A5079712911- Cancer Genomics and Diagnostics
- Cancer Immunotherapy and Biomarkers
- Pancreatic and Hepatic Oncology Research
- Colorectal Cancer Treatments and Studies
- Head and Neck Cancer Studies
- Tumors and Oncological Cases
- Epigenetics and DNA Methylation
- RNA modifications and cancer
- Single-cell and spatial transcriptomics
- Cholangiocarcinoma and Gallbladder Cancer Studies
- Cancer-related molecular mechanisms research
- Genomics and Chromatin Dynamics
- Esophageal Cancer Research and Treatment
- Environmental DNA in Biodiversity Studies
- Molecular Biology Techniques and Applications
- Ubiquitin and proteasome pathways
- Lung Cancer Treatments and Mutations
- Radiomics and Machine Learning in Medical Imaging
- Extracellular vesicles in disease
- Fungal and yeast genetics research
- Sarcoma Diagnosis and Treatment
- Cancer-related gene regulation
- Genetic factors in colorectal cancer
- Renal cell carcinoma treatment
University of Toronto
2017-2024
Association of Canadian Map Libraries and Archives
2023
University Health Network
2017-2022
Princess Margaret Cancer Centre
2017-2022
Health Net
2021
York University
2015-2021
Abstract Purpose: Circulating tumor DNA (ctDNA) enables personalized treatment strategies in oncology by providing a noninvasive source of clinical biomarkers. In patients with low ctDNA abundance, tumor-naïve methods are needed to facilitate implementation. Here, using locoregionally confined head and neck squamous cell carcinoma (HNSCC) as an example, we demonstrate detection simultaneous profiling mutations methylation. Experimental Design: We conducted CAncer Personalized Profiling deep...
Abstract Early kinetics of circulating tumor DNA (ctDNA) in plasma predict response to pembrolizumab but typically requires sequencing matched tissue or fixed gene panels. We analyzed genome-wide methylation and fragment-length profiles using cell-free methylated immunoprecipitation (cfMeDIP-seq) 204 samples from 87 patients before during treatment with a pan-cancer phase II investigator-initiated trial (INSPIRE). trained signature independent array data The Cancer Genome Atlas quantify...
The small ubiquitin-like modifier (SUMO) is implicated in various cellular activities, including transcriptional regulation. We previously showed that the yeast activator Gcn4 becomes sumoylated during activation, facilitating its eventual promoter eviction and shut off. Here we show corepressor Tup1 sumoylated, at two specific lysines, under stress conditions. Mutation of these sites has no effect on recruitment or RNAP II occupancy immediately following induction. However, levels...
Transcription-related proteins are frequently identified as targets of sumoylation, including multiple subunits the RNA polymerase II (RNAPII) general transcription factors (GTFs). However, it is not known how sumoylation affects GTFs or whether they sumoylated when assemble at promoters to facilitate RNAPII recruitment and initiation. To explore can regulate genome-wide, we performed SUMO ChIP-seq in yeast found, agreement with others, that most chromatin-associated detected genes encoding...
Abstract Background: Plasma cell-free DNA (cfDNA) tests represent a promising approach for cancer screening. cfDNA methylome approaches are well-suited MCED; however, different methodologies vary in performance and many show decreased early-stage or low-shedding tumors. Here we present retrospective case-control study evaluating the of novel genome-wide enrichment platform MCED. Methods: The full cohort (N=4,322) includes cases (individuals with newly diagnosed treatment-naïve cancer) age-...
Cell-free methylated DNA immunoprecipitation sequencing (cfMeDIP-seq) identifies genomic regions with methylation, using a protocol adapted to work low-input samples and cell-free (cfDNA). We developed set of synthetic spike-in controls for cfMeDIP-seq provide simple inexpensive reference quantitative normalization. designed 54 fragments combinations methylation status (methylated unmethylated), fragment length (80 bp, 160 320 bp), G + C content (35%, 50%, 65%), fraction CpG dinucleotides...
Abstract Background: Plasma-based tests to quantify circulating cell-free DNA cancer signal have emerged as viable applications across the continuum, from early detection optimal disease management. Here we demonstrate feasibility of a tissue-agnostic, genome-wide methylome enrichment platform based on methylated immunoprecipitation and high throughput sequencing (cfMEDIP-seq) for detection, quantification, prognostication in head neck (HNC). Methods: Pre-treatment plasma samples individuals...
Abstract Introduction: Plasma-derived cell-free DNA (cfDNA) can be used to identify cancer signals, including minimal residual disease (MRD), in patients who have undergone curative treatments. The methylated immunoprecipitation and high-throughput sequencing (cfMeDIP-seq) methodology is combined with custom algorithms that leverage differentially regions (DMRs) found cfDNA distinguish between non-cancer signals. This novel non-degradative, tissue-agnostic approach was developed bypass the...
<p>Overall survival (OS) and progression free (PFS) in included patients by cohort. (A) Kaplan-meier curves are shown indicating the OS PFS of five histology-specific cohorts. (B) Forest plot hazard ratios for each cohort a Cox proportional hazards model, with Cohort A as reference level.</p>
<p>Predicting survival outcomes using cancer-specific methylation (CSM) scores at baseline and cycle 3 of pembrolizumab. We computed CSM across the trial cohort. At both 3, patients were split into above- below-median groups. Survival are shown, with hazard ratios p-values adjusted for cohort a Cox model. PFS analysis excludes one patient who progressed before collection sample.</p>
<p>Association of tumor burden with cancer mutation concentration (CMC), as well cancer-specific methylation (CSM) and fragment length score (FLS). We computed CMC from personalized tumor-informed arrays. also CSM FLS fragmentomic analysis respectively data cell-free methylated DNA immunoprecipitation sequencing (cfMeDIP-seq) assays. Coefficients p-values were using Spearman correlations.</p>
<p>Examples of cancer-specific methylation score calculation. Cancer-specific scores were computed using the sum inferred absolute values for all reads overlapping an independently-trained signature. Here, we show examples illustrating how levels are from coverage depths in 300 bp bins while adjusting density CpGs.</p>
<p>CMC and CSM early kinetics discordant cases</p>
<p>Cell-free DNA from cancer patients demonstrates greater fragment length variability. (A) Genome wide lengths were computed and averaged within 5 megabase windows. Normalized short-to-long ratios calculated. Shaded confidence intervals represent 80% 95% of the data. (B) The variance mean across compared log fold change between normal variances are shown for each window. Windows with significantly different identified using non-parametric Ansari-Bradley tests. Neighbouring windows...
<p>Predicting survival outcomes using fragment length score (FLS) at baseline and cycle 3 of pembrolizumab. FLS was determined as the mean log2 transformed cancer-to-normal ratio each in a given cfMeDIP-seq sample. At both 3, patients were split into above- or below-median groups. Survival are shown, with hazard ratios p-values adjusted for cohort Cox model. PFS analysis excludes one patient who progressed before collection sample.</p>
<p>Cancer-specific methylation (CSM) and fragment length scores (FLS) are moderately correlated. CSM FLS were computed for each sample. Correlation testing between log-adjusted was performed using Spearman's method.</p>
<p>Predicting survival outcomes using cancer mutation concentration (CMC) at baseline and cycle 3 of pembrolizumab. CMC was determined a tumor-informed bespoke approach across the trial cohort. At both 3, patients were split into above- or below-median groups. Survival are shown, with hazard ratios p-values adjusted for cohort Cox model. PFS analysis excludes one patient who progressed before collection sample.</p>
<p>Multivariate Cox analysis of the change in fragment length score (FLS) from baseline to cycle 3 pembrolizumab. Covariates clude cohort, PD-L1 expression, and tumor mutation burden.</p>
<p>Non-negative matrix factorization identifies characteristic cancer-associated signatures of shorter fragment lengths and greater nucleosome core occupancy. (A) Genome-wide were used as features in a two-component non-negative analysis. This revealed longer component. The weight the was elevated cell-free DNA cancer patients relative to normal controls. (B) distances ends centers also factorization. two components with different proportions intra-nucleosomal ends. signature more (C)...
<p>Multivariable analysis of OS and PFS using cancer mutation concentration (CMC) at baseline cycle 3 pembrolizumab. CMC was determined a bespoke targeted approach across the trial cohort. At both 3, patients were split into above- or below-median groups. Survival outcomes are shown in multivariable including cohort, PD-L1 expression, tumor burden (TMB).</p>
<div>Abstract<p>Early kinetics of circulating tumor DNA (ctDNA) in plasma predict response to pembrolizumab but typically requires sequencing matched tissue or fixed gene panels. We analyzed genome-wide methylation and fragment-length profiles using cell-free methylated immunoprecipitation (cfMeDIP-seq) 204 samples from 87 patients before during treatment with a pan-cancer phase II investigator-initiated trial (INSPIRE). trained signature independent array data The Cancer Genome...
<p>Increase in both ctDNA metrics identifies a subgroup with particularly poor outcome. Post-hoc analysis of ΔCSM and ΔCMC together demonstrates that decrease either metric was sufficient to result significantly improved PFS OS, whereas increase identified group outcomes. at cycle 3 excludes one patient who progressed before the collection sample.</p>