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3270 Higher Mutational Burden Is an Independent Predictor of Shorter Time to First Treatment in Untreated Chronic Lymphocytic Leukemia Patients

Program: Oral and Poster Abstracts
Session: 642. Chronic Lymphocytic Leukemia: Clinical and Epidemiological: Poster II
Hematology Disease Topics & Pathways:
Research, Lymphoid Leukemias, Translational Research, CLL, genomics, Diseases, Lymphoid Malignancies, Biological Processes
Sunday, December 10, 2023, 6:00 PM-8:00 PM

Mariia Mikhaleva, MD1,2*, Svitlana Tyekucheva, PhD3,4*, Kiyomi Mashima, MD, PhD1,5, Stacey M Fernandes, BS1*, Matthew S. Davids, MD, MMSc1,5 and Jennifer R. Brown, MD, PhD1,5

1Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA
2Russian Research Institute of Hematology and Transfusiology, Saint-Petersburg, Russia
3Department of Data Science, Dana-Farber Cancer Institute, Boston, MA
4Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA
5Department of Medicine, Harvard Medical School, Boston, MA

Background. Recent advancements in next-generation sequencing (NGS) technologies have revolutionized the ability to comprehensively profile chronic lymphocytic leukemia (CLL), unveiling various molecular lesions. Complex mutational landscapes and diverse combinatorial patterns of genetic alterations lead to heterogeneity of clinical course and outcomes. The primary objective of this study was to identify patterns of co-occurrence (CO) and mutual exclusivity (ME) among mutations in CLL and their impact on time to first treatment (TTFT).

Methods. The cohort included 795 treatment-naïve (TN) patients (pts) with CLL diagnosed according to iwCLL guidelines. The median follow-up time for the cohort was 3.91 years (range 0 – 42.8). The median time from diagnosis to mutational analysis was 6.6 months (26.50 – 33.27, 95% CI). Mutational screening was performed by a clinical targeted NGS panel, covering all or hotspot exons of 95 genes – the Rapid Heme Panel implemented by BWH (Kluk MJ, et al. J Mol Diagn. 2016;18(4):507-515). Standard protocols were applied to analyze IGHV gene mutational status, chromosomal aberrations by FISH with probes for 11q, 13q, 17p, and trisomy 12, and stimulated karyotype, where complex karyotype (CK) was defined as ≥3 abnormalities. CO and ME patterns were analyzed in pts with a higher mutational burden, determined as ≥2 distinct mutated genes, using Fisher’s exact test (p<.05). Control for false discovery rate was performed using the Benjamini, Krieger and Yekutieli method (q=20%). TTFT was the time from diagnosis to initial treatment.

Results. We detected 1798 mutations in 719 (90.4%) pts. No mutations were detected in 9.6% (n=76) patients, while a single mutated gene was found in 216 (27.2%) pts, 2 mutated genes in 206 (25.9%) pts, and mutations in 3 and ≥4 genes were found in 153 (19.2%) and 144 (18.1%) pts, respectively. The most mutated (≥10%) genes in the cohort were ATM (18.1%), NOTCH1 (17.7%), TP53 (13.2%), SF3B1 (12.3%), TET2 (10.2%), and DNMT3A (10.1%).

A higher mutational burden was associated with clinical Rai stages 1-4 [p=.003]; elevated (>3.5 mg/L) levels of baseline ß-2 microglobulin (B2M) [p=.036] and established high-risk genomic features: del(17p) [p<.001], del(11q) [p=.021], CK [p=.009], unfavorable ZAP70 [p=.027] and unmutated IGHV (UM-IGHV) [p<.001] (incidence of UM-IGHV cases is 48.4% (n=359) in cohort). At the same time, cases with 0-1 mutation were more likely to have del(13q) [p=.006]. Sex and age >65 years at diagnosis were not associated with mutational burden.

Otherwise, lack of any mutations was associated with absence of del(17p) (0% vs 11.1% [p=.002]), lower rates of B2M >3.5 mg/L (3.9% vs 21.7% [p<.001]), less frequent UM-IGHV (25.4% vs 50.9% [p<.001]), lower ratio of CK (7.0% vs 17.5% [p=.024] and age >65 years at diagnosis (21.1% vs 35.1% [p=.014]).

After controlling for multiple comparisons, no genes showed significant mutational co-occurrence. UM-IGHV cases were enriched in mutated ATM [p=.003], NOTCH1 [p<.00001], SF3B1 [p=.0012] and XPO1 [p<.00001]. Mutated NOTCH1 [p<.00001], as well as KRAS [p=.0012], occurred along with tri12. In contrast, UM-IGHV did not co-occur with mutations in MYD88 [p<.00001], as previously reported. Del(13q) did not co-occur with mutated BRAF [p=.0006] or BCOR [p=.006]. Mutated TP53 [p=.008] and SF3B1 [p=.0013] were absent in tri12 positive cases.

Increased mutational burden in ≥2 distinct mutated genes predicted a shorter TTFT than 0 or 1 mutated gene (HR 2.16; 95%CI 1.57 – 2.97; p<.001). Factors including Rai stages 1-4 (HR 2.63; 95%CI 1.88 – 3.7; p<0.001), UM-IGHV (HR 2.4; 95%CI 1.74 – 3.3; p<.001), CK (HR 1.47; 95%CI 1.07 – 2.0; p=.018), mutational burden in ≥2 genes (HR 1.57; 95%CI 1.14 – 2.2; p=.006) and del(17p)/TP53mut (HR 1.79; 95%CI 1.15 – 2.8; p=.01) were independently associated with worsened TTFT (Figure 1). Neither mutated TP53 without del(17p) (HR 1.47; 95%CI 0.92 – 2.3; p=.104), or wild-type TP53 with del(17p) (HR 1.03; 95%CI 0.51 – 2.1; p=.932) were significant predictors of TTFT.

Conclusions: Higher mutational burden is associated with worsened TTFT in CLL pts independently of other genomic events. In this cohort we did not see co-occurrence of specific mutations.

Disclosures: Davids: Secura Bio: Consultancy; MEI Pharma: Research Funding; Aptitude Health: Consultancy; Ascentage Pharma: Consultancy, Research Funding; Adaptive Biosciences: Consultancy; BeiGene: Consultancy; Genentech: Consultancy, Research Funding; Janssen: Consultancy; Merck: Consultancy; Mingsight Pharmaceuticals: Consultancy; Surface Oncology: Research Funding; BMS: Consultancy; Curio Science: Consultancy; Eli Lilly: Consultancy; Research to Practice: Consultancy; TG Therapeutics: Consultancy, Research Funding; Takeda: Consultancy; ONO Pharmaceuticals: Consultancy; Novartis: Research Funding; AstraZeneca: Consultancy, Research Funding; AbbVie: Consultancy, Research Funding. Brown: Alloplex Biotherapeutics: Consultancy; Pfizer: Consultancy; Grifols Worldwide Operations: Consultancy; BeiGene: Consultancy, Research Funding; Acerta/AstraZeneca: Consultancy; iOnctura: Consultancy, Research Funding; Kite: Consultancy; Merck: Consultancy; Numab Therapeutics: Consultancy; MEI Pharma: Research Funding; Hutchmed: Consultancy; Loxo/Lilly: Consultancy, Research Funding; Gilead: Research Funding; Genentech/Roche: Consultancy; Pharmacyclics: Consultancy; SecuraBio: Research Funding; TG Therapeutics: Research Funding; Abbvie: Consultancy.

*signifies non-member of ASH