BIOTA Philippines Conference System, 52nd BIOTA Annual National Convention and Scientific Sessions

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Mapple April Anne Cayabyab, Noreen De Guzman, Mia Kelly Manaloto, Evelyn Labastilla, Chester Deocaris

Last modified: 2017-03-11


Cancer, being considered as one of the major health problems, has long been known to be the result of genetic abnormalities. The presence of immunosurveillance that inhibits cancer development and progression has generated substantial interest in the cancer neoepitope landscape. Identification of mutation-derived tumor epitopes with superior properties as immunological targets for cancer immunotherapy is still a priority. In-silico neoepitope prediction was conducted to identify immunogenic peptides for the three most common cancer types; lung, liver, and prostate cancer. Mutations were derived from the top 50 genes for every individual tumor represented in the COSMIC database ( In this study, cancer-associated peptides from lung (5,343), liver (2,620), and prostate (1,442) with annotated missense mutations were retrieved. Sequences of the mutated peptides were submitted to IEDB analysis resource ( to predict their binding affinity to HLA-A*0201 and HLA-A*1101 molecules. Candidate neoepitopes were selected based on their IC50 values lower than 50nM and were considered to be strong binders to HLA molecules. Analysis of the total mutant peptides generated 435 neoepitopes in lung, 148 in liver, and 119 in prostate cancer for HLA-A*0201 and 348, 194, 91, for HLA-A*1101 in lung, liver, and prostate cancer respectively. Bound conformations and binding energy of the selected neoepitopes against the HLA molecules were verified through Autodock Vina ( by conducting computational docking simulation. Neoepitopes derived from the study can be further investigated for their immunological relevance and be exploited in vaccine development against the said cancers.

Key words: neoepitopes, HLA-A, binding affinity, in-silico, docking

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