Precision oncology: Advances, strategies, challenges

Benjamin Lewis

doi:10.35841/aatr-9.3.193

Short Communication - Journal of Translational Research (2025) Volume 9, Issue 3

Precision oncology: Advances, strategies, challenges

Benjamin Lewis^*

Department of Oncology Research, University of Melbourne, Melbourne, Australia

*Corresponding Author:: Benjamin Lewis
Department of Oncology Research
University of Melbourne, Melbourne, Australia.
E-mail: benjamin.lewis@unimelb.edu.au

Received : 03-Jul-2025, Manuscript No. aatr-194; Editor assigned : 07-Jul-2025, PreQC No. aatr-194(PQ); Reviewed : 25-Jul-2025, QC No aatr-194; Revised : 05-Aug-2025, Manuscript No. aatr-194(R); Published : 14-Aug-2025 , DOI : 10.35841/aatr-9.3.194

Citation: Lewis B. Precision oncology: Advances, strategies, challenges. aatr. 2025;09(03):194.

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Introduction

This article explores the latest developments in precision oncology for non-small cell lung cancer (NSCLC). It highlights new therapeutic strategies, including targeted therapies and immunotherapies, which significantly improved patient outcomes. The discussion also covers the ongoing challenges in translating these advancements into routine clinical practice, emphasizing the need for robust biomarker identification and resistance mechanisms understanding [1].

This review focuses on the application of liquid biopsy in non-small cell lung cancer (NSCLC), particularly for early detection and monitoring of minimal residual disease. It discusses the evolving landscape of biomarkers found in liquid samples, such as circulating tumor DNA (ctDNA) and circulating tumor cells (CTCs), and their potential to revolutionize NSCLC management by enabling timely interventions and personalized treatment adjustments [2].

This paper investigates how to improve precision oncology by tackling the challenge of drug resistance in cancer. It delves into the molecular mechanisms that lead to therapeutic failure and explores strategies to circumvent or overcome these resistance pathways. The authors emphasize the importance of comprehensive molecular profiling and adaptive treatment strategies to maintain long-term efficacy and improve patient outcomes [3].

This review explores the growing role of artificial intelligence (AI) and machine learning (ML) in precision oncology. It details various applications, including biomarker discovery, predictive modeling for treatment response, and drug repurposing. The article also addresses the inherent challenges, such as data privacy, model interpretability, and the need for robust validation, highlighting the translational gap between AI research and clinical utility [4].

This article critically evaluates the current state of CAR T-cell therapy for solid tumors, an area presenting unique translational challenges compared to hematologic malignancies. It outlines key obstacles like antigen heterogeneity, the immunosuppressive tumor microenvironment, and systemic toxicity. The authors discuss innovative strategies under investigation, including novel CAR designs and combination therapies, aiming to enhance efficacy and safety for solid tumor patients [5].

This paper underscores the pivotal role of the tumor microenvironment (TME) in governing cancer progression and therapeutic outcomes. It elaborates on the complex interplay between cancer cells and various stromal components, immune cells, and extracellular matrix, highlighting how these interactions influence tumor growth, metastasis, and resistance to treatment. The authors discuss strategies for therapeutically targeting the TME to enhance existing cancer therapies [6].

This article delves into the complex landscape of biomarker discovery and validation within immuno-oncology. It outlines the significant challenges, such as tumor heterogeneity and the dynamic nature of immune responses, but also highlights emerging opportunities, including advanced genomic and proteomic platforms. The discussion emphasizes the critical need for rigorous translational pipelines to bring reliable predictive and prognostic biomarkers to clinical practice for immune checkpoint inhibitor therapies [7].

This review highlights the exciting progress in nanotechnology-based drug delivery systems for cancer therapy. It discusses how nanocarriers can improve drug solubility, target specificity, and reduce off-target toxicity, thereby enhancing therapeutic efficacy. The article also addresses the significant translational hurdles, including scalable manufacturing, regulatory approval, and long-term safety, which need to be overcome for widespread clinical adoption [8].

This article highlights the emerging field of epigenetic therapy as a promising avenue for precision oncology. It reviews various epigenetic targets and the development of drugs, such as histone deacetylase inhibitors and DNA methyltransferase inhibitors, for cancer treatment. The authors discuss the potential for these therapies to reverse drug resistance and enhance the efficacy of conventional treatments, emphasizing the need for robust biomarker identification to guide patient selection [9].

This article explores the intricate relationship between the gut microbiome and cancer, examining its influence on both carcinogenesis and the response to various cancer therapies, particularly immunotherapy. It synthesizes current evidence on how microbial composition can modulate anti-tumor immunity and drug metabolism. The authors discuss the exciting translational implications, such as fecal microbiota transplantation and dietary interventions, for optimizing cancer treatment strategies [10].

Conclusion

Recent advancements in cancer research highlight a multifaceted approach to precision oncology. New therapeutic strategies for non-small cell lung cancer (NSCLC), including targeted therapies and immunotherapies, have significantly improved patient outcomes, though challenges remain in biomarker identification and understanding resistance mechanisms. Liquid biopsy is transforming early detection and minimal residual disease monitoring in NSCLC through biomarkers like ctDNA and CTCs. Overcoming drug resistance is a key focus, requiring insights into molecular mechanisms and adaptive treatment strategies. Artificial Intelligence and Machine Learning are increasingly integrated into precision oncology for biomarker discovery and predictive modeling, despite facing hurdles in data privacy and validation. For solid tumors, CAR T-cell therapy faces unique challenges such as antigen heterogeneity and the immunosuppressive tumor microenvironment, necessitating innovative designs and combination therapies. The tumor microenvironment itself is critical for cancer progression and therapeutic response, making its targeted modulation a promising strategy. Biomarker discovery and validation in immuno-oncology also require rigorous translational pipelines due to tumor heterogeneity and dynamic immune responses. Emerging fields like epigenetic therapy offer new ways to reverse drug resistance, while nanotechnology-based drug delivery systems aim to enhance drug solubility and target specificity, though translational hurdles exist. Finally, the gut microbiome's intricate role in carcinogenesis and therapy response, particularly immunotherapy, suggests new translational implications for optimizing treatment through interventions like fecal microbiota transplantation and dietary adjustments.