R expression. Direct tissue sampling biodistribution experiment confirmed high tracer uptake in INS-1 tumors and receptor specificity in both INS-1 tumor and pancreas. In conclusion, (18)F-FBEM-EM3106B exhibited GLP-1R-receptor-specific targeting properties in insulinomas. The favorable characteristics of (18)F-FBEM-EM3106B, such as high specific activity and high tumor uptake, and high tumor to nontarget uptake, demonstrate that it is a promising tracer for clinical insulinoma imaging.

Development of potent glucagon-like peptide-1 agonists with high enzyme stability via introduction of multiple lactam bridges.

Glucagon-like peptide-1 (GLP-1) has the ability to lower the blood glucose level, and its regulatory functions make it an attractive therapeutic agent for the treatment of type 2 diabetes. However, its rapid degradation by enzymes like dipeptidyl peptidase-IV (DPP-IV) and neutral endopeptidase (NEP) 24.11 severely compromises its effective clinical use. Whereas specific DPP-IV inhibitors have been developed, NEP 24.11 targets multiple sites in the GLP-1 sequence, which makes it difficult to block. To address this drawback, we have designed and synthesized conformationally constrained GLP-1 analogues by introducing multiple lactam bridges that stabilized both alpha-helices in the N- and C-terminal regions simultaneously. In addition to improving the receptor activation capability (up to 5-fold) by fixing the alpha-helical conformations required for optimal receptor interaction, the introduced lactam bridges provided outstanding shielding over NEP 24.11 (half-life of >96 h). These highly constrained peptides are the first examples of NEP 24.11-resistant GLP-1 analogues.

Search for alpha-helical propensity in the receptor-bound conformation of glucagon-like peptide-1.

To elucidate the receptor-bound conformation of glucagon-like peptide-1 (GLP-1), a series of conformationally constrained GLP-1 analogues were synthesized by introducing lactam bridges between Lys(i) and Glu(i)(+4) to form alpha-helices at various positions. The activity and affinity of these analogues to GLP-1 receptors suggested that the receptor-bound conformation comprises two alpha-helical segments between residues 11-21 and 23-34. It is notable that the N-terminal alpha-helix is extended to Thr(11), and that Gly(22) plays a pivotal role in arranging the two alpha-helices. Based on these findings, a highly potent bicyclic GLP-1 analogue was synthesized which is the most conformationally constrained GLP-1 analogue reported to date.