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Cancers
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Application of Novel Technologies in the Early Detection of Gynaecological...
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Application of Novel Technologies in the Early Detection of Gynaecological Cancers

A special issue of Cancers (ISSN 2072-6694). This special issue belongs to the section "Methods and Technologies Development".

Deadline for manuscript submissions: closed (30 September 2023) | Viewed by 7094

Special Issue Editors

Dr. Sarah Joanne Bowden

E-Mail Website
Guest Editor
Imperial College Faculty of Medicine, London, UK
Interests: genetics and epigenetics in cervical cancer; endometrial cancer
Prof. Dr. Maria Kyrgiou

E-Mail Website
Guest Editor
1. Department of Metabolism, Digestion and Reproduction, Imperial College London, London SW7 2AZ, UK
2. Imperial College Healthcare NHS Trust, London W2 1NY, UK
Interests: gynaecological cancers; human pappilomavirus (HPV); HPV vaccination; cervical cancer; cervical intraepithelian neoplasia (CIN); cervical screening; ovarian cancer; endometrial cancer; microbiome; epigenetics; organoids
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

We are pleased to invite you to this special issue of cancers on novel technologies for early detection of Gynaecological Cancers. As the number of -omics based technologies are rapidly expanding, molecular discoveries have the potential to offer novel insights into cancer and potentially early detection.

While HPV-based screening programmes exist for cervical cancer, molecular technologies could lead to enhanced detection of high-grade disease and implementation in low-resource settings. The incidence of uterine cancer is increasing, and novel technologies may allow for early detection and guide management of endometrial hyperplasia. Meanwhile the majority of ovarian cancer is detected at a late stage, and accurate biomarkers of early disease are urgently needed. Here we welcome submissions on the applications of novel technologies, especially molecular techniques, for early detection of all gynaecological cancers.

In this Special Issue, original research articles and reviews are welcome. Research areas may include (but are not limited to) the following:

  • Epigenetics
  • Genetics
  • Biomarkers
  • Ultrasound
  • Microbiome
  • mRNA

We look forward to receiving your contributions

Dr. Sarah Joanne Bowden
Prof. Dr. Maria Kyrgiou
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 short 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

  • epigenetics 
  • genetics 
  • biomarkers 
  • ultrasound 
  • microbiome 
  • mRNA

Published Papers (3 papers)

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Research

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18 pages, 434 KiB  
Article
Breast Cancer Detection Using Convoluted Features and Ensemble Machine Learning Algorithm
by Muhammad Umer, Mahum Naveed, Fadwa Alrowais, Abid Ishaq, Abdullah Al Hejaili, Shtwai Alsubai, Ala’ Abdulmajid Eshmawi, Abdullah Mohamed and Imran Ashraf
Cancers 2022, 14(23), 6015; https://0-doi-org.brum.beds.ac.uk/10.3390/cancers14236015 - 06 Dec 2022
Cited by 18 | Viewed by 2274
Abstract
Breast cancer is a common cause of female mortality in developing countries. Screening and early diagnosis can play an important role in the prevention and treatment of these cancers. This study proposes an ensemble learning-based voting classifier that combines the logistic regression and [...] Read more.
Breast cancer is a common cause of female mortality in developing countries. Screening and early diagnosis can play an important role in the prevention and treatment of these cancers. This study proposes an ensemble learning-based voting classifier that combines the logistic regression and stochastic gradient descent classifier with deep convoluted features for the accurate detection of cancerous patients. Deep convoluted features are extracted from the microscopic features and fed to the ensemble voting classifier. This idea provides an optimized framework that accurately classifies malignant and benign tumors with improved accuracy. Results obtained using the voting classifier with convoluted features demonstrate that the highest classification accuracy of 100% is achieved. The proposed approach revealed the accuracy enhancement in comparison with the state-of-the-art approaches. Full article
(This article belongs to the Special Issue Application of Novel Technologies in the Early Detection of Gynaecological Cancers)
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15 pages, 2833 KiB  
Article
Influences of Gastrointestinal Microbiota Dysbiosis on Serum Proinflammatory Markers in Epithelial Ovarian Cancer Development and Progression
by Diane E. Mahoney, Prabhakar Chalise, Faith Rahman and Janet D. Pierce
Cancers 2022, 14(12), 3022; https://0-doi-org.brum.beds.ac.uk/10.3390/cancers14123022 - 20 Jun 2022
Cited by 3 | Viewed by 2136
Abstract
GI microbiota has been implicated in producing the inflammatory tumor microenvironment of several cancers. Women with ovarian cancer often report GI-related symptoms at diagnosis although minimal is known about the possible GI bacteria that may trigger pro-tumorigenic immune responses in early EOC. The [...] Read more.
GI microbiota has been implicated in producing the inflammatory tumor microenvironment of several cancers. Women with ovarian cancer often report GI-related symptoms at diagnosis although minimal is known about the possible GI bacteria that may trigger pro-tumorigenic immune responses in early EOC. The purpose of this study was to investigate the influences of GI microbiota dysbiosis on serum inflammatory markers during EOC utilizing a rodent model. This experimental design consisted of C57BL/6 mice randomly assigned to either the microbiota dysbiosis group (n = 6) or control group (n = 5). The CD7BL/6 mice assigned to the microbiota dysbiosis group were administered a mixture of broad-spectrum antibiotics (bacitracin and neomycin) for 2 weeks. Both groups were injected intraperitoneally with mouse ovarian epithelial cells that induce ovarian tumorigenesis. Levels of C-reactive protein (CRP), interleukin-6 (IL-6), and tumor necrosis factor-alpha (TNF-α) were assessed in the serum, and the composition of the GI microbiota in fecal samples was measured using 16S rRNA gene sequencing. Overall CRP serum levels were significantly lower and TNFα levels were significantly higher in the microbiota dysbiosis group compared to the control group. The abundances of microbiota that correlated with CRP serum levels in the combined groups were genus Parabacteroides, Roseburia, and Emergencia and species Ruminococcus faecis, Parabacteroides distasonis, Roseburia Faecis, and Emergencia timonensis. This study provides evidence to support for further investigation of the GI microbial profiles in patients at risk of EOC. Full article
(This article belongs to the Special Issue Application of Novel Technologies in the Early Detection of Gynaecological Cancers)
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Other

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13 pages, 1562 KiB  
Perspective
A Critical Overview of Predictors of Heart Sparing by Deep-Inspiration-Breath-Hold Irradiation in Left-Sided Breast Cancer Patients
by Gianluca Ferini, Vito Valenti, Anna Viola, Giuseppe Emmanuele Umana and Emanuele Martorana
Cancers 2022, 14(14), 3477; https://0-doi-org.brum.beds.ac.uk/10.3390/cancers14143477 - 18 Jul 2022
Cited by 13 | Viewed by 2218
Abstract
Radiotherapy represents an essential part of the therapeutic algorithm for breast cancer patients after conservative surgery. The treatment of left-sided tumors has been associated with a non-negligible risk of developing late-onset cardiovascular disease. The cardiac risk perception has especially increased over the last [...] Read more.
Radiotherapy represents an essential part of the therapeutic algorithm for breast cancer patients after conservative surgery. The treatment of left-sided tumors has been associated with a non-negligible risk of developing late-onset cardiovascular disease. The cardiac risk perception has especially increased over the last years due to the prolongation of patients’ survival owing to the advent of new drugs and an ever earlier cancer detection through screening programs. Improvements in radiation delivery techniques could reduce the treatment-related heart toxicity. The deep-inspiration-breath-hold (DIBH) irradiation is one of the most advanced treatment approaches, which requires specific technical equipment and uses inspiration to displace the heart from the tangential radiation fields. However, not all patients benefit from its use. Moreover, DIBH irradiation needs patient compliance and accurate training. Therefore, such a technique may be unjustifiably cumbersome and time-consuming as well as unnecessarily expensive from a mere healthcare cost point of view. Hence the need to early select only the true beneficiaries while tailoring more effective heart-sparing techniques for the others and streamlining the workflow, especially in high-volume radiation oncology departments. In this literature overview, we collected some possible predictors of cardiac dose sparing in DIBH irradiation for left breast treatment in an effort to provide an easy-to-consult summary of simple instruments to insiders for identifying patients actually benefitting from this technique. We critically reviewed the reliability and weaknesses of each retrieved finding, aiming to inspire new insights and discussions on this much-debated topic. Full article
(This article belongs to the Special Issue Application of Novel Technologies in the Early Detection of Gynaecological Cancers)
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