Aim: There is increasing evidence that the aberrant expression of cancer-testis (CT) antigens - a family that are both auto-immunogenic and mainly restricted to tumours in various types of human cancers - makes them attractive immunotherapy targets, as well as possible cancer diagnostic markers1, 2. Therefore, we aimed to measure differences in CT antigen-specific antibody repertoires between melanoma patient samples, and assess whether these could identify novel diagnostic or prognostic biomarkers, which could aid in the detection and management of cancer.
Methods: We carried out a retrospective serological study of antibody titres across a large cohort of eighty-eight malignant melanoma patients undergoing a variety of distinct cancer treatments (surgery, chemotherapy, radiotherapy, immunotherapy or none), using our recently developed and validated novel CT antigen microarray platform3, 4.
Results: We successfully identified abundant antibody titres towards two antigens, NY-ESO-1 and CTAG2 - a highly homologous pair - expressed across 48% (n = 42/88) and 45% (n = 40/88) of all patients, respectively, with reported diagnostic and clinical efficacy predictive biomarker potential. Additionally, when considering treatment specific antibody patterns, the highest antibody levels were observed for treatment naïve patients, which may be due to more responsive immune systems. Furthermore, the overlap in antibody titres of this pair validated our array platform, showing consistency amongst our obtained results across patients. Although this cohort was quite diverse regarding demographics (age and gender) and treatment undergone, the achieved statistical power was above recommended (power > 0.8), thus supporting these findings.
Conclusion: In conclusion, we showed that our novel protein microarray platform represents a sensitive, high-throughput and readily customizable means to detect and quantify the presence of large panels of cancer-specific human antibodies in serum, obtaining consistently robust, high quality and reproducible data, and demonstrating its potential feasibility and inferred biological significance.