Volume 5, Issue 3 e70065
REVIEW ARTICLE
Open Access

Molecular mechanisms of ageing in cancer development and therapeutic response: Translational implications for precision oncology

Laiba Husain

Corresponding Author

Laiba Husain

Department of Social and Behavioral Sciences, Peter O'Donnell Jr. School of Public Health, University of Texas Southwestern Medical Center, Dallas, Texas, USA

Correspondence

Laiba Husain, PhD Peter O'Donnell Jr. School of Public Health UT Southwestern Medical Center 5323 Harry Hines Boulevard, Dallas, TX 75390–9066, USA.

Email: [email protected]

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First published: 23 June 2025

Abstract

Background

The intricate relationship between cellular ageing processes and cancer development represents one of the most significant challenges in contemporary oncology. As populations worldwide experience unprecedented demographic shifts towards advanced age, understanding the molecular mechanisms that link ageing to cancer initiation, progression, and therapeutic response has become essential for developing effective precision medicine approaches.

Main body

This review examines the fundamental molecular pathways through which ageing influences cancer biology, including telomere dysfunction, cellular senescence, DNA damage accumulation, and epigenetic alterations. These age-related changes create a permissive environment for oncogenesis while simultaneously affecting therapeutic efficacy and treatment tolerance. Key ageing-associated molecular signatures include p16^INK4a^ upregulation, shortened telomeres, increased DNA damage response activation, and altered chromatin structure. The accumulation of senescent cells with age contributes to chronic inflammation and tissue dysfunction that promotes tumour development. Additionally, age-related changes in drug metabolism, DNA repair capacity, and immune function significantly impact therapeutic outcomes. Recent advances in molecular ageing biomarkers, including transcriptomic ageing clocks and protein-based signatures, offer promising approaches for personalizing cancer treatment strategies. The integration of ageing biology into precision oncology frameworks presents opportunities for developing age-informed therapeutic protocols that optimize efficacy while minimizing toxicity. Emerging technologies, including artificial intelligence-driven molecular analysis and advanced imaging techniques, enable more precise characterization of ageing-cancer interactions at the cellular and tissue levels.

Conclusion

The molecular mechanisms underlying ageing-cancer relationships provide critical insights for advancing precision oncology approaches. Understanding these pathways enables the development of targeted interventions that account for age-related biological changes, ultimately improving therapeutic outcomes for older cancer patients. Future research must focus on translating molecular ageing discoveries into clinically actionable tools that enhance treatment personalization and optimize care delivery across the cancer continuum.

1 BACKGROUND

The convergence of global population ageing and cancer incidence presents new challenges for modern healthcare systems. Cancer predominantly affects older adults, with approximately 60% of new diagnoses occurring in patients over 65 years of age.1 This demographic reality reflects fundamental biological relationships between ageing processes and cancer development that operate at molecular, cellular, and tissue levels. Understanding these mechanistic connections has become essential for advancing precision oncology approaches that can effectively serve ageing populations.

The molecular hallmarks of ageing, including genomic instability, telomere attrition, epigenetic alterations, loss of proteostasis, deregulated nutrient sensing, mitochondrial dysfunction, cellular senescence, stem cell exhaustion, and altered intercellular communication, create conditions that promote cancer initiation and progression.1 These age-related changes fundamentally alter the cellular environment in ways that increase oncogenic risk while simultaneously affecting therapeutic response and treatment tolerance.2

Recent advances in molecular biology techniques, including single-cell sequencing, proteomics, and advanced imaging modalities, have enabled detailed characterization of ageing-cancer interactions at unprecedented resolution.3, 4 These technological capabilities offer new opportunities for translating molecular ageing research into clinically actionable insights that can inform precision oncology strategies.5, 6

The clinical significance of ageing-cancer molecular relationships extends beyond academic interest to practical implications for treatment selection, dosing strategies, and outcome prediction. Age-related changes in drug metabolism, DNA repair capacity, immune function, and tissue architecture significantly impact therapeutic efficacy and toxicity profiles.7, 8 Developing molecular frameworks that account for these ageing-related factors represents a critical need for optimizing cancer care in an ageing society.9

This review examines the current understanding of molecular mechanisms linking ageing to cancer development and therapeutic response, evaluates emerging biomarkers and technological approaches for characterizing these relationships, and discusses translational implications for advancing precision oncology in ageing populations. The synthesis of ageing biology and cancer research provides a foundation for developing more effective, personalized treatment approaches that account for the complex biological realities of cancer in older adults.

1.1 Molecular hallmarks of ageing in cancer development

1.1.1 Genomic instability and DNA damage accumulation

The accumulation of DNA damage represents a fundamental mechanism linking ageing to cancer development. Age-related decline in DNA repair capacity, including reduced efficiency of homologous recombination, non-homologous end joining, and base excision repair pathways, creates conditions that promote oncogenic mutations.10, 11 The progressive accumulation of DNA lesions with age establishes a mutational landscape that increases cancer risk while simultaneously affecting therapeutic response to DNA-damaging agents.

Genomic instability manifests through multiple pathways during ageing, including increased chromosomal aberrations, microsatellite instability, and loss of heterozygosity. These changes create the genomic foundation for cancer initiation while influencing therapeutic vulnerability to targeted agents.12 Understanding individual variation in DNA damage accumulation and repair capacity offers opportunities for personalizing treatment approaches based on molecular ageing status rather than chronological age alone.

Recent research has identified specific DNA damage signatures associated with ageing that can be quantified through advanced sequencing techniques.13 These molecular signatures provide insights into individual ageing trajectories and cancer risk profiles that extend beyond traditional demographic assessments.

1.1.2 Telomere dysfunction and chromosomal instability

Telomere dysfunction represents a critical mechanistic link between cellular ageing and cancer development that extends beyond simple telomere shortening. Recent work has illuminated the central role of replication stress and telomere fragility in this process, providing insights into how ageing-related telomere dysfunction promotes tumorigenesis while simultaneously affecting therapeutic response.14, 15

Progressive telomere attrition leads to chromosomal instability through multiple interconnected pathways. While critically short telomeres activate DNA damage checkpoints that can induce senescence or apoptosis as a tumour suppressor mechanism, cells that bypass these checkpoints may acquire additional mutations through chromosomal instability, promoting cancer progression.13, 14 However, the relationship between telomeres and cancer risk is more complex than previously understood, with both excessively short and unusually long telomeres contributing to cancer development under different circumstances.14

1.1.3 The burden of telomere fragility and replication stress

A paradigm shift in understanding telomere dysfunction has emerged from the recognition that structural abnormalities and replication stress can drive cellular dysfunction independent of telomere length. Fragile telomeres, characterized by abnormalities and increased susceptibility to breakage during replication, represent critical vulnerability points that accumulate with age due to intense replicative stress.14, 15 These fragile sites appear as gaps or constrictions in metaphase chromosomes and indicate regions where replication forks have stalled, often due to the formation of secondary DNA structures such as G-quadruplexes or DNA damage that hampers replication machinery progression.

Key factors contributing to telomere fragility include inadequate telomerase activity and dysfunction in shelterin complex components—proteins that protect telomeres and regulate their maintenance.14 The accumulation of fragile telomeres creates a cellular environment that promotes both degenerative ageing processes and oncogenic transformation. In ageing contexts, fragile telomeres contribute to cellular senescence and tissue dysfunction even without detectable telomere shortening. In cancer, these same fragile telomeres drive genomic instability through mechanisms such as chromosomal fusions and breakage-fusion-bridge cycles, creating the genetic diversity that allows tumour cells to evolve and adapt to therapeutic pressures.14

Molecular assessment of telomere dysfunction now encompasses not only telomere length measurement but also assessment of telomere structural integrity and replication stress markers. Emerging research suggests that telomere fragility biomarkers may provide a more precise prediction of therapeutic response than length measurements alone, particularly for DNA repair inhibitors and immunotherapy approaches.16 The development of clinically applicable techniques for assessing telomere dysfunction represents a critical translational research priority for advancing precision oncology in ageing populations.

1.1.4 Cellular senescence and inflammatory microenvironments

The accumulation of senescent cells during ageing creates chronic inflammatory conditions that fundamentally alter the tissue microenvironment and promote cancer development through complex, interconnected mechanisms. This process represents a critical nexus where ageing biology, telomere dysfunction, and inflammation converge to influence both cancer initiation and therapeutic response.15, 17, 18

Senescent cells secrete inflammatory cytokines, growth factors, and matrix-remodelling enzymes through the senescence-associated secretory phenotype (SASP), establishing tissue environments that support tumour initiation and progression.17, 19 The aged microenvironment, enriched with senescent cells and their secretory factors, has been shown to drive melanoma metastasis and therapy resistance through mechanisms involving sFRP2 signalling pathways.8 Importantly, recent evidence demonstrates that telomere dysfunction can induce cellular senescence without detectable shortening, suggesting that structural telomere abnormalities and replication stress play roles in ageing-cancer relationships independent of simple length reduction.14, 15

The transcriptional heterogeneity of senescent cells adds complexity to their role in cancer development, with different senescent cell populations exhibiting distinct SASP profiles that may either promote or inhibit tumorigenesis depending on cellular context and microenvironmental factors.17 This heterogeneity has important implications for the therapeutic targeting of senescent cells in cancer prevention and treatment.

Furthermore, the relationship between telomeres and inflammation is bidirectional and dynamic. Chronic inflammation accelerates telomere shortening through multiple mechanisms, including increased oxidative stress generation and direct inhibition of telomerase activity by pro-inflammatory cytokines such as IL-6 and TNF-α.15 Conversely, telomere dysfunction activates inflammatory pathways through DNA damage response signalling, creating feedback loops that perpetuate both cellular ageing and oncogenic conditions.

Telomerase itself emerges as a central player in modulating inflammatory responses beyond its canonical role in telomere maintenance. The enzyme's non-canonical functions include enhancing mitochondrial function, reducing oxidative stress, and directly regulating inflammatory gene expression through interactions with transcription factors such as NF-κB.15 These diverse functions position telomerase as both a biomarker of ageing-cancer relationships and a potential therapeutic target for modulating the ageing-inflammation-cancer axis.

Molecular markers of cellular senescence, including p16^INK4a^ expression, senescence-associated β-galactosidase activity, and DNA damage foci, provide measurable indicators of ageing-related tissue dysfunction that correlate with both chronic inflammatory status and cancer risk.1, 17, 15 The development of senolytic therapies that selectively eliminate senescent cells represents a promising therapeutic approach for simultaneously addressing ageing-related inflammation and cancer prevention.15, 20

1.1.5 Epigenetic alterations and gene expression changes

Age-related epigenetic changes occur through specific molecular mechanisms that directly influence cancer development. DNA methyltransferase activity patterns change with ageing, with DNMT1 showing decreased fidelity during replication while DNMT3A/3B exhibits altered target specificity, leading to progressive CpG island hypermethylation at tumour suppressor gene promoters including CDKN2A, MLH1, and BRCA1.21, 22 Simultaneously, histone modification patterns undergo systematic changes through altered histone-modifying enzyme expression, with increased histone deacetylase (HDAC) activity and decreased histone acetyltransferase (HAT) activity creating global chromatin condensation that affects tumour suppressor gene accessibility and DNA repair pathway activity.23, 24

The progressive accumulation of these epigenetic changes during ageing establishes distinct molecular signatures that can be quantified through advanced genomic techniques. Epigenetic ageing clocks, based on DNA methylation patterns, provide robust measures of biological ageing that correlate with cancer risk and therapeutic response.13, 16 These molecular ageing assessments offer more precise approaches for treatment personalization than chronological age alone.

Epigenetic modifications represent potentially reversible molecular changes that may be targeted through therapeutic interventions. The development of epigenetic therapies, including DNA methyltransferase inhibitors and histone deacetylase inhibitors, provides opportunities for modulating ageing-related cancer risk and enhancing therapeutic response.3, 20 Understanding individual epigenetic ageing profiles enables more precise application of these targeted interventions.

1.2 Age-related changes in therapeutic response

1.2.1 Pharmacokinetic and pharmacodynamic alterations

Ageing significantly affects drug metabolism, distribution, and elimination in ways that impact therapeutic efficacy and toxicity.25 Age-related changes in liver function, kidney clearance, body composition, and protein binding alter drug pharmacokinetics and require careful consideration in treatment planning. These physiological changes interact with molecular ageing processes to create complex patterns of therapeutic response that vary significantly among individuals.

Pharmacodynamic changes associated with ageing include altered cellular sensitivity to therapeutic agents, modified DNA repair capacity, and changed immune function. These molecular changes affect both therapeutic efficacy and toxicity profiles in ways that extend beyond simple pharmacokinetic adjustments. Understanding individual variation in pharmacodynamic ageing enables more precise dosing strategies and treatment selection.

Recent advances in pharmacogenomics and molecular ageing assessment provide opportunities for personalized therapeutic approaches based on individual ageing-related changes rather than population-based age adjustments.26 The integration of molecular ageing biomarkers with pharmacokinetic modelling represents a promising approach for optimizing treatment protocols in older cancer patients.

1.2.2 DNA repair capacity and treatment sensitivity

Age-related decline in DNA repair capacity significantly affects response to DNA-damaging therapeutic agents, including chemotherapy and radiation therapy. Reduced efficiency of DNA repair pathways can enhance therapeutic sensitivity in some contexts while promoting treatment resistance in others. Understanding individual DNA repair capacity provides valuable insights for optimizing treatment selection and combination strategies.

Molecular assessment of DNA repair pathway function, including homologous recombination deficiency and mismatch repair status, enables more precise prediction of therapeutic response. These biomarkers are particularly relevant for selecting patients who may benefit from DNA repair inhibitors, including PARP inhibitors and platinum-based chemotherapy. The development of functional assays for DNA repair capacity represents an important translational research priority.

The interaction between ageing-related DNA repair decline and therapeutic response varies across different cancer types and treatment modalities. Personalized approaches that account for individual DNA repair status offer opportunities for optimizing therapeutic efficacy while minimizing toxicity. Integration of molecular ageing assessments with treatment planning requires continued research and clinical validation.

1.2.3 Immune system ageing and immunotherapy response

Immunosenescence, the age-related decline in immune function, significantly affects the response to immunotherapy through mechanisms that are intimately connected to telomere biology and chronic inflammation.15, 27 The complex interplay between telomerase activity, inflammatory signalling, and immune function creates distinct challenges for cancer treatment in ageing populations that require careful consideration in precision oncology approaches.

Changes in T cell function, reduced antigen presentation capacity, and altered cytokine profiles characteristic of immunosenescence create immune environments that may be less responsive to checkpoint inhibitors and other immunotherapeutic agents.27 Chronic inflammation associated with ageing—termed “inflammaging”—contributes to immune dysfunction through persistent activation of inflammatory pathways that can exhaust immune cell populations and alter their functional capacity.15 The telomerase-inflammation axis plays a central role in these processes, as telomerase deficiency in immune cells contributes to premature senescence and inflammatory cytokine production.

Molecular characterization of immune ageing now incorporates assessment of telomere dynamics, inflammatory marker profiles, and immune cell composition to provide a more precise evaluation of immunotherapy potential. Emerging therapeutic approaches include strategies to rejuvenate immune function through modulation of the telomerase-inflammation axis, potentially enhancing immunotherapy response in older cancer patients while addressing underlying ageing-related immune dysfunction.15

1.2.4 Molecular biomarkers of ageing in cancer

Transcriptomic ageing signatures, based on age-related changes in gene expression patterns, provide insights into cellular ageing status and functional capacity.28 These molecular profiles can be assessed through standard tissue sampling techniques and offer practical approaches for clinical implementation. The development of simplified ageing signatures suitable for routine clinical use represents an important translational research goal.

Epigenetic ageing clocks, particularly those based on DNA methylation patterns, have demonstrated robust associations with cancer risk and therapeutic response.29, 30 These molecular ageing measures provide stable, quantifiable assessments that can be integrated into clinical decision-making processes. Continued research into epigenetic ageing mechanisms will enhance understanding of ageing-cancer relationships and improve clinical applications.

Protein-based biomarkers of ageing offer practical approaches for clinical assessment that can be implemented through standard laboratory techniques.31 Age-related changes in protein expression, modification, and function provide measurable indicators of cellular ageing status that correlate with cancer risk and therapeutic response. The development of protein ageing signatures suitable for routine clinical use represents an important research priority.

Inflammatory protein markers, including cytokines and acute phase reactants, reflect age-related increases in chronic inflammation that promote cancer development. These biomarkers can be easily measured through standard laboratory assays and provide valuable insights into individual ageing status. Integration of inflammatory ageing markers into clinical assessment protocols offers opportunities for enhanced treatment personalization.

Advanced proteomic techniques enable comprehensive assessment of age-related protein changes that extend beyond individual biomarkers to include complex protein interaction networks.32 These systems-level approaches provide deeper insights into ageing mechanisms and their relationships to cancer development and therapeutic response. Continued technological advancement will enhance the clinical applicability of proteomic ageing assessments.

Advanced imaging techniques provide non-invasive approaches for assessing ageing-related changes through multiple modalities.33, 34 Positron emission tomography and magnetic resonance imaging can assess age-related changes in tissue metabolism, blood flow, and cellular composition while emerging optical techniques and molecular contrast agents enable detailed characterization of ageing processes including senescent cell accumulation and inflammatory activity. When combined with radiomics analysis, these approaches identify ageing-associated tissue changes that correlate with treatment response and survival outcomes.

However, it is important to note that the traditional approach to cancer treatment based on chronological age fails to capture the profound heterogeneity in individual ageing trajectories that fundamentally impact therapeutic outcomes.35 Biological age—representing the actual physiological and molecular state of an individual—can vary dramatically from chronological age, with some 70-year-olds exhibiting the molecular signatures of 50-year-olds while others show accelerated ageing patterns more typical of 90-year-olds. This variability has critical implications for cancer treatment stratification, as patients with similar chronological ages may have vastly different treatment tolerances and therapeutic responses based on their underlying biological ageing status.

Recent studies demonstrate that biological age acceleration—the difference between biological and chronological age—predicts cancer treatment outcomes more accurately than chronological age alone.36, 37 Patients with accelerated biological ageing show increased chemotherapy toxicity, reduced immunotherapy response, and higher rates of treatment discontinuation, regardless of their chronological age. Conversely, individuals with decelerated biological ageing may tolerate aggressive treatments typically reserved for younger patients, suggesting opportunities for treatment intensification in biologically younger older adults.

Ageing heterogeneity manifests across multiple biological domains simultaneously, creating complex individual ageing profiles that resist simple categorization.35, 38 Cardiovascular ageing, immune system ageing, cognitive ageing, and cellular senescence can proceed at different rates within the same individual, resulting in mosaic ageing patterns that require multidimensional assessment approaches. For example, a patient may exhibit accelerated immune ageing that compromises immunotherapy response while maintaining robust cardiovascular function that supports aggressive chemotherapy regimens.

Epigenetic ageing clocks reveal substantial individual variation in ageing trajectories, with some individuals showing epigenetic age acceleration in specific tissue types while maintaining normal ageing patterns in others.39, 40 This tissue-specific ageing heterogeneity has important implications for cancer treatment, as therapeutic efficacy and toxicity may depend on the ageing status of specific organ systems targeted by treatment.

The recognition of ageing heterogeneity necessitates moving beyond chronological age-based treatment guidelines towards personalized approaches that account for individual biological ageing profiles.16, 41 Emerging precision oncology frameworks incorporate multiple ageing biomarkers to create comprehensive biological age assessments that guide treatment selection, dosing modifications, and supportive care interventions. For instance, patients with accelerated DNA methylation ageing but preserved functional status might benefit from intermediate-intensity treatment approaches that account for their mixed ageing profile.

Practical implementation of ageing heterogeneity assessment requires integrating molecular ageing biomarkers with a comprehensive geriatric assessment to capture both biological and functional ageing dimensions.42, 43 This multimodal approach enables the identification of patients whose biological ageing status suggests different treatment approaches than their chronological age would indicate, optimizing both therapeutic efficacy and patient safety.

The field is moving towards a dynamic ageing assessment that captures not only baseline biological age but also ageing trajectory and resilience to therapeutic stress.44, 45 Longitudinal monitoring of ageing biomarkers during treatment can identify patients experiencing accelerated ageing from therapy-related damage, enabling proactive interventions to maintain treatment tolerance and optimize outcomes. This approach represents a fundamental shift from static age-based treatment decisions towards dynamic, personalized ageing management throughout the cancer care continuum.

While these molecular biomarkers show promise for precision oncology applications, their clinical implementation faces significant challenges. The integration of these diverse ageing assessments into practical clinical workflows requires sophisticated technological approaches that can handle complex, multi-dimensional data and translate it into actionable clinical insights. This technological integration represents both the current bottleneck and future opportunity for ageing-informed precision oncology.

1.2.5 Technological advances in ageing-cancer research

Despite strong biological rationale for ageing-guided immunotherapy decisions—including associations between ageing, increased tumour mutational burden, and higher immune checkpoint gene expression—no clinical trials directly use molecular ageing clocks to guide checkpoint inhibitor therapy.46, 47 Instead, current practice relies on traditional geriatric screening tools. The ELDERS study across European centres employs G8 screening and comprehensive geriatric assessment rather than molecular ageing biomarkers to guide immunotherapy decisions in patients ≥70 years.47 Similarly, Spanish Lung Cancer Group studies use conventional geriatric assessments for pembrolizumab treatment in elderly patients with advanced NSCLC, achieving 61.7% overall survival at 1 year.48

The regulatory environment presents substantial barriers to ageing biomarker clinical adoption. Commercial platforms like TruDiagnostic's TruAge test ($399) and Zymo Research's myDNAge testing ($299) operate as laboratory-developed tests under CLIA oversight rather than FDA-approved diagnostics.49 These platforms lack clinical validation for cancer treatment decisions and have no established reimbursement pathways through Medicare or commercial insurance. Investigation of leading cancer centres reveals minimal integration of molecular ageing biomarkers into clinical workflows, with precision oncology platforms focusing on tumour genomics rather than ageing biology.50

Multiple completed randomized controlled trials validate alternative approaches to age-informed cancer care. The GERICO study (NCT02748811) showed 45% vs 28% treatment completion rates when comprehensive geriatric assessment guided colorectal cancer chemotherapy decisions.51 The Alliance A171601 study (NCT03633331) evaluated palbociclib in 93 elderly breast cancer patients using geriatric assessment for toxicity prediction, demonstrating feasible treatment delivery with appropriate dose modifications guided by functional rather than molecular ageing markers.52

1.2.6 Exemplar workflow: Predicting immunotherapy response in ageing tumour microenvironments

The convergence of artificial intelligence, single-cell technologies, and advanced imaging modalities is creating opportunities to understand and clinically apply ageing-cancer relationships through integrated analytical workflows.4, 53 Rather than isolated technological advances, the field is moving towards platforms that combine multiple data types to generate clinically actionable insights for precision oncology in ageing populations.

A paradigmatic example of integrated technology application involves predicting immunotherapy responsiveness in older cancer patients through multi-modal data integration. This workflow begins with single-cell RNA sequencing of tumour biopsies from elderly patients, capturing the cellular heterogeneity and ageing-associated changes in the tumour microenvironment.54, 55 Single-cell analysis reveals age-related alterations in T-cell exhaustion markers, macrophage polarization states, and fibroblast senescence signatures that correlate with immunotherapy resistance.

Machine learning algorithms then integrate these single-cell profiles with clinical ageing assessments, DNA methylation ageing clocks, and radiological ageing signatures from CT scans to create comprehensive ageing–immune interaction models.56, 57 Deep learning approaches, particularly graph neural networks, can capture complex cellular communication patterns within aged tumour microenvironments that traditional analyses miss. These models identify specific combinations of cellular ageing states, immune cell dysfunction, and tissue architecture changes that predict poor immunotherapy response in older adults.

The workflow culminates in clinical decision support tools that integrate real-time molecular ageing assessment with treatment recommendation algorithms. For example, patients showing high levels of senescent fibroblasts, exhausted T cells, and accelerated epigenetic ageing might be flagged for combination therapies that include senolytic agents alongside checkpoint inhibitors, or for alternative treatment strategies that account for their ageing-associated immune dysfunction.58

Molecular imaging technologies are also being integrated with ageing biomarker platforms to provide a non-invasive assessment of ageing-cancer interactions.33, 34 Positron emission tomography (PET) imaging using novel tracers can visualize senescent cell accumulation, inflammatory activity, and metabolic ageing signatures in cancer patients. When combined with radiomics analysis—extraction of quantitative features from medical images using machine learning—these approaches can identify ageing-associated tissue changes that correlate with treatment response and survival outcomes.

Artificial intelligence-driven analysis of routine imaging studies (CT, MRI) can extract ageing signatures from tissue texture, vascular patterns, and organ morphology that complement molecular ageing assessments.57 For instance, machine learning models trained on imaging data from thousands of patients can identify radiological ageing patterns that predict chemotherapy tolerance independently of chronological age, enabling more precise treatment personalization.

The integration of genomic, transcriptomic, proteomic, and metabolomic ageing signatures through artificial intelligence creates molecular ageing profiles that exceed the predictive power of individual biomarker classes.31, 32 Machine learning approaches can identify complex molecular ageing patterns that span multiple biological systems and predict clinical outcomes with greater accuracy than single-platform approaches.

These integrated platforms enable real-time updating of ageing assessments as new molecular data becomes available during treatment, allowing for dynamic treatment optimization based on evolving ageing-cancer interactions. For example, monitoring changes in circulating ageing biomarkers during therapy can trigger treatment modifications before clinical deterioration becomes apparent.30

The translation of these integrated technological approaches into clinical practice requires systematic validation and implementation frameworks. Successful clinical integration involves developing standardized data collection protocols, creating interoperable analytical platforms, and establishing clinical decision support systems that can operate within existing healthcare workflows.42, 43 Early examples include institutions implementing combined molecular ageing assessment with traditional geriatric evaluation to guide treatment decisions, though these remain largely investigational.

1.3 Future directions and clinical implementation

1.3.1 Immediate research priorities (2–5 years)

Validation of ageing biomarkers in prospective clinical trials represents the most urgent research priority. Specifically, multi-centre studies integrating epigenetic ageing clocks with comprehensive geriatric assessment in cancer patients receiving immunotherapy are needed within the next 24 months to establish clinical utility. The development of point-of-care ageing assessment tools that can provide results within clinical decision-making timeframes (≤48 h) requires immediate technological development and regulatory pathway establishment.

1.3.2 Medium-term integration goals (5–10 years)

Healthcare system adaptation must focus on creating standardized ageing biomarker testing infrastructure and training programs for oncology providers. Economic models demonstrating the cost-effectiveness of ageing-informed treatment approaches are essential for insurance coverage and widespread adoption. Digital health platform integration should enable real-time ageing assessment updates during treatment, with quality improvement initiatives providing systematic evidence for clinical benefits.

1.3.3 Long-term vision (10+ years)

The ultimate goal involves the seamless integration of dynamic ageing assessment into all cancer care decisions, moving beyond chronological age to biological age-informed treatment selection, dosing, and monitoring. This requires coordinated efforts across research, clinical, regulatory, and healthcare system domains to create a new standard of care that optimizes outcomes for the growing population of older cancer patients.

2 CONCLUSION

The molecular mechanisms underlying ageing-cancer relationships provide fundamental insights for advancing precision oncology approaches in an ageing society. Recent technological advances in genomics, proteomics, and computational biology have created unprecedented opportunities for characterizing these relationships and translating insights into clinical applications through molecular ageing biomarkers, advanced imaging techniques, and integrated analytical approaches that account for individual ageing biology rather than chronological age alone.

The translational implications extend across multiple domains of clinical practice, including treatment selection, dosing optimization, and novel therapeutic target identification. However, successful clinical translation requires coordinated efforts to validate molecular ageing biomarkers, develop practical assessment tools suitable for routine use, and establish the healthcare system infrastructure necessary for implementation.

The ultimate goal extends beyond academic advancement to encompass meaningful improvements in cancer care outcomes for older adults. Understanding and addressing the molecular mechanisms that link ageing to cancer development and therapeutic response provides pathways for developing more effective, personalized treatment approaches that enhance both survival and quality of life for ageing cancer patients—essential knowledge for addressing one of the most significant healthcare challenges of the 21st century.

AUTHOR CONTRIBUTIONS

LH conceived and designed the review, conducted the literature search, analyzed and synthesized the reviewed studies, wrote the original manuscript draft, and completed all revisions including approval of the final manuscript.

ETHICS STATEMENT

This review article is based on analysis of previously published literature and does not involve primary data collection, human subjects, animal studies, or clinical trials. As such, no ethics approval was required for this work.

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