The applications of single-cell multiomics in drug screening

Abstract

Single-cell multiomics (scMultiomics) technologies and methods encompassing transcriptomics, genomics, epigenomics, proteomics, and metabolomics, together with associated computational tools have profoundly revolutionized disease research, enabling unprecedented dissection of cellular heterogeneity and dynamic biological responses. The use of scMultiomics technologies to study drug drug screening, actions and responses has not only unlocked novel avenues in precision drug screening but also transformed our understanding of how small molecules target specific cell types in cancer treatment, as well as their connections to disease etiology and progression from a high-resolution view of their functional diversity. In this review, we systematically explore how scMultiomics technologies develop and drive advancements in drug screening. With a specific focus on the applications in target identification, drug response, and drug resistance, we highlight how scMultiomics can link cellular-level insights with individualized drug screening, which in turn promises actionable strategies to improve therapeutic precision in drug development.

Keywords

scMultiomics / Drug screening / Drug response / Drug resistance

CRediT authorship contribution statement

Qingming Xue: Writing - review & editing, Writing - original draft, Investigation, Data curation. Hanyu Hu: Writing - review & editing, Writing - original draft, Investigation, Data curation. Ruogu Wang: Writing - review & editing, Writing - original draft, Investigation, Data curation. Fei Wu: Writing - review & editing, Writing - original draft, Investigation, Data curation. Haiqing Xiong: Writing - review & editing, Writing - original draft, Funding acquisition, Conceptualization.

Ethics approval

Not applicable.

Declaration of generative AI in scientific writing

Not applicable.

Funding information

H.X. was supported by grants from the Non-profit Central Research Institute Fund of Chinese Academy of Medical Sciences (2022-RC18007); CAMS Innovation Fund for Medical Sciences (CIFMS) (2023-I2M-2-007, 2022-I2M-1-022); The National Natural Science Foundation of China (32470884); State Key Laboratory of Experimental Hematology Research Grant (Z22-09).

Data availability

Not applicable.

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgments

We thank all members of the Xiong lab for critical comments on this manuscript. BioRender (https://Biorender.com) was used for generating cartoon illustrations.

Appendix A. Supplementary data

Supplementary data to this article can be found online at https://doi.org/10.1016/j.pscia.2025.100090.

References

[1] C. Karampelias, H. Lickert, Greasing the machinery toward maturation of stem cellderived β cells, Cell Stem Cell 31 (6) (2024) 793-794, https://doi.org/10.1016/j.stem.2024.05.001.

[2] B. Van de Sande, J.S. Lee, E. Mutasa-Gottgens, B. Naughton, W. Bacon, J. Manning, Y. Wang, J. Pollard, M. Mendez, J. Hill, N. Kumar, X. Cao, X. Chen, M. Khaladkar, J. Wen, A. Leach, E. Ferran, Applications of single-cell RNA sequencing in drug discovery and development, Nat. Rev. Drug Discov. 22 (6) (2023) 496-520, https://doi.org/10.1038/s41573-023-00688-4.

[3] J. Chen, X. Wang, A. Ma, Q.E. Wang, B. Liu, L. Li, D. Xu, Q. Ma, Deep transfer learning of cancer drug responses by integrating bulk and single-cell RNA-seq data, Nat. Commun. 13 (1) (2022) 6494, https://doi.org/10.1038/s41467-022-34277-7.

[4] Z. Li, M. Seehawer, K. Polyak, Untangling the web of intratumour heterogeneity, Nat. Cell Biol. 24 (8) (2022) 1192-1201, https://doi.org/10.1038/s41556-022-00969-х.

[5] M.K. Samur, R. Szalat, N.C. Munshi, Single-cell profiling in multiple myeloma: insights, problems, and promises, Blood 142 (4) (2023) 313-324, https://doi.org/10.1182/blood.2022017145.

[6] P. Zhang, X. Wang, X. Cen, Q. Zhang, Y. Fu, Y. Mei, X. Wang, R. Wang, J. Wang, H. Ouyang, T. Liang, H. Xia, X. Han, G. Guo, A deep learning framework for in silico screening of anticancer drugs at the single-cell level, Natl. Sci. Rev. 12 (2) (2025), https://doi.org/10.1093/nsr/nwae451nwae451.

[7] M.A. Goyette, M. Lipsyc-Sharf, K. Polyak, Clinical and translational relevance of intratumor heterogeneity, Trends Cancer 9 (9) (2023) 726-737, https://doi.org/10.1016/j.trecan.2023.05.001.

[8] M. Tanaka, L. Lum, K.H. Hu, P. Chaudhary, S. Hughes, C. Ledezma-Soto, B. Samad, D. Superville, K. Ng, A. Chumber, C. Benson, Z.N. Adams, K. Kersten, O.A. Aguilar, L. Fong, A.J. Combes, M.F. Krummel, M.Q. Reeves, Tumor cell heterogeneity drives spatial organization of the intratumoral immune response, J. Exp. Med. 222 (6) (2025), https://doi.org/10.1084/jem.20242282.

[9] C.G. Lucas, K. Mirchia, K. Seo, H. Najem, W.C. Chen, N. Zakimi, K. Foster, C. D. Eaton, M.A. Cady, A. Choudhury, S.J. Liu, J.J. Phillips, S.T. Magill, C. M. Horbinski, D.A. Solomon, A. Perry, H.N. Vasudevan, A.B. Heimberger, D. R. Raleigh, Spatial genomic, biochemical and cellular mechanisms underlying meningioma heterogeneity and evolution, Nat. Genet. 56 (6) (2024) 1121-1133, https://doi.org/10.1038/s41588-024-01747-1.

[10] A.A. Hippen, D.K. Omran, L.M. Weber, E. Jung, R. Drapkin, J.A. Doherty, S. C. Hicks, C.S. Greene, Performance of computational algorithms to deconvolve heterogeneous bulk ovarian tumor tissue depends on experimental factors, Genome Biol. 24 (1) (2023) 239, https://doi.org/10.1186/s13059-023-03077-7.

[11] A. Lomakin, J. Svedlund, C. Strell, M. Gataric, A. Shmatko, G. Rukhovich, J.S. Park, Y.S. Ju, S. Dentro, V. Kleshchevnikov, V. Vaskivskyi, T. Li, O.A. Bayraktar, S. Pinder, A.L. Richardson, S. Santagata, P.J. Campbell, H. Russnes, M. Gerstung, M. Nilsson, L.R. Yates, Spatial genomics maps the structure, nature and evolution of cancer clones, Nature 611 (7936) (2022) 594-602, https://doi.org/10.1038/s41586-022-05425-2.

[12] S. Rao, C. Verrill, L. Cerundolo, N.K. Alham, Z. Kaya, M. O'Hanlon, A. Hayes, A. Lambert, M. James, I.D.C. Tullis, J. Niederer, S. Lovell, A. Omer, F. Lopez, T. Leslie, F. Buffa, R.J. Bryant, A.D. Lamb, B. Vojnovic, D.C. Wedge, I.G. Mills, D. J. Woodcock, I. Tomlinson, F.C. Hamdy, Intra-prostatic tumour evolution, steps in metastatic spread and histogenomic associations revealed by integration of multiregion whole-genome sequencing with histopathological features, Genome Med. 16 (1) (2024) 35, https://doi.org/10.1186/s13073-024-01302-x.

[13] F. Tang, C. Barbacioru, Y. Wang, E. Nordman, C. Lee, N. Xu, X. Wang, J. Bodeau, B. B. Tuch, A. Siddiqui, K. Lao, M.A. Surani, mRNA-Seq whole-transcriptome analysis of a single cell, Nat. Methods 6 (5) (2009) 377-382, https://doi.org/10.1038/nmeth.1315.

[14] C. Chen, J. Xu, J.H. Sussman, T. Vincent, J.S. Tumulty, S. Yoshimura, F. Alikarami, W. Yu, Y.Y. Ding, C.H. Chen, E.Y. Li, A. Yang, X. Qin, S. Bandyopadhyay, J. Peng, P. Pölönen, H. Newman, B.L. Wood, J. Hu, R. Shraim, A.D. Hughes, C. Diorio, L. Uppuluri, G. Shi, T. Ryan, T. Fuller, M.L. Loh, E.A. Raetz, S.P. Hunger, S. B. Pounds, C.G. Mullighan, D. Frank, J.J. Yang, K.M. Bernt, D.T. Teachey, K. Tan, Single-cell panleukemia signatures of HSPC-like blasts predict drug response and clinical outcome, Blood 145 (23) (2025) 2685-2700, https://doi.org/10.1182/blood.2024027270.

[15] X. Wang, M. Duan, J. Li, A. Ma, G. Xin, D. Xu, Z. Li, B. Liu, Q. Ma, MarsGT: multiomics analysis for rare population inference using single-cell graph transformer, Nat. Commun. 15 (1) (2024) 338, https://doi.org/10.1038/s41467-023-44570-8.

[16] C.A. Ladaika, A.H. Ghobashi, W.C. Boulton, S.A. Miller, H.M. O'Hagan, LSD1 and CoREST2 potentiate STAT3 activity to promote enteroendocrine cell differentiation in mucinous colorectal cancer, Cancer Res. 85 (1) (2025) 52-68, https://doi.org/10.1158/0008-5472.Can-24-0788.

[17] S. Lobato-Moreno, U. Yildiz, A. Claringbould, N.H. Servaas, E.P. Vlachou, C. Arnold, H.G. Bauersachs, V. Campos-Fornés, M. Kim, I. Berest, K.D. Prummel, K. M. Noh, M. Marttinen, J.B. Zaugg, Single-cell ultra-high-throughput multiplexed chromatin and RNA profiling reveals gene regulatory dynamics, Nat. Methods 22 (6) (2025) 1213-1225, https://doi.org/10.1038/s41592-025-02700-8.

[18] Z.C. Jia, X. Yang, Y.K. Wu, M. Li, D. Das, M.X. Chen, J. Wu, The art of finding the right drug target: emerging methods and strategies, Pharmacol. Rev. 76 (5) (2024) 896-914, https://doi.org/10.1124/pharmrev.123.001028.

[19] L. Hoffer, G. Charifi-Hoareau, S. Barelier, S. Betzi, T. Miller, X. Morelli, P. Roche, ChemoDOTS: a web server to design chemistry-driven focused libraries, Nucleic Acids Res. 52 (W1) (2024) W461-w468, https://doi.org/10.1093/nar/gkae326.

[20] T. Kenakin, Know your molecule: pharmacological characterization of drug candidates to enhance efficacy and reduce late-stage attrition, Nat. Rev. Drug Discov. 23 (8) (2024) 626-644, https://doi.org/10.1038/s41573-024-00958-9.

[21] K. Tang, S. Wang, W. Gao, Y. Song, B. Yu, Harnessing the cyclization strategy for new drug discovery, Acta Pharm. Sin. B 12 (12) (2022) 4309-4326, https://doi.org/10.1016/j.apsb.2022.09.022.

[22] G.M. Kline, K. Nugroho, J.W. Kelly, Inverse Drug Discovery identifies weak electrophiles affording protein conjugates, Curr. Opin. Chem. Biol. 67 (2022) 102113, https://doi.org/10.1016/j.cbpa.2021.102113.

[23] K. Wu, E. Karapetyan, J. Schloss, J. Vadgama, Y. Wu, Advancements in small molecule drug design: a structural perspective, Drug Discov. Today 28 (10) (2023) 103730, https://doi.org/10.1016/j.drudis.2023.103730.

[24] A. Sadri, Is target-based drug discovery efficient? Discovery and "Off-Target" mechanisms of all drugs, J. Med. Chem. 66 (18) (2023) 12651-12677, https://doi.org/10.1021/acs.jmedchem.2c01737.

[25] E. Garaci, M. Paci, C. Matteucci, C. Costantini, P. Puccetti, L. Romani, Phenotypic drug discovery: a case for thymosin alpha-1, Front. Med. 11 (2024) 1388959, https://doi.org/10.3389/fmed.2024.1388959.

[26] F. Vincent, A. Nueda, J. Lee, M. Schenone, M. Prunotto, M. Mercola, Phenotypic drug discovery: recent successes, lessons learned and new directions, Nat. Rev. Drug Discov. 21 (12) (2022) 899-914, https://doi.org/10.1038/s41573-022-00472-w.

[27] B.P. Munson, M. Chen, A. Bogosian, J.F. Kreisberg, K. Licon, R. Abagyan, B. M. Kuenzi, T. Ideker, De novo generation of multi-target compounds using deep generative chemistry, Nat. Commun. 15 (1) (2024) 3636, https://doi.org/10.1038/s41467-024-47120-y.

[28] D.E. Mortenson, G.J. Brighty, L. Plate, G. Bare, W. Chen, S. Li, H. Wang, B. F. Cravatt, S. Forli, E.T. Powers, K.B. Sharpless, I.A. Wilson, J.W. Kelly, "Inverse drug discovery" strategy to identify proteins that are targeted by latent electrophiles as exemplified by aryl fluorosulfates, J. Am. Chem. Soc. 140 (1) (2018) 200-210, https://doi.org/10.1021/jacs.7b08366.

[29] S.M. Paul, D.S. Mytelka, C.T. Dunwiddie, C.C. Persinger, B.H. Munos, S. R. Lindborg, A.L. Schacht, How to improve R&D productivity: the pharmaceutical industry's grand challenge, Nat. Rev. Drug Discov. 9 (3) (2010) 203-214, https://doi.org/10.1038/nrd3078.

[30] L.M. Alcântara, T.C.S. Ferreira, F.R. Gadelha, D.C. Miguel, Challenges in drug discovery targeting TriTryp diseases with an emphasis on leishmaniasis, Int J Parasitol Drugs Drug Resist 8 (3) (2018) 430-439, https://doi.org/10.1016/j.ijpddr.2018.09.006.

[31] C. Ye, D.J. Ho, M. Neri, C. Yang, T. Kulkarni, R. Randhawa, M. Henault, N. Mostacci, P. Farmer, S. Renner, R. Ihry, L. Mansur, C.G. Keller, G. McAllister, M. Hild, J. Jenkins, A. Kaykas, DRUG-seq for miniaturized high-throughput transcriptome profiling in drug discovery, Nat. Commun. 9 (1) (2018) 4307, https://doi.org/10.1038/s41467-018-06500-x.

[32] R. Xie, Y. Liu, S. Wang, X. Shi, Z. Zhao, L. Liu, Y. Liu, Z. Li, Combinatorial perturbation sequencing on single cells using microwell-based droplet random pairing, Biosens. Bioelectron. 220 (2023) 114913, https://doi.org/10.1016/j.bios.2022.114913.

[33] V. Gudiño, R. Bartolomé-Casado, A. Salas, Single-cell omics in inflammatory bowel disease: recent insights and future clinical applications, Gut 74 (8) (2025) 1335-1345, https://doi.org/10.1136/gutjnl-2024-334165.

[34] M.D. Carpenter, D.K. Fischer, S. Zhang, A.M. Bond, K.S. Czarnecki, M.T. Woolf, H. Song, E.A. Heller, Cell-type specific profiling of histone post-translational modifications in the adult mouse striatum, Nat. Commun. 13 (1) (2022) 7720, https://doi.org/10.1038/s41467-022-35384-1.

[35] Z. Zheng, J. Chen, X. Chen, L. Huang, W. Xie, Q. Lin, X. Li, K.C. Wong, Enabling single-cell drug response annotations from bulk RNA-seq using SCAD, Adv. Sci. (Weinheim, Baden-Wurttemberg, Germany) 10 (11) (2023) e2204113, https://doi.org/10.1002/advs.202204113.

[36] B. Liu, S. Hu, X. Wang, Applications of single-cell technologies in drug discovery for tumor treatment, iScience 27 (8) (2024) 110486, https://doi.org/10.1016/j.isci.2024.110486.

[37] L. Wen, F. Tang, Recent advances in single-cell sequencing technologies, Precis. Clin. Med. 5 (1) (2022) pbac002, https://doi.org/10.1093/pcmedi/pbac002.

[38] Y. Hou, H. Guo, C. Cao, X. Li, B. Hu, P. Zhu, X. Wu, L. Wen, F. Tang, Y. Huang, J. Peng, Single-cell triple omics sequencing reveals genetic, epigenetic, and transcriptomic heterogeneity in hepatocellular carcinomas, Cell Res. 26 (3) (2016) 304-319, https://doi.org/10.1038/cr.2016.23.

[39] I.C. Macaulay, W. Haerty, P. Kumar, Y.I. Li, T.X. Hu, M.J. Teng, M. Goolam, N. Saurat, P. Coupland, L.M. Shirley, M. Smith, N. Van der Aa, R. Banerjee, P. D. Ellis, M.A. Quail, H.P. Swerdlow, M. Zernicka-Goetz, F.J. Livesey, C.P. Ponting, T. Voet, G&T-seq: parallel sequencing of single-cell genomes and transcriptomes, Nat. Methods 12 (6) (2015) 519-522, https://doi.org/10.1038/nmeth.3370.

[40] H. Chai, X. Huang, G. Xiong, J. Huang, K.K. Pels, L. Meng, J. Han, D. Tang, G. Pan, L. Deng, Q. Xiao, X. Wang, M. Zhang, K. Banecki, D. Plewczynski, C.L. Wei, Y. Ruan, Tri-omic single-cell mapping of the 3D epigenome and transcriptome in whole mouse brains throughout the lifespan, Nat. Methods 22 (5) (2025) 994-1007, https://doi.org/10.1038/s41592-025-02658-7.

[41] S.J. Clark, R. Argelaguet, C.A. Kapourani, T.M. Stubbs, H.J. Lee, C. Alda-Catalinas, F. Krueger, G. Sanguinetti, G. Kelsey, J.C. Marioni, O. Stegle, W. Reik, scNMT-seq enables joint profiling of chromatin accessibility DNA methylation and transcription in single cells, Nat. Commun. 9 (1) (2018) 781, https://doi.org/10.1038/s41467-018-03149-4.

[42] W. Xu, W. Yang, Y. Zhang, Y. Chen, N. Hong, Q. Zhang, X. Wang, Y. Hu, K. Song, W. Jin, X. Chen, ISSAAC-seq enables sensitive and flexible multimodal profiling of chromatin accessibility and gene expression in single cells, Nat. Methods 19 (10) (2022) 1243-1249, https://doi.org/10.1038/s41592-022-01601-4.

[43] Y. Li, Z. Huang, L. Xu, Y. Fan, J. Ping, G. Li, Y. Chen, C. Yu, Q. Wang, T. Song, T. Lin, M. Liu, Y. Xu, N. Ai, X. Meng, Q. Qiao, H. Ji, Z. Qin, S. Jin, N. Jiang, M. Wang, S. Shu, F. Zhang, W. Zhang, G.H. Liu, L. Chen, L. Jiang, UDA-seq: universal droplet microfluidics-based combinatorial indexing for massive-scale multimodal single-cell sequencing, Nat. Methods 22 (2025) 1199-1212, https://doi.org/10.1038/s41592-024-02586-y.

[44] H. Xiong, Q. Wang, C.C. Li, A. He, Single-cell joint profiling of multiple epigenetic proteins and gene transcription, Sci. Adv. 10 (1) (2024) eadi3664, https://doi.org/10.1126/sciadv.adi3664.

[45] Q. Wang, H. Xiong, S. Ai, X. Yu, Y. Liu, J. Zhang, A. He, CoBATCH for highthroughput single-cell epigenomic profiling, Mol. Cell 76 (1) (2019) 206-216.e7, https://doi.org/10.1016/j.molcel.2019.07.015.

[46] S. Ai, H. Xiong, C.C. Li, Y. Luo, Q. Shi, Y. Liu, X. Yu, C. Li, A. He, Profiling chromatin states using single-cell itChIP-seq, Nat. Cell Biol. 21 (9) (2019) 1164-1172, https://doi.org/10.1038/s41556-019-0383-5.

[47] H. Xiong, Y. Luo, Q. Wang, X. Yu, A. He, Single-cell joint detection of chromatin occupancy and transcriptome enables higher-dimensional epigenomic reconstructions, Nat. Methods 18 (6) (2021) 652-660, https://doi.org/10.1038/s41592-021-01129-z.

[48] M. Liu, Y. Yue, X. Chen, K. Xian, C. Dong, M. Shi, H. Xiong, K. Tian, Y. Li, Q. C. Zhang, A. He, Genome-coverage single-cell histone modifications for embryo lineage tracing, Nature 640 (8059) (2025) 828-839, https://doi.org/10.1038/s41586-025-08656-1.

[49] C. Luo, H. Liu, F. Xie, E.J. Armand, K. Siletti, T.E. Bakken, R. Fang, W.I. Doyle, T. Stuart, R.D. Hodge, L. Hu, B.A. Wang, Z. Zhang, S. Preissl, D.S. Lee, J. Zhou, S. Y. Niu, R. Castanon, A. Bartlett, A. Rivkin, X. Wang, J. Lucero, J.R. Nery, D. A. Davis, D.C. Mash, R. Satija, J.R. Dixon, S. Linnarsson, E. Lein, M.M. Behrens, B. Ren, E.A. Mukamel, J.R. Ecker, Single nucleus multi-omics identifies human cortical cell regulatory genome diversity, Cell Genom. 2 (3) (2022), https://doi.org/10.1016/j.xgen.2022.100107.

[50] L. Yu, X. Wang, Q. Mu, S.S.T. Tam, D.S.C. Loi, A.K.Y. Chan, W.S. Poon, H.K. Ng, D. T.M. Chan, J. Wang, A.R. Wu, scONE-seq: a single-cell multi-omics method enables simultaneous dissection of phenotype and genotype heterogeneity from frozen tumors, Sci. Adv. 9 (1) (2023), https://doi.org/10.1126/sciadv.abp8901eabp.8901.

[51] L. Chang, E. Deng, J. Wang, W. Zhou, J. Ao, R. Liu, D. Su, X. Fan, Single-cell thirdgeneration sequencing-based multi-omics uncovers gene expression changes governed by ecDNA and structural variants in cancer cells, Clin. Transl. Med. 13 (8) (2023) e1351, https://doi.org/10.1002/ctm2.1351.

[52] S.G. Kathman, S.J. Koo, G.L. Lindsey, H.L. Her, S.M. Blue, H. Li, S. Jaensch, J. R. Remsberg, K. Ahn, G.W. Yeo, B. Ghosh, B.F. Cravatt, Remodeling oncogenic transcriptomes by small molecules targeting NONO, Nat. Chem. Biol. 19 (7) (2023) 825-836, https://doi.org/10.1038/s41589-023-01270-0.

[53] Z. Tan, S. Qin, H. Liu, X. Huang, Y. Pu, C. He, Y. Yuan, Z. Su, Small molecules reprogram reactive astrocytes into neuronal cells in the injured adult spinal cord, J. Adv. Res. 59 (2024) 111-127, https://doi.org/10.1016/j.jare.2023.06.013.

[54] T. Wang, S. Shi, Y. Shi, P. Jiang, G. Hu, Q. Ye, Z. Shi, K. Yu, C. Wang, G. Fan, S. Zhao, H. Ma, A.C.Y. Chang, Z. Li, Q. Bian, C.P. Lin, Chemical-induced phase transition and global conformational reorganization of chromatin, Nat. Commun. 14 (1) (2023) 5556, https://doi.org/10.1038/s41467-023-41340-4.

[55] F. Perner, E.M. Stein, D.V. Wenge, S. Singh, J. Kim, A. Apazidis, H. Rahnamoun, D. Anand, C. Marinaccio, C. Hatton, Y. Wen, R.M. Stone, D. Schaller, S. Mowla, W. Xiao, H.A. Gamlen, A.J. Stonestrom, S. Persaud, E. Ener, J.A. Cutler, J. G. Doench, G.M. McGeehan, A. Volkamer, J.D. Chodera, R.P. Nowak, E.S. Fischer, R.L. Levine, S.A. Armstrong, S.F. Cai, MEN1 mutations mediate clinical resistance to menin inhibition, Nature 615 (7954) (2023) 913-919, https://doi.org/10.1038/s41586-023-05755-9.

[56] Z. Yu, J. Spiegel, L. Melidis, W.W.I. Hui, X. Zhang, A. Radzevičius, S. Balasubramanian, Chem-map profiles drug binding to chromatin in cells, Nat. Biotechnol. 41 (9) (2023) 1265-1271, https://doi.org/10.1038/s41587-022-01636-0.

[57] C. Dong, X. Meng, T. Zhang, Z. Guo, Y. Liu, P. Wu, S. Chen, F. Zhou, Y. Ma, H. Xiong, S. Shu, A. He, Single-cell EpiChem jointly measures drug-chromatin binding and multimodal epigenome, Nat. Methods 21 (9) (2024) 1624-1633, https://doi.org/10.1038/s41592-024-02360-0.

[58] M. Vicari, R. Mirzazadeh, A. Nilsson, R. Shariatgorji, P. Bjärterot, L. Larsson, H. Lee, M. Nilsson, J. Foyer, M. Ekvall, P. Czarnewski, X. Zhang, P. Svenningsson, L. Käll, P.E. Andrén, J. Lundeberg, Spatial multimodal analysis of transcriptomes and metabolomes in tissues, Nat. Biotechnol. 42 (7) (2024) 1046-1050, https://doi.org/10.1038/s41587-023-01937-y.

[59] P. Guo, L. Mao, Y. Chen, C.N. Lee, A. Cardilla, M. Li, M. Bartosovic, Y. Deng, Multiplexed spatial mapping of chromatin features, transcriptome and proteins in tissues, Nat. Methods 22 (3) (2025) 520-529, https://doi.org/10.1038/s41592-024-02576-0.

[60] A.J. Rubin, K.R. Parker, A.T. Satpathy, Y. Qi, B. Wu, A.J. Ong, M.R. Mumbach, A. L. Ji, D.S. Kim, S.W. Cho, B.J. Zarnegar, W.J. Greenleaf, H.Y. Chang, P.A. Khavari, Coupled single-cell CRISPR screening and epigenomic profiling reveals causal gene regulatory networks, Cell 176 (1-2) (2019) 361-376.e17, https://doi.org/10.1016/j.cell.2018.11.022.

[61] L. Binan, A. Jiang, S.A. Danquah, V. Valakh, B. Simonton, J. Bezney, R.T. Manguso, K.B. Yates, R. Nehme, B. Cleary, S.L. Farhi, Simultaneous CRISPR screening and spatial transcriptomics reveal intracellular, intercellular, and functional transcriptional circuits, Cell 188 (8) (2025) 2141-2158.e18, https://doi.org/10.1016/j.cell.2025.02.012.

[62] L.Y. Zhu, J.B. Yuan, L. Zhang, C.X. He, X. Lin, B. Xu, G.H. Jin, Loss of MLL induces epigenetic dysregulation of Rasgrf1 to attenuate kras-driven lung tumorigenesis, Cancer Res. 82 (22) (2022) 4153-4163, https://doi.org/10.1158/0008-5472.Can-22-1475.

[63] G. Feng, Y. Wu, Y. Hu, W. Shuai, X. Yang, Y. Li, L. Ouyang, G. Wang, Small molecule inhibitors targeting m(6)A regulators, J. Hematol. Oncol. 17 (1) (2024) 30, https://doi.org/10.1186/s13045-024-01546-5.

[64] G.H. Liu, T. Chen, X. Zhang, X.L. Ma, H.S. Shi, Small molecule inhibitors targeting the cancers, MedComm 3 (4) (2022) e181, https://doi.org/10.1002/mco2.181.

[65] W. Zhao, A. Dovas, E.F. Spinazzi, H.M. Levitin, M.A. Banu, P. Upadhyayula, T. Sudhakar, T. Marie, M.L. Otten, M.B. Sisti, J.N. Bruce, P. Canoll, P.A. Sims, Deconvolution of cell type-specific drug responses in human tumor tissue with single-cell RNA-seq, Genome Med. 13 (1) (2021) 82, https://doi.org/10.1186/s13073-021-00894-y.

[66] C. Tlemsani, L. Pongor, F. Elloumi, L. Girard, K.E. Huffman, N. Roper, S. Varma, A. Luna, V.N. Rajapakse, R. Sebastian, K.W. Kohn, J. Krushkal, M.I. Aladjem, B. A. Teicher, P.S. Meltzer, W.C. Reinhold, J.D. Minna, A. Thomas, Y. Pommier, SCLCCellMiner: a resource for small cell lung cancer cell line genomics and pharmacology based on genomic signatures, Cell Rep. 33 (3) (2020) 108296, https://doi.org/10.1016/j.celrep.2020.108296.

[67] M.T. Santaguida, R. Kita, S.A. Schaffert, E.K. Anderson, K.A. Ali, D.C. Strachan, M. Lacher, W.C. Anderson, A. Paul, C.W. Dailey, S. Wen, J.R. Pressley, A. Ling, L. Henry, S. Balasubramanian, K. Dempsey, K. Vanderlaag, J. Wagner, Development of a multiomics and functional drug sensitivity platform to investigate cell type specific drug effects in AML, J. Clin. Oncol. 39 (15_suppl) (2021) e19013, https://doi.org/10.1200/JCO.2021.39.15_suppl.e19013.

[68] J. Engesser, R. Khatri, D.P. Schaub, Y. Zhao, H.J. Paust, Z. Sultana, N. Asada, J. H. Riedel, V. Sivayoganathan, A. Peters, A. Kaffke, S.L. Jauch-Speer, T. GoldbeckStrieder, V.G. Puelles, U.O. Wenzel, O.M. Steinmetz, E. Hoxha, J.E. Turner, H. W. Mittrücker, T. Wiech, T.B. Huber, S. Bonn, C.F. Krebs, U. Panzer, Immune profiling-based targeting of pathogenic T cells with ustekinumab in ANCAassociated glomerulonephritis, Nat. Commun. 15 (1) (2024) 8220, https://doi.org/10.1038/s41467-024-52525-w.

[69] R. Ahmad, B. Budnik, A review of the current state of single-cell proteomics and future perspective, Anal. Bioanal. Chem. 415 (28) (2023) 6889-6899, https://doi.org/10.1007/s00216-023-04759-8.

[70] Á. Végvári, J.E. Rodriguez, R.A. Zubarev, Single-cell chemical proteomics (SCCP) interrogates the timing and heterogeneity of cancer cell commitment to death, Anal. Chem. 94 (26) (2022) 9261-9269, https://doi.org/10.1021/acs.analchem.2c00413.

[71] W. Zhang, D. Maeser, A. Lee, Y. Huang, R.F. Gruener, I.G. Abdelbar, S. Jena, A. G. Patel, R.S. Huang, Integration of pan-cancer cell line and single-cell transcriptomic profiles enables inference of therapeutic vulnerabilities in heterogeneous tumors, Cancer Res. 84 (12) (2024) 2021-2033, https://doi.org/10.1158/0008-5472.Can-23-3005.

[72] Y.C. Hsu, Y.C. Chiu, T.P. Lu, T.H. Hsiao, Y. Chen, Predicting drug response through tumor deconvolution by cancer cell lines, Patterns (N Y) 5 (4) (2024) 100949, https://doi.org/10.1016/j.patter.2024.100949.

[73] M. Lan, S. Zhang, L. Gao, Efficient generation of paired single-cell multiomics profiles by deep learning, Adv. Sci. (Weinheim, Baden-Wurttemberg, Germany) 10 (21) (2023) e2301169, https://doi.org/10.1002/advs.202301169.

[74] L. Gong, H. Sun, L. Liu, X. Sun, T. Fang, Z. Yu, W. Sui, J. Xu, T. Wang, F. Feng, L. Lei, W. Rui, Y. Liu, X. Zhao, G. An, X. Lin, L. Qiu, M. Hao, LILRB4 represents a promising target for immunotherapy by dual targeting tumor cells and myeloidderived suppressive cells in multiple myeloma, Haematologica 109 (11) (2024) 3650-3669, https://doi.org/10.3324/haematol.2024.285099.

[75] K. Khodosevich, K. Dragicevic, O. Howes, Drug targeting in psychiatric disorders how to overcome the loss in translation? Nat. Rev. Drug Discov. 23 (3) (2024) 218-231, https://doi.org/10.1038/s41573-023-00847-7.

[76] A. Zhuang, X. Gu, T. Ge, S. Wang, S. Ge, P. Chai, R. Jia, X. Fan, Targeting histone deacetylase suppresses tumor growth through eliciting METTL14-modified m(6) A RNA methylation in ocular melanoma, Cancer Commun. 43 (11) (2023) 1185-1206, https://doi.org/10.1002/cac2.12471.

[77] S. Lambo, D.L. Trinh, R.E. Ries, D. Jin, A. Setiadi, M. Ng, V.G. Leblanc, M.R. Loken, L.E. Brodersen, F. Dai, L.M. Pardo, X. Ma, S.M. Vercauteren, S. Meshinchi, M. A. Marra, A longitudinal single-cell atlas of treatment response in pediatric AML, Cancer Cell 41 (12) (2023) 2117-2135.e12, https://doi.org/10.1016/j.ccell.2023.10.008.

[78] C. Luo, R. Zhang, R. Guo, L. Wu, T. Xue, Y. He, Y. Jin, Y. Zhao, Z. Zhang, P. Zhang, S. Ye, X. Li, D. Li, W. Zhang, C. Wang, L. Lai, Q. Pan-Hammarström, K. W. Wucherpfennig, Z. Gao, D. Pan, Z. Zeng, Integrated computational analysis identifies therapeutic targets with dual action in cancer cells and T cells, Immunity 58 (3) (2025) 745-765.e9, https://doi.org/10.1016/j.immuni.2025.02.007.

[79] Y. Tan, J. Huang, D. Li, C. Zou, D. Liu, B. Qin, Single-cell RNA sequencing in dissecting microenvironment of age-related macular degeneration: challenges and perspectives, Ageing Res. Rev. 90 (2023) 102030, https://doi.org/10.1016/j.arr.2023.102030.

[80] J. Qi, H. Sun, Y. Zhang, Z. Wang, Z. Xun, Z. Li, X. Ding, R. Bao, L. Hong, W. Jia, F. Fang, H. Liu, L. Chen, J. Zhong, D. Zou, L. Liu, L. Han, F. Ginhoux, Y. Liu, Y. Ye, B. Su, Single-cell and spatial analysis reveal interaction of FAP(+) fibroblasts and SPP1(+) macrophages in colorectal cancer, Nat. Commun. 13 (1) (2022) 1742, https://doi.org/10.1038/s41467-022-29366-6.

[81] C. Chen, X. Zhang, M. Yue, Spatial multi-omics in medicinal plants: from biosynthesis pathways to industrial applications, Trends Plant Sci. 29 (5) (2024) 510-513, https://doi.org/10.1016/j.tplants.2024.02.008.

[82] S. Zhang, Y. Xiao, X. Mo, X. Chen, J. Zhong, Z. Chen, X. Liu, Y. Qiu, W. Dai, J. Chen, X. Jin, G. Fan, Y. Hu, Simultaneous profiling of RNA isoforms and chromatin accessibility of single cells of human retinal organoids, Nat. Commun. 15 (1) (2024) 8022, https://doi.org/10.1038/s41467-024-52335-0.

[83] S. Tietscher, J. Wagner, T. Anzeneder, C. Langwieder, M. Rees, B. Sobottka, N. de Souza, B. Bodenmiller, A comprehensive single-cell map of T cell exhaustionassociated immune environments in human breast cancer, Nat. Commun. 14 (1) (2023) 98, https://doi.org/10.1038/s41467-022-35238-w.

[84] Y.C. Cohen, M. Zada, S.Y. Wang, C. Bornstein, E. David, A. Moshe, B. Li, S. ShlomiLoubaton, M.E. Gatt, C. Gur, N. Lavi, C. Ganzel, E. Luttwak, E. Chubar, O. Rouvio, I. Vaxman, O. Pasvolsky, M. Ballan, T. Tadmor, A. Nemets, O. Jarchowcky-Dolberg, O. Shvetz, M. Laiba, O. Shpilberg, N. Dally, I. Avivi, A. Weiner, I. Amit, Identification of resistance pathways and therapeutic targets in relapsed multiple myeloma patients through single-cell sequencing, Nat. Med. 27 (3) (2021) 491-503, https://doi.org/10.1038/s41591-021-01232-w.

[85] C.J. Frangieh, J.C. Melms, P.I. Thakore, K.R. Geiger-Schuller, P. Ho, A.M. Luoma, B. Cleary, L. Jerby-Arnon, S. Malu, M.S. Cuoco, M. Zhao, C.R. Ager, M. Rogava, L. Hovey, A. Rotem, C. Bernatchez, K.W. Wucherpfennig, B.E. Johnson, O. Rozenblatt-Rosen, D. Schadendorf, A. Regev, B. Izar, Multimodal pooled Perturb-CITE-seq screens in patient models define mechanisms of cancer immune evasion, Nat. Genet. 53 (3) (2021) 332-341, https://doi.org/10.1038/s41588-021-00779-1.

[86] C.E. Eyler, H. Matsunaga, V. Hovestadt, S.J. Vantine, P. van Galen, B.E. Bernstein, Single-cell lineage analysis reveals genetic and epigenetic interplay in glioblastoma drug resistance, Genome Biol. 21 (1) (2020) 174, https://doi.org/10.1186/s13059-020-02085-1.