The interaction of lymphoma cells with their microenvironment has an important role in disease pathogenesis and is being actively pursued therapeutically using immunomodulatory drugs, including immune checkpoint inhibitors. Diffuse large B-cell lymphoma (DLBCL) is an aggressive high-grade disease that remains incurable in ~40% of patients treated with R-CHOP immunochemotherapy. The FOXP1 transcription factor is abundantly expressed in such high-risk DLBCL and we recently identified its regulation of immune response signatures, in particular, its suppression of the cell surface expression of major histocompatibility class II (MHC-II), which has a critical role in antigen presentation to T cells. Using CRISPR/Cas9 genome editing we have depleted Foxp1 expression in the aggressive murine A20 lymphoma cell line. When grown in BALB/c mice, this cell line provides a high-fidelity immunocompetent disseminated lymphoma model that displays many characteristics of human DLBCL. Transient Foxp1-depletion using siRNA, and stable depletion using CRISPR (generated by independently targeting Foxp1 exon six or seven) upregulated cell surface I-Ab (MHC-II) expression without impairing cell viability in vitro. RNA sequencing of Foxp1-depleted A20 clones identified commonly deregulated genes, such as the B-cell marker Cd19, and hallmark DLBCL signatures such as MYC-targets and oxidative phosphorylation. Immunocompetent animals bearing Foxp1-depleted A20 lymphomas showed significantly-improved survival, and 20% did not develop tumors; consistent with modulating immune surveillance, this was not observed in immunodeficient NOD SCIDγ mice. The A20 Foxp1 CRISPR model will help to further characterize the contribution of Foxp1 to lymphoma immune evasion and the potential for Foxp1 targeting to synergize with other immunotherapies.
The effectiveness of mental health care can be improved through coordinated and wide-scale outcome measurement. The International Consortium for Health Outcomes Measurement has produced collaborative sets of outcome measures for various mental health conditions, but no universal guideline exists for eating disorders. This Position Paper presents a set of outcomes and measures for eating disorders as determined by 24 international experts from professional and lived experience backgrounds. An adapted Delphi technique was used, and results were assessed through an open review survey. Final recommendations suggest outcomes should be tracked across four domains: eating disorder behaviours and cognitions, physical health, co-occurring mental health conditions, and quality of life and social functioning. Outcomes are collected using three to five patient-reported measures. For children aged between 6 years and 12 years, the measures include the Children's Eating Attitude Test (or, for those with avoidant restrictive food intake disorder, the Eating Disorder in Youth Questionnaire), the KIDSCREEN-10, and the Revised Children's Anxiety and Depression Screener-25. For adolescents aged between 13 years and 17 years, the measures include the Eating Disorder Examination Questionnaire (EDE-Q; or, for avoidant restrictive food intake disorder, the Nine-Item Avoidant Restrictive Food Intake Disorder Screener [NIAS]), the two-item Patient Health Questionnaire (PHQ-2), the nine-item Patient Health Questionnaire (PHQ-9), the two-item Generalised Anxiety Disorder (GAD-2), the seven-item Generalised Anxiety Disorder (GAD-7), and the KIDSCREEN-10. For adults older than 18 years, measures include the EDE-Q (or, for avoidant restrictive food intake disorder, the NIAS), the PHQ-2, the PHQ-9, the GAD-2, the GAD-7, the Clinical Impairment Assessment, and the 12-item WHO Disability Assessment Schedule 2.0. These questionnaires should be supplemented by information on patient characteristics and circumstances (ie, demographic, historical, and clinical factors). International adoption of these guidelines will allow comparison of research and clinical interventions to determine which settings and interventions work best, and for whom.
A combination of genetic and functional approaches has identified three independent breast cancer risk loci at 2q35. A recent fine-scale mapping analysis to refine these associations resulted in 1 (signal 1), 5 (signal 2), and 42 (signal 3) credible causal variants at these loci. We used publicly available in silico DNase I and ChIP-seq data with in vitro reporter gene and CRISPR assays to annotate signals 2 and 3. We identified putative regulatory elements that enhanced cell-type-specific transcription from the IGFBP5 promoter at both signals (30- to 40-fold increased expression by the putative regulatory element at signal 2, 2- to 3-fold by the putative regulatory element at signal 3). We further identified one of the five credible causal variants at signal 2, a 1.4 kb deletion (esv3594306), as the likely causal variant; the deletion allele of this variant was associated with an average additional increase in IGFBP5 expression of 1.3-fold (MCF-7) and 2.2-fold (T-47D). We propose a model in which the deletion allele of esv3594306 juxtaposes two transcription factor binding regions (annotated by estrogen receptor alpha ChIP-seq peaks) to generate a single extended regulatory element. This regulatory element increases cell-type-specific expression of the tumor suppressor gene IGFBP5 and, thereby, reduces risk of estrogen receptor-positive breast cancer (odds ratio = 0.77, 95% CI 0.74-0.81, p = 3.1 × 10-31).
We recently identified a novel susceptibility variant, rs865686, for estrogen-receptor positive breast cancer at 9q31.2. Here, we report a fine-mapping analysis of the 9q31.2 susceptibility locus using 43 160 cases and 42 600 controls of European ancestry ascertained from 52 studies and a further 5795 cases and 6624 controls of Asian ancestry from nine studies. Single nucleotide polymorphism (SNP) rs676256 was most strongly associated with risk in Europeans (odds ratios [OR] = 0.90 [0.88-0.92]; P-value = 1.58 × 10(-25)). This SNP is one of a cluster of highly correlated variants, including rs865686, that spans ∼14.5 kb. We identified two additional independent association signals demarcated by SNPs rs10816625 (OR = 1.12 [1.08-1.17]; P-value = 7.89 × 10(-09)) and rs13294895 (OR = 1.09 [1.06-1.12]; P-value = 2.97 × 10(-11)). SNP rs10816625, but not rs13294895, was also associated with risk of breast cancer in Asian individuals (OR = 1.12 [1.06-1.18]; P-value = 2.77 × 10(-05)). Functional genomic annotation using data derived from breast cancer cell-line models indicates that these SNPs localise to putative enhancer elements that bind known drivers of hormone-dependent breast cancer, including ER-α, FOXA1 and GATA-3. In vitro analyses indicate that rs10816625 and rs13294895 have allele-specific effects on enhancer activity and suggest chromatin interactions with the KLF4 gene locus. These results demonstrate the power of dense genotyping in large studies to identify independent susceptibility variants. Analysis of associations using subjects with different ancestry, combined with bioinformatic and genomic characterisation, can provide strong evidence for the likely causative alleles and their functional basis.