Biology subjects

Roden, D. L.

Publications and source records attributed to Roden, D. L..

11 recordsLinked to original sources

bioRxiv2024

Profiling of epithelial functional states and fibroblast phenotypes in hormone therapy-naive localised prostate cancer

Localised prostate cancers (PCa) are heterogeneous and multifocal, with diverse outcomes. Current prognostic methods are epithelium-centric, overlooking the complex cellular landscape within the tumour microenvironment (TME), which remains incompletely characterised. We performed a comprehensive analysis of cancerous and adjacent-benign cores from 24 patients with hormone therapy-naive localised PCa using single-cell RNA-sequencing. By integrating copy number variation and transcriptional signatures, we classified epithelial cells across a malignant spectrum, revealing widespread molecular perturbation. We found an expansion of Club cell phenotypes, suggestive of Luminal dedifferentiation. We also performed a detailed annotation of stromal phenotypes, focusing on fibroblasts, and identified a novel peri-neural fibroblast population. Spatial transcriptomics elucidated the precise anatomical distribution of CAFs within the PCa TME. This study provides a valuable foundation for advancing our understanding of PCa pathobiology and developing a comprehensive cellular model of the disease. Statement of SignificanceOur study leverages single-cell RNA-sequencing and spatial transcriptomics to provide a comprehensive cellular annotation of hormone therapy-naive localised PCa. We reveal widespread molecular perturbations in epithelial cells and map distinct fibroblast populations to specific anatomical niches. Notably, we identify a novel peri-neural phenotype associated with nerves, which merits further functional characterisation and exploration as a potential therapeutic target.

cancer biology↗

bioRxiv2023

An experimental comparison of the Digital Spatial Profiling and Visium spatial transcriptomics technologies for cancer research

BackgroundSpatial transcriptomic technologies are powerful tools for resolving the spatial heterogeneity of gene expression in tissue samples. However, little evidence exists on relative strengths and weaknesses of the various available technologies for profiling human tumour tissue. In this study, we aimed to provide an objective assessment of two common spatial transcriptomics platforms, 10X Genomics Visium and Nanostrings GeoMx DSP. MethodThe abilities of the DSP and Visium platforms to profile transcriptomic features were compared using matching cell line and primary breast cancer tissue samples. A head-to-head comparison was conducted using data generated from matching samples and synthetic tissue references. Platform specific features were also assessed according to manufacturers recommendations to evaluate the optimal usage of the two technologies. ResultsWe identified substantial variations in assay design between the DSP and Visium assays such as transcriptomic coverage and composition of the transcripts detected. When the data was standardised according to manufacturers recommendations, the DSP platform was more sensitive in gene expression detection. However, its specificity was diminished by the presence of non-specific detection. Our results also confirmed the strength and weakness of each platform in characterising spatial transcriptomic features of tissue samples, in particular their application to hypothesis generation versus hypothesis testing. ConclusionIn this study, we share our experience on both DSP and Visium technologies as end users. We hope this can guide future users to choose the most suitable platform for their research. In addition, this dataset can be used as an important resource for the development of new analysis tools.

cancer biology↗

bioRxiv2021

DNA barcoding reveals ongoing immunoediting of clonal cancer populations during metastatic progression and in response to immunotherapy

Cancers evade the immune system in order to grow or metastasise through the process of cancer immunoediting. While immune checkpoint inhibitors have been effective for reactivating tumour immunity in some types of cancer, many other solid cancers, including breast cancer, remain largely non-responsive. Understanding the way non-responsive cancers evolve to evade immunity, what resistance pathways are activated and whether this occurs at the clonal level will improve immunotherapeutic design. We tracked cancer cell clones during the immunoediting process and determined clonal transcriptional profiles that allow immune evasion in murine mammary tumour growth in response to immunotherapy with anti-PD1 and anti-CTLA4. Clonal diversity was significantly restricted by immunotherapy treatment in both primary tumours and metastases. These findings demonstrate that immunoediting selects for pre-existing breast cancer cell populations and that immunoediting is not static, it is ongoing during metastasis and immunotherapy treatment. Isolation of immunotherapy resistant clones revealed unique and overlapping transcriptional signatures. The overlapping gene signature was associated with poor survival of basal-like breast cancer patients in two cohorts. At least one of these overlapping genes has an existing small molecule that can potentially be used to improve immunotherapy response.

cancer biology↗

bioRxiv2020

Spatial Deconvolution of HER2-positive Breast Tumors Reveals Novel Intercellular Relationships

In the past decades, transcriptomic studies have revolutionized cancer treatment and diagnosis. However, tumor sequencing strategies typically result in loss of spatial information, critical to understand cell interactions and their functional relevance. To address this, we investigate spatial gene expression in HER2-positive breast tumors using Spatial Transcriptomics technology. We show that expression-based clustering enables data-driven tumor annotation and assessment of intra-and interpatient heterogeneity; from which we discover shared gene signatures for immune and tumor processes. We integrate and spatially map tumor-associated types from single cell data to find: segregated epithelial cells, interactions between B and T-cells and myeloid cells, co-localization of macrophage and T-cell subsets. A model is constructed to infer presence of tertiary lymphoid structures, applicable across tissue types and technical platforms. Taken together, we combine different data modalities to define novel interactions between tumor-infiltrating cells in breast cancer and provide tools generalizing across tissues and diseases.

cancer biology↗

bioRxiv2020

Cryopreservation of human cancers conserves tumour heterogeneity for single-cell multi-omics analysis

BackgroundHigh throughput single-cell RNA sequencing (scRNA-Seq) has emerged as a powerful tool for exploring cellular heterogeneity amongst complex human cancers. scRNA-Seq studies using fresh human surgical tissue is logistically difficult, precludes histopathological triage of samples and limits the ability to perform batch processing. This hinderance can often introduce technical biases when integrating patient datasets and increase experimental costs. Although tissue preservation methods have been previously explored to address such issues, it is yet to be examined on complex human tissues, such as solid cancers, and on high throughput scRNA-Seq platforms. ResultsWe show that the viable cryopreservation of human cancers provides high quality single-cell transcriptomes using the Chromium 10X platform. We sequenced a total of [~]120,000 cells from fresh and cryopreserved replicates across three breast cancers, two prostate cancers and a cutaneous melanoma. Importantly, tumour heterogeneity identified from fresh tissues was largely conserved in cryopreserved replicates. We show that sequencing of single cells prepared from cryopreserved tissue fragments or from cryopreserved cell suspensions is comparable to sequenced cells prepared from fresh tissue, with cryopreserved cell suspensions displaying higher correlations with fresh tissue in gene expression. We then show that cryopreservation had minimal impacts on results of downstream analyses such as biological pathway enrichment. Further, we demonstrate the advantage of cryopreserving whole-cells for immunophenotyping methods such as CITE-Seq, which is impossible using other preservation methods such as single nuclei-sequencing. ConclusionsOur study guides new experimental designs for tissue biobanking for future clinical single-cell RNA sequencing studies.

cancer biology↗

bioRxiv2020

Single-cell analysis reveals diverse stromal subsets associated with immune evasion in triple-negative breast cancer

The tumour stroma regulates nearly all stages of carcinogenesis. Stromal heterogeneity in human triple-negative breast cancers (TNBCs) remains poorly understood, limiting the development of stromal-targeted therapies. Single cell RNA-sequencing of five TNBCs revealed two cancer-associated fibroblast (CAF) and two perivascular-like (PVL) subpopulations. CAFs clustered into two states, the first with features of myofibroblasts and the second characterised by high expression of growth factors and immunomodulatory molecules. PVL cells clustered into two states consistent with a differentiated and immature phenotype. We showed that these stromal states have distinct morphologies, spatial relationships and functional properties in regulating the extracellular matrix. Using cell-signalling predictions, we provide evidence that stromal-immune crosstalk acts via a diverse array of immunoregulatory molecules. Importantly, the investigation of gene signatures from inflammatory-CAFs and differentiated-PVL cells in independent TNBC patient cohorts revealed strong associations with cytotoxic T-cell dysfunction and exclusion, respectively. Such insights present promising candidates to further investigate for new therapeutic strategies in the treatment of TNBCs.

cancer biology↗

bioRxiv2020

ID4 represses myoepithelial differentiation of mammary stem cells through its interaction with HEB

Differentiation of stem cells embedded within the mammary epithelium is orchestrated by lineage-specifying transcription factors. Unlike the well-defined luminal hierarchy, dissection of the basal lineage has been hindered by a lack of specific markers. Inhibitor of Differentiation 4 (ID4) is a basally-restricted helix-loop-helix (HLH) transcription factor essential for mammary development. Here we show that ID4 is highly expressed in basal stem cells and decreases during myoepithelial differentiation. By integrating transcriptomic, proteomic, and ChIP-sequencing data, we reveal that ID4 is required to suppress myoepithelial gene expression and cell fate. We identify the bHLH protein HEB as a direct binding partner of ID4, and describe a previously-unknown role for this regulator in mammary development. HEB binds to E-boxes in regulatory elements of developmental genes, negatively regulated by ID4, involved in extracellular matrix synthesis and cytoskeletal contraction. Together our findings support a model whereby ID4 binds to HEB and blocks it from promoting myoepithelial specialisation. These new insights expand our current understanding into control of myoepithelial differentiation and mammary gland morphogenesis.

developmental biology↗

bioRxiv2019

Targeting the Id1-Kif11-Aurka axis in triple negative breast cancer using combination therapy

Evidence points to breast cancer following a hierarchical model, with Cancer Stem Cells (CSCs) driving critical phenotypes of the bulk tumor. Chemoresistant CSCs are not an abstract concept but have clinical consequences as they drive relapse and ultimately lead to mortality in patients, making it imperative to understand how these subpopulations of cells survive. Our previous work (1-2) has demonstrated that the bHLH transcription factor, Inhibitor of Differentiation 1 (Id1) and its closely related family member Id3, have an important role in maintaining the CSC phenotype in the Triple Negative breast cancer (TNBC) subtype. A genetic screen conducted to further elucidate the molecular mechanism underlying the Id (Id1/3) mediated CSC phenotypes in TNBC revealed critical cell cycle genes such as Kif11 and Aurka as putative Id targets. We take this work forward by investigating how alteration in Kif11 and Aurka via Id proteins promotes the CSC phenotype in TNBC. Cells lacking Id are poised in a state of G0/G1 arrest from which they can re-enter the cell cycle. Intriguingly, depletion of Kif11 and Aurka independently did not phenocopy the G0/G1 arrest observed in Id knockdown (Id KD) cells. We have further explored the hypothesis that we can deplete the chemo resistant Id expressing CSC population by combining chemotherapy with targeted therapy using existing small molecule inhibitors (against Id target Kif11) to more effectively debulk the entire tumor. This work opens up exciting new possibilities of targeting Id targets like Kif11, in the TNBC subtype which is currently refractory to chemotherapy.

cancer biology↗

bioRxiv2019

Single-cell RNAseq uncovers involution mimicry as an aberrant development pathway during breast cancer metastasis

Both luminal and basal breast cancer subtypes originate in the mammary luminal progenitor cell compartment. Basal breast cancer is associated with younger age, early relapse, and high mortality rate. Here we used unbiased droplet-based single-cell RNAseq to elucidate the cellular basis of tumour progression during the specification of the basal breast cancer subtype from the luminal progenitor population. Basal-like cancer cells resembled the alveolar lineage that is specified upon pregnancy and showed molecular features indicative of an interaction with the tumour microenvironment (TME) including epithelial-to-mesenchymal transition (EMT), hypoxia, lactation and involution. Involution signatures in luminal breast cancer tumours with alveolar lineage features were associated with worse prognosis and features of basal breast cancer. Our high-resolution molecular characterisation of the tumour ecosystem also revealed a highly interactive cell-cell network reminiscent of an involution process. This involution mimicry involves malignant education of cancer-associated fibroblasts and myeloid cell recruitment to support tissue remodelling and sustained inflammation. Our study shows how luminal breast cancer acquires an aberrant post-lactation developmental program that involves both cancer cells and cells from the TME, to shift molecular subtype and promote tumour progression, with potential to explain the increased risk and poor prognosis of breast cancer associated to childbirth.

cancer biology↗

bioRxiv2018

Id proteins promote a cancer stem cell phenotype in triple negative breast cancer via Robo1-dependent c-Myc activation

Breast cancers display phenotypic and functional heterogeneity and several lines of evidence support the existence of cancer stem cells (CSCs) in certain breast cancers, a minor population of cells capable of tumor initiation and metastatic dissemination. Identifying factors that regulate the CSC phenotype is therefore important for developing strategies to treat metastatic disease. The Inhibitor of Differentiation Protein 1 (Id1) and its closely related family member Inhibitor of Differentiation 3 (Id3) (collectively termed Id) are expressed by a diversity of stem cells and are required for metastatic dissemination in experimental models of breast cancer. In this study, we show that ID1 is expressed in rare neoplastic cells within ER-negative breast cancers. To address the function of Id1 expressing cells within tumors, we developed two independent murine models of Triple Negative Breast Cancer (TNBC) in which a genetic reporter permitted the prospective isolation of Id1+ cells. Id1+ cells are enriched for self-renewal in tumorsphere assays in vitro and for tumor initiation in vivo. Conversely, depletion of Id1 and Id3 in the 4T1 murine model of TNBC demonstrates that Id1/3 are required for cell proliferation and self-renewal in vitro, as well as primary tumor growth and metastatic colonization of the lung in vivo. Using combined bioinformatic analysis, we have defined a novel mechanism of Id protein function via negative regulation of the Roundabout Axon Guidance Receptor Homolog 1 (Robo1) leading to activation of a Myc transcriptional programme.

cancer biology↗

bioRxiv2018

Single cell transcriptomics reveals molecular subtype and functional heterogeneity in models of breast cancer

Breast cancer has long been classified into a number of molecular subtypes that predict prognosis and therefore influence clinical treatment decisions. Cellular heterogeneity is also evident in breast cancers and plays a key role in the development, evolution and metastatic progression of many cancers. How clinical heterogeneity relates to cellular heterogeneity is poorly understood, so we approached this question using single cell gene expression analysis of well established in vitro and in vivo models of disease.\n\nTo explore the cellular heterogeneity in breast cancer we first examined a panel of genes that define the PAM50 classifier of molecular subtype. Five breast cancer cell line models (MCF7, BT474, SKBR3, MDA-MB-231, and MDA-MB-468) were selected as representatives of the intrinsic molecular subtypes (luminal A and B, basal-like, and Her2-enriched). Single cell multiplex RT-PCR was used to isolate and quantify the gene expression of single cells from each of these models, and the PAM50 classifier applied. Using this approach, we identified heterogeneity of intrinsic subtypes at single-cell level, indicating that cells with different subtypes exist within a cell line. Using the Chromium 10X system, this study was extended into thousands of cells from the MCF7 cell-line and an ER+ patient derived xenograft (PDX) model and again identified significant intra-tumour heterogeneity of molecular subtype.\n\nEstrogen Receptor (ER) is an important driver and therapeutic target in many breast cancers. It is heterogeneously expressed in a proportion of clinical cases but the significance of this to ER activity is unknown. Significant heterogeneity in the transcriptional activation of ER regulated genes was observed within tumours. This differential activation of the ER cistrome aligned with expression of two known transcriptional co-regulatory factors of ER (FOXA1 and PGR).\n\nTo examine the degree of heterogeneity for other important phenotypic traits, we used an unsupervised clustering approach to identify cellular sub-populations with diverse cancer associated transcriptional properties, such as: proliferation; hypoxia; and treatment resistance. In particular, we show that we can identify two distinct sub-populations of cells that may have denovo resistance to endocrine therapies in a treatment naive PDX model of ER+ breast cancer. One of these consists of cells with a non-proliferative transcriptional phenotype that is enriched for transcriptional properties of ERBB2 tumours. The other is heavily enriched for components of the primary cilia. Gene regulatory networks were used to identify transcription factor regulons that are active in each cell, leading us to identify potential transcriptional drivers (such as E2F7, MYB and RFX3) of the cilia associated endocrine resistant cells. This rare subpopulation of cells also has a highly heterogenous mix of intrinsic subtypes highlighting a potential role of intra-tumour subtype heterogeneity in endocrine resistance and metastatic potential.\n\nOverall, These results suggest a high degree of cellular heterogeneity within breast cancer models, even cell lines, that can be functionally dissected into sub-populations of cells with transcriptional phenotypes of potential clinical relevance.

cancer biology↗