Page 231 - 2022_01-Haematologica-web

Baseline SUVmax in FL and tumor proliferation
body SUVmax was recorded. The whole-body SUVmax corresponded to the single hottest tumor voxel in the whole-body acquisition. In order to determine TMTV, we performed the calculation based on relative threshold (>41% SUVmax threshold as recommended by the European Association of Nuclear Medicine) using Beth Israel Plugin.14
Data mining and transcriptome analyses
For gene expression analysis, RNA was extracted from the available frozen tumor samples (n=38 of 48). cDNA was prepared from minimum 500 pg RNA per sample and hybridized on GeneChip Human Gene HTA 2.0 Affymetrix microarrays (Affymetrix UK Ltd.), by the Lyon University genomic facility ProfileXpert-LCMT (Lyon, France), were done according to the manufacturer's protocol. Data are available on the NCBI Gene Expression Omnibus website (http://www.ncbi.nlm.nih.gov/geo/): GEO dataset GSE148070. Details of the methods used are presented in the Online Supplementary Methods.
Histopathology and immunohistochemistry studies
Samples fixed in 10% buffered formalin were processed for routine histopathological and immunohistochemical (IHC) exam- ination. The IHC slides were digitalized using Panoramic 250 Flash II digital microscopes (3DHISTECH, Budapest, Hungary). IHC staining was evaluated both via manual scoring and with an automated method using image analysis software (see details in the Online Supplementary Methods).15,16
Mutation profile analysis with next-generation sequencing
After DNA extraction of 51 available FL FFPE (n=33 from train- ing cohort and n=18 from validation cohort), samples were sequenced on an Illumina MiSeqDx using our lymphopanel of 43 genes involved in B-cell lymphomagenesis.17 Sequencing and data analysis was performed as previously described17,18 (see details in the Online Supplemental Methods).
Statistics analysis
PFS was defined as the time from the first cycle of immunochemotherapy to progression or death (event) or last fol- low-up/change of treatment (censored data). POD24 was defined as primary-refractory disease (less than partial response), progres- sion, transformation or relapse within 24 months after diagnosis. OS was defined as the time from the start of therapy to death or last follow-up. All survival rates were estimated using the Kaplan- Meier method, and log-rank test were assessed using R software. Median follow-up was calculated with the Kaplan-Meier reverse method.19 Optimal cutoff to predict PFS was determined using the R ‘Survival’ package20,21 and log-rank test-based P-values. Indeed, the multiple tests performed by this package were corrected using the Benjamini-Hochberg method22 to control the false discovery rate (FDR) and determine the optimal threshold. For comparisons between groups, a normality test followed by a Wilcoxon test or Student’s t-test were performed using R software. The compound linear and nonlinear relationship between Ki-67 percentage and SUVmax level was automatically examined by computing the maxi- mal information coefficient (MIC) with an algorithm running the MINE method.23
Results
Study population
A total of 132 patients were included in the study, with
48 patients in the training cohort and 84 in the validation cohorts. The median age of the whole population was 61.8 years old (range, 28-87 years) (Online Supplementary Table S1). Most patients had advanced clinical stages (84%); 54% had high risk and 34% had intermediate risk FLIPI. FL histological grade was grade 1-2 in 91% of cases. The treat- ments were comparable between groups, with mostly rit- uximab plus CHOP or CHOP-like and rituximab mainte- nance (89%). With a median of follow-up of 43.4 months (interquartile range [IQR] 25.4-65.3 month), ten patients died from progressive disease and three from a second malignancy.
SUVmax at baseline correlates with the risk
of progression in follicular lymphoma patients
The median baseline SUVmax was 9.15 (range, 2.5-34.6; IQR 8.3-13.8) in our series of 132 patients (Online Supplementary Table S2). Baseline SUVmax was related neither to baseline TMTV (Pearson index= 0.35) nor to the largest lymph node size (Pearson index= 0.06). Baseline TMTV was related to the size of the largest mass assessed in 119 patients (Pearson index=0.76). It is worth noting that the SUVmax median of 12 FL grade 3A was not significantly dif- ferent from that of FL grade 1-2. We determined that a SUVmax 14.5 was an accurate threshold (sensitivity of 0.95, specificity of 0.16, false positive rate of 0.59, and precision of 0.85) that was able to distinguish patients with different outcomes. Only 14% of patients (n=19) had SUV >14.5.
max Overall PFS was significantly lower in patients with SUVmax>14.5 than in those with SUVmax≤14.5 (HR= 0.28; P=0.00046), and 2-year PFS was 54% versus 86% (P=0.006). (Figure 1A, left and 1B). On univariate analysis, factors associated with PFS were SUVmax (P=0.0016), FLIPI (P=0.048), elevated lactate dehydrogenase (LDH) (P=0.022), and elevated B2 microglobulin (P=0.038). The type of treatment regimen (R-chemotherapy vs. anti- CD20-lenalidomide) and baseline TMTV had no effect on PFS (Figure 1A, right). In a multivariate Cox model (SUVmax, FLIPI, LDH, B2 microglobulin), SUVmax was the only factor retaining an independent prognostic value for PFS
(HR=0.25; P=0.0066).
Twelve patients (25%) experienced disease progression
within 24 months after the start of therapy. POD24 events were more common in the subset of patients with SUVmax>14.5 (55% of patients with SUVmax>14.5) than in those with SUVmax≤14.5 (15% of patients with SUVmax≤14.5). Median OS was 23.9 months for patients with SUVmax>14.5 and not reached for patients with low SUVmax (HR 0.37; P=0.06).
Baseline SUVmax does not correlate with immune infiltration
In order to investigate whether the immune infiltration signature in baseline biopsies was associated with an increased 18FDG uptake, we compared patients with SUVmax>14.5 and SUVmax≤14.5, and the immune profile deter- mined by immunochemistry (IHC) and transcriptome approaches.
We first measured the sample enrichment score (SES) of both ‘T-cell activation’ and ‘IEGS33’ gene sets in each tran- scriptome from our FL training cohort and from 1,446 NHL and normal lymphoid tissue downloaded from public cohorts available in GEO data set.8,19
The 38 available frozen FL samples from our training cohort and 148 of the 1,446 NHL samples had a high score
haematologica | 2022; 107(1)
223