Biology subjects

Liang, W. S.

Publications and source records attributed to Liang, W. S..

10 recordsLinked to original sources

bioRxiv2023

A public resource of single cell transcriptomes and multiscale networks from persons with and without Alzheimer's disease

The emergence of technologies that can support high-throughput profiling of single cell transcriptomes offers to revolutionize the study of brain tissue from persons with and without Alzheimers disease (AD). Integration of these data with additional complementary multiomics data such as genetics, proteomics and clinical data provides powerful opportunities to link observed cell subpopulations and molecular network features within a broader disease-relevant context. We report here single nucleus RNA sequencing (snRNA-seq) profiles generated from superior frontal gyrus cortical tissue samples from 101 exceptionally well characterized, aged subjects from the Banner Brain and Body Donation Program in combination with whole genome sequences. We report findings that link common AD risk variants with CR1 expression in oligodendrocytes as well as alterations in peripheral hematological lab parameters, with these observations replicated in an independent, prospective cohort study of ageing and dementia. We also observed an AD-associated CD83(+) microglial subtype with unique molecular networks that encompass many known regulators of AD-relevant microglial biology, and which are associated with immunoglobulin IgG4 production in the transverse colon. These findings illustrate the power of multi-tissue molecular profiling to contextualize snRNA-seq brain transcriptomics and reveal novel disease biology. The transcriptomic, genetic, phenotypic, and network data resources described within this study are available for access and utilization by the scientific community.

genomics↗

bioRxiv2022

RNA sequencing analyses of gene expression by CRISPR/Cas9 knockout of CLL-1 gene in acute myeloid leukemia cells

CLL-1 has been revealed its potential role in acute myeloid leukemia (AML), however, the underlying mechanisms remain unclear. CRISPR/Cas9 strategy was employed to knock out CLL-1 gene in U937 cells and western-blot was used to validate the success of knock out. CCK8 and Transwell assays were used to detect cells viability and migration, respectively. RNA-sequencing was performed to profile mRNA expression in CLL-1 gene knock-out and wide type U937 cells. A cutoff of 1.5-fold change and false discovery rate (FDR) <0.05 was used to screen differentially expressed genes (DEGs), which were presented by volcano plots and hierarchical cluster heatmap. Protein-protein interaction (PPI) network was constructed by String database and Cytoscape software. Furthermore, hub genes were mined by CytoNCA and MCODE, which were subjected to functional enrichment using R package. Finally, the findings were validated using qRT-PCR and western-blot. The protein level of CLL-1 was significantly lowered, and cell viability and migration were suppressed in knock-out cells compared to wide type. Using RNA-sequencing and bioinformatics analysis, 452 DEGs (179 up-regulated and 273 down-regulated) were obtained, and several important hub genes (such as CCR2, FBXO21, UBB and UBE2C) were filtered out, which were enriched in 132 GO terms and 36 KEGG pathways such as chemokine signaling pathway and ubiquitin mediated proteolysis. A total of 8 representative genes mRNA expressions were validated by qRT-PCR, and the protein levels of 6 genes were confirmed by western-blot. CLL-1 gene might exert its role in AML through modulating genes enriched in multiple functions such as chemokine signaling and ubiquitination. Our results may give us new knowledge of CLL-1 in AML and provide a basis for mining novel targets.

genetics↗

bioRxiv2020

Bisbee: A proteomics validated analysis package for detecting differential splicing, identifying splice outliers, and predicting splice event protein effects

Here we present a novel statistical approach to splicing outlier and differential splicing detection, implemented in a software package called Bisbee. We leverage Bisbees prediction of protein level effects to benchmark using matched RNAseq and mass spectrometry data from normal tissues. Bisbee exhibits improved sensitivity and specificity over existing approaches. We applied Bisbee to confirm a pathogenic splicing event in a rare disease and to identify tumor-specific splice isoforms associated with an oncogenic splice factor mutation. We also identified common tumor associated splice isoforms replicated in an independent dataset, demonstrating the utility of Bisbee in discovering disease relevant splice variants.

bioinformatics↗

bioRxiv2019

Tumor cell phenotype and heterogeneity differences in IDH1 mutant vs wild-type gliomas

Glioma is recognized to be a highly heterogeneous CNS malignancy, whose diverse cellular composition and cellular interactions have not been well characterized. To gain new clinical- and biological-insights into the genetically-bifurcated IDH1 mutant (mt) vs wildtype (wt) forms of glioma, we integrated multiplexed immunofluorescence single cell data for 43 protein markers across cancer hallmarks, in addition to cell spatial metrics, genomic sequencing and magnetic resonance imaging (MRI) quantitative features. Molecular and spatial heterogeneity scores for angiogenesis and cell invasion differ between IDHmt and wt gliomas irrespective of prior treatment and tumor grade; these differences also persisted in the MR imaging features of peritumoral edema and contrast enhancement volumes. Longer overall survival for IDH1mt glioma patients may reflect generalized altered cellular, molecular, spatial heterogeneity which manifest in discernable radiological manifestations.

genomics↗

bioRxiv2019

ACValidator: a novel assembly-based approach for in silico validation of circular RNAs

Circular RNAs (circRNAs) are evolutionarily conserved RNA species that are formed when exons back-splice to each other. Current computational algorithms to detect these back-splicing junctions produce divergent results, and hence there is a need for a method to distinguish true positive circRNAs. To this end, we developed ACValidator (Assembly based CircRNA Validator) for in silico validation of circRNAs. ACValidator extracts reads from a user-defined window on either side of the circRNA junction and assembles them to generate contigs. These contigs are aligned against the circRNA sequence to find contigs spanning the backspliced junction. When evaluated on simulated datasets, ACValidator achieved over 80% sensitivity and specificity on datasets with an average of 10 circRNA-supporting reads and with read lengths of at least 100 bp. In experimental datasets, ACValidator produced higher validation percentages for samples treated with ribonuclease R compared to non-treated samples. Our workflow is applicable to non-polyA-selected RNAseq datasets and can also be used as a candidate selection strategy for experimental validations. All workflow scripts are freely accessible on our github page https://github.com/tgen/ACValidator along with detailed instructions to set up and run ACValidator. Author summaryCircular RNAs (circRNAs) are a recent addition to the class of non-coding RNAs and are produced when exons back-splice and form closed circular loops. Although several computational algorithms have been developed to detect circRNAs from RNA sequencing (RNAseq) data, they produce divergent results. We hence developed the software Assembly based Circular RNA Validator (ACValidator) as an orthogonal strategy to separately validate predicted circRNAs in silico. ACValidator takes as input a sequence alignment mapping (SAM) file and the circRNA coordinate(s) to be validated. Reads surrounding the circRNA junction are extracted from the SAM file and assembled to generate contigs. These contigs are then aligned against the circRNA sequence to identify contigs that span the back-spliced junction. We evaluated our workflow on simulated as well as experimental datasets to demonstrate the utility of our approach. ACValidator is implemented in python and is highly computationally efficient, with a run time of less than 2 minutes for an 8 GB SAM file. This workflow is applicable to non-polyA-selected RNAseq datasets and can also be used as a candidate selection strategy for experimental validations.

bioinformatics↗

bioRxiv2019

Identification of frequent activating HER2 mutations in primary canine pulmonary adenocarcinoma

Naturally occurring primary canine lung cancers are aggressive malignancies that are increasingly common in pet dogs. They share clinicopathologic features with human lung cancers in never-smokers, but their genetic underpinnings are unknown. Through multi-platform sequencing of 88 primary canine lung tumors or cell lines, we discovered somatic, coding HER2 (ERRB2) point mutations in 38% of canine pulmonary adenocarcinomas (cPAC, 28/74), but none in adenosquamous (cPASC, 0/11) or squamous cell (cPSCC, 0/3) carcinomas. In cPASC, PTEN was the most frequently mutated gene (18%) while one case each bore likely pathogenic HRAS, KRAS, EGFR, MET, TP53, or VHL somatic mutations. In cPSCC, no recurrently mutated genes were identified, but individual somatic coding mutations were found in BRAF and PTPN11. In cPAC, we also identified recurrent somatic mutation of TP53 (13.5%), SMAD4 (5.4%), PTEN (4.1%), and VHL (2.7%). cPACs assessed by exome sequencing displayed a low somatic mutation burden (median 64 point mutations, 19 focal copy number variants, and 1 translocation). The majority (93%) of HER2 mutations were hotspot V659E transmembrane domain (TMD) mutations comparable to activating mutations at this same site in human cancer. Other HER2 mutations identified in this study were located in the extracellular domain and TMD. HER2V659E was detected in the plasma of 33% (2/6) of dogs with localized HER2V659E tumors. HER2V659E correlated with constitutive phosphorylation of AKT in cPAC cell lines and HER2V659E lines displayed hypersensitivity to the HER2 inhibitors lapatinib and neratinib relative to HER2-wild-type cell lines. These findings have translational and comparative relevance for lung cancer and HER2 inhibition.

cancer biology↗

bioRxiv2018

Joint analysis of matched tumor samples with varying tumor contents improves somatic variant calling in the absence of a germline sample

Archival tumor samples represent a potential rich resource of annotated specimens for translational genomics research. However, standard variant calling approaches require a matched normal sample from the same individual, which is often not available in the retrospective setting, making it difficult to distinguish between true somatic variants and germline variants that are private to the individual. Archival sections often contain adjacent normal tissue, but this normal tissue can include infiltrating tumor cells. Comparative somatic variant callers are designed to exclude variants present in the normal sample, so a novel approach is required to leverage sequencing of adjacent normal tissue for somatic variant calling. Here we present LumosVar 2.0, a software package designed to jointly analyze multiple samples from the same patient. The approach is based on the concept that the allelic fraction of somatic variants, but not germline variants, would be reduced in samples with low tumor content. LumosVar 2.0 estimates allele specific copy number and tumor sample fractions from the data, and uses the model to determine expected allelic fractions for somatic and germline variants and classify variants accordingly. To evaluate using LumosVar 2.0 to jointly call somatic variants with tumor and adjacent normal samples, we used a glioblastoma dataset with matched high tumor content, low tumor content, and germline exome sequencing data (to define true somatic variants) available for each patient. We show that both sensitivity and positive predictive value are improved by analyzing the high tumor and low tumor samples jointly compared to analyzing the samples individually or compared to in-silico pooling of the two samples. Finally, we applied this approach to a set of breast and prostate archival tumor samples for which normal samples were not available for germline sequencing, but tumor blocks containing adjacent normal tissue were available for sequencing. Joint analysis using LumosVar 2.0 detected several variants, including known cancer hotspot mutations that were not detected by standard somatic variant calling tools using the adjacent normal as a reference. Together, these results demonstrate the potential utility of leveraging paired tissue samples to improve somatic variant calling when a constitutional DNA sample is not available.

bioinformatics↗

bioRxiv2017

Ponatinib shows potent antitumor activity in small cell carcinoma of the ovary hypercalcemic type (SCCOHT) through multi-kinase inhibition

Structured AbstractPurpose: Subunits of the SWI/SNF chromatin-remodeling complex are tumor suppressors inactivated in [~]20% of all cancers. Yet, few targeted treatments for SWI/SNF-mutant cancers exist. Small cell carcinoma of the ovary, hypercalcemic type (SCCOHT) is a rare, aggressive ovarian cancer in young women that is universally driven by loss of the SWI/SNF ATPase subunits, SMARCA4 and SMARCA2. Given poor two-year survival rates for these women, a great need exists for effective targeted therapies.\n\nExperimental Design: To identify underlying therapeutic vulnerabilities in SCCOHT, we conducted high-throughput siRNA and drug screens. Complementary proteomics approaches comprehensively profiled kinases inhibited by ponatinib. Ponatinib was tested for efficacy in two PDX models and one cell line xenograft model of SCCOHT.\n\nResults: FGFRs and PDGFRs were overlapping hits between screens and the receptor tyrosine kinase (RTK) family was enriched in the siRNA screen hits. Evaluation of eleven RTK inhibitors in three SCCOHT cell lines identified ponatinib, an inhibitor of multiple RTKs, as the most effective clinically approved agent. Proteomics approaches confirmed inhibition of known targets of ponatinib and more than 20 non-canonical ponatinib targets. Ponatinib also delayed tumor doubling time 4-fold in SCCOHT-1 xenografts and reducing final tumor volumes in two SCCOHT patient-derived xenograft (PDX) models by 58.6% and 42.5%.\n\nConclusion: Ponatinib is an effective agent for SCCOHT in both in vitro and in vivo preclinical models through its inhibition of multiple kinases. Clinical investigation of this FDA-approved oncology drug in SCCOHT is warranted.\n\nAdditional InformationThis work was supported by research funds from the Canadian Cancer Society Research Institute 34 (#703458, D.G.H.), the National Institutes of Health (R01 CA195670-01, B.E.W., D.G.H., and 35 J.M.T., and T32 HL007106-39 to E.M.C), the Terry Fox Research Institute Initiative New Frontiers Program in Cancer (#1021, D.G.H.), the British Columbia Cancer Foundation (D.G.H.), the VGH & UBC Foundation (D.G.H.), the Anne Rita Monahan Foundation (P.R.), the Marsha Rivkin Center for Ovarian Cancer Research (J.M.T.), the Ovarian Cancer Alliance of Arizona (J.M.T.), the Small Cell Ovarian Cancer Foundation (P.R., J.D.L., B.V., and J.M.T.), and philanthropic support to the TGen Foundation (J.M.T.).\n\nCOI disclosure statement: The authors declare no potential conflicts of interest.

cancer biology↗

bioRxiv2017

A multicenter, randomized study of decitabine as epigenetic priming with induction chemotherapy in children with AML

BackgroundDecitabine is a deoxycytidine nucleoside derivative inhibitor of DNA-methyltransferases, which has been studied extensively and is approved for myelodysplastic syndrome in adults but with less focus in children. Accordingly, we conducted a phase 1 multicenter, randomized, open-label study to evaluate decitabine pre-treatment before standard induction therapy in children with newly diagnosed AML to assess safety and tolerability and explore a number of biologic endpoints.\n\nResultsTwenty-four patients were fully assessable for all study objectives per protocol (10 in Arm A, 14 in Arm B). All patients experienced neutropenia and thrombocytopenia. The most common grade 3 and 4 non-hematologic adverse events observed were gastrointestinal toxicities and hypophosphatemia. Plasma decitabine PK were similar to previously reported adult data. Overall CR/CRi was similar for the two arms. MRD negativity at end-induction was 85% in Arm A versus 67% in Arm B patients. DNA methylation measured in peripheral blood over the course of treatment tracked with blast clearance and matched marrow aspirates at day 0 and day 21. Unlike end-point marrow analyses, promoter methylation in blood identified an apparent reversal of response in the lone treatment failure, one week prior to the patients marrow aspirate confirming non-response. Decitabine-induced effects of end-induction marrows in Arm A were reflected by changes in DNA methylation and gene expression comparison with matched paired marrow diagnostic aspirates.\n\nConclusionsThis first-in-pediatrics trial demonstrates that decitabine prior to standard combination chemotherapy is feasible and well tolerated in children with newly diagnosed AML. Pre-treatment with decitabine may represent a newer therapeutic option for pediatric AML, especially as it appears to induce important epigenetic alterations. The novel biological correlates studied in this trial offer a clinically relevant window into disease progression and remission. Additional studies are needed to definitively assess whether decitabine can enhance durability responses in children with AML. This trial was registered at www.clinicaltrials.gov as NCT01177540.

clinical trials↗

bioRxiv2017

Evaluation of pre-analytical factors affecting plasma DNA analysis

Pre-analytical factors can significantly affect circulating cell-free DNA (cfDNA) analysis. However, there are few robust methods to rapidly assess sample quality and the impact of pre-analytical processing. To address this gap and to evaluate effects of DNA extraction methods and blood collection tubes on cfDNA yield and fragment size, we developed a multiplexed droplet digital PCR (ddPCR) assay with 5 short and 4 long amplicons targeting single copy genomic loci (mean amplicon size: 71 bp and 471 bp respectively). Using this assay, we compared performance of 7 cfDNA extraction kits and found cfDNA yield and fragment size varies significantly between them. We also compared 3 blood collection protocols used to collect plasma samples from 23 healthy volunteers (EDTA tubes processed within 1 hour and Cell-free DNA BCT tubes at ambient temperature processed within 24 hours and 72 hours of collection). To assess whether cell-stabilizing preservative in BCT tubes introduced noise in cfDNA, we performed digital targeted sequencing. We found no significant differences in cfDNA yield, fragment size and background sequencing noise between these protocols. In 219 clinical samples tested for quality using the ddPCR assay, cfDNA fragment size was significantly shorter in plasma samples immediately processed for ctDNA analysis compared to archived samples, suggesting background DNA contributed by lysed peripheral blood cells. In summary, we describe a multiplexed ddPCR approach that enables cfDNA quality assessment and could inform the design of future circulating tumor DNA studies.\n\nGene namesNone

genomics↗