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Challenges for the Pathologist in the era of Personalized Medicine

This article discusses the challenges faced by pathologists in the era of personalized medicine, particularly in the context of cancer treatment. It explores the concept of personalized therapy, diagnostic steps in lung cancer, actionable genetic alterations, and biomarker issues. The article also highlights the complex testing landscape and the multiple methods available for biomarker analysis.

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Challenges for the Pathologist in the era of Personalized Medicine

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  1. Challenges for the Pathologistin the era ofPersonalized Medicine Prof Keith M Kerr Department of Pathology Aberdeen University Medical School Aberdeen, UK

  2. Disclosures Acted as Speaker and/or Consultant for: AstraZeneca, Roche, Boehringer Ingeheim, Bristol-Myers-Squibb, Clovis, Eli Lilly, MSD, Novartis, Pfizer

  3. Personalised approach to treating cancer Understanding the molecular basis of cancer has identified specific drivers and allowed for sub-classification of the disease, revealing the potential for targeted agents ‘ONE SIZE FITS ALL’ PERSONALISED THERAPY Drug Drug X X Y Z • Personalised treatment consists of three essential components : • Oncogenic target that drives cancer growth • Predictive biomarker that detects presence of the target • Well conducted clinical studies that confirm treatment efficacy in the identified patient group

  4. Diagnostic steps in lung cancer Morphological diagnosis of lung cancer Separate SCLC from NSCLC Subtype NSCLC where possible Predictive Immunohistochemistry Only when needed Identification of Actionable genetic alterations

  5. The Challenge: Subtyping non-small cell carcinomas? • Squamous (Cis/Gem) vs Non-squamous (Cis/Pem) cytotoxic chemotherapy • Contraindication of anti-angiogenic therapy for squamous carcinomas • Triage for molecular testing • Simple immunohistochemistry has solved this problem (TTF1, p63, p40, CK5/6) • NSCLC-NOS rate should be <10%

  6. It is worthwhile finding an Actionable genetic alteration in Lung cancer Driver detected – Targeted Rx Kris MG et al. JAMA 2014; 311, 1998-2006

  7. ROS1 fusion genes 1.1-2.6% Adenocarcinomas Fusion correlates with protein (IHC) Sensitive to crizotinib Kerr KM. J Clin Pathol 2013;66:832–838 BRAF mutations 2.5-4% Adenocarcinomas Incl V600E other V600 Smoking vs non-smoking Vemurafenib KRAS mutations 25-35% Adenocarcinomas MEK inhibition? HER2 mutations 1-2% Adenocarcinomas Mutually exclusive of EGFR, KRAS Traztuzamab? • NTRK1 fusion • MPRIP-NTRK1 and CD74-NTRK1 • 3.3% of ‘onco-negative’ adenocarcinomas • Trk inhibitors exist Vaishnavi A et al. Nat Med 2013; 19, 1469-72 • CD74-NRG1 fusion • Search in ‘onco-negative’ adenocarcinomas • ERBB3 and PI3K-AKT pathway activation • Mucinous adenocarcinomas • Potential therapeutic target • Fernandez-Cuesta L et al. Can Disc 2014; jan30 epub RET fusion genes ~1% Adenocarcinomas Vandetanib & others MET upregulation 4% amplification, ~50% overexpression Biomarker issues Failed trials

  8. FGFR1 amplification Biomarker issues Definition of amplification 20% may be overestimate? Ponatinib – FGFR1 inhibitor Wynes MW et al. Clin Cancer Res 2014;20:3299-3309 Clin Can Res 2012;18, 2443-51 Discoid Domain Receptor 2 mutation Prevalence 3.8% Good in vitro target – miRNA & Dasatinib Limited clinical evidence Hammerman PS et al. Cancer Discov 2011 PI3Kinase ~30% amplification ~6% mutations – addictive?? Inhibitors exist IGFR1 Figitumumab Some effect in squamous Toxicity MET Inhibitors exist So far no success EGFR TKI vs MoAb Mutations – rarity (vIII – 8%) Targeting the receptor

  9. Panel of 54 genes with potentially druggable alterations Govindan et al. Cell. 2012 Sep 14;150:1121-34

  10. The Challenge: Lots of targets – Lots of drugs? • Practical reality • EGFR mutation • ALK gene fusion • ‘Nearly routine’? • BRAF mutation • ROS1 gene fusion • Many more potential drugs with biomarkers

  11. Methods of biomarker analysis Change in DNA sequence Change in Gene copy # mRNA transcript Transcription

  12. Methods of biomarker analysis Change in DNA sequence Change in Gene copy # DNA mutational analysis Microarray FISH/CISH mRNA transcript RT-PCR Transcription

  13. Methods of biomarker analysis Change in DNA sequence Change in Gene copy # DNA mutational analysis Next-generation sequencing Microarray FISH/CISH mRNA transcript RT-PCR Transcription

  14. Methods of biomarker analysis Change in DNA sequence Change in Gene copy # DNA mutational analysis Next-generation sequencing Microarray FISH/CISH mRNA transcript RT-PCR Transcription Protein Translation

  15. Methods of biomarker analysis Change in DNA sequence Change in Gene copy # DNA mutational analysis Next-generation sequencing Microarray FISH/CISH mRNA transcript RT-PCR Transcription Immunohistochemistry Protein Translation

  16. Methods of biomarker analysis Change in DNA sequence Change in Gene copy # DNA mutational analysis Next-generation sequencing Microarray FISH/CISH mRNA transcript RT-PCR Transcription Immunohistochemistry Protein Translation Biological Activity Oncogenesis Drug target

  17. The Challenge:Complex testing landscape • Biomarkers at different stages between gene and protein • Complex testing strategy • Multiplex testing offers some solutions • Can be confusing: EGFR • Sometimes unclear which approach is the best • Multiple biomarkers in the same ‘diagnostic space’

  18. Methods of ALK biomarker analysis Change in DNA sequence Change in Gene copy # NGS Break-apart FISH PCR for ALK fusion gene transcripts mRNA transcript Transcription IHC for ALK protein Protein Translation Biological Activity Oncogenesis Drug target

  19. Prognostic and predictive biomarkers are used to guide treatment decisions in oncology Prognostic Predictive Provides information on outcome, independent of the administered therapy Provides information on outcome with regards to a specific therapy Prognostic biomarkers may help define patient’s prognosis, risk of recurrenceor the duration of survival Predictive biomarkers estimate response or survival of a specific patient on a specific therapy and can be a target for therapy Biomarkers for NSCLC ERCC1 Ki67/MIB1 p53 BRAF EGFR KRAS MET PD-L1 ALK HER2 RET ROS1

  20. High levels if PD1 or PDL1 protein expression (IHC) may inhibit Immune response Chen, et al. Clin Cancer Res 2012 Block PD1 or PDL1 Immune damage to tumour

  21. Biomarkers for Immunotherapy? PD-L1 Negative PD-L1 Positive (predictive of response) Less responseMore response 1% 5% 10% 50% cell positive ? Intensity of staining? Immune cell staining? Several therapeutics Several companion diagnostics………… Gandhi L, et al. AACR 2014. Abstract CT105.

  22. PD-L1 as a predictive immune biomarker: assays,sample collection and analysis in NSCLC studies PD-L1Assay Sample Source and Collection Definition of Positivity† †Definition of PD-L1 positivity differs between assay methodologies. 1. Garon EB, et al. Presented at ESMO 2014 (abstr. LBA43); 2. Rizvi NA, et al. Presented at ASCO 2014 (abstr. 8007); 3. Gettinger S et al. Poster p38 presented at ASCO 2014 (abstr. 8024);4. Brahmer JR et al. Poster 293 presented at ASCO 2014 (abstr. 8112^); 5. http://www.clinicaltrials.gov/ct2/show/NCT02041533 Accessed January 2015;6 . Rizvi NA et al. Poster presented at ASCO 2014 (abstr. TPS8123); 7. Soria J-C, et al. ESMO 2014 (abstr. 1322P); 8. Brahmer JR, et al. Poster presented at ASCO 2014 (abstr. 8021^); 9. Segal NH, et al. Presented at ASCO 2014 (abstr. 3002^); 10. Segal NH, et al. ESMO 2014 (abstr. 1058PD). Ab, antibody; IHC, immunohistochemistry

  23. The Challenge: Delivery • Reliable • Accurate • Timely • Relevant • Cost

  24. The Challenge: Delivery • Reliable – will the test work? • Pre-analytics • Formalin fixed-Paraffin embedded tissue (FFPE) • DNA for mutations • DNA quality – fragmentation • Single test – 1.5% complete failure • Multiple tests - ? • FISH <10% • RNA PCR >10% ? • IHC <5%

  25. The Challenge: Delivery • Reliable – will the test work? • Accurate – is the test outcome correct? • False positive tests – contamination • False negative test • DNA quantity • DNA ‘purity’ – how much is from tumour • Enough for multiplex testing? • FISH: 10-20% ALK tests challenged • RNA PCR: ~20% failed in recent ETOP study (ALK) • IHC: antibody specificity, non-specific staining • Biomarker Heterogeneity

  26. The Challenge: Delivery • Reliable – will the test work? • Accurate – is the test outcome correct? • Timely - How quickly do you really need the results? • More tests – more time • More complexity - more time • Communication Patient-Physician-Lab-Physician-Patient

  27. The Challenge: Delivery • Reliable – will the test work? • Accurate – is the test outcome correct? • Timely - How quickly do you really need the results? • Relevant • Are the biomarker tests needed? • Has the lab performed the correct test?

  28. The Challenge: Delivery • Reliable – will the test work? • Accurate – is the test outcome correct? • Timely - How quickly do you really need the results? • Relevant • Cost • Technology is not cheap • Manpower is not cheap • Companion diagnostics are not cheap • Pathology and Therapy: budgets & reimbursement

  29. Challenges for the Pathologistin the era ofPersonalized Medicine • Morphological assessment • Range of Biomarkers • Molecular diversity • Testing complexity • Sample limitations • Service delivery

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