Browsing by Author "Rozenblatt-Rosen, Orit"
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Item Open Access An integrated cell atlas of the lung in health and disease.(Nature medicine, 2023-06) Sikkema, Lisa; Ramírez-Suástegui, Ciro; Strobl, Daniel C; Gillett, Tessa E; Zappia, Luke; Madissoon, Elo; Markov, Nikolay S; Zaragosi, Laure-Emmanuelle; Ji, Yuge; Ansari, Meshal; Arguel, Marie-Jeanne; Apperloo, Leonie; Banchero, Martin; Bécavin, Christophe; Berg, Marijn; Chichelnitskiy, Evgeny; Chung, Mei-I; Collin, Antoine; Gay, Aurore CA; Gote-Schniering, Janine; Hooshiar Kashani, Baharak; Inecik, Kemal; Jain, Manu; Kapellos, Theodore S; Kole, Tessa M; Leroy, Sylvie; Mayr, Christoph H; Oliver, Amanda J; von Papen, Michael; Peter, Lance; Taylor, Chase J; Walzthoeni, Thomas; Xu, Chuan; Bui, Linh T; De Donno, Carlo; Dony, Leander; Faiz, Alen; Guo, Minzhe; Gutierrez, Austin J; Heumos, Lukas; Huang, Ni; Ibarra, Ignacio L; Jackson, Nathan D; Kadur Lakshminarasimha Murthy, Preetish; Lotfollahi, Mohammad; Tabib, Tracy; Talavera-López, Carlos; Travaglini, Kyle J; Wilbrey-Clark, Anna; Worlock, Kaylee B; Yoshida, Masahiro; Lung Biological Network Consortium; van den Berge, Maarten; Bossé, Yohan; Desai, Tushar J; Eickelberg, Oliver; Kaminski, Naftali; Krasnow, Mark A; Lafyatis, Robert; Nikolic, Marko Z; Powell, Joseph E; Rajagopal, Jayaraj; Rojas, Mauricio; Rozenblatt-Rosen, Orit; Seibold, Max A; Sheppard, Dean; Shepherd, Douglas P; Sin, Don D; Timens, Wim; Tsankov, Alexander M; Whitsett, Jeffrey; Xu, Yan; Banovich, Nicholas E; Barbry, Pascal; Duong, Thu Elizabeth; Falk, Christine S; Meyer, Kerstin B; Kropski, Jonathan A; Pe'er, Dana; Schiller, Herbert B; Tata, Purushothama Rao; Schultze, Joachim L; Teichmann, Sara A; Misharin, Alexander V; Nawijn, Martijn C; Luecken, Malte D; Theis, Fabian JSingle-cell technologies have transformed our understanding of human tissues. Yet, studies typically capture only a limited number of donors and disagree on cell type definitions. Integrating many single-cell datasets can address these limitations of individual studies and capture the variability present in the population. Here we present the integrated Human Lung Cell Atlas (HLCA), combining 49 datasets of the human respiratory system into a single atlas spanning over 2.4 million cells from 486 individuals. The HLCA presents a consensus cell type re-annotation with matching marker genes, including annotations of rare and previously undescribed cell types. Leveraging the number and diversity of individuals in the HLCA, we identify gene modules that are associated with demographic covariates such as age, sex and body mass index, as well as gene modules changing expression along the proximal-to-distal axis of the bronchial tree. Mapping new data to the HLCA enables rapid data annotation and interpretation. Using the HLCA as a reference for the study of disease, we identify shared cell states across multiple lung diseases, including SPP1+ profibrotic monocyte-derived macrophages in COVID-19, pulmonary fibrosis and lung carcinoma. Overall, the HLCA serves as an example for the development and use of large-scale, cross-dataset organ atlases within the Human Cell Atlas.Item Open Access COVID-19 tissue atlases reveal SARS-CoV-2 pathology and cellular targets.(Nature, 2021-07) Delorey, Toni M; Ziegler, Carly GK; Heimberg, Graham; Normand, Rachelly; Yang, Yiming; Segerstolpe, Åsa; Abbondanza, Domenic; Fleming, Stephen J; Subramanian, Ayshwarya; Montoro, Daniel T; Jagadeesh, Karthik A; Dey, Kushal K; Sen, Pritha; Slyper, Michal; Pita-Juárez, Yered H; Phillips, Devan; Biermann, Jana; Bloom-Ackermann, Zohar; Barkas, Nikolaos; Ganna, Andrea; Gomez, James; Melms, Johannes C; Katsyv, Igor; Normandin, Erica; Naderi, Pourya; Popov, Yury V; Raju, Siddharth S; Niezen, Sebastian; Tsai, Linus T-Y; Siddle, Katherine J; Sud, Malika; Tran, Victoria M; Vellarikkal, Shamsudheen K; Wang, Yiping; Amir-Zilberstein, Liat; Atri, Deepak S; Beechem, Joseph; Brook, Olga R; Chen, Jonathan; Divakar, Prajan; Dorceus, Phylicia; Engreitz, Jesse M; Essene, Adam; Fitzgerald, Donna M; Fropf, Robin; Gazal, Steven; Gould, Joshua; Grzyb, John; Harvey, Tyler; Hecht, Jonathan; Hether, Tyler; Jané-Valbuena, Judit; Leney-Greene, Michael; Ma, Hui; McCabe, Cristin; McLoughlin, Daniel E; Miller, Eric M; Muus, Christoph; Niemi, Mari; Padera, Robert; Pan, Liuliu; Pant, Deepti; Pe'er, Carmel; Pfiffner-Borges, Jenna; Pinto, Christopher J; Plaisted, Jacob; Reeves, Jason; Ross, Marty; Rudy, Melissa; Rueckert, Erroll H; Siciliano, Michelle; Sturm, Alexander; Todres, Ellen; Waghray, Avinash; Warren, Sarah; Zhang, Shuting; Zollinger, Daniel R; Cosimi, Lisa; Gupta, Rajat M; Hacohen, Nir; Hibshoosh, Hanina; Hide, Winston; Price, Alkes L; Rajagopal, Jayaraj; Tata, Purushothama Rao; Riedel, Stefan; Szabo, Gyongyi; Tickle, Timothy L; Ellinor, Patrick T; Hung, Deborah; Sabeti, Pardis C; Novak, Richard; Rogers, Robert; Ingber, Donald E; Jiang, Z Gordon; Juric, Dejan; Babadi, Mehrtash; Farhi, Samouil L; Izar, Benjamin; Stone, James R; Vlachos, Ioannis S; Solomon, Isaac H; Ashenberg, Orr; Porter, Caroline BM; Li, Bo; Shalek, Alex K; Villani, Alexandra-Chloé; Rozenblatt-Rosen, Orit; Regev, AvivCOVID-19, which is caused by SARS-CoV-2, can result in acute respiratory distress syndrome and multiple organ failure1-4, but little is known about its pathophysiology. Here we generated single-cell atlases of 24 lung, 16 kidney, 16 liver and 19 heart autopsy tissue samples and spatial atlases of 14 lung samples from donors who died of COVID-19. Integrated computational analysis uncovered substantial remodelling in the lung epithelial, immune and stromal compartments, with evidence of multiple paths of failed tissue regeneration, including defective alveolar type 2 differentiation and expansion of fibroblasts and putative TP63+ intrapulmonary basal-like progenitor cells. Viral RNAs were enriched in mononuclear phagocytic and endothelial lung cells, which induced specific host programs. Spatial analysis in lung distinguished inflammatory host responses in lung regions with and without viral RNA. Analysis of the other tissue atlases showed transcriptional alterations in multiple cell types in heart tissue from donors with COVID-19, and mapped cell types and genes implicated with disease severity based on COVID-19 genome-wide association studies. Our foundational dataset elucidates the biological effect of severe SARS-CoV-2 infection across the body, a key step towards new treatments.Item Open Access The Human Tumor Atlas Network: Charting Tumor Transitions across Space and Time at Single-Cell Resolution.(Cell, 2020-04) Rozenblatt-Rosen, Orit; Regev, Aviv; Oberdoerffer, Philipp; Nawy, Tal; Hupalowska, Anna; Rood, Jennifer E; Ashenberg, Orr; Cerami, Ethan; Coffey, Robert J; Demir, Emek; Ding, Li; Esplin, Edward D; Ford, James M; Goecks, Jeremy; Ghosh, Sharmistha; Gray, Joe W; Guinney, Justin; Hanlon, Sean E; Hughes, Shannon K; Hwang, E Shelley; Iacobuzio-Donahue, Christine A; Jané-Valbuena, Judit; Johnson, Bruce E; Lau, Ken S; Lively, Tracy; Mazzilli, Sarah A; Pe'er, Dana; Santagata, Sandro; Shalek, Alex K; Schapiro, Denis; Snyder, Michael P; Sorger, Peter K; Spira, Avrum E; Srivastava, Sudhir; Tan, Kai; West, Robert B; Williams, Elizabeth H; Human Tumor Atlas NetworkCrucial transitions in cancer-including tumor initiation, local expansion, metastasis, and therapeutic resistance-involve complex interactions between cells within the dynamic tumor ecosystem. Transformative single-cell genomics technologies and spatial multiplex in situ methods now provide an opportunity to interrogate this complexity at unprecedented resolution. The Human Tumor Atlas Network (HTAN), part of the National Cancer Institute (NCI) Cancer Moonshot Initiative, will establish a clinical, experimental, computational, and organizational framework to generate informative and accessible three-dimensional atlases of cancer transitions for a diverse set of tumor types. This effort complements both ongoing efforts to map healthy organs and previous large-scale cancer genomics approaches focused on bulk sequencing at a single point in time. Generating single-cell, multiparametric, longitudinal atlases and integrating them with clinical outcomes should help identify novel predictive biomarkers and features as well as therapeutically relevant cell types, cell states, and cellular interactions across transitions. The resulting tumor atlases should have a profound impact on our understanding of cancer biology and have the potential to improve cancer detection, prevention, and therapeutic discovery for better precision-medicine treatments of cancer patients and those at risk for cancer.