Biology subjects

Sun, R. X.

Publications and source records attributed to Sun, R. X..

6 recordsLinked to original sources

bioRxiv2023

Integration of Patient-Derived Organoids and Organ-on-Chip Systems: Investigating Colorectal Cancer Invasion within the Mechanical and GABAergic Tumor Microenvironment

Three-dimensional (3D) in vitro models are essential in cancer research, but they often neglect physical forces. In our study, we combined patient-derived tumor organoids with a microfluidic organ-on-chip system to investigate colorectal cancer (CRC) invasion in the tumor microenvironment (TME). This allowed us to create patient-specific tumor models and assess the impact of physical forces on cancer biology. Our findings showed that the organoid-on-chip models more closely resembled patient tumors at the transcriptional level, surpassing organoids alone. Using omics methods and live-cell imaging, we observed heightened responsiveness of KRAS mutant tumors to TME mechanical forces. These tumors also utilized the {gamma}-aminobutyric acid (GABA) neurotransmitter as an energy source, increasing their invasiveness. This bioengineered model holds promise for advancing our understanding of cancer progression and improving CRC treatments. HighlightsO_LIMicrofluidic organ-on-chip system integrated with patient-derived CRC organoids C_LIO_LIPhysical forces influence invasion, particularly in KRAS mutant tumor cells C_LIO_LIGABAergic signaling contributes to increased invasion within a dynamic TME C_LIO_LIThis model explores patient heterogeneity, TME interactions, and cancer progression C_LI GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=193 SRC="FIGDIR/small/557797v1_ufig1.gif" ALT="Figure 1"> View larger version (51K): org.highwire.dtl.DTLVardef@1b181bborg.highwire.dtl.DTLVardef@bc5b6eorg.highwire.dtl.DTLVardef@16b4fcorg.highwire.dtl.DTLVardef@c43b9f_HPS_FORMAT_FIGEXP M_FIG C_FIG

cancer biology↗

bioRxiv2019

Identifying TCDD-resistance genes via murine and rat comparative genomics and transcriptomics

The aryl hydrocarbon receptor (AHR) mediates many of the toxic effects of 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD). However, the AHR alone is insufficient to explain the widely different outcomes among organisms. Attempts to identify unknown factor(s) have been confounded by genetic variability of model organisms. Here, we evaluated three transgenic mouse lines, each expressing a different rat AHR isoform (rWT, DEL, and INS), as well as C57BL/6 and DBA/2 mice. We supplement these with whole-genome sequencing and transcriptomic analyses of the corresponding rat models: Long-Evans (L-E) and Han/Wistar (H/W) rats. These integrated multi-species genomic and transcriptomic data were used to identify genes associated with TCDD-response phenotypes.\n\nWe identified several genes that show consistent transcriptional changes in both transgenic mice and rats. Hepatic Pxdc1 was significantly repressed by TCDD in C57BL/6, rWT mice, and in L-E rat. Three genes demonstrated different AHRE-1 (full) motif occurrences within their promoter regions: Cxxc5 had fewer occurrences in H/W, as compared with L-E; Sugp1 and Hgfac (in either L-E or H/W respectively). These genes also showed different patterns of mRNA abundance across strains.\n\nThe AHR isoform explains much of the transcriptional variability: up to 50% of genes with altered mRNA abundance following TCDD exposure are associated with a single AHR isoform (30% and 10% unique to DEL and rWT respectively following 500 g/kg TCDD). Genomic and transcriptomic evidence allowed identification of genes potentially involved in phenotypic outcomes: Pxdc1 had differential mRNA abundance by phenotype; Cxxc5 had altered AHR binding sites and differential mRNA abundance.\n\nAuthor SummaryEnvironmental contaminants such as dioxins cause many toxic responses, anything from chloracne (common in humans) to death. These toxic responses are mostly regulated by the Ahr, a ligand-activated transcription factor with roles in drug metabolism and immune responses, however other contributing factors remain unclear. Studies are complicated by the underlying genetic heterogeneity of model organisms. Our team evaluated a number of mouse and rat models, including two strains of mouse, two strains of rat and three transgenic mouse lines which differ only at the Ahr locus, that present widely different sensitivities to the most potent dioxin: 2,3,7,8 tetrachlorodibenzo-p-dioxin (TCDD). We identified a number of changes to gene expression that were associated with different toxic responses. We then contrasted these findings with results from whole-genome sequencing of the H/W and L-E rats and found some key genes, such as Cxxc5 and Mafb, which might contribute to TCDD toxicity. These transcriptomic and genomic datasets will provide a valuable resource for future studies into the mechanisms of dioxin toxicities.

genomics↗

bioRxiv2019

Sex Differences in Mutational Processes

Sex differences have been observed in multiple facets of cancer epidemiology, treatment and biology, and in most cancers outside the sex organs. Efforts to link these clinical differences to specific molecular features have focused on somatic mutations within the coding regions of the genome. Here, we describe the first pan-cancer analysis of sex differences in whole genomes of 1,983 tumours of 28 subtypes from the ICGC Pan-Cancer Analysis of Whole Genomes project. We both confirm the results of exome studies, and also uncover previously undescribed sex differences. These include sex-biases in coding and non-coding cancer drivers, mutation prevalence and strikingly, in mutational signatures related to underlying mutational processes. These results underline the pervasiveness of molecular sex differences and strengthen the call for increased consideration of sex in cancer research. Sex disparities in cancer epidemiology include an increased overall cancer risk in males corresponding with higher incidence in most tumor types, even after adjusting for known risk factors1,2. Cancer mortality is also higher in males, due in part to better survival for female patients in many cancer types, including those of the colon and head & neck3. Interestingly, female colorectal cancer patients respond better to surgery4 and adjuvant chemotherapy, though this is partially due to biases in tumour location and microsatellite instability5. Similarly, premenopausal female nasopharyngeal cancer patients have improved survival regardless of tumour stage, radiation or chemotherapy regimen6. There is a growing body of evidence for sex differences in cancer genomics7-13, but their molecular origins and clinical implications remain largely elusive. Previous studies have mostly focused on protein coding regions, leaving the vast majority of the genome unexplored. We hypothesized that there are uncharacterized sex differences in the non-coding regions of the genome. Using whole genome sequencing data from the Pan-cancer Analysis of Whole Genomes (PCAWG) project14, we performed a survey of sex-biased mutations in 1,983 samples (1,213 male, 770 female) from 28 tumour subtypes, excluding those of the sex organs (Supplementary Table 1). We also excluded the X and Y chromosomes to focus on autosomal sex differences in cancers affecting both men and women, but there are known to be significant X-chromosome mutational differences between tumours arising in men and women15. Our analysis revealed sex differences in both genome-wide phenomena and in specific genes. These sex-biases occur not only at the pan-cancer level across all 1,983 samples, but also in individual tumour subtypes.

cancer biology↗

bioRxiv2018

Accurate Reference-Free Somatic Variant-Calling by Integrating Genomic, Sequencing and Population Data

The detection of somatic single nucleotide variants (SNVs) is critical in both research and clinical applications. Studies of human cancer typically use matched normal (reference) samples from a distant tissue to increase SNV prediction accuracy. This process both doubles sequencing costs and poses challenges when reference samples are not readily available, such as for many cell-lines. To address these challenges, we created S22S: an approach for the prediction of somatic mutations without need for matched reference tissue. S22S takes underlying sequence data, augments them with genomic background context and population frequency information, and classifies SNVs as somatic or non-somatic. We validated S22S using primary tumor/normal pairs from four tumor types, spanning two different sequencing technologies. S22S robustly identifies somatic SNVs, with the area under the precision recall curve reaching 0.97 in kidney clear cell carcinoma, comparable to the best tumor/normal analysis pipelines. S22S is freely available at http://labs.oicr.on.ca/Boutros-lab/software/s22s.

bioinformatics↗

bioRxiv2018

The Origins and Consequences of Localized and Global Somatic Hypermutation

Cancer is a disease of the genome, but the dramatic inter-patient variability in mutation number is poorly understood. Tumours of the same type can differ by orders of magnitude in their mutation rate. To understand potential drivers and consequences of the underlying heterogeneity in mutation rate across tumours, we evaluated both local and global measures of mutation density: both single-stranded and double-stranded DNA breaks in 2,460 tumours of 38 cancer types. We find that SCNAs in thousands of genes are associated with elevated rates of point-mutations, while similarly point-mutation patterns in dozens of genes are associated with specific patterns of DNA double-stranded breaks. These candidate drivers of mutation density are enriched for known cancer drivers, and preferentially occur early in tumour evolution, appearing clonally in all cells of a tumour. To supplement this understanding of global mutation density, we developed and validated a tool called SeqKat to identify localized \"rainstorms\" of point-mutations (kataegis). We show that rates of kataegis differ by four orders of magnitude across tumour types, with malignant lymphomas showing the highest. Tumours with TP53 mutations were 2.6-times more likely to harbour a kataegic event than those without, and 239 SCNAs were associated with elevated rates of kataegis, including loss of the tumour-suppressor CDKN2A. We identify novel subtypes of kataegic events not associated with aberrant APOBEC activity, and find that these are localized to specific cellular regions, enriched for MYC-target genes. Kataegic events were associated with patient survival in some, but not all tumour types, highlighting a combination of global and tumour-type specific effects. Taken together, we reveal a landscape of genes driving localized and tumour-specific hyper-mutation, and reveal novel mutational processes at play in specific tumour types.

cancer biology↗

bioRxiv2017

BPG: Seamless, Automated and Interactive Visualization of Scientific Data

We introduce BPG, an easy-to-use framework for generating publication-quality, highly-customizable plots in the R statistical environment. This open-source package includes novel methods of displaying high-dimensional datasets and facilitates generation of complex multi-panel figures, making it ideal for complex datasets. A web-based interactive tool allows online figure customization, from which R code can be downloaded for seamless integration with computational pipelines. BPG is available at http://labs.oicr.on.ca/boutros-lab/software/bpg

bioinformatics↗