Discovering a biomarker in CA19-9 negative Pancreatic Cancer

Background: Pancreatic cancer (PC) is one of the leading causes of death by cancer, globally as it’s impossible to diagnose the disorder in an early stage. Cancer incidences have been increasing in India due to lifestyle changes and are expected to grow in time. While PC is not one of the most common cancers found in the Indian population, its incidence is anticipated to increase with time. Howsoever small maybe its cases, the lack of proper diagnosis prevents successful treatment of patients thereby causing lethality. Inspite of surgical resection of tumor, the 5-year survival rate stands below 7% in the USA whereas the same data is not available for Indian population. Thus, there is a need to perform survival analysis in Indian population. Moreover, discovering a biomarker that can be used with precise specificity and sensitivity will enable early diagnosis thereby circumventing lethality. Towards this end, currently, a glycosylation marker sialyl lewis a, also commonly known as CA19-9, is being used to diagnose PC. While there are several caveats to using CA19-9 as the PC biomarker, one of them being that not all PC patients express clinically detectable levels of CA19-9. Thus, there is a need to identify a novel biomarker to be used together with CA19-9 thereby increasing its specificity and sensitivity. To complete this, the following aims shall be completed.

Aim 1: Generation of CA19-9 negative PC cell lines

Delete fucosyltransferase 3 from aggressive PC cell lines and determine the levels of CA19-9 in both the control and KD/KO cells, both from the cell lysate and media supplement. On successfully reducing CA19-9 levels, use normal pancreatic and pancreatic cancer cell lines, control and fucosyltransferase 3 KD/KO, to perform RNAseq, proteomics, and metabolomics analysis. This will help identify differentially expressed genes in CA19-9 high vs low PC.

Aim 2: Clinical validation of biomarkers identified in CA19-9 low PC cell lines

Collect PC tissues from Caucasian population to identify CA19-9 high vs low expressing samples. On segregating these samples, first perform proteomics on CA19-9 high vs low tissues (FFPE preserved). Evaluate the biomarkers differentially expressed in proteomics, using immunohistochemistry in CA19-9 high vs low PC tissues derived from Indian population. Serum from CA19-9 high vs low patients shall further be used to determine the levels of these biomarkers. On successfully identifying novel biomarkers, calculate sensitivity, specificity and build ROC curves.