Biology subjects

Tan, I. B.

Publications and source records attributed to Tan, I. B..

8 recordsLinked to original sources

bioRxiv2025

Comprehensive benchmarking of methods for mutation calling in circulating tumor DNA

Detection of somatic mutations in cell-free DNA (cfDNA) is challenging due to low variant allele frequencies and pronounced DNA degradation. Here, we present a novel approach and resource for benchmarking of somatic variant calling algorithms in cfDNA samples from cancer patients. Using longitudinally collected cfDNA samples from colorectal and breast cancer patients, we identify patient-matched samples with high and ultra-low circulating tumor DNA (ctDNA) levels. These sample pairs, preserving patient-specific germline and somatic haematopoiesis variant backgrounds, were used to generate dilution series capturing characteristics of bona-fide cfDNA samples. To benchmark the accuracy and limit of detection of 9 somatic variant calling algorithms, we used deep Whole Genome Sequencing (WGS, 150x) and ultra-deep Whole Exome Sequencing (WES, 2,000x) to construct a reference set of [~]37,000 Single Nucleotide Variants and [~]58,000 Insertions/Deletions. We tested methods under variable ctDNA levels and depth of sequencing, generating guidelines for method choice depending on use case. Using a machine learning approach, we further evaluated the potential of fine-tuning individual variant callers, revealing features that may improve accuracy in cfDNA samples. Overall, we present a new resource for benchmarking of somatic variant calling methods in cfDNA, providing insights on method choice to realize the potential of liquid biopsies in precision oncology.

bioinformatics↗

bioRxiv2024

ctQC improves biological inferences from single cell and spatial transcriptomics data

Quality control (QC) is the first critical step in single cell and spatial data analysis pipelines. QC is particularly important when analysing data from primary human samples, since genuine biological signals can be obscured by debris, perforated cells, cell doublets and ambient RNA released into the "soup" by cell lysis. Consequently, several QC methods for single cell data, employ fixed or data-driven quality thresholds. While these approaches efficiently remove empty droplets, they often retain low-quality cells. Here, we propose cell type-specific QC (ctQC), a stringent, data-driven QC approach that adapts to cell type differences and discards soup and debris. Evaluating single cell RNA-seq data from colorectal tumors, human spleen, and peripheral blood mononuclear cells, we demonstrate that ctQC outperforms existing methods by improving cell type separation in downstream clustering, suppressing cell stress signatures, revealing patient-specific cell states, eliminating artefactual clusters and reducing ambient RNA artifacts. When applied to sequencing-based spatial RNA profiling data (Slide-seq), ctQC improved spatial coherence of cell clusters and consistency with anatomical structures. These results demonstrate that strict, data-driven, cell-type-specific QC is applicable to diverse sample types and substantially improves the quality and reliability of biological inferences from single cell and spatial RNA profiles.

bioinformatics↗

bioRxiv2023

The cholesterol biosynthesis enzyme FAXDC2 couples Wnt/beta-catenin to RTK/MAPK signaling

Wnts, cholesterol, and MAPK signaling are essential for development and adult homeostasis. Here we report for the first time that fatty acid hydroxylase domain containing 2 (FAXDC2), a previously uncharacterized enzyme, functions as a methyl sterol oxidase catalyzing C4 demethylation in the Kandutsch-Russell branch of the cholesterol biosynthesis pathway. FAXDC2, a paralog of MSMO1, regulates the abundance of specific C4-methyl sterols lophenol and dihydro-TMAS. Highlighting its clinical relevance, FAXDC2 is repressed in Wnt/{beta}-catenin high cancer xenografts, in a mouse genetic model of Wnt activation, and in human colorectal cancers. Moreover, in primary human colorectal cancers, the sterol lophenol, regulated by FAXDC2, accumulates in the cancerous tissues and not in adjacent normal tissues. FAXDC2 links Wnts to RTK/MAPK signaling. Wnt inhibition drives increased recycling of RTKs and activation of the MAPK pathway, and this requires FAXDC2. Blocking Wnt signaling in Wnt-high cancers causes both differentiation and senescence; and this is prevented by knockout of FAXDC2. Our data shows the integration of three ancient pathways, Wnts, cholesterol synthesis, and RTK/MAPK signaling, in cellular proliferation and differentiation. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=116 SRC="FIGDIR/small/571793v1_ufig1.gif" ALT="Figure 1"> View larger version (32K): org.highwire.dtl.DTLVardef@6608f2org.highwire.dtl.DTLVardef@d5566eorg.highwire.dtl.DTLVardef@1d889aorg.highwire.dtl.DTLVardef@f37411_HPS_FORMAT_FIGEXP M_FIG C_FIG

cancer biology↗

bioRxiv2023

A transcriptome-wide meta-analysis reveals lack of cancer-cell intrinsic determinants of response to immune checkpoint blockade

Immune-checkpoint therapy (ICB) has conferred significant and durable clinical benefit to some cancer patients. However, most patients do not respond to ICB, and reliable biomarkers of ICB response are needed to improve patient stratification. Here, we performed a transcriptome-wide meta-analysis across 1,486 tumors from ICB-treated patients and tumors with expected ICB outcomes based on microsatellite status. Using a robust transcriptome deconvolution approach, we inferred cancer and stroma-specific gene expression differences and identified cell-type specific features of ICB response across cancer types. Consistent with current knowledge, stromal expression of CXCL9, CXCL13, and IFNG were the top determinants of favorable ICB response. In addition, we identified a group of potential immune-suppressive genes, including FCER1A, associated with poor response to ICB. Strikingly, PD-L1 expression in stromal cells, but not cancer cells, is correlated with ICB response across cancer types. Furthermore, the unbiased transcriptome-wide analysis failed to identify cancer-cell intrinsic features of ICB response conserved across tumor types. Overall, our results challenge the prevailing dogma that cancer cells present tissue-agnostic molecular markers that modulate immune activity and ICB treatment response. These results have implications for the development of improved ICB treatments and diagnostics.

cancer biology↗

bioRxiv2021

Heatrich-BS enables efficient CpG enrichment and highly scalable cell-free DNA methylation profiling

Genome wide analysis of cell-free DNA (cfDNA) methylation profile has been shown to be a promising approach for sensitive and specific multi-cancer detection. However, scaling these assays for clinical translation is impractical due to the high cost of whole genome bisulfite sequencing. We showed that the small fraction of GC-rich genome is highly enriched in CpG sites and disproportionately harbored the majority of cancer-specific methylation signature. Here, we report on the simple but effective Heat enrichment of CpG-rich regions for Bisulfite Sequencing (Heatrich-BS) platform that enables focused methylation profiling in these highly informative regions. Our novel method and bioinformatics algorithm enable high accuracy and sensitivity in tumor burden estimation and quantitative monitoring of colorectal patient response to treatment, at much reduced sequencing requirement. Heatrich-BS holds great potential for highly scalable screening and regular monitoring of cancer using liquid biopsy.

genomics↗

bioRxiv2019

The chromatin structuring protein HMGA2 influences human subtelomere stability and cancer chemosensitivity

The transient build-up of DNA supercoiling during the translocation of replication forks threatens genome stability and is controlled by DNA topoisomerases (TOPs). This crucial process has been exploited with TOP poisons for cancer chemotherapy. However, pinpointing cellular determinants of the best clinical response to TOP poisons still remains enigmatic. Here, we present an integrated approach and demonstrate that endogenous and exogenous expression of the oncofetal high-mobility group AT-hook 2 (HMGA2) protein exhibited broad protection against the formation of hydroxyurea-induced DNA breaks in various cancer cells, thus corroborating our previously proposed model in which HMGA2 functions as a replication fork chaperone that forms a protective DNA scaffold at or close to stalled replication forks. We now further demonstrate that high levels of HMGA2 also protected cancer cells against DNA breaks triggered by the clinically important TOP1 poison irinotecan. This protection is most likely due to the recently identified DNA supercoil constraining function of HMGA2 in combination with exclusion of TOP1 from binding to supercoiled substrate DNA. In contrast, low to moderate HMGA2 protein levels surprisingly potentiated the formation of irinotecan-induced genotoxic covalent TOP1-DNA cleavage complexes. Our data from cell-based and several in vitro assays indicate that, mechanistically, this potentiating role involves enhanced drug-target interactions mediated by HMGA2 in ternary complexes with supercoiled DNA. Subtelomeric regions were found to be extraordinarily vulnerable to these genotoxic challenges induced by TOP1 poisoning, pointing at strong DNA topological barriers located at human telomeres. These findings were corroborated by an increased irinotecan sensitivity of patient-derived xenografts of colorectal cancers exhibiting low to moderate HMGA2 levels. Collectively, we uncovered a therapeutically important control mechanism of transient changes in chromosomal DNA topology that ultimately leads to enhanced human subtelomere stability. Author SummaryDNA replication fork stability in rapidly dividing cancer cells is of utmost importance for the maintenance of genome stability and cancer cell viability. Cancer cells efficiently prevent fork collapse into lethal double strand breaks as a first line of defense during replication stress, but the corresponding protective mechanisms often remain elusive. Uncontrolled high levels of DNA supercoiling that are generally regulated by topoisomerases can cause replication stress and are major threats to fork stability. Using a multidisciplinary approach, we identified a possible regulatory mechanism of replication stress, which appears to involve mitigating the consequences of DNA topological changes by the oncofetal replication fork chaperone HMGA2. Our work provides mechanistic insights into the control of DNA damage triggered by clinically important anti-cancer drugs, which is mediated by the replication fork chaperone HMGA2. We thereby also identify HMGA2 expression as a predictive therapeutic marker, which could allow clinicians to take informed decisions to prevent tumor recurrence and improve survival.

cancer biology↗

bioRxiv2018

Liquid biopsy in gastrointestinal stromal tumors -- Simultaneous detection of primary and secondary mutations with an NGS based circulating tumor DNA assay

Introduction Introduction Methods Results Discussion References Gastrointestinal Stromal tumors (GISTs) are the most common neoplasms of mesenchymal origin arising from the gastrointestinal tract. GISTs are mostly characterised by one predominant activating mutation in KIT (KIT proto-oncogene receptor tyrosine kinase) or PDGFRA (platelet derived growth factor receptor alpha) genes1-3. Under pharmacological pressure, one or more secondary mutations can develop in KIT, conferring resistance to tyrosine kinase inhibitor, imatinib. In imatinib-resistant GISTs, secondary mutations can occur in the ATP binding pocket, encoded by exons 13 and 14 or in the kinase activation loop, encoded predominantly by exon 174. In vitro studies ha ...

molecular biology↗

bioRxiv2017

ConsensusDriver Improves Upon Individual Algorithms For Predicting Driver Alterations In Different Cancer Types And Individual Patients -- A Toolbox For Precision Oncology

BackgroundIn recent years, several large-scale cancer genomics studies have helped generate detailed molecular profiling datasets for many cancer types and thousands of patients. These datasets provide a unique resource for studying cancer driver prediction methods and their utility for precision oncology, both to predict driver genetic alterations in patient subgroups (e.g. defined by histology or clinical phenotype) or even individual patients.\n\nMethodsWe performed the most comprehensive assessment to date of 18 driver gene prediction methods, on more than 3,400 tumour samples, from 15 cancer types, to determine their suitability in guiding precision medicine efforts. These methods have diverse approaches, which can be classified into five categories: functional impact on proteins in general (FI) or specific to cancer (FIC), cohort-based analysis for recurrent mutations (CBA), mutations with expression correlation (MEC) and methods that use gene interaction network-based analysis (INA).\n\nResultsThe performance of driver prediction methods varies considerably, with concordance with a gold-standard varying from 9% to 68%. FI methods show relatively poor performance (concordance <22%) while CBA methods provide conservative results, but require large sample sizes for high sensitivity. INA methods, through the integration of genomic and transcriptomic data, and FIC methods, by training cancer-specific models, provide the best trade-off between sensitivity and specificity. As the methods were found to predict different subsets of drivers, we propose a novel consensus-based approach, ConsensusDriver, which significantly improves the quality of predictions (20% increase in sensitivity). This tool can be applied to predict driver alterations in patient subgroups (e.g. defined by histology or clinical phenotype) or even individual patients.\n\nConclusionExisting cancer driver prediction methods are based on very different assumptions and each of them can only detect a particular subset of driver events. Consensus-based methods, like ConsensusDriver, are thus a promising approach to harness the strengths of different driver prediction paradigms.

bioinformatics↗