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396


Binding domain mutations provide insight into CTCF's relationship with chromatin and its contribution to gene regulation

Do, Catherine; Jiang, Guimei; Cova, Giulia; Katsifis, Christos C; Narducci, Domenic N; Sakellaropoulos, Theodore; Vidal, Raphael; Lhoumaud, Priscillia; Tsirigos, Aristotelis; Regis, Faye Fara D; Kakabadze, Nata; Nora, Elphege P; Noyes, Marcus; Hansen, Anders S; Skok, Jane A
Here we used a series of CTCF mutations to explore CTCF's relationship with chromatin and its contribution to gene regulation. CTCF's impact depends on the genomic context of bound sites and the unique binding properties of WT and mutant CTCF proteins. Specifically, CTCF's signal strength is linked to changes in accessibility, and the ability to block cohesin is linked to its binding stability. Multivariate modelling reveals that both CTCF and accessibility contribute independently to cohesin binding and insulation, however CTCF signal strength has a stronger effect. CTCF and chromatin have a bidirectional relationship such that at CTCF sites, accessibility is reduced in a cohesin-dependent, mutant specific fashion. In addition, each mutant alters TF binding and accessibility in an indirect manner, changes which impart the most influence on rewiring transcriptional networks and the cell's ability to differentiate. Collectively, the mutant perturbations provide a rich resource for determining CTCF's site-specific effects.
PMID: 38370764
ISSN: 2692-8205
CID: 5840692

Self supervised artificial intelligence predicts poor outcome from primary cutaneous squamous cell carcinoma at diagnosis

Coudray, Nicolas; Juarez, Michelle C; Criscito, Maressa C; Quiros, Adalberto Claudio; Wilken, Reason; Jackson Cullison, Stephanie R; Stevenson, Mary L; Doudican, Nicole A; Yuan, Ke; Aquino, Jamie D; Klufas, Daniel M; North, Jeffrey P; Yu, Siegrid S; Murad, Fadi; Ruiz, Emily; Schmults, Chrysalyne D; Cardona Machado, Cristian D; Cañueto, Javier; Choudhary, Anirudh; Hughes, Alysia N; Stockard, Alyssa; Leibovit-Reiben, Zachary; Mangold, Aaron R; Tsirigos, Aristotelis; Carucci, John A
Primary cutaneous squamous cell carcinoma (cSCC) is responsible for ~10,000 deaths annually in the United States. Stratification of risk of poor outcome at initial biopsy would significantly impact clinical decision-making during the initial post operative period where intervention has been shown to be most effective. Using whole-slide images (WSI) from 163 patients from 3 institutions, we developed a self supervised deep-learning model to predict poor outcomes in cSCC patients from histopathological features at initial diagnosis, and validated it using WSI from 563 patients, collected from two other academic institutions. For disease-free survival prediction, the model attained a concordance index of 0.73 in the development cohort and 0.84 in the Mayo cohort. The model's interpretability revealed that features like poor differentiation and deep invasion were strongly associated with poor prognosis. Furthermore, the model is effective in stratifying risk among BWH T2a and AJCC T2, known for outcome heterogeneity.
PMID: 39955424
ISSN: 2398-6352
CID: 5794132

AI accurately identifies targetable alterations in lung cancer histological images

Le, Hortense; Tsirigos, Aristotelis
PMID: 39930263
ISSN: 1759-4782
CID: 5793232

The common murine retroviral integration site activating Hhex marks a distal regulatory enhancer co-opted in human Early T-cell precursor leukemia

Hardwick, Joyce; Rodriguez-Hernaez, Javier; Gambi, Giovanni; Venters, Bryan J; Guo, Yan; Li, Liqi; Love, Paul E; Copeland, Neal G; Jenkins, Nancy A; Papaioannou, Dimitrios; Aifantis, Iannis; Tsirigos, Aristotelis; Ivan, Mircea; Davé, Utpal P
The Hhex gene encodes a transcription factor that is important for both embryonic and post-natal development, especially of hematopoietic tissues. Hhex is one of the most common sites of retroviral integration in mouse models. We found the most common integrations in AKXD (recombinant inbred strains) T-ALLs occur 57-61kb 3' of Hhex and activate Hhex gene expression. The genomic region of murine leukemia virus (MLV) integrations has features of a developmental stage-specific cis regulatory element (CRE), as evidenced by ATAC-seq in murine progenitor cells and high H3K27 acetylation at the syntenic CRE in human hematopoietic cell lines. With ChIP-exonuclease, we describe occupancy of LIM domain binding protein 1 (LDB1), the constitutive partner of the LIM Only-2 (LMO2), GATA1, and TAL1 transcription factors at GATA sites and a composite GATA-E box within the CRE. With virtual 4C analysis, we observed looping between this +65kb CRE and the proximal intron 1 enhancer of HHEX in primary human ETP-ALLs and in normal progenitor cells. Our results show that retroviral integrations at intergenic sites can mark and take advantage of CREs. Specifically, in the case of HHEX activation, this newly described +65kb CRE is co-opted in the pathogenesis of ETP-ALL by the LMO2/LDB1 complex.
PMID: 39880094
ISSN: 1083-351x
CID: 5780992

Quantitative and Morphology-Based Deep Convolutional Neural Network Approaches for Osteosarcoma Survival Prediction in the Neoadjuvant and Metastatic Setting

Coudray, Nicolas; Occidental, Michael A; Mantilla, Jose G; Claudio Quiros, Adalberto; Yuan, Ke; Balko, Jan; Tsirigos, Aristotelis; Jour, George
PURPOSE/OBJECTIVE:Necrosis quantification in the neoadjuvant setting using pathology slide review is the most important validated prognostic marker in conventional osteosarcoma. Herein, we explored three deep learning strategies on histology samples to predict outcome for OSA in the neoadjuvant setting. EXPERIMENTAL DESIGN/METHODS:Our study relies on a training cohort from New York University (New York, NY) and an external cohort from Charles university (Prague, Czechia). We trained and validated the performance of a supervised approach that integrates neural network predictions of necrosis/tumor content, and compared predicted overall survival (OS) using Kaplan-Meier curves. Furthermore, we explored morphology-based supervised and self-supervised approaches to determine whether intrinsic histomorphological features could serve as a potential marker for OS in the setting of neoadjuvant. RESULTS:Excellent correlation between the trained network and the pathologists was obtained for the quantification of necrosis content (R2=0.899, r=0.949, p < 0.0001). OS prediction cutoffs were consistent between pathologists and the neural network (22% and 30% of necrosis, respectively). Morphology-based supervised approach predicted OS with p-value=0.0028, HR=2.43 [1.10-5.38]. The self-supervised approach corroborated the findings with clusters enriched in necrosis, fibroblastic stroma, and osteoblastic morphology associating with better OS (lg2HR; -2.366; -1.164; -1.175; 95% CI=[-2.996; -0.514]). Viable/partially viable tumor and fat necrosis were associated with worse OS (lg2HR;1.287;0.822;0.828; 95% CI=[0.38-1.974]). CONCLUSIONS:Neural networks can be used to automatically estimate the necrosis to tumor ratio, a quantitative metric predictive of survival. Furthermore, we identified alternate histomorphological biomarkers specific to the necrotic and tumor regions themselves which can be used as predictors.
PMID: 39561274
ISSN: 1557-3265
CID: 5758442

Universal receptive system as a novel regulator of transcriptomic activity of Staphylococcus aureus

Tetz, George; Kardava, Kristina; Vecherkovskaya, Maria; Khodadadi-Jamayran, Alireza; Tsirigos, Aristotelis; Tetz, Victor
Our previous studies revealed the existence of a Universal Receptive System that regulates interactions between cells and their environment. This system is composed of DNA- and RNA-based Teazeled receptors (TezRs) found on the surface of prokaryotic and eukaryotic cells, as well as integrases and recombinases. In the current study, we aimed to provide further insight into the regulatory role of TezR and its loss in Staphylococcus aureus gene transcription. To this end, transcriptomic analysis of S. aureus MSSA VT209 was performed following the destruction of TezRs. Bacterial RNA samples were extracted from nuclease-treated and untreated S. aureus MSSA VT209. After destruction of the DNA-based-, RNA-, or combined DNA- and RNA-based TezRs of S. aureus, 103, 150, and 93 genes were significantly differently expressed, respectively. The analysis revealed differential clustering of gene expression following the loss of different TezRs, highlighting individual cellular responses following the loss of DNA- and RNA-based TezRs. KEGG pathway gene enrichment analysis revealed that the most upregulated pathways following TezR inactivation included those related to energy metabolism, cell wall metabolism, and secretion systems. Some of the genetic pathways were related to the inhibition of biofilm formation and increased antibiotic resistance, and we confirmed this at the phenotypic level using in vitro studies. The results of this study add another line of evidence that the Universal Receptive System plays an important role in cell regulation, including cell responses to the environmental factors of clinically important pathogens, and that nucleic acid-based TezRs are functionally active parts of the extrabiome.
PMID: 39754239
ISSN: 1475-2859
CID: 5781912

3D chromatin hubs as regulatory units of identity and survival in human acute leukemia

Gambi, Giovanni; Boccalatte, Francesco; Rodriguez Hernaez, Javier; Lin, Ziyan; Nadorp, Bettina; Polyzos, Alexander; Tan, Jimin; Avrampou, Kleopatra; Inghirami, Giorgio; Kentsis, Alex; Apostolou, Effie; Aifantis, Iannis; Tsirigos, Aristotelis
Cancer progression involves genetic and epigenetic changes that disrupt chromatin 3D organization, affecting enhancer-promoter interactions and promoting growth. Here, we provide an integrative approach, combining chromatin conformation, accessibility, and transcription analysis, validated by in silico and CRISPR-interference screens, to identify relevant 3D topologies in pediatric T cell leukemia (T-ALL and ETP-ALL). We characterize 3D hubs as regulatory centers for oncogenes and disease markers, linking them to biological processes like cell division, inflammation, and stress response. Single-cell mapping reveals heterogeneous gene activation in discrete epigenetic clones, aiding in patient stratification for relapse risk after chemotherapy. Finally, we identify MYB as a 3D hub regulator in leukemia cells and show that the targeting of key regulators leads to hub dissolution, thereby providing a novel and effective anti-leukemic strategy. Overall, our work demonstrates the relevance of studying oncogenic 3D hubs to better understand cancer biology and tumor heterogeneity and to propose novel therapeutic strategies.
PMID: 39719705
ISSN: 1097-4164
CID: 5767452

MetFinder: A Tool for Automated Quantitation of Metastatic Burden in Histological Sections From Preclinical Models

Karz, Alcida; Coudray, Nicolas; Bayraktar, Erol; Galbraith, Kristyn; Jour, George; Shadaloey, Arman Alberto Sorin; Eskow, Nicole; Rubanov, Andrey; Navarro, Maya; Moubarak, Rana; Baptiste, Gillian; Levinson, Grace; Mezzano, Valeria; Alu, Mark; Loomis, Cynthia; Lima, Daniel; Rubens, Adam; Jilaveanu, Lucia; Tsirigos, Aristotelis; Hernando, Eva
As efforts to study the mechanisms of melanoma metastasis and novel therapeutic approaches multiply, researchers need accurate, high-throughput methods to evaluate the effects on tumor burden resulting from specific interventions. We show that automated quantification of tumor content from whole slide images is a compelling solution to assess in vivo experiments. In order to increase the outflow of data collection from preclinical studies, we assembled a large dataset with annotations and trained a deep neural network for the quantitative analysis of melanoma tumor content on histopathological sections of murine models. After assessing its performance in segmenting these images, the tool obtained consistent results with an orthogonal method (bioluminescence) of measuring metastasis in an experimental setting. This AI-based algorithm, made freely available to academic laboratories through a web-interface called MetFinder, promises to become an asset for melanoma researchers and pathologists interested in accurate, quantitative assessment of metastasis burden.
PMID: 39254030
ISSN: 1755-148x
CID: 5690152

Matrix glycosaminoglycans and proteoglycans in human cornea organoids and similarities with fetal corneal stages

Ashworth, Sean; Dhanuka, Manas; Khodadadi-Jamayran, Alireza; Koduri, Madhuri Amulya; Maiti, George; Chakravarti, Shukti
PURPOSE/OBJECTIVE:We developed human cornea organoids (HCOs) from induced pluripotent stem cells (iPSCs) where single-cell RNA-sequence (scRNA-seq) analysis suggested similarity with developing rather than mature human corneas. We performed immunohistology to determine the presence of corneal glycosaminoglycans as an assessment of maturity. We undertook a detailed comparison of the HCO scRNA-seq data with a recent scRNA-seq study of human fetal corneas at different stages to gauge the HCO's maturity. METHODS:We generated HCOs from a second iPSC line, NCRM-1, to assess the reproducibility of HCO development. We stained sections from both HCO lines with Alcian blue and picrosirius red to determine deposition of sulfated glycosaminoglycans and fibrillar collagens. We immunolocalized glycosaminoglycan biosynthetic enzymes and proteoglycan core proteins. The scRNA-seq data from IMR90.4 HCOs were compared to that of fetal corneas using MetaNeighbor analysis to assess the similarity of HCOs to different stages of human corneal development. RESULTS:The MetaNeighbor analysis suggests closer alignment of the IMR90.4 HCOs with 17-18 post-conception week fetal human corneas. HCOs from both iPSC lines deposit sulfated glycosaminoglycans and fibrillar collagens. Immunohistology showed chondroitin/dermatan sulfate (CS/DS) and keratan sulfate in the presumptive stromal and some epithelial layers. The NCRM-1-derived HCOs show increased CS/DS staining compared to the IMR90.4 derived HCOs. CONCLUSIONS:Both HCO lines show similar developmental patterns and timeline. The NCRM-1 HCO line may have more glycosaminoglycan deposition. Overall, the glycosaminoglycan deposition pattern is consistent with an immature tissue. Optimizations based on our current findings may yield more mature stromal cells and cornea-typical proteoglycans.
PMID: 39615587
ISSN: 1937-5913
CID: 5775232

An inflammatory state defines a high-risk T-lineage acute lymphoblastic leukemia subgroup

Gower, Mark; Li, Ximing; Aguilar-Navarro, Alicia G; Lin, Brian; Fernandez, Minerva; Edun, Gibran; Nader, Mursal; Rondeau, Vincent; Arruda, Andrea; Tierens, Anne; Eames Seffernick, Anna; Pölönen, Petri; Durocher, Juliette; Wagenblast, Elvin; Yang, Lin; Lee, Ho Seok; Mullighan, Charles G; Teachey, David; Rashkovan, Marissa; Tremblay, Cedric S; Herranz, Daniel; Itkin, Tomer; Loghavi, Sanam; Dick, John E; Schwartz, Gregory; Perusini, Maria Agustina; Sibai, Hassan; Hitzler, Johann; Gruber, Tanja A; Minden, Mark; Jones, Courtney L; Dolgalev, Igor; Jahangiri, Soheil; Tikhonova, Anastasia N
T-lineage acute lymphoblastic leukemia (ALL) is an aggressive cancer comprising diverse subtypes that are challenging to stratify using conventional immunophenotyping. To gain insights into subset-specific therapeutic vulnerabilities, we performed an integrative multiomics analysis of bone marrow samples from newly diagnosed T cell ALL, early T cell precursor ALL, and T/myeloid mixed phenotype acute leukemia. Leveraging cellular indexing of transcriptomes and epitopes in conjunction with T cell receptor sequencing, we identified a subset of patient samples characterized by activation of inflammatory and stem gene programs. These inflammatory T-lineage samples exhibited distinct biological features compared with other T-lineage ALL samples, including the production of proinflammatory cytokines, prevalence of mutations affecting cytokine signaling and chromatin remodeling, an altered immune microenvironment, and poor treatment responses. Moreover, we found that, although inflammatory T-lineage ALL samples were less sensitive to dexamethasone, they exhibited unique sensitivity to a BCL-2 inhibitor, venetoclax. To facilitate classification of patients with T-lineage ALL, we developed a computational inflammatory gene signature scoring system, which stratified patients and was associated with disease prognosis in three additional patient cohorts. By identifying a high-risk T-lineage ALL subtype on the basis of an inflammatory score, our study provides a framework for targeted therapeutic approaches for these challenging-to-treat cancers.
PMID: 39742502
ISSN: 1946-6242
CID: 5779592