Biology subjects

Wong, K. K.

Publications and source records attributed to Wong, K. K..

8 recordsLinked to original sources

bioRxiv2026

CEP-IP with CMRF in SEA-AD Microglia: A Mitochondrial Co-expression Module Linked to Cognition

Single-nucleus RNA-seq (snRNA-seq) studies of Alzheimer's disease (AD) routinely filter nuclei by mitochondrial percentage (%MT), yet whether these reads carry information about cognition is rarely examined. In the Seattle Alzheimer's Disease Brain Cell Atlas (SEA-AD) microglia snRNA-seq dataset, a transcriptome-wide screen identified a module of MT-CO3 and eight co-expressed mitochondrial genes. Three microglial populations were analyzed: PVM_3, M4 (Mic.13-like), and PVM_1, with a housekeeping-gene control. The CEP-IP pipeline with a copula monotone recovery filter (CMRF) used per-cell Spearman and Kendall scores, an inflection point (IP), and a cross-validated copula space boundary to isolate MT-CO3 Module cells. The donor percentage of Module cells past the IP (Module post-IP%) was significantly associated with worse cognition (MMSE and CASI; FDR<0.05) in all three populations. In PVM_3 and M4, these associations remained significant after adjustment for tissue quality, plaque burden, tangle burden, and contamination, and after doublet removal. PVM_3 and M4 Module post-IP% repeated in each donor's regions beyond chance, and no per-cell %MT cutoff reproduced the Module cells. In two external datasets without cognitive scores, the MT-CO3 module and its IP replicated. However, at the donor level, Module post-IP% could not be separated from mean %MT, and the source of the mitochondrial transcripts (e.g., retained cytoplasm or a true change in mitochondrial content) remains unresolved. Routine %MT filtering in AD snRNA-seq may therefore remove cells that carry information about cognition. The R package cepip, the pipeline code, and a software container that reproduced the findings are publicly available.

bioinformatics↗

bioRxiv2025

M1C is a druggable target for NSCLC KRAS G12C mutant tumors resistant to KRAS inhibitors

Treatment of NSCLC KRAS G12C mutant tumors with the allele-selective sotorasib inhibitor is invariably associated with acquired resistance. The MUC1-encoded oncogenic M1C protein is necessary for self-renewal of NSCLC KRAS mutant cells. We report that treatment of NSCLC KRAS G12C cells with sotorasib induces M1C expression by a STAT1-dependent pathway. In turn, M1C drives sotorasib resistance by NF-{kappa}B-mediated induction of the epithelial-mesenchymal transition (EMT). Targeting M1C(R)NF-{kappa}B signaling (i) suppresses EMT, and (ii) reverses sotorasib resistance. Of translational relevance, treatment with a M1C antibody-drug conjugate (ADC) is effective against sotorasib-resistant NSCLC KRAS G12C cell line and patient-derived tumor xenografts. Clinically, targeted treatment of patients with NSCLC KRAS G12C tumors overexpressing MUC1 associates with decreases in overall survival. These findings identify M1C as a key effector of sotorasib resistance and as a target for treatment of patients with refractory NSCLC KRAS G12C mutant tumors.

cancer biology↗

bioRxiv2024

Multiomics data analysis identifies TM4SF4 as a cell surface target in hepatocellular carcinoma

The clinical application of cellular immunotherapy in hepatocellular carcinoma (HCC) is impeded by the lack of a cell surface target frequently expressed in HCC cells and with minimal presence in normal tissues to reduce on-target, off-tumor toxicity. In this in silico analysis, a longlist of genes (n=12,948) expressed in HCCs according to The Human Protein Atlas database were examined. The aim was to identify the optimal cell surface target, without being shed into circulation, in HCCs and with restrictive expression profile in other normal human tissues. A total of eight genes were shortlisted and they were subsequently ranked according to the combination of their transcript and protein expression levels in HCC cases (n=791) derived from four independent datasets (TCGA, CNHPP, GSE14520, and CHCC). TM4SF4 was the top-ranked target with the highest expression in HCCs. TM4SF4 demonstrated more favorable expression profile with significantly lower expression in normal human tissues but more highly expressed in HCC cases compared with seven other common HCC therapeutic targets. Furthermore, scRNA-seq (GSE149614 and GSE134355) and immunohistochemistry (HPA) datasets showed that TM4SF4 was absent in immune cell populations but highly expressed in the bile duct canaliculi of hepatocytes, a region that is inaccessible to immune cells. In scRNA-seq dataset of HCCs (GSE149614), TM4SF4 expression was positively associated with mitochondrial components and oxidative phosphorylation Gene Ontologies in HCC cells (n=15,787 cells), suggesting its potential roles in mitochondrial-mediated oncogenic effects in HCC. Taken together, TM4SF4 is proposed as a promising cell surface target in HCC.

cancer biology↗

bioRxiv2024

Directed Evolution of Acoustic Reporter Genes Using High-Throughput Acoustic Screening

A major challenge in the fields of biological imaging and synthetic biology is noninvasively visualizing the functions of natural and engineered cells inside opaque samples such as living animals. One promising technology that addresses this limitation is ultrasound (US), with its penetration depth of several cm and spatial resolution on the order of 100 {micro}m.1 Within the past decade, reporter genes for US have been introduced2,3 and engineered4,5 to link cellular functions to US signals via heterologous expression in commensal bacteria and mammalian cells. These acoustic reporter genes (ARGs) represent a novel class of genetically encoded US contrast agent, and are based on air-filled protein nanostructures called gas vesicles (GVs).6 Just as the discovery of fluorescent proteins was followed by the improvement and diversification of their optical properties through directed evolution, here we describe the evolution of GVs as acoustic reporters. To accomplish this task, we establish high-throughput, semi-automated acoustic screening of ARGs in bacterial cultures and use it to screen mutant libraries for variants with increased nonlinear US scattering. Starting with scanning site saturation libraries for two homologs of the primary GV structural protein, GvpA/B, two rounds of evolution resulted in GV variants with 5- and 14-fold stronger acoustic signals than the parent proteins. We anticipate that this and similar approaches will help high-throughput protein engineering play as large a role in the development of acoustic biomolecules as it has for their fluorescent counterparts.

bioengineering↗

bioRxiv2022

Long-term ovarian cancer survivors: spatial transcriptomics depict ligand-receptor crosstalk heterogeneity at the tumor-stroma interface

Advanced high-grade serous ovarian cancer (HGSC) is an aggressive disease that accounts for 70% of all ovarian cancer deaths. Nevertheless, 15% of patients diagnosed with advanced HGSC survive more than 10 years. The identification of predictive markers associated with tumors developed from these long-term survivors (LTS) is crucial to identifying therapeutic targets for the disease, and thus improving patient survival rates. Reports to date have not fully established the stromal heterogeneity of the tumor microenvironment (TME) in ovarian cancer and its association with clinical outcomes. We used a spatial transcriptomics platform to generate spatially resolved transcript profiles in treatment naive advanced HGSC from LTS and short-term survivors (STS), and determined whether cancer-associated fibroblasts (CAFs) heterogeneity is associated with survival in patients with advanced HGSC. We integrated spatial transcriptomics with single-cell RNA sequencing data to distinguish tumor and stroma regions, and developed a method to investigate spatially resolved ligand-receptor interactions between various tumor and CAF subtypes in the TME. In addition, we used multiplex immunohistochemistry techniques to validate our findings. We found that a specific subtype of CAFs and its spatial location relative to a particular ovarian cancer cell subtype in the TME correlate with long-term survival in advanced HGSC patients. We also demonstrated that significant APOE-LRP5 crosstalk occurred at the stroma-tumor interface in tumor tissues from STS compared to LTS, suggesting that such crosstalk plays a crucial role in modulating the malignant phenotype of HGSC, and could serve as a predictive biomarker of patient survival.

cancer biology↗

bioRxiv2018

Intron retention as a novel source of cancer neoantigens

Personalized cancer vaccine strategies directed at tumor neoantigens derived from somatic mutations in the DNA are currently under prospective evaluation1, 2. Alterations in tumor RNA, rather than DNA, may also represent a previously-unexplored source of neoantigens. Here, we show that intron retention, a widespread feature of cancer transcriptomes3, 4, represents a novel source of tumor neoantigens. We developed an in silico approach to identify retained intron neoantigens from RNA sequencing data and applied this methodology to tumor samples from patients with melanoma treated with immune checkpoint blockade5, 6, discovering that the retained intron neoantigen burden in these samples augments the DNA-derived, somatic neoantigen burden. We validated the existence of retained intron derived neoantigens by implementing this technique on cancer cell lines with mass spectrometry-derived immunopeptidome data7, 8, revealing that retained intron neoantigens were complexed with MHC I experimentally. Unexpectedly, we observed a trend toward lack of clinical benefit from immune checkpoint blockade in high retained intron load-tumors, which harbored transcriptional signatures consistent with cell cycle dysregulation and DNA damage repair. Our results demonstrate the contribution of transcriptional dysregulation to the overall burden of tumor neoantigens, provide a foundation for augmenting personalized cancer vaccine development with a new class of tumor neoantigens, and demonstrate how global transcriptional dysregulation may impact selective response to immune checkpoint blockade.\n\nStatement of significanceWe developed and experimentally validated a computational pipeline to identify a novel class of tumor neoantigens derived from RNA-based intron retention, which is prevalent throughout cancer transcriptomes. The discovery of transcriptionally-derived tumor neoantigens expands the tumor immunopeptidome and contributes potential substrates for personalized cancer vaccine development.

cancer biology↗

bioRxiv2017

Development and validation of an expanded carrier screen that optimizes sensitivity via full-exon sequencing and panel-wide copy-number-variant identification

PurposeBy identifying pathogenic variants across hundreds of genes, expanded carrier screening (ECS) enables prospective parents to assess risk of transmitting an autosomal recessive or X-linked condition. Detection of at-risk couples depends on the number of conditions tested, the diseases respective prevalences, and the screens sensitivity for identifying disease-causing variants. Here we present an analytical validation of a 235-gene sequencing-based ECS with full coverage across coding regions, targeted assessment of pathogenic noncoding variants, panel-wide copy-number-variant (CNV) calling, and customized assays for technically challenging genes.\n\nMethodsNext-generation sequencing, a customized bioinformatics pipeline, and expert manual call review were used to identify single-nucleotide variants, short insertions and deletions, and CNVs for all genes except FMR1 and those whose low disease incidence or high technical complexity precludes novel variant identification or interpretation. Variant calls were compared to reference and orthogonal data.\n\nResultsValidation of our ECS data demonstrated >99% analytical sensitivity and >99% specificity. A preliminary assessment of 15,177 patient samples reveals the substantial impact on fetal disease-risk detection attributable to novel CNV calling (13.9% of risk) and technically challenging conditions (15.5% of risk), such as congenital adrenal hyperplasia.\n\nConclusionValidated, high-fidelity identification of different variant types--especially in diseases with complicated molecular genetics--maximizes at-risk couple detection.

genetics↗

bioRxiv2016

Systematic Design and Comparison of Expanded Carrier Screening Panels

Purpose: The recent growth in pan-ethnic expanded carrier screening (ECS) has raised questions about how such panels might be designed and evaluated systematically. Design principles for ECS panels might improve clinical detection of at-risk couples and facilitate objective discussions of panel choice.\n\nMethods: Guided by medical-society statements, we propose a method for the design of ECS panels that aims to maximize the aggregate and per-disease sensitivity and specificity across a range of Mendelian disorders considered serious by a systematic classification scheme. We evaluated this method retrospectively using results from 474,644 de-identified carrier screens. We then constructed several idealized panels to highlight strengths and limitations of different ECS methodologies.\n\nResults: Based on modeled fetal risks for \"severe\" and \"profound\" diseases, a commercially available ECS panel (Counsyl) is expected to detect 183 affected conceptuses per 100,000 US births. A screens sensitivity is greatly impacted by two factors: (1) the methodology used (e.g., full-exon sequencing finds up to 46 more affected fetuses per 100,000 than targeted genotyping with an optimal 50 variant panel), and (2) the detection rate of the screen for diseases with high prevalence and complex molecular genetics (e.g., fragile X syndrome, spinal muscular atrophy, 21-hydroxylase deficiency, and alpha-thalassemia account for 54 affected fetuses per 100,000).\n\nConclusion: The described approaches allow principled, quantitative evaluation of which diseases and methodologies are appropriate for pan-ethnic expanded carrier screening.

genetics↗