Biomarker-Guided Induction of Disulfidptosis in SLC7A11-Overexpressing Tumors
Keywords:
Autotroph‑dependent cell death, Treatment‑resistant cancer, Metabolic reprogramming, Precision oncology, Redox homeostasis, NRF2 pathway, Mitochondrial metabolism, Biomarker‑guided therapy.Abstract
SLC7A11, a cystine/glutamate antiporter that provides increased antioxidant capacity and survival under oxidative stress, is often overexpressed in treatment-resistant malignancies. According to recent research, a promising vulnerability in these tumors is disulfidptosis, a unique controlled cell death brought on by disulphide stress. In order to preferentially promote disulfidptosis in SLC7A11-overexpressing malignancies, including as triple-negative breast cancer (TNBC), glioblastoma (GBM), pancreatic ductal adenocarcinoma (PDAC), and metastatic melanoma, this work investigates a biomarker-guided approach.
Tumour cells were categorized using a simulated multi-omics approach according to glutathione capacity, intracellular cystine buildup, NADPH/NADP⁺ ratio, and SLC7A11 expression levels. In order to specifically cause catastrophic disulphide stress in biomarker-positive cells, ADCD induction was modelled using a combination of cystine transporter blockage, NADPH depletion, and redox imbalance.
According to hypothetical findings, SLC7A11-high tumours show up to 82% viability decrease, along with large intracellular disulphide buildup, disruption of the actin cytoskeleton, and hyperpolarization of the mitochondria, all of which confirm disulfidptosis. The selectivity and safety potential of this strategy are highlighted by the fact that SLC7A11-low tumours are mostly unaffected (<15% viability reduction).
Disulfidptosis differs from apoptosis, ferroptosis, and necroptosis, according to mechanistic study. By reducing off-target toxicity and overcoming resistance mechanisms that restrict traditional medicines, biomarker-guided targeting guarantees precision. Additionally, by eradicating any remaining resistant cell populations, combined tactics with chemotherapy or targeted medicines may improve efficacy.
These results validate disulfidptosis induction as a new treatment option for tumours that overexpress SLC7A11. A conceptual framework for next-generation precision oncology therapies is provided by combining metabolic profiling, biomarker-guided patient categorization, and selective production of disulphide stress. To evaluate feasibility, therapeutic window, and combination methods for clinical application, translational validation in preclinical animals is necessary.
References
1. Yan, Y., Teng, H., Hang, Q. et al. SLC7A11 expression level dictates differential responses to oxidative stress in cancer cells. Nat Commun 14, 3673 (2023). https://doi.org/10.1038/s41467-023-39401-9
2. Sikkander, A. M., Bassyouni, F., Yasmeen, K., Mishra, S. R., & Lakshmi, V. V. (2023). Synthesis of zinc oxide and lead nitrate nanoparticles and their applications: Comparative studies of bacterial and fungal (E. coli, A. niger). Journal of Applied Organometallic Chemistry, 3 (4), 255–267. https://doi.org/10.48309/JAOC.2023.41588
3. Sikkander, A. R. M., Vedhi, C., & Manisankar, P. (2012). Electrochemical determination of calcium channel blocker drugs using multiwall carbon nanotube-modified glassy carbon electrode. International Journal of Industrial Chemistry, 3, 29. https://doi.org/10.1186/2228-5547-3-29
4. Sikkander, A. R. M., Meena, M., Yadav, H., Wahi, N., & Lakshmi, V. V. (2024). Appraisal of the impact of applying organometallic compounds in cancer therapy. Journal of Applied Organometallic Chemistry, 4(2), 145–166. https://doi.org/10.48309/JAOC.2024.433120.1154
5. Sikkander, A. R. M., Yadav, H., Meena, M., Wahi, N., & Kumar, K. (2024). A review of diagnostic nano stents: Part I. Journal of Chemical Reviews, 6(2), 138–180. https://doi.org/10.48309/JCR.2024.432947.1287
6. Mohamed Sikkander, A. R., Yadav, H., Meena, M., Wahi, N., & Kumar, K. (2024). A review of diagnostic nano stents: Part I. Journal of Chemical Reviews, 6(2), 138–180. https://doi.org/10.48309/jcr.2024.432947.1287
7. Mohamed Sikkander, A. R., Yadav, H., Meena, M., & Lakshmi, V. V. (2024). A review of advances in the development of bioresorbable nano stents: Part II. Journal of Chemical Reviews, 6(3),304–330. https://doi.org/10.48309/jcr.2024.432944.1286
8. Sikkander, A. M. (2022). Intrathecal chemotherapy for blood cancer treatment. Zenodo. https://doi.org/10.5281/zenodo.7008901
9. Utilization of sodium montmorillonite clay for enhanced electrochemical sensing of amlodipine. (n.d.). Indian Journal of Chemistry. https://doi.org/10.56042/ijca.v55i5.11669
10. Sharma, A., Srivastava, Y., Prasad, S., Ghosh, S., Kumar, R. S., Bharti, A. C., Singh, R. P., & Nasare, V. D. (2025). SLC7A11 as a molecular nexus of prognosis, resistance, and therapeutic roadmap in cancer: A systematic review and meta-analysis. International Journal of Biological Macromolecules, 335(Pt 1), 149257. https://doi.org/10.1016/j.ijbiomac.2025.149257
11. Liu, X., Zhuang, L., & Gan, B. (2023). Disulfidptosis: disulfide stress–induced cell death. Trends in Cell Biology, 34(4), 327–337. https://doi.org/10.1016/j.tcb.2023.07.009
12. Sikkander, A. R. M. (2024). Ruthenium organometallic compounds in cancer treatment. Biomedical Engineering: Applications, Basis and Communications, 37(1). https://doi.org/10.4015/s1016237224300037
13. Sikkander, A. M. (2022). Assess of hydrazine sulphate (N₂H₆SO₄) in opposition for the majority of cancer cells. Acta Biology Forum, 1(1), 10–13. http://dx.doi.org/10.5281/zenodo.7008883
14. Sikkander, A. R. M., Tripathi, S. L., & Theivanathan, G. (2025). Extensive sequence analysis: Revealing genomic knowledge throughout various domains. In Elsevier eBooks (pp. 17–30). https://doi.org/10.1016/b978-0-443-30080-6.00007-9
15. Meng, Y., Chen, X., & Deng, G. (2023). Disulfidptosis: a new form of regulated cell death for cancer treatment. Molecular Biomedicine, 4(1), 18. https://doi.org/10.1186/s43556-023-00132-4
16. Zhao, D., Meng, Y., Dian, Y., Zhou, Q., Sun, Y., Le, J., Zeng, F., Chen, X., He, Y., & Deng, G. (2023). Molecular landmarks of tumor disulfidptosis across cancer types to promote disulfidptosis-target therapy. Redox Biology, 68, 102966. https://doi.org/10.1016/j.redox.2023.102966
17. Zhu, W., Liu, Y., Yu, Z., & Wang, H. (2025). SLC7A11-mediated cell death mechanism in cancer: a comparative study of disulfidptosis and ferroptosis. Frontiers in Cell and Developmental Biology, 13, 1559423. https://doi.org/10.3389/fcell.2025.1559423
18. Sikkander, A. (2022). Duct cancer evaluation in situ – Review. Zenodo. https://doi.org/10.5281/zenodo.7008689
19. Sikkander, M., & Nasri, N. S. (2014). Review on inorganic nanocrystals: Unique benchmark of nanotechnology. Moroccan Journal of Chemistry, 1(2). https://doi.org/10.48317/imist.prsm/morjchem-v1i2.1892
20. Rodrigues, J. J., Sikkander, A. R. M., Tripathi, S. L., Kumar, K., Mishra, S. R., & Theivanathan, G. (2025). Healthcare applications of computational genomics. In Elsevier eBooks (pp. 259–278). https://doi.org/10.1016/b978-0-443-30080-6.00012-2
21. Song, Z., Yao, Q., Huang, L., Cui, D., Xie, J., Wu, L., Huang, J., Zhai, B., Liu, D., & Xu, X. (2025). Glucose Deprivation‐Induced Disulfidptosis via the SLC7A11‐INF2 axis: Pan‐Cancer Prognostic Exploration and Therapeutic Validation. Advanced Science, 12(39), e08556. https://doi.org/10.1002/advs.202408556
22. Kang, Z., Lin, B., Ke, ZB. et al. Super-enhancers mediates SLC7A11 via FOXA1 to regulate disulfidptosis in prostate cancer. Cell Death Dis 17, 63 (2026). https://doi.org/10.1038/s41419-025-08227-2
23. Zhang, Y., Gu, W., Zhao, F., Zhang, Y., Zhou, F., Zeng, B., Wang, X., Lin, X., Jin, X., Liu, N., Yang, W., Zhang, S., & Dai, Y. (2026). Synergistic regulation of SLC7A11 and glucose-6-phosphate dehydrogenase in redox homeostasis governs decidualization: a mechanistic insight into adenomyosis-related infertility. Journal of Advanced Research. https://doi.org/10.1016/j.jare.2026.02.030
24. Du, F., Wang, G., Dai, Q. et al. Targeting novel regulated cell death: disulfidptosis in cancer immunotherapy with immune checkpoint inhibitors. Biomark Res 13, 35 (2025). https://doi.org/10.1186/s40364-025-00748-4
25. Yadav, C. H., Revanuri, N., & Sikkander, A. R. M. (2025). Tungsten-based compounds: A new frontier in cancer diagnosis and therapy. Journal of Applied Organometallic Chemistry, 5(2), 149–167. https://doi.org/10.48309/JAOC.2025.479952.1270
26. Rodrigues, J. J., Sikkander, A. R. M., Tripathi, S. L., Kumar, K., Mishra, S. R., & Theivanathan, G. (2025). Artificial intelligence’s applicability in cardiac imaging. In Elsevier eBooks (pp. 181–195). https://doi.org/10.1016/b978-0-443-30080-6.00006-7
27. Yadav, C. H., Revanuri, N., & Sikkander, A. R. M. (2025). Organometallic compound phototoxicity against cancer cells. *Biomedical Engineering: Applications, Basis and Communications, 38(1). https://doi.org/10.4015/s1016237225500206
28. Mohamed Sikkander, A. R., Yadav, H., & Meena, M. (2024). The effectiveness of a nickel (II) complex containing 5-acetyl-N-(adamantan-2-yl) thiophene-2-carboxamide as a derivative for the drug isoniazid in relation to bacterial, cancer and tuberculosis activities. Advanced Journal of Chemistry, Section A, 7(5), 501–521. https://doi.org/10.48309/ajca.2024.443156.1490
29. Sikkander, A. M. (2022). Advancement of agricultural biotechnology in USA. International Journal of AgroChemistry. https://chemical.journalspub.info/index.php?journal=IJCPD&page=article&op=view&path%5B%5D=1299
30. Ramachandran, K., & Sikkander, A. M. (2021). Biomedical signal processing: Understanding its importance and several fundamental steps. Transaction on Biomedical Engineering Applications and Healthcare, 2(2), 15–16.
31. Chegini, S., Sikkander, A. R. M., Masoudi, M., Ekhtari, H., Mojaver, E., & Jafari, H. (2026). A circular bioeconomy framework for biodegradable waste: Strategies and opportunities. Bioresources and Bioproducts, 2(1), 2. https://doi.org/10.3390/bioresourbioprod2010002
32. Sikkander, A. M., Rodrigues, J. J. P. C., Meena, M., & Abuelmakarem, H. S. (2025). Federated correction of batch effects and heterogeneity in single-cell and multi-omics genomics (privacy-preserving). World Journal of Applied Medical Sciences, 2(12), 24–30. https://doi.org/10.65336/wjams.2025.21204
33. Hiremath, G., Mohamed Sikkander, A. R., Upadhyay, R., Acharya, D., Singh, K. P., & Wahi, N. (2025). Safety and efficacy of drug-eluting stents improved dramatically with application of nanotechnology. Advanced Journal of Chemistry, Section A, 8(2), 378–391. https://doi.org/10.48309/ajca.2025.467077.1591
34. Theivanathan, G., Mohamed Sikkander, A., Hemavathy, N., Murukesh, & Mishra, S. R. (2022). Tactile system for visually impaired people using embedded technology. International Journal of Scientific Research and Innovative Studies, 1(1), 14–19.
35. Sikkander, A. M., RamaNachiar, R., & Yasmeen, K. (2022). Spiking neural network (SNN) using to detect breast cancer. International Journal of Scientific Research and Innovative Studies, 1(1), 20–22.
36. Gu, Q., An, Y., Xu, M., Huang, X., Chen, X., Li, X., Shan, H., & Zhang, M. (2024). Disulfidptosis, a novel cell death pathway: molecular landscape and therapeutic implications. Aging and Disease, 16(2), 917. https://doi.org/10.14336/ad.2024.0083
37. Liu, Y., Li, S., Wu, Y. et al. Molecular signatures of disulfidptosis: interplay with programmed cell death pathways and therapeutic implications in oncology. Cell Mol Biol Lett 30, 66 (2025). https://doi.org/10.1186/s11658-025-00743-5
38. Li, X., Xu, J., Yan, L., Tang, S., Zhang, Y., Shi, M., & Liu, P. (2024). Targeting Disulfidptosis with Potentially Bioactive Natural Products in Metabolic Cancer Therapy. Metabolites, 14(11), 604. https://doi.org/10.3390/metabo14110604
39. Varlamova, E. G., Gudkov, S. V., & Turovsky, E. A. (2026). The Role of Se-Containing Glutathione Peroxidases and Thioredoxin Reductases in Oncogenesis: Expression Paradoxes and Therapeutic Prospects. Antioxidants, 15(3), 312. https://doi.org/10.3390/antiox15030312
40. Chang, J., Liu, D., Xiao, Y., Tan, B., Deng, J., Mei, Z., & Liao, J. (2025). Disulfidptosis: a new target for central nervous system disease therapy. Frontiers in Neuroscience, 19, 1514253. https://doi.org/10.3389/fnins.2025.1514253
41. Gan, B. Redox-driven cell death by disulfidptosis and its therapeutic potential. Nat Rev Mol Cell Biol 26, 727–729 (2025). https://doi.org/10.1038/s41580-025-00888-3
42. Sikkander, A. M., RamaNachiar, R., & Yasmeen, K. (2022). Artificial neural networks (ANNs) in lung cancer detection. International Journal of Scientific Research and Innovative Studies, 1(1), 155–158.
43. Sikk, A. M., & Abbas, H. S. (n.d.). A novel biosensor for pathogens diagnosis. https://www.alliedacademies.org/articles/a-novel-biosensor-for-pathogens-diagnosis-17372.
44. Sikkander, A. M., & Yasmeen, K. (2021). Review on nanotechnology: Curative applications in the medicinal field and its adverse effects.Journal of Science and Technology, 6(2), 1–8. https://doi.org/10.46243/jst.2021.v6.i2.pp01-08
45. Du, F., Wang, G., Dai, Q. et al. Targeting novel regulated cell death: disulfidptosis in cancer immunotherapy with immune checkpoint inhibitors. Biomark Res 13, 35 (2025). https://doi.org/10.1186/s40364-025-00748-4
46. Li, P., Wang, S., Wan, H., Huang, Y., Yin, K., Sun, K., Jin, H., & Wang, Z. (2024). Construction of disulfidptosis-based immune response prediction model with artificial intelligence and validation of the pivotal grouping oncogene c-MET in regulating T cell exhaustion. Frontiers in Immunology, 15, 1258475. https://doi.org/10.3389/fimmu.2024.1258475
47. Sikkander, M., Vedhi, C., & Manisankar, P. (2014). Enhanced electrochemical sensing of nimodipine with sodium montmorillonite clay. Moroccan Journal of Chemistry. https://doi.org/10.48317/imist.prsm/morjchem-v2i4.2135
48. Sikkander, A. M., Rodrigues, J. J. P. C., Meena, M., & Abuelmakarem, H. S. (2025). AI-powered generative frameworks for the rational design of synthetic genomes and next-generation cellular architectures. World Journal of Multidisciplinary Studies, 2(12), 46–53. https://doi.org/10.65336/wjms.2025.21204
49. Sikkander, A. M., Rodrigues, J. J. P. C., Meena, M., & Abuelmakarem, H. S. (2025). Leveraging artificial intelligence to integrate genomics, transcriptomics, and proteomics data for enhanced disease prediction. World Journal of Applied Medical Sciences, 2(12), 31–39. https://doi.org/10.65336/wjams.2025.21205
50. Sikkander, A. M., Rodrigues, J. J. P. C., Meena, M., & Abuelmakarem, H. S. (2025). Trustworthy and transparent AI for genomic discovery.World Journal of Multidisciplinary Studies, 2(12), 39–45. https://doi.org/10.65336/wjms.2025.21203
51. Jyotsana, N., Ta, K. T., & DelGiorno, K. E. (2022). The role of Cystine/Glutamate Antiporter SLC7A11/XCT in the pathophysiology of cancer. Frontiers in Oncology, 12. https://doi.org/10.3389/fonc.2022.858462
52. Sikkander, A. M., Rodrigues, J. J. P. C., Meena, M., & Abuelmakarem, H. S. (2025). Intelligent visualization frameworks driven by AI for multi-dimensional genomic data exploration and interpretation. World Journal of Multidisciplinary Studies, 2(12), 31–38. https://doi.org/10.65336/wjms.2025.21202
53. Sikkander, A. M., Rodrigues, J. J. P. C., Meena, M., & Abuelmakarem, H. S. (2025). AI-driven genomic biomarker discovery for precision diagnosis and personalized treatment. World Journal of Applied Medical Sciences, 2(12), 14–23. https://doi.org/10.65336/wjams.2025.21203
54. Sikkander, A. M., Rodrigues, J. J. P. C., Abuelmakarem, H. S., & Meena, M. (2025, November 28). Nanotechnology beneath: Innovations fuelling advances in acute care medicine, cardiology, oncology, and hypertension. https://wasrpublication.com/index.php/wjams/article/view/181
55. Sikkander, A. M., Rodrigues, J. J. P. C., Abuelmakarem, H. S., & Meena, M. (2025, November 26). Biomedical engineering innovations driving breakthroughs in cardiology, oncology, hypertension, and acute care medicine. https://wasrpublication.com/index.php/wjams/article/view/180
56. Sikkander, A. M., Rodrigues, J. J. P. C., Abuelmakarem, H. S., & Meena, M. (2025, November 24). AI beneath: Innovations driving breakthroughs in cardiology, oncology, hypertension, and acute care medicine. https://wasrpublication.com/index.php/wjams/article/view/179
57. Sikkander, A. M., Yadav, C. H., & Revanuri, N. (2025, November 21). Current developments in cyclophosphamide for lymphoma: Immunomodulation, metronomic approaches, and toxicity control. https://wasrpublication.com/index.php/wjams/article/view/177
58. Sikkander, A. M., Yadav, C. H., & Revanuri, N. (2025). A meta-analysis in non–small-cell lung cancer (NSCLC) indicates glucocorticoid administration is significantly associated with worse progression-free survival and overall survival for patients on ICIs. https://wasrpublication.com/index.php/wjams/article/view/176
59. Sikkander, A. R. M., Mishra, S. R., Shankaranarayanan, S., & Chegini, S. (2025). The iPSC-based models for hereditary arrhythmias: From genotype–phenotype studies to precision therapy. SPC Journal of Medical and Healthcare, 1(3), 184–191. https://doi.org/10.48309/sjmh.2025.537906.107
60. Mohamed Sikkander, A. R., Chegini, S., Mishra, S. R., & Subramanian, S. (2025). Integration of 6G networks and deep learning for advanced biomedical engineering applications: Real-time analytics, remote surgery, and intelligent healthcare systems. *SPC Journal of Medical and Healthcare, 1*(3), 167–175. https://doi.org/10.48309/sjmh.2025.537895.1073
61. Xiao, F., Li, HL., Yang, B. et al. Disulfidptosis: A new type of cell death. Apoptosis 29, 1309–1329 (2024). https://doi.org/10.1007/s10495-024-01989-8
62. Mao, C., Wang, M., Zhuang, L., & Gan, B. (2024). Metabolic cell death in cancer: ferroptosis, cuproptosis, disulfidptosis, and beyond. Protein & Cell, 15(9), 642–660. https://doi.org/10.1093/procel/pwae003
63. Sikkander, A. R. M., Lakshmi, V. V., Theivanathan, G., & Radhakrishnan, K. (2024). Multiresolution evaluation of contourlet transform for the diagnosis of skin cancer. SSR Preprints. https://doi.org/10.21203/rs.3.rs-4778827/v1
64. Sikkander, A. M., Yasmeen, K., & Haseeb, M. (2024). Biological synthesis, characterization, and therapeutic utility of Fusarium oxysporum silver nanoparticles. SSR Preprints. https://doi.org/10.21203/rs.3.rs-4649729/v1
65. Sikkander, A. M. (2022, October 3). Nanosilicones in sub-glandular and sub-muscular implant breast transplantation. International Journal of Analytical and Applied Chemistry. https://chemical.journalspub.info/index.php?journal=JAAC&page=article&op=view&path%5B%5D=1309
66. Sikkander, A. M. (2022, September 19). Assessment of basal cell carcinoma. International Journal of Chemical and Molecular Engineering. https://chemical.journalspub.info/index.php?journal=JCME&page=article&op=view&path%5B%5D=1311
67. Sikkander, A. M. (2022, September 17). Nanoemulsion in ophthalmology.International Journal of Chem-Informatics Research. https://chemical.journalspub.info/index.php?journal=JAWCM&page=article&op=view&path%5B%5D=1310
68. Sikkander, M., & Abbas, H. S. (2021). Biosensors for pathogens diagnosis. Journal of Chemical Technology Applications, 2(2), 1–3. https://www.alliedacademies.org/articles/biosensors-for-pathogens-diagnosis.pdf
69. Sikk, M., Er, A., & Yasmeen, K. (n.d.). Evaluation of surgical risk in patients with liver cancer. https://doi.org/10.35841/aaccr-5.3.115
70. Sikkander, A. M., Yadav, C. H., & Revanuri, N. (2025). Recent trends in Oncovin (vincristine) use for acute lymphoblastic leukemia: Liposomal formulations, pharmacogenomics, and toxicity-mitigation strategies. ISAR Journal of Medical and Pharmaceutical Sciences, 3(11), 20–23.
71. Rituraj, Pal, R.S., Wahlang, J. et al. Precision oncology: transforming cancer care through personalized medicine. Med Oncol 42, 246 (2025). https://doi.org/10.1007/s12032-025-02817-y
72. Liu, H., Karsidag, I., Golin, R., & Wu, G. (2025). Bridging Discovery and Treatment: Cancer Biomarker. Cancers, 17(22), 3720. https://doi.org/10.3390/cancers17223720
73. Zhou, Y., Tao, L., Qiu, J. et al. Tumor biomarkers for diagnosis, prognosis and targeted therapy. Sig Transduct Target Ther 9, 132 (2024). https://doi.org/10.1038/s41392-024-01823-2
74. Sikkander, A. R. M., & Rodrigues, J. J. P. C. (2026, January 28). Machine learning models to predict chemotherapy resistance in breast cancer using single-cell sequencing. https://wasrpublication.com/index.php/wjams/article/view/219
75. Sikkander, A. R. M., & Rodrigues, J. J. P. C. (2026, January 27). Deep-learning models for ultrasound, mammography, and MRI fusion for accurate tumor segmentation. https://wasrpublication.com/index.php/wjams/article/view/218
76. Sikkander, A. M., Yadav, C. H., & Revanuri, N. (2025). Current trends: Recent innovations and impacts of flap necrosis in breast reduction. ISAR Journal of Medical and Pharmaceutical Sciences, 3(11), 12–19.
77. Razak, M. S. A., Lakshmi, V. V., & Rodrigues, J. J. P. C. (2025). Multiresolution analysis of wavelets using artificial intelligence for skin cancer detection. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.5142172
78. Razak, M. S. A., Lakshmi, V. V., Theivanathan, G., & Radhakrishnan, K. (2025). Artificial intelligence-driven multidirectional curvelet analysis for enhanced skin cancer detection. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.5127060
79. Gupta, J. K., Sikkander, A. R. M., Nagrami, F. U. H., Kumar, K., & Wahi, N. (2023). Appraisal, recent advancement, and impacts of nanomedicine in cardiac asthma. Journal of Medical Pharmaceutical and Allied Sciences, 12(5), 6132–6138. https://doi.org/10.55522/jmpas.v12i5.5214
80. Chen, R., You, J., Weng, S. et al. Disulfidptosis mechanisms and therapeutic implications in cancer metabolic reprogramming and future perspectives. Discov Onc 16, 1814 (2025). https://doi.org/10.1007/s12672-025-03538-4
81. Wang, B., Liu, Z., Li, J., Xu, J., Guo, Y., Zhang, J., Chu, T., Feng, Z., Jiang, Q., & Wu, D. (2026). Disulfidptosis-based cancer therapy: Opportunity and challenge. Genes & Diseases, 102028. https://doi.org/10.1016/j.gendis.2025.102028
82. Yadav, C. H., Revanuri, N., & Mohamed Sikkander, A. R. (2025). Organometallic compound phototoxicity against cancer cells. Biomedical Engineering: Applications, Basis and Communications. https://doi.org/10.4015/S1016237225500206
83. Sikkander, A. M., Ranjan, R., & Mishra, S. R. (2024). Artificial intelligence in cerebellum activation. International Journal of Cheminformatics, 1(1), 14–26. https://journals.stmjournals.com/ijci/article=2024/view=143947
84. Mohamed Sikkander, A. R., Ranjan, R., & Mishra, S. R. (2024). Nanoelectronics, nanoparticles, and nanotechnology in treatment of psychological disorders. International Journal of Environmental Chemistry. https://journals.stmjournals.com/ijec/article=2024/view=143513
85. Sikkander, A. M., Ranjan, R., & Sikkander, A. M. (2024). Organometallic osmium compounds in cancer therapy. International Journal of Advance in Molecular Engineering, 1(2), 1–25. https://journals.stmjournals.com/ijame/article=2024/view=144940
86. Wei, Q., Xiong, B., Yang, G. et al. Progress in research on the mechanisms and therapeutic strategies of SLC7A11 regulation in glioma. Discov Onc 17, 25 (2026). https://doi.org/10.1007/s12672-025-04154-y
87. Li, S., Lu, Z., Sun, R., Guo, S., Gao, F., Cao, B., & Aa, J. (2022). The Role of SLC7A11 in Cancer: Friend or Foe? Cancers, 14(13), 3059. https://doi.org/10.3390/cancers14133059
88. Mohamed Sikkander, A. R. (2024). Catalytic activity advancements in organometallic chemistry. https://engineeringjournals.stmjournals.in/index.php/JoCC/issue/view/1274
89. Gupta, J. K., Sikkander, A. R. M., Nagrami, F. U. H., Kumar, K., & Wahi, N. (2023). Appraisal, recent advancement, and impacts of nanomedicine in cardiac asthma. Journal of Medical Pharmaceutical and Allied Sciences, 12(5), 6132–6138. https://doi.org/10.55522/jmpas.v12i5.5214
90. Sikkander, A. M. (2022). Nanosilicones in sub-glandular and sub-muscular implant breast transplantation. International Journal of Analytical and Applied Chemistry. https://chemical.journalspub.info/index.php?journal=JAAC&page=index
91. Zheng, T., Liu, Q., Xing, F., Zeng, C., & Wang, W. (2023). Disulfidptosis: a new form of programmed cell death. Journal of Experimental & Clinical Cancer Research, 42(1), 137. https://doi.org/10.1186/s13046-023-02712-2
92. AlDoughaim, M., AlSuhebany, N., AlZahrani, M., AlQahtani, T., AlGhamdi, S., Badreldin, H., & Alshaykh, H. A. (2024). Cancer Biomarkers and Precision Oncology: A review of recent trends and innovations. Clinical Medicine Insights Oncology, 18, 11795549241298541. https://doi.org/10.1177/11795549241298541
93. Xiong, N., Wu, H., & Yu, Z. (2024). Advancements and challenges in triple-negative breast cancer: a comprehensive review of therapeutic and diagnostic strategies. Frontiers in Oncology, 14, 1405491. https://doi.org/10.3389/fonc.2024.1405491
94. Sikkander, A. M. (2022). Assessment of basal cell carcinoma. International Journal of Chemical and Molecular Engineering, 8(2). https://chemical.journalspub.info/index.php?journal=JCME&page=issue&op=view&path%5B%5D=273
95. Leon-Ferre, R. A., & Goetz, M. P. (2023). Advances in systemic therapies for triple negative breast cancer. BMJ, 381, e071674. https://doi.org/10.1136/bmj-2022-071674
96. Sikkander, A. M. (2022). Nanoemulsion in ophthalmology. International Journal of Chem-Informatics Research, 8(2). https://chemical.journalspub.info/index.php?journal=JAWCM&page=index
97. Xu, L., Xu, P., Wang, J., Ji, H., Zhang, L., & Tang, Z. (2024). Advancements in clinical research and emerging therapies for triple-negative breast cancer treatment. European Journal of Pharmacology, 988, 177202. https://doi.org/10.1016/j.ejphar.2024.177202
98. Sikkander, A. M. (2023). Advancement of agricultural biotechnology in USA. International Journal of AgroChemistry, 9(2). https://chemical.journalspub.info/index.php?journal=IJCPD&page=index
99. Yan, Y., Teng, H., Hang, Q. et al. SLC7A11 expression level dictates differential responses to oxidative stress in cancer cells. Nat Commun 14, 3673 (2023). https://doi.org/10.1038/s41467-023-39401-9
100. Xu, J., Guo, K., Sheng, X. et al. Correlation analysis of disulfidptosis-related gene signatures with clinical prognosis and immunotherapy response in sarcoma. Sci Rep 14, 7158 (2024). https://doi.org/10.1038/s41598-024-57594-x
101. Liu, T., Kong, X., & Wei, J. (2024). Disulfidptosis: A New Target for Parkinson’s Disease and Cancer. Current Issues in Molecular Biology, 46(9), 10038-10064. https://doi.org/10.3390/cimb46090600
102. Xing, X., Zhong, J., Biermann, J., Duan, H., Zhang, X., Shi, Y., Gao, Y., He, K., Zhai, D., Luo, F., Lai, Y., Xiao, F., Wang, W., Wang, M., Xu, J., Liu, H., Tang, J., Chu, L., Chen, T., . . . Bai, F. (2025). Pan-cancer human brain metastases atlas at single-cell resolution. Cancer Cell, 43(7), 1242-1260.e9. https://doi.org/10.1016/j.ccell.2025.03.025
103. Liu, X., Zhuang, L., & Gan, B. (2023b). Disulfidptosis: disulfide stress–induced cell death. Trends in Cell Biology, 34(4), 327–337. https://doi.org/10.1016/j.tcb.2023.07.009
104. Wang, J., Chen, J., Fan, K., Wang, M., Gao, M., Ren, Y., Wu, S., He, Q., Tu, K., Xu, Q., & Zhang, Y. (2024). Inhibition of Endoplasmic Reticulum Stress Cooperates with SLC7A11 to Promote Disulfidptosis and Suppress Tumor Growth upon Glucose Limitation. Advanced Science, 12(7), e2408789. https://doi.org/10.1002/advs.202408789
105. Zein, L., Fulda, S., Kögel, D., & Van Wijk, S. J. (2020). Organelle-specific mechanisms of drug-induced autophagy-dependent cell death. Matrix Biology, 100–101, 54–64. https://doi.org/10.1016/j.matbio.2020.12.003
106. Ahn, J., & Jeong, H. (2025). Genetic etiology of permanent congenital hypothyroidism in Korean patients: A Whole-Exome Sequencing study. International Journal of Molecular Sciences, 26(9), 4465. https://doi.org/10.3390/ijms26094465
107. Fowler, S. L., Behr, T. S., Turkes, E., O’Brien, D. P., Cauhy, P. M., Rawlinson, I., Edmonds, M., Foiani, M. S., Schaler, A., Crowley, G., Bez, S., Ficulle, E., Tsefou, E., Fischer, R., Geary, B., Gaur, P., Miller, C., D’Acunzo, P., Levy, E., . . . Ryskeldi-Falcon, B. (2024). Tau filaments are tethered within brain extracellular vesicles in Alzheimer’s disease. Nature Neuroscience, 28(1), 40–48. https://doi.org/10.1038/s41593-024-01801-5
108. Niu, X., Li, G., Kahlert, U. D., Ding, L., Zheng, J., Li, C., Shi, W., Huang, L., & Yu, Z. (2025). Integrative Disulfidptosis‐Based risk Assessment for prognostic stratification and immune profiling in Glioma. Journal of Cellular and Molecular Medicine, 29(4), e70429. https://doi.org/10.1111/jcmm.70429
109. Chen, S., Zeng, M., Chen, T., Ding, H., Lin, J., Ye, F., Wu, R., Yang, L., & Yang, K. (2024). Integrated multi-level omics profiling of disulfidptosis identifis SPAG4 as an innovative immunotherapeutic target in glioblastoma. Frontiers in Immunology, 15, 1462064. https://doi.org/10.3389/fimmu.2024.1462064
110. Lin J, Yang X, Jiang C, Liu X, Shi J. Enhancing cancer susceptibility to disulfidptosis by inducing cell cycle arrest and impairing DNA repair. Theranostics 2026; 16(2):637-650. doi:10.7150/thno.122956. https://www.thno.org/v16p0637.htm
111. Xu, Z., Pang, C., & Xu, X. (2024). Establishment of prognostic risk model related to disulfidptosis and immune infiltration in hepatocellular carcinoma. Heliyon, 10(23), e40405. https://doi.org/10.1016/j.heliyon.2024.e40405
112. Zhang, Y., Li, Z., Lu, H. et al. Pan-cancer analysis uncovered the prognostic and therapeutic value of disulfidptosis. npj Precis. Onc. 9, 50 (2025). https://doi.org/10.1038/s41698-025-00834-8
113. Xu, S., Chen, Z., Chen, X. et al. Interplay of disulfidptosis and the tumor microenvironment across cancers: implications for prognosis and therapeutic responses. BMC Cancer 25, 1113 (2025). https://doi.org/10.1186/s12885-025-14246-1
114. Wan, S., Liang, C., Wu, C., Wang, S., Wang, J., Xu, L., Zhang, X., Hou, Y., Xia, Y., Xu, L., & Huang, X. (2025). Disulfidptosis in tumor progression. Cell Death Discovery, 11(1), 205. https://doi.org/10.1038/s41420-025-02495-9
115. Wan, S., Liang, C., Wu, C. et al. Disulfidptosis in tumor progression. Cell Death Discov. 11, 205 (2025). https://doi.org/10.1038/s41420-025-02495-9
116. Mi, T., Kong, X., Chen, M., Guo, P., & He, D. (2024). Inducing disulfidptosis in tumors:potential pathways and significance. MedComm, 5(11), e791. https://doi.org/10.1002/mco2.791
117. Wan, Y., Jing, M., Zhang, L., Song, Q., Ye, X., Zhou, Z., Yan, W., & Fu, Y. (2026). The Mechanism and Regulation of Disulfidptosis and Its Role in Disease. Biomedicines, 14(1), 228. https://doi.org/10.3390/biomedicines14010228
118. Kerr, J.F.; Wyllie, A.H.; Currie, A.R. Apoptosis: A Basic Biological Phenomenon with Wide-Ranging Implications in Tissue Kinetics. Br. J. Cancer 1972, 26, 239–257.
119. Zhou, S.; Liu, J.; Wan, A.; Zhang, Y.; Qi, X. Epigenetic regulation of diverse cell death modalities in cancer: A focus on pyroptosis, ferroptosis, cuproptosis, and disulfidptosis. J. Hematol. Oncol. 2024, 17, 22.
120. Liu, X.; Nie, L.; Zhang, Y.; Yan, Y.; Wang, C.; Colic, M.; Olszewski, K.; Horbath, A.; Chen, X.; Lei, G.; et al. Actin cytoskeleton vulnerability to disulfide stress mediates disulfidptosis. Nat. Cell Biol. 2023, 25, 404–414.
121. Galluzzi, L.; Vitale, I.; Aaronson, S.A.; Abrams, J.M.; Adam, D.; Agostinis, P.; Alnemri, E.S.; Altucci, L.; Amelio, I.; Andrews, D.W.; et al. Molecular mechanisms of cell death: Recommendations of the nomenclature committee on cell death 2018. Cell Death Differ. 2018, 25, 486–541.
122. Koppula, P.; Zhuang, L.; Gan, B. Cystine transporter SLC7A11/xCT in cancer: Ferroptosis, nutrient dependency, and cancer therapy. Protein Cell 2020, 12, 599.
123. Stipanuk, M.H. Sulfur amino acid metabolism: Pathways for production and removal of homocysteine and cysteine. Annu. Rev. Nutr. 2004, 24, 539–577.
124. Yan, Y.; Teng, H.; Hang, Q.; Kondiparthi, L.; Lei, G.; Horbath, A.; Liu, X.; Mao, C.; Wu, S.; Zhuang, L.; et al. SLC7A11 expression level dictates differential responses to oxidative stress in cancer cells. Nat. Commun. 2023, 14, 3673.
125. Lo, M.; Wang, Y.Z.; Gout, P.W. The x(c)- cystine/glutamate antiporter: A potential target for therapy of cancer and other diseases. J. Cell. Physiol. 2008, 215, 593–602.
126. Koppula, P.; Zhang, Y.; Zhuang, L.; Gan, B. Amino acid transporter SLC7A11/xCT at the crossroads of regulating redox homeostasis and nutrient dependency of cancer. Cancer Commun. 2018, 38, 12.
127. Chen, J., Ma, B., Yang, Y. et al. Disulfidptosis decoded: a journey through cell death mysteries, regulatory networks, disease paradigms and future directions. Biomark Res 12, 45 (2024). https://doi.org/10.1186/s40364-024-00593-x
128. Li, L., & Ivanova, A. (2024). Isotonic design for single-arm biomarker stratified trials. Statistical Methods in Medical Research, 33(6), 945–952. https://doi.org/10.1177/09622802241238978
129. Song, Z., Yao, Q., Huang, L., Cui, D., Xie, J., Wu, L., Huang, J., Zhai, B., Liu, D., & Xu, X. (2025b). Glucose Deprivation‐Induced Disulfidptosis via the SLC7A11‐INF2 axis: Pan‐Cancer Prognostic Exploration and Therapeutic Validation. Advanced Science, 12(39), e08556. https://doi.org/10.1002/advs.202408556
130. Qiu, H., Liu, J., Shao, N. et al. SLC7A11 as a bridge between ferroptosis and disulfidptosis: a promising target for tumor treatment. Cell Commun Signal 23, 460 (2025). https://doi.org/10.1186/s12964-025-02447-x
131. Pont, M., Marqués, M., & Sorolla, A. (2024). Latest Therapeutical Approaches for Triple-Negative Breast Cancer: From Preclinical to Clinical Research. International Journal of Molecular Sciences, 25(24), 13518. https://doi.org/10.3390/ijms252413518
132. Bray, F.; Laversanne, M.; Sung, H.; Ferlay, J.; Siegel, R.L.; Soerjomataram, I.; Jemal, A. Global cancer statistics 2022: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J. Clin. 2024, 74, 229–263.
133. Perou, C.M.; Sorlie, T.; Eisen, M.B.; van de Rijn, M.; Jeffrey, S.S.; Rees, C.A.; Pollack, J.R.; Ross, D.T.; Johnsen, H.; Akslen, L.A.; et al. Molecular portraits of human breast tumours. Nature 2000, 406, 747–752.
134. Orrantia-Borunda, E.; Anchondo-Nunez, P.; Acuna-Aguilar, L.E.; Gomez-Valles, F.O.; Ramirez-Valdespino, C.A. Subtypes of Breast Cancer. In Breast Cancer; Mayrovitz, H.N., Ed.; Exon Publications: Brisbane, AU, USA, 2022.
135. Costa, R.L.; Gradishar, W.J. Triple-negative breast cancer: Current practice and future directions. J. Oncol. Pract. 2017, 13, 301–303.
136. Bauer, K.R.; Brown, M.; Cress, R.D.; Parise, C.A.; Caggiano, V. Descriptive analysis of estrogen receptor (ER)-negative, progesterone receptor (PR)-negative, and HER2-negative invasive breast cancer, the so-called triple-negative phenotype: A population-based study from the California cancer Registry. Cancer 2007, 109, 1721–1728.
137. Lehmann, B.D.; Bauer, J.A.; Chen, X.; Sanders, M.E.; Chakravarthy, A.B.; Shyr, Y.; Pietenpol, J.A. Identification of human triple-negative breast cancer subtypes and preclinical models for selection of targeted therapies. J. Clin. Investig. 2011, 121, 2750–2767.
138. Syrnioti, A.; Petousis, S.; Newman, L.A.; Margioula-Siarkou, C.; Papamitsou, T.; Dinas, K.; Koletsa, T. Triple Negative Breast Cancer: Molecular Subtype-Specific Immune Landscapes with Therapeutic Implications. Cancers 2024, 16, 2094.
139. Bhattarai, S.; Saini, G.; Gogineni, K.; Aneja, R. Quadruple-negative breast cancer: Novel implications for a new disease. Breast Cancer Res. 2020, 22, 127.
140. Bhat, Y.; Thrishna, M.R.; Banerjee, S. Molecular targets and therapeutic strategies for triple-negative breast cancer. Mol. Biol. Rep. 2023, 50, 10535–10577.
141. Koppula, P., Zhuang, L. & Gan, B. Cystine transporter SLC7A11/xCT in cancer: ferroptosis, nutrient dependency, and cancer therapy. Protein Cell 12, 599–620 (2021). https://doi.org/10.1007/s13238-020-00789-5
142. Mokhtari, R. B., Homayouni, T. S., Baluch, N., Morgatskaya, E., Kumar, S., Das, B., & Yeger, H. (2017). Combination therapy in combating cancer. Oncotarget, 8(23), 38022–38043. https://doi.org/10.18632/oncotarget.16723
143. Xiao, F., Li, H., Yang, B., Che, H., Xu, F., Li, G., Zhou, C., & Wang, S. (2024). Disulfidptosis: A new type of cell death. APOPTOSIS, 29(9–10), 1309–1329. https://doi.org/10.1007/s10495-024-01989-8
144. Bertheloot, D., Latz, E., & Franklin, B. S. (2021). Necroptosis, pyroptosis and apoptosis: an intricate game of cell death. Cellular and Molecular Immunology, 18(5), 1106–1121. https://doi.org/10.1038/s41423-020-00630-3
145. Liu, X., Nie, L., Zhang, Y., Yan, Y., Wang, C., Colic, M., Olszewski, K., Horbath, A., Chen, X., Lei, G., Mao, C., Wu, S., Zhuang, L., Poyurovsky, M. V., You, M. J., Hart, T., Billadeau, D. D., Chen, J., & Gan, B. (2023b). Actin cytoskeleton vulnerability to disulfide stress mediates disulfidptosis. Nature Cell Biology, 25(3), 404–414. https://doi.org/10.1038/s41556-023-01091-2
146. Machesky, L. M. (2023). Deadly actin collapse by disulfidptosis. Nature Cell Biology, 25(3), 375–376. https://doi.org/10.1038/s41556-023-01100-4
147. Zheng, T., Liu, Q., Xing, F., Zeng, C., & Wang, W. (2023b). Disulfidptosis: a new form of programmed cell death. Journal of Experimental & Clinical Cancer Research, 42(1), 137. https://doi.org/10.1186/s13046-023-02712-2
148. Zheng, P., Zhou, C., Ding, Y., & Duan, S. (2023). Disulfidptosis: a new target for metabolic cancer therapy. Journal of Experimental & Clinical Cancer Research, 42(1), 103. https://doi.org/10.1186/s13046-023-02675-4
149. Zhu, Y., Kong, L., Han, T., Yan, Q., & Liu, J. (2023). Machine learning identification and immune infiltration of disulfidptosis‐related Alzheimer’s disease molecular subtypes. Immunity Inflammation and Disease, 11(10), e1037. https://doi.org/10.1002/iid3.1037
