The BIOLOGY of HIGH RISK CLL Gianluca Gaidano, M.D., Ph.D. Division of Hematology Department of Translational Medicine University of Eastern Piedmont Novara-Italy
Disclosures Roche (Advisory Board) Janssen (Advisory Board) Gilead (Advisory Board) Amgen (Advisory board; research support) Morphosys (Advisory Board) Abbvie (Advisory Board)
Outline • The genetic landscape of CLL • Molecular prognosticators of CLL • Molecular predictors of CLL • Richter syndrome biomarkers • Novel biomarkers
Pathogenesis of CLL Microenvironment Secondary Trasforming Interactions Lesion Lesion Progression Predisposition Initiation Promotion/Accumulation Chemorefractoriness Transformation Polygenic del13q Signaling pathways TP53 IRF4 +12 BCR NOTCH1 IRF8 MYD88 NF-kB SF3B1 MYC TLR BIRC3 Other CD38 ATM VLA-4 integrins MYC NOTCH CDKN2A CXCR4
CLL is genetically heterogeneous and lacks disease defining genetic lesions • One of the tumor with the lowest background mutation load (0.6 per Mb) • No unifying gene mutations • TP53 , NOTCH1 , SF3B1 , ATM mutated in >5% CLL The wordcloud shows the genes that are reported as mutated in CLL by the v77 of the Catalogue of Somatic Mutations in Cancer (COSMIC). The size of the font is proportional to the mutation frequency
NOTCH BCR NF-kB TLR BIRC3 MYD88 NOTCH1 MAPK TRAF3 FBXW7 NFKBIE SPEN RAS BRAF MAP2K1 Cell CDKN2A cycle DNA damage response P TP53 TP53 del13q ( miR15/16 ) ATM P P TP53 BCL2 SF3B RPS15 POT1 Apoptosis Moia et al, 2018
Outline • The genetic landscape of CLL • Molecular prognosticators of CLL • Molecular predictors of CLL • Richter syndrome biomarkers • Novel biomarkers
Genetic-based models of CLL prognosis Cytogenetic model Mutational- cytogenetic model 1.0 Matched general population 13q-Deletion 0.8 Cumulative probability of OS (%) Survival 0.6 Trisomy 12 0.4 N 0.2 del13q 26% Normal/+12 40% NOTCH1 M/ SF3B1 M/del11q 17% (N=325) 0.0 TP53 DIS/ BIRC3 DIS 17% 0 2 4 6 8 10 12 14 Years from diagnosis Months Döhner H, et al. N Engl J Med. 2000 Rossi et al, Blood 2013
CLL-IPI Overall survival (all patients) Variable Adverse factor Coeff. HR Grading TP53 (17p) deleted and/or mutated 1.442 4.2 4 IGHV status Unmutated 0.941 2.6 2 2 B2M, mg/L > 3.5 0.665 2.0 Overall survival Clinical stage Binet B/C or Rai I-IV 0.499 1.6 1 Age > 65 years 0.555 1.7 1 Low 0 – 10 Prognostic Score Risk group Score Patients 5-year OS, N (%) % Intermediate 0 – 1 Low 340 (29) 93.2 Intermediate 2 – 3 High 464 (39) 79.4 3.5 Very high 4 – 6 High 326 (27) 63.6 1.9 7 – 10 Very High 62 (5) 23.3 3.6 Time (months) International CLL-IPI working group. Lancet Oncol 2016
Outline • The genetic landscape of CLL • Molecular prognosticators of CLL • Molecular predictors of CLL • Richter syndrome biomarkers • Novel biomarkers
Clinical applications of predictive and prognostic biomarkers in CLL Predictive biomarkers Prognostic biomarkers Treatment tailoring Patient counseling Frequency of follow-up Identify those apropriate for early intervention trials
Naive Germinal Center Antigen-experienced, M-CLL B-cells B-cells memory B-cells T-cell dependent affinity maturation MBL Ag • Genetic lesions • BCR stimulation • Microenvironmental interactions Ag MBL U-CLL Antigen-experienced B-cells T-cell independent immune response (no somatic hypermutation)
IGHV mutated patients gain the greatest benefit from FCR MDACC Phase II study (N=300) 1 100 CLL8 study vs. FC (N=817) 2 100 75 75 IGHV mutated IGHV mutated, FCR PFS (%) PFS (%) 50 50 IGHV mutated, FC 25 25 IGHV unmutated, FCR IGHV unmutated p<0.0001 p<0.001 IGHV unmutated, FC 0 0 0 2 4 6 8 10 12 14 16 0 2 4 6 8 Time (years) Time (years) Italian retrospective analysis (N=404) 3 100 100 Matched general p=0.227 a population 75 75 Low-risk ( IGHV p<0.0001 a PFS (%) OS (%) mutated) 50 50 Intermediate-risk ( IGHV unmutated 25 25 p<0.0001 a and/or del[11q]) High-risk (del[17p]) 0 0 0 2 4 6 8 10 0 2 4 6 8 10 Time (years) Time (years) a p-value vs. matched general population 1. Thompson PA, et al. Blood 2016; 127:303 – 309. 2. Fischer K, et al. FCR: fludarabine, cyclophosphamide, rituximab; MDACC: MD Anderson Blood 2016; 127:208 – 215. 3. Rossi D et al. Blood 2015; 126 1921 – 1924. Cancer Center; OS: overall survival; PFS: progression-free survival
Guideline recommendations for IGHV analysis in clinical practice Recommendation When Not generally iwCLL - indicated BCSH Not recommended - Not generally NCCN - indicated ESMO Desirable Before treatment Hallek et al. Blood. 2008; Oscier et al. Br J Haematol. 2013 Zelenetz et al J Natl Cancer Inst 2015 Eichhorts et al, Ann Oncol 2015.
BCRi are efficacious regardless of IGHV status Analysis of idelalisib-treated patients with Analysis of ibrutinib-treated patients with R/R R/R CLL from Phase III Study 116/117 CLL/SLL from Phase Ib/II Study PCYC-1102/1103 100 100 80 IGHV mutated (n=19) 80 IGHV mutated (n=16) 60 60 PFS (%) PFS (%) 40 40 IGHV unmutated (n=91) IGHV unmutated (n=79) 20 20 0 0 0 2 4 6 8 10 12 14 16 18 20 22 24 26 0 6 12 18 24 30 36 42 48 54 60 66 72 Time (months) Time (months) Sharman JP, et al. ASH 2014, #330; O’Brien S, et al . ASH 2016, #233
Major stereotyped subsets represent distinct CLL variants very aggressive #2 12% major subsets very aggressive #8 #1 high propensity for Richter’s transformation #4 the paradigmatic indolent subset Tobin et al. Blood 2003; Ghiotto et al. J Clin Invest 2004; Stamatopoulos et al. Blood 2007; Chu et al. Blood 2008; Catera et al. Mol Med 2008; Rossi et al. Clin Cancer Res 2009; Sutton et al. Blood 2009; Chu et al. Blood 2010; Marincevic et al. Haematologica 2010; Maura et al. PLosOne 2011; Ntoufa et al. Mol Med 2012; Agathangelidis et al. Blood 2012; Strefford et al. Leukemia 2013; Rossi et al. Blood 2013; Papakonstantinou et al Mol Med 2013; Vardi et al. Clin Cancer Res 2013; Sutton et al. Mol Med 2014; Mansouri et al. J Exp Med 2015 Courtesy of K Stamatopoulos
BcR stereotypy refines prognostication in CLL Distinct clinical outcomes for subsets #1, #2 and #4, Subset #2 is as bad as CLL with TP53 aberrations though essentially devoid of such lesions independently of genomic aberrations or SHM status Baliakas et al. Blood 2015 Baliakas et al. Lancet Haematol. 2014 100% #2, n=212 del(17p), n=284 #4 75% % untreated 50% p=0.5 25% #1 #2 0% 0 5 10 15 20 25 30 Time years Subset #8: the highest risk for Richter’s transformation All express IGHV4-34, all concern IG mutated CLL, amongst all CLL yet the outcome is different Rossi et al. Clin Cancer Res. 2009 Xochelli et al. Clin Cancer Res 2017 Courtesy of K Stamatopoulos
TP53 abnormalities in CLL Missense Nonsense Frameshift M P M P M P M P P P p arm 5’ 3’ p53 EX4 EX9 TP53 DNA BINDING 393 1 q arm del(17p) LOH normal del(17p) p53 wt/mut Chr17 p53 mut p53 wt p53 mut (>80%) (rare) (rare) cdc2 p21 100% TP53 M 90% cyclin B del17p13 80% N=25/38 TP53 M/del17p13 Cell cycle arrest (65.7%) cyclin B P 70% Frequency p53 p21 60% N=44/99 50% (44.4%) Caspase 9 40% BAX P P p53 30% N=30/318 20% N=13/268 (9.4%) N=1/63 (4.8%) 10% (1.5%) 0% MBL Early stage CLL F-refactory Richter DNA damage CLL requiring CLL syndrome Apoptosis treatment Dohner et al, New Engl J Med 2000 ; Rasi et al, Haematologica 2012; Zainuddin et al, Leuk Res 2011; Zenz et al J Clin Oncol 2010;Rossi et al Blood 2011; Rossi et al Blood 2014
TP53 abnormalities in CLL 17p-censored 11q-censored +12q-censored 13q-single- 1.0 censored FC and TP53 WT No aberration- 0.9 censored FC and TP53 mut 0.8 FCR and TP53 WT FCR and TP53 mut 0.7 0.6 0.5 0.4 0.3 17p- on FCR 0.2 0.1 FCR 0.0 0 6 12 18 24 30 36 42 48 0 6 12 18 24 30 36 42 48 54 PFS Months Months Stilgenbaueret al, Blood 2014 Hallek et al, Lancet 2010
Chemoimmunotherapy (CIT) vs novel agents in TP53 disrupted CLL Relapsed/Refractory CLL Response rate PFS CR PR PR-L 100% 100% 80% 79% 83% 79% 72% 78% 80% 12-months PFS 80% Response rate 60% 60% 40% 35% 40% 22% 18% 20% 20% 7% 0% 0% CIT CIT Novel agents Novel agents Badoux Blood 2011; Fisher J Clin Oncol 2011; O’Brien , ASH 2014; Sharman ASH 2014; Byrd ASH 2015; Stilgenbauer, ASH 2015
TP53 disruption is a prognostic biomarker in CLL treated with novel agents Ibrutinib in real-world practice Ibrutinib in trials 1.0 0.8 Proportion With PFS del(17p) 0.6 del(11q) No del(17p) or del(11q) + Censored 0.4 0.2 0 0 6 12 18 24 30 36 42 Months Venetoclax Idelalisib+R Byrd JC, Blood 2015; Thompson PA, Cancer 2015; Winqvist M, Haematologica 2016; Barrientos, ASCO,2015, 7011; Roberts, et al New Engl J Med 2016
Guideline recommendations for TP53 analysis in clinical practice When What iwCLL Before treatment 17p deletion ERIC Before treatment TP53 mutation BCSH Before treatment 17p deletion and TP53 mutation NCCN Before treatment 17p deletion and TP53 mutation ESMO Before treatment 17p deletion and TP53 mutation Hallek et al. Blood. 2008; Oscier et al. Br J Haematol. 2013 Pospisilova et al. Leukemia. 2012 Zelenetz et al J Natl Cancer Inst 2015 Eichhorts et al, Ann Oncol 2015.
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