Key points about expression profile intrinsic subtypes. Analytically robust expression profiles from FFPE sections using Nanostring technology

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1 Analytically robust expression profiles from FFPE sections using Nanostring technology Torsten O. Nielsen, MD/PhD, FRCPC Professor of Pathology and Laboratory Medicine University of British Columbia, Vancouver, Canada COI statement: Dr. Nielsen is a coinventor of the PAM50 test, which has been licensed to Nanostring 1 Outline of Presentation 1) Intrinsic molecular subtypes of breast cancer 2) Subtyping by immunohistochemistry 3) Subtyping by qrt PCR 4) Nanostring techology 5) Development for clinical use classification of breast cancer using gene expression profile microarrays Modified from Perou, 2010, Cold Spring Harb Perspect Biol. DOI: /cshperspect.a Key points about expression profile intrinsic subtypes Unsupervised biological signature: genes selected because they discriminate intrinsic patterns, not clinical outcome categories Breast cancers more clearly segregate this way than other common carcinomas Patterns hold up on multiple platforms and independent investigators Outcome-based Classifiers: Oncotype Recurrence Score Mammaprint Endopredict Breast Cancer Index Biology-based Classifers: Microarray-based Intrinsic subtyping Stromal signatures Genomic Grade Index NextGen Sequencing Based Aparicio integrated groups 1

2 The Major Intrinsic Biological Subtypes HER2E Breast Cancer Estrogen Response genes: ESR1, PGR, GATA3, FOXA1 Proliferation genes: MKI67, CCNB1, CENPF, FOXA1, MYBL2, ORC6L HER2 associated: ERBB2, GRB7 Basal like markers: KRT5, KRT17, ERBB1, TRIM29, CRYAB Lum A Lum B HER2E Basal / % of cases are HER2E well-studied; identifiable by FISH and IHC (as well as PAM50) very aggressive natural history responds to anthracyclines, taxanes, trastuzumab & new anti-her2 agents ER PR HER2 EGFR CK5/6 Ki67 Luminal A Breast Cancer most common type: ~40-50%. Older pts. express ER-associated proteins, and respond to endocrine therapy antiapoptotic phenotype: BCL2, slow growing, eventually metastasizes (to nodes and bone), good 5- and 10-year outcomes do NOT express proliferation or HER2- associated genes, chemotx may not benefit Luminal B Breast Cancer ~25-35% of cases (depends on study pop n ) includes cases which co-express hormone receptors and HER2, and ER positive cases with high proliferation Disease specific survival hazard ratio ~ 2.0 vs Luminal A may benefit from both hormonal and chemotherapy ER PR HER2 EGFR CK5/6 Ki67 Basal Like Breast Cancer hallmarks do NOT express estrogen receptor nor ER associated genes (including PR, GATA3, BCL2, FOXA1) do NOT express HER2 nor associated genes (e.g. GRB7) Genome-wide Profiling: Problems & Limitations Costs high for equipment Data processing & analysis is complex Needs special tissue handling ER PR HER2 CK5/6 Does not work well on FFPE 2

3 immunohistochemistry Morphology confirms tumor & pattern cf. to diagnostic gold standard tissue from standard handling format for ready application integration into hospital lab testing main format of archival tissue linked to existing outcome data Immediate clinical applicability Subtyping in a clinical setting breast cancer prognosis (DSS) by subtype BCCA 4000 case series, diagnosed >20% + +/ + +/ 13% >13% + LumA LumB intrinsic subtype is also prognostic for local and regional relapses, post lumpectomy and post mastectomy basal TNP non-basal HER2 Lum/HER2 subtype median survival w/ mets (yr) most common site of met Lum A 2.2 bone Lum B 1.6 bone other risk HER2E 0.7 bone brain, liver, lung basal 0.5 lung brain 3

4 Triple Negative Breast Cancer: a heterogenous entity clinical assays of convenience (ER/PR/HER2) are not great at predicting molecular subtype TNBC as defined at local hospitals compared to expression profile Won JR et al., Modern Pathol Survey of Basal Biomarkers 72 biomarkers were drawn from (1) existing markers, (2) review of published literature, and (3) gene expression profile data. (2) (1) existing markers e.g. ER neg PR neg HER2 neg CK5/6 EGFR (3) PRESENTED BY: Maggie Cheang, Aleix Prat, and Chuck Perou INPP4B neg Biomarker Sensitivity Specificity Odds Ratio Neg INPP4B Nestin Neg ER CK c Kit p Fascin etc. Biomarker Sensitivity Specificity Odds Ratio Neg INPP4B Nestin Neg ER CK c Kit p Fascin etc. LIMITATIONS OF IMMUNOHISTOCHEMISTRY Quality control is difficult Semiquantitative at best Limited capacity to subtype accurately (70-80%) 4

5 Expression profiling of FFPE cancer specimens at the RNA level 16 genes (+ 5 controls), derived from published expression profiles fitted for prognosis in ER(+), node (-) Tissue sent to central lab (California) as not FDA approved $4000 / test (but cost effective) PAM50 qpcr panel basal proliferation estrogen HER2 Cohort: ER+, tamoxifen-treated breast cancers from BC: outcomes by PAM50-assigned intrinsic subtype and Risk Of Relapse Relapse Free Survival luminal ESR1 Basal HER2E ERBB2 5

6 predicting tamoxifen benefit in MA.12 Chia SK, Nielsen TO & colleagues Clinical Cancer Research 2012 N = 398 PAM50 Assigns subtype on paraffin blocks Assigns a Risk Of Relapse (ROR) similar to recurrence score Identifies very low risk women: <10% relapse even without chemotherapy Works better than standard clinical grading and immunohistochemistry predicting anthracycline benefit in MA.5 Cheang MC, Nielsen TO & colleagues Clinical Cancer Research 2012 node (+) women, randomized to adjuvant CMF vs. CEF (anthracycline substitution) N = 476 relapse-free survival overall survival predicting benefit of dose-dense chemotx CALGB 9741: N = 1321 node (+); AC/T q2wk vs q3wk HER2E HER2E subtype: CEF is superior basal CMF CEF Luminal and basal: no significant differences Basal: trend to CMF actually being better intrinsic subtype by PAM50 remains prognostic however interaction test by treatment arm is negative: subtype does not predict value of q2wk (dosedense) over q3wk (standard cycles) chemotx Data generation by Nielsen, Perou, Ellis. Data handling by M Liu, W Barry, B Pitcher (Alliance central office) An easy and reliable way to measure RNA on standard pathology (FFPE) tissues: Nanostring ner Analysis System ner Probe Sets Geiss G, Nature Biotechnology 2008; 26: No cdna synthesis, cloning, or amplification, no enzymes Digital readout: 1 count = 1 mrna; detection limit ~2000 molecules; range ng FFPE total RNA can measure > 800 genes Compared to PCR: lower effort, little increased cost with increased numbers of genes Gene specific oligos are bases long: capture has biotin tag, has gene-specific fluorscent bar code One mrna template in specimen = one pairing of capture probe to = one fluorescent bar code signal to count 6

7 ner Assay ner Assay ner Prep Station CodeSet s Reporter s 1. Isolate RNA from FFPE section, and mrna mix with code set Capture & Reporter Probes d mrna Excess Reporters ner Assay ner Assay ner Prep Station ner Prep Station Reporter s Reporter s d Probes to Cartridge 3. Biotin on capture probe binds avidin on slide Surface of cartridge is coated with streptavidin for image collecting and barcode counting 4. Electric current lays down probe-rnas flat in straight lines ner Assay ner Assay ner Digital Analyzer ner Digital Analyzer Reporter s Reporter s Code Gene ESR1 3 ERBB2 1 MKI67 2 Surface Codes are counted and tabulated One coded = 1 mrna 7

8 Procedure of Nanostring RNA assay EGAPP criteria Evaluation of Genomic Applications in Practice and Prevention HE slides reviewed by a pathologist Unstained slides macrodissected to remove non-tumor tissue, and total RNA extracted Hybridization of RNA and et Nanostring assay conducted on 250ng extracted RNA using the NanoString ner Analysis system Analytical Validity: measurement precision, across observers and sites (clinical labs) Clinical Validity: demonstration of independent value for prognosis or prediction on large clinical specimen series Day 1: macrodissection Day 2: RNA isolation Hybridization: overnight Prep station: 2.5 hour Digital analyzer: 4-6 hour Clinical Utility = Analytical Validity + Clinical Validity 44 Nanostring PAM50 assay: analytical reproducibility 43 breast cancer specimens 3 sites / 3 operators / 3 machines % technical success rate 97% subtype concordance Standard deviation of ROR < 2.9 Nanostring PAM50 assay: clinical validity 1. Prognosis in ER positive breast cancer including for late recurrence events, and node (+) cases 2. Predicting value of specific chemotherapy regimens Presented March 2013 at USCAP meeting in Baltimore Nanostring PAM50 test, applied to the ABCSG8 breast cancer clinical trial presented by Gnant & Nielsen at SABCS December 2012 all patients receive 5 yrs hormone tx ABCSG8 (N= 3714) Postmenopausal ER+ women, grade 1 or 2 breast cancer No chemotherapy (Dubsky PC et al., JCO 2012) Distant relapse-free survival Nanostring PAM50 on ABCSG8: results ROR Risk Group Patients (%) Events by 10 years Estimated % with no recurrence at 10 years 498 (34%) % ( ) 478 (32%) % ( ) 502 (34%) % ( ) Total 1,478 (100%) patients re-consented for long term follow-up (or deceased) Median follow up 11 years 1620 blocks collected: 25 (1.5%) insufficient cancer in block on path review 73 (4.5%) insufficient RNA isolated 44 (2.7%) failed QC specs for Nanostring device (i.e. control genes) Overall, 1478 patients (91.2%) were informative for PAM50 yr PAM50 adds prognostic information beyond Clinical Treatment Score in all patients: Likelihood ratio test LR 2 = 54, P < multi-analytical gene-expression test performed on-site in a hospital lab yr 8

9 Nanostring PAM50 test applied to the ATAC breast cancer clinical trial 1007 patients, adjuvant tamoxifen or anastrazole: Dowsett et al., in press PAM50 has much more clinical predictive value than OncotypeDX for likelihood of distant recurrence in ER+, node (-) Also: fewer cases classified as intermediate risk with PAM50 (22%, vs 27% by RS) Long term Aromatase inhibitors Trials including all ER(+) women support long term (>10 yr) use of aromatase inhibitors... due to risk of late relapses Problems: noncompliance, cost, risk of osteoporosis ATAC trial: not prognostic for late relapse = IHC4 test, Oncotype Recurrence Score PAM50 identifies a group of 37% of women who do not need long term AI PAM50 identifies a very low risk group: even when there is nodal involvement! (Gnant M et al. platform presentation ASCO June 2, 2013) (40% of patients) PAM50 identifies a very low risk group: even when there is nodal involvement! (Gnant M et al. platform presentation ASCO June 2, 2013) PAM50 identifies a very low risk group: even when there is nodal involvement! (Gnant M et al. platform presentation ASCO June 2, 2013) (21% of patients) 9

10 Different Assays Track the Same Biology IHC Mamma- Print (array) Oncotype (qrt-pcr) Intrinsic / PAM50 ER+ PR+ HER2- Ki67 low good prog low RS other ER+ ER- HER2+ poor prognosis Triple neg. or basal high Recurrence Score Lum A Lum B HER2 basal (ROR low) (ROR high) good prognosis group: may not need chemotherapy poor prognosis groups: what about prediction? which chemotherapy regimen is best, for which patients? Charlotte L. T. Jørgensen, Torsten O. Nielsen, Karsten D. Bjerre, Shuzhen Liu, Brett Wallden, Eva Balslev, Dorte L. Nielsen and Bent Ejlertsen Gemcitabine in metastatic breast cancer Scandinavian Breast Group 0102: patients with advanced, metastatic breast cancer randomized to standard docetaxel, vs. gemcitabine + (lower dose) docetaxel Nielsen D et al JCO 2011: no clinically meaningful benefit from gemcitabine BUT not analyzed by subtype in vitro data suggests basals are most susceptible to gemcitabine DBCG clinical trial population (N = 337) DBCG translational study population (n = 273) DBCG / PAM50 translational study population (n = 270) PAM50 successful (n = 270) Nanostring PAM50 profiling of SBG0102 FFPE samples not available / unsuitable for PAM50 (n = 64) RNA extraction unsuccessful (n = 3) % 31% Assays run in Vancouver; all statistical analyses prespecified and performed independently at DBCG Primary hypothesis: basal breast cancers will have a better outcome in the gemcitabine arm 36% 17% 16% predicting gemcitabine benefit in SBG0102 Tykjaer-Jorgensen C et al. SABCS 2013 metastatic breast cancer, randomized to docetaxel vs. gemcitabine + docetaxel N = 270, PAM50 by Nanostring trial overall = no significant differences but by subtype basals do much better on gemcitabine effect masked by opposite finding in HER2 still need to validate in a second similar trial, to reach level 1 evidence Active development projects Prediction for anthracycline benefit New breast cancer signatures: predicting responsiveness to radiation therapy Signatures in other cancers: hepatocellular carcinoma (186 genes), medulloblastoma (22 genes) Other Nanostring uses: quantifying mirna, DNA copy number, fusion genes, ChIP assays. Does not detect point mutations. Clinical Meaning Of Intrinsic Subtypes Lum A Lum B HER2 basal hormonal tx trastuzumab prognosis cyclophospha mide, taxanes anthracyclines gemcitabine light blue = shown by IHC, microarray and/or PCR dark blue = confirmed by Nanostring PAM50 10

11 JNCI 101: November 4, 2009 to obtain Level 1 Evidence from archived tissue from completed Phase III trials 1. Validated test with completely predefined classifier 2. Analysis plan prespecified in writing 3. Results of analysis still need to be validated on a second, similar clinical trial dataset Level 1 evidence Lum A Lum B HER2 basal hormonal tx + + (short term) (long term) - - trastuzumab prognosis cyclophospha mide, taxanes anthracyclines gemcitabine Plans: generate Level 1 evidence for the PAM50 assay s Clinical Utility issue completed underway antiestrogen MA.12, ATAC, ABCSG8 anthracyclines MA5 DBCG 89D taxanes GEICAM 9906 CALGB 9344 gemcitabine SBG0102? dose dense chemo CALGB 9741 MA21 need for XRT OCOG/BC DBCG 82C collaborations involve Canadian, US, Danish, Spanish and Austrian clinical trial groups (so far ) PAM50 Nanostring intrisic subtype test: current status Received CE mark for use in Europe Registry studies for FDA approval complete & submitted (decision pending) marketed as Prosigna test Conclusions 1) Molecular intrinsic subtypes have become a fundamental concept in understanding breast cancer biology, diagnosis and treatment 2) Translating from discovery on microarrays into available, valid clinical tests takes >10 years 3) Nanostring based version of test is analytically valid. Tells us who needs therapy (level 1 evidence), & may predict which therapy is best (confirmatory studies on clinical trials pending) acknowledgements COLLABORATING NETWORK Chuck Perou (UNC Chapel Hill) Matthew Ellis (Washington U) Philip Bernard (University of Utah) S. Ferree, J. Storhoff Lois Shepherd (NCICCTG) Mitch Dowsett (UK), M Gnant (Austria) Bent Ejlertsen (Denmark) FUNDING US Nat l Institute of Health CBCF (BC/Yukon); BCRF Michael Smith Foundation for Health Research Nanostring technologies UBC & BCCA Blake Gilks David Huntsman Stephen Chia Karen Gelmon Sam Leung Doris Gao Jennifer Won David Voduc Christine Chow Charlotte Tykjaer Jorgensen (DBCG) Tinne Laurberg (Aarhus) 11