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Cancers
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Oncology: State-of-the-Art Research in UK, 2nd Edition
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Oncology: State-of-the-Art Research in UK, 2nd Edition

A special issue of Cancers (ISSN 2072-6694). This special issue belongs to the section "Cancer Therapy".

Deadline for manuscript submissions: 31 March 2025 | Viewed by 3369

Special Issue Editors

Prof. Dr. Kwok-Leung Cheung

E-Mail Website
Guest Editor
School of Medicine, University of Nottingham, Derby DE22 3DT, UK
Interests: breast cancer; breast surgery; non-operative therapy; endocrine therapy; geriatric oncology
Special Issues, Collections and Topics in MDPI journals
Dr. Ruth Parks

E-Mail Website
Guest Editor
School of Medicine, University of Nottingham, Derby DE22 3DT, UK
Interests: breast cancer; geriatric oncology; breast surgery

Special Issue Information

Dear Colleagues,

This Special Issue is the second edition of the previous one, Oncology: State-of-the-Art Research in UK. (https://www.mdpi.com/journal/cancers/special_issues/Oncology_UK).

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 the research of 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 welcome.  

Prof. Dr. Kwok-Leung Cheung
Dr. Ruth Parks
Guest Editors

Manuscript Submission Information

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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Related Special Issue

Published Papers (3 papers)

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Research

18 pages, 3537 KiB  
Article
Characterization of Breast Cancer Intra-Tumor Heterogeneity Using Artificial Intelligence
by Ayat G. Lashen, Noorul Wahab, Michael Toss, Islam Miligy, Suzan Ghanaam, Shorouk Makhlouf, Nehal Atallah, Asmaa Ibrahim, Mostafa Jahanifar, Wenqi Lu, Simon Graham, Mohsin Bilal, Abhir Bhalerao, Nigel P. Mongan, Fayyaz Minhas, Shan E Ahmed Raza, Elena Provenzano, David Snead, Nasir Rajpoot and Emad A. Rakha
Cancers 2024, 16(22), 3849; https://doi.org/10.3390/cancers16223849 - 16 Nov 2024
Viewed by 472
Abstract
Intra-tumor heterogeneity (ITH) is a fundamental characteristic of breast cancer (BC), influencing tumor progression, prognosis, and therapeutic responses. However, the complexity of ITH in BC makes its accurate characterization challenging. This study leverages deep learning (DL) techniques to comprehensively evaluate ITH in early-stage [...] Read more.
Intra-tumor heterogeneity (ITH) is a fundamental characteristic of breast cancer (BC), influencing tumor progression, prognosis, and therapeutic responses. However, the complexity of ITH in BC makes its accurate characterization challenging. This study leverages deep learning (DL) techniques to comprehensively evaluate ITH in early-stage luminal BC and provide a nuanced understanding of its impact on tumor behavior and patient outcomes. A large cohort (n = 2561) of early-stage luminal BC was evaluated using whole slide images (WSIs) of hematoxylin and eosin-stained slides of excision specimens. Morphological features of both the tumor and stromal components were meticulously annotated by a panel of pathologists in a subset of cases. A DL model was applied to develop an algorithm to assess the degree of heterogeneity of various morphological features per individual case utilizing defined patches. The results of extracted features were used to generate an overall heterogeneity score that was correlated with the clinicopathological features and outcome. Overall, 162 features were quantified and a significant positive correlation between these features was identified. Specifically, there was a significant association between a high degree of intra-tumor heterogeneity and larger tumor size, poorly differentiated tumors, highly proliferative tumors, tumors of no special type (NST), and those with low estrogen receptor (ER) expression. When all features are considered in combination, a high overall heterogeneity score was significantly associated with parameters characteristic of aggressive tumor behavior, and it was an independent predictor of poor patient outcome. In conclusion, DL models can be used to accurately decipher the complexity of ITH and provide extra information for outcome prediction. Full article
(This article belongs to the Special Issue Oncology: State-of-the-Art Research in UK, 2nd Edition)
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11 pages, 444 KiB  
Article
Ethnicity and Socioeconomic Disparities in Clinical Trial Participation for Ovarian Cancer: A Retrospective Observational Study in London
by Karim H. El-Shakankery, Joanna Kefas, Kieran Palmer, Andrew Houston, Uma Mukherjee, Kangbo Gao, Weiteen Tan, Shanthini M. Crusz, Michael J. Flynn, Jonathan A. Ledermann, Michelle Lockley, Mary McCormack, Nicola MacDonald, Shibani Nicum, Michael John Devlin and Rowan E. Miller
Cancers 2024, 16(21), 3590; https://doi.org/10.3390/cancers16213590 - 24 Oct 2024
Viewed by 734
Abstract
Background: Ethnic and socioeconomic disparities in cancer outcomes are exacerbated by clinical trial underrepresentation. This study aims to identify inequalities in ethnicity and socioeconomic features among ovarian cancer clinical trial participants in two London cancer centres. Methods: All ovarian cancer patients treated between [...] Read more.
Background: Ethnic and socioeconomic disparities in cancer outcomes are exacerbated by clinical trial underrepresentation. This study aims to identify inequalities in ethnicity and socioeconomic features among ovarian cancer clinical trial participants in two London cancer centres. Methods: All ovarian cancer patients treated between 2017 and 2022 were included. Patients participating in clinical trials were classified as the trial population (TP); the remainder were considered the non-trial population (NTP). Data on disease characteristics and sociodemographic features, including ethnicity and Indices of Multiple Deprivation (IMD) deciles, were accessed from electronic patient records. Results: Of the 892 patients, 212 (24%) were enrolled in trials: 87 in Phase II, 103 in Phase III, and 21 in prospective, non-investigational medicinal product trials. The TP were more likely to be of White ethnicity (72.6% vs. 57.5%; p < 0.001), younger (mean age 58 vs. 60; p = 0.003), living in less deprived areas (most deprived tercile: 21.2% vs. 34.0%; p = 0.004), and English-speaking (95.8% vs. 90.9%; p = 0.041). In the multivariate analysis, White ethnicity (p < 0.0001), age (p = 0.003), IMD decile (p = 0.007), and interpreter requirement (p = 0.037) were independent predictors of trial participation. Conclusions: Ethnic and socioeconomic inequalities affect trial participation, potentially worsening health disparities in ovarian cancer patients. Strategies to overcome trial recruitment barriers for underserved groups are needed to improve the equity of care. Full article
(This article belongs to the Special Issue Oncology: State-of-the-Art Research in UK, 2nd Edition)
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25 pages, 12375 KiB  
Article
Anogenital HPV-Related Cancers in Women: Investigating Trends and Sociodemographic Risk Factors
by Micol Lupi, Sofia Tsokani, Ann-Marie Howell, Mosab Ahmed, Danielle Brogden, Paris Tekkis, Christos Kontovounisios and Sarah Mills
Cancers 2024, 16(12), 2177; https://doi.org/10.3390/cancers16122177 - 8 Jun 2024
Viewed by 1661
Abstract
The incidences of anogenital HPV-related cancers in women are on the rise; this is especially true for anal cancer. Medical societies are now beginning to recommend anal cancer screening in certain high-risk populations, including high-risk women with a history of genital dysplasia. The [...] Read more.
The incidences of anogenital HPV-related cancers in women are on the rise; this is especially true for anal cancer. Medical societies are now beginning to recommend anal cancer screening in certain high-risk populations, including high-risk women with a history of genital dysplasia. The aim of this study is to investigate national anogenital HPV cancer trends as well as the role of demographics, deprivation, and ethnicity on anogenital cancer incidence in England, in an attempt to better understand this cohort of women which is increasingly affected by anogenital HPV-related disease. Demographic data from the Clinical Outcomes and Services Dataset (COSD) were extracted for all patients diagnosed with anal, cervical, vulval and vaginal cancer in England between 2014 and 2020. Outcomes included age, ethnicity, deprivation status and staging. An age over 55 years, non-white ethnicity and high deprivation are significant risk factors for late cancer staging, as per logistic regression. In 2019, the incidences of anal and vulval cancer in white women aged 55–74 years surpassed that of cervical cancer. More needs to be done to educate women on HPV-related disease and their lifetime risk of these conditions. Full article
(This article belongs to the Special Issue Oncology: State-of-the-Art Research in UK, 2nd Edition)
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