Advanced Biomarkers and Precision Medicine: Innovative Strategies to Prevent Cancer Recurrence

Advanced Biomarkers and Precision Medicine: Innovative Strategies to Prevent Cancer Recurrence

Authors

  • M. Shankar Ganesh Department of Pharmacy Practice, JKKN College of Pharmacy, Salem - Kochi Hwy, Tamil Nadu 638183, India https://orcid.org/0009-0007-1322-3413
  • R. Revanth Department of Pharmacy Practice, JKKN College of Pharmacy, Salem - Kochi Hwy, Tamil Nadu 638183, India
  • C. Mahesh Elaya Bharathi Department of Pharmacy Practice, JKKN College of Pharmacy, Salem - Kochi Hwy, Tamil Nadu 638183, India

DOI:

https://doi.org/10.30683/1929-2279.2025.14.01

Keywords:

Cancer reoccurrence, Precision medicine strategy, Immunotherapy Approaches, Genetic and Molecular Profiling, Predictive Biomarkers, Liquid Biopsies, AI tool

Abstract

Objective: This review aims to synthesize evidence on the efficacy and challenges of precision medicine strategies in cancer treatment, focusing on their role in mitigating recurrence and enhancing patient-specific therapy.

Data Sources: Examination of current literature on precision medicine techniques such as immunotherapy (including checkpoint inhibitors, adoptive cell therapy, and cancer vaccines), genetic and molecular profiling for personalized treatment strategies, predictive biomarkers for selecting responsive patients, AI for improved diagnostic and prognostic accuracy, and liquid biopsies for non-invasive monitoring of minimal residual disease.

Conclusion: Precision medicine in oncology offers a paradigm shift toward personalized care, potentially reducing cancer recurrence through tailored treatment modalities. While immunotherapy introduces novel mechanisms to fight cancer, its efficacy is sometimes limited by tumor evolution. Genetic and molecular profiling, along with predictive biomarkers, enable the customization of therapy plans. AI and machine learning algorithms promise to refine detection, treatment, and monitoring processes. Liquid biopsies emerge as a pivotal tool for early detection and surveillance of cancer recurrence. Further research and clinical trials are crucial for integrating these advanced strategies into standard care, aiming to enhance patient outcomes and minimize recurrence rates.

References

Sathishkumar K, Chaturvedi M, Das P, Stephen S, Mathur P. Cancer incidence estimates for 2022 & projection for 2025: Result from National Cancer Registry Programme, India. The Indian Journal of Medical Research. Published online December 13, 2022. DOI: https://doi.org/10.4103/ijmr.ijmr_1821_22

Kulothungan V, Sathishkumar K, Leburu S, et al. Burden of cancers in India - estimates of cancer crude incidence, YLLs, YLDs and DALYs for 2021 and 2025 based on National Cancer Registry Program. BMC Cancer 2022; 22(1). DOI: https://doi.org/10.1186/s12885-022-09578-1

Gavas S, Quazi S, Karpiński TM. Nanoparticles for Cancer Therapy: Current Progress and Challenges. Nanoscale Research Letters 2021; 16(1). DOI: https://doi.org/10.1186/s11671-021-03628-6

Berardi R, Morgese F, Rinaldi S, et al. Benefits and Limitations of a Multidisciplinary Approach in Cancer Patient Management. Cancer Management and Research 2020; Volume 12: 9363-9374. DOI: https://doi.org/10.2147/CMAR.S220976

Schwaederle M, Zhao M, Lee JJ, et al. Impact of Precision Medicine in Diverse Cancers: A Meta-Analysis of Phase II Clinical Trials. Journal of Clinical Oncology 2015; 33(32): 3817-3825. DOI: https://doi.org/10.1200/JCO.2015.61.5997

Gandara DR, Li T, Lara PN, et al. Algorithm for Codevelopment of New Drug-Predictive Biomarker Combinations: Accounting for Inter- and Intrapatient Tumor Heterogeneity 2012; 13(5): 321-325. DOI: https://doi.org/10.1016/j.cllc.2012.05.004

Courtney D, Davey MG, Moloney BM, et al. Breast cancer recurrence: factors impacting occurrence and survival. Irish Journal of Medical Sciences (IJMS) 2022; 191(6): 2501-2510. DOI: https://doi.org/10.1007/s11845-022-02926-x

Mahvi DA, Liu R, Grinstaff MW, Colson YL, Raut CP. Local Cancer Recurrence: The Realities, Challenges, and Opportunities for New Therapies. CA - A Cancer Journal for Clinicians 2018; 68(6): 488-505. DOI: https://doi.org/10.3322/caac.21498

Esmatabadi MJD, Bakhshinejad B, Motlagh FM, Babashah S, Sadeghizadeh M. Therapeutic resistance and cancer recurrence mechanisms: Unfolding the story of tumour coming back. Journal of Biosciences 2016; 41(3): 497-506. DOI: https://doi.org/10.1007/s12038-016-9624-y

Spring L, Bardia A, Modi S. Advances in systemic therapies for triple negative breast cancer. BMJ 2023; 376: o232.

Wang J, Wu SG. Breast Cancer: An Overview of Current Therapeutic Strategies, Challenge, and Perspectives. Breast Cancer: Targets and Therapy 2023; Volume 15: 721-730. DOI: https://doi.org/10.2147/BCTT.S432526

Ashrafi A, Akter Z, Modareszadeh P, et al. Current Landscape of Therapeutic Resistance in Lung Cancer and Promising Strategies to Overcome Resistance. Cancers 2022; 14(19): 4562. DOI: https://doi.org/10.3390/cancers14194562

Gyanani V, Haley JC, Goswami R. Challenges of Current Anticancer Treatment Approaches with Focus on Liposomal Drug Delivery Systems. Pharmaceuticals 2021; 14(9): 835. DOI: https://doi.org/10.3390/ph14090835

Sameer Ullah Khan, Fatima K, Shariqa Aisha, Malik F. Unveiling the mechanisms and challenges of cancer drug resistance. Cell Communication and Signaling 2024; 22(1). DOI: https://doi.org/10.1186/s12964-023-01302-1

Xie J, Qi W, Cao L, et al. Predictors for Fear of Cancer Recurrence in Breast Cancer Patients Referred to Radiation Therapy During the COVID-19 Pandemic: A Multi-Center Cross-Section Survey. Frontiers in Oncology 2021; 11. DOI: https://doi.org/10.3389/fonc.2021.650766

Aronson SL, Stein van, Sonke GS, Driel van. Future of HIPEC for ovarian cancer. BJOG: An International Journal of Obstetrics and Gynaecology 2022; 130(2): 135-140. DOI: https://doi.org/10.1111/1471-0528.17289

Chi C, Du Y, Ye J, et al. Intraoperative Imaging-Guided Cancer Surgery: From Current Fluorescence Molecular Imaging Methods to Future Multi-Modality Imaging Technology. Theranostics 2014; 4(11): 1072-1084. DOI: https://doi.org/10.7150/thno.9899

Nicole White-Al Habeeb, Vathany Kulasingam, Diamandis EP, et al. The Use of Targeted Therapies for Precision Medicine in Oncology. Clinical Chemistry 2016; 62(12): 1556-1564. DOI: https://doi.org/10.1373/clinchem.2015.247882

Sosinsky A, Ambrose J, Cross W, et al. Insights for precision oncology from the integration of genomic and clinical data of 13,880 tumors from the 100,000 Genomes Cancer Programme. Nature Medicine. Published online January 11, 2024: 1-11. DOI: https://doi.org/10.1038/s41591-023-02682-0

Hinshaw DC, Shevde LA. The Tumor Microenvironment Innately Modulates Cancer Progression. Cancer Research 2019; 79(18): 4557-4566. DOI: https://doi.org/10.1158/0008-5472.CAN-18-3962

Gajewski TF, Schreiber H, Fu YX. Innate and adaptive immune cells in the tumor microenvironment. Nature Immunology 2013; 14(10): 1014-1022. DOI: https://doi.org/10.1038/ni.2703

Shalapour S, Karin M. Immunity, inflammation, and cancer: an eternal fight between good and evil. Journal of Clinical Investigation 2015; 125(9): 3347-3355. DOI: https://doi.org/10.1172/JCI80007

Srinivas PR, Kramer BS, Srivastava S. Trends in biomarker research for cancer detection. The Lancet Oncology 2001; 2(11): 698-704. DOI: https://doi.org/10.1016/S1470-2045(01)00560-5

Keshaviah A, Dellapasqua S, Rotmensz N, et al. CA15-3 and alkaline phosphatase as predictors for breast cancer recurrence: a combined analysis of seven International Breast Cancer Study Group trials. Annals of Oncology 2007; 18(4): 701-708. DOI: https://doi.org/10.1093/annonc/mdl492

Garcia-Murillas I, Schiavon G, Weigelt B, et al. Mutation tracking in circulating tumor DNA predicts relapse in early breast cancer. Science Translational Medicine 2015; 7(302): 302ra133-302ra133. DOI: https://doi.org/10.1126/scitranslmed.aab0021

Jae Youl Cho, Jae Hoon Lim, Jae Hoon Cheong, et al. Gene Expression Signature–Based Prognostic Risk Score in Gastric Cancer 2011; 17(7): 1850-1857. DOI: https://doi.org/10.1158/1078-0432.CCR-10-2180

Daoud M, Mayo M. A survey of neural network-based cancer prediction models from microarray data. Artificial Intelligence in Medicine 2019; 97: 204-214. DOI: https://doi.org/10.1016/j.artmed.2019.01.006

Kussmann M, Rezzi S, Daniel H. Profiling techniques in nutrition and health research. Current Opinion in Biotechnology 2008; 19(2): 83-99. DOI: https://doi.org/10.1016/j.copbio.2008.02.003

Kaddurah-Daouk R, Kristal BS, Weinshilboum RM. Metabolomics: A Global Biochemical Approach to Drug Response and Disease. Annual Review of Pharmacology and Toxicology 2008; 48(1): 653-683. DOI: https://doi.org/10.1146/annurev.pharmtox.48.113006.094715

Simon R. Sensitivity, Specificity, PPV, and NPV for Predictive Biomarkers. Journal of the National Cancer Institute 2015; 107(8): djv153. DOI: https://doi.org/10.1093/jnci/djv153

Macerola E, Poma AM, Vignali P, et al. Predictive Biomar-kers in Thyroid Cancer. Frontiers in Oncology 2022; 12. DOI: https://doi.org/10.3389/fonc.2022.901004

Pao W, Miller VA. Epidermal Growth Factor Receptor Mutations, Small-Molecule Kinase Inhibitors, and Non–Small-Cell Lung Cancer: Current Knowledge and Future Directions. Journal of Clinical Oncology 2005; 23(11): 2556-2568. DOI: https://doi.org/10.1200/JCO.2005.07.799

Voss MH, A. Ari Hakimi, Pham CG, et al. Tumor Genetic Analyses of Patients with Metastatic Renal Cell Carcinoma and Extended Benefit from mTOR Inhibitor Therapy. Clinical Cancer Research 2014; 20(7): 1955-1964. DOI: https://doi.org/10.1158/1078-0432.CCR-13-2345

Mushtaq A, Kapoor V, Latif A, et al. Efficacy and toxicity profile of carfilzomib based regimens for treatment of multiple myeloma: A systematic review. Critical Reviews in Oncology/Hematology 2018; 125: 1-11. DOI: https://doi.org/10.1016/j.critrevonc.2018.02.008

Volpe G, Cignetti A, Panuzzo C, et al. Alternative BCR/ABL Splice Variants in Philadelphia Chromosome–Positive Leukemias Result in Novel Tumor-Specific Fusion Proteins that May Represent Potential Targets for Immunotherapy Approaches. Cancer Research 2007; 67(11): 5300-5307. DOI: https://doi.org/10.1158/0008-5472.CAN-06-3737

Hudis CA. Trastuzumab — Mechanism of Action and Use in Clinical Practice. New England Journal of Medicine 2007; 357(1): 39-51. DOI: https://doi.org/10.1056/NEJMra043186

Cremolini C, Antoniotti C, Lonardi S, et al. Activity and Safety of Cetuximab Plus Modified FOLFOXIRI Followed by Maintenance With Cetuximab or Bevacizumab for RAS and BRAF Wild-type Metastatic Colorectal Cancer: A Randomized Phase 2 Clinical Trial. JAMA oncology 2018; 4(4): 529-536. DOI: https://doi.org/10.1001/jamaoncol.2017.5314

Robak T, Dmoszynska A, Solal-Céligny P, et al. Rituximab Plus Fludarabine and Cyclophosphamide Prolongs Progression-Free Survival Compared With Fludarabine and Cyclophosphamide Alone in Previously Treated Chronic Lymphocytic Leukemia. Journal of Clinical Oncology 2010; 28(10): 1756-1765. DOI: https://doi.org/10.1200/JCO.2009.26.4556

Dappa E, Elger T, Hasenburg A, Düber C, Battista MJ, Hötker AM. The value of advanced MRI techniques in the assessment of cervical cancer: a review. Insights into Imaging 2017; 8(5): 471-481. DOI: https://doi.org/10.1007/s13244-017-0567-0

Wang Z, Xiao XL, Zhang ZT, He K, Hu F. A Radiomics Model for Predicting Early Recurrence in Grade II Gliomas Based on Preoperative Multiparametric Magnetic Resonance Imaging. Frontiers in Oncology 2021; 11. DOI: https://doi.org/10.3389/fonc.2021.684996

West CM, Barnett GC. Genetics and genomics of radiotherapy toxicity: towards prediction. Genome Medicine 2011; 3(8): 52. DOI: https://doi.org/10.1186/gm268

Venook AP, Niedzwiecki D, Lopatin M, et al. Biologic Determinants of Tumor Recurrence in Stage II Colon Cancer: Validation Study of the 12-Gene Recurrence Score in Cancer and Leukemia Group B (CALGB) 9581. Journal of Clinical Oncology 2013; 31(14): 1775-1781. DOI: https://doi.org/10.1200/JCO.2012.45.1096

Mandalà M, Galli F, Cattaneo L, et al. Mitotic rate correlates with sentinel lymph node status and outcome in cutaneous melanoma greater than 1 millimeter in thickness: A multi-institutional study of 1524 cases. Journal of the American Academy of Dermatology 2017; 76(2): 264-273.e2. DOI: https://doi.org/10.1016/j.jaad.2016.08.066

FRIEDMAN GD, VAN DEN EEDEN SK. Risk Factors for Pancreatic Cancer: An Exploratory Study. International Journal of Epidemiology 1993; 22(1): 30-37. DOI: https://doi.org/10.1093/ije/22.1.30

Barlesi F, Mazieres J, Merlio JP, et al. Routine molecular profiling of patients with advanced non-small-cell lung cancer: results of a 1-year nationwide programme of the French Cooperative Thoracic Intergroup (IFCT). The Lancet 2016; 387(10026): 1415-1426. DOI: https://doi.org/10.1016/S0140-6736(16)00004-0

Malone ER, Oliva M, Sabatini PJB, Stockley TL, Siu LL. Molecular profiling for precision cancer therapies. Genome Medicine 2020; 12(1). DOI: https://doi.org/10.1186/s13073-019-0703-1

Hackenberg M, Barturen G, Oliver JL. NGSmethDB: a database for next-generation sequencing single-cytosine-resolution DNA methylation data. Nucleic Acids Research 2010; 39(Database): D75-D79. DOI: https://doi.org/10.1093/nar/gkq942

Bettegowda C, Sausen M, Leary RJ, et al. Detection of circulating tumor DNA in early- and late-stage human malignancies. Science translational medicine 2014; 6(224): 224ra24.

Nowell P. The clonal evolution of tumor cell populations. Science 1976; 194(4260): 23-28 DOI: https://doi.org/10.1126/science.959840

Mahmood H, Shaban M, Rajpoot N, Khurram SA. Artificial Intelligence-based methods in head and neck cancer diagnosis: an overview. British Journal of Cancer 2021; 124(12): 1934-1940. DOI: https://doi.org/10.1038/s41416-021-01386-x

Jiang F, Jiang Y, Zhi H. Artificial intelligence in healthcare: past, present and future. Stroke and Vascular Neurology 2017; 2(4): 230-243. DOI: https://doi.org/10.1136/svn-2017-000101

Oermann EK, Kress MAS, Collins BT, et al. Predicting Survival in Patients With Brain Metastases Treated With Radiosurgery Using Artificial Neural Networks. Neurosurgery 2013; 72(6): 944-952. DOI: https://doi.org/10.1227/NEU.0b013e31828ea04b

Kim D, Joung JG, Sohn KA, et al. Knowledge boosting: a graph-based integration approach with multi-omics data and genomic knowledge for cancer clinical outcome prediction. Journal of the American Medical Informatics Association 2014; 22(1): 109-120. DOI: https://doi.org/10.1136/amiajnl-2013-002481

Vazquez AI, Veturi Y, Behring M, et al. Increased Proportion of Variance Explained and Prediction Accuracy of Survival of Breast Cancer Patients with Use of Whole-Genome Multiomic Profiles. Genetics 2016; 203(3): 1425-1438. DOI: https://doi.org/10.1534/genetics.115.185181

Siravegna G, Marsoni S, Siena S, Bardelli A. Integrating liquid biopsies into the management of cancer. Nature Reviews Clinical Oncology 2017; 14(9): 531-548. DOI: https://doi.org/10.1038/nrclinonc.2017.14

van Dongen J, Macintyre E, Gabert J, et al. Standardized RT-PCR analysis of fusion gene transcripts from chromosome aberrations in acute leukemia for detection of minimal residual disease. Leukemia 1999; 13(12): 1901-1928. DOI: https://doi.org/10.1038/sj.leu.2401592

Young Joo Lee, Yoon KA, Han JY, et al. Circulating Cell-Free DNA in Plasma of Never Smokers with Advanced Lung Adenocarcinoma Receiving Gefitinib or Standard Chemotherapy as First-Line Therapy. Clinical Cancer Research 2011; 17(15): 5179-5187. DOI: https://doi.org/10.1158/1078-0432.CCR-11-0400

Coombes RC, Page K, Salari R, et al. Personalized Detection of Circulating Tumor DNA Antedates Breast Cancer Metastatic Recurrence. Clinical Cancer Research 2019; 25(14): 4255-4263. DOI: https://doi.org/10.1158/1078-0432.CCR-18-3663

Deng X, Nakamura Y. Cancer Precision Medicine: From Cancer Screening to Drug Selection and Personalized Immunotherapy. Trends in Pharmacological Sciences 2017; 38(1): 15-24. DOI: https://doi.org/10.1016/j.tips.2016.10.013

Jordan EJ, Kim HR, Arcila ME, et al. Prospective comprehensive molecular characterization of lung adenocarcinomas for efficient patient matching to approved and emerging therapies. Cancer Discov 2017; 7(6): 596-609. DOI: https://doi.org/10.1158/2159-8290.CD-16-1337

Su Z, Dias-Santagata D, Duke M, et al. A platform for rapid detection of multiple oncogenic mutations with relevance to targeted therapy in non-small-cell lung cancer. J Mol Diagn 2011; 13(1): 74-84. DOI: https://doi.org/10.1016/j.jmoldx.2010.11.010

MacConaill LE, Garcia E, Shivdasani P, et al. Prospective enterprise-level molecular genotyping of a cohort of cancer patients 2014; 16(6): 660-672. DOI: https://doi.org/10.1016/j.jmoldx.2014.06.004

Li T, Kung HJ, Mack PC, Gandara DR. Genotyping and genomic profiling of non-small-cell lung cancer: Implications for current and future therapies. J Clin Oncol 2013; 31(8): 1039-1049. DOI: https://doi.org/10.1200/JCO.2012.45.3753

Zehir A, Benayed R, Shah RH, et al. Mutational landscape of metastatic cancer revealed from prospective clinical sequencing of 10,000 patients. Nat Med 2017; 23(6): 703-713. DOI: https://doi.org/10.1038/nm.4333

Kanai M, Yoshimura K, Tsumura T, et al. Current clinical practice of precision medicine using comprehensive genomic profiling tests in biliary tract cancer in Japan. Curr Oncol 2022; 29(10): 7272-7284. DOI: https://doi.org/10.3390/curroncol29100573

Levantini E, et al. Editorial: Impact of tumor microenvironment on lung cancer. Front Oncol 2023. DOI: https://doi.org/10.3389/fonc.2023.1136803

Pittet MJ, et al. Deciphering tumor microenvironment: CXCL9 and SPP1 as crucial determinants of tumor-associated macrophage polarity and prognostic indicators. Mol Cancer 2023. Available at: https://molecular-cancer.biomedcentral.com/articles/10.1186/s12943-023-01540-2.

Sun X, et al. Tumor microenvironment and cancer therapy. Front Oncol 2022. Available at: https://www.frontiersin.org/ articles/10.3389/fonc.2022.1136803/full.

Chen Y, et al. Roles of hypoxia in the tumor microenvironment and targeted therapy. Front Oncol 2023. DOI: https://doi.org/10.3389/fonc.2022.961637

Tumor microenvironment remodeling after neoadjuvant immunotherapy in non-small cell lung cancer revealed by single-cell RNA sequencing. Genome Med 2023.

Wei X, Dong J. Reactivation of ERK and Akt confers resistance of mutant BRAF colon cancer cells to the HSP90 inhibitor AUY922. Oncotarget 2016; 7(49): 49597-49610. DOI: https://doi.org/10.18632/oncotarget.10414

Shin YK, et al. Identification of novel protein biomarkers and drug targets for colorectal cancer by integrating human plasma proteome with genome. Genome Med 2023. Available at: https://genomemedicine.biomedcentral.com/ articles/10.1186/s13073-023-01012-1.

Fan J, et al. Biomarkers for immune checkpoint inhibitors in colorectal cancer: recent advances and future perspectives. Cancer Biol Med 2023. Available at: https://www.cancerbio-med.org/index.php/cocr/article/view/2154.

Chu L, et al. Identification of exosome protein panels as predictive biomarkers for non-small cell lung cancer. Biol Proced Online 2023. Available at: https://biologicalpro-ceduresonline.biomedcentral.com/articles/10.1186/s12575-023-00169-3.

Tan S, et al. Engineering biomarkers through systems biology for cancer therapy. Biomark Res 2023. Available at: https://biomarkerres.biomedcentral.com/articles/10.1186/s40364-023-00405-8.

Lê MG, et al. Machine learning-based models for the prediction of breast cancer recurrence risk. BMC Med Inform Decis Mak 2023. Available at: https://bmcmedinform-decismak.biomedcentral.com/articles/10.1186/s12911-023-01924-3.

Singh R, et al. Cervical cancer survival prediction by machine learning algorithms: a systematic review. BMC Cancer 2023.

Lee M. Deep Learning Techniques with Genomic Data in Cancer Prognosis: A Comprehensive Review of the 2021–2023 Literature. MDPI Biology 2023; 12(7): 893. DOI: https://doi.org/10.3390/biology12070893

Chen Y, et al. Machine learning prediction of pathological complete response and overall survival of breast cancer patients in an underserved inner-city population. Breast Cancer Res 2023.

Downloads

Published

2025-01-29

How to Cite

Ganesh, M. S. ., Revanth, R. ., & Elaya Bharathi, C. M. . (2025). Advanced Biomarkers and Precision Medicine: Innovative Strategies to Prevent Cancer Recurrence. Journal of Cancer Research Updates, 14, 1–11. https://doi.org/10.30683/1929-2279.2025.14.01

Issue

Section

Articles
Loading...