Comprehensive Detection of Single Amino Acid Variants and Evaluation of Their Deleterious Potential in a PANC‑1 Cell Line

Identifying single amino acid variants
(SAAVs) in cancer is critical
for precision oncology. Several advanced algorithms are now available
to identify SAAVs, but attempts to combine different algorithms and
optimize them on large data sets to achieve a more comprehensive coverage
of SAAVs have not been implemented. Herein, we report an expanded
detection of SAAVs in the PANC-1 cell line using three different strategies,
which results in the identification of 540 SAAVs in the mass spectrometry
data. Among the set of 540 SAAVs, 79 are evaluated as deleterious
SAAVs based on analysis using the novel AssVar software in which one
of the driver mutations found in each protein of KRAS, TP53, and SLC37A4
is further validated using independent selected reaction monitoring
(SRM) analysis. Our study represents the most comprehensive discovery
of SAAVs to date and the first large-scale detection of deleterious
SAAVs in the PANC-1 cell line. This work may serve as the basis for
future research in pancreatic cancer and personal immunotherapy and
treatment.