CLINICAL UTILITY OF INTEGRATED GENOMIC PROFILING IN PEDIATRIC LEUKEMIA
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1 CLINICAL UTILITY OF INTEGRATED GENOMIC PROFILING IN PEDIATRIC LEUKEMIA FUMIN LIN, Ph.D. CANCER GENOMIC DIAGNOSTIC LABORATORY DIVISION OF GENOMIC DIAGNOSTICS 1
2 PEDIATRIC LEUKEMIA Common types of leukemia in children: Acute lymphoblastic leukemia (ALL) Acute myelogenous leukemia (AML) Juvenile myelomonocytic leukemia (JMML) Leukemia is the most common cancer in children: Accounts for one third of pediatric cancer Affects approximately 4,000 children each year in the U.S. Biologically diverse diseases containing various genomic alternations including SNVs, indels, CNVs and gene fusion 2
3 COMPREHENSIVE HEME PANEL AT CHOP Patient samples (blood, bone marrow or FFPE) Heme panel (Agilent): 99 Leukemia-related cancer genes 2 leukemia drug toxicity genes TAT: 3 weeks DNA isolation and Heme panel library construction 1 st and 2 nd review RNA isolation and Fusion panel library construction 1 st and 2 nd review Fusion panel (Archer): 106 major fusion partner genes 586 known fusions and novel ones TAT: 1-3 weeks GC review Director report sign out 3
4 LEUKEMIA CASES SINCE JAN Heme cases: 73% comprehensive, 23% heme only and 4% fusion only Clinically significant variants are identified in 87% of cases result case percentage Tier1/2 (clinically significant) % Tier3 (VOUS) % Tier4 (rare benign) % ALL AML JMML CML others Number Percentage 69.38% 20.00% 3.75% 0.63% 6.25% [CATEG ORY NAME] 9% Tier4 (rare benign) [PERCE NTAGE] Tier1/2 (clinical ly significa nt 87% CML JMML 1% 4% AML 20% others 6% ALL 69% 4
5 RESULTS: SNV&INDEL 178 clinically significant SNVs or Indels (65% positive) 61 genes Gene time Frequency NRAS % KRAS % NOTCH % RUNX % TP % WT % PTPN % CREBBP % FLT % JAK % PAX % MPL % NF % Cancer-related Variant time Frequency NRAS c.38g>a % KRAS c.436g>a % NRAS c.35g>a % JAK2 c.2047a>g % KRAS c.35g>a % KRAS c.35g>c % KRAS c.38g>a % NRAS c.182a>g % NRAS c.37g>c % TP53 c.789_833delinsccct % WHSC1 c.3295g>a % Drug (Mercaptopurine) Toxicity Variant time Frequency TPMT c.719a>g % TPMT c.460g>a % NUDT15 c.415c>t % 5
6 RESULTS: SNV & INDEL ALL: 115 SNV/Indel identified in 38 genes (64% positive; enriched with KRAS, NOTCH1, PAX5 and PTPN11 variants) AML: 59 SNV/Indel identified in 37 genes (75% positive; enriched with RUNX1 variants) NRAS and TP53 are frequently mutated in both. NRAS c.38g>a found in both. ALL Gene time frequency KRAS % NOTCH % NRAS % TP % PAX % CREBBP % PTPN % JAK % Variant time frequency KRAS c.436g>a % NRAS c.35g>a % NRAS c.38g>a % KRAS c.35g>a % KRAS c.38g>a % NRAS c.182a>g % JAK2 c.2047a>g % TP53 c.789_833delinsccct % WHSC1 c.3295g>a % AML Gene time frequency RUNX % ASXL % FLT % NRAS % TP % Variant time frequency NRAS c.38g>a % RUNX1 c.247_248insgga % TERT c.-124c>a % 6
7 >400 clinically significant CNVs reported (67.5% positive) CNV time frequency loss/loh of 9p (CDKN2A/B) % gain of chr % RESULTS: CNV loss/loh of 19p (TCF3) 10% gain of 17q (IKZF3) 10% loss/loh of 17p (TP53) 7% [CATEGORY NAME] 30% loss/loh of 9p (PAX5) % loss/loh of 7p (IKZF1) % loss/loh of 19p (TCF3) % loss/loh of 7p (IKZF1) 11% [CATEGORY NAME] 18% gain of 17q (IKZF3) % loss/loh of 17p (TP53) % loss/loh of 9p (PAX5) 12% 7
8 RESULTS: CNV ALL: 74% positive AML: 69% positive Distinct CNV patterns between ALL and AML ALL CNV present times frequency loss/loh of 9p (CDKN2A/B) % gain of chr % loss/loh of 9p (PAX5) % gain of 17q (IKZF3) % loss/loh of 7p (IKZF1) % loss/loh of 19p (TCF3) % loss/loh of 17p (TP53) % AML CNV present times frequency gain of chr % loss of chr % 8
9 RESULTS: FUSION 25 fusions identified in 43 patients (27% positive) 20 known fusions and 5 novel ones(*) Fusion 5' partner 3' partner time frequency ETV6-RUNX % TCF3-? TCF3 PBX1, HLF % KMT2A-? KMT2A MLLT3, MLLT1, MLLT10, MAML % PAX5-? PAX5 SOX5*, MBNL1*, JAK2, DACH1, AHCYL2* %?-CRLF2 P2RY8, IGH CRLF %?-ABL1 NUP214, BCR ABL % TBL1XR1-PIK3CA % SEC16A-NOTCH % RUNX1-RUNX1T % PML-RARA % NUP98-KDM5A % FUS-ERG % EPOR-IGH % VIM-ALK* % EWSR1-HLF* % 9
10 RESULTS: FUSION ALL: 21 fusions found in 38 cases (34%) AML: 4 fusions found in 5 cases (16%) ALL AML Fusion in ALL 5' partner 3' partner time frequency ETV6-RUNX % TCF3-? TCF3 PBX1, HLF % Fusion in AML time frequency KMT2A-MLLT % NUP98-KDM5A % PAX5-? PAX5 SOX5*, MBNL1*, JAK2, DACH1, AHCYL2* % RUNX1-RUNX1T % KMT2A-? KMT2A MLLT3, MLLT1, MAML %?-CRLF2 P2RY8, IGH CRLF %?-ABL1 NUP214, BCR ABL % PML-RARA % 10
11 IMPACT ON DIAGNOSIS, PROGNOSIS AND THERAPY Change/specify diagnosis Pancytopenia ALL Concern for leukemia JMML Treatment suggestion BCR-ABL1 ALL; CRLF2-, JAK2-, ABL1-associated fusions for Ph-like ALL KRAS, NRAS variants TPMT, NUDT15 SNPs 6-mercaptopurine intolerance Further test suggestion Germline mutation Prognosis prediction masked low-hypodiploid genomic profile POOR PROGNOSIS RUNX1-RUNX1T1 GOOD PROGNOSIS Treatment Change/specify diagnosis Further test suggestion prognosis prediction suggestion case number percentage 6.25% 21.25% 11.88% 39.38% 11
12 CASE EXAMPLE Patient: DGD HR 11 y/0 female Original diagnosis: new leukemia T-ALL? Not a typical T-ALL New diagnosis: leukemia with mixed lineage (T/Myeloid) BM morphology ~50% blasts CD3 T-cell marker positive MPO Myeloid marker dim positive 12
13 CASE EXAMPLE: SNV&INDEL Gene (gene) Transcript cdna (cnomen) Protein(pNomen) Read depth Allele Frequency WT1 NM_ c.1138delinsgg p.arg380glyfs* WT1 NM_ c.1109_1110inst p.val371fs Sanger confirmation c.1138delinsgg c.1109_1110inst 13
14 CASE EXAMPLE: CNV ABL1 amp CDKN2A/B loss cnloh Loss Gain 14
15 CASE EXAMPLE: FUSION NUP214-ABL1 15
16 CASE EXAMPLE: SUMMARY Overall findings support a leukemia of mixed lineage. Biallelic WT1 variants component of myeloid leukemia (poor prognosis) NUP214-ABL1 T-ALL (tyrosine kinase inhibitor/poor prognosis) 16
17 SUMMARY: COMPREHENSIVE HEME PANEL CLINICAL UTILITY We have studied 160 hematological malignancies using the CHOP Comprehensive Heme NGS Panel Clinically significant variants (Tier 1 and Tier 2 ) were found in 87% of cases Genomic profiling played significant part in diagnosis in 6.25% patients, prognosis in 39.38%, and therapeutic decision making in 21.25%. Potential germline/postzygotic mutations leading to cancer predisposition in 11.88% patients. Germline testing and genetic counseling were recommended for these patients 17
18 DGD Cancer Genomic Diagnostics Marilyn M. Li, M.D. Lea Surrey, M.D. Minjie Luo, Ph.D. Gerald Wertheim, M.D. Xiaonan Zhao, Ph.D. Michelle Thiess Junxia Tang, Ph.D. Kieran Pechter, Ph.D. Samuel Baker, Ph.D. Luanne Wainwright Donna Wilmoth Adam Gleason Tammy Grou Heather Krapf Nicole Blake DGD Leadership Robert Doms, M.D. Ph.D. Nancy Spinner, Ph.D. Laughlin Rice Surabhi Mulchandani Zhenming Yu, Ph.D. DGD Bioinformatics Mahdi Sarmady, Ph.D. Kajia Cao, Ph.D. Chao Wu, Ph.D. DGD GC Core Alisha Wilkens Gozde Akgumus Daniel Gallo Other DGD members CHOP Cancer Center and Pathology Dept. Steve Hunger, M.D. John Maris, M.D. Yael Mosse, M.D. Sarah Tasian, M. D. Angela Waanders, M.D. Bruce Pawel, M.D. Mariarita Santi-Vicini, M.D. Jennifer Pogoriler M.D. PhD Suzanne MacFarland M.D. And others Fengqi Chang PhD 18
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