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Emerging Diagnostic and Treatment Approaches for Gynecological Cancers
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Emerging Diagnostic and Treatment Approaches for Gynecological Cancers

A special issue of Journal of Clinical Medicine (ISSN 2077-0383). This special issue belongs to the section "Obstetrics & Gynecology".

Deadline for manuscript submissions: 31 October 2025 | Viewed by 315

Special Issue Editor

Dr. Marco D'Indinosante

E-Mail Website
Guest Editor
Dipartimento per le Scienze Della Salute Della Donna, del Bambino e di Sanità Pubblica, UOC Ginecologia Oncologica, Fondazione Policlinico Universitario Agostino Gemelli IRCCS, 00168 Rome, Italy
Interests: gynecologic oncology; ovarian cancer; cervical cancer; endometrial cancer; minimally invasive surgery
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

This Special Issue of the Journal of Clinical Medicine is dedicated to exploring the latest advancements in the diagnosis and treatment of gynecologic cancers. Despite significant progress in understanding their molecular mechanisms, these malignancies continue to pose considerable challenges in clinical management. The primary objective is to investigate novel strategies for early detection, identify reliable predictive biomarkers, and enhance personalized treatment approaches, with a particular emphasis on immunotherapy, targeted therapies, and precision medicine.

Additionally, this issue will cover cutting-edge developments in surgical techniques, radiation therapy, and integrative treatment modalities. We welcome original research articles and comprehensive reviews that present groundbreaking findings, aiming to offer a broad perspective on emerging opportunities to improve patient survival and quality of life.

We invite contributions from oncologists, gynecologists, molecular biologists, nurses, psychologists, and other professionals engaged in gynecologic cancer research. Original trials, systematic reviews, and meta-analyses are encouraged to foster a deeper understanding of these malignancies and drive innovation in patient care.

We look forward to receiving your valuable contributions.

Dr. Marco D'Indinosante
Guest Editor

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. Journal of Clinical Medicine 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 2600 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

  • gynecologic oncology
  • surgical gynecology
  • biomarkers
  • endometrial carcinoma
  • ovarian carcinoma
  • cervical carcinoma

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Published Papers (1 paper)

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Research

11 pages, 817 KiB  
Article
Machine Learning Based Assessment of Inguinal Lymph Node Metastasis in Patients with Squamous Cell Carcinoma of the Vulva
by Gilbert Georg Klamminger, Meletios P. Nigdelis, Annick Bitterlich, Bashar Haj Hamoud, Erich-Franz Solomayer, Annette Hasenburg and Mathias Wagner
J. Clin. Med. 2025, 14(10), 3510; https://doi.org/10.3390/jcm14103510 - 17 May 2025
Viewed by 207
Abstract
Background/Objectives: Despite great efforts from both clinical and pathological sides to address the extent of metastatic inguinal lymph node involvement in patients with vulvar cancer, current research attempts are still mostly aimed at identifying new imaging parameters or superior tissue diagnostic workflows [...] Read more.
Background/Objectives: Despite great efforts from both clinical and pathological sides to address the extent of metastatic inguinal lymph node involvement in patients with vulvar cancer, current research attempts are still mostly aimed at identifying new imaging parameters or superior tissue diagnostic workflows rather than alternative ways of statistical data analysis. In the present study, we therefore establish a supervised machine learning algorithm to predict groin metastasis in patients with squamous cell carcinoma of the vulva (VSCC) based on classical histomorphological features. Methods: In total, 157 patients with VSCC were included in this retrospective study. After initial exploration of valuable clinicopathological predictor variables by means of Spearman correlation, a decision tree was trained and internally validated (5-fold cross-validation) using a training data set (n = 126) and afterwards externally validated employing a holdout validation data set (n = 31) using standard metrices such sensitivity, positive predictive value, and AUROC curve. Results: Our established classifier can predict inguinal lymph node status with an internal accuracy of 79.4% (AUROC value = 0.64). Reaching similar performances and an overall accuracy of 83.9% on an unknown data input (external validation set), our classifier demonstrates robustness. Conclusions: The presented results suggest that machine learning can predict groin lymph node status in VSCC based on histological findings of the primary tumor. Such research attempts may be useful in the future for an additional assessment of inguinal lymph nodes, aiming to maximize oncological safety when targeting the most accurate diagnosis of lymph node involvement. Full article
(This article belongs to the Special Issue Emerging Diagnostic and Treatment Approaches for Gynecological Cancers)
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