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2980 Chromothripsis and Genomic Complexity As Pejorative Prognostic Markers in Pediatric and Adult T-ALL

Program: Oral and Poster Abstracts
Session: 618. Acute Lymphoblastic Leukemias: Biomarkers, Molecular Markers and Minimal Residual Disease in Diagnosis and Prognosis: Poster II
Hematology Disease Topics & Pathways:
Lymphoid Leukemias, ALL, Research, Translational Research, Diseases, Lymphoid Malignancies, Technology and Procedures, molecular testing
Sunday, December 10, 2023, 6:00 PM-8:00 PM

Estelle Balducci1,2*, Mathieu Simonin, MD, PhD1,2*, Nicolas Duployez, PharmD, PhD3,4*, Thomas Steimlé, MD1,2*, Marie-Emilie Dourthe, MD, PhD1,2*, Patrick Villarese, PhD1,2*, Stéphane Ducassou, MD, PhD5*, Isabelle Arnoux, PharmD6*, Jean-Michel Cayuela, PharmD, PhD7*, Marie Balsat, MD8*, Lucien Courtois, PharmD1,2*, Guillaume P Andrieu, PhD1,2*, Aurore Touzart, MD, PhD1,2*, Françoise Huguet, M.D.9*, Arnaud Petit, MD, PhD10*, Norbert Ifrah, MD, PhD11, Hervé Dombret, MD, PhD12, André Baruchel, MD, PhD13,14, Claude Preudhomme, PharmD, PhD3,4*, Nicolas Boissel, MD, PhD12* and Vahid Asnafi, MD, PhD1,2*

1Laboratory of Onco-Hematology, Necker Children's Hospital, Assistance Publique-Hôpitaux de Paris (AP-HP), Paris, France
2INSERM U1151, Institut Necker Enfants Malades (INEM), Paris, France
3INSERM U1277 CANTHER, Univ. Lille, Lille, France
4Laboratory of Hematology, Centre Hospitalier Universitaire (CHU) Lille, Lille, France
5Service d'onco-hématologie pédiatrique, Hôpital Pellegrin Tripode, Bordeaux, France
6Laboratory of Hematology, La Timone University Hospital, Assitance Publique des Hôpitaux de Marseille (AP-HM), Marseille, France
7Laboratory of Hematology and EA 3518 University Hospital Saint-Louis, AP-HP and Université de Paris, Paris, France
8Clinical Hematology Department, Hospices Civils de Lyon, Lyon Sud Hospital, Pierre-Bénite, France, Lyon, France
9Hematology Department, Institut Universitaire du Cancer-Oncopole, CHU de Toulouse, Toulouse, France
10Department of Pediatric Hematology and Oncology, Assistance Publique-Hôpitaux de Paris (AP-HP), GH HUEP, Armand Trousseau Hospital, Paris, France
11PRES LUNAM, CHU Angers Service des Maladies du Sang and INSERM U 892, Angers, France
12Université Paris Diderot, Institut Universitaire d'Hématologie, EA-3518, Assistance Publique-Hôpitaux de Paris, University Hospital Saint-Louis, Paris, France
13Institut Universitaire d'Hématologie, EA-3518, University Hospital Saint-Louis, Assistance Publique des Hôpitaux de Paris (APHP), Paris, France
14Department of Pediatric Hematology and Immunology, University Hospital Robert Debré, Assistance Publique des Hôpitaux de Paris (APHP), Paris, France

Introduction: T-cell acute lymphoblastic leukemia (T-ALL) is an aggressive neoplasm that accounts for 25% and 15% of adult and pediatric ALL, respectively. The prognosis is particularly poor in patients with relapsed disease, justifying the research for novel predictive markers of relapse. To date, a significant series of adult and pediatric T-ALL with analysis using high-resolution SNP-array is still missing.

Methods: Here, we report a comprehensive high-resolution SNP-array profiling in a large well-characterized cohort of 317 T-ALL patients all uniformly treated according to the French FRALLE and GRAALL protocols. SNP-array results have been correlated with clinico-biological data including age range, immunophenotype, oncogenetic and survival data.

Results: The SNP-array analysis detected at least one genomic imbalance (CNVs and UPDs combined) in 304/317 (96%) T-ALL cases with a mean of 6.3 (range 0-47) genomic imbalances per sample. Among genomic imbalances detected by SNP-array analysis, we identified 35 recurrent genomic imbalances (i.e. observed in at least 2% of T-ALL patients). The most common recurrent CNV was the del(9p) including CDKN2A/B at 9p21 (~70%). Unexpectedly, the second more frequent CNV was del(13q) minimally including RB1 and/or DLEU1 at 13q14 (~14%). The third more frequent CNV was the del(6q) minimally encompassing CASP8AP2 at 6q15 (~11%). The following recurrent CNVs were: del(12p) minimally including ETV6 and/or CDKN1B at 12p13 (~9%), del(18p) minimally including PTPN2 at 18p11 (~9%), del(1p) minimally including RPL22 at 1p36 (~9%), del(17q) minimally including NF1/SUZ12 at 17q11 (~8%). Two regions were identified as being recurrently affected by UPDs: 9p21 (CDKN2A/B) (~28%), and 12q14 (SH2B3) (~2%). Chromothripsis was detected in 6 (~2%) cases. The present study revealed relative minor differences in the genomic landscape of T-ALL according to age range consisting primarily of higher incidence of del(1p36)/RPL22, del(13q14)/RB1/DLEU1, del(12p13)/ETV6/CDKN1B, and del(18p11)/PTPN2 and lower incidence of del(9p21) and UPD(9p21)/CDKN2A/B in T-ALL older than 30 years. Comparison of SNP-array results according to immunophenotype and oncogenetic mainly highlighted the specific cytogenetic pattern of the SIL-TAL1 subgroup which exhibited a low genomic complexity with a lower number of genomic imbalances per sample and a lower diversity in genomic imbalances. Using the “survcutpoint” approach, we determined that a cutoff of 15 alterations was the most significant threshold to stratify the patients into a high- and a low-risk group of relapse according to the number of alterations detected with our SNP-array approach. Compared to patients harboring less than 15 alterations (n=296), patients with ≥ 15 genomic imbalances (n=21) had a significantly shorter event-free survival (EFS) and increased cumulative incidence of relapse (CIR) (4y-EFS: 38% vs. 64%; hazard ratio (HR): 2.1, 95%CI (1.2 – 3.7); P=.008, 4y-CIR: 53% vs. 26%; subdistribution hazard ratio (SHR): 2.9, 95%CI (1.5 – 5.4); P=.001) (Figure 1A). Additionally, survival analysis revealed the poor outcome conferred by the presence of chromothripsis (n=6) as well as gain(6q27)/MLLT4 (n=10) and del(16p13)/CREBBP (n=15) despite the low number of affected cases (4y-EFS: 17% vs. 63%; HR: 3.1, 95%CI (1.3 – 7.8); P=.01 and 4y-CIR: 83% vs. 26%; SHR: 5.0, 95%CI (2.2 – 11.3); P <.001 for chromothripsis; 4y-EFS: 30% vs. 63%; HR: 2.5, 95%CI (1.2 – 5.4); P=.002 and 4y-CIR: 57% vs. 27%; SHR: 2.8, 95%CI (0.96 – 8.1); P=.06 for gain (6q27)/MLLT4; 4y-EFS: 40% vs. 63%; HR: 2.5, 95%CI (1.3 – 4.8); P=.005 and CIR in the FRALLE cohort; CIR: 4y-CIR: 50% vs. 21%; SHR: 5.4, 95%CI (1.5 – 20.0); P=.001 for del(16p13)/CREBBP) (Figure 1B).

Conclusion: Our study demonstrated that the whole genome analysis of imbalances provides new insights to refine the risk stratification in T-ALL. Notably, genomic complexity (≥ 15 genomic imbalances) and chromothripis demonstrated an association with an inferior outcome in terms of EFS and CIR in pediatric and adult T-ALL.

Disclosures: Huguet: Amgen: Consultancy, Membership on an entity's Board of Directors or advisory committees; Clinign: Consultancy, Membership on an entity's Board of Directors or advisory committees; Incyte Corporation: Consultancy, Membership on an entity's Board of Directors or advisory committees; Novartis: Consultancy, Membership on an entity's Board of Directors or advisory committees; Pfizer: Consultancy, Membership on an entity's Board of Directors or advisory committees; Servier: Consultancy, Membership on an entity's Board of Directors or advisory committees. Dombret: Jazz Pharmaceuticals: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Pfizer: Research Funding; Servier: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Incyte: Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Support for attending meetings; Astellas: Research Funding. Baruchel: Novartis: Honoraria; Celgene: Honoraria; Servier: Honoraria; Jazz: Honoraria; Astra-Zeneca: Honoraria. Boissel: Astellas Pharma: Honoraria; ARIAD/Incyte: Honoraria; Servier: Consultancy, Honoraria, Other: Advisory role; Novartis: Consultancy, Honoraria, Other: Advisory role, Research Funding; Amgen: Consultancy, Honoraria, Other: Expert Testimony and advisory role, Research Funding.

*signifies non-member of ASH