Biology subjects

Sims, A. H.

Publications and source records attributed to Sims, A. H..

9 recordsLinked to original sources

bioRxiv2021

Toll-like receptor 2 orchestrates a potent anti-tumor response in non-small cell lung cancer

Targeting early-stage lung cancer is vital to improve overall survival. We previously identified Toll-like receptor 2 (TLR2) as a regulator of oncogene-induced senescence (OIS) and the senescence-associated secretory phenotype (SASP), both key for tumor suppression. Here, we demonstrate that TLR2 is widely expressed in human lung tumor epithelium where it correlates with improved survival and clinical regression. Using genetically engineered mouse models of lung cancer we have shown that Tlr2 is a tumor suppressor in lung cancer initiation via regulation of proliferation and the SASP. The SASP is integral in the regulation of immune surveillance of premalignant cells, and we observe impaired myeloid derived immune surveillance following Tlr2 loss. Lastly, we show that administration of a synthetic Tlr2 agonist significantly reduces preinvasive lung tumor growth. Our data highlight an unexpected tumor surveillance pathway in early-stage lung cancer with therapeutic potential. Statement of significanceLung cancer is a major cancer of unmet need. This study identifies a novel tumor suppressor mechanism in lung cancer. Not only does this highlight a potential therapeutic target for early-stage disease but also multiple secreted candidate biomarkers that could be exploited to augment lung cancer screening approaches.

cancer biology↗

bioRxiv2021

LBH is a cancer stem cell- and metastasis-driving oncogene essential for WNT stem cell function in breast cancer

Cancer stem cells (CSCs) initiate tumors, resist treatment, and seed lethal metastases; yet CSC-specific treatments are lacking. Aggressive, treatment-resistant triple-negative breast cancers (TNBC) exhibit WNT pathway activation and are CSC enriched. Here, we show that Limb-Bud- and-Heart (LBH), a WNT/{beta}-catenin target required for normal mammary stem cell self-renewal, marks poor prognosis, stem-like TNBC, and is a key controller of breast cancer stemness. LBH is specifically expressed in tumor-initiating CD44+CD24-/low breast CSCs. LBH overexpression confers stem-like, metastatic traits on both TNBC and luminal origin, non-TNBC breast cancer cells by activating stem cell transcriptional programs. Importantly, silencing LBH potently suppresses tumor initiation and metastasis in vivo, and sensitizes TNBC cells to chemotherapy. LBH knockout in the MMTV-Wnt1 breast cancer mouse model, furthermore, revealed LBH is required for WNT-driven breast CSC expansion. Our findings identify LBH as an essential CSC driver downstream of WNT, and a new molecular target for anti-cancer stem cell therapy.

cancer biology↗

bioRxiv2020

Identification of stromal genes differentially expressed in lobular breast cancer highlights role for pregnancy-associated-plasma protein-A

BackgroundInvasive lobular carcinoma (ILC) is the second most common histological subtype of breast cancer and exhibits a number of clinico-pathological characteristics that are distinct from the more common invasive ductal carcinoma (IDC). Despite these differences, ILC is treated in the same way as IDC. We set out to identify alterations in the tumor microenvironment (TME) of ILC with potential clinical significance. MethodsWe used laser-capture microdissection (LCM) to separate tumor epithelium from stroma in 23 ER+ ILC samples. Gene expression analysis was used to identify genes that are enriched in the stroma of ILC, but not IDC or normal breast. Results45 genes involved in regulation of the extracellular matrix (ECM) were enriched in the stroma of ILC, but not stroma from ER+ IDC or normal breast. Of these, 10 were expressed in cancer-associated fibroblasts (CAFs) and were increased in ILC compared to IDC in bulk gene expression datasets. PAPPA was the most enriched in the stroma compared to the tumor epithelial compartment in ILC. PAPPA encodes pregnancy-associated plasma protein-A (PAPP-A), a metalloproteinase that cleaves insulin-like binding protein-4 (IGFBP-4) increasing IGF-1 bioavailability and subsequent downstream signaling. Analysis of PAPPA and IGF1 associated genes identified a paracrine signaling pathway and active PAPP-A was shown to be secreted from primary CAFs. Comprehensive survival analysis across 3000 breast cancers identified PAPPA as a potential ILC-specific prognostic marker. ConclusionsThis is the first study to demonstrate molecular differences in the TME between ILC and IDC and identifies PAPP-A, a CAF-derived proteinase, as a potential prognostic marker.

cancer biology↗

bioRxiv2020

Targeting STAT3 signalling using stabilised sulforaphane (SFX-01) inhibits endocrine resistant stem-like cells in ER-positive breast cancer

PURPOSEEstrogen receptor (ER) positive breast cancer is frequently sensitive to endocrine therapy. Multiple mechanisms of endocrine therapy resistance have been identified, including cancer stem-like cell (CSC) activity. Sulforaphane (SFN) has previously been shown to target CSCs but its mechanism of action is unclear. Here we investigate SFX-01, a stabilised formulation of SFN, for its effects on breast CSC activity in ER+ preclinical models and to study its mechanism. EXPERIMENTAL DESIGNCSC activity was measured by mammosphere formation efficiency (MFE), aldehyde dehydrogenase (ALDH) activity, and tumor formation using patient samples and patient-derived xenograft (PDX) tumors treated with SFX-01 alone or in combination with tamoxifen or fulvestrant. Gene expression and SFN target proteins in treated samples were assessed. RESULTSSFX-01 reduced MFE of both ER+ primary and metastatic patient samples. Both tamoxifen and fulvestrant increased MFE and ALDH activity of PDX tumors, which was reversed by combination with SFX-01. SFX-01 significantly reduced tumor initiating cell frequency in secondary transplants at limiting dilution and reduced the formation of spontaneous lung micrometastases by PDX tumors in mice. Mechanistically, we establish that both tamoxifen and fulvestrant induce STAT3 phosphorylation. SFX-01 suppressed phospho-STAT3 and SFN directly bound STAT3 in patient and PDX samples. Analysis of ALDH+ cells from endocrine-resistant patient samples revealed activation of STAT3 target genes MUC1 and OSMR, which were inhibited by SFX-01 in patient samples. Increased expression of these genes after 3 months endocrine treatment of ER+ patients (n=68) predicted poor prognosis. CONCLUSIONSOur data establish the importance of STAT3 signaling in CSC-mediated resistance to endocrine therapy and the potential of SFX-01 for improving clinical outcomes in ER+ breast cancer.

cancer biology↗

bioRxiv2019

PAK4 regulates stemness and progression in endocrine resistant ER-positive metastatic breast cancer

Despite the effectiveness of endocrine therapies to treat estrogen receptor-positive (ER+) breast tumours, two thirds of patients will eventually relapse due to de novo or acquired resistance to these agents. Cancer Stem-like Cells (CSCs), a rare cell population within the tumour, accumulate after anti-estrogen treatments and are likely to contribute to their failure. Here we studied the role of p21-activated kinase 4 (PAK4) as a promising target to overcome endocrine resistance and disease progression in ER+ breast cancers. PAK4 predicts for resistance to tamoxifen and poor prognosis in 2 independent cohorts of ER+ tumours. We observed that PAK4 strongly correlates with CSC activity in metastatic patient-derived samples irrespective of breast cancer subtype. However, PAK4-driven mammosphere-forming CSC activity increases alongside progression only in ER+ metastatic samples. PAK4 activity increases in ER+ models during acquired resistance to endocrine therapies. Targeting PAK4 with either CRT PAKi, a small molecule inhibitor of PAK4, or with specific siRNAs abrogates CSC activity/self-renewal in clinical samples and endocrine-resistant cells. Together, our findings establish that PAK4 regulates stemness during disease progression and that its inhibition reverses endocrine resistance in ER+ breast cancers. HighlightsO_LIPAK4 predicts for failure of endocrine therapies and poor prognosis C_LIO_LIPAK4 drives stemness and progression in ER+ metastatic breast cancer C_LIO_LITargeting PAK4 abrogates breast CSC activity and restores sensitivity to endocrine treatments C_LIO_LITargeting PAK4 will improve outcome of ER+ breast cancer patients C_LI List of Abbreviations that appeared in abstractCancer Stem-like Cells (CSCs) p21-activated kinase 4 (PAK4) Estrogen Receptor (ER)

cancer biology↗

bioRxiv2019

The milk protein alpha-casein suppresses triple negative breast cancer stem cell activity via STAT and HIF-1alpha signalling pathways in breast cancer cells and fibroblasts

Triple negative breast cancer (TNBC) is the most lethal breast cancer subtype. Extended periods of lactation protect against breast cancer development, but the mechanisms underlying this protection are unknown. We examined the effects of the milk protein alpha-casein over expression in the triple negative MDA-MB-231 breast cancer cell line. The effects of recombinant alpha-casein added exogenously to MDA-MB-231 breast cancer cells, and immortalised human fibroblasts were also investigated. We used transcriptional reporters to understand the signalling pathways downstream of alpha-casein in breast cancer cells and these fibroblasts that were activated by breast cancer cells. To extend our findings to the clinical setting, we analysed public gene expression datasets to further understand the relevance of these signalling pathways in triple negative breast cancer cells and patient samples. Finally, we used small molecular inhibitors to target relevant pathways and highlight these as potential candidates for the treatment of TN breast cancer. High levels of alpha-casein gene expression were predictive of good prognosis across 263 TNBC patient tumour samples. Alpha-casein over expression or exogenous addition reduces cancer stem cell (CSC) activity. HIF-1alpha was identified to be a key downstream target of alpha-casein, in both breast cancer cells and activated fibroblasts, and STAT transcription factors to be upstream of HIF-1alpha. Interestingly, HIF-1alpha is regulated by STAT3 in breast cancer cells, but STAT1 is the regulator of HIF-1alpha in activated fibroblasts. In analysis of 573 TNBC patient samples, alpha-casein expression, inversely correlated to HIF-1alpha, STAT3 and STAT1. STAT1 and STAT3 inhibitors target HIF-1alpha signalling in activated fibroblasts and MDA-MB-231 breast cancer cells respectively, and also abrogate CSC activities. Our findings provide an explanation for the protective effects of lactation in TNBC. Clinical data correlates high alpha-casein expression with increased recurrence-free survival in TNBC patients. Mechanistically, alpha-casein reduces breast cancer stem cell activity in vitro, and STAT3 and STAT1 were identified as regulators of pro-tumorigenic HIF-1alpha signalling in breast cancer cells and fibroblasts respectively.

cancer biology↗

bioRxiv2018

Functionally Coherent Transcription Factor Target Networks Illuminate Control of Epithelial Remodelling and Oncogenic Notch

BackgroundCell identity is governed by gene expression, regulated by Transcription Factor (TF) binding at cis-regulatory modules. Decoding the relationship TF binding patterns and the regulation of cognate target genes is nontrivial, remaining a fundamental limitation in understanding cell decision-making mechanisms. Identification of TF physical binding that is biologically neutral is a current challenge. We studied cell identity in the context of Epithelial to Mesenchymal Transition (EMT), a cell programme fundamental for normal embryonic development that contributes to tumour progression and fibrosis.\n\nResultsWe developed the NetNC software for discovery of functionally coherent TF targets. NetNC was applied to analyse gene regulation by the EMT TFs Snail, Twist in early embryogenesis and also to modENCODE HOT regions. Predicted neutral binding accounted for 50% to [≥]80% of candidate target genes assigned from significant binding peaks. Novel gene functions and network modules were identified, including regulation of chromatin organisation and crosstalk with notch signalling. Orthologues of predicted TF targets discriminated breast cancer molecular subtypes and NetNC analysis predicted new gene functions; for example, evidencing networks that reshape Waddingtons landscape during EMT-like phenotype switching. Predicted invasion roles for SNX29, ATG3, UNK and IRX4 were validated using a tractable cell model.\n\nConclusionsWe found extensive neutral TF binding across the nine datasets examined and showed that NetNC performs well in identifying functionally coherent targets. HOT regions had comparatively high functional coherence. Our results illuminate conserved molecular networks that regulate epithelial remodelling in development and disease, with potential implications for precision medicine.

systems biology↗

bioRxiv2018

Molecular changes during extended neoadjuvant letrozole treatment of breast cancer: distinguishing acquired resistance from dormant tumours

BackgroundThe risk of recurrence for endocrine-treated breast cancer patients persists for many years or even decades following surgery and apparently successful adjuvant therapy. This period of dormancy and acquired resistance is inherently difficult to investigate, previous efforts have been limited to in vitro or in vivo approaches. In this study, sequential tumour samples from patients receiving extended neoadjuvant endocrine treatment were characterised as a novel clinical model.\n\nMethodsConsecutive tumour samples from 62 patients undergoing extended (4-45 months) neoadjuvant aromatase inhibitor, letrozole, therapy were subjected to transcriptomic and proteomic analysis, representing before ([≤]0), early-on (13-120 days) and long-term (>120 days) neoadjuvant letrozole treatment. Patients with at least a 40% initial reduction in tumour size by 4 months of treatment were included. Of these, 42 patients with no subsequent progression were classified as \"dormant\", and the remaining 20 patients as \"acquired resistant\".\n\nResultsChanges in gene expression in dormant tumours begin early and become more pronounced at later timepoints. Therapy-induced changes in resistant tumours were common features of treatment, rather than being specific to resistant phenotype. Comparative analysis of long-term treated dormant and resistant tumours highlighted changes in epigenetics pathways including DNA methylation and histone acetylation. DNA methylation marks 5-methylcytosine and 5-hydroxymethylcytosine were significantly reduced in resistant tumours compared to dormant tissues after extended letrozole treatment.\n\nConclusionsThis is the first patient-matched gene expression study investigating long-term aromatase inhibitor-induced dormancy and acquired resistance in breast cancer. Dormant tumours continue to change during treatment whereas acquired resistant tumours more closely resemble their diagnostic samples. Global loss of DNA methylation was observed in resistant tumours under extended treatment. Epigenetic alterations may lead to escape from dormancy and drive acquired resistance in a subset of patients supporting a potential role for therapy targeted at these epigenetic alterations in the management of endocrine resistant breast cancer.

cancer biology↗

bioRxiv2017

Continuous Biomarker Assessment by Exhaustive Survival Analysis

Publicly available high-throughput molecular data can enable biomarker identification and evaluation in a meta-analysis. However, a continuous biomarkers underlying distribution and/or potential confounding factors associated with outcome will inevitably vary between cohorts and is often ignored. The survivALL R package (https://CRAN.R-project.org/package=survivALL) allows researchers to generate visual and numerical comparisons of all possible points-of-separation, enabling quantitative biomarkers to be reliably evaluated within and across datasets, independent of compositional variation. Here, we demonstrate survivALLs ability to robustly and reproducibly determine an applicable level of gene expression for patient prognostic classification, in datasets of similar and dissimilar compositions. We believe survivALL represents a significant improvement over existing methodologies in stratifying patients and determining quantitative biomarker(s) cut-points for public and novel datasets.

bioinformatics↗