Biology subjects

Brenton, J. D.

Publications and source records attributed to Brenton, J. D..

At least 19 recordsLinked to original sources

bioRxiv2026

Single-cell mapping of the fallopian tube reveals a genomically unstable secretory cell state enriched in carriers of germline BRCA1/2 mutations

Carriers of germline BRCA1 or BRCA2 alterations have a substantially increased lifetime risk of high-grade serous ovarian carcinoma (HGSOC), which originates from the secretory cells of the fallopian tube. However, comparative multi-omic analyses of bulk fallopian tube tissue from BRCA1/2 carriers and the general population have, to date, revealed only limited differences. New molecular biomarkers of early malignant transformation in the FT are needed to enable non-surgical cancer interception in high-risk individuals through window-of-opportunity trials prior to risk-reducing surgery. We performed a comprehensive single-cell, multi-regional analysis of fallopian tubes from 34 women, including 15 carriers of germline BRCA1/2 alterations. Using a metacell-based approach applied to single-cell transcriptomic data, we identify both established and previously unrecognised cellular populations, and characterise phenotypic variation associated with menopausal status, menstrual cycle phase, hormonal contraception use, and anatomical region of the fallopian tube. Menopause was associated with depletion of ciliated cells, whilst both secretory (SEC) and ciliated epithelial cells (CEC) shifted to a glandular phenotype in the luteal phase. Previous hormonal contraception usage had lasting effects including depletion of CD163-positive tissue resident macrophages and progesterone-specific increase of MHC-II expression in SECs. Metacell analysis further identified distinct subpopulations of SECs, most frequently in BRCA1/2 carriers, characterised by high TP53 expression and markedly elevated histone levels. This phenotype is consistent with replication stress, cell-cycle arrest, and activation of innate immune signalling pathways. Protein-level validation in matched samples showed enrichment of cells with increased {gamma}H2AX expression and persistent 53BP1 foci in BRCA1/2 carriers. Together our data supports the role of BRCA1/2 in maintaining genomic integrity and a BRCA1/2 haploinsufficient phenotype characterised by increased replication stress in the fallopian tube epithelium. Our findings provide evidence for distinct immune responses in users of hormonal contraception and demonstrate early events in malignant transformation. They establish potential biomarkers in microscopically normal FT and a framework for measurement of cancer risk with the goal of enabling molecularly informed cancer interception in high-risk individuals.

cancer biology↗

bioRxiv2026

scUnique: Measuring Ongoing Chromosomal Instability

Chromosomal instability is a hallmark of cancer that can drive tumour heterogeneity and treatment resistance. However, scalable methods to measure the dynamics of chromosomal instability are lacking and thus historic genomic scars can be hard to distinguish from markers of currently active mutational processes. Here, we introduce scUnique, a novel approach to measure ongoing chromosomal instability from single-cell whole genome sequencing (scWGS) data. scUnique performs phylogeny-aware joint segmentation to refine single-cell copy number profiles and identifies recent copy number aberrations as statistically supported changes on the leaves of the inferred phylogenetic tree. This yields a per-cell measure of ongoing chromosomal instability at genome-wide resolution. We validate scUnique in (i) a comprehensive benchmarking study, (ii) in CRISPR-Cas-based experimental systems, and (iii) single-cell derived clones of a well-characterised ovarian model. We show that scUnique distinguishes ongoing HRD and FBI mutational processes. These results show that scUnique provides quantitative, scalable, genome-level information about ongoing chromosomal instability, not available in previous studies relying on bulk DNA-sequencing or single-cell imaging. In the future, these improved measurements could refine the understanding of mechanisms of chromosomal instability and lead to dynamic biomarkers for improved treatment decisions.

cancer biology↗

bioRxiv2026

WNT-driven chromosomal instability as a biomarker for PORCN inhibition

Targeting Porcupine (PORCN), a key regulator of the WNT-signalling pathway, has shown therapeutic potential in multiple cancers. Despite strong target engagement and acceptable safety profiles through human phase I clinical trials, low phase II efficacy has stalled further clinical development. Given that aberrant WNT signalling can drive tumorigenesis by inducing chromosomal instability (CIN), we hypothesised that genomic CIN signatures might serve as a predictive biomarker to help improve response rates. Using a controlled in vitro model and single-cell whole-genome sequencing, we demonstrate that acute WNT-activation directly induces three distinct types of CIN: whole genome duplication, replication stress, and impaired homologous recombination. We translated these observations into a composite CIN signature biomarker that significantly correlated with both genetic dependency and pharmacological inhibition of PORCN across 195 and 24 cell lines, respectively. Through a large-scale meta-analysis of patient-derived and cell line xenografts, we established that this composite CIN signature biomarker quantitatively predicts in vivo PORCN inhibitor sensitivity (R=-0.71, p<0.002). By applying an optimised biomarker threshold, refined through modelling of human patient data, to the The Cancer Genome Atlas dataset, we successfully retrospectively modelled previous trial results and identified gastroesophageal cancers as a high-prevalence (36.6%) indication for future development. We validated this strategy in a mouse clinical trial of gastric and esophageal xenografts, where biomarker-guided stratification achieved an objective response rate of 60% and significantly decreased risk of progression (HR=0.21, p=0.0345). These data establish an actionable, trail-ready framework for further PORCN inhibitor clinical development.

cancer biology↗

bioRxiv2024

Coordinated protein modules define DNA damage responses to carboplatin at single cell resolution in human ovarian carcinoma models

Tubo-ovarian high-grade serous carcinoma (HGSC) is the most lethal gynecological malignancy and frequently responds to platinum-based chemotherapy because of common genetic and somatic impairment of DNA damage repair (DDR) pathways. The mechanisms of clinical platinum resistance are diverse and poorly molecularly defined. Consequently, there are no biomarkers or medicines that improve patient outcomes. Herein we use single cell mass cytometry (CyTOF) to systematically evaluate the phosphorylation and abundance of proteins known to participate in the DNA damage response (DDR). Single cell analyses of highly characterized HGSC cell lines that phenocopy human patients show that cells with comparable levels of intranuclear platinum, a proxy for carboplatin uptake, undergo different cell fates. Unsupervised analyses revealed a continuum of DDR responses. Decompositional methods were used to identify eight distinct protein modules of carboplatin resistance and sensitivity at single cell resolution. CyTOF profiling of primary and secondary platinum-resistance patient models shows that a complex DDR sensitivity module is strongly associated with response, suggesting it as a potential tool to clinically characterize complex drug resistance phenotypes.

cancer biology↗

bioRxiv2024

Primary culture of high grade serous ovarian cancer cells, selection and derivation of three cell lines

Cell line models for high grade serous ovarian cancer (HGSOC) are limited in number and are poorly clinically annotated. Consequently, existing models often fail to recapitulate common features of HGSOC, inhibiting mechanistic and therapeutic discovery. We generated and characterised three spontaneously immortalized continuous HGSOC cell lines named CIOV1, CIOV2, and CIOV3 and confirmed that each cell line retained the genomic and pathologic characteristics of its parental tumour. We show that subclonal cell populations present at initiation, expanded and contracted during the culturing process before converging on a stable immortalized line. These lines are new valuable models to study acquired chemoresistance of HGSOC.

cancer biology↗

bioRxiv2023

Heme oxygenase-1 expressing omental macrophages as a therapeutic target in ovarian high grade serous carcinoma

Ovarian high grade serous carcinoma (HGSC) remains a disease of poor prognosis that is unresponsive to current immune checkpoint inhibitors. Although PI3K pathway alterations are common in HGSC, attempts to target this pathway have been unsuccessful. We hypothesised aberrant PI3K pathway activation may alter the HGSC immune microenvironment and present a novel targeting strategy. We used both murine models and HGSC patient samples to study the impact of loss of Pten, a negative regulator of PI3K pathway signalling. We identified populations of resident macrophages specifically in Pten null omental tumours. These macrophages derive from peritoneal fluid macrophages and have a unique gene expression programme, marked by high levels of HMOX1 expression, the gene for the enzyme heme oxygenase-1. Targeting resident peritoneal macrophages prevents appearance of HMOX1hi macrophages and in doing so reduces tumour growth. Furthermore, direct inhibition of HMOX1 extends survival in vivo. HMOX1hi macrophages with corresponding gene expression programmes are also identified in human HGSC tumours and their presence correlates with activated tumoural PI3K pathway/mTOR signalling and poor overall survival in HGSC patients. In contrast, tumours with low number of HMOX1hi macrophages are marked by increased adaptive immune response gene expression. Our data suggest that HMOX1hi macrophages represent a potential therapeutic target and biomarker for poor prognosis HGSC.

cancer biology↗

bioRxiv2023

Predicting response to cytotoxic chemotherapy

Cytotoxic chemotherapies have been a crucial part of cancer treatment for over 40 years. While their primary target is cancer cells, they can also harm normal cells, resulting in dose-limiting toxicity. Most chemotherapies were approved before the advent of precision biomarkers, as such, many patients experience severe toxic side effects without any benefit. To address this challenge, we have developed three precision biomarkers to predict response to platins, taxanes, and anthracyclines. Based on chromosomal instability (CIN) signatures, these biomarkers can be computed from a single genomic test. For platins and taxanes, we used CIN signatures related to impaired homologous recombination, while for anthracyclines, we discovered a CIN signature representing micronuclei induction which predicts resistance. In a clinical study involving 41 high-grade serous ovarian cancers, patients predicted to be sensitive by these biomarkers showed significantly prolonged progression-free survival. To further validate the effectiveness of the taxane and anthracycline predictors, we conducted a retrospective randomised control study involving 182 ovarian and 219 breast cancer patients. Patients predicted as resistant showed increased risk of time to treatment failure compared to standard of care, hazard ratios of 1.73 (95%CI=0.98-3.07) for taxane in ovarian, 3.67 (95%CI=2.12-6.34) for taxane in breast, and 1.93 (95%CI=1.22-3.04) for doxorubicin in ovarian. We also found that liquid biopsies can be used to make these predictions in up to 30% of ovarian cancer patients. Our findings highlight the clinical value of CIN signatures in predicting treatment response to various chemotherapies across multiple different types of cancer. The ability to quantify multiple CIN signature biomarkers using a single genomic test offers a unified approach to guide treatment decisions for cytotoxic chemotherapies. Ultimately, this has the potential to transform the current one-size-fits-all chemotherapy approach into a more precise and tailored form of medicine.

cancer biology↗

bioRxiv2022

Molecular landscape and functional characterization of centrosome amplification in ovarian cancer

High grade serous ovarian carcinoma (HGSOC) is characterised by poor outcome and extreme chromosome instability (CIN). Therapies targeting centrosome amplification (CA), a key mediator of chromosome missegregation and CIN, may have significant clinical utility in HGSOC. However, the prevalence of CA in HGSOC, its relationship to genomic biomarkers of CIN and its potential impact on therapeutic response have not been defined. Using high-throughput multi-regional microscopy on 287 clinical HGSOC tumour tissues and 73 ovarian cancer cell lines, we show that CA through centriole overduplication is a highly recurrent and heterogeneous feature of HGSOC and is strongly associated with CIN and genome subclonality. Cell-based studies showed that high prevalence CA is phenocopied in ovarian cancer cell lines, and that high CA is associated with increased multi-treatment resistance; most notably to paclitaxel which is the most common treatment used in HGSOC. CA in HGSOC may therefore present a potential driver of tumour evolution and a powerful biomarker for response to standard-of-care treatment.

cancer biology↗

bioRxiv2022

High-grade serous ovarian carcinoma organoids as models of chromosomal instability

High-grade serous ovarian carcinoma (HGSOC) is the most genomically complex cancer, characterised by ubiquitous TP53 mutation, profound chromosomal instability and heterogeneity. The mutational processes driving chromosomal instability in HGSOC can be distinguished by specific copy number signatures. To develop clinically relevant models of these mutational processes we derived 15 continuous HGSOC patient-derived organoids (PDOs). We carried out detailed bulk transcriptomic, bulk genomic, single cell genomic, and drug sensitivity characterisation of the organoids. We show that PDOs comprise communities of different clonal populations and represent models of different causes of chromosomal instability including homologous recombination deficiency, chromothripsis, tandem-duplicator phenotype and whole genome duplication. We also show that these PDOs can be used as exploratory tools to study transcriptional effects of copy number alterations as well as compound-sensitivity tests. In summary, HGSOC PDO cultures provide a genomic tool for studies of specific mutational processes and precision therapeutics.

cancer biology↗

bioRxiv2022

LGR5 targeting molecules as therapeutic agents for multiple cancer types

Leucine-rich repeat-containing G-protein receptor 5 (LGR5) has been characterised as a stem cell and cancer stem cell marker. Previous analyses of LGR5 transcript levels indicate high level expression discriminates malignancies such as colorectal cancer (CRC) and pre-B acute lymphoblastic leukaemia (pre-B ALL) from healthy tissues suggesting LGR5 protein expression may provide a molecular handle for prognosis and treatment. We have developed highly specific, high affinity antibodies to the extracellular domain of human LGR5 (-LGR5) that detect high LGR5 protein levels in colorectal cancer (CRC), hepatocellular carcinoma (HCC), and pre-B ALL. In contrast, there is low to undetectable levels of LGR5 protein in normal colon and rectal epithelia, liver, ovarian tissues, brain and immune cell types. LGR5 is rapidly internalised from the plasma membrane and trafficked to intracellular vesicular compartments including lysosomes. Treatment of high LGR5-expressing CRC and pre-B ALL cancer cell lines with an antibody-drug conjugate version of -LGR5 (-LGR5-ADC) lead to effective cell killing at nanomolar concentrations. Interventional treatment of pre-B ALL tumours with -LGR5-ADC in vivo led to rapid tumour attrition. We further demonstrated the therapeutic utility of humanised -LGR5 by using the corresponding scFv fragment for the generation of -LGR5 chimeric antigen receptors (CARs) and a Bispecific T cell Engager (BiTE). -LGR5-CAR-NK cells were effective at killing LGR5-expressing cells while -LGR5/-CD3 BiTEs induce T cell activation and killing of NALM6 cells by cytotoxic CD8+ T cells. Taken together, this study establishes -LGR5-based therapeutic modalities that effectively discriminate and target CRC, HCC and pre-B ALL tumour cells. One Sentence SummaryWe generated novel antibodies against the cancer cell marker LGR5, validated diagnostic use in prioritizing specific cancer types for targeting, and developed antibody-based therapeutics.

cell biology↗

bioRxiv2022

Longitudinal monitoring of disease burden and response using ctDNA from dried blood spots in xenograft models

Whole genome sequencing (WGS) of circulating tumour DNA (ctDNA) is now a clinically important biomarker for predicting therapy response, disease burden and disease progression. However, the translation of ctDNA monitoring into vital pre-clinical PDX models has not been possible owing to low circulating blood volumes in small rodents. Here, we describe the longitudinal detection and monitoring of ctDNA from minute volumes of blood in PDX mice. We developed a xenograft Tumour Fraction (xTF) metric using shallow WGS of dried blood spots (DBS), and demonstrate its application to quantify disease burden, monitor treatment response and predict disease outcome in a pre-clinical study of PDX mice. Further, we show how our DBS-based ctDNA assay can be used to detect gene-specific copy number changes and examine the copy number landscape over time. Use of sequential DBS ctDNA assays will transform future trial designs in both mice and patients.

cancer biology↗

bioRxiv2021

Absolute copy number fitting from shallow whole genome sequencing data

Low-coverage or shallow whole genome sequencing (sWGS) approaches can efficiently detect somatic copy number aberrations (SCNAs) at low cost. This is clinically important for many cancers, in particular cancers with severe chromosomal instability (CIN) that frequently lack actionable point mutations and are characterised by poor disease outcome. Absolute copy number (ACN), measured in DNA copies per cancer cell, is required for meaningful comparisons between copy number states, but is challenging to estimate and in practice often requires manual curation. Using a total of 60 cancer cell lines, 148 patient-derived xenograft (PDX) and 142 clinical tissue samples, we evaluate the performance of available tools for obtaining ACN from sWGS. We provide a validated and refined tool called Rascal (relative to absolute copy number scaling) that provides improved fitting algorithms and enables interactive visualisation of copy number profiles. These approaches are highly applicable to both pre-clinical and translational research studies on SCNA-driven cancers and provide more robust ACN fits from sWGS data than currently available tools.

bioinformatics↗

bioRxiv2020

Somatic chromosomal number alterations affecting driver genes inform in-vitro and clinical drug response in high-grade serous ovarian cancer

The genomic complexity and heterogeneity of high-grade serous ovarian cancer (HGSOC) has hampered the realisation of successful therapies and effective personalised treatment is an unmet clinical need. Here we show that primary HGSOC spheroid models can be used to predict drug response and use them to demonstrate that somatic copy number alterations (SCNAs) in frequently amplified HGSOC cancer genes significantly correlate with gene expression and drug response. These genes are often located in areas of the genome with frequent clonal SCNAs. MYC chromosomal copy number is associated with ex-vivo and clinical response to paclitaxel and ex-vivo response to mTORC1/2 inhibition. Activation of the mTOR survival pathway in the context to MYC-amplified HGSOC is mostly due to increased prevalence of SCNAs in genes from the PI3K pathway. These results suggest that SCNAs encompassing driver genes could be used to inform therapeutic response in the context of clinical trials testing personalised medicines.

cancer biology↗

bioRxiv2019

Detection of ctDNA from dried blood spots after DNA size selection

Recent advances in the research and clinical applications of circulating tumour DNA (ctDNA) is limited by practical considerations of sample collection. Whole genome sequencing (WGS) is increasingly used for analysis of ctDNA, identifying copy-number alterations, fragment size patterns, and other genomic features. We hypothesised that low-depth WGS data may be generated from minute amounts of cell-free DNA, and that fragment-size selection may be effective to remove contaminating genomic DNA (gDNA) from small volumes of blood. There are practical advantages to using dried blood spots as these are easier to collect, facilitate serial sampling, and support novel study designs in prospective human studies, animal models and expand the utilisation of archival samples by the removal of gDNA in small volumes. We therefore developed a protocol for the isolation and analysis of cell-free DNA from dried blood spots. Analysing a dried blood spot of 50L frozen whole blood from a patient with melanoma, we identified ctDNA based on tumour-specific somatic copy-number alterations, and found a fragment size profile similar to that observed in plasma DNA processed by traditional methods. We extended this approach to detect tumour-derived cell-free DNA in a dried blood spot from a mouse xenograft model and were able to identify ctDNA from the originally grafted ascites. Together, our data suggests that ctDNA can be detected and monitored in dried blood spots. This will enable new approaches for sample collection from patients and in vivo models.

cancer biology↗

bioRxiv2019

Computed Tomography Measures of Inter-site tumor Heterogeneity for Classifying Outcomes in High-Grade Serous Ovarian Carcinoma: a Retrospective Study

AbstractO_ST_ABSBackgroundC_ST_ABSHigh grade serous ovarian carcinoma shows marked intra-tumoral heterogeneity which is associated with decreased survival and resistance to platinum-based chemotherapy. Pre-treatment quantification of spatial tumor heterogeneity by multiple tissue sampling is not clinically feasible. Using standard-of-care CT imaging to non-invasively quantify heterogeneity could have high clinical utility and would be highly cost-effective. Texture analysis measures local variations in computed tomography (CT) image intensity. Haralick texture methods are typically used to capture the heterogeneity of entire lesions; however, this neglects the possible presence of texture habitats within the lesion, and the differences between metastatic sites. The primary aim of this study was to develop texture analysis of intra-site and inter-site spatial heterogeneity from standard-of-care CT images and to correlate these measures with clinical and genomic features in patients with HGSOC. Methods and findingsWe analyzed the data from a retrospective cohort of 84 patients with HGSOC consisting of 46 patients from Memorial Sloan Kettering Cancer Center (MSKCC) and 38 non-MSKCC cases selected from The Cancer Imaging Archive (TCIA). Inclusion criteria consisted of FIGO stage II-IV HGSOC, attempted primary cytoreductive surgery, intravenous contrast-enhanced CT of abdomen and pelvis performed prior to surgery and availability of molecular tumor data analysed as per the Cancer Genome Atlas (TCGA) Research Network ovarian cancer project. Manual segmentation and image analysis was performed on 463 metastatic tumor sites from 84 patients. In the MSKCC cohort the median number of tumor sites was 7 (interquartile range 5-9) and 4 (interquartile range 3-4) in the TCIA patients. Sub-regions were produced within each tumor site by grouping voxels with similar Haralick texture using the Kernel K-means method. We derived statistical measures of intra- and inter-site tumor heterogeneity (IISTH) including cluster sites entropy (cSE), cluster sites standard deviation (cluDev) and cluster sites dissimilarity (cluDiss) from sub-regions identified within and between individual tumor sites. Unsupervised clustering was used to group patient IISTH measures into low, medium, high, and ultra-high heterogeneity clusters from each cohort. The IISTH measure cluDiss was an independent predictor of progression-free survival (PFS) in multivariable analysis in both datasets (MSKCC hazard ratio [HR] 1.04, 95% CI 1.01-1.06, P = 0.002; TCIA HR 1.05, 95% CI 1.00-1.10, P = 0.049). Low and medium IISTH clusters were associated with longer PFS in multivariable analysis (MSKCC HR 2.94, 90% CI 1.29-6.70, P = 0.009, TCIA HR 5.94, 95% CI 1.05-33.6, P = 0.044). IISTH measures were robust to differences in the CT imaging systems. Average Haralick textures contrast (TCIA HR 1.08, 95% CI 1.01-1.10, P = 0.019) and homogeneity (TCIA HR 1.09, 95% CI 1.02-1.16, P = 0.008) were associated with PFS in mutivariate analysis only in the TCIA dataset. All other average Haralick textures and total tumor volume were not associated with PFS in either dataset. ConclusionsTexture measures of intra- and inter-site tumor heterogeneity from standard of care CT images are correlated with shorter PFS in HGSOC patients. These quantitative methods are independent of the CT imaging system and can thus be applied in clinical practice. The methodology proposed here enables the non-invasive quantification of intra-tumoral heterogeneity and disease stratification for future experimental medicine studies and clinical trials, particularly in cases where total tumour volume and averaged textures have low predictive power. Author summaryO_ST_ABSWhy was this study done?C_ST_ABSO_LITumor heterogeneity is a feature of many solid malignancies including ovarian cancer. C_LIO_LIRecent genomic research suggests that intra-site tumor heterogeneity (heterogeneity within a single tumor site) and inter-site tumor heterogeneity (heterogeneity between different metastatic sites in the same patient) correlate with clinical outcome in HGSOC. C_LI What did the researchers do and find?O_LIWe developed quantitative and non-invasive image-analysis based measures for predicting outcome in HGSOC patients by combining image-based information from within and between multiple tumor sites. C_LIO_LIUsing datasets from two sources, we demonstrate that these image-based tumor heterogeneity measures predict progression free survival in patients with HGSOC. C_LI What do these findings mean?O_LINon-invasive measures of CT image heterogeneity may predict outcomes in HGSOC patients. C_LIO_LIWider application of these CT image heterogeneity measures could prove useful for stratifying patients to different therapies given that total tumour volume and averaged textures have low predictive power. C_LI

bioinformatics↗

bioRxiv2018

frenchFISH: Poisson models for quantifying DNA copy-number from fluorescence in situ hybridisation of tissue sections

Chromosomal aberration and DNA copy number change are robust hallmarks of cancer. Imaging of spots generated using fluorescence in situ hybridisation (FISH) of locus specific probes is routinely used to detect copy number changes in tumour nuclei. However, it often does not perform well on solid tumour tissue sections, where partially represented or overlapping nuclei are common. To overcome these challenges, we have developed a computational approach called FrenchFISH, which comprises a nuclear volume correction method coupled with two types of Poisson models: either a Poisson model for improved manual spot counting without the need for control probes; or a homogenous Poisson Point Process model for automated spot counting. We benchmarked the performance of FrenchFISH against previous approaches in a controlled simulation scenario and exemplify its use in 12 ovarian cancer FFPE-tissue sections, for which we assess copy number alterations in three loci (c-Myc, hTERC and SE7). We show that FrenchFISH outperforms standard spot counting approaches and that the automated spot counting is significantly faster than manual without loss of performance. FrenchFISH is a general approach that can be used to enhance clinical diagnosis on sections of any tissue.\n\nAuthor summaryCancer genomes can look very chaotic, because cancer cells are unable to fully repair errors in DNA replication during cell division. While a healthy genome has two copies of every chromosome, in a cancer genome some pieces can be lost completely and others can appear in 50 copies. To diagnose cancers and to decide on the right therapeutic strategy for a patient, it can be very important to know how many copies of a particular piece of DNA exist in a cell. The standard technique used in the clinic to assess DNA copy number is called FISH, short for fluorescence in situ hybridisation. This technique uses fluorescent probes that bind to a DNA piece of interest and show up as glowing spots in a microscopic image. Counting the spots in an image is a labour-and time-intensive process that is generally done by well-trained experts. Here we present a statistical approach to automatically count FISH spots, which outperforms previously proposed methods, and has the potential to substantially speed up clinical diagnostics.

bioinformatics↗

bioRxiv2018

Unraveling Tumor-Immune Heterogeneity in Advanced Ovarian Cancer Uncovers Immunogenic Effect of Chemotherapy

In metastatic cancer, the role of heterogeneity at the tumor-immune microenvironment, its molecular underpinnings and clinical relevance remain largely unexplored. To understand tumor-immune dynamics at baseline and upon chemotherapy treatment, we performed unbiased pathway and cell type-specific immunogenomics analysis of treatment-naive (38 samples from 8 patients) and paired chemotherapy treated (80 paired samples from 40 patients) high-grade serous ovarian cancer (HGSOC) samples. Whole transcriptome analysis and image-based quantification of T cells from treatment-naive tumors revealed ubiquitous variability in immune signaling and distinct immune microenvironments co-existing within the same individuals and within tumor deposits at diagnosis. To systematically explore cell type composition of the tumor microenvironment using bulk mRNA, we derived consensus immune and stromal cell gene signatures by intersecting state-of-the-art deconvolution methods, providing improved accuracy and sensitivity when compared to HGSOC immunostaining and leukocyte methylation data sets. Cell-type deconvolution and pathway analyses revealed that Myc and Wnt signaling associate with immune cell exclusion in untreated HGSOC. To evaluate the effect of chemotherapy on the intrinsic tumor-immune heterogeneity, we compared site-matched and site-unmatched tumors before and after neoadjuvant chemotherapy. Transcriptomic and T-cell receptor sequencing analyses showed that site-matched samples had increased cytotoxic immune activation and oligoclonal expansion of T cells after chemotherapy, which was not seen in site-unmatched samples where heterogeneity could not be accounted for. These results demonstrate that the tumor-immune interface in advanced HGSOC is intrinsically heterogeneous, and thus requires site-specific analysis to reliably unmask the impact of therapy on the tumor-immune microenvironment.

cancer biology↗

bioRxiv2017

Copy-number signatures and mutational processes in ovarian carcinoma

Tumours with profound copy-number aberration elude molecular stratification due to their genomic complexity. By representing this complexity as a mixture of copy-number signatures, we provide molecular explanations for differing clinical outcomes. Here we present a method for copy-number signature identification, deriving eight signatures in 117 shallow whole-genome sequenced high-grade serous ovarian cancers (HGSOC), which validated on independent cohorts of 95 deep whole-genome sequenced, and 402 SNP array-profiled cases. Three copy-number signatures predicted longer overall survival, while the others predicted poorer outcome. We found evidence for the mutational processes giving rise to copy-number change for six of the eight signatures via correlations with other genomic features. Our results provide insights into the pathogenesis of HGSOC by uncovering multiple mutational processes that shape genomes following TP53 mutation. Importantly, our work shows that most HGSOC have a mixture of mutational processes suggesting that targeting a single mutator phenotype may be therapeutically suboptimal.

cancer biology↗