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Circulating Tumour DNA (ctDNA) as a Prognostic and Predictive Marker in Colorectal Cancer - a Pilot Study

ABSTRACT: In clinical practice, there are currently no biomarkers that can guide colorectal cancer treatment in the primary and curative setting. Improved biomarker-based adjuvant treatments would be of greatest value in order to reduce the risk of relapse. There are reasons to believe that measurements of circulating tumor DNA (ctDNA) in plasma could be used to monitor minimal residual disease after surgery. To address this question, a pilot study was conducted with the purpose to demonstrate the feasibility to perform prospective profiling of ctDNA in a cohort of patients with colorectal cancer stage I-III using the already created Nordic infrastructure for clinical research built up for the ALASCCA trial. If the pilot study proves successful, a large randomised controlled Nordic multicenter study is planned where patients with positive ctDNA 4-6 weeks after radical surgery will be randomised to chemotherapy and/or a biologic agent.

DISEASE(S): Colon Cancer,Colorectal Cancer,Colorectal Neoplasms

PROVIDER: 2365236 | ecrin-mdr-crc |

REPOSITORIES: ECRIN MDR

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Project description:The glycosylation of antibody-based proteins is vital in conferring the right therapeutic outcomes of the patient. Despite this, significant infrastructure is required to analyse biologic glycosylation in various unit operations from biologic development, process development to QA/QC in bio-manufacturing. The simplified mass spectrometers offer ease of operation as well as the portability of method development across various operations. Furthermore, data analysis would need to have a degree of automation to relay information back to the manufacturing line. We set out to investigate the applicability of using a semiautomated data analysis workflow to investigate glycosylation in different biologic development test cases. The workflow involves data acquisition using a BioAccord LC-MS system with a data-analytical tool called GlycopeptideGraphMS along with Progenesis QI to semi-automate glycoproteomic characterisation and quantitation in complex LC-MS1 data of a glycoproteomic analysis. Data analysis which involved identifying glycopeptides and their quantitative glycosylation was performed in 30 minutes with minimal user intervention. To demonstrate the effectiveness of the antibody and biologic glycopeptide assignment in various scenarios akin to biologic development activities, we demonstrate the effectiveness in the filtering of IgG1 and IgG2 subclasses from human serum IgG as well as innovator drugs trastuzumab and adalimumab and glycoforms by virtue of their glycosylation pattern. We demonstrate a high correlation between conventional released glycan analysis with fluorescent tagging and glycopeptide assignment derived from GraphMS. GraphMS workflow was then used to monitor the glycoform of our in-house trastuzumab biosimilar produced in fed-batch cultures, and it offers valuable insights into the effect of culture media changes on bioprocess and biologic characterisation. The demonstrated utility of GraphMS to semi-automate quantitation and qualitative identification of glycopeptides proves to be an easy and scalable data analysis method that can complement emerging multi-attribute monitoring (MAM) analytical toolsets in bioprocess environments.

Dataset Information

Circulating Tumour DNA (ctDNA) as a Prognostic and Predictive Marker in Colorectal Cancer - a Pilot Study

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