Weigert, Oliver

Abstract With the introduction of large-scale molecular profiling methods and high-throughput sequencing technologies, the genomic features of most lymphoid neoplasms have been characterized at an unprecedented scale. Although the principles for the classification and diagnosis of these disorders, founded on a multidimensional definition of disease entities, have been consolidated over the past 25 years, novel genomic data have markedly enhanced our understanding of lymphomagenesis and enriched the description of disease entities at the molecular level. Yet, the current diagnosis of lymphoid tumors is largely based on morphological assessment and immunophenotyping, with only few entities being defined by genomic criteria. This paper, which accompanies the International Consensus Classification of mature lymphoid neoplasms, will address how established assays and newly developed technologies for molecular testing already complement clinical diagnoses and provide a novel lens on disease classification. More specifically, their contributions to diagnosis refinement, risk stratification, and therapy prediction will be considered for the main categories of lymphoid neoplasms. The potential of whole-genome sequencing, circulating tumor DNA analyses, single-cell analyses, and epigenetic profiling will be discussed because these will likely become important future tools for implementing precision medicine approaches in clinical decision making for patients with lymphoid malignancies.

Abstract Background: Follicular lymphoma (FL) is the second most common nodal lymphoma worldwide and remains incurable for most patients (pts). FL is recognized to be a highly heterogeneous disease and a subset of pts experience remarkable poor outcome. In a recent study, 19-26% of pts receiving first-line R-CHOP experienced progression of disease (POD) within 24 months after diagnosis and had a 5-year (yr) overall survival (OS) of only 34-50%, as compared to a 5-yr OS of 90-94% for pts without POD within 24 months (Casulo et al., J Clin Oncol 2015). Consequently, event-free survival at 12 (EFS12) and 24 months (EFS24) have been suggested as novel surrogate endpoints for poor overall survival in clinical trials and useful for patient counseling (Maurer et al., ASH 2014). We have previously shown that a clinicogenetic risk model (m7-FLIPI) that includes the mutation status of seven genes (EZH2, ARID1A, MEF2B, EP300, FOXO1, CREBBP, and CARD11), the FL International Prognostic Index (FLIPI), and the Eastern Cooperative Oncology Group (ECOG) performance status, improves risk stratification for failure-free survival (FFS) and OS in pts with FL receiving first-line immunochemotherapy (Pastore et al., Lancet Oncology 2015). An online tool is available at: http://www.glsg.de/m7-flipi. It would be advantageous to determine prognosis prior to front-line therapy rather than after POD. Thus, we aimed to investigate the predictive utility of the m7-FLIPI for early POD. Patients and Methods: Clinical and mutation data were available from two independent cohorts: 151 pts who received R-CHOP and IFN maintenance as part of a randomized trial of the German Low-Grade Lymphoma Study Group (GLSG), and 107 pts from a population-based registry of the British Columbia Cancer Agency (BCCA) who received R-CVP. Among the latter, 93 (87%) received R-maintenance by intention to treat. All pts had symptomatic, advanced stage or bulky disease considered ineligible for curative radiotherapy, and a biopsy specimen obtained </=12 months prior to the initiation of first-line therapy. POD was defined as progression, relapse, or death due to any cause. POD12 and POD24 were defined based on POD status at 12 and 24 months after therapy initiation, respectively. Logistic regression analysis was performed to assess if m7-FLIPI was predictive of early POD using the statistical software R (version 3.1.2). Results: In the GLSG cohort, median age was 57 yrs (range 27-77), 51% had high-risk FLIPI, and 5-yr failure-free survival (FFS) and OS rates were 66% and 83%, respectively (median follow-up for OS 7.7 yrs). In the BCCA cohort, median age was higher (62 yrs, 37-83), but high-risk FLIPI was similarly frequent (50%); 5-yr FFS and OS rates were 58% and 74%, respectively (median follow-up for OS 6.7 yrs). A total of 43 GLSG (28%) and 24 BCCA pts (22%) were classified as high-risk by m7-FLIPI, with a 5-yr OS of 65% and 42%, respectively. In the GLSG cohort, 8 (5%) and 29 pts (19%) had POD within 12 and 24 months, respectively, 4 and 10 pts were censored before POD12 and POD24 (table). High-risk m7-FLIPI pts were significantly more likely to experience early POD with an Odds Ratio (OR) of 20.80 (95% confidence interval (CI) 3.53-395.96; p=0.0052) for POD12 and 6.33 (95% CI 2.67-15.69; p<0.0001) for POD24. Likewise, in the BCCA cohort, 16 (15%) and 28 pts (26%) experienced POD12 and POD24, respectively (table). The OR for high-risk m7-FLIPI pts was 4.69 (95% CI 1.52-14.65; p=0.0068) for POD12, and 5.36 (95% CI 2.03-14.60; p=0.0008) for POD24. In the GLSG and BCCA cohorts, the m7-FLIPI had a sensitivity of 88% and 50%, a specificity of 75% and 82%, a positive predictive value (PPV) of 16 and 33%, and a negative predictive value (NPV) of 96% and 90% to predict POD12. For POD24, sensitivity was 62% and 46%, specificity 79% and 86%, PPV 42% and 54%, and NPV 82% and 82%, respectively. Conclusion: We conclude that patients classified as high-risk m7-FLIPI are highly enriched among those with early progression of disease. However, approximately one-half of patients with progression by 24 months after therapy initiation are classified as low-risk m7-FLIPI. Thus, further efforts are needed to refine the m7-FLIPI and thereby capture additional cases that may benefit from innovative first-line approaches. Table. Population m7-FLIPI N POD12 POD24 GLSG Total 151 8/147* 29/141* High-risk 43 7 18 Low-risk 108 1 11 BCCA Total 107 16/107 28/107 High-risk 24 8 13 Low-risk 83 8 15 *Pts censored were removed Disclosures Ansell: Bristol-Myers Squibb: Research Funding; Celldex: Research Funding.

Abstract Although recent advances in molecular genetics have enabled improved risk classification of follicular lymphoma (FL) using, for example, the m7-FLIPI score, the impact on treatment has been limited. We aimed to assess the prognostic significance of copy-number aberrations (CNAs) and copy-neutral loss of heterozygosity (cnLOH) identified by chromosome genomic-array testing (CGAT) at FL diagnosis using prospectively collected clinical trial specimens from 255 patients enrolled in the SWOG study S0016. The impact of genomic aberrations was assessed for early progression (progressed or died within 2 years after registration), progression-free survival (PFS), and overall survival (OS). We showed that increased genomic complexity (ie, the total number of aberration calls) was associated with poor outcome in FL. Certain chromosome arms were critical for clinical outcome. Prognostic CNAs/cnLOH were identified: whereas early progression was correlated with 2p gain (P = .007; odds ratio [OR] = 2.55 [1.29, 5.03]) and 2p cnLOH (P = .005; OR = 10.9 [2.08, 57.2]), 2p gain specifically encompassing VRK2 and FANCL predicted PFS (P = .01; hazard ratio = 1.80 [1.14, 2.68]) as well as OS (P = .005; 2.40 [1.30, 4.40]); CDKN2A/B (9p) deletion correlated with worse PFS (P = .004, 3.50 [1.51, 8.28]); whereas CREBBP (16p) (P &lt; .001; 6.70 [2.52, 17.58]) and TP53 (17p) (P &lt; .001; 3.90 [1.85, 8.31]) deletion predicted worse OS. An independent cohort from the m7-FLIPI study was explored, and the prognostic significance of aberration count, and TP53 and CDKN2A/B deletion were further validated. In conclusion, assessing genomic aberrations at FL diagnosis with CGAT improves risk stratification independent of known clinical parameters, and provides a framework for development of future rational targeted therapies.

Key Points The posttreatment end point progression of FL within 24 months (POD24) is strongly associated with OS. A pretreatment clinicogenetic risk model (m7-FLIPI) predicts POD24 and OS and identifies the smallest subgroup with highest unmet need.