[Clinical use and evolution of circulating biomarkers in the era of personalized oncology: From protein markers to bioclinical scores]

Stability of ten serum tumor markers after one year of storage at -18°C

OBJECTIVES

The storage of serum tumor markers (STM) at -18 °C for one year has been a legal requirement in France since 1999, but has been abolished in 2022. This raises the question of the relevance of maintaining these biobanks in terms of conditions of storage. These should only be implemented after validation; in order to maintain the integrity of the biological sample and must be controlled over time according to the laboratory's procedures. The aim of the study was to assess the suitability of storing 10 STMs by evaluating their stability after one year of storage at -18 °C.

METHODS

A new immuno-enzymatic assay (A+1) was conducted on samples that had been stored at -18 °C for one year after an initial assay (A) of one of the following STMs: carcino-embryonic antigen (CEA), alpha-fetoprotein (AFP), carbohydrate antigen 125 (CA125), carbohydrate antigen 15-3 (CA15-3), carbohydrate antigen 19-9 (CA19-9), total (TPSA), and free (FPSA) prostate-specific antigen, calcitonin (CT), thyroglobulin (TG), and neuro-specific enolase (NSE). The results were confronted to four different permissible error sources.

RESULTS

In total, 1148 A+1 assays were performed. A strong correlation between A+1 and A values was found for all analytes, but with a statistically significant reduction in the mean A+1 concentration compared to the mean A concentration in 7/10 STMs. The bias induced by conservation seems to be technically unsustainable if we rely on the repositories closest to the current analytical performances.

CONCLUSIONS

These results support the discontinuation of mandatory STM biobank storage at -18 °C, which requires considerable technical time and organizational effort.

Treatment of evolving cancers will require dynamic decision support

Cancer research has traditionally focused on developing new agents, but an underexplored question is that of the dose and frequency of existing drugs. Based on the modus operandi established in the early days of chemotherapies, most drugs are administered according to predetermined schedules that seek to deliver the maximum tolerated dose and are only adjusted for toxicity. However, we believe that the complex, evolving nature of cancer requires a more dynamic and personalized approach. Chronicling the milestones of the field, we show that the impact of schedule choice crucially depends on processes driving treatment response and failure. As such, cancer heterogeneity and evolution dictate that a one-size-fits-all solution is unlikely-instead, each patient should be mapped to the strategy that best matches their current disease characteristics and treatment objectives (i.e. their 'tumorscape'). To achieve this level of personalization, we need mathematical modeling. In this perspective, we propose a five-step 'Adaptive Dosing Adjusted for Personalized Tumorscapes (ADAPT)' paradigm to integrate data and understanding across scales and derive dynamic and personalized schedules. We conclude with promising examples of model-guided schedule personalization and a call to action to address key outstanding challenges surrounding data collection, model development, and integration.