Biology subjects

Conway, J. R.

Publications and source records attributed to Conway, J. R..

4 recordsLinked to original sources

bioRxiv2024

Fast label-free live imaging reveals key roles of flow dynamics and CD44-HA interaction in cancer cell arrest on endothelial monolayers

Leukocyte extravasation is a key component of the innate immune response, while circulating tumor cell extravasation is a critical step in metastasis formation. Despite their importance, the mechanisms underlying leukocyte and tumor cell extravasation remain incompletely understood. Here, we developed an imaging pipeline that integrates fast, label-free live-cell imaging with deep learning-based image analysis to quantitatively track and compare the initial steps of extravasation--cell landing and arrest on an endothelial monolayer--under physiological flow conditions. We find that pancreatic ductal adenocarcinoma (PDAC) cells exhibit variable adhesion strength and flow sensitivity. Remarkably, some PDAC cells demonstrate comparable endothelial engagement as leukocytes, preferentially arresting at endothelial junctions, potentially due to increased stiffness at these sites, which leads to exposure to the underlying basal extracellular matrix. PDAC cells also tend to cluster in regions with high, heterogeneous expression of the endothelial CD44 receptor. Simulations suggest that clustering results from the combination of CD44-mediated attachment and localized flow disturbances that facilitate subsequent cell attachment. Targeting CD44 using siRNA or function-blocking antibodies, or degrading its ligand hyaluronic acid (HA), almost completely abolishes PDAC cell attachment. Overall, we demonstrate that cancer and immune cells share both common and unique features in endothelial adhesion under flow, and identify CD44 and HA as key mediators of PDAC cell arrest.

cell biology↗

bioRxiv2021

Molecular features of exceptional response to neoadjuvant anti-androgen therapy in high-risk localized prostate cancer

High-risk localized prostate cancer (HRLPC) is associated with a substantial risk of recurrence and prostate cancer-specific mortality1. Recent clinical trials have shown that intensifying anti-androgen therapies administered prior to prostatectomy can induce pathologic complete responses (pCR) or minimal residual disease (MRD) (<5 mm), together termed exceptional response, although the molecular determinants of these clinical outcomes are largely unknown. Here, we performed whole exome (WES) and whole transcriptome sequencing (RNA-seq) on pre-treatment multi-regional tumor biopsies from exceptional responders (ER: pCR and MRD patients) and non-responders (NR: pathologic T3 or lymph node positive disease) treated with intensive anti-androgen therapies prior to prostatectomy. SPOP mutation and SPOPL copy number loss were exclusively observed in ER, while TP53 mutation and PTEN copy number loss were exclusively observed in NR. These alterations were clonal in all tumor phylogenies per patient. Additionally, transcriptional programs involving androgen signaling and TGF{beta} signaling were enriched in ER and NR, respectively. The presence of these alterations in routine biopsies from patients with HRLPC may inform the prospective identification of responders to neoadjuvant anti-androgen therapies to improve clinical outcomes and stratify other patients to alternative biologically informed treatment strategies.

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↗

bioRxiv2017

UpSetR: An R Package For The Visualization Of Intersecting Sets And Their Properties

Venn and Euler diagrams are a popular yet inadequate solution for quantitative visualization of set intersections. A scalable alternative to Venn and Euler diagrams for visualizing intersecting sets and their properties is needed. We developed UpSetR, an open source R package that employs a scalable matrix-based visualization to show intersections of sets, their size, and other properties. UpSetR is available at https://cran.r-project.org/package=UpSetR and released under the MIT License. A Shiny app is available at https://gehlenborglab.shinyapps.io/upsetr/.

bioinformatics↗