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Colon Cancer is the third most common cause of cancer-related death

Cancer Prevention: Translational Research in Colon Cancer Matthew R. Young Gene Regulation Section Laboratory of Cancer Prevention CCR, NCI.

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Colon Cancer is the third most common cause of cancer-related death

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  1. Cancer Prevention: Translational Research in Colon CancerMatthew R. YoungGene Regulation Section Laboratory of Cancer PreventionCCR, NCI

  2. Translational Cancer Prevention: How do we approach Translational Research in Cancer Prevention? Colon Cancer:Anatomy of Colon Cancer Risk factors for Colon Carcinogenesis Colon Cancer Prevention: Polyp Prevention Trial (PPT) Mouse MetabolomicsCancer Stem CellsNutrition

  3. Molecular Targeted Carcinogenesis Prevention: Benefits at any stage. Cancer prevention prolongs the natural lifetime due to reduced death from cancer

  4. Cancer progression:1. Initiation can be a single mutagenic event.2. Promotion results from chronic exposure to tumor promoters e.r. TPA, EGF, UV radiation, TNFά or stress lead to benign tumors.3. Progression results when benign tumors progress to carcinoma.Receptors activation increases protein kinase activity, resulting in and increase in transcription factors. Translation factors lead to mis-regulation of target proteins.

  5. TRANSLATING PREVENTIONHow do we approach Translational Research in Cancer Prevention? Behavior modification in the general population: Smoking cessation, Weight reduction Diet modification ExerciseDrugs in high risk groups: Tamoxifen: to prevent breast cancer DFMO + Sulindac: to prevent colon cancer Aspirin: breast and colon NSAIDS (Celecoxib) Adenoma Prevention Trail Diet supplementsVaccines in the general population: HVP vaccine: to prevent cervical cancer. HBV vaccine: to prevent liver cancerAntibiotics in high risk groups: Block H-pylori induce gastric and esophageal cancer

  6. Colon Cancer is the third most common cause of cancer-related death

  7. Risk factors Associated with Colon CancerAfrican-American race..Sedentary Life styleAgeDiabetesA personal history of colorectal cancer or polyps. SmokingObesityInflammatory intestinal conditions. RadiationAlcoholInherited syndromes that increase colon cancer risk.Family history of colon cancer and colon polyps.Low-fiber, high-fat diet.

  8. Trends in overweight prevalence

  9. The Anatomy of the Colon Differentiated cells Transit- amplifying cells Stem cell niche

  10. Tumor Promotion in the Colon Progression Initiation Promotion Activated Myofibroblast HGF Myofibroblast Myeloid cells IL-6 TNFa Normal organization of the intestinal crypt Accumulation of other genetic lesions, RAS and PTEN, Progression towards an invasive growing CRC Loss of wild-type APC or β-catenin mutation Transformation of healthy crypts towards an adenoma

  11. Stages of colon carcinogenesis ~50% of US population have adenoma(s) by age 70 years

  12. TRANSLATING PREVENTION. Basic research uses molecular processes, molecular target identification and targeted drug discovery. Preclinical research uses target validation and target discovery as well as response biomarkers and molecular targets as endpoints. Clinical research used drug-based and dietary interventions as well as response biomarfer and molecular target identification. Cancer Prevention

  13. The Polyp Prevention Trial (PPT) Multicenter randomized controlled trial examining the effect of a low-fat (20% of total energy intake), high-fiber (18 g/1000 kcal), high-vegetable and -fruit (5-8 daily servings) dietary pattern on the recurrence of adenomatous polyps of the large bowel, Eligibility one or more adenomas removed within 6 months complete nonsurgical polyp removal complete colonic examination age 35 years or older; no history of colorectal cancer, inflammatory bowel disease, or large bowel resection; satisfactory completion of a food frequency questionnaire and 4-day food record

  14. Dry Bean Intake Inversely Associatedwith Advanced Adenoma Recurrence Advanced Adenoma Recurrence OR (95% CI) P-trend: 0.001 Q2 Q3 Q4 3.4 12.0 41.5 ∆ Dry Bean Intake (T(1,2,3)-T0; in g/d)

  15. Ob/Ob Obese MiceSingle mutation within the Ob (leptin) geneDevelop obesity, hyperphagia, hyperinsulinemia, and hyperglycemiaInjected with colon carcinogen azoxymethane (AOM) to induce colon cancer Placed on diets after final AOM( injection for 40 weeks 1) Control diet (modified AIN-93G) 2) Cooked Whole navy bean diet 3) Bean Residue fraction diet 4) Bean ethanol Extract fraction diet

  16. Navy Beans and their Fractions Decrease Colon Lesion Incidence* in AOM-Induced Obese Mice

  17. Biomarkers that predict Colon Cancer and Efficacy of interventions in mice and humans IL-6 a response biomarker for dietary prevention of colonCarcinogenesis in Ob mice,Mentor-Marcel Can Prev Res ,2009

  18. Decrease in serum levels ofIL-6 anindicator of efficacious response to bean diet

  19. Bean diet attenuates colon gene expression changes induced by AOM in ob/ob mice AOM AOM + Bean extract * * * * IL-6 Tnfrsf8 Stat 4 Sftpd

  20. Human Relevance of IL-6 as a Biomarker of Response to Dietary InterventionInterleukin-6 as a Potential Indicator for Dietary PreventionOf High Risk Adenoma Recurrence in the Polyp Prevention Trial, Bobe G et al, Cancer Prevention Research, 2010

  21. Colon Carcinogenesis stages in the mouse

  22. Two-Stage Colon Carcinogenesis Model AOM/DSSMice develop ACFs, dysplastic lesions, adenomas and adenocarcinomas.Lesions have elevated b-catenin, cyclooxygenase-2 (COX-2) and inducible nitric oxide synthase (iNOS) activity First tumors appeared Start Diet Day 0 7 14 21 28 35 42 49 56 70 1-2% DSSin dist. water AOM 10 mg/kg BW Mice 6 wks of age

  23. MRI is useful for monitoring efficacy of dietary and/or pharmacological interventions in colon carcinogenesis Polyps Detected Initial polyps Enlarge Tumor burden Unhealthy Normal Untreated 29 50 60 Days after AOM injection

  24. MRI is useful for monitoring efficacy of dietary and/or pharmacological interventions in colon carcinogenesis

  25. Bean Extracts and Isorhamnetin diets inhibit inflammation induced colon cancer. Isorhamnetin, Kaempferol and Bean Extracts decreased tumor burdenIsorhamnetin and the Bean Extracts decreased morbidity associated with AOM/DSS treatment

  26. Pilot study to assess efficacy of lifestyle alteration.Legume Inflammation Feeding Experiment (LIFE). The effects of a high legume (dry bean) diet on markers of insulin resistance (IR) and inflammation in patients at high risk for CRC.

  27. Legume Inflammation Feeding ExperimentElaine Lanza, Cytonix; Terry Hartman, PSU; Robb Chapkin Tx A & M Blood (B) B B B B B weeks F F F Legume Diet Legume Diet Legume Diet Ad libitum Weight change Feces (F) American Diet Legume Diet Ad Libitum Weight change American Diet

  28. Candidate molecular biomarkers identified from exfoliated colonocytes.Two- and three-gene combinations provide robust classifiers with potential to noninvasively identify discriminative molecular signatures for differential diagnostic purposes.

  29. Potential biomarkers associated with consumption of Legume Enriched and Healthy American diets D LegumeP-valueD Healthy AmericanP-value sTNFR1 - 3.7% 0.005 - 4.4% 0.001 CRP -20.2% 0.018 -18.3% 0.007 C-peptide - 2.8% 0.407 - 0.1 0.605 Legume Diet Legume Diet American Diet American Diet

  30. Potential biomarkers associated with consumption of reduced energy legume enriched diets. Mean body weight - 4.4 P<0.001 BMI -4.5% P<0.001 Other markers significantly reduced (P<0.001)Total Cholesterol, LDL-C, TG, C-peptide, fasting glucose, Leptin Legume Diet Legume Diet American Diet American Diet Legume Diet Ad libitum Weight change

  31. Metabolomics for identification of Biomarkers for Dietary Intervention and Protection. Metabolomics: The systematic study of all metabolites in an organism and how they change in relation to a biological perturbation such as diet, disease or intervention

  32. Metabolomics for identifying biomarkers from the LIFE study. Serum was collected from participants before and after consumption of bean enriched weight maintenance diet. Anticipated results:Identification of biomarkers for complianceDiscovery of biomarkers of efficacy B B Legume Diet American Diet Legume Diet American Diet B B

  33. Metabolomics for identifying biomarkers from the LIFE study274 named biochemicals identified; 87 biochemicals were significanly different between pre and post bean dietsPipecolate increased more than 6-fold in post bean diet.  ExtremeMean Value Metabolite Name ___ Box and Whiskers Legend Median Value Data Points Upper Quartile Lower Quartile Scaled Intensity “Max” of distribution “Min” of distribution Treatment Group

  34. Diet-derived Metabolites Diet-derived metabolites showed significantly different plasma levels in pre-diet and post-diet samples. Trigonelline (N-methylnicotinate)

  35. Gut Bacterial Metabolites. Several metabolites generated by gut bacterial metabolism showed significantly different plasma levels in pre-diet and post-diet samples

  36. Potential Markers of Dietary CompliancePotential candidates for markers of compliance to bean diet include the following. Gut bacterial metabolites pipecolate and indole proprionate. Diet derived 1,5-anhydroglucitol (1,5-AG)Modified amino acid N-acetylornithine

  37. Metabolomics for identifying biomarkers from the AOM/DSS induced CRC in mice AOM 2% DSS Diet serum/feces 0 7 12 14 21 28 35 42 49 56 63 70 Days

  38. Metabolomics from Mice fed Bean Extracts Correlates with Metabolomics from Human (LIFE) Study Pipecolate and N-acetyl-ornithine, proposed biomarkers of bean diet compliance identified elevated in both bean diet plasma groups. Also a similar subtle yet significant decrease in 1,5-anhydroglucitol was observed in both animal groups on bean diet.

  39. Metabolomics from Mice fed Bean Extracts Correlates with Metabolomics from Human (LIFE) StudyDecreased lysophospholipids Decreased medium- chain fatty acids Decrease in carnitine/acylcarnitines, No notable change in long-chain FA; Collectively indicating increased FA metabolism for energy in bean diet-fed animals

  40. Fetal metabolomics from mice fed bean extract dietIncrease in Alcohol sugars,Krebs cycle intermediates (citrate, alpha-ketoglutarate, fumarate and malate) were also significantly elevated in feces of bean extract fed mice.Fecal nucleotide breakdown products including nitrogenous bases, ribose and 2-deoxyribose, as well as phosphate were substantially increased in bean extract fed mice

  41. The NCI-Translational Research Working Group:Lifestyle Alteration Developmental Pathway LIFE: Short term feeding study to measure the effects of a bean diet on markers of insulin resistance (IR) and inflammation in patients at high risk for CRC.Develop Biomarkers-Metabolomics: Metabolic biomarkers of compliance identified in human serum Develop Biomarkers-Metabolomics: Metabolic biomarkers of compliance identified in human serum also detected in mouse serum and feces. Young et al., unpublished

  42. The NCI-Translational Research Working Group:Lifestyle Alteration Developmental Pathway LIFE: Short term feeding study to measure the effects of a bean diet on markers of insulin resistance (IR) and inflammation in patients at high risk for CRC.Develop Biomarkers-Metabolomics: Metabolic biomarkers of compliance identified in human serum Develop Biomarkers-Metabolomics: Metabolic biomarkers of compliance identified in human serum also detected in mouse serum and feces. Young et al., unpublished

  43. Metabolomic analysis from the Polyp Prevention Trial: Identification of metabolic biomarkers associated with reduced adenoma recurrence. 3 groups of 125 participants 2 time points, baseline and after 3 years Control: Participants with no change in tumors Intervention, bean consumption: participants who consumed high bean diet and showed a reduced recurrence of adenomas Tumor Positive: Participants with increased recurrence of adenoma after 3 yr

  44. BIOMARKERS AND MOLECULAR TARGETS OF NON-TOXIC DIETARY INTERVENTIONS FOR CANCER PREVENTION Laboratory of Cancer Prevention Nancy Colburn, Noriko Yoshikawa, Alyson Baker, Qiou Wei, Glenn Hegamyer, Shakir Saud, Elaine LanzaLIFE Study, Terryl J. Hartman, Pennsylvania State, Zhiying ZhangRobb Chapkin, Texas A & MObese mice, Marcie Bennink, Michigan State University, Kati Barrett Division of Cancer Prevention, John Milner, Young Kim, Gerd Bobe, Prevention Fellow, Roycelynn Mentor-Marcel, Prevention Fellow Statistician Paul Albert, NCISmall Animal Imaging Program, Pete Choyke, Marcelino Bernardo, Lilia Ileva, Joe Kalen, Lisa RIffle

  45. AP-1 and NF-kB Matthew Young, Arindam Dhar, Jing Hu, Connie Matthews, Moon-IL Kang, Brett Hollingshead, Qiou Wei, Gerd Bobe,Roycelynn Mentor-Marcel Jim McMahon, MTDP NCI; Curt Henrich, MTDP, Powel Brown, Baylor Univ; Peter Choyke and SAIP, NCI; Elaine Lanza, Cytonix; Terry Hartman, PSU; Rob Chapkin, TX A&M; Gary Stoner, OHU; Michel Toledano, IBITECS, FrancePdcd4Hsin-Sheng Yang, Joan Cmarik, Aaron Jansen, Halina ZakowiczArti Santhanam, Tobias Schmid, Brett Hollingshead, Noriko Yoshikawa, Nahum Sonenberg, McGill Univ.; Myung Cho, Seoul Nat Univ; Alex Wlodawer, Nicole LaRonde, NCI; Michele Pagano, NYU; Heike Allgayer, Klinikum Mannheim; Bruce Shapiro, NCI

  46. Laboratory of Cancer Prevention LCP 2009

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