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Oncology: State-of-the-Art Research in UK

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A special issue of Cancers (ISSN 2072-6694).

Deadline for manuscript submissions: closed (30 November 2022) | Viewed by 26425

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Prof. Dr. Kwok-Leung Cheung

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School of Medicine, University of Nottingham, Royal Derby Hospital Centre, Derby DE22 3DT, UK
Interests: breast cancer; breast surgery; non-operative therapy; endocrine therapy; geriatric oncology
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Among many other countries, the UK is at the forefront of cancer research. There are commitments from stakeholders from academic institutions, health service organisations, industries, funding bodies and public and patient advocacy groups to support research into all types of cancer. We have a unique National Health Service, which emphasises the needs of everyone and is free at the point of delivery. It believes that integrating research into the health service organisation will improve outcomes and transform cancer care.

In this Special Issue, we aim to showcase state-of-the-art research in oncology in the UK. We invite submissions looking at all kinds of research covering all cancer types and stages, from basic laboratory research to translational and clinical research, including cohort studies, randomised controlled trials and epidemiological studies. Narrated reviews describing the history and significant contributions of cancer research in the UK are also welcomed.

Prof. Dr. Kwok-Leung Cheung
Guest Editor

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Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Cancers is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2900 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

cancer
oncology
research
United Kingdom
UK

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Oncology: State-of-the-Art Research in UK, 2nd Edition in Cancers (3 articles)

Published Papers (9 papers)

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Research

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11 pages, 2878 KiB

Open AccessArticle

Female Sex but Not Oestrogen Receptor Expression Predicts Survival in Advanced Gastroesophageal Adenocarcinoma—A Post-hoc Analysis of the GO2 Trial

by Mark A. Baxter, Lindsay C. Spender, Shaun Walsh, Susan Bray, Gemma Skinner, Sharon King, Peter S. Hall, Matthew J. Seymour, Russell D. Petty and on behalf of the GO2 Investigators

Cancers 2023, 15(9), 2591; https://doi.org/10.3390/cancers15092591 - 3 May 2023

Cited by 1 | Viewed by 1963

Abstract

Gastroesophageal adenocarcinoma is a disease of older adults that is associated with a very poor prognosis. It is less common and has better outcomes in females. The reason for this is unknown but may relate to signalling via the main oestrogen receptors (ER) α and β. In this study, we sought to investigate this using the GO2 clinical trial patient cohort. GO2 recruited older and/or frail patients with advanced gastroesophageal cancer. Immunohistochemistry was performed on tumour samples from 194 patients. The median age of the population was 76 years (range 52–90), and 25.3% were female. Only one (0.5%) tumour sample was positive for ERα, compared to 70.6% for ERβ expression. There was no survival impact according to ERβ expression level. Female sex and younger age were associated with lower ERβ expression. Female sex was also associated with improved overall survival. To our knowledge, this is the largest study worldwide of ER expression in a cohort of patients with advanced gastroesophageal adenocarcinoma. It is also unique, given the age of the population. We have demonstrated that female sex is associated with better survival outcomes with palliative chemotherapy but that this does not appear to be related to ER IHC expression. The differing ER expression according to age supports the concept of a different disease biology with age. Full article

(This article belongs to the Special Issue Oncology: State-of-the-Art Research in UK)

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25 pages, 6700 KiB

Open AccessArticle

High Throughput Fluorescence-Based In Vitro Experimental Platform for the Identification of Effective Therapies to Overcome Tumour Microenvironment-Mediated Drug Resistance in AML

by Yoana Arroyo-Berdugo, Maria Sendino, David Greaves, Natalia Nojszewska, Orest Idilli, Chi Wai So, Lucy Di Silvio, Ruby Quartey-Papafio, Farzin Farzaneh, Jose Antonio Rodriguez and Yolanda Calle

Cancers 2023, 15(7), 1988; https://doi.org/10.3390/cancers15071988 - 27 Mar 2023

Cited by 3 | Viewed by 2871

Abstract

The interactions between Acute Myeloid Leukaemia (AML) leukemic stem cells and the bone marrow (BM) microenvironment play a critical role during AML progression and resistance to drug treatments. Therefore, the identification of novel therapies requires drug-screening methods using in vitro co-culture models that closely recreate the cytoprotective BM setting. We have developed a new fluorescence-based in vitro co-culture system scalable to high throughput for measuring the concomitant effect of drugs on AML cells and the cytoprotective BM microenvironment. eGFP-expressing AML cells are co-cultured in direct contact with mCherry-expressing BM stromal cells for the accurate assessment of proliferation, viability, and signaling in both cell types. This model identified several efficacious compounds that overcome BM stroma-mediated drug resistance against daunorubicin, including the chromosome region maintenance 1 (CRM1/XPO1) inhibitor KPT-330. In silico analysis of genes co-expressed with CRM1, combined with in vitro experiments using our new methodology, also indicates that the combination of KPT-330 with the AURKA pharmacological inhibitor alisertib circumvents the cytoprotection of AML cells mediated by the BM stroma. This new experimental model and analysis provide a more precise screening method for developing improved therapeutics targeting AML cells within the cytoprotective BM microenvironment. Full article

(This article belongs to the Special Issue Oncology: State-of-the-Art Research in UK)

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16 pages, 1986 KiB

Open AccessArticle

Subcellular Epithelial HMGB1 Expression Is Associated with Colorectal Neoplastic Progression, Male Sex, Mismatch Repair Protein Expression, Lymph Node Positivity, and an ‘Immune Cold’ Phenotype Associated with Poor Survival

by Ross J. Porter, Graeme I. Murray, Sandra Hapca, Andrew Hay, Stephanie G. Craig, Matthew P. Humphries, Jacqueline A. James, Manuel Salto-Tellez, Daniel P. Brice, Susan H. Berry and Mairi H. McLean

Cancers 2023, 15(6), 1865; https://doi.org/10.3390/cancers15061865 - 20 Mar 2023

Cited by 2 | Viewed by 2054

Abstract

New treatment targets are needed for colorectal cancer (CRC). We define expression of High Mobility Group Box 1 (HMGB1) protein throughout colorectal neoplastic progression and examine the biological consequences of aberrant expression. HMGB1 is a ubiquitously expressed nuclear protein that shuttles to the cytoplasm under cellular stress. HMGB1 impacts cellular responses, acting as a cytokine when secreted. A total of 846 human tissue samples were retrieved; 6242 immunohistochemically stained sections were reviewed. Subcellular epithelial HMGB1 expression was assessed in a CRC Tissue Microarray (n = 650), normal colonic epithelium (n = 75), adenomatous polyps (n = 52), and CRC polyps (CaP, n = 69). Stromal lymphocyte phenotype was assessed in the CRC microarray and a subgroup of CaP. Normal colonic epithelium has strong nuclear and absent cytoplasmic HMGB1. With progression to CRC, there is an emergence of strong cytoplasmic HMGB1 (p < 0.001), pronounced at the leading cancer edge within CaP (p < 0.001), and reduction in nuclear HMGB1 (p < 0.001). In CRC, absent nuclear HMGB1 is associated with mismatch repair proteins (p = 0.001). Stronger cytoplasmic HMGB1 is associated with lymph node positivity (p < 0.001) and male sex (p = 0.009). Stronger nuclear (p = 0.011) and cytoplasmic (p = 0.002) HMGB1 is associated with greater CD4⁺ T-cell density, stronger nuclear HMGB1 is associated with greater FOXP3⁺ (p < 0.001) and ICOS⁺ (p = 0.018) lymphocyte density, and stronger nuclear HMGB1 is associated with reduced CD8⁺ T-cell density (p = 0.022). HMGB1 does not directly impact survival but is associated with an ‘immune cold’ tumour microenvironment which is associated with poor survival (p < 0.001). HMGB1 may represent a new treatment target for CRC. Full article

(This article belongs to the Special Issue Oncology: State-of-the-Art Research in UK)

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9 pages, 8150 KiB

Open AccessArticle

Lymphocyte Classification from Hoechst Stained Slides with Deep Learning

by Jessica Cooper, In Hwa Um, Ognjen Arandjelović and David J. Harrison

Cancers 2022, 14(23), 5957; https://doi.org/10.3390/cancers14235957 - 1 Dec 2022

Cited by 2 | Viewed by 2684

Abstract

Multiplex immunofluorescence and immunohistochemistry benefit patients by allowing cancer pathologists to identify proteins expressed on the surface of cells. This enables cell classification, better understanding of the tumour microenvironment, and more accurate diagnoses, prognoses, and tailored immunotherapy based on the immune status of individual patients. However, these techniques are expensive. They are time consuming processes which require complex staining and imaging techniques by expert technicians. Hoechst staining is far cheaper and easier to perform, but is not typically used as it binds to DNA rather than to the proteins targeted by immunofluorescence techniques. In this work we show that through the use of deep learning it is possible to identify an immune cell subtype without immunofluorescence. We train a deep convolutional neural network to identify cells expressing the T lymphocyte marker CD3 from Hoechst 33342 stained tissue only. CD3 expressing cells are often used in key prognostic metrics such as assessment of immune cell infiltration, and by identifying them without the need for costly immunofluorescence, we present a promising new approach to cheaper prediction and improvement of patient outcomes. We also show that by using deep learning interpretability techniques, we can gain insight into the previously unknown morphological features which make this possible. Full article

(This article belongs to the Special Issue Oncology: State-of-the-Art Research in UK)

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18 pages, 5275 KiB

Open AccessArticle

Integrative, In Silico and Comparative Analysis of Breast Cancer Secretome Highlights Invasive-Ductal-Carcinoma-Grade Progression Biomarkers

by Stavroula L. Kastora, Georgios Kounidas, Valerie Speirs and Yazan A. Masannat

Cancers 2022, 14(16), 3854; https://doi.org/10.3390/cancers14163854 - 9 Aug 2022

Cited by 2 | Viewed by 2656

Abstract

Globally, BC is the most frequently diagnosed cancer in women. The aim of this study was to identify novel secreted biomarkers that may indicate progression to high-grade BC malignancies and therefore predict metastatic potential. A total of 33 studies of breast cancer and 78 of other malignancies were screened via a systematic review for eligibility, yielding 26 datasets, 8 breast cancer secretome datasets, and 18 of other cancers that were included in the comparative secretome analysis. Sequential bioinformatic analysis using online resources enabled the identification of enriched GO_terms, overlapping clusters, and pathway reconstruction. This study identified putative predictors of IDC grade progression and their association with breast cancer patient mortality outcomes, namely, HSPG2, ACTG1, and LAMA5 as biomarkers of in silico pathway prediction, offering a putative approach by which the abovementioned proteins may mediate their effects, enabling disease progression. This study also identified ITGB1, FBN1, and THBS1 as putative pan-cancer detection biomarkers. The present study highlights novel, putative secretome biomarkers that may provide insight into the tumor biology and could inform clinical decision making in the context of IDC management in a non-invasive manner. Full article

(This article belongs to the Special Issue Oncology: State-of-the-Art Research in UK)

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18 pages, 2132 KiB

Open AccessArticle

The Epigenetic Regulatory Protein CBX2 Promotes mTORC1 Signalling and Inhibits DREAM Complex Activity to Drive Breast Cancer Cell Growth

by Lucie J. Bilton, Chloe Warren, Rebecca M. Humphries, Shannon Kalsi, Ella Waters, Thomas Francis, Wojtek Dobrowinski, Pedro Beltran-Alvarez and Mark A. Wade

Cancers 2022, 14(14), 3491; https://doi.org/10.3390/cancers14143491 - 18 Jul 2022

Cited by 12 | Viewed by 2884

Abstract

Chromobox 2 (CBX2) is a chromatin-binding component of polycomb repressive complex 1, which causes gene silencing. CBX2 expression is elevated in triple-negative breast cancer (TNBC), for which there are few therapeutic options. Here, we aimed to investigate the functional role of CBX2 in TNBC. CBX2 knockdown in TNBC models reduced cell numbers, which was rescued by ectopic expression of wild-type CBX2 but not a chromatin binding-deficient mutant. Blocking CBX2 chromatin interactions using the inhibitor SW2_152F also reduced cell growth, suggesting CBX2 chromatin binding is crucial for TNBC progression. RNA sequencing and gene set enrichment analysis of CBX2-depleted cells identified downregulation of oncogenic signalling pathways, including mTORC1 and E2F signalling. Subsequent analysis identified that CBX2 represses the expression of mTORC1 inhibitors and the tumour suppressor RBL2. RBL2 repression, in turn, inhibits DREAM complex activity. The DREAM complex inhibits E2F signalling, causing cell senescence; therefore, inhibition of the DREAM complex via CBX2 may be a key oncogenic driver. We observed similar effects in oestrogen receptor-positive breast cancer, and analysis of patient datasets suggested CBX2 inhibits RBL2 activity in other cancer types. Therapeutic inhibition of CBX2 could therefore repress mTORC1 activation and promote DREAM complex-mediated senescence in TNBC and could have similar effects in other cancer types. Full article

(This article belongs to the Special Issue Oncology: State-of-the-Art Research in UK)

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22 pages, 2154 KiB

Open AccessArticle

Habitat Imaging of Tumors Enables High Confidence Sub-Regional Assessment of Response to Therapy

by Paul David Tar, Neil A. Thacker, Muhammad Babur, Grazyna Lipowska-Bhalla, Susan Cheung, Ross A. Little, Kaye J. Williams and James P. B. O’Connor

Cancers 2022, 14(9), 2159; https://doi.org/10.3390/cancers14092159 - 26 Apr 2022

Cited by 6 | Viewed by 2370

Abstract

Imaging biomarkers are used in therapy development to identify and quantify therapeutic response. In oncology, use of MRI, PET and other imaging methods can be complicated by spatially complex and heterogeneous tumor micro-environments, non-Gaussian data and small sample sizes. Linear Poisson Modelling (LPM) enables analysis of complex data that is quantitative and can operate in small data domains. We performed experiments in 5 mouse models to evaluate the ability of LPM to identify responding tumor habitats across a range of radiation and targeted drug therapies. We tested if LPM could identify differential biological response rates. We calculated the theoretical sample size constraints for applying LPM to new data. We then performed a co-clinical trial using small data to test if LPM could detect multiple therapeutics with both improved power and reduced animal numbers compared to conventional t-test approaches. Our data showed that LPM greatly increased the amount of information extracted from diffusion-weighted imaging, compared to cohort t-tests. LPM distinguished biological response rates between Calu6 tumors treated with 3 different therapies and between Calu6 tumors and 4 other xenograft models treated with radiotherapy. A simulated co-clinical trial using real data detected high precision per-tumor treatment effects in as few as 3 mice per cohort, with p-values as low as 1 in 10,000. These findings provide a route to simultaneously improve the information derived from preclinical imaging while reducing and refining the use of animals in cancer research. Full article

(This article belongs to the Special Issue Oncology: State-of-the-Art Research in UK)

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17 pages, 1434 KiB

Open AccessArticle

A Model to Detect Significant Prostate Cancer Integrating Urinary Peptide and Extracellular Vesicle RNA Data

by Shea P. O’Connell, Maria Frantzi, Agnieszka Latosinska, Martyn Webb, William Mullen, Martin Pejchinovski, Mark Salji, Harald Mischak, Colin S. Cooper, Jeremy Clark, Daniel S. Brewer and on behalf of The Movember GAP1 Urine Biomarker Consortium

Cancers 2022, 14(8), 1995; https://doi.org/10.3390/cancers14081995 - 14 Apr 2022

Cited by 9 | Viewed by 2895

Abstract

There is a clinical need to improve assessment of biopsy-naïve patients for the presence of clinically significant prostate cancer (PCa). In this study, we investigated whether the robust integration of expression data from urinary extracellular vesicle RNA (EV-RNA) with urine proteomic metabolites can accurately predict PCa biopsy outcome. Urine samples collected within the Movember GAP1 Urine Biomarker study (n = 192) were analysed by both mass spectrometry-based urine-proteomics and NanoString gene-expression analysis (167 gene-probes). Cross-validated LASSO penalised regression and Random Forests identified a combination of clinical and urinary biomarkers for predictive modelling of significant disease (Gleason Score (Gs) ≥ 3 + 4). Four predictive models were developed: ‘MassSpec’ (CE-MS proteomics), ‘EV-RNA’, and ‘SoC’ (standard of care) clinical data models, alongside a fully integrated omics-model, deemed ‘ExoSpec’. ExoSpec (incorporating four gene transcripts, six peptides, and two clinical variables) is the best model for predicting Gs ≥ 3 + 4 at initial biopsy (AUC = 0.83, 95% CI: 0.77–0.88) and is superior to a standard of care (SoC) model utilising clinical data alone (AUC = 0.71, p < 0.001, 1000 resamples). As the ExoSpec Risk Score increases, the likelihood of higher-grade PCa on biopsy is significantly greater (OR = 2.8, 95% CI: 2.1–3.7). The decision curve analyses reveals that ExoSpec provides a net benefit over SoC and could reduce unnecessary biopsies by 30%. Full article

(This article belongs to the Special Issue Oncology: State-of-the-Art Research in UK)

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Review

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19 pages, 4386 KiB

Open AccessReview

Organ-on-a-Chip and Microfluidic Platforms for Oncology in the UK

by Joanne Nolan, Oliver M. T. Pearce, Hazel R. C. Screen, Martin M. Knight and Stefaan W. Verbruggen

Cancers 2023, 15(3), 635; https://doi.org/10.3390/cancers15030635 - 19 Jan 2023

Cited by 16 | Viewed by 4772

Abstract

Organ-on-chip systems are capable of replicating complex tissue structures and physiological phenomena. The fine control of biochemical and biomechanical cues within these microphysiological systems provides opportunities for cancer researchers to build complex models of the tumour microenvironment. Interest in applying organ chips to investigate mechanisms such as metastatsis and to test therapeutics has grown rapidly, and this review draws together the published research using these microfluidic platforms to study cancer. We focus on both in-house systems and commercial platforms being used in the UK for fundamental discovery science and therapeutics testing. We cover the wide variety of cancers being investigated, ranging from common carcinomas to rare sarcomas, as well as secondary cancers. We also cover the broad sweep of different matrix microenvironments, physiological mechanical stimuli and immunological effects being replicated in these models. We examine microfluidic models specifically, rather than organoids or complex tissue or cell co-cultures, which have been reviewed elsewhere. However, there is increasing interest in incorporating organoids, spheroids and other tissue cultures into microfluidic organ chips and this overlap is included. Our review includes a commentary on cancer organ-chip models being developed and used in the UK, including work conducted by members of the UK Organ-on-a-Chip Technologies Network. We conclude with a reflection on the likely future of this rapidly expanding field of oncological research. Full article

(This article belongs to the Special Issue Oncology: State-of-the-Art Research in UK)

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