Biology subjects

Paik, S.

Publications and source records attributed to Paik, S..

4 recordsLinked to original sources

bioRxiv2026

Accurate somatic variant detection from formalin fixed, paraffin embedded tissue (FFPE) derived WES and WGS by DeepOmicsFFPE-PLUS, a sequence context-based transformer

Formalin-fixed paraffin-embedded (FFPE) tissues represent a vast archival resource for genomic studies, yet their utility remains constrained by fixation-induced DNA damage and subsequent sequencing artifacts. To comprehensively characterize and address this challenge, we analyzed matched FFPE and fresh-frozen tumor samples from two institutions, spanning different storage durations, DNA qualities, sequencing platforms (WES and WGS), exome capture kits, and somatic variant callers. We found that FFPE-induced artifacts exhibit strong batch- and age-specific patterns, with a predominance of C:G>T:A substitutions, which particularly complicate the accurate identification of low allele frequency true variants. Enzymatic repair methods partially alleviated these artifacts but remained insufficient. To overcome these limitations, we developed DeepOmicsFFPE-PLUS(https://github.com/Theragen-Bio/DeepOmicsFFPE-PLUS), an advanced AI-based tool to accurately distinguish true somatic variants from FFPE-specific artifacts. DeepOmicsFFPE-PLUS demonstrated consistently superior performance across diverse conditions, achieving high sensitivity and specificity--even for low-frequency variants--outperforming existing tools. Application of our model to WGS data further enabled recovery of biologically relevant mutational signatures, including restoration of microsatellite instability (MSI)-associated signatures initially obscured by FFPE artifacts. Our findings underscore the necessity of artifact-aware variant calling in FFPE genomics and establish DeepOmicsFFPE-PLUS as a robust tool for artifact removal, enabling high-fidelity downstream analyses and personalized therapeutic target discovery.

cancer biology↗

bioRxiv2021

In vitro validation of neoantigen prediction algorithm for developing personalized cancer vaccine therapy

BackgroundThe development of personalized neoantigen-based therapeutic cancer vaccines relies on computational algorithm-based pipelines. One of the critical issues in the pipeline is obtaining higher positive predictive value (PPV) performance, i.e., how many are immunogenic when selecting the top 5 to 20 candidate neoepitopes for the vaccination. We attempted to test the PPV of a neoepitope prediction algorithm Neopepsee. MethodsSix breast cancer patients and patient-derived xenografts from three lung cancer patients and their paired peripheral blood samples were subjected to whole-exome and RNA sequencing. Neoantigen was predicted using two different algorithms (Neopepsee and pVACseq). Response of induced memory T cells to neopeptide candidates was evaluated by IFN-{gamma} Enzyme-linked immune absorbent spot (ELISpot) assays of peripheral blood mononuclear cell (PBMC) from three HLA-matched donors. Positive ELISpot response to a candidate peptide in at least 2 of 3 donor PBMC was regarded as an immunogenic response. ResultsNeopepsee predicted 159 HLA-A matched neoepitope candidates out of 898 somatic mutations in nine patients (six breast and three lung cancer patients), whereas pVACseq predicted 84 HLA-A matched candidates. A total of 26 neopeptide candidates overlapped between the two predicted candidate pools. Among the candidates, 28 (20%, 28/ 137) and 15 (20%, 15/ 75) were positive by ELISpot assay, respectively. Among 26 overlapped candidates, 20 could be tested, and 7 of them (35%) were validated by ELISpot. Neopepsee identified at least one neoepitope in 7 of 9 patients (range 0-6), compared to 6 by pVACseq (range 0-5). ConclusionAs suggested by Tumor Neoantigen Selection Alliance (TESLA), our results demonstrate low PPV of individual prediction models as well as the complementary nature of the Neopepsee and pVACseq and may help design neoepitope targeted cancer vaccines. Our data contribute a significant addition to the database of tested neoepitope candidates that can be utilized to further train and improve the prediction algorithms.

immunology↗

bioRxiv2020

Immunotherapy efficacy in colorectal cancer is dependent on activation of a microbial-metabolite-immune circuit

Cancer is a leading cause of death globally. Checkpoint blockade therapies offer a promising treatment for many cancers, but have been ineffective for colorectal cancers. Previous studies have shown a dependency of immunotherapies on the microbiota. Consequently, we hypothesized that specific gut bacteria promote immunotherapy for colorectal cancer. We identify three commensal bacteria and a microbial metabolite, inosine, that enhance the efficacy of immune checkpoint blockade therapy in colorectal cancer. We show that inosine interacts with the adenosine A2A receptor on T cells resulting in intestinal Th1 cell differentiation. Decreased gut barrier function induced by immunotherapy increased the translocation of bacterial metabolites and promoted cancer protective Th1 cell activation. This microbial-metabolite-immune circuit provides a mechanism for a new class of bacteria-enhanced checkpoint blockade therapies. The efficacy of this mechanism differs among colorectal cancer subtypes and highlights the strengths as well as potential limitations of this novel bacterial co-therapy for cancer.

cancer biology↗

bioRxiv2019

Loss of BubR1 Acetylation instigates Replication Stress leading to Complex Chromosomal Rearrangement in tumors

Chromosome number and structure instability is the hallmark of cancer. Equal chromosome segregation is guaranteed by the spindle assembly checkpoint (SAC), thus defective SAC leads to chromosome instability. However, aneuploidy alone is not oncogenic, and whether compromised SAC is associated with structure instability remains elusive. BubR1 is a core component of SAC, which is acetylated at lysine 250 in mitosis. Previously, we showed that deficiency of BubR1 acetylation in mice (K243R/+) leads to spontaneous tumorigenesis via chromosome mis-segregation. Here, we asked whether loss of BubR1 acetylation is associated with chromosome structure instability by examining K243R/+ mice intercrossed to p53-deficient mice. Genome-wide sequencing and spectral karyotyping of the double mutant mouse tumors revealed that BubR1 acetylation deficiency leads to complex chromosome rearrangements, including Robertsonian-like whole-arm translocations and premature sister-chromatid separations (PMSCS). In primary MEFs, replication stress was markedly increased in telomeres and centromeres, suggesting that the replication stress underlies the significant increase of DNA damage and subsequent chromosome rearrangements. Furthermore, defects in BubR1 acetylation at K250 were detected in human cancers as well. Collectively, we propose that chromosome mis-segregation by the loss of BubR1 acetylation causes chromosome structure instability, leading to massive chromosome rearrangements through the induction of replication stress.

cancer biology↗