Baseline and Kinetic Circulating Tumor Cell Counts Are Prognostic Factors in a Prospective Study of Metastatic Colorectal Cancer.
Virgílio Souza E SilvaEmne Ali AbdallahAngelo Borsarelli Carvalho de BritoAlexcia Camila BraunMilena Shizue TarikiCelso Abdon Lopes de MelloVinicius Fernando CalsavaraRachel RiechelmannLudmilla Thomé Domingos ChinenPublished in: Diagnostics (Basel, Switzerland) (2021)
The discovery of predictive biomarkers in metastatic colorectal cancer (mCRC) is essential to improve clinical outcomes. Recent data suggest a potential role of circulating tumor cells (CTCs) as prognostic indicators. We conducted a follow-on analysis from a prospective study of consecutive patients with mCRC. CTC analysis was conducted at two timepoints: baseline (CTC1; before starting chemotherapy), and two months after starting treatment (CTC2). CTC isolation/quantification were completed by ISET® (Rarecells, France). CTC expressions of drug resistance-associated proteins were evaluated. Progression-free survival (PFS) and overall survival (OS) were estimated by the Kaplan-Meier method. Seventy-five patients were enrolled from May 2012 to May 2014. A CTC1 cut-off of >1.5 CTCs/mL was associated with an inferior median OS compared to lower values. A difference of CTC2-CTC1 > 5.5 CTCs/mL was associated with a reduced median PFS. By multivariate analysis, CTC1 > 1.5 CTCs/mL was an independent prognostic factor for worse OS. Multi-drug resistance protein-1 (MRP-1) expression was associated with poor median OS. CTC baseline counts, kinetics, and MRP-1 expression were predictive of clinical outcomes. Larger studies are warranted to explore the potential clinical benefit of treating mCRC patients with targeted therapeutic regimens guided by CTC findings.
Keyphrases
- circulating tumor cells
- prognostic factors
- circulating tumor
- metastatic colorectal cancer
- free survival
- end stage renal disease
- squamous cell carcinoma
- ejection fraction
- chronic kidney disease
- small molecule
- cancer therapy
- stem cells
- peritoneal dialysis
- bone marrow
- mesenchymal stem cells
- deep learning
- artificial intelligence
- drug delivery
- locally advanced
- protein protein