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Heng, Y. J.

Publications and source records attributed to Heng, Y. J..

4 recordsLinked to original sources

African Green Monkey Cerebrospinal Fluid miRNome Captures Conserved miRNAs Relevant to Human Neurodegenerative Disease

BackgroundThe African green monkey (AGM) is increasingly used as a model for early-stage Alzheimers disease (AD), with cerebrospinal fluid (CSF) targeted for biomarker discovery and longitudinal disease monitoring of shifts in the central nervous system. MicroRNAs (miRNAs) are particularly informative indicators of early neuropathological change. Despite the complementary value of an early-stage disease model and a molecular marker capable of capturing early change, the miRNA composition (miRNome) of AGM remains undefined. We established the AGM CSF miRNome from antemortem samples using miRNA sequencing and a qRT-PCR-based array. We also developed a hierarchical annotation pipeline to classify miRNAs as either family-conserved or unclassified and to assess sequence alignment across humans and other species. ResultsWe used untargeted miRNA sequencing to characterize the AGM CSF miRNome and identified 205 miRNAs that could be classified into three family-conserved categories: canonical, noncanonical, and 3'-terminal variants. Of these, 150 were also detected using a human-targeted qRT-PCR array, providing independent support for the sequence-derived miRNome. Sequencing abundance and qRT-PCR array Ct values showed significant cross-platform concordance overall, although concordance was lower for 3'-terminal isomiRs than for canonical miRNAs. Comparison with human GTEx tissue-expression data indicated that several human homologs of AGM CSF miRNAs exhibited brain-preferential expression. Notably, predicted targets of many of these miRNAs were enriched for pathways implicated in neurodegenerative disease. Finally, we identified 20 unclassified candidates that could not be assigned to established miRNA families, two of which we propose as putatively novel miRNAs. ConclusionThe AGM CSF miRNome is substantially conserved with the human miRNome but also contains 3'-terminal isomiRs and unclassified miRNA candidates. AGM CSF contains miRNAs homologous to human miRNAs associated with AD and other neuropathologies, highlighting the translational potential of this model. However, our study also reveals challenges related to species-specific sequence variation and reduced cross-platform concordance for isomiRs. Thus, comparative studies will be needed to validate the functional and biomarker relevance of these miRNAs across species. More generally, this initial miRNome provides a reference resource for future studies of miRNAs in AGM across disease-related, physiological, experimental, and evolutionary contexts.

genomics↗

MicroRNA spatial profiling for assessing drug efficacy in BRCA1-related triple-negative breast tumors

BRCA1/2-mutated breast cancers exhibit homologous recombination deficiency (HRD) and are initially sensitive to poly(ADP-ribose) polymerase (PARP) inhibitors, but 40-70% of patients develop resistance, creating a need for predictive biomarkers that capture treatment-associated spatial heterogeneity. Using the K14-Cre Brca1f/fTrp53f/fmodel with tumors that acquired PARP inhibitor resistance, we evaluated PARP inhibitor combinations with either PI3K inhibition or Poly(I:C) in vivo. To determine how treatment altered tumor spatial microRNA (miRNA) profiles, we applied our hydrogel-based, nanoliter well array in situ miRNA assay to quantify and spatially profile miRNAs on FFPE sections from tumors treated for 10 days and developed spatial miRNA analysis frameworks integrating latent Dirichlet allocation (LDA) and principal component analysis (PCA). We also incorporated immune architecture using Structural Similarity Index Measure (SSIM) maps to assess co-localization of immune infiltration and miRNA topics. Both combinations improved antitumor activity compared to PARP inhibition alone. The resulting spatial miRNA topics stratified early tumors according to subsequent PARP inhibitor sensitivity or resistance and distinguished their treatment regimens, while SSIM analysis revealed co-localization of immune infiltration and miRNA topics. This integrative spatial miRNA assay and analysis identified a let-7a-dominant topic associated with PARP inhibitor resistance, indicating that spatial miRNA profiling may inform therapeutic stratification in BRCA1/2-related breast cancers.

biochemistry↗

Somatic mutational profiles and germline polygenic risk scores in human cancer

The mutational profile of a cancer reflects the activity of the mutagenic processes which have been operative throughout the lineage of the cancer cell. These processes leave characteristic profiles of somatic mutations called mutational signatures. Mutational signatures, including single-based substitution (SBS) signatures, may reflect the effects of exogenous or endogenous exposures. Here, we used polygenic risk score (PRS) as proxies for exposures and examined the association between somatic mutational profiles and germline PRS in 12 cancer types from The Cancer Genome Atlas project. We found 17 statistically significant associations after Bonferroni correction (p < 3.15x10-5), including positive associations between germline inflammatory bowel disease PRS and number of somatic mutations of signature SBS1 in prostate cancer and APOBEC-related signatures in breast cancer. The age at menarche PRS was inversely associated with mutation counts of SBS1 in prostate cancer. Our analysis suggests that there are robust associations between tumor somatic mutational profiles and germline PRS. These may reflect mechanisms through hormone regulation and immunological responses that contribute to cancer etiology and drive cancer progression.

genomics↗

Automated Clear Cell Renal Carcinoma Grade Classification with Prognostic Significance

We developed an automated 2-tiered Fuhrmans grading system for clear cell renal cell carcinoma (ccRCC). Whole slide images (WSI) and clinical data were retrieved for 395 The Cancer Genome Atlas (TCGA) ccRCC cases. Pathologist 1 reviewed and selected regions of interests (ROIs). Nuclear segmentation was performed. Quantitative morphological, intensity, and texture features (n=72) were extracted. Features associated with grade were identified by constructing a Lasso model using data from cases with concordant 2-tiered Fuhrmans grades between TCGA and Pathologist 1 (training set n=235; held-out test set n=42). Discordant cases (n=118) were additionally reviewed by Pathologist 2. Cox proportional hazard model evaluated the prognostic efficacy of the predicted grades in an extended test set which was created by combining the test set and discordant cases (n=160). The Lasso model consisted of 26 features and predicted grade with 84.6% sensitivity and 81.3% specificity in the test set. In the extended test set, predicted grade was significantly associated with overall survival after adjusting for age and gender (Hazard Ratio 2.05; 95% CI 1.21-3.47); manual grades were not prognostic. Future work can adapt our computational system to predict WHO/ISUP grades, and validating this system on other ccRCC cohorts.

pathology↗