The aim of this thesis is generate prototype-tests suitable for randomized prospective validation of auto-antibody based diagnostic testing using serum samples. Tumours can stimulate the production of auto-antibodies against autologous cellular proteins known as TAAs (tumour associated antigens). This discovery has lead to a possibility of using the auto-antibodies as serological tools for the early diagnosis and management of breast cancer.
The recombinant proteins expressed by the SEREX clones, identified from screenings of brain and lung tumour, were used for the production of the protein microarrays and macroarrays. The protein microarrays showed better correlation between the replicates of the serum samples used. The optimized protocols were used for the subsequent experiments. A sizable panel of 642 clone-proteins was selected by marker-screening on protein macroarrays with 38000 clones. These 642 clone-proteins were used to generate protein microarrays that differentiated serum samples from breast cancer patients and controls. Antigenic peptide motifs were identified by in-silico analysis of 642 clone-proteins and peptide arrays were generated using synthetically generated peptides.
Comparative studies between protein microarrays and peptide microarrays were done using breast cancer and healthy control samples.
Simultaneously, SEREX strategy was used for the identification of the immunogenic TAAs. I identified 192 cDNA expression clones derived from breast cancer tissue samples and the selection was done using breast cancer sera. The genes corresponding to these clones were found over-represented for the pathways that are known to be associated with cancers. These genes showed typical features of TAAs, like over-expression, mutations and fusion genes.