{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,27]],"date-time":"2026-09-27T00:00:19Z","timestamp":1790467219746,"version":"4.1.0"},"reference-count":116,"publisher":"American Society of Hematology","issue":"4","content-domain":{"domain":["ashpublications.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2023,1,26]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Single-cell analysis has emerged over the past decade as a transformative technology informative for the systematic analysis of complex cell populations such as in cancers and the tumor immune microenvironment. The methodologic and analytical advancements in this realm have evolved rapidly, scaling from but a few cells at its outset to the current capabilities of processing and analyzing hundreds of thousands of individual cells at a time. The types of profiling attainable at individual cell resolution now range from genetic and transcriptomic characterization and extend to epigenomic and spatial analysis. Additionally, the increasing ability to achieve multiomic integration of these data layers now yields ever richer insights into diverse molecular disease subtypes and the patterns of cellular circuitry on a per-cancer basis. Over the years, chronic lymphocytic leukemia (CLL) consistently has been at the forefront of genomic investigation, given the ready accessibility of pure leukemia cells and immune cells from circulating blood of patients with this disease. Herein, we review the recent forays into the application of single-cell analysis to CLL, which are already revealing a new understanding of the natural progression of CLL, the impact of novel therapies, and the interactions with coevolving nonmalignant immune cell populations. As we emerge from the end of the beginning of this technologic revolution, CLL stands poised to reap the benefits of single-cell analysis from the standpoints of uncovering fresh fundamental biological knowledge and of providing a path to devising regimens of personalized diagnosis, treatment, and monitoring.<\/jats:p>","DOI":"10.1182\/blood.2021014669","type":"journal-article","created":{"date-parts":[[2022,9,12]],"date-time":"2022-09-12T21:57:54Z","timestamp":1663019874000},"page":"369-379","update-policy":"https:\/\/doi.org\/10.1182\/blood.2019cm0000","source":"Crossref","is-referenced-by-count":9,"title":["The end of the beginning: application of single-cell sequencing to chronic lymphocytic leukemia"],"prefix":"10.1182","volume":"141","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2127-5938","authenticated-orcid":false,"given":"Adi","family":"Nagler","sequence":"first","affiliation":[{"name":"1Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA"},{"name":"2Broad Institute of Massachusetts Institute of Technology and Harvard University, Cambridge, MA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3348-5054","authenticated-orcid":false,"given":"Catherine J.","family":"Wu","sequence":"additional","affiliation":[{"name":"1Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA"},{"name":"2Broad Institute of Massachusetts Institute of Technology and Harvard University, Cambridge, MA"},{"name":"3Harvard Medical School, Boston, MA"},{"name":"4Department of Medicine, Brigham and Women\u2019s Hospital, Boston, MA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"234","reference":[{"issue":"1","key":"2023082817051134100_bib1","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1038\/nmeth.2801","article-title":"Method of the year 2013","volume":"11","year":"2014","journal-title":"Nat 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