Molecular epidemiology of clonal diploids: a quick overview and a short DIY (do it yourself) notice.

In this short review we report the basic notions needed for understanding the population genetics of clonal diploids. We focus on the consequences of clonality on the distribution of genetic diversity within individuals, between individuals and between populations. We then summarise how to detect clonality in mainly sexual populations, conversely, how to detect sexuality in mainly clonal populations and also how genetic differentiation between populations is affected by clonality in diploids. This information is then used for building recipes on how to analyse and interpret genetic polymorphism data in molecular epidemiology studies of clonal diploids.

Expression of MYC, IgM, As Well As Non-Germinal Centre B-Cell Like Immunophenotype and Positive Immunofish Index Predict a Worse Progression Free Survival and Overall Survival in a Series of 670 De Novo Diffuse Large B-Cell Lymphomas Included in Clinical Trials: A GELA Study of the 2003 Program

Introduction: Diffuse large B-cell lymphomas (DLBCL) represent a heterogeneous disease with variable clinical outcome. Identifying phenotypic biomarkers of tumor cells on paraffin sections that predict different clinical outcome remain an important goal that may also help to better understand the biology of this lymphoma. Differentiating non-germinal centre B-cell-like (non-GCB) from Germinal Centre B-cell-like (GCB) DLBCL according to Hans algorithm has been considered as an important immunohistochemical biomarker with prognostic value among patients treated with R-CHOP although not reproducibly found by all groups. Gene expression studies have also shown that IgM expression might be used as a surrogate for the GCB and ABC subtypes with a strong preferential expression of IgM in ABC DLBCL subtype. ImmunoFISH index based on the differential expression of MUM-1, FOXP1 by immunohistochemistry and on the BCL6 rearrangement by FISH has been previously reported (C Copie-Bergman, J Clin Oncol. 2009;27:5573-9) as prognostic in an homogeneous series of DLBCL treated with R-CHOP. In addition, oncogenic MYC protein overexpression by immunohistochemistry may represent an easy tool to identify the consequences of MYC deregulation in DLBCL. Our aim was to analyse by immunohistochemistry the prognostic relevance of MYC, IgM, GCB/nonGCB subtype and ImmunoFISH index in a large series of de novo DLBCL treated with Rituximab (R)-chemotherapy (anthracyclin based) included in the 2003 program of the Groupe d'Etude des Lymphomes de l'Adulte (GELA) trials. Methods: The 2003 program included patients with de novo CD20+ DLBCL enrolled in 6 different LNH-03 GELA trials (LNH-03-1B, -B, -3B, 39B, -6B, 7B) stratifying patients according to age and age-adjusted IPI. Tumor samples were analyzed by immunohistochemistry using CD10, BCL6, MUM1, FOXP1 (according to Barrans threshold), MYC, IgM antibodies on tissue microarrays and by FISH using BCL6 split signal DNA probes. Considering evaluable Hans score, 670 patients were included in the study with 237 (35.4%) receiving intensive R-ACVBP regimen and 433 (64.6%) R-CHOP/R-mini-CHOP. Results: 304 (45.4%) DLBCL were classified as GCB and 366 (54.6%) as non-GCB according to Hans algorithm. 337/567 cases (59.4%) were positive for the ImmunoFISH index (i.e. two out of the three markers positive: MUM1 protein positive, FOXP1 protein Variable or Strong, BCL6 rearrangement). Immunofish index was preferentially positive in the non-GCB subtype (81.3%) compared to the GCB subtype (31.2%), (p<0.001). IgM was recorded as positive in tumor cells in 351/637 (52.4%) DLBCL cases with a preferential expression in non-GCB 195 (53.3%) vs GCB subtype 100(32.9%), p<0.001). MYC was positive in 170/577 (29.5%) cases with a 40% cut-off and in 44/577 (14.2%) cases with a cut-off of 70%. There was no preferential expression of MYC among GCB or non-GCB subtype (p>0.4) for both cut-offs. Progression-free Survival (PFS) was significantly worse among patients with high IPI score (p<0.0001), IgM positive tumor (p<0.0001), MYC positive tumor with a 40% threshold (p<0.001), ImmunoFISH positive index (p<0.002), non-GCB DLBCL subtype (p<0.0001). Overall Survival (OS) was also significantly worse among patients with high IPI score (p<0.0001), IgM positive tumor (p=0.02), MYC positive tumor with a 40% threshold (p<0.01), ImmunoFISH positive index (p=0.02), non-GCB DLBCL subtype (p<0.0001). All significant parameters were included in a multivariate analysis using Cox Model and in addition to IPI, only the GCB/non-GCB subtype according to Hans algorithm predicted significantly a worse PFS among non-GCB subgroup (HR 1.9 [1.3-2.8] p=0.002) as well as a worse OS (HR 2.0 [1.3-3.2], p=0.003). This strong prognostic value of non-GCB subtyping was confirmed considering only patients treated with R- CHOP for PFS (HR 2.1 [1.4-3.3], p=0.001) and for OS (HR 2.3 [1.3-3.8], p=0.002). Conclusion: Our study on a large series of patients included in trials confirmed the relevance of immunohistochemistry as a useful tool to identify significant prognostic biomarkers for clinical use. We show here that IgM and MYC might be useful prognostic biomarkers. In addition, we confirmed in this series the prognostic value of the ImmunoFISH index. Above all, we fully validated the strong and independent prognostic value of the Hans algorithm, daily used by the pathologists to subtype DLBCL.

FTO genotype is associated with phenotypic variability of body mass index.

There is evidence across several species for genetic control of phenotypic variation of complex traits, such that the variance among phenotypes is genotype dependent. Understanding genetic control of variability is important in evolutionary biology, agricultural selection programmes and human medicine, yet for complex traits, no individual genetic variants associated with variance, as opposed to the mean, have been identified. Here we perform a meta-analysis of genome-wide association studies of phenotypic variation using ∼170,000 samples on height and body mass index (BMI) in human populations. We report evidence that the single nucleotide polymorphism (SNP) rs7202116 at the FTO gene locus, which is known to be associated with obesity (as measured by mean BMI for each rs7202116 genotype), is also associated with phenotypic variability. We show that the results are not due to scale effects or other artefacts, and find no other experiment-wise significant evidence for effects on variability, either at loci other than FTO for BMI or at any locus for height. The difference in variance for BMI among individuals with opposite homozygous genotypes at the FTO locus is approximately 7%, corresponding to a difference of ∼0.5 kilograms in the standard deviation of weight. Our results indicate that genetic variants can be discovered that are associated with variability, and that between-person variability in obesity can partly be explained by the genotype at the FTO locus. The results are consistent with reported FTO by environment interactions for BMI, possibly mediated by DNA methylation. Our BMI results for other SNPs and our height results for all SNPs suggest that most genetic variants, including those that influence mean height or mean BMI, are not associated with phenotypic variance, or that their effects on variability are too small to detect even with samples sizes greater than 100,000.