Journal of Precision Biosciences
Biopharmaceuticals and medical sciences | Online ISSN 3064-9226
  1. You are here:
  2. Home
  3. Journals
  4. Biological Sciences
REVIEWS   (Open Access)
Contents Vol 5 (1)

Advances in Individualized Therapeutics Design in Cancer

Wei Zhang 1, 2, Shamsuddin Sultan Khan 1*, John Catanzaro 1

+ Author Affiliations

Journal of Precision Biosciences 5 (1) 1-13 https://doi.org/10.25163/biosciences.515801

Submitted: 02 January 2023 Revised: 31 January 2023  Published: 01 February 2023 

Abstract

Cancer is a complex and heterogeneous disease that requires personalized treatment approaches to optimize patient outcomes. Individualized therapeutic design, which involves tailoring cancer treatment based on patient-specific factors, has emerged as a promising strategy for improving cancer care. In this review article, we provide an overview of conventional cancer treatment methods and their limitations, as well as the concept and importance of individualized therapeutic design in cancer treatment. We discuss the various factors influencing individualized therapeutic design in cancer treatment, such as genetic, epigenetic, environmental, and lifestyle factors, and the techniques for implementing individualized therapeutic design, including molecular profiling, imaging, and data analysis techniques. We also present case studies and clinical trials that demonstrate the effectiveness of individualized therapeutic design in cancer treatment. However, challenges and limitations to the implementation of individualized therapeutic design exist, including the cost and accessibility of personalized medicine, ethical considerations, and disease heterogeneity.An advanced immunotherapeutic strategy based on precision medicine concepts is known as precision-based immuno-molecular augmentation. To enhance therapeutic outcomes, this strategy entails customizing therapies based on individual genetic and biological traits. Targeting specific molecular markers on cells, precision-based immuno-molecular augmentation enables the production of highly specific immunomodulatory medicines, including gene treatments, monoclonal antibodies, and tailored vaccinations. The aim is to optimize the immune response of the body in a highly focused manner, avoiding side effects and maximizing efficacy against certain threats. Hence, a comparative analysis of the existing such therapies was also performed. We conclude by highlighting the potential use of precision-based immuno-molecular augmentation Prediction tools for individualized therapeutic design in cancer treatment and providing recommendations for future research and clinical practice. Overall, individualized therapeutic design using precision-based immuno-molecular augmentation has the potential to revolutionize cancer care and improve patient outcomes.

Keywords: Individualized targeted immunotherapy, peptide, Precision medicine, Edited Sequences, ITI-PES, precision-based immuno-molecular augmentation, Inflammation, Cancer, Autoimmune

References

Abbas, Z., & Rehman, S. (2018). An overview of cancer treatment modalities. Neoplasm, 1, 139–157.

Almåsbak, H., Aarvak, T., & Vemuri, M. C. (2016). CAR T cell therapy: a game changer in cancer treatment. Journal of Immunology Research, 2016.

Aust, S., Schwameis, R., Gagic, T., Müllauer, L., Langthaler, E., Prager, G., Grech, C., Reinthaller, A., Krainer, M., & Pils, D. (2020). Precision medicine tumor boards: Clinical applicability of personalized treatment concepts in ovarian cancer. Cancers, 12(3), 548.

Beltrán-García, J., Osca-Verdegal, R., Mena-Mollá, S., & García-Giménez, J. L. (2019). Epigenetic IVD tests for personalized precision medicine in cancer. Frontiers in Genetics, 10, 621.

Blonde, L., Dendy, J. A., Skolnik, N., & White Jr, J. R. (2018). From randomized controlled trials to the real world: putting evidence into context. J Fam Pract, 67(Suppl. 8), S55–S60.

Diaz, J. L. A., & Bardelli, A. (2014). Liquid biopsies: genotyping circulating tumor DNA. Journal of Clinical Oncology: Official Journal of the American Society of Clinical Oncology, 32(6), 579–586.

Dienstmann, R., Vermeulen, L., Guinney, J., Kopetz, S., Tejpar, S., & Tabernero, J. (2017). Consensus molecular subtypes and the evolution of precision medicine in colorectal cancer. Nature Reviews Cancer, 17(2), 79–92.

Dowall, S. D., Graham, V. A., Tipton, T. R. W., & Hewson, R. (2009). Multiplex cytokine profiling with highly pathogenic material: Use of formalin solution in luminex analysis. Journal of Immunological Methods, 348(1–2), 30–35. https://doi.org/10.1016/j.jim.2009.06.007

Esteva, A., Kuprel, B., Novoa, R. A., Ko, J., Swetter, S. M., Blau, H. M., & Thrun, S. (2017). Dermatologist-level classification of skin cancer with deep neural networks. Nature, 542(7639), 115–118.

Fiegl, H., Millinger, S., Mueller-Holzner, E., Marth, C., Ensinger, C., Berger, A., Klocker, H., Goebel, G., & Widschwendter, M. (2005). Circulating tumor-specific DNA: a marker for monitoring efficacy of adjuvant therapy in cancer patients. Cancer Research, 65(4), 1141–1145.

Fraser, M., Berlin, A., Bristow, R. G., & Van der Kwast, T. (2015). Genomic, pathological, and clinical heterogeneity as drivers of personalized medicine in prostate cancer. Urologic Oncology: Seminars and Original Investigations, 33(2), 85–94.

Galbán, C. J., Chenevert, T. L., Meyer, C. R., Tsien, C., Lawrence, T. S., Hamstra, D. A., Junck, L., Sundgren, P. C., Johnson, T. D., & Ross, D. J. (2009). The parametric response map is an imaging biomarker for early cancer treatment outcome. Nature Medicine, 15(5), 572–576.

Ganggayah, M. D., Taib, N. A., Har, Y. C., Lio, P., & Dhillon, S. K. (2019). Predicting factors for survival of breast cancer patients using machine learning techniques. BMC Medical Informatics and Decision Making, 19, 1–17.

Gulshan, V., Peng, L., Coram, M., Stumpe, M. C., Wu, D., Narayanaswamy, A., Venugopalan, S., Widner, K., Madams, T., & Cuadros, J. (2016). Development and validation of a deep learning algorithm for detection of diabetic retinopathy in retinal fundus photographs. Jama, 316(22), 2402–2410.

Hess, G. P., Fonseca, E., Scott, R., & Fagerness, J. (2015). Pharmacogenomic and pharmacogenetic-guided therapy as a tool in precision medicine: current state and factors impacting acceptance by stakeholders. Genetics Research, 97, e13.

Hodi, F. S., O’day, S. J., McDermott, D. F., Weber, R. W., Sosman, J. A., Haanen, J. B., Gonzalez, R., Robert, C., Schadendorf, D., & Hassel, J. C. (2010). Improved survival with ipilimumab in patients with metastatic melanoma. New England Journal of Medicine, 363(8), 711–723.

Howe, F. A., Barton, S. J., Cudlip, S. A., Stubbs, M., Saunders, D. E., Murphy, M., Wilkins, P., Opstad, K. S., Doyle, V. L., & McLean, M. A. (2003). Metabolic profiles of human brain tumors using quantitative in vivo 1H magnetic resonance spectroscopy. Magnetic Resonance in Medicine: An Official Journal of the International Society for Magnetic Resonance in Medicine, 49(2), 223–232.

Institute, N. C. (2023). Treatment for Cancer. https://www.cancer.gov/about-cancer/treatment

Iqbal, M. J., Javed, Z., Sadia, H., Qureshi, I. A., Irshad, A., Ahmed, R., Malik, K., Raza, S., Abbas, A., & Pezzani, R. (2021). Clinical applications of artificial intelligence and machine learning in cancer diagnosis: looking into the future. Cancer Cell International, 21(1), 1–11.

Jinek, M., Chylinski, K., Fonfara, I., Hauer, M., Doudna, J. A., & Charpentier, E. (2012). A programmable dual-RNA–guided DNA endonuclease in adaptive bacterial immunity. Science, 337(6096), 816–821.

Khan, S. S., Catanzaro, J. A., & Yuryev, A. (2023). Precision-based immuno-molecular augmentation (pbima) computerized system, method, and therapeutic vaccine. Google Patents.

Kris, M. G., Johnson, B. E., Berry, L. D., Kwiatkowski, D. J., Iafrate, A. J., Wistuba, I. I., Varella-Garcia, M., Franklin, W. A., Aronson, S. L., & Su, P.-F. (2014). Using multiplexed assays of oncogenic drivers in lung cancers to select targeted drugs. Jama, 311(19), 1998–2006.

Kushi, L. H., Doyle, C., McCullough, M., Rock, C. L., Demark-Wahnefried, W., Bandera, E. V, Gapstur, S., Patel, A. V, Andrews, K., & Gansler, T. (2012). American Cancer Society Guidelines on nutrition and physical activity for cancer prevention: reducing the risk of cancer with healthy food choices and physical activity. CA: A Cancer Journal for Clinicians, 62(1), 30–67.

Lambin, P., Leijenaar, R. T. H., Deist, T. M., Peerlings, J., De Jong, E. E. C., Van Timmeren, J., Sanduleanu, S., Larue, R. T. H. M., Even, A. J. G., & Jochems, A. (2017). Radiomics: the bridge between medical imaging and personalized medicine. Nature Reviews Clinical Oncology, 14(12), 749–762.

Le Tourneau, C., Delord, J.-P., Gonçalves, A., Gavoille, C., Dubot, C., Isambert, N., Campone, M., Trédan, O., Massiani, M.-A., & Mauborgne, C. (2015). Molecularly targeted therapy based on tumour molecular profiling versus conventional therapy for advanced cancer (SHIVA): a multicentre, open-label, proof-of-concept, randomised, controlled phase 2 trial. The Lancet Oncology, 16(13), 1324–1334.

Lewis, S., Hectors, S., & Taouli, B. (2021). Radiomics of hepatocellular carcinoma. Abdominal Radiology, 46, 111–123.

Lu, H., Diaz, D. J., Czarnecki, N. J., Zhu, C., Kim, W., Shroff, R., Acosta, D. J., Alexander, B. R., Cole, H. O., Zhang, Y., Lynd, N. A., Ellington, A. D., & Alper, H. S. (2022). Machine learning-aided engineering of hydrolases for PET depolymerization. Nature, 604(7907), 662–667. https://doi.org/10.1038/s41586-022-04599-z

Mirzaie, A., Halaji, M., Dehkordi, F. S., Ranjbar, R., & Noorbazargan, H. (2020). A narrative literature review on conventional medicine options for treatment of corona virus disease 2019 (COVID-19). Complementary Therapies in Clinical Practice, 40. https://doi.org/10.1016/j.ctcp.2020.101214

Navin, N., & Hicks, J. (2011). Future medical applications of single-cell sequencing in cancer. Genome Medicine, 3, 1–12.

O’Connor, J. P. B., Aboagye, E. O., Adams, J. E., Aerts, H. J. W. L., Barrington, S. F., Beer, A. J., Boellaard, R., Bohndiek, S. E., Brady, M., & Brown, G. (2017). Imaging biomarker roadmap for cancer studies. Nature Reviews Clinical Oncology, 14(3), 169–186.

Pantel, K., & Alix-Panabières, C. (2019). Liquid biopsy and minimal residual disease—latest advances and implications for cure. Nature Reviews Clinical Oncology, 16(7), 409–424.

Pardoll, D. M. (2012). The blockade of immune checkpoints in cancer immunotherapy. Nature Reviews Cancer, 12(4), 252–264.

Patel, A. P., Tirosh, I., Trombetta, J. J., Shalek, A. K., Gillespie, S. M., Wakimoto, H., Cahill, D. P., Nahed, B. V, Curry, W. T., & Martuza, R. L. (2014). Single-cell RNA-seq highlights intratumoral heterogeneity in primary glioblastoma. Science, 344(6190), 1396–1401.

Peer, D., Karp, J. M., Hong, S., Farokhzad, O. C., Margalit, R., & Langer, R. (2007). Nanocarriers as an emerging platform for cancer therapy. Nature Nanotechnology, 2(12), 751–760.

Penas-Prado, M., & Gilbert, M. R. (2007). Molecularly targeted therapies for malignant gliomas: advances and challenges. Expert Review of Anticancer Therapy, 7(5), 641–661.

Robert, C., Long, G. V, Brady, B., Dutriaux, C., Maio, M., Mortier, L., Hassel, J. C., Rutkowski, P., McNeil, C., & Kalinka-Warzocha, E. (2015). Nivolumab in previously untreated melanoma without BRAF mutation. New England Journal of Medicine, 372(4), 320–330.

Rock, C. L., Doyle, C., Demark-Wahnefried, W., Meyerhardt, J., Courneya, K. S., Schwartz, A. L., Bandera, E. V, Hamilton, K. K., Grant, B., & McCullough, M. (2012). Nutrition and physical activity guidelines for cancer survivors. CA: A Cancer Journal for Clinicians, 62(4), 242–274.

Roychowdhury, S., Iyer, M. K., Robinson, D. R., Lonigro, R. J., Wu, Y.-M., Cao, X., Kalyana-Sundaram, S., Sam, L., Balbin, O. A., & Quist, M. J. (2011). Personalized oncology through integrative high-throughput sequencing: a pilot study. Science Translational Medicine, 3(111), 111ra121-111ra121.

Savell, K. E., Bach, S. V, Zipperly, M. E., Revanna, J. S., Goska, N. A., Tuscher, J. J., Duke, C. G., Sultan, F. A., Burke, J. N., & Williams, D. (2019). A neuron-optimized CRISPR/dCas9 activation system for robust and specific gene regulation. Eneuro, 6(1).

Schott, A. F., Goldstein, L. J., Cristofanilli, M., Ruffini, P. A., McCanna, S., Reuben, J. M., Perez, R. P., Kato, G., & Wicha, M. (2017). Phase Ib Pilot Study to Evaluate Reparixin in Combination with Weekly Paclitaxel in Patients with HER-2–Negative Metastatic Breast CancerReparixin and Weekly Paclitaxel in Metastatic Breast Cancer. Clinical Cancer Research, 23(18), 5358–5365.

Schwaederle, M., Zhao, M., Lee, J. J., Eggermont, A. M., Schilsky, R. L., Mendelsohn, J., Lazar, V., & Kurzrock, R. (2015). Impact of precision medicine in diverse cancers: a meta-analysis of phase II clinical trials. Journal of Clinical Oncology, 33(32), 3817.

Siravegna, G., & Bardelli, A. (2014). Genotyping cell-free tumor DNA in the blood to detect residual disease and drug resistance. Genome Biology, 15, 1–6.

Society, A. C. (2023). What is Chemotherapy? https://www.cancer.org/cancer/managing-cancer/treatment-types/chemotherapy.html

Teixeira, M. Z. (2020). Clinical research protocol to evaluate the effectiveness and safety of individualized homeopathic medicine in the treatment and prevention of the COVID-19 epidemic (p. 60). http://fi-admin.bvsalud.org/document/view/vt87x

Thierry, A. R., El Messaoudi, S., Mollevi, C., Raoul, J. L., Guimbaud, R., Pezet, D., Artru, P., Assenat, E., Borg, C., & Mathonnet, M. (2017). Clinical utility of circulating DNA analysis for rapid detection of actionable mutations to select metastatic colorectal patients for anti-EGFR treatment. Annals of Oncology, 28(9), 2149–2159.

Topalian, S. L., Hodi, F. S., Brahmer, J. R., Gettinger, S. N., Smith, D. C., McDermott, D. F., Powderly, J. D., Carvajal, R. D., Sosman, J. A., & Atkins, M. B. (2012). Safety, activity, and immune correlates of anti–PD-1 antibody in cancer. New England Journal of Medicine, 366(26), 2443–2454.

Tsimberidou, A.-M., Wen, S., Hong, D. S., Wheler, J. J., Falchook, G. S., Fu, S., Piha-Paul, S., Naing, A., Janku, F., & Aldape, K. (2014). Personalized medicine for patients with advanced cancer in the phase I program at MD Anderson: validation and landmark analyses. Clinical Cancer Research, 20(18), 4827–4836.

Turnbull, A. K. (2015). Personalized medicine in cancer: where are we today? Future Oncology, 11(20), 2795–2798.

Verma, M. (2012). Personalized medicine and cancer. Journal of Personalized Medicine, 2(1), 1–14.

Wan, J. C. M., Massie, C., Garcia-Corbacho, J., Mouliere, F., Brenton, J. D., Caldas, C., Pacey, S., Baird, R., & Rosenfeld, N. (2017). Liquid biopsies come of age: towards implementation of circulating tumour DNA. Nature Reviews Cancer, 17(4), 223–238.

Wang, J., Chang, S., Li, G., & Sun, Y. (2017). Application of liquid biopsy in precision medicine: opportunities and challenges. Frontiers of Medicine, 11, 522–527.

Wang, L.-X., & Xie, Y.-M. (2020). Suggestions on design of evidence-based conventional Chinese medicine clinical study for new public health emergencies. Zhongguo Zhongyao Zazhi, 45(10), 2291–2295. https://doi.org/10.19540/j.cnki.cjcmm.20200318.501

Weitzel, J. N., Blazer, K. R., MacDonald, D. J., Culver, J. O., & Offit, K. (2011). Genetics, genomics, and cancer risk assessment: state of the art and future directions in the era of personalized medicine. CA: A Cancer Journal for Clinicians, 61(5), 327–359.

Wistuba, I. I., Gelovani, J. G., Jacoby, J. J., Davis, S. E., & Herbst, R. S. (2011). Methodological and practical challenges for personalized cancer therapies. Nature Reviews Clinical Oncology, 8(3), 135–141.

Yuryev, A., Catanzaro, J., & Khan, M. S. S. (2019a). Combined Analysis of Tumor RNAseq, Urine Proteomics and WES Profiles from Patient with Gallbladder Cancer. Biosciences, 1(1), 026-105. doi:10.25163/biosciences.112091DB112921119

Dillman, R. O. (2005). International Society for Biological Therapy for Cancer: 20th Anniversary. Journal of Immunotherapy, 28(3), 169-174.

PDF
Abstract
Export Citation

View Dimensions


View Plumx


View Altmetric




Save
0
Citation
341
View

Share