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Processing single-cell RNA-seq datasets using SingCellaR.
Single-cell RNA sequencing has led to unprecedented levels of data complexity. Although several computational platforms are available, performing data analyses for multiple datasets remains a significant challenge. Here, we provide a comprehensive analytical protocol to interrogate multiple datasets on SingCellaR, an analysis package in R. This tool can be applied to general single-cell transcriptome analyses. We demonstrate steps for data analyses and visualization using bespoke pipelines, in conjunction with existing analysis tools to study human hematopoietic stem and progenitor cells. For complete details on the use and execution of this protocol, please refer to Roy et al. (2021).
Outcomes and characteristics of nonmelanoma skin cancers in patients with myeloproliferative neoplasms on ruxolitinib.
Nonmelanoma skin cancers (NMSCs) in ruxolitinib-treated patients with myeloproliferative neoplasms behave aggressively, with adverse features and high recurrence. In our cohort, mortality from metastatic NMSC exceeded that from myelofibrosis. Vigilant skin assessment, counseling on NMSC risks, and prospective ruxolitinib-NMSC studies are crucial.
Supp Table 6 from Human Bone Marrow Organoids for Disease Modeling, Discovery, and Validation of Therapeutic Targets in Hematologic Malignancies
<p>Supplementary Table 6 qRT PCR Probes</p>
Supp Table 1 from Human Bone Marrow Organoids for Disease Modeling, Discovery, and Validation of Therapeutic Targets in Hematologic Malignancies
<p>Supplementary Table 1 VEGFAC Top Differentially Expressed Genes by Cluster</p>
Supplementary Information from Human Bone Marrow Organoids for Disease Modeling, Discovery, and Validation of Therapeutic Targets in Hematologic Malignancies
<p>Supplementary Materials and Methods, Supplementary Figures S1-S12</p>
Data from Human Bone Marrow Organoids for Disease Modeling, Discovery, and Validation of Therapeutic Targets in Hematologic Malignancies
<div>Abstract<p>A lack of models that recapitulate the complexity of human bone marrow has hampered mechanistic studies of normal and malignant hematopoiesis and the validation of novel therapies. Here, we describe a step-wise, directed-differentiation protocol in which organoids are generated from induced pluripotent stem cells committed to mesenchymal, endothelial, and hematopoietic lineages. These 3D structures capture key features of human bone marrow—stroma, lumen-forming sinusoids, and myeloid cells including proplatelet-forming megakaryocytes. The organoids supported the engraftment and survival of cells from patients with blood malignancies, including cancer types notoriously difficult to maintain <i>ex vivo</i>. Fibrosis of the organoid occurred following TGFβ stimulation and engraftment with myelofibrosis but not healthy donor–derived cells, validating this platform as a powerful tool for studies of malignant cells and their interactions within a human bone marrow–like milieu. This enabling technology is likely to accelerate the discovery and prioritization of novel targets for bone marrow disorders and blood cancers.</p>Significance:<p>We present a human bone marrow organoid that supports the growth of primary cells from patients with myeloid and lymphoid blood cancers. This model allows for mechanistic studies of blood cancers in the context of their microenvironment and provides a much-needed <i>ex vivo</i> tool for the prioritization of new therapeutics.</p><p><i><a href="https://aacrjournals.org/cancerdiscovery/article/doi/10.1158/2159-8290.CD-22-1303" target="_blank">See related commentary by Derecka and Crispino, p. 263</a>.</i></p><p><i><a href="https://aacrjournals.org/cancerdiscovery/article/doi/10.1158/2159-8290.CD-13-2-ITI" target="_blank">This article is highlighted in the In This Issue feature, p. 247</a></i></p></div>
Supp Table 2 from Human Bone Marrow Organoids for Disease Modeling, Discovery, and Validation of Therapeutic Targets in Hematologic Malignancies
<p>Supplementary Table 2 Gene sets for GSEA</p>
Supp Table 5 from Human Bone Marrow Organoids for Disease Modeling, Discovery, and Validation of Therapeutic Targets in Hematologic Malignancies
<p>Supplementary Table 5 Antibodies</p>
Supp Table 2 from Human Bone Marrow Organoids for Disease Modeling, Discovery, and Validation of Therapeutic Targets in Hematologic Malignancies
<p>Supplementary Table 2 Gene sets for GSEA</p>
Supp Table 1 from Human Bone Marrow Organoids for Disease Modeling, Discovery, and Validation of Therapeutic Targets in Hematologic Malignancies
<p>Supplementary Table 1 VEGFAC Top Differentially Expressed Genes by Cluster</p>
Supp Table 6 from Human Bone Marrow Organoids for Disease Modeling, Discovery, and Validation of Therapeutic Targets in Hematologic Malignancies
<p>Supplementary Table 6 qRT PCR Probes</p>
Supp Table 5 from Human Bone Marrow Organoids for Disease Modeling, Discovery, and Validation of Therapeutic Targets in Hematologic Malignancies
<p>Supplementary Table 5 Antibodies</p>
Supp Table 7 from Human Bone Marrow Organoids for Disease Modeling, Discovery, and Validation of Therapeutic Targets in Hematologic Malignancies
<p>Supplementary Table 7 NGS Panel</p>
Supp Table 3 from Human Bone Marrow Organoids for Disease Modeling, Discovery, and Validation of Therapeutic Targets in Hematologic Malignancies
<p>Supplementary Table 3 HD and MPN samples.</p>
Supp Table 3 from Human Bone Marrow Organoids for Disease Modeling, Discovery, and Validation of Therapeutic Targets in Hematologic Malignancies
<p>Supplementary Table 3 HD and MPN samples.</p>
Supplementary Information from Human Bone Marrow Organoids for Disease Modeling, Discovery, and Validation of Therapeutic Targets in Hematologic Malignancies
<p>Supplementary Materials and Methods, Supplementary Figures S1-S12</p>