Browsing by Subject "neoantigen"

Now showing 1 - 2 of 2
  • Thumbnail Image
    Item
    Intron Retention Induced Neoantigen as Biomarkers in Diseases
    (2022-08) Dong, Chuanpeng; Yan, Jingwen; Liu, Yunlong; Huang, Kun; Wan, Jun; Liu, Xiaowen
    Alternative splicing is a regulatory mechanism that generates multiple mRNA transcripts from a single gene, allowing significant expansion in proteome diversity. Disruption of splicing mechanisms has a large impact on the transcriptome and is a significant driver of complex diseases by producing condition-specific transcripts. Recent studies have reported that mis-spliced RNA transcripts can be another major source of neoantigens directly associated with immune responses. Particularly, aberrant peptides derived from unspliced introns can be presented by the major histocompatibility complex (MHC) class I molecules on the cell surface and elicit immunogenicity. In this dissertation, we first developed an integrated computational pipeline for identifying IR-induced neoantigens (IR-neoAg) from RNA sequencing (RNA-Seq) data. Our workflow also included a random forest classifier for prioritizing the neoepitopes with the highest likelihood to induce a T cell response. Second, we analyzed IR neoantigen using RNA-Seq data for multiple myeloma patients from the MMRF study. Our results suggested that the IR-neoAg load could serve as a prognosis biomarker, and immunosuppression in the myeloma microenvironment might offset the increasing neoantigen load effect. Thirdly, we demonstrated that high IR-neoAg predicts better overall survival in TCGA pancreatic cancer patients. Moreover, our results indicated the IR-neoAg load might be useful in identifying pancreatic cancer patients who might benefit from immune checkpoint blockade (ICB) therapy. Finally, we explored the association of IR-induced neo-peptides with neurodegeneration disease pathology and susceptibility. In conclusion, we presented a state-of-art computational solution for identifying IR-neoAgs, which might aid neoantigen-based vaccine development and the prediction of patient immunotherapy responses. Our studies provide remarkable insights into the roles of alternative splicing in complex diseases by directly mediating immune responses.
  • Thumbnail Image
    Item
    Predictive Molecular Biomarkers for Human Health Risk
    (2024-07) Jiang, Guanglong; Liu, Yunlong; Yan, Jingwen; Wan, Jun; Wang, Juexin
    Molecular biomarkers play vital roles in disease risk assessment, personalized treatment selection and therapy response monitoring. This thesis explores the use of diverse molecular biomarkers for the assessment of human health risks, primarily in cancers. MiRNAs and their isoforms (isomiR) are promising biomarker candidates due to their comprehensive regulation of gene expression and involvement in physiology and pathological processes. The first study demonstrates that genetic variations in miRNA precursor regions influence the biogenesis of isomiRs in 95 SNP-isomiR pairs. Notably, we identified a SNP (rs6505162) impacting hsa-miR-423 isomiRs, potentially linked to breast cancer pathogenesis, suggesting their potential as biomarkers in disease assessment. The findings also highlight the mechanism of genetic regulation of isomiR generation and advance our understanding of miRNA mediated post-transcriptional regulation. Secondly, we explored the predictive capacity of aberrant intron-retention neoantigen burden (INB) in predicting the response to immune checkpoint inhibitors (ICI) in metastatic cancers. Both INB and tumor mutation burden (TMB) were strong predictors of ICI therapy duration (p = 0.019 and 0.038, respectively), with patients exhibiting elevated levels demonstrating exceptional treatment duration. Patients with high INB or TMB had improved overall survival (OS) (p = 1.1×10-4). Importantly, INB and TMB were uncorrelated, indicating that they capture distinct aspects of tumor neoantigen. Together, the combined assessment of INB and TMB offers improved accuracy in predicting clinical response to ICI therapies. Finally, we extend the application of molecular biomarkers to the assessment of minimal residual disease for risk stratification in triple negative breast cancer (TNBC) with residual disease after neoadjuvant chemotherapy. Detection of circulating tumor DNA (ctDNA) was a significant predictor of inferior distant disease-free survival (DDFS) (p = 0.006), disease-free survival (DFS) (p = 0.009) and OS (p = 0.002). The combination of circulating tumor cell (CTC) and ctDNA markers provided superior sensitivity and prognostic value. In conclusion, the studies provide compelling evidence for the utility of diverse molecular biomarkers – including miRNA isoforms, abnormal splicing-based neoantigen metrics and circulating tumor DNA in disease prediction and treatment efficacy assessment. By elucidating the roles of diverse biomarkers in predicting cancer pathogenesis and therapeutic response, we pave the way towards more personalized and effective approaches to managing human health risks.