Making Sense of Novel Prognostics: NOTCH1, SF3B1 Jennifer R Brown, MD PhD Director, CLL Center Dana-Farber Cancer Institute October 24, 2014

What is High Risk CLL? Historically defined solely by clinical features: –Stage, lymphocyte doubling time,  2m –Therapy resistance Biologic prognostic factors are increasingly important: IGHV, FISH, somatic mutation profile

Immunoglobulin V H Gene Mutation Years from Diagnosis Blood 94: 1840, 1999 Med Surv 9 yrs Med Surv >24 yrs

Overall Survival by FISH Patients surviving (%) Months 17p- 11q- 12q trisomy Normal 13q deletion as sole abnormality NEJM 2000;343:1910 Del 17p: 32 m Del 11q: 79 m

IGHV Mutation and Cytogenetics: Independent Predictors Blood 100: 1410, 2002

Insights from Sequencing: NOTCH Mutations NOTCH1: recurrent mutation (2 bp deletion; P2515fs) -Fabbri et al: -15.1% overall, assoc with UM IGHV and TP53 disruption -21% in chemorefractory -31% in Richter ’ s transformation -predictor poor OS in MVA -Puente et al: -12.2% overall, assoc with UM IGHV, ZAP70, CD38 -23% in RT; poor OS 21% at 10 yrs Fabbri et al. J Exp Med Jul 4;208(7): Puente et al. Nature Jun 5;475(7354):101-5.

NOTCH Mutations: Short TFS and Higher Risk RT Blood 119: 521, 2012

Mutation Discovery Through Sequencing a Large Initial Sample Set Increases detection of the full range of mutated genes Enables reconstruction of gene pathways underlying disease pathogenesis Reveals associations between genetic events and clinically important disease features NEJM 365:2497, 2011

Sequencing CLL Reveals 9 Significantly Mutated Genes Recently associated Established Novel MAPK1 DDX3X ZMYM3 NOTCH1 FBXW7 ATM MYD88 SF3B1 TP53 Significantly mutated genes # mutations / 91 CLLs NEJM 365:2497, 2011

SF3B1 Mutated in 15% of CLLs SF3B1 chromosome 2 q PP2A repeats R625L N626H K700E (  7) G740E K741N G742D (  2) Q903R aa At the catalytic core of U2 snRNP 14 mutations in 14 CLL patients in a restricted region of the C-terminal domain - K700E was recurrent Mutations in SF3B1 also seen in myelodysplasia Yoshida et al, Nature 2011; Papaemmanuil et al, NEJM 2011

The Significantly Mutated Genes Associate with Known Prognostic Markers P<0.001 P=0.004 P=0.009 P=0.001 del(13q) Trisomy 12 del(11q) del(17p) TP53 SF3B1 MYD88 NOTCH1 FISH Cytogenetic Features Significantly mutated genes IGHV mutational Status 191 MAPK1 FBXW7 ATM DDX3X ZMYM3 RNA processing Notch1 signaling Inflammatory pathway Cell cycle or DNA damage NEJM 365:2497, 2011

SF3B1 Mutation Independently Predicts Poor Prognosis Months from diagnosis to first therapy NEJM 365:2497, 2011

SF3B1 Mutations Confer Poor Prognosis Rossi et al Blood 2011;118:6904-8

BIRC3 Mutation Associated with Poor OS Blood 119:2854

Frequency of CE (%) N=202 cases N=469 samples Median interval between sampling: 62 months Inclusion criteria: >2 years of follow-up >2 sequential samples collected at the following time points: a.Diagnosis b.Progression requiring treatment in progressive cases c.Last follow-up in non-progressive/untreated cases New NOTCH1, SF3B1 and BIRC3 Lesions are Developed During the CLL Clinical Course N=36 18% N=13 6% N=9 4% N=10 5% N=10 5% N=8 4% N=10 5% N=5 2% N=6 3% N=5 2% N=4 2% N=1 0.5% N=0 High risk clonal evolution (TP53, NOTCH1, SF3B1, BIRC3) 24% at 10 years Blood 2013;121(8):1403–1412

16 previously reported CLL drivers Wang et al., NEJM, 2011 Quesada et al., Nat Gen, 2011 Fabbri et al., JEM, 2011 Brown et al., Clin Can Res, 2011 Edelmann et al., Blood Recurrent Drivers in CLL (n=160 Patients) 82/160 WES used in Wang et al. NEJM 2011 * 9 novel putative CLL drivers identified Landau et al Cell 2013

NOTCH1 Mutation Status: High Risk Patient Characteristics

Number affected % of affected samples that are clonal * Higher rate of clonal frequencies, q<0.1 Inferring Earlier and Later Drivers in CLL Landau et al Cell 2013;152:714–726

Biology of High Risk CLL Clinical significance of del17p/TP53 mutation > del11q > UM IGHV is well established Genomic complexity (FISH, karyotype or CN) associates with prognosis and appears quite adverse– but has not been routinely studied –Not analyzed in multivariable analyses Sequencing data suggest SF3B1, NOTCH1 and subclonal driver mutations associate with poor prognosis –Increasing data on TP53, SF3B1 and NOTCH1 in clinical cohorts

Recurrent Mutations Refine Prognosis Balakas et al. Leukemia 2014: 1-8.

Recurrent Mutations Refine Prognosis

Recurrent Mutations Correlated to Cytogenetics Jeromin et al. Leukemia 2014:

Balakas et al. Leukemia 2014: 1-8. Recurrent Mutations Refine Prognosis

del13q14 Normal/+12 NOTCH1 M/SF3B1 M/del11q22-q23 TP53 DIS/BIRC3 DIS del13q14 Normal/+12 NOTCH1 M/SF3B1 M/del11q22-q23 TP53 DIS/BIRC3 DIS OS Treatment Integrated Mutational and Cytogenetic Model for CLL Prognostication N%10-years OS 15526%69% 22839%57% 9917%37% 10117%29% p< N%Treated at 10 years 15526%41% 22839%50% 9917%83% 10117%100% Rossi et al. Blood 2013;121(8):1403

+12 by FISH By Integrating Mutations, ~20% Low Cytogenetic Risk CLL are Reclassified into High Risk Subgroups del13q14 only by FISHNormal by FISH Rossi et al

What About After Therapy?

CLL8 Study Design 817 patients with untreated, active CLL and good physical fitness (CIRS ≤ 6, creatinine clearance ≥ 70 mL/min) R FCR FC 6 courses Follow up C1C2C3C4C5C6 Median observation time 5.9 years Demographics similar between two treatment arms Hallek M, et al: Lancet. 376:1164, 2010

CLL8: Addition of Rituximab to FC

CLL8: Addition of Rituximab to Fludarabine and Cyclophosphamide

CLL8: Survival after FCR by FISH 17p deletion Lancet 2010: 376: q 13q-single 11q- Not 17p-/11q-/+12q/13q- 17p-

MDACC: TTF after FCR Based on FISH ( ) Proportion Courtesy of M Keating

MDACC: TTP for FCR Responders by IGHV and 11q Proportion

Incidence of Genetic Lesions CLL8:CLL3X:*CLL2H: # 1st LineHigh-RiskF-refractory (FC vs. FCR)(Allo-SCT)(Alemtuzumab) n=635n=80n=97 TP53 mut NOTCH1 mut SF3B1 mut IGHV UM p q *Dreger et al. abstract 966, Tue 8:45, # Schnaiter et al. abstract 710, Mo 4:45

Cox regression including: FC, FCR, age, sex, stage, ECOG, B-symptoms, WBC, TK, β2MG, 11q-, +12, 13q-, 17p-, IGHV, TP53, NOTCH1, SF3B1 CLL8 Multivariable Analysis: PFS PFS:HR p-value FCR <.001 TK> IGHV UM < q < p <.001 TP53 mut <.001 SF3B1 mut

OS: HR p-value FCR Age>65 y ECOG> ß2MG> TK> IGHV U < p <.001 TP53 mut <.001 CLL8 Multivariable Analysis: OS

CLL8: Impact of TP53 Mutation on OS FCR FC TP53: wild type mutated Therapy:

Cox regression including: FC, FCR, TP53, NOTCH1, SF3B1, and treatment interaction CLL8 Multivariable Analysis: Predictive Factors PFS:HR p-value FCR <.001 TP53 mut <.001 SF3B1 mut NOTCH1 mut Interaction OS: HR p-value FCR TP53 mut <.001 NOTCH1 mut Interaction

CLL8: NOTCH1 as Predictive Marker FCR FC NOTCH1: wild type mutated Therapy:

Mutation Frequency in Fludarabine Refractory CLL Rossi et al. Blood 2013;121:1403

TP53, SF3B1, and NOTCH1 Mutations and Outcome of Allotransplantation Dreger et al. Blood 2013: 121 (16);

Summary SF3B1 mutation: associated with 11q deletion, UM IGHV, and shorter TTFT and PFS, ?OS NOTCH1 mutation: associated with trisomy 12, UM IGHV, shorter TTFT and Richter’s transformation –? No benefit of anti-CD20 antibody Genomic complexity is adverse but requires further analysis in large trials

Summary Deletion of 17p or TP53 mutation predict highest risk CLL, followed by 11q deletion (NOTCH1, SF3B1) and Unmutated IGHV –Early data suggest high response but shorter PFS with 17p or 11q deletion even with BCR pathway inhibitors –No good data with BCR inhibitors for NOTCH1, SF3B1 AlloSCT may overcome poor prognosis of these somatic mutations

What is Actionable? 17p / TP53: prognosis; therapy selection (TP53 independent: BCR, ?SCT) 11q: prognosis; FC-based CIT Mutated IGHV (esp trisomy 12): FCR SF3B1, NOTCH1, BIRC3: prognosis

Acknowledgments DFCI Biostatistics Donna Neuberg Lillian Werner Haesook Kim Kristen Stevenson Brown Lab, DFCI Bethany Tesar Stacey Fernandes Sasha Vartanov Reina Improgo Josephine Klitgaard NIH, NHGRI CLL Research Consortium Okonow-Lipton Fund Melton Fund Rosenbach Fund Lymphoma Program, DFCI Arnold S Freedman David C Fisher Ann S LaCasce Eric Jacobsen Philippe Armand Matthew Davids Clinical Research Karen Francoeur Karen Campbell Shannon Milillo Hazel Reynolds Center for Cancer Genome Discovery, DFCI Megan Hanna Laura Macconaill Wu Lab, DFCI Catherine Wu Dan-Avi Landau Lili Wang Youzhong Wan Broad Institute Eric Lander Gaddy Getz Carrie Sougnez Nir Hacohen Stacey Gabriel Mike Lawrence Petar Stojanov Andrey Sivachenko Kristian Cibulskis David Deluca