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PubMed2026

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

INTRODUCTION: Cancer and ageing have a bidirectional relationship: age is the strongest risk factor for cancer, and cancer and treatments can accelerate ageing. Therefore, biological age can differ from chronological age; biomarkers are needed to stratify interventions to minimise accelerated ageing. METHODS: PhenoAge was calculated from routine blood test results of patients attending a Geriatric Oncology clinic. PhenoAgeAccel was the residual from a regression of PhenoAge against age. RESULTS: Data were available for 173 patients (62% male). Mean PhenoAge was higher than age (84.3 (12.6) vs 76.2 (7.24), p&#x202f;<&#x202f;0.001), though the two were correlated (r&#x202f;=&#x202f;0.579, p&#x202f;<&#x202f;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). PhenoAge correlated with Clinical Frailty Score and Timed Up and Go (CFS: Rs=0.31, p&#x202f;<&#x202f;0.001; TUG: Rs=0.25, p&#x202f;<&#x202f;0.005); there were no correlations with age. PhenoAgeAccel correlated with the number of CGA interventions made (Rs=0.17, p&#x202f;<&#x202f;0.05), unlike age and PhenoAge. Patients with diabetes mellitus had a higher PhenoAgeAccel compared to those without (3.40 vs -1.71, p&#x202f;=&#x202f;0.002). In patients receiving systemic anti-cancer treatment, patients with PhenoAgeAccel calculated pre-treatment had less age acceleration than those with PhenoAgeAccel calculated post-treatment, both overall (2.18 vs -2.87; p&#x202f;=&#x202f;0.048) and in matched samples (n&#x202f;=&#x202f;21, 7.76 vs -2.87, p&#x202f;<&#x202f;0.001). CONCLUSIONS: PhenoAgeAccel is a greater predictor of risk than chronological age in older people with cancer. This makes it a promising biomarker to stratify patients for holistic geriatric assessment, dose reductions, or future geroprotective measures which could be integrated within electronic healthcare record systems.

Humans↗
PubMed2026

Older adults with resectable gastric cancer undergoing perioperative chemotherapy or preoperative chemoradiotherapy plus perioperative chemotherapy: A secondary analysis of the AGITG TOPGEAR phase III trial.

PURPOSE: To evaluate treatment adherence, adverse events, and survival in older (&#x2265;70 years) adults undergoing perioperative treatment for gastric cancer. METHODS: Patients with resectable gastric/gastro-esophageal junction adenocarcinoma (ECOG 0-1) enrolled in the phase III TOPGEAR trial were randomized to perioperative chemotherapy (ECF/ECX or FLOT) alone or perioperative chemotherapy plus preoperative chemoradiotherapy (45&#x202f;Gy in 25 fractions with concurrent fluoropyrimidine). In this exploratory analysis, treatment completion, grade &#x2265;&#x202f;3 adverse events (CTCAE v3.0), surgical outcomes, overall survival (OS) and progression-free survival (PFS) were compared between older and younger adults. RESULTS: Of the 574 patients enrolled, 135 (24%) were &#x2265;&#x202f;70 years. Older adults more frequently required preoperative chemotherapy dose reductions, omissions, or delays (chemoradiotherapy: 55% vs 35%, p&#x202f;=&#x202f;0.004; chemotherapy: 60% vs 48%, p&#x202f;=&#x202f;0.087). Rates of grade &#x2265;&#x202f;3 adverse events were comparable between older and younger patients (chemoradiotherapy: 66% vs 67%, p&#x202f;=&#x202f;0.874; chemotherapy: 68% vs 59%, p&#x202f;=&#x202f;0.220), but older adults more often had hematologic toxicity and grade &#x2265;&#x202f;3 diarrhea in the chemotherapy group (56% vs 37%, p&#x202f;=&#x202f;0.006; 21% vs 6%, p&#x202f;<&#x202f;0.001). Resection rates, grade 3/4 surgical complications, number of removed lymph nodes, and 30-/90-day mortality were similar by age. OS and PFS were comparable across age groups, with numerically favorable outcomes for older adults (OS: HR 0.86, 95% CI 0.58-1.26 [chemoradiotherapy]; HR 0.75, 95% CI 0.51-1.11 [chemotherapy]; PFS: HR 0.78, 95% CI 0.53-1.15 [chemoradiotherapy]; HR 0.70, 95% CI 0.47-1.03 [chemotherapy]). CONCLUSIONS: Older adults with gastric cancer achieved comparable oncologic outcomes to younger patients, despite more frequent treatment modifications and higher hematologic toxicity.

Humans↗
PubMed2026

Tissue-Level Transcriptomic Entropy Reveals Organ-Specific Aging Patterns and Predicts Cancer Progression.

Although aging and cancer share complex molecular mechanisms, distinguishing causative factors from byproducts remains challenging. Here, we investigated the role of tissue transcriptomic entropy-a measure of transcriptional disorder-in aging and cancer processes by analyzing RNA-sequencing data from over 25,000 samples from human and mouse tissues. We found that entropy changes during aging are highly tissue-specific, with some tissues showing increased entropy while others exhibit decreased or stable entropy levels. Moreover, transcriptomic entropy strongly correlates with age-related processes, showing positive associations with proliferation, cellular senescence, somatic mutation burden, and cellular reprogramming, whereas it negatively correlates with stemness. In cancer, we observed that primary tumors generally display higher entropy than normal tissue, with its levels further increasing in metastatic stages. Cancer treatment modulated entropy patterns in multiple contexts, with changes suggesting a role for transcriptional complexity in tumor plasticity and therapy resistance. Elevated entropy levels predicted poor survival outcomes in multiple cancer types, suggesting its potential as a prognostic marker. Furthermore, differential expression analysis revealed that entropy-associated genes are enriched in developmental processes and depleted in metabolic pathways, indicating a possible link to cellular dedifferentiation. Finally, we found increased entropy in various age-related disorders beyond cancer, suggesting that transcriptomic entropy may be a common feature in age-related diseases. Our findings establish transcriptomic entropy as a fundamental parameter in aging and cancer progression, offering new insights into disease mechanisms.

Humans↗