A study on classifying tumor neoantigens to enhance the accuracy of liquid biopsy in CRC cancer.

person Fenghua Guo HaploX Biotechnology, Shenzhen, China info_outline Fenghua Guo, Wenting Liao, Jun Li, Yaru Chen

Authors person Fenghua Guo HaploX Biotechnology, Shenzhen, China info_outline Fenghua Guo, Wenting Liao, Jun Li, Yaru Chen Organizations HaploX Biotechnology, Shenzhen, China Abstract Disclosures Research Funding No funding sources reported Background: Personalized neoantigen vaccines are a promising therapeutic approach in colorectal cancer (CRC). These vaccines are designed based on the identification of specific gene mutations, aiming to evoke an immune response. However, a major challenge arises from the need to distinguish true mutated sites from numerous false positives, particularly in samples of liquid biopsy, where detection rates may be relatively low. To address this issue, we have developed a robust pipeline to enhance the precision and efficiency of detecting target gene mutations, which is crucial during the neoantigen design process. Methods: In this study, an extensive analysis was conducted using tissue and blood samples from a cohort of 859 CRC patients. We identified mutations in the top third most frequently mutated genes (APC, TP53, and KRAS). To design antigenic sequences, the mutations at these gene sites were concatenated with 14 amino acids from both up and down flanking regions. Subsequently, we utilized a similarity scoring algorithm (pairwise2.align from Biopython) to assess the mutation correlation between oncogenes (APC and KRAS) and the suppressor gene TP53. Results: This study observed that mutations within a specific gene tend to generate distinct patterns of new antigens. The majority of APC mutations (90.04%) in the vicinity of the mutation sites led to premature stop codons. Regarding KRAS, the mutation sites with the highest frequency were in the vicinity of the c.35 and c.182 positions, sharing identical neoantigens with NRAS. In contrast, TP53 mutations appeared to be more influenced by other mutations. Neoantigens derived from TP53 were identified, and it was observed that 82.27% of the sequences exhibited more than 40% similarity with other mutations in the same sample.This may be indicative of a co-occurrence mechanism. Conclusions: The classification of neoantigens appears to be similar to the classification of oncogenes and tumor suppressor genes, which may contribute to adjust the minimum detection threshold of liquid biopsy from the perspective of neoantigens. Gene Mutation Number Classification Mutation Neoantigen Mutation Number within Gene Percentage APC 954 premature stop codon c.4348C > T c.4666dup c.646C > T c.2626C > T c.637C > T c.694C > T ... SKTPPPPPQTAQTK* PKESNENQEKEAEKNY* EQLGTCQDMEKRAQ* NYHPATENPGTSSK* AMEEQLGTCQDMEK* IARIQQIEKDILRI* ... 859 90.04% other 95 9.96% KRAS 484 cluster and shared with NRAS c.35G > A c.35G > T c.38G > A c.34G > T c.34G > A c.183A > C c.182A > G c.182A > T ... MTEYKLVVVGADGVGKSALTIQLIQN MTEYKLVVVGAVGVGKSALTIQLIQN MTEYKLVVVGAGDVGKSALTIQLIQNH DGETCLLDILDTAGHEEYSAMRDQYMRTG DGETCLLDILDTAGREEYSAMRDQYMRTG ... 419 86.57% other 65 13.43% Gene Total sample (tissue and blood) Sample with TP53 mutation Similarity scores above 0.4 Percentage TP53 90 79 65 82.27%