Follicular lymphoma triggers phenotypic and functional remodeling of the human lymphoid stromal cell landscape.

Lymphoid stromal cells (LSCs) are essential organizers of immune responses. We analyzed tonsillar tissue by combining flow cytometry, in situ imaging, RNA sequencing, and functional assays, defining three distinct human LSC subsets. The integrin CD49a designated perivascular stromal cells exhibiting features of local committed LSC precursors and segregated cytokine and chemokine-producing fibroblastic reticular cells (FRCs) supporting B and T cell survival. The follicular dendritic cell transcriptional profile reflected active responses to B cell and non-B cell stimuli. We therefore examined the effect of B cell stimuli on LSCs in follicular lymphoma (FL). FL B cells interacted primarily with CD49a+ FRCs. Transcriptional analyses revealed LSC reprogramming in situ downstream of the cytokines tumor necrosis factor (TNF) and transforming growth factor ß (TGF-ß), including increased expression of the chemokines CCL19 and CCL21. Our findings define human LSC populations in healthy tissue and reveal bidirectional crosstalk between LSCs and malignant B cells that may present a targetable axis in lymphoma.

Diagnosis of chronic B-cell lymphoproliferative disease in peripheral blood = how machine learning may help to the interpretation of flow cytometry data.

Flow cytometry (FCM) has become a method of choice for immunologic characterization of chronic lymphoproliferative disease (CLPD). To reduce the potential subjectivities of FCM data interpretation, we developed a machine learning random forest algorithm (RF) allowing unsupervised analysis. This assay relies on 16 parameters obtained from our FCM screening panel, routinely used in the exploration of peripheral blood (PB) samples (mean fluorescence intensity values (MFI) of CD19, CD45, CD5, CD20, CD200, CD23, HLA-DR, CD10 in CD19-gated B cells, ratio of kappa/Lambda, and different ratios of MFI B-cells/T-cells [CD20, CD200, CD23]). The RF algorithm was trained and validated on a large cohort of more than 300 annotated different CLPD cases (chronic B-cell leukemia, mantle cell lymphoma, marginal zone lymphoma, follicular lymphoma, splenic red pulp lymphoma, hairy cell leukemia) and non-tumoral selected from PB samples. The RF algorithm was able to differentiate tumoral from non-tumoral B-cells in all cases and to propose a correct CLPD classification in more than 90% of cases. In conclusion the RF algorithm could be proposed as an interesting help to FCM data interpretation allowing a first B-cells CLPD diagnostic hypothesis and/or to guide the management of complementary analysis (additional immunologic markers and genetic).

Genomic landscape of follicular lymphoma across a wide spectrum of clinical behaviors.

While some follicular lymphoma (FL) patients do not require treatment or experience prolonged responses, others relapse early, and little is known about genetic alterations specific to patients with a particular clinical behavior. We selected 56 grade 1-3A FL patients according to their need of treatment or timing of relapse: never treated (n = 7), non-relapsed (19), late relapse (14), early relapse or POD24 (11), and primary refractory (5). We analyzed 56 diagnostic and 12 paired relapse lymphoid tissue biopsies and performed copy number alteration (CNA) analysis and next generation sequencing (NGS). We identified six focal driver losses (1p36.32, 6p21.32, 6q14.1, 6q23.3, 9p21.3, 10q23.33) and 1p36.33 copy-neutral loss of heterozygosity (CN-LOH). By integrating CNA and NGS results, the most frequently altered genes/regions were KMT2D (79%), CREBBP (67%), TNFRSF14 (46%) and BCL2 (40%). Although we found that mutations in PIM1, FOXO1 and TMEM30A were associated with an adverse clinical behavior, definitive conclusions cannot be drawn, due to the small sample size. We identified common precursor cells harboring early oncogenic alterations of the KMT2D, CREBBP, TNFRSF14 and EP300 genes and 16p13.3-p13.2 CN-LOH. Finally, we established the functional consequences of mutations by means of protein modeling (CD79B, PLCG2, PIM1, MCL1 and IRF8). These data expand the knowledge on the genomics behind the heterogeneous FL population and, upon replication in larger cohorts, could contribute to risk stratification and the development of targeted therapies.

Real-life targeted next-generation sequencing for lymphoma diagnosis over 1 year from the French Lymphoma Network.

As the impact of targeted next-generation sequencing (TNGS) on daily diagnosis has not been evaluated, we performed TNGS (46 genes) on lymphomas of unclear subtype following expert haematopathological review. The potential impact on patient care and modifications of final diagnosis were divided into major and minor changes according to the European Society of Medical Oncology (ESMO) guidelines. Among 229 patients [19 primary central nervous system lymphomas (PCNSL), 48 large B-cell lymphomas (LBCLs), 89 small BCLs (SBCLs), seven Hodgkin lymphomas (HL), 66 T-cell lymphomas], the overall concordance rate of histological and TNGS diagnosis was 89·5%. TNGS confirmed the histological diagnosis in 144 cases (62·9%), changed the diagnosis in 24 cases (10·5%) and did not help to clarify diagnosis in 61 cases (26·7%). Modifications to the final diagnosis had a clinical impact on patient care in 8·3% of cases. Diagnostic modifications occurred in all types of lymphoma except in PCNSL and HL; the modification rate was 14·6% in SBCL and 12·5% in LBCL. While comparing informative and uninformative cases, no differences were found in terms of DNA amplification, quality or depth of sequencing and biopsy type. The present study highlights that TNGS may directly contribute to a more accurate diagnosis in difficult-to-diagnose lymphomas, thus improving the clinical management in routine practice.

Adverse outcome in follicular lymphoma is associated with MYC rearrangements but not MYC extra copies.

Follicular lymphomas (FLs) with MYC rearrangements (MYC-R) and extra copies of MYC (MYC-EC) are rare and the prognosis impact is uncertain. We conducted a retrospective study including 321 FL patients, among whom 259 (81%) had no 8q24 alterations and 62 (19%) were assigned to 8qAlt. Forty-five cases were classified as MYC-EC and six as MYC-R. MYC-R patients were significantly older (P = 0·008), had higher follicular lymphoma international prognostic index (FLIPI) stage (P = 0·05) and ß2-microglobulin (ß2m; P = 0·05). Among patients treated with immuno-chemotherapy, four presented a MYC-R and 25 a MYC-EC. Univariate analysis showed the absence of significant difference between MYC-EC and normal MYC (MYC-NL) regarding progression-free survival (PFS; HR1·3; 95% CI [0·4-1·6]) and specific overall survival (SOS; HR 1·6; 95% CI [0·4-5·7]). Those results were compared to data from the PRIMA trial. This confirmed that MYC-EC had no impact on PFS (P = 0·86) or SOS (P = 0·9). Conversely, MYC-R was associated with a trend to inferior outcome regarding PFS (HR : 6·1; 95% CI [2·2-17·1]; P = 0·00026), lymphoma-related death (SOS; HR 13·6; 95% CI [2·9-65]; P = 0·00014) and risk of transformation (transformation-free survival (TFS); HR 82·7; 95% CI [14·8-463·4]; P < 0·0001). In conclusion, MYC-EC has no prognostic impact in FL but MYC-R FL tended to be associated with an increased risk of transformation and poorer outcome.

A gene-expression profiling score for prediction of outcome in patients with follicular lymphoma: a retrospective training and validation analysis in three international cohorts.

BACKGROUND: Patients with follicular lymphoma have heterogeneous outcomes. Predictor models to distinguish, at diagnosis, between patients at high and low risk of progression are needed. The objective of this study was to use gene-expression profiling data to build and validate a predictive model of outcome for patients treated in the rituximab era. METHODS: A training set of fresh-frozen tumour biopsies was prospectively obtained from 160 untreated patients with high-tumour-burden follicular lymphoma enrolled in the phase 3 randomised PRIMA trial, in which rituximab maintenance was evaluated after rituximab plus chemotherapy induction (median follow-up 6·6 years [IQR 6·0-7·0]). RNA of sufficient quality was obtained for 149 of 160 cases, and Affymetrix U133 Plus 2.0 microarrays were used for gene-expression profiling. We did a multivariate Cox regression analysis to identify genes with expression levels associated with progression-free survival independently of maintenance treatment in a subgroup of 134 randomised patients. Expression levels from 95 curated genes were then determined by digital expression profiling (NanoString technology) in 53 formalin-fixed paraffin-embedded samples of the training set to compare the technical reproducibility of expression levels for each gene between technologies. Genes with high correlation (>0·75) were included in an L2-penalised Cox model adjusted on rituximab maintenance to build a predictive score for progression-free survival. The model was validated using NanoString technology to digitally quantify gene expression in 488 formalin-fixed, paraffin-embedded samples from three independent international patient cohorts from the PRIMA trial (n=178; distinct from the training cohort), the University of Iowa/Mayo Clinic Lymphoma SPORE project (n=201), and the Barcelona Hospital Clinic (n=109). All tissue samples consisted of pretreatment diagnostic biopsies and were confirmed as follicular lymphoma grade 1-3a. The patients were all treated with regimens containing rituximab and chemotherapy, possibly followed by either rituximab maintenance or ibritumomab-tiuxetan consolidation. We determined an optimum threshold on the score to predict patients at low risk and high risk of progression. The model, including the multigene score and the threshold, was initially evaluated in the three validation cohorts separately. The sensitivity and specificity of the score for the prediction of the risk of lymphoma progression at 2 years were assessed on the combined validation cohorts. FINDINGS: In the training cohort, the expression levels of 395 genes were associated with a risk of progression. 23 genes reflecting both B-cell biology and tumour microenvironment with correlation coefficients greater than 0·75 between the two technologies and sample types were retained to build a predictive model that identified a population at an increased risk of progression (p<0·0001). In a multivariate Cox model for progression-free survival adjusted on rituximab maintenance treatment and Follicular Lymphoma International Prognostic Index 1 (FLIPI-1) score, this predictor independently predicted progression (adjusted hazard ratio [aHR] of the high-risk group compared with the low-risk group 3·68, 95% CI 2·19-6·17 [p<0·0001]). The 5-year progression-free survival was 26% (95% CI 16-43) in the high-risk group and 73% (64-83) in the low-risk group. The predictor performances were confirmed in each of the individual validation cohorts (aHR comparing high-risk to low-risk groups 2·57 [95% CI 1·65-4·01] in cohort 1; 2·12 [1·32-3·39] in cohort 2; and 2·11 [1·01-4·41] in cohort 3). In the combined validation cohort, the median progression-free survival was 3·1 years (95% CI 2·4-4·8) in the high-risk group and 10·8 years (10·1-not reached) in the low-risk group (p<0·0001). The risk of lymphoma progression at 2 years was 38% (95% CI 29-46) in the high-risk group and 19% (15-24) in the low-risk group. In a multivariate analysis, the score predicted progression-free survival independently of anti-CD20 maintenance treatment and of the FLIPI score (aHR for the combined cohort 2·30, 95% CI 1·72-3·07). INTERPRETATION: We developed and validated a robust 23-gene expression-based predictor of progression-free survival that is applicable to routinely available formalin-fixed, paraffin-embedded tumour biopsies from patients with follicular lymphoma at time of diagnosis. Applying this score could allow individualised therapy for patients according to their risk category. FUNDING: Roche, SIRIC Lyric, LYSARC, National Institutes of Health, the Henry J Predolin Foundation, and the Spanish Plan Nacional de Investigacion.

What Does This Mutation Mean? The Tools and Pitfalls of Variant Interpretation in Lymphoid Malignancies.

High throughput sequencing (HTS) is increasingly important in determining cancer diagnoses, with subsequent prognostic and therapeutic implications. The biology of cancer is becoming increasingly deciphered and it is clear that therapy needs to be individually tailored. Whilst translational research plays an important role in lymphoid malignancies, few guidelines exist to guide biologists and routine laboratories through this constantly evolving field. In this article, we review the challenges of interpreting HTS in lymphoid malignancies and provide a toolkit to interpret single nucleotide variants obtained from HTS. We define the pre-analytical issues such as sequencing DNA obtained from formalin-fixed and paraffin-embedded tissue (FFPE), the acquisition of germline DNA, or the bioinformatic pitfalls, the analytical issues encountered and how to manage them. We describe the main constitutional and cancer databases, their characteristics and limitations, with an emphasis on variant interpretation in lymphoid malignancies. Finally, we discuss the challenges of predictions that one can make using in silico or in vitro modelling, pharmacogenomic screening, and the limits of those prediction tools. This description of the current status in genomic interpretation highlights the need for new large databases and international collaboration in the lymphoma field.

Exome sequencing identifies recurrent BCOR alterations and the absence of KLF2, TNFAIP3 and MYD88 mutations in splenic diffuse red pulp small B-cell lymphoma.

Splenic diffuse red pulp lymphoma is an indolent small B-cell lymphoma recognized as a provisional entity in the World Health Organization 2008 classification. Its precise relationship to other related splenic B-cell lymphomas with frequent leukemic involvement or other lymphoproliferative disorders remains undetermined. We performed whole-exome sequencing to explore the genetic landscape of ten cases of splenic diffuse red pulp lymphoma using paired tumor and normal samples. A selection of 109 somatic mutations was then evaluated in a cohort including 42 samples of splenic diffuse red pulp lymphoma and compared to those identified in 46 samples of splenic marginal zone lymphoma and eight samples of hairy-cell leukemia. Recurrent mutations or losses in BCOR (the gene encoding the BCL6 corepressor) - frameshift (n=3), nonsense (n=2), splicing site (n=1), and copy number loss (n=4) - were identified in 10/42 samples of splenic diffuse red pulp lymphoma (24%), whereas only one frameshift mutation was identified in 46 cases of splenic marginal zone lymphoma (2%). Inversely, KLF2, TNFAIP3 and MYD88, common mutations in splenic marginal zone lymphoma, were rare (one KLF2 mutant in 42 samples; 2%) or absent (TNFAIP3 and MYD88) in splenic diffuse red pulp lymphoma. These findings define an original genetic profile of splenic diffuse red pulp lymphoma and suggest that the mechanisms of pathogenesis of this lymphoma are distinct from those of splenic marginal zone lymphoma and hairy-cell leukemia.

BCL2 mutations do not confer adverse prognosis in follicular lymphoma patients treated with rituximab.

BCL2 mutations have been suggested to confer an adverse prognosis to follicular lymphoma (FL) patients, but their prognostic value has not been assessed in patients treated with a rituximab-containing regimen. Here we evaluated the prognostic value of BCL2 mutations in a large prospective cohort of 252 patients with FL treated with immunochemotherapy in the PRIMA randomized trial. Using a DNA-targeted sequencing approach, we detected amino acid altering mutations in 135 patients (54%) and showed that these mutations were probably mediated by the over-activation of AICDA (activation-induced cytidine deaminase) in the context of the t(14;18) translocation. The BCL2 variants identified in PRIMA patients affected the BH1, BH2, and BH3 functional motifs at a lower frequency than the N-terminus and flexible loop domain, with mostly conservative aminoacid changes. With a median follow-up of 6.7 years, we did not observe any impact of BCL2 mutations either on overall survival or progression-free survival.

Molecular characterization and follow-up of five CML patients with new BCR-ABL1 fusion transcripts.

We report five chronic myeloid leukaemia (CML) patients in whom we identified and characterized undescribed BCR-ABL1 fusion transcripts. We investigated the precise features of the molecular rearrangements and the minimal residual disease follow-up for these five patients. Three resulted from new rearrangements between the BCR and ABL1 sequences (the breakpoints being located within BCR exon 13 in two cases and within BCR exon 18 in one case). The other two cases revealed a complex e8-[ins]-a2 fusion transcript involving a third partner gene, PRDM12 and SPECC1L, respectively. Moreover, single nucleotide polymorphism-array analysis performed in the latter two cases showed copy number alterations shared by the two patients, thus identifying genes that were deleted during rearrangement and suggesting their potential role in CML pathogenesis. Interestingly, we highlight that the prognosis of alterations, such as the presence of an e8a2 transcript or the deletion of various genes, which have been controversial, may be definitively erased by the introduction of tyrosine kinase inhibitors (TKIs).

Manipulating the physical distance between cells during soil colonization reveals the importance of biotic interactions in microbial community assembly.

BACKGROUND: Microbial communities are of tremendous importance for ecosystem functioning and yet we know little about the ecological processes driving the assembly of these communities in the environment. Here, we used an unprecedented experimental approach based on the manipulation of physical distance between neighboring cells during soil colonization to determine the role of bacterial interactions in soil community assembly. We hypothesized that experimentally manipulating the physical distance between bacterial cells will modify the interaction strengths leading to differences in microbial community composition, with increasing distance between neighbors favoring poor competitors. RESULTS: We found significant differences in both bacterial community diversity, composition and co-occurrence networks after soil colonization that were related to physical distancing. We show that reducing distances between cells resulted in a loss of bacterial diversity, with at least 41% of the dominant OTUs being significantly affected by physical distancing. Our results suggest that physical distancing may differentially modulate competitiveness between neighboring species depending on the taxa present in the community. The mixing of communities that assembled at high and low cell densities did not reveal any "home field advantage" during coalescence. This confirms that the observed differences in competitiveness were due to biotic rather than abiotic filtering. CONCLUSIONS: Our study demonstrates that the competitiveness of bacteria strongly depends on cell density and community membership, therefore highlighting the fundamental role of microbial interactions in the assembly of soil communities.

Real life evaluation of AlphaMissense predictions in hematological malignancies.

High-throughput sequencing plays a pivotal role in hematological malignancy diagnostics, but interpreting missense mutations remains challenging. In this study, we used the newly available AlphaMissense database to assess the efficacy of machine learning to predict missense mutation effects and its impact to improve our ability to interpret them. Based on the analysis of 2073 variants from 686 patients analyzed for clinical purpose, we confirmed the very high accuracy of AlphaMissense predictions in a large real-life data set of missense mutations (AUC of ROC curve 0.95), and provided a comprehensive analysis of the discrepancies between AlphaMissense predictions and state of the art clinical interpretation.

Experimental community coalescence sheds light on microbial interactions in soil and restores impaired functions.

BACKGROUND: Microbes typically live in communities where individuals can interact with each other in numerous ways. However, knowledge on the importance of these interactions is limited and derives mainly from studies using a limited number of species grown in coculture. Here, we manipulated soil microbial communities to assess the contribution of interactions between microorganisms for assembly of the soil microbiome. RESULTS: By combining experimental removal (taxa depletion in the community) and coalescence (mixing of manipulated and control communities) approaches, we demonstrated that interactions between microorganisms can play a key role in determining their fitness during soil recolonization. The coalescence approach not only revealed the importance of density-dependent interactions in microbial community assembly but also allowed to restore partly or fully community diversity and soil functions. Microbial community manipulation resulted in shifts in both inorganic nitrogen pools and soil pH, which were related to the proportion of ammonia-oxidizing bacteria. CONCLUSIONS: Our work provides new insights into the understanding of the importance of microbial interactions in soil. Our top-down approach combining removal and coalescence manipulation also allowed linking community structure and ecosystem functions. Furthermore, these results highlight the potential of manipulating microbial communities for the restoration of soil ecosystems. Video Abstract.