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Signaling Pathway Biomarkers in Gastrointestinal Malignancies HGF EGFR/EGFR MET HER2/EGFR Gab1 RAS Shp2 Shc Grb2 SOS PI3K/AKT Pathway RAF MEK ERK/ MAPK PI3K/AKT Pathway Personalized Medicine May Help Guide Treatment Planning • In medical practice, clinicians typically prescribe medications according to general information about what might be effective for patients based on product labeling; this trial-and-error approach is in contrast to the goal of personalized medicine1 • From the FDA’s perspective, “personalized medicine promises to increase benefits and reduce risks for patients by improving both the safety and efficacy of medical products” • For any individual patient, the actual safety and effectiveness of a treatment may vary as a result of genetic and environmental factors, as well as the interaction of these factors • Advances in diagnostic tools used to measure or evaluate an indicator of a normal biological process, pathogenic process, or response to a therapeutic intervention may permit clinicians to individualize or personalize treatment for patients by identifying those who may or may not benefit from a particular treatment plan 1,2 Before personalized medicine approach After personalized medicine approach or Genotype Normal gene Mutated gene The top panel illustrates an example in which patients get the same drug, regardless of genotype. The lower panel illustrates a personalized medicine approach in which treatment selection is based on specific patient genotype (eg, presence of mutated gene).1,3 Biomarkers in Gastrointestinal Malignancies That May Have Clinical Utility • Aberrant signal transduction due to a variety of mechanisms drives carcinogenesis by promoting abnormal cell growth, proliferation, invasion, angiogenesis, and disrupting apoptosis4 • Identification of particular molecules or biomarkers (proteins and genes) within specific signaling pathways may provide information that may aid in cancer detection, diagnosis, or may inform or guide treatment plans5 • A biomarker is a characteristic that can be scientifically measured and evaluated to serve as an indicator of a normal or pathogenic biologic process and/or a response to a specific treatment plan1 • Several biomarkers have been identified or are being investigated in various gastrointestinal malignancies6–9 • HER2, EGFR, VEGFR, mTOR, MET, PDGFR, and IGFR are putative biomarkers in esophagogastric adenocarcinoma; while FGF2, VEGF, EGFR, HER2, MET, PI3K, phospho-Akt, and RAS/RAF are potential biomarkers in gastric cancer HER2=human epidermal growth factor receptor 2; EGFR= epidermal growth factor receptor; VEGFR=vascular endothelial growth factor receptor; mTOR=mammalian target of rapamycin; MET=mesenchymal-epithelial transition factor receptor; PDGFR=platelet-derived growth factor receptor; IGFR=insulin-like growth factor receptor; FGF2=fibroblast growth factor-basic; CA 19-9=carbohydrate antigen 19-9; MUC1=mucin 1; SMAD4=mothers against decapentaplegic homolog 4; HENT1= human equilibrative nucleoside transporter 1 • In pancreatic cancer, CA 19-9, a prognostic serum biomarker indicates disease recurrence after surgical resection; MUC1 and mesothelin expression are under investigation as prognostic biomarkers that predict survival, and SMAD4 levels have been reported to be associated with disease progression10 • The mutational status of BRAF, KRAS, NRAS, and PTEN/PI3KCA are under investigation in mCRC11 • The presence of aberrations such as gene amplification or protein overexpression in MET is a negative prognostic indicator in gastric cancer8,9,12 • Other biomarkers, such as c-Kit, a growth factor receptor present in gastrointestinal stromal cell tumors (GIST), have been shown to be a predictive biomarker for response to specific treatment plans13 HGF EGFR/EGFR HER2/EGFR MET Gab1 RAS Shp2 Shc Grb2 SOS RAF PI3K/AKT Pathway MEK ERK/ MAPK PI3K/AKT Pathway Biomarkers in Gastric Cancer • Multiple molecular abnormalities have been identified in gastric carcinomas, resulting in aberrant signaling that promote carcinogenesis7 • Aberrant activation of HER2 or MET stimulates downstream signaling through PI3K/AKT, key proteins in the regulation of genes that affect cell survival and apoptosis, and through the RAS/RAF pathway, which promotes cell growth and proliferation7,14 • HER2 is overexpressed in 12–22% of gastric cancers and in 20–30% of esophageal adenocarcinomas6,14 • While evidence shows that HER2 may act as both a prognostic and predictive biomarker for these malignancies, evidence indicates that HER2 is primarily a predictive biomarker in gastric cancer15 • MET, is a receptor tyrosine kinase, whose ligand is hepatocyte growth factor (HGF)9,16 • In some malignancies, abnormal stimulation of MET promotes transformation, tumor invasion, progression, metastases, and the epithelial-mesenchymal transition that accompanies some tumors • Aberrant signaling through MET can occur as a result of receptor overexpression, upregulated production of HGF, or amplification of the MET gene16 • Mutations in the MET gene can lead to constitutive activation of the receptor and promote proliferation and anti-apoptotic signaling17 • Cross-talk between MET and other receptors, including EGFR, HER2, and HER3, can also lead to constitutive activation of the PI3K/AKT pathway7 • Overexpression of the MET protein and amplification of the MET gene has been observed in 26-74% and 2-23% of gastric cancers, respectively17-25 • Investigators have examined the relationship between aberrant MET and different characteristics of gastric carcinomas such as depth of tumor invasion, lymph node metastasis, stage of disease, and poorer survival • When MET protein expression was assessed by immunohistochemistry (IHC), 14% of samples in one study showed no MET protein expression; immunoreactivity ranged from weak to strong in tumor cells of the remaining tumors; normal gastric mucosa weakly expressed MET protein26 • Aberrant MET can be identified in a majority of esophageal adenocarcinomas, many colorectal adenocarcinomas, and high MET expression may be associated with development of metastases and poorer outcomes13 • Other biomarkers under investigation in upper gastrointestinal malignancies include VEGF, SMO, and mTOR, which have been studied in patients with metastatic gastric cancer16 HGF EGFR/EGFR HER2/EGFR MET Gab1 RAS Shp2 Shc Grb2 SOS RAF PI3K/AKT Pathway MEK ERK/ MAPK PI3K/AKT Pathway Biomarkers in Pancreatic Cancer • Pancreatic cancer is extremely aggressive, and it remains a leading cause of cancer-related deaths worldwide27 • CA 19-9 has long been thought to inform behavior of pancreatic carcinomas • Tumor suppressor genes that have been implicated in the pathogenesis of pancreatic cancer include p53, p21, and SMAD4, and activating mutations in oncogenes including KRAS and cyclin D—these mutations occur in up to 75%, 60%, 55%, 90%, and 82%, of pancreatic cancers respectively • MUC1 and mesothelin expression, as measured by IHC, are prognostic biomarkers in pancreatic cancer that predict survival9 • Furthermore, the molecular markers HENT1, ERCC1, and RRM1 may predict response to a specific antimetabolite therapy • Correlative analysis of blood based biomarkers from patients with advanced pancreatic cancer identified statistically significant prognostic markers for overall survival, including Ang2, CRP, ICAM-1, IGFBP-1, and TSP-2 28 • MUC1 is expressed in >60% of pancreatic adenocarcinomas.29-35 Studies have shown that SMAD4 is inactivated in ≥30% of pancreatic ductal adenocarcinomas. KRAS has been shown to be mutated in ~80% of pancreatic cancers. • Mutations in KRAS are common in pancreatic cancers; these gain-of-function mutations result in inappropriate stimulation through downstream signaling cascades that ultimately promote tumor initiation, progression, proliferation, and invasion36 • In addition, constitutively activated KRAS signaling contributes to up-regulation of other molecules that promote expansion of the desmoplastic stroma characteristic of pancreatic carcinoma • Aberrant signaling through KRAS may also indirectly promote collagen production and further promotes tumor invasion and progression • Reactivation of downstream mediators in pancreatic cancer bypass the EGFR pathway, allowing resistance to develop37 • Such resistance mechanisms include the PI3K/AKT and Hedgehog pathways HGF EGFR/EGFR HER2/EGFR MET Gab1 RAS Shp2 Shc Grb2 SOS RAF PI3K/AKT Pathway MEK ERK/ MAPK PI3K/AKT Pathway Biomarkers in Colorectal Cancer • Chromosomal instability, which involves DNA copy number variation, may provide prognostic information in CRC10 • Recent studies indicate that microsatellite instability, DNA methylation and DNA copy number may be helpful towards selection of an appropriate treatment plan • Multiple signaling pathways have been implicated in the pathogenesis of mCRC38,39 • Aberrant signaling through the RAS/RAF pathway occurs as a consequence of mutations in KRAS, NRAS, or BRAF in mCRC—these aberrations in genes and proteins may impact treatment pans38,40 • Oncogenic mutations in phosphoinositide-3 kinase (PI3K) are present in 12–30% of colorectal cancers42,43 Genetic mutations in chromosomal instability–positive colorectal cancers41 Oncogenes KRAS: Cell proliferation, survival, and transformation CTNNB1: Regulation of Wnt pathway target genes that promote tumor growth and invasion PIK3CA: Cell proliferation and survival Tumor suppressor genes APC: Inhibition of Wingless/Wnt signaling; cytoskeletal regulation TP53: Cell cycle arrest, apoptosis induction SMAD4, SMAD2: Intracellular mediators of the TGF-β pathway DCC: cell surface receptor for netrin-1 • Patients with mCRC having BRAF mutations have been shown to have decreased survival as compared with patients with unmutated BRAF 38,40 • The prevalence of different mutations that affect the RAS/RAF pathway in mCRC patients has been analyzed—overall, mutations in KRAS exon 2 have been observed in ~40% of mCRC44–46 • Other distinct mutations in KRAS, as well as mutations in NRAS, account for another ~10% of patients with mCRC • Taken together, this indicates that mutations in NRAS and KRAS may affect up to 50% of patients with mCRC • Mutations in BRAF affect 8–10% of all mCRC patients, and up to 15% of mCRC patients with unmutated KRAS HGF EGFR/EGFR HER2/EGFR MET Gab1 RAS Shp2 Shc Grb2 SOS RAF PI3K/AKT Pathway MEK ERK/ MAPK PI3K/AKT Pathway Evaluating Biomarkers With Companion Diagnostics May Help Inform Treatment Plan Decisions • Increased understanding of the key molecular pathways in carcinogenesis has resulted in the identification of a variety of biomarkers1,12 • Development of diagnostic tests based on biomarkers may help stratify patients into subpopulations that differ in their susceptibility to a different disease or their response to a specific treatment plan; which may include diet, therapy, and exercise47 • A companion diagnostic (CDx) is an in vitro diagnostic (IVD) device or an imaging tool that provides information that is essential for the safe and effective use of a corresponding therapeutic product 2 • A CDx may identify the patients who are more likely to benefit or have increased risk of serious adverse events from treatment with a particular therapeutic product • Biomarker-based CDx must demonstrate both analytic and clinical validity to achieve regulatory approval, and the robustness of the development process must be ensured and documented 1,2 • Additional investigation must demonstrate the relevance and usefulness of CDx Patient population Diagnostic negative Diagnostic positive Identification of biomarkers and development of diagnostic tests may be used to determine whether certain patients may differ in their responses to specific treatment plans1,2 • IVD, a reagent, instrument, or system intended for use in diagnosis of disease or other conditions, including a determination of the state of health, in order to cure, mitigate, treat, or prevent disease or its sequelae.1 Such products are intended for use in the collection, preparation, and examination of specimens taken from the human body. • Laboratory developed tests are designed, manufactured, and used by a single laboratory • In contrast, IVD kits are generally developed by conventional manufacturers, submitted for FDA review, and if cleared or approved, are sold to labs, hospitals, and/or physicians’ offices, where these kits are used to perform the tests • Deeper sequencing and more extensive mutational analysis (eg, next generation sequencing of multiple genes) is demonstrating the presence of biomarker mutations48 • The FDA recognizes that regulatory oversight of CDx to ensure that tests “provide a reasonable assurance of safety and effectiveness, while also fostering innovation and progress in personalized medicine”1 HGF EGFR/EGFR HER2/EGFR MET Gab1 RAS Shp2 Shc Grb2 SOS RAF PI3K/AKT Pathway MEK ERK/ MAPK PI3K/AKT Pathway Amgen is Committed to Advancing the Science of Personalized Medicine • New information is continuously emerging that refines our understanding of the molecular pathways and biomarkers that drive the carcinogenic process3 • Research to evaluate biomarkers in gastrointestinal malignancies is ongoing • CDx may play a role in predicting likelihood of response, patients unlikely to respond, or individuals at greater risk of adverse effects to a given treatment plan • Integrating biomarkers into routine clinical practice may aid in detection, diagnosis, and treatment planning • Amgen remains committed to the science of personalized medicine and biomarkers HGF EGFR/EGFR HER2/EGFR MET Gab1 RAS Shp2 Shc Grb2 SOS RAF PI3K/AKT Pathway MEK ERK/ MAPK PI3K/AKT Pathway Definitions A biomarker is a characteristic that can be scientifically measured and evaluated to serve as an indicator of a normal biologic process, a disease, or as a response to a therapeutic intervention. Biomarkers are generally measured using either a diagnostic test, IVD test, imaging diagnostic, or other objective measurement method.1 Prognostic markers provide information regarding the natural history of a disease; they are useful in predicting probable clinical outcomes; prognostic enrichment strategies (those with a greater likelihood of having a disease-related endpoint event or a substantial worsening in condition) for example, could be selection of high-risk patients to include in a trial.1,38 Predictive biomarkers provide information regarding the likelihood of response to a particular therapy or patients who may or may not benefit from certain treatments. Thus, a trial employing a predictive enrichment strategy would include patients more likely to respond to a particular intervention or treatment plan.38 A companion diagnostic (CDx) is an IVD device or an imaging tool that provides information that is essential for the safe and effective use of a corresponding therapeutic product.1,2 References 1. U.S. Food and Drug Administration. October 2013. 2. U.S. Food and Drug Administration. 2011. Retrieved from http://www.fda.gov/medicaldevices/ deviceregulationandguidance/guidancedocuments/ ucm262292.htm 3. Walther A, Johnstone E, Swanton C, et al. Nat Rev Cancer. 2009 Jul;9(7):489-499. 25. Lee JH, Han SU, Cho H, et al. Oncogene. 2000;19: 4947–4953. 26. Heideman DA, Snijders PJ, Bloemena E, et al. J Pathol. 2001;194:428-435. 27. Ballehaninna UK, Chamberlain RS. Tumour Biol. 2013 Aug 17. [Epub ahead of print]. 4. Hanahan D, Weinberg RA. Cell. 2011;144:646-674. 28. Nixon AB, Pang H, Starr MD, et al. Clin Cancer Res. 2013. DOI: 10.1158/1078-0432. CCR-13-0926. 5. Bhatt AN, Mathur R, Farooque A, Verma A, et al. Indian J Med Res. 2010;132:129–149. 29. Ho SB, Niehans GA, Lyftogt C, et al. Cancer Res. 1993;53:641-651. 6. Kordes, S, et al. Crit Rev Oncol Hematol. 2013 Oct 12. [Epub ahead of print]. 30. Chhieng DC, Benson E, Eltoum I, et al. Cancer Cytopathol. 2003;99:365-371. 7. Wadwha R, Song S, Lee J-S, et al. Nature Rev Clin Oncol. 2013;10:643–655. 31. Adsay NV, Merati K, Andea A, et al. Mod Pathol. 2002;15:1087-1095. 8. Gomez-Martin C, Plaza JC, Pazo-Cid R, et al. J Clin Oncol. 2013 Oct 14. [Epub ahead of print]. 32. Iacobuzio-Donahue CA, Fu B, Yachida S, et al. J Clin Oncol. 2009;27:1806-1813. 9. Avan, A., Maftouh M, Funel N, et al. Curr Med Chem. 2013 Aug 23. [Epub ahead of print]. 33. Hahn SA, Schutte M, Hoque ATMS, et al. Science. 1996;271:350-353. 10. Fong ZV, Winter JM. Cancer J. 2012;18:530–538. 11. Silvestri A, Pin E, Huijbers A, et al. J Intern Med. 2013;274(1):1–24. 12. Ardekani GS, Jafarnejad SM, Tan L, et al. PLoS One. 2012;7(10): e47054. 13. Tuynman JB, Lagarde SM, Ten Kate FJ, et al. Br J Cancer. 2008 25;98(6):1102–1118. 14. Desai MD, Saroya BS, Lockhart AC. Expert Opin Investig Drugs. 2013;22(3):341–356. 15. Jørgensen JT, Hersom M. J Cancer. 2012;3:137-144. 34. Rozenblum E, Schutte M, Goggins M, et al. Cancer Res. 1997;57:1731-1734. 35. Moore PS, Orlandini S, Zamboni G, et al. Br J Cancer. 2001;84:253-262. 36. Lou E, Subramanian S, Steer CJ. Pancreas. 2013;42:1218-1226. 37. Silvestri N, Gnoni A, Brunetti AE, et al. Curr Med Chem. 2013;21(8):948-965. 38. Moorcraft SY, Smyth EC, Cunningham D. Therap Adv Gastroenterol. 2013;6(5):381–395. 16. Popa EC, Shah MA. Curr Treat Options Oncol. 2013;14(3):321– 336. 39. Wong A, Ma BB. Clin Gastroenterol Hepatol. 2013 Sep 8. [Epub ahead of print]. 17. Janjigian YY, Tang LH, Coit DG, et al. Cancer Epidemiol Biomarkers Prev. 2011;20(5):1021–1027. 40. Neuzillet C, Tijeras-Raballand A, de Mestier L, et al. Pharmacol Ther. 2013 Oct 9. [Epub ahead of print]. 18. Lennerz JK, Kwak EL, Ackerman A, et al. J Clin Oncol. 2011;29(36):4803–4810. 41. Pino MS, Chung DC, et al. Gastroenterology. 2010;138:2059–2072. 19. Drebber U, Baldus SE, Nolden B, et al. Oncol Rep. 2008;19:1477– 1483. 42. Jehan Z, Bavi P, Sultana M, et al. J Pathol. 2009;219:337-346. 20. Nakajima M, Sawada H, Yamada Y, et al. Cancer. 1999;85(9):1894–1902. 44. Data on file. Amgen, Inc. 2014. 21. Taniguchi T, Kitamura M, Arai K, et al. Br J Cancer. 1997;75(5):673–677. 22. Wu CW, Li AF, Chi CW,et al. Oncol Rep. 1998;5(4):817–822. 23. Amemiya H, Kono K, Itakura J, et al. Oncology. 2002;63(3):286– 296. 24. Park WS, Oh RR, Kim YS, et al. Apmis. 2000;108(3): 195–200. 43. Samuels Y, Wang Z, Bardelli A, et al. Science. 2004;304:554. 45. Fearon ER. Annu Rev Pathol Mech Dis. 2011;6:479–507. 46. Vaughn CP, ZoBell SD, Furtado LV, et al. Genes, Chromosomes, and Cancer. 2011;50:301-312. 47. Jones LW, Demark-Wahnefried W. Lancet Oncol. 2006;7(12):1017-1026. 48. Nohaile M. Drug Discov Today. 2011;16(19–20):878–883. Notes Notes This booklet contains forward-looking statements that are based on Amgen’s current expectations and beliefs and are subject to a number of risks, uncertainties, and assumptions that could cause actual results to differ materially from those described. All statements, other than statements of historical fact, are statements that could be deemed forward-looking statements. Forward-looking statements involve significant risks and uncertainties, including those more fully described in the Risk Factors found in the most recent Annual Report on Form 10-K and periodic reports on Form 10-Q and Form 8-K filed by Amgen with the U.S. Securities and Exchange Commission, and actual results may vary materially. Except where otherwise indicated, Amgen is providing this information as of May 15, 2014 and does not undertake any obligation to update any forward-looking statements contained in this booklet as a result of new information, future events, or otherwise. Provided as an educational resource. Do not copy or distribute. ©2014 Amgen Inc. All rights reserved. 79855-R1-V1