Faculty Bibliography

The identification of molecular subgroups of pediatric B-cell acute lymphocytic leukemia (B-ALL) has proven to be a powerful tool in understanding disease pathogenesis and treatment stratification. Studies have suggested aberrant transcription factor function and epigenetic regulation can explain differences between B-ALL subtypes, however, the impact of 3D genome re-organization remains unclear. Here we used in situ Hi-C and RNA-seq to profile the chromatin architectural landscape in healthy B-cell progenitors and B-ALL patient samples harboring prognostically relevant structural variations, including ETV6::RUNX1, KMT2A::AFF1, and BCR::ABL. We showed that B-ALLs undergo subtype-specific changes that, in part, reflect the differentiation stage of the disease, and that they acquire aberrant chromatin configurations that allow expression of oncogenic drivers. One such driver, ERG, displayed increased interactivity and expression in ETV6::RUNX1 B-ALL, and evidence suggests it plays a role in regulating survival and differentiation. Overall, these results underscore the essential role of 3D nuclear organization in acute leukemia.

Cancer cells activate the integrated stress response (ISR) to adapt to stress and resist therapy¹. ISR signals converge on activating transcription factor 4 (ATF4), which controls cell-intrinsic transcriptional programs that are involved in metabolic adaptation, survival and growth^2,3. However, whether the ISR-ATF4 axis influences anti-tumour immune responses remains mostly unknown. Here we show that loss of ATF4 decreases tumour progression considerably in immunocompetent mice, but not in immunocompromised ones, by enhancing T cell-dependent anti-cancer immune responses. An unbiased genetic screen of ATF4-regulated genes identifies lipocalin 2 (LCN2) as the principal ATF4-dependent effector that impairs anti-tumour immunity by favouring infiltration with immunosuppressive interstitial macrophages. Furthermore, we find that LCN2 promotes T cell exclusion and immune evasion in preclinical mouse models, and correlates with decreased T cell infiltration in patients with lung and pancreatic adenocarcinomas. Anti-LCN2 antibodies promote robust anti-tumour T cell responses in mouse models of aggressive solid tumours. Our study shows that the ATF4-LCN2 axis has a cell-extrinsic role in suppressing anti-cancer immunity, and could pave the way for an immunotherapy approach that targets LCN2.

Disorders affecting the hair follicle (HF) and pilosebaceous unit impose psychosocial and financial burdens on patients and may signal risk for other medical conditions. Human genetic studies help to identify key physiological mechanisms that govern health and are increasingly used to improve drug development. GWASs identify genetic variants that are common in the population and implicate disease mechanisms that are widely shared among patients. In this study, we synthesize knowledge about the biology of the pilosebaceous unit that has been derived from GWASs of hair-related diseases. We identify the key genetic drivers and reveal fundamental biological themes that cut across diseases to identify crucial regulators of HF health.

Inactivation of tumor suppressor genes (TSGs) imparts a cellular fitness in cancers, including in acute myeloid leukemia (AML). The detection of silenced TSGs without direct mutations presents challenges in designing targeted cancer treatments, yet it also opens a therapeutic opportunity to restore their function. In this study, we identified the transcriptional repressor ZBTB7A as a TSG that is down-regulated in samples from patients with AML and is associated with poor survival outcomes. Loss of ZBTB7A amplifies TNF signaling, driving a dysfunctional inflammatory state that accelerates AML progression in vivo. Mechanistically, the mRNA decay factor ZFP36L2 binds to the 3' untranslated region (3'UTR) of ZBTB7A, promoting its transcript degradation in human AML cells. To identify therapeutic targets, we developed a CRISPR-based screening approach coupled with fluorescence in situ hybridization and flow cytometry (FISH-Flow), pinpointing the KDM4 family of histone demethylases as a vulnerability to restore ZBTB7A function. Pharmacologic inhibition of KDM4 up-regulated ZBTB7A expression, promoted terminal differentiation in patient-derived xenograft models, and demonstrated broad antileukemic efficacy across AML subtypes as well as preserved normal hematopoiesis. These findings reveal regulatory mechanisms of ZBTB7A and support epigenetic therapy as a promising strategy to reactivate its tumor suppressor function in hematologic cancers.

Standard techniques for detecting genomic rearrangements in formalin-fixed paraffin-embedded (FFPE) biopsies have important limitations. We performed FFPE-compatible Hi-C on 44 clinical biopsies comprising large B cell lymphomas (n = 18), plasma cell neoplasms (n = 14), and other diverse lymphoid cancers, identifying consistent topological differences between malignant B cell and plasma cell states. Hi-C detected expected oncogene rearrangements at high concordance with fluorescence in situ hybridization (FISH) and supported enhancer hijacking in recurrent rearrangements of BCL2, CCND1, and MYC plus unanticipated variants involving homologous loci. Hi-C identified unanticipated non-coding rearrangements involving PD-1 ligand genes and other loci of potential therapeutic relevance, distinguished between functionally divergent classes of BCL6 rearrangements, and provided topological information supporting interpretation of variant MYC rearrangements. Hi-C revealed disease-selective MYC locus topological features that correlated with disease-selective MYC locus enhancers and rearrangement breakpoint distributions. FFPE-compatible Hi-C detects oncogene rearrangements and their topological consequences at genome-wide scale, finding clinically relevant drivers missed by standard approaches.

Hair traits are nonpathogenic features that vary among individuals. Unlike hair follicle (HF) diseases, which are rare in the population, hair traits can be measured in everyone. This facilitates the construction of large cohorts that are well-powered for gene discovery. GWASs identify genetic variants that are widely shared among people globally, providing knowledge with broad population relevance. We compile findings from hair trait GWASs to deepen our understanding of HF biology. In reviewing genetic factors that influence hair traits, we demonstrate overlap with disease genes, underscoring that genetic studies of traits improve our knowledge about health and disease.

The understanding of the mechanisms that control key features of immune cells in various disease contexts remains limited, and few techniques are available for manipulating immune cells. Thus, discovering novel strategies for regulating immune cells is essential for gaining insight into their roles in health and disease. In this study, we investigated the potential of the recently described Universal Receptive System to regulate human immune cell functions. This was achieved for the first time by specifically targeting newly discovered surface-bound DNA- and RNA-based receptors on leukocytes using endonucleases and generating "Leukocyte-Tells." Using this approach, 1,496 genes were upregulated, many of which are related to immune cell signaling, migration, endocytosis, and phagocytosis pathways. The antimicrobial and anticancer activities of Leukocyte-Tells exceeded those of control leukocytes in vitro. Under some conditions, such as in antibiofilm experiments against biofilms of Staphylococcus spp., Pseudomonas spp, Candida spp., and other microorganisms, Leukocyte-Tells showed up to 1,000,000-fold higher activities than did control leukocytes. Additionally, Leukocyte-Tells exhibited significantly higher levels of TNF, IL-1β, IFN-γ, IL-6, and IL-10 production. Our findings reveal, for the first time, that the Universal Receptive System can orchestrate fundamental properties of immune cells, including enhanced antimicrobial and anti-tumor activities. This novel approach offers a new avenue for understanding the biology and regulation of white blood cells. Regulation of leucocyte activity is crucial for a properly functioning immune response and developing novel cell-based therapies. Our previous findings demonstrated the existence of nucleic acid-based receptors (Teazeled receptors, TezRs) that govern the responses of various cell types to a diverse array of environmental factors. Here, we discovered that by modulating these TezRs, we could upregulate immune cell signaling, migration, endocytosis, and phagocytosis pathways in leukocytes. By leveraging TezRs, we generated Leukocyte-Tells, which exhibited significantly higher antimicrobial and anticancer activities than the original immune cells.

UNLABELLED:Deep learning methods for image segmentation and classification in histopathology generally utilize supervised learning, relying on manually created labels for model development. Here, we applied a self-supervised framework to characterize kidney histology without the use of pathologist annotations, training on whole slide images to identify histomorphological phenotype clusters (HPCs) and create slide-level vector representations. HPCs developed in the training set were visually consistent when transferred to five diverse internal and external validation sets (1,421 WSIs in total). Specific HPCs were reproducibly associated with slide-level pathologist quantifications, such as interstitial fibrosis (AUC = 0.83). Additionally, hierarchical clustering of tissue patterns revealed patient groups related to kidney function and genotype, and specific HPCs predicted longitudinal kidney function decline. Overall, we demonstrated the translational application of a self-supervised framework to summarize distinct kidney tissue patterns with phenotypic and prognostic relevance. SUPPLEMENTARY INFORMATION:The online version contains supplementary material available at 10.1038/s41598-025-19193-2.

PURPOSE/UNASSIGNED:Cancer treatment has been revolutionized by immune checkpoint inhibitors (ICI). However, a subset of patients do not respond and/or they experience significant adverse events. Attempts to integrate reliable biomarkers of ICI response as part of standard care have been hampered by limited generalizability. We previously reported our supervised machine learning (ML) model in a retrospective cohort of metastatic melanoma. EXPERIMENTAL DESIGN/UNASSIGNED:In this study, we expanded our testing to include larger cohorts of patients with melanoma accrued at several sites, including patients enrolled in clinical trials in both adjuvant and metastatic settings. We examined pretreatment hematoxylin and eosin slides from 639 patients with stage III/IV melanoma treated with ICIs [anti-cytotoxic T-lymphocyte-associated protein 4 (n = 212), anti-programmed death 1 (n = 271), or the combination (n = 156)]. We tested the generalizability of our supervised ML algorithm to predict response to ICIs in the metastatic melanoma cohort and then developed a self-supervised ML model to identify the histologic morphologies associated with patients' survival following ICI use in adjuvant and metastatic melanoma cohorts. RESULTS/UNASSIGNED:We predicted the response to ICI treatment with an AUC of 0.72. The deep convolutional neural network classified patients into high and low risk based on their likelihood of progression-free survival (P < 0.0001). We uncovered a novel association of specific histomorphologic tumor features-epithelioid histology and a low tumor-stroma ratio-with survival following ICI treatment. CONCLUSIONS/UNASSIGNED:Our data support the generalizability of our developed ML algorithm in predicting response to ICI treatment in patients with metastatic unresectable melanoma. We also showed, for the first time, tumor features associated with patients' overall survival.