{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,3]],"date-time":"2026-01-03T05:18:14Z","timestamp":1767417494069,"version":"3.48.0"},"reference-count":31,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100012524","name":"American Lebanese Syrian Associated Charities","doi-asserted-by":"crossref","id":[{"id":"10.13039\/100012524","id-type":"DOI","asserted-by":"crossref"}]},{"name":"National Institutes of Health National Cancer Institute","award":["T32-CA236748"],"award-info":[{"award-number":["T32-CA236748"]}]},{"name":"National Institutes of Health National Cancer Institute","award":["R01-CA132946"],"award-info":[{"award-number":["R01-CA132946"]}]},{"name":"National Institutes of Health National Cancer Institute","award":["R01-CA270120"],"award-info":[{"award-number":["R01-CA270120"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Genes"],"abstract":"<jats:p>Background: Rapid advances in biotechnology provide researchers with the opportunity to integrate omics profiles (genomics, epigenomics, transcriptomics, proteomics, etc.) with multiple phenotypes or experimental conditions. In cancers such as acute myeloid leukemia (AML), where combination therapies are standard of care, identifying genetic drivers of drug resistance requires evaluating how genes are associated with multiple drug response phenotypes. Statistical analyses associating omics profiles with multiple phenotypes yield multiple significance values and rankings for each of many genes. There is a great need to consolidate these multiple rankings into a consensus ranking to prioritize specific genes for detailed follow-up wet-lab or clinical studies. Methods\/Results: Here, we evaluate the well-known Fisher\u2019s method, the sum of squared z-statistics (SSz), and the recently published cellMCD method as tools for gene prioritization. In simulation studies, cellMCD showed very similar or highly superior performance to the widely used Fisher\u2019s and SSz methods. These advantages were also observed in an example application involving a CRISPR drug screen of an acute myeloid leukemia cell line. Conclusions: In summary, our results indicate that cellMCD should be more widely used for prioritizing discoveries from multiple omic association studies. These methods are available as an R package on github.<\/jats:p>","DOI":"10.3390\/genes17010049","type":"journal-article","created":{"date-parts":[[2026,1,2]],"date-time":"2026-01-02T12:23:44Z","timestamp":1767356624000},"page":"49","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["cellMCD Effectively Discovers Drug Resistance and Sensitivity Genes for Acute Myeloid Leukemia"],"prefix":"10.3390","volume":"17","author":[{"given":"Dora","family":"Obodo","sequence":"first","affiliation":[{"name":"Department of Biostatistics, St. Jude Children\u2019s Research Hospital, Memphis, TN 38105, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3036-4748","authenticated-orcid":false,"given":"Nam H. K.","family":"Nguyen","sequence":"additional","affiliation":[{"name":"Department of Pharmacotherapy and Translational Research, Center for Pharmacogenomics and Precision Medicine, College of Pharmacy, University of Florida, Gainesville, FL 32610, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4396-7460","authenticated-orcid":false,"given":"Xueyuan","family":"Cao","sequence":"additional","affiliation":[{"name":"Department of Health Promotion, Disease Prevention, and Preventive Medicine, The University of Tennessee Health Science Center, Memphis, TN 38163, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4326-4463","authenticated-orcid":false,"given":"Phani Krishna","family":"Parcha","sequence":"additional","affiliation":[{"name":"Department of Pharmacotherapy and Translational Research, Center for Pharmacogenomics and Precision Medicine, College of Pharmacy, University of Florida, Gainesville, FL 32610, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5134-8929","authenticated-orcid":false,"given":"Christopher D.","family":"Vulpe","sequence":"additional","affiliation":[{"name":"Department of Pharmacotherapy and Translational Research, Center for Pharmacogenomics and Precision Medicine, College of Pharmacy, University of Florida, Gainesville, FL 32610, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0411-0007","authenticated-orcid":false,"given":"Jatinder K.","family":"Lamba","sequence":"additional","affiliation":[{"name":"Department of Pharmacotherapy and Translational Research, Center for Pharmacogenomics and Precision Medicine, College of Pharmacy, University of Florida, Gainesville, FL 32610, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Stanley B.","family":"Pounds","sequence":"additional","affiliation":[{"name":"Department of Biostatistics, St. Jude Children\u2019s Research Hospital, Memphis, TN 38105, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2026,1,1]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"695","DOI":"10.1038\/s41580-023-00615-w","article-title":"The technological landscape and applications of single-cell multi-omics","volume":"24","author":"Baysoy","year":"2023","journal-title":"Nat. Rev. Mol. Cell Biol."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"349","DOI":"10.1007\/978-1-0716-2986-4_16","article-title":"Statistical Methods Inspired by Challenges in Pediatric Cancer Multi-omics","volume":"2629","author":"Fridley","year":"2023","journal-title":"Statistical Genomics"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"1078","DOI":"10.1182\/bloodadvances.2024014157","article-title":"Genome-wide CRISPR\/Cas9 screen identifies AraC-daunorubicin-etoposide response modulators associated with outcomes in pediatric AML","volume":"9","author":"Nguyen","year":"2025","journal-title":"Blood Adv."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"408","DOI":"10.1038\/s41588-020-0590-9","article-title":"Using antagonistic pleiotropy to design a chemotherapy-induced evolutionary trap to target drug resistance in cancer","volume":"52","author":"Lin","year":"2020","journal-title":"Nat. Genet."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"735","DOI":"10.1038\/s41375-019-0604-8","article-title":"A six-gene leukemic stem cell score identifies high risk pediatric acute myeloid leukemia","volume":"34","author":"Elsayed","year":"2020","journal-title":"Leukemia"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"2013","DOI":"10.1093\/bioinformatics\/btp357","article-title":"PROMISE: A tool to identify genomic features with a specific biologically interesting pattern of associations with multiple endpoint variables","volume":"25","author":"Pounds","year":"2009","journal-title":"Bioinformatics"},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Cao, X., Crews, K.R., Downing, J., Lamba, J., and Pounds, S.B. (2016). CC-PROMISE effectively integrates two forms of molecular data with multiple biologically related endpoints. BMC Bioinform., 17.","DOI":"10.1186\/s12859-016-1217-0"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"2610","DOI":"10.1080\/01621459.2023.2267777","article-title":"The Cellwise Minimum Covariance Determinant Estimator","volume":"119","author":"Raymaekers","year":"2024","journal-title":"J. Am. Stat. Assoc."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"110366","DOI":"10.1016\/j.spl.2025.110366","article-title":"CellMCD+: An improved outlier-resistant cellwise minimum covariance determinant method","volume":"220","author":"Babu","year":"2025","journal-title":"Stat. Probab. Lett."},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Kotz, S., and Johnson, N.L. (1992). Statistical Methods for Research Workers. Breakthroughs in Statistics: Methodology and Distribution, Springer.","DOI":"10.1007\/978-1-4612-4380-9"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"6980","DOI":"10.1038\/s41598-021-86465-y","article-title":"Powerful p-value combination methods to detect incomplete association","volume":"11","author":"Yoon","year":"2011","journal-title":"Sci. Rep."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"178","DOI":"10.1017\/S0305004100016595","article-title":"The distribution of quadratic forms in a normal system, with applications to the analysis of covariance","volume":"30","author":"Cochran","year":"1934","journal-title":"Math. Proc. Camb. Philos. Soc."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"1412","DOI":"10.1182\/blood-2023-174281","article-title":"CRISPR\/Cas9 Screen Identifies CPX-351 and 7+3 Regimens Response Modulators with Distinct Sensitive and Resistant Profiles","volume":"142","author":"Nguyen","year":"2023","journal-title":"Blood"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"554","DOI":"10.1186\/s13059-014-0554-4","article-title":"MAGeCK enables robust identification of essential genes from genome-scale CRISPR\/Cas9 knockout screens","volume":"15","author":"Li","year":"2014","journal-title":"Genome Biol."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"756","DOI":"10.1038\/s41596-018-0113-7","article-title":"Integrative analysis of pooled CRISPR genetic screens using MAGeCKFlute","volume":"14","author":"Wang","year":"2019","journal-title":"Nat. Protoc."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"25436","DOI":"10.1074\/jbc.273.39.25436","article-title":"A functional role for mitochondrial protein kinase Calpha in Bcl2 phosphorylation and suppression of apoptosis","volume":"273","author":"Ruvolo","year":"1998","journal-title":"J. Biol. Chem."},{"key":"ref_17","first-page":"86","article-title":"Environmental and chemotherapeutic agents induce breakage at genes involved in leukemia-causing gene rearrangements in human hematopoietic stem\/progenitor cells","volume":"779","author":"Thys","year":"2015","journal-title":"Mutat. Res."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"281","DOI":"10.1038\/s41588-023-01640-3","article-title":"A new genomic framework to categorize pediatric acute myeloid leukemia","volume":"56","author":"Umeda","year":"2024","journal-title":"Nat. Genet."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"103","DOI":"10.1016\/j.omto.2018.12.008","article-title":"Expression and Prognosis Analyses of Runt-Related Transcription Factor Family in Human Leukemia","volume":"12","author":"Sun","year":"2019","journal-title":"Mol. Ther. Oncolytics"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"3323","DOI":"10.1182\/blood-2008-06-162248","article-title":"Runx2 induces acute myeloid leukemia in cooperation with Cbf\u03b2-SMMHC in mice","volume":"113","author":"Kuo","year":"2009","journal-title":"Blood"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"81","DOI":"10.1038\/s41408-024-01066-y","article-title":"The landscape of NUP98 rearrangements clinical characteristics and treatment response from 1491 acute leukemia patients","volume":"14","author":"Tian","year":"2024","journal-title":"Blood Cancer J."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"204","DOI":"10.1002\/pbc.23179","article-title":"Leukemic mutations in the methylation-associated genes DNMT3A and IDH2 are rare events in pediatric AML: A report from the Children\u2019s Oncology Group","volume":"57","author":"Ho","year":"2011","journal-title":"Pediatr. Blood Cancer"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"702","DOI":"10.1182\/blood-2010-02-268953","article-title":"Prevalence and prognostic implications of WT1 mutations in pediatric acute myeloid leukemia (AML): A report from the Children\u2019s Oncology Group","volume":"116","author":"Ho","year":"2010","journal-title":"Blood"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"1965","DOI":"10.1182\/blood.2023022202","article-title":"PI3K\u03b3 maintains the self-renewal of acute myeloid leukemia stem cells by regulating the pentose phosphate pathway","volume":"143","author":"Gu","year":"2024","journal-title":"Blood"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"800","DOI":"10.1016\/j.ajhg.2013.04.002","article-title":"Mutations in ERCC4, encoding the DNA-repair endonuclease XPF, cause Fanconi anemia","volume":"92","author":"Bogliolo","year":"2013","journal-title":"Am. J. Hum. Genet."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"214","DOI":"10.1016\/j.beha.2014.10.002","article-title":"Fanconi anemia and the development of leukemia","volume":"27","author":"Alter","year":"2014","journal-title":"Best Pract. Res. Clin. Haematol."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"407","DOI":"10.1038\/s41580-022-00452-3","article-title":"Human topoisomerases and their roles in genome stability and organization","volume":"23","author":"Pommier","year":"2022","journal-title":"Nat. Rev. Mol. Cell Biol."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"2753","DOI":"10.1158\/0008-5472.CAN-24-3840","article-title":"A Machine Learning\u2013Based Strategy Predicts Selective and Synergistic Drug Combinations for Relapsed Acute Myeloid Leukemia","volume":"85","author":"Chen","year":"2025","journal-title":"Cancer Res."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"19","DOI":"10.1038\/s41698-020-0122-1","article-title":"Machine learning approaches to drug response prediction: Challenges and recent progress","volume":"4","author":"Adam","year":"2020","journal-title":"npj Precis. Oncol."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"108432","DOI":"10.1016\/j.cmpb.2024.108432","article-title":"Combining clinical and molecular data for personalized treatment in acute myeloid leukemia: A machine learning approach","volume":"257","author":"Karathanasis","year":"2024","journal-title":"Comput. Methods Programs Biomed."},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Zhang, B., Liu, H., Wu, F., Ding, Y., Wu, J., Lu, L., Bajpai, A.K., Sang, M., and Wang, X. (2024). Identification of hub genes and potential molecular mechanisms related to drug sensitivity in acute myeloid leukemia based on machine learning. Front. Pharmacol., 15.","DOI":"10.3389\/fphar.2024.1359832"}],"container-title":["Genes"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2073-4425\/17\/1\/49\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,1,3]],"date-time":"2026-01-03T05:14:11Z","timestamp":1767417251000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2073-4425\/17\/1\/49"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,1,1]]},"references-count":31,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2026,1]]}},"alternative-id":["genes17010049"],"URL":"https:\/\/doi.org\/10.3390\/genes17010049","relation":{},"ISSN":["2073-4425"],"issn-type":[{"type":"electronic","value":"2073-4425"}],"subject":[],"published":{"date-parts":[[2026,1,1]]}}}