Identifying biomarkers of accelerated ageing in cancer patients from routine clinical data

3884
Clodagh Bottomley1 2, Evelyne Liuu2,3,4, Danielle Harari2,3, Tania Kalsi2,3 and Carly Welch2 3
1GKT School of Medical Education, King's College London 2 Department of Twin Research & Genetic Epidemiology, King’s College London 3Department of Ageing and Health, GSTT, 4Department of Geriatrics, University Hospital of Poitiers, France
Scientific Research
SP - Other medical conditions
Cancer

Abstract

Introduction

Cancer and ageing have a bidirectional relationship: age is the strongest risk factor for cancer, and cancer and treatments can accelerate ageing. Consequently, biological age of patients with cancer is likely to deviate from chronological age. Validated biomarkers of biological age are needed to quantify this and stratify interventions to minimise accelerated ageing.

Methods

Using the BioAge R Package, PhenoAge was calculated from eight blood test results of patients attending the Geriatric Oncology Liaison Development (GOLD) clinic at Guy’s Hospital between 2022 and 2025. PhenoAgeAccel, a biomarker of accelerated ageing, was the residual from a linear regression of PhenoAge by age.

Results

Data were available for 173 patients (62% male). Mean PhenoAge was higher than mean age (84.3 (12.6) vs 76.2 (7.24), p<0.001), though the two were correlated (r=0.579, p<0.001). Unlike age, PhenoAge and PhenoAgeAccel were associated with one-year mortality (PhenoAge OR = 1.083, 95% CI: 1.038-1.136; PhenoAgeAccel OR = 1.096, 95% CI: 1.047-1.155, p<0.001).

In all patients, PhenoAge correlated with Clinical Frailty Scale and Timed Up and Go (CFS: Rs=0.31, p<0.001; TUG: Rs=0.25, p<0.005), whereas there were no correlations with age (CFS: Rs=0.1, p=0.21; TUG: Rs=0.16, p=0.07). PhenoAgeAccel correlated with the number of CGA interventions made per patient (Rs=0.17, p<0.05), but age and PhenoAge did not.

Patients with diabetes had a higher PhenoAgeAccel (3.40 (9.78) vs -1.71 (10.53), p=0.002). In patients receiving systemic anti-cancer treatment (SACT), PhenoAgeAccel pre-SACT was lower than when measured post-SACT (2.18 (10.64) vs. -2.87 (7.98); p=0.048) overall and in matched samples (n = 21, 7.76 ± 11.98 vs -2.87 ± 7.98, p<0.001).

Conclusions

PhenoAgeAccel is a promising biomarker to identify older people with cancer who may benefit from holistic geriatric assessment, dose reductions, or future geroprotective measures. This process could be automated through integration of PhenoAge within electronic healthcare record systems and clinician alerts. 

Comments

Always good to routine hospital data being utilised in scores like this - interesting stuff! How long after chemo were the tests done? Was this repeated at another time point later on in their recovery? I imagine some of the ageing effects of chemo might relate to chemo induced cellular senescence which in theory has a degree of reversibility depending on how well the immune system recovers.

Submitted by lucy.g.rimmer_29554 on

Permalink

Thanks for your comment! Unfortunately in this analysis we included results obtained at any time point after starting chemo  (including from the first few days following treatment up to patients who had already completed treatment). That's a really interesting point in terms of reversibility of these changes and is definitely something we would like to explore in a future study with more detailed analysis by both time following treatment and specific treatment type.