Integrative Biomedical Research
Integrative Biomedical Research (Journal of Angiotherapy) | Online ISSN 3068-6326
463
Citations
1.8m
Views
757
Articles
Volume 10 Number 1 2026
REVIEWS (Open Access)
Integrating Genomics, Transcriptomics, and Organoid-Based Drug Testing for Precision Cancer Care
Yoghinni Manogaran 1*, Ahmed Ahmed Al-Akwaa 2
Integrative Biomedical Research 10 (1) 1-8 https://doi.org/10.25163/biomedical.10110907
Submitted: 14 January 2026 Revised: 01 March 2026 Accepted: 09 March 2026 Published: 11 March 2026
Abstract
Genomic profiling has reshaped oncology, yet only a minority of sequenced patients ever receive a molecularly matched therapy, and identical driver mutations often yield inconsistent clinical outcomes. This gap suggests that static DNA-level data alone cannot capture the dynamic, evolving biology of tumors. We synthesized real-world implementation cohorts, diagnostic-platform comparisons, biomarker-pathobiology data, and workforce-competency evidence drawn from recently published precision oncology literature, and we outline a prospective multi-omic pipeline — combining targeted DNA panels, transcriptomics, methylation and copy-number signatures, and patient-derived organoid drug screening — layered onto machine-learning fusion models. Across programs such as KOSMOS and the pediatric integrative-genomics cohort, actionable alterations were identified in 55–100% of patients, yet molecularly matched treatment was ultimately delivered to only 38–51% of cases. Transcriptomic and functional assays improved concordance between predicted and observed drug sensitivity, while copy-number and methylation signatures added prognostic information beyond single-nucleotide variants. Diagnostic-platform trade-offs (depth versus breadth), clonal hematopoiesis confounding in liquid biopsy, and demographic underrepresentation in reference databases emerged as recurring, largely unresolved barriers. A closed-loop framework that pairs multi-omic profiling with functional validation and tiered workforce competencies offers a plausible route toward durable, equitable precision oncology, though prospective, adequately powered trials are still needed to confirm its clinical benefit.
Keywords: precision oncology; multi-omics; functional precision oncology; patient-derived organoids; liquid biopsy; molecular tumor board; machine learning
References
Acebedo, A., Bedard, P. L., Brown, S., Ceca, E., Fiandalo, M., Fuchs, H., Guo, X., Hoppe, J. N., Kehl, K. L., Kundra, R., Lavery, J. A., LeNoue-Newton, M. L., Lepisto, E., Mastrogiacomo, B., Micheel, C. M., Nayan, C., Newcomb, A., Nichols, C., Panageas, K. S., . . . Yu, C. (2025). Collaborating across sectors in service of open science, precision oncology, and patients: An overview of the AACR Project GENIE Biopharma Collaborative (BPC). ESMO Real World Data and Digital Oncology, 1, 100075.
Adedokun, K. A., Fayemo, T. H., Oyeniyi, G. M., Bello, A., Orugun, O. A., Imodoye, S. O., Ogunlakin, A. D., Eziagu, U. B., Dewan, S. M. R., Khan, S. A., Oladejo, M. K., & Adewole, P. D. (2026). Integrative drug discovery through molecular, cellular, genomic, and immunological approaches: From gene editing to precision antibody engineering. Next Materials, 12, 102232. https://doi.org/10.1016/j.nxmate.2026.102232
Basety, S., Gudepu, R., & Velidandi, A. (2026). Artificial intelligence in lung cancer: A narrative review of recent advances in diagnosis, biomarker discovery, and drug development. Pharmaceutics, 18, 00201.
Bulic, L., Brlek, P., Hrvatin, N., Brenner, E., Škaro, V., Projic, P., Rogan, S. A., Bebek, M., Shah, P., & Primorac, D. (2026). AI-driven advances in precision oncology: Toward optimizing cancer diagnostics and personalized treatment. AI, 7, 00011.
Chanhih, N., Laraqui, A., Hassine, S., Ameur, A., Hamedoun, L., El Annaz, H., Abi, R., Tagajdid, M. R., Amine, I. L., Ennibi, K., Benjouad, A., & Belayachi, L. (2025). Circulating tumor DNA as a biomarker for precision medicine in prostate cancer: A systematic review. International Journal of Molecular Sciences, 26, 11049.
Chetta, M., Bukvic, N., & Rosati, A. (2026). The ctDNA paradigm: Dynamic observation, quantitative analysis, and interpretive limits in precision oncology. Genes, 17, 00754.
Diaz, F. C., Waldrup, B., Carranza, F. G., Manjarrez, S., & Velazquez-Villarreal, E. (2026). Deciphering RTK-RAS and MAPK pathway dependencies in gemcitabine-treated pancreatic ductal adenocarcinoma through conversational artificial intelligence. International Journal of Molecular Sciences, 27, 03011.
Drury, A., Hamdi, Y., Mulder, N., Rueter, J., Kelley, L., Blazer, K., Casolino, R., & Gray, S. W. (2026). Building a genomics-capable cancer workforce: A competency-based framework for education and training in precision oncology. eClinicalMedicine, 99, 104142. https://doi.org/10.1016/j.eclinm.2026.104142
Fadiel, A., Malpani, P., Eichenbaum, K. D., Naftolin, F., Hassouneh, A., Chong, G., & Odunsi, K. (2026). Integrative computational approaches to prostate cancer with conditional reprogramming and AI-driven precision medicine. Cells, 15, 00700.
Kanavos, K. P., Alcaraz, A., Argento, F., Colaci, C., Alfie, V., Pichon-Riviere, A., Augustovski, F., & Mills, M. (2025). Value assessment framework for next-generation sequencing and comprehensive genomic profiling in European oncology. eBioMedicine, 121, 105947. https://doi.org/10.1016/j.ebiom.2025.105947
Kar, P., Qiu, Z., & Maulik, U. (2026). A genomic data analysis-based technique for personalized and precision medicine. Array, 30, 100965.
Kaštelan, S., Gilevska, F., Tomic, Z., Živko, J., & Nikuševa-Martic, T. (2026). Precision oncology in ocular melanoma: Integrating molecular and liquid biopsy biomarkers. Current Issues in Molecular Biology, 48(1), 00131. https://doi.org/10.3390/cimb480100131
Kim, K. H., & Yoo, B. C. (2026). Circulating RNA as a functional component of liquid biopsy in cancer: Concepts, classification, and clinical applications. International Journal of Molecular Sciences, 27, 02403.
Kim, T. Y., Kim, S. Y., Kim, J. H., Jung, H. A., Choi, Y. J., Hwang, I. G., Cha, Y., Lee, G.-W., Lee, Y.-G., Kim, T. M., Lee, S.-H., Lee, S., Yun, H., Choi, Y. L., Yoon, S., Han, S. W., Kim, T.-Y., Kim, T. W., Zang, D. Y., & Kang, J. H. (2024). Nationwide precision oncology pilot study: KOrean Precision Medicine Networking Group Study of MOlecular profiling-guided therapy based on genomic alterations in advanced solid tumors (KOSMOS) KCSG AL-20-05. ESMO Open, 9(10), 103709. https://doi.org/10.1016/j.esmoop.2024.103709
Knebel, P., Harris, J., Steveson, I., Kearns, B., Todeschini, A. S., Perrett, L., Anderson, D., Beltran, E., Leary, B., Settle, J., Carlson, I., Christensen, H., Trujano, A., Alton, A. B., Dixon, K., & Barrott, J. J. (2026). Hidden in the noise: Low-variant allele frequency mutations and their impact on precision oncology. Journal of Genome Biotechnology and Genetics, 1(1), 00004.
Kotsifaki, A., Kalouda, G., Karalexis, E., Stathaki, M., Metaxas, G., & Armakolas, A. (2025). Emerging breast cancer subpopulations: Functional heterogeneity beyond the classical subtypes. International Journal of Molecular Sciences, 26, 11599.
Lee, S., Kim, A., Kim, R. H., You, Y. S., Kim, H. S., Chung, S., Lee, S. H., Yahng, S. A., Kim, I. K., & Kim, H. J. (2026). Precision oncology at a crossroads: How organoid platforms are reshaping the field. Organoids, 5, 00016.
Macrea, C. M., Ilias, T., Costea, A., Trif, P., Murvai, V. R., & Fratila, O. C. (2026). The genetic landscape of colorectal cancer: From molecular alterations to therapeutic decision pathways. Cancers, 18(25), 02526. https://doi.org/10.3390/cancers182502526
Ortega-García, J. A., Shakeel, O., Wood, N. M., Pérez-Martínez, A., Fuster-Soler, J. L., & Miller, M. D. (2025). Beyond precision: Ambiomic survivorship in childhood and AYA cancer. Cancers, 18, 00007.
Palizban, F., March, M. E., Wang, X., Snyder, J., Wang, F., Mentch, F., Mahesh, Y., Thomas, A., Watson, D. J., Qu, H., Connolly, J., Saeidian, A. H., Vahidnezhad, H., Glessner, J., & Hakonarson, H. (2026). Unsupervised deep representation learning and probabilistic clustering for the systems-level discovery of germline mutation signatures in pediatric cancers. Biomedicines, 14(7), 01438. https://doi.org/10.3390/biomedicines140701438
Pokorna, P., Palova, H., Adamcova, S., Jugas, R., Al Tukmachi, D., Kyr, M., Knoflickova, D., Kozelkova, K., Bystry, V., Mejstrikova, S., Merta, T., Trachtova, K., Podlipna, E., Mudry, P., Pavelka, Z., Bajciova, V., Tinka, P., Jarosova, M., Ivkovic, T. C., . . . Slaby, O. (2024). Real-world performance of integrative clinical genomics in pediatric precision oncology. Laboratory Investigation, 104(12), 102161. https://doi.org/10.1016/j.labinv.2024.102161
Qiu, Z., Kar, P., & Maulik, U. (2026). A genomic data analysis-based technique for personalized and precision medicine. Array, 30, 100965.
Rescigno, P., & Greystoke, A. (2026). Illuminating the spectrum of genomic sequencing approaches in the precision oncology era: A UK perspective. Cancer Treatment and Research Communications, 46, 101054. https://doi.org/10.1016/j.ctrc.2026.101054
Rusciano, D. (2026). Molecular oncodiagnostics in precision oncology: Integrating tumor transcriptomics, patient pharmacogenetics, and ex vivo chemoresistance testing to improve individual chemotherapy response. Journal of Personalized Medicine, 16(1), 00176.
Tinland, J., & de Montgolfier, S. (2026). Genomic stratification of risks in oncology: Narrative literature review of epistemological, operational, and ethical challenges. SSM - Qualitative Research in Health, 10, 100822.
Tutar-Torun, E., Kurt, B., Sener-Akcora, D., Yilmaz, A. M., Sahin, A., Arga, K. Y., Cakir, M. O., Bahsi, T., & Ozdogan, M. (2026). Functional precision oncology in rectal cancer liver metastasis: Integrated genomic and organoid-based drug sensitivity profiling. Organoids, 5, 00014.
Wang, H., Chang, Y., Wang, K., & Liu, R. (2025). Recent advances in nccRCC classification and therapeutic approaches. Cells, 14(22), 1781. https://doi.org/10.3390/cells14221781
Yaacov, A. (2026). Consensus copy-number alteration signatures from clinical panels enable pan-cancer risk stratification and therapy response association. International Journal of Molecular Sciences, 27(4), 1764. https://doi.org/10.3390/ijms27041764