Jurkat Cells — The Gold-Standard T-Cell Model for Immunology and Leukemia Research

Introduction

Jurkat Cells, also known by synonyms JM, JM-Jurkat, Jurkat-FHCRC, FHCRC-11, and FCCH1024, represent one of the most widely used human T-cell lines in biomedical research. Established in the mid-1970s from the peripheral blood of a patient with childhood T acute lymphoblastic leukemia (also classified as precursor T-cell acute lymphoblastic leukemia), the line was first described by Schneider, Schwenk, and colleagues in landmark publications from 1975 and 1977. [1][2] Over five decades, Jurkat cells have become an indispensable tool for studying T-cell receptor (TCR) signalling, apoptosis, cytokine production, and the molecular biology of T-cell malignancies. Their robust growth in suspension culture, well-characterised immunophenotype, and extensive omics annotation make them a cornerstone reference model across immunology, oncology, and drug discovery.

Key Takeaways

• Jurkat cells (Cellosaurus accession CVCL_0065) are an immortalised human T-cell leukemia line derived from peripheral blood.
• They express CD3, CD4, and CD45 surface markers and carry a functional T-cell receptor complex.
• The line harbours well-characterised mutations in BAX, TP53, NOTCH1, PTEN/INPP5D, MSH2, and MSH6, making it microsatellite-instability high (MSI-high).
• Jurkat cells are central to TCR signalling research and established much of the current understanding of T-cell activation pathways.
• They serve as a preferred model for apoptosis studies, leukemia drug testing, and emerging CAR-T cell technology development.
• Extensive multi-omics data — including proteomics, phosphoproteomics, DNA methylation, and drug sensitivity profiles — are publicly available for this line.

What is the Jurkat Cell Line?

Jurkat was derived from the peripheral blood of a 14-year-old male patient with childhood T acute lymphoblastic leukemia (precursor T-cell acute lymphoblastic leukemia). The line was established by Schneider and Schwenk, who first reported it as the "JM" cell line in 1975, demonstrating that T-cell markers were expressed throughout the cell cycle. [1] Subsequent characterisation confirmed its EBV-genome-negative status and T-cell lineage identity. [2][3] Early antigenic studies by Kaplan and Peterson showed that T-cell lymphoma-associated antigens detected on this line were also present on cord blood lymphocytes, linking the model to physiological T-cell biology. [4]

Immunophenotypically, Jurkat cells express CD3, CD4, and CD45, display a rearranged T-cell receptor, and lack c-kit expression, consistent with a lymphoid lineage. [5][6] The TCR gene rearrangement profile is well-defined and has been employed as a reference standard in clonality diagnostics. [7] Cytogenetically, the line is hypotetraploid with a characteristic deletion in the short arm of chromosome 2 and displays MSI-high status. [8] Key somatic mutations include loss-of-function mutations in MSH2 (nonsense) and MSH6 (frameshift) and BAX, a heterozygous NOTCH1 mutation, heterozygous TP53 nonsense mutation, and biallelic inactivation of INPP5D (SHIP1), reflecting the complex genomic landscape of T-cell malignancies.

Cell Culture Information

Jurkat Cells – niedrige Konfluenz

Jurkat Cells – hohe Konfluenz

Advantages of Jurkat Cells

Jurkat cells offer a uniquely robust platform for studying human T-cell biology. They grow rapidly in suspension with a doubling time of 25–35 hours, making them well-suited for large-scale biochemical and functional assays. The line expresses a complete, signalling-competent TCR–CD3 complex alongside the CD4 co-receptor, faithfully recapitulating key aspects of helper T-cell biology. Their amenability to genetic manipulation — evidenced by the enormous catalogue of derivative knockout and reporter lines — allows investigators to dissect individual signalling components with precision. The cell line has been fully authenticated by STR profiling and is negative for mycoplasma and non-inherent viral contamination, ensuring experimental reproducibility. [9][10]

The breadth of publicly available multi-omics data for Jurkat cells is unparalleled among T-cell lines. The line is included in the Cancer Cell Line Encyclopedia (CCLE), the LL-100 blood cancer panel, the ENCODE project, and the Cancer Dependency Map, providing researchers with genome-wide genetic, transcriptomic, proteomic, and drug-sensitivity annotation. [11][12][13] This rich annotation enables comparative and integrative analyses that would be impractical with primary T-cell isolates. Furthermore, the well-characterised mutational background — including defined deficiencies in PTEN/SHIP1 and DNA mismatch repair — makes Jurkat cells a tractable model for studying PI3K-Akt pathway deregulation and genomic instability simultaneously. [14][15]

For drug discovery applications, the suspension growth format simplifies compound exposure and sampling. Jurkat cells respond robustly to TCR stimulation, cytokine treatment, and pro-apoptotic stimuli, generating reproducible, quantifiable readouts in cytokine assays, flow cytometry, and viability assays. Their responsiveness to both classical chemotherapeutics and novel targeted agents has made them a first-line screening tool in leukemia drug development. Their participation in landmark pharmacogenomic studies such as the CCLE has further validated their predictive utility. [16][17]

Limitations of Jurkat Cells

Despite their widespread use, Jurkat cells carry several well-documented genetic aberrations that can confound experimental interpretation. The line lacks functional BAX protein expression due to biallelic frameshift mutations, rendering it intrinsically resistant to certain pro-apoptotic stimuli that depend on this effector. [15] The biallelic inactivation of SHIP1 (INPP5D) and the loss of functional PTEN result in constitutive PI3K-Akt pathway activation, which may skew results in signalling studies. [14][18] Investigators must therefore interpret apoptosis and survival data in the context of these specific deficiencies, and should validate key findings in primary T cells or alternative models.

The line is MSI-high due to homozygous loss-of-function mutations in the mismatch repair genes MSH2 and MSH6, leading to elevated rates of secondary mutation accumulation over prolonged culture. [19][20] This genomic instability means that different laboratory stocks may have diverged in their mutational profiles, underscoring the importance of regular cell line authentication by STR profiling and adherence to low-passage banking. The hypotetraploid karyotype, heterogeneity in ploidy, and the characteristic chromosome 2p deletion introduce additional complexity when interpreting gene dosage effects. [8]

As a transformed cancer cell line, Jurkat cells do not fully recapitulate the biology of normal primary human T lymphocytes. Notably, the line harbours activating NOTCH1 mutations and a heterozygous TP53 nonsense mutation, features associated with malignant transformation rather than normal T-cell physiology. [21][22] Results obtained in Jurkat cells — particularly those related to cytotoxic effector function, exhaustion, or differentiation — should therefore be validated in primary T-cell systems or appropriate in vivo models before translational conclusions are drawn.

Applications of Jurkat Cells in Research

T-Cell Receptor Signalling and Immune Activation

Jurkat cells have served as the cornerstone model for decoding T-cell receptor signalling for nearly five decades. The landmark review by Abraham and Weiss (2004) — the single most-cited paper associated with this cell line — comprehensively chronicled how studies in Jurkat cells established the fundamental framework of TCR signalling. [23] That work demonstrated that Jurkat-based experiments uncovered the roles of Lck, ZAP-70, and LAT as essential proximal kinases and adaptors downstream of TCR engagement, discoveries that remain foundational to modern immunology. Virtually every major node of the TCR-to-NFAT/NF-κB/AP-1 signalling axis was first characterised or validated in this cell line. [23]

Recent studies continue to leverage Jurkat cells for T-cell activation research. Investigations into the immunomodulatory properties of sulforaphane used Jurkat cells to demonstrate that this natural isothiocyanate attenuates early T-cell activation events, including IL-2 production, CD25 induction, and cytokine secretion following TCR stimulation. [24] These findings establish a mechanistic basis for the anti-inflammatory effects of dietary cruciferous compounds. Similarly, a study of interleukin-2 inducible T-cell kinase (ITK) inhibitors used Jurkat cells to validate that novel covalent pyrazole-based compounds potently suppress downstream phosphorylation and IL-2 secretion following TCR stimulation, with in vivo efficacy in a murine model. [25]

Jurkat cells have also been used to investigate how transcription factors modulate T-cell identity in pathological contexts. A study of TCF7 deficiency in chronic obstructive pulmonary disease (COPD)-related immune dysregulation employed TCF7-knockout Jurkat cells alongside primary patient T cells to validate a three-gene disease signature. Western blotting of TCF7-deficient Jurkat cells with genetic rescue confirmed the role of TCF7 in maintaining T-cell lymphoid gene programmes. [26] Additionally, experiments examining STUB1-mediated ubiquitination of the Fli-1 transcription factor used Jurkat cells as an in vitro platform to characterise the STUB1/Fli-1 signalling axis relevant to CD4⁺ T-cell activation during inflammation. [27]

Apoptosis and Cell Death Mechanisms

Jurkat cells have long been a standard model for dissecting apoptotic signalling pathways in T cells, notwithstanding their BAX deficiency. Research into the regulation of mitochondrial autophagy used CRISPR/Cas9-mediated FADD knockout Jurkat cells to demonstrate that FADD governs mitochondrial number via PGC1-α-dependent and autophagy-related mechanisms. [28] Rapamycin-induced autophagy and chloroquine-mediated inhibition experiments, monitored by LC3B Western blot and mtCO1/β-globin qPCR, confirmed that FADD plays a regulatory role in mitophagy independently of its canonical death receptor function.

A mechanistically important study of cyclin-dependent kinase (CDK) inhibitors used Jurkat cells alongside other leukemia models to establish that CDK9 and CDK12/13 — but not cell-cycle-relevant CDKs — drive apoptosis through transcriptional repression of the short-lived anti-apoptotic proteins Mcl-1 and Bfl-1/A1. [29] Specific inhibitors AZD4573, atuveciclib, SR4835, and THZ531 produced strong apoptotic responses in Jurkat cells, delineating the mechanistic basis for their clinical potential. These findings clarify why CDK inhibitors targeting RNA polymerase II elongation are more cytotoxic than those targeting cell-cycle CDKs.

Studies of microRNA regulation used Jurkat cells to explore how LNA-anti-miR-92b and LNA-anti-miR-181b modulate BAX, BCL-2, and MCL-1 gene expression in acute lymphoblastic leukemia. [30] Piperine, a natural alkaloid, was shown to sensitise Jurkat cells by altering miRNA profiles and shifting the balance toward pro-apoptotic BCL-2 family members. Separately, a scoping review highlighted in vitro evidence that docosahexaenoic acid (DHA) exerts dose- and time-dependent cytotoxic effects in Jurkat cells via pro-apoptotic pathways, with synergistic effects when combined with standard chemotherapeutic agents used in paediatric ALL. [31] Historical characterisation confirmed that the absence of BAX protein in Jurkat cells results from single base deletions in the coding microsatellite, with functional consequences for apoptotic resistance. [15]

Leukemia Biology and Drug Discovery

As a model of childhood T acute lymphoblastic leukemia (precursor T-cell ALL), Jurkat cells have been integral to characterising the molecular genetics of T-cell malignancies. Seminal work established that more than 50% of human T-ALLs harbour activating NOTCH1 mutations, a finding validated and extended using the Jurkat cell line and other T-ALL models. [21] Comprehensive mutation analyses have identified frequent alterations in p53, p16/p15, PTEN, and DNA mismatch repair genes across T-ALL cell lines including Jurkat, painting a detailed genomic portrait of this disease. [32][33][34][18]

Drug repurposing strategies have employed Jurkat cells alongside other leukemia models to evaluate novel anticancer agents. A recent study examined the cytotoxic potential of chemically modified tetracycline analogues — including COL-3, doxycycline, and minocycline — in Jurkat, K562, and KG-1a cells. [35] COL-3 displayed the highest potency and modulated the JAK2/STAT3 pathway and BCL-2 family proteins, demonstrating the utility of Jurkat cells in mechanistic drug profiling. Jurkat cells have further been used to assess targeted drug delivery systems: an anti-CD22-ScFv-decorated β-cyclodextrin metal-organic framework nanoplatform loaded with daunorubicin was evaluated for selectivity in CD22-positive versus CD22-negative (Jurkat) cells, validating the specificity of the targeting system. [36]

Large-scale pharmacogenomic initiatives have included Jurkat cells as part of their reference panels. The Cancer Cell Line Encyclopedia (CCLE) and related landscape pharmacogenomic studies profiled Jurkat cells for drug sensitivity across hundreds of compounds, linking genomic features to therapeutic vulnerabilities. [11][16] Integrative multi-omics analyses of childhood ALL cell lines, including Jurkat, identified lineage-dependent drug response correlations and novel therapeutic candidates, providing a framework for precision medicine in paediatric leukemia. [17] Authenticity studies confirmed that the line maintains stable growth characteristics and genetic fingerprints over long-term culture. [37]

Proteomics, Glycomics, and Multi-Omics Research

Jurkat cells have become a reference standard for large-scale proteomics and post-translational modification (PTM) profiling. A landmark quantitative acetylome study using high-resolution mass spectrometry — including Jurkat cells — identified 3,600 lysine acetylation sites on 1,750 proteins, revealing that acetylation preferentially targets large macromolecular complexes and co-regulates major cellular functions including chromatin remodelling and cell cycle progression. [38] Similarly, the UbiSite methodology used Jurkat cells to identify over 63,000 unique ubiquitination sites on 9,200 proteins, including widespread N-terminal ubiquitination, advancing the field of ubiquitin biology. [39]

Phosphoproteomics efforts have also relied heavily on Jurkat cells. The Augmented Multiple-Protease-Based Human Phosphopeptide Atlas incorporated Jurkat data to define a less biased atlas of 37,771 unique phosphopeptides and 18,430 unique phosphosites, demonstrating the tryptic bias in public repositories and the value of multi-enzyme approaches. [40] Comparative proteomic analyses across eleven common cell lines, including Jurkat, revealed that despite distinct cellular origins, proteome coverage remains surprisingly consistent, with cell-type-specific expression patterns emerging for key signalling proteins. [41] Pan-cancer proteomic mapping of 949 cancer cell lines further positioned Jurkat within a broad landscape of protein biomarkers linked to drug sensitivity and cancer vulnerability. [42]

Glycomics studies have characterised the N-glycan profiles of Jurkat cell membrane proteins, revealing cell-type-specific patterns in sialic acid linkage and glycosyltransferase expression that distinguish Jurkat from B-cell and myeloid lines. [43] A comprehensive quantitative proteomics study of protein O-GlcNAcylation used Jurkat cells as one of three human cell models to demonstrate cell-type-specific and common responses of the O-GlcNAc modification under N-glycosylation inhibition, identifying over 1,000 O-GlcNAcylated proteins. [44] Dynamic DNA methylation profiling across 82 human cell lines, including Jurkat, illuminated the relationship between methylation patterns, gene expression, and cancer-specific epigenetic signatures. [45]

CAR-T Cell Technology and Immunotherapy

Jurkat cells have found a prominent role in the emerging field of CAR-T cell technology and synthetic receptor engineering. A proof-of-concept study developed a label-free rapid optical imaging (ROI) biosensor with machine-learning analysis for direct quantification of CAR-T cells from whole blood, using Jurkat cells spiked into blood samples to validate detection performance. [46] This approach addressed the critical clinical need for real-time monitoring of CAR-T cell expansion without the costs and delays of conventional laboratory methods.

In the context of next-generation therapeutic receptor platforms, Jurkat cells served as the primary in vitro validation system for comparing SNIPR, synNotch, and TRUCK synthetic receptor architectures adapted for Alzheimer's disease. [47] All three platforms were expressed in Jurkat cells using an amyloid-beta-targeting binding domain, and receptor-driven transgene expression was quantified to benchmark their relative performance. Jurkat cells also contributed to an assessment of a novel hypothermic preservation formulation (SUL-138) for clinical-grade CAR-T cell products, where Jurkat cells served as a model T-cell substrate to evaluate mitochondrial stability and cell viability during cold storage and rewarming. [48]

Jurkat cells have additionally been employed as a source of small extracellular vesicles (sEVs) for nanomedicine applications. sEVs isolated from Jurkat cells by size-exclusion chromatography were loaded with curcumin via sonication to generate a targeted therapeutic formulation for oral squamous cell carcinoma. [49] In vitro and in vivo assays demonstrated that Jurkat-derived sEVs enhanced curcumin's tumour-suppressive effects, illustrating the versatility of this cell line as a biological material source beyond its classical use as a signalling model. An acellular normothermic spleen perfusion platform further validated steroid immunosuppression mechanisms using effluent T cells compared against Jurkat cell transcriptional benchmarks. [50]

Conclusion

Jurkat cells (CVCL_0065) have earned their status as the gold-standard human T-cell model through five decades of transformative contributions across immunology, oncology, and molecular biology. From elucidating the core TCR signalling paradigm to enabling cutting-edge CAR-T cell research, this precursor T-cell acute lymphoblastic leukemia-derived line continues to underpin discoveries of fundamental and translational importance. Its well-characterised mutational landscape, extensive multi-omics annotation, and tractability for genetic engineering make it an irreplaceable tool — provided researchers account for its specific genetic limitations. Whether your research addresses T-cell activation, apoptosis, leukemia drug sensitivity, or next-generation immunotherapy, Jurkat Cells provide a proven, well-validated foundation. Explore the full specifications, including the Jurkat E6.1 Cells subclone, or place an order at cytion.com.

Key Publications

1. Schwenk HU, Schneider U (1975) Cell cycle dependency of a T-cell marker on lymphoblasts. Blut. PMID: 1103999
2. Schneider U, Schwenk HU, Bornkamm G (1977) Characterization of EBV-genome negative "null" and "T" cell lines derived from children with acute lymphoblastic leukemia and leukemic transformed non-Hodgkin lymphoma. International journal of cancer. PMID: 68013
3. Schneider U, Schwenk HU (1977) Characterization of "T" and "non-T" cell lines established from children with acute lymphoblastic leukemia and non-Hodgkin lymphoma after leukemic transformation. Haematology and blood transfusion. PMID: 204546
4. Kaplan J, Peterson WD Jr (1976) Detection of T-cell lymphoma-associated antigens on cord blood lymphocytes and phytohemagglutinin-stimulated blasts. Cancer research. PMID: 1086134
5. Morita S, Tsuchiya S, Fujie H (1996) Cell surface c-kit receptors in human leukemia cell lines and pediatric leukemia: selective preservation of c-kit expression on megakaryoblastic cell lines during adaptation to in vitro culture. Leukemia. PMID: 8558913
6. Burger R, Hansen-Hagge TE, Drexler HG (1999) Heterogeneity of T-acute lymphoblastic leukemia (T-ALL) cell lines: suggestion for classification by immunophenotype and T-cell receptor studies. Leukemia research. PMID: 9933131
7. Sandberg Y, Verhaaf B, van Gastel-Mol EJ (2007) Human T-cell lines with well-defined T-cell receptor gene rearrangements as controls for the BIOMED-2 multiplex polymerase chain reaction tubes. Leukemia. PMID: 17170727
8. LaGree KA, Lee AT, Stetten G (1988) The human Jurkat (FHCRC-11) cell line is heterogeneous in ploidy and cell size and releases detergent-soluble DNA. Experimental hematology. PMID: 3165345
9. Raimondi V, Minuzzo S, Ciminale V (2017) STR Profiling of HTLV-1-Infected Cell Lines. Methods in molecular biology (Clifton, N.J.). PMID: 28357668
10. Uphoff CC, Pommerenke C, Denkmann SA (2019) Screening human cell lines for viral infections applying RNA-Seq data analysis. PloS one. PMID: 30629668
11. Barretina J, Caponigro G, Stransky N (2012) The Cancer Cell Line Encyclopedia enables predictive modelling of anticancer drug sensitivity. Nature. PMID: 22460905
12. Quentmeier H, Pommerenke C, Dirks WG (2019) The LL-100 panel: 100 cell lines for blood cancer studies. Scientific reports. PMID: 31160637
13. Ghandi M, Huang FW, Jané-Valbuena J (2019) Next-generation characterization of the Cancer Cell Line Encyclopedia. Nature. PMID: 31068700
14. Lo TC, Barnhill LM, Kim Y (2009) Inactivation of SHIP1 in T-cell acute lymphoblastic leukemia due to mutation and extensive alternative splicing. Leukemia research. PMID: 19473701
15. Brimmell M, Mendiola R, Mangion J (1998) BAX frameshift mutations in cell lines derived from human haemopoietic malignancies are associated with resistance to apoptosis and microsatellite instability. Oncogene. PMID: 9583678
16. Iorio F, Knijnenburg TA, Vis DJ (2016) A Landscape of Pharmacogenomic Interactions in Cancer. Cell. PMID: 27397505
17. Leo IR, Aswad L, Stahl M (2022) Integrative multi-omics and drug response profiling of childhood acute lymphoblastic leukemia cell lines. Nature communications. PMID: 35354797
18. Sakai A, Thieblemont C, Wellmann A (1998) PTEN gene alterations in lymphoid neoplasms. Blood. PMID: 9787181
19. Hosoya N, Hangaishi A, Ogawa S (1998) Frameshift mutations of the hMSH6 gene in human leukemia cell lines. Japanese journal of cancer research : Gann. PMID: 9510473
20. Inoue K, Kohno T, Takakura S (2000) Frequent microsatellite instability and BAX mutations in T cell acute lymphoblastic leukemia cell lines. Leukemia research. PMID: 10739008
21. Weng AP, Ferrando AA, Lee W (2004) Activating mutations of NOTCH1 in human T cell acute lymphoblastic leukemia. Science (New York, N.Y.). PMID: 15472075
22. Cheng J, Haas M (1990) Frequent mutations in the p53 tumor suppressor gene in human leukemia T-cell lines. Molecular and cellular biology. PMID: 2144611
23. Abraham RT, Weiss A (2004) Jurkat T cells and development of the T-cell receptor signalling paradigm. Nature reviews. Immunology. PMID: 15057788
24. Fu Q, Gardner EM, Rockwell CE (2026) The Plant Compound Sulforaphane Attenuates Induction of Cytokines and Other Early Activation Events in Jurkat Cells. Journal of dietary supplements. PMID: 42152521
25. Ruan Z, Pan Z (2026) Discovery of pyrazole-based selective covalent ITK inhibitors with In vivo activity. European journal of medicinal chemistry. PMID: 42224937
26. Wang Z, Yang Y, Wang L (2026) Unfolding Immune Dysregulation in COPD: Identification of a Three-Gene Signature and Functional Validation of TCF7 in Human Lung Tissue and T Lymphocytes. International journal of molecular sciences. PMID: 42196213
27. Li P, Liu L, Wu Y (2026) STUB1-mediated ubiquitination regulates Fli-1 stability and CD4⁺T cell activation during inflammation. Molecular medicine (Cambridge, Mass.). PMID: 42192504
28. Lin CZ, Zhu ZX, Zhong Q (2026) [Regulation of Mitochondrial Autophagy by FADD in Jurkat Cells]. Zhongguo shi yan xue ye xue za zhi. PMID: 42227456
29. Krings KS, Hatzfeld J, Weller S (2026) Inhibition of RNA polymerase II-activating CDK9 and CDK12/13, but not of cell cycle relevant CDKs, induces apoptosis by downregulating the short-lived Bcl-2 proteins Mcl1 and Bfl1/A1. Cell death & disease. PMID: 42204137
30. Torkamani M, Forghanifard MM, Zarrinpour V (2025) Investigating the Impact of LNA-anti-miR-92b, miR-181b, TNF-α, and Piperine on Gene Expression and Cell Viability in Jurkat Cells: Implications for Acute Lymphoblastic Leukemia. Galen medical journal. PMID: 42038900
31. Bittencourt VB, Schveitzer MC, da Costa RF (2026) Omega-3 fatty acids in pediatric acute lymphocytic leukemia: A scoping review. Clinical nutrition ESPEN. PMID: 42107536
32. Kawamura M, Ohnishi H, Guo SX (1999) Alterations of the p53, p21, p16, p15 and RAS genes in childhood T-cell acute lymphoblastic leukemia. Leukemia research. PMID: 10071127
33. Siebert R, Willers CP, Schramm A (1995) Homozygous loss of the MTS1/p16 and MTS2/p15 genes in lymphoma and lymphoblastic leukaemia cell lines. British journal of haematology. PMID: 8547074
34. Borgonovo Brandter L, Heyman M, Rasool O (1996) p16INK4/p15INK4B gene inactivation is a frequent event in malignant T-cell lines. European journal of haematology. PMID: 8641406
35. Hassan ZM, Mamand DR, El-Gawly HW (2026) Differential Modulation of JAK/STAT3 Signaling and BCL-2 Family Proteins by Tetracycline Analogues in Leukemia Models. Pharmaceutics. PMID: 42076067
36. Khabiri A, Rastegari B, Rafiei Dehbidi G (2026) Target-specific daunorubicin nanoplatform based on anti-CD22-ScFv decorated β-cyclodextrin metal organic frameworks. Therapeutic delivery. PMID: 42183612
37. Beesley AH, Palmer ML, Ford J (2006) Authenticity and drug resistance in a panel of acute lymphoblastic leukaemia cell lines. British journal of cancer. PMID: 17117183
38. Choudhary C, Kumar C, Gnad F (2009) Lysine acetylation targets protein complexes and co-regulates major cellular functions. Science (New York, N.Y.). PMID: 19608861
39. Akimov V, Barrio-Hernandez I, Hansen SVF (2018) UbiSite approach for comprehensive mapping of lysine and N-terminal ubiquitination sites. Nature structural & molecular biology. PMID: 29967540
40. Giansanti P, Aye TT, van den Toorn H (2015) An Augmented Multiple-Protease-Based Human Phosphopeptide Atlas. Cell reports. PMID: 26074081
41. Geiger T, Wehner A, Schaab C (2012) Comparative proteomic analysis of eleven common cell lines reveals ubiquitous but varying expression of most proteins. Molecular & cellular proteomics : MCP. PMID: 22278370
42. Gonçalves E, Poulos RC, Cai Z (2022) Pan-cancer proteomic map of 949 human cell lines. Cancer cell. PMID: 35839778
43. Reinke SO, Bayer M, Berger M (2012) The analysis of N-glycans of cell membrane proteins from human hematopoietic cell lines reveals distinctions in their pattern. Biological chemistry. PMID: 22944676
44. Fu L, Yin K, Xu X (2026) Systematic Quantification of Protein O-GlcNAcylation Reveals Common and Cell-Type-Specific Responses to N-Glycosylation Inhibition in Human Cells. Analytical chemistry. PMID: 42153620
45. Varley KE, Gertz J, Bowling KM (2013) Dynamic DNA methylation across diverse human cell lines and tissues. Genome research. PMID: 23325432
46. Yu N, Porter RM, Zhou X (2026) Machine Learning-Assisted Rapid Optical Imaging for Label-Free CAR T-Cell Detection in Whole Blood. Biosensors. PMID: 42187436
47. Siebrand CJ, Mayeri Z, Brown I (2026) In vitro comparison of Aβ-targeting SNIPR, synNotch, and TRUCK for cell-based drug delivery in Alzheimer's disease. bioRxiv : the preprint server for biology. PMID: 42146485
48. Öner A, Nooteboom N, Oosting L (2026) A Novel Hypothermic Preservation Formulation Containing SUL-138 Enables Long-Term Hypothermic Storage of Clinical-Grade CAR-T Cells. Pharmaceutics. PMID: 42076066
49. Ludwig N, Feldmann C, Spoerl S (2026) Extracellular Vesicle-Mediated Delivery of Curcumin Suppresses Tumor Progression in Murine Oral Squamous Cell Carcinoma. Cancers. PMID: 42192945
50. Callais NA, Welch S, Rainwater RR (2026) Acellular normothermic spleen perfusion resolves transcriptional and non-transcriptional mechanisms of steroid immunosuppression. bioRxiv : the preprint server for biology. PMID: 42239436