Diffuse large B-cell lymphoma (DLBCL) patients are treated using relatively homogeneous protocols, irrespective of their biological and clinical variability. Here we have developed a protein-expression-based outcome predictor for DLBCL. Using tissue microarrays (TMAs), we have analyzed the expression of 52 selected molecules in a series of 152 DLBCLs. The study yielded relevant information concerning key biological aspects of this tumor, such as cell-cycle control and apoptosis. A biological predictor was built with a training group of 103 patients, and was validated with a blind set of 49 patients. The predictive model with 8 markers can identify the probability of failure for a given patient with 78% accuracy. After stratifying patients according to the predicted response under the logistic model, 92.3% patients below the 25 percentile were accurately predicted by this biological score as "failure-free" while 96.2% of those above the 75 percentile were correctly predicted as belonging to the "fatal or refractory disease" group. Combining this biological score and the International Prognostic Index (IPI) improves the capacity for predicting failure and survival. This predictor was then validated in the independent group. The protein-expression-based score complements the information obtained from the use of the IPI, allowing patients to be assigned to different risk categories.

Current treatments of sporadic Burkitt's lymphoma (sBL) are associated with severe toxicities. A better understanding of sBL formation would facilitate development of less toxic therapies. The etiology of sBL remains, however, largely unknown, C-MYC up-regulation being the only lesion known to occur in all sBL cases. Several studies examining the role of C-MYC in the pathogenesis of BL have concluded that C-MYC translocation is not the only critical event and that additional unidentified factors are expected to be involved in the formation of this tumor. We herein report that a gene distinct from C-MYC, E2F1, is involved in the formation of all or most sBL tumors. We found that E2F1 is highly expressed in Burkitt's lymphoma cell lines and sBL lymphoma specimens. Our data indicate that its elevated expression is not merely the consequence of the presence of more cycling cells in this tumor relative to other cell lines or to other neoplasias. In fact, we show that reduction of its expression in sBL cells inhibits tumor formation and decreases their proliferation rate. We also provide data suggesting that E2F1 collaborates with C-MYC in sBL formation. E2F1 expression downregulation did not affect, however, the proliferation of human primary diploid fibroblasts. Because E2F1 is not needed for cell proliferation of normal cells, our results reveal E2F1 as a promising therapeutic target for sBL. [Cancer Res 2009;69(9):4052-8]

Critical illness in COVID-19 is an extreme and clinically homogeneous disease phenotype that we have previously shown1 to be highly efficient for discovery of genetic associations2. Despite the advanced stage of illness at presentation, we have shown that host genetics in patients who are critically ill with COVID-19 can identify immunomodulatory therapies with strong beneficial effects in this group3. Here we analyse 24,202 cases of COVID-19 with critical illness comprising a combination of microarray genotype and whole-genome sequencing data from cases of critical illness in the international GenOMICC (11,440 cases) study, combined with other studies recruiting hospitalized patients with a strong focus on severe and critical disease: ISARIC4C (676 cases) and the SCOURGE consortium (5,934 cases). To put these results in the context of existing work, we conduct a meta-analysis of the new GenOMICC genome-wide association study (GWAS) results with previously published data. We find 49 genome-wide significant associations, of which 16 have not been reported previously. To investigate the therapeutic implications of these findings, we infer the structural consequences of protein-coding variants, and combine our GWAS results with gene expression data using a monocyte transcriptome-wide association study (TWAS) model, as well as gene and protein expression using Mendelian randomization. We identify potentially druggable targets in multiple systems, including inflammatory signalling (JAK1), monocyte–macrophage activation and endothelial permeability (PDE4A), immunometabolism (SLC2A5 and AK5), and host factors required for viral entry and replication (TMPRSS2 and RAB2A).

Here we describe the results of a genome-wide study conducted in 11 939 COVID-19 positive cases with an extensive clinical information that were recruited from 34 hospitals across Spain (SCOURGE consortium). In sex-disaggregated genome-wide association studies for COVID-19 hospitalization, genome-wide significance (p < 5x10−8) was crossed for variants in 3p21.31 and 21q22.11 loci only among males (p = 1.3x10−22 and p = 8.1x10−12, respectively), and for variants in 9q21.32 near TLE1 only among females (p = 4.4x10−8). In a second phase, results were combined with an independent Spanish cohort (1598 COVID-19 cases and 1068 population controls), revealing in the overall analysis two novel risk loci in 9p13.3 and 19q13.12, with fine-mapping prioritized variants functionally associated with AQP3 (p = 2.7x10−8) and ARHGAP33 (p = 1.3x10−8), respectively. The meta-analysis of both phases with four European studies stratified by sex from the Host Genetics Initiative confirmed the association of the 3p21.31 and 21q22.11 loci predominantly in males and replicated a recently reported variant in 11p13 (ELF5, p = 4.1x10−8). Six of the COVID-19 HGI discovered loci were replicated and an HGI-based genetic risk score predicted the severity strata in SCOURGE. We also found more SNP-heritability and larger heritability differences by age (<60 or ≥ 60 years) among males than among females. Parallel genome-wide screening of inbreeding depression in SCOURGE also showed an effect of homozygosity in COVID-19 hospitalization and severity and this effect was stronger among older males. In summary, new candidate genes for COVID-19 severity and evidence supporting genetic disparities among sexes are provided.