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Personalized Medicine in Women's Cancer
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Personalized Medicine in Women's Cancer

A special issue of Journal of Personalized Medicine (ISSN 2075-4426). This special issue belongs to the section "Clinical Medicine, Cell, and Organism Physiology".

Deadline for manuscript submissions: closed (28 February 2021) | Viewed by 36983

Special Issue Editor

Dr. Eleanor E. R. Harris

E-Mail Website
Guest Editor
University Hospitals Case Western Reserve University, Cleveland, OH, USA
Interests: breast cancer; gynecologic cancers; radiosensitivity assays; clinical trials

Special Issue Information

Dear Colleagues, 

Precision medicine for cancer care individualizes treatment regimens through predictive and prognostic assessment of the risk of recurrence or progression for each individual’s tumor. Precision should be sought for each phase of care, from detection, to diagnosis, to treatment and to survivorship. Personalization is achieved by quantifying the inherent biological behaviors of each tumor, in contradiction to the traditional diagnostic and prognostic estimations based on clinicopathologic features. Extensive research focused on women’s cancers, including breast, ovarian and other gynecologic cancers, is being conducted in multiple disciplines. Clinical trial design is adapting to the new paradigms of patient selection based on tumor-specific molecular assays rather than grouping heterogenous patient populations into two or three comparison arms. This Special Issue of the Journal of Personalized Medicine aims to highlight the current state of the science and showcase some of the latest findings in the field of precision medicine research and advances in the diagnosis and treatment of Women’s Cancers. Studies that use tumor-specific and patient-specific technologies and assays to improve survival and other outcomes are featured.

Dr. Eleanor E. R. Harris
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 Personalized Medicine is an international peer-reviewed open access monthly 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

  • Breast cancer
  • Ovarian cancer
  • Cervix cancer
  • Uterine cancer
  • Precision medicine
  • Molecular assays

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Published Papers (10 papers)

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Research

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17 pages, 1515 KiB  
Article
Machine Learning-Based Approach Highlights the Use of a Genomic Variant Profile for Precision Medicine in Ovarian Failure
by Ismael Henarejos-Castillo, Alejandro Aleman, Begoña Martinez-Montoro, Francisco Javier Gracia-Aznárez, Patricia Sebastian-Leon, Monica Romeu, Jose Remohi, Ana Patiño-Garcia, Pedro Royo, Gorka Alkorta-Aranburu and Patricia Diaz-Gimeno
J. Pers. Med. 2021, 11(7), 609; https://doi.org/10.3390/jpm11070609 - 27 Jun 2021
Cited by 5 | Viewed by 2579
Abstract
Ovarian failure (OF) is a common cause of infertility usually diagnosed as idiopathic, with genetic causes accounting for 10–25% of cases. Whole-exome sequencing (WES) may enable identifying contributing genes and variant profiles to stratify the population into subtypes of OF. This study sought [...] Read more.
Ovarian failure (OF) is a common cause of infertility usually diagnosed as idiopathic, with genetic causes accounting for 10–25% of cases. Whole-exome sequencing (WES) may enable identifying contributing genes and variant profiles to stratify the population into subtypes of OF. This study sought to identify a blood-based gene variant profile using accumulation of rare variants to promote precision medicine in fertility preservation programs. A case–control (n = 118, n = 32, respectively) WES study was performed in which only non-synonymous rare variants <5% minor allele frequency (MAF; in the IGSR) and coverage ≥ 100× were considered. A profile of 66 variants of uncertain significance was used for training an unsupervised machine learning model to separate cases from controls (97.2% sensitivity, 99.2% specificity) and stratify the population into two subtypes of OF (A and B) (93.31% sensitivity, 96.67% specificity). Model testing within the IGSR female population predicted 0.5% of women as subtype A and 2.4% as subtype B. This is the first study linking OF to the accumulation of rare variants and generates a new potential taxonomy supporting application of this approach for precision medicine in fertility preservation. Full article
(This article belongs to the Special Issue Personalized Medicine in Women's Cancer)
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13 pages, 977 KiB  
Article
Phenomapping of Patients with Primary Breast Cancer Using Machine Learning-Based Unsupervised Cluster Analysis
by Sara Ferro, Daniele Bottigliengo, Dario Gregori, Aline S. C. Fabricio, Massimo Gion and Ileana Baldi
J. Pers. Med. 2021, 11(4), 272; https://doi.org/10.3390/jpm11040272 - 5 Apr 2021
Cited by 12 | Viewed by 3001
Abstract
Primary breast cancer (PBC) is a heterogeneous disease at the clinical, histopathological, and molecular levels. The improved classification of PBC might be important to identify subgroups of the disease, relevant to patient management. Machine learning algorithms may allow a better understanding of the [...] Read more.
Primary breast cancer (PBC) is a heterogeneous disease at the clinical, histopathological, and molecular levels. The improved classification of PBC might be important to identify subgroups of the disease, relevant to patient management. Machine learning algorithms may allow a better understanding of the relationships within heterogeneous clinical syndromes. This work aims to show the potential of unsupervised learning techniques for improving classification in PBC. A dataset of 712 women with PBC is used as a motivating example. A set of variables containing biological prognostic parameters is considered to define groups of individuals. Four different clustering methods are used: K-means, self-organising maps, hierarchical agglomerative (HAC), and Gaussian mixture models clustering. HAC outperforms the other clustering methods. With an optimal partitioning parameter, the methods identify two clusters with different clinical profiles. Patients in the first cluster are younger and have lower values of the oestrogen receptor (ER) and progesterone receptor (PgR) than patients in the second cluster. Moreover, cathepsin D values are lower in the first cluster. The three most important variables identified by the HAC are: age, ER, and PgR. Unsupervised learning seems a suitable alternative for the analysis of PBC data, opening up new perspectives in the particularly active domain of dissecting clinical heterogeneity. Full article
(This article belongs to the Special Issue Personalized Medicine in Women's Cancer)
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15 pages, 2605 KiB  
Article
Response Predictivity to Neoadjuvant Therapies in Breast Cancer: A Qualitative Analysis of Background Parenchymal Enhancement in DCE-MRI
by Daniele La Forgia, Angela Vestito, Maurilia Lasciarrea, Maria Colomba Comes, Sergio Diotaiuti, Francesco Giotta, Agnese Latorre, Vito Lorusso, Raffaella Massafra, Gennaro Palmiotti, Lucia Rinaldi, Rahel Signorile, Gianluca Gatta and Annarita Fanizzi
J. Pers. Med. 2021, 11(4), 256; https://doi.org/10.3390/jpm11040256 - 1 Apr 2021
Cited by 20 | Viewed by 3653
Abstract
Background: For assessing the predictability of oncology neoadjuvant therapy results, the background parenchymal enhancement (BPE) parameter in breast magnetic resonance imaging (MRI) has acquired increased interest. This work aims to qualitatively evaluate the BPE parameter as a potential predictive marker for neoadjuvant therapy. [...] Read more.
Background: For assessing the predictability of oncology neoadjuvant therapy results, the background parenchymal enhancement (BPE) parameter in breast magnetic resonance imaging (MRI) has acquired increased interest. This work aims to qualitatively evaluate the BPE parameter as a potential predictive marker for neoadjuvant therapy. Method: Three radiologists examined, in triple-blind modality, the MRIs of 80 patients performed before the start of chemotherapy, after three months from the start of treatment, and after surgery. They identified the portion of fibroglandular tissue (FGT) and BPE of the contralateral breast to the tumor in the basal control pre-treatment (baseline). Results: We observed a reduction of BPE classes in serial MRI checks performed during neoadjuvant therapy, as compared to baseline pre-treatment conditions, in 61.3% of patients in the intermediate step, and in 86.7% of patients in the final step. BPE reduction was significantly associated with sequential anthracyclines/taxane administration in the first cycle of neoadjuvant therapy compared to anti-HER2 containing therapies. The therapy response was also significantly related to tumor size. There were no associations with menopausal status, fibroglandular tissue (FGT) amount, age, BPE baseline, BPE in intermediate, and in the final MRI step. Conclusions: The measured variability of this parameter during therapy could predict therapy effectiveness in early stages, improving decision-making in the perspective of personalized medicine. Our preliminary results suggest that BPE may represent a predictive factor in response to neoadjuvant therapy in breast cancer, warranting future investigations in conjunction with radiomics. Full article
(This article belongs to the Special Issue Personalized Medicine in Women's Cancer)
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15 pages, 283 KiB  
Article
The Need of Personalized Medicine in Coping with Stress during Infertility Treatment
by Małgorzata Nagórska, Bogdan Obrzut, Dariusz Ulman and Dorota Darmochwał-Kolarz
J. Pers. Med. 2021, 11(1), 56; https://doi.org/10.3390/jpm11010056 - 18 Jan 2021
Cited by 11 | Viewed by 3263
Abstract
The term personalized medicine was created for oncological patients, but due to its positive clinical results it is now used in many other fields of medicine, including reproductive medicine. The aim of the study was to determine the level of stress and strategies [...] Read more.
The term personalized medicine was created for oncological patients, but due to its positive clinical results it is now used in many other fields of medicine, including reproductive medicine. The aim of the study was to determine the level of stress and strategies of coping with stress in patients treated for infertility. The study—using a questionnaire developed by the authors, the Perceived Stress Scale-10 (PSS-10), and the Coping Orientation to Problems Experienced Inventory (Mini-COPE)—was conducted among 456 people from infertile couples. Conclusions: More than half of the studied patients demonstrated a high level of stress. The choice of coping strategies was related to the respondents’ gender and level of stress as well as their experience with assisted reproductive technology. Full article
(This article belongs to the Special Issue Personalized Medicine in Women's Cancer)
11 pages, 640 KiB  
Article
The Double Life-Saving Approach of Abdominal Radical Trachelectomy during Pregnancy for Early-Stage Cervical Cancer—An Overview of the Literature and Our Institutional Experience
by Mihai Stanca, Victoria Ciobanu, Mihai Gheorghe, Szilard Leo Kiss, Alexandra Lavinia Cozlea and Mihai Emil Căpîlna
J. Pers. Med. 2021, 11(1), 29; https://doi.org/10.3390/jpm11010029 - 5 Jan 2021
Cited by 4 | Viewed by 4708
Abstract
(1) Background: Cervical cancer is the most common type of cancer encountered during pregnancy, with a frequency of 0.8–1.5 cases per 10,000 births. It is a dire condition endangering patients’ lives and pregnancy outcomes, and jeopardizing their fertility. However, there is a lack [...] Read more.
(1) Background: Cervical cancer is the most common type of cancer encountered during pregnancy, with a frequency of 0.8–1.5 cases per 10,000 births. It is a dire condition endangering patients’ lives and pregnancy outcomes, and jeopardizing their fertility. However, there is a lack of current evidence and consensus regarding a standard surgical technique for pregnant patients who suffer from this condition during pregnancy. The study aims to comprehensively update all published data, evaluating the obstetrical and oncological results of pregnant patients who underwent abdominal radical trachelectomy during early stages of cervical cancer. (2) Methods: A literature search on the Medline, PubMed, and Google Scholar databases was performed, including all articles in question up to July 2020. This study presents an overview of the literature and our institutional experience. (3) Results: A total of 25 cases of abdominal radical trachelectomy were performed during pregnancy for early cervical cancer, including the five cases managed by the authors. Of these, 81% (19 patients) gave birth to live newborns through elective C-section, and 19% (6 patients) experienced miscarriage shortly after the procedure. None of the 25 patients (100%) reported disease recurrence. (4) Conclusions: The results of the current study were satisfactory. However, abdominal radical trachelectomy does not represent the current standard of care for cervical cancer during pregnancy, but it could play an important role if more evidence on its effectiveness will be provided. Full article
(This article belongs to the Special Issue Personalized Medicine in Women's Cancer)
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Review

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16 pages, 308 KiB  
Review
The Female Reproductive Tract Microbiome—Implications for Gynecologic Cancers and Personalized Medicine
by Anthony E. Rizzo, Jennifer C. Gordon, Alicia R. Berard, Adam D. Burgener and Stefanie Avril
J. Pers. Med. 2021, 11(6), 546; https://doi.org/10.3390/jpm11060546 - 11 Jun 2021
Cited by 14 | Viewed by 3464
Abstract
The microbial colonization of the lower female reproductive tract has been extensively studied over the past few decades. In contrast, the upper female reproductive tract including the uterine cavity and peritoneum where the ovaries and fallopian tubes reside were traditionally assumed to be [...] Read more.
The microbial colonization of the lower female reproductive tract has been extensively studied over the past few decades. In contrast, the upper female reproductive tract including the uterine cavity and peritoneum where the ovaries and fallopian tubes reside were traditionally assumed to be sterile under non-pathologic conditions. However, recent studies applying next-generation sequencing of the bacterial 16S ribosomal RNA gene have provided convincing evidence for the existence of an upper female reproductive tract microbiome. While the vaginal microbiome and its importance for reproductive health outcomes has been extensively studied, the microbiome of the upper female reproductive tract and its relevance for gynecologic cancers has been less studied and will be the focus of this article. This targeted review summarizes the pertinent literature on the female reproductive tract microbiome in gynecologic malignancies and its anticipated role in future research and clinical applications in personalized medicine. Full article
(This article belongs to the Special Issue Personalized Medicine in Women's Cancer)
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14 pages, 1130 KiB  
Review
Liquid Biopsy: A New Tool for Overcoming CDKi Resistance Mechanisms in Luminal Metastatic Breast Cancer
by Miriam González-Conde, Celso Yañez-Gómez, Rafael López-López and Clotilde Costa
J. Pers. Med. 2021, 11(5), 407; https://doi.org/10.3390/jpm11050407 - 13 May 2021
Cited by 3 | Viewed by 2964
Abstract
Breast cancer (BC) is the most common cancer diagnosed in women worldwide. Approximately 70% of BC patients have the luminal subtype, which expresses hormone receptors (HR+). Adjuvant endocrine treatments are the standard of care for HR+/HER2− BC patients. Over time, approximately 30% of [...] Read more.
Breast cancer (BC) is the most common cancer diagnosed in women worldwide. Approximately 70% of BC patients have the luminal subtype, which expresses hormone receptors (HR+). Adjuvant endocrine treatments are the standard of care for HR+/HER2− BC patients. Over time, approximately 30% of those patients develop endocrine resistance and metastatic disease. Cyclin-dependent kinase inhibitors (CDKi), in combination with an aromatase inhibitor or fulvestrant, have demonstrated superior efficacies in increasing progression-free survival, with a safe toxicity profile, in HR+/HER2− metastatic BC patients. CDKi blocks kinases 4/6, preventing G1/S cell cycle transition. However, not all of the patients respond to CDKi, and those who do respond ultimately develop resistance to the combined therapy. Studies in tumour tissues and cell lines have tried to elucidate the mechanisms that underlie this progression, but there are still no conclusive data. Over the last few years, liquid biopsy has contributed relevant information. Circulating tumour materials are potential prognostic markers for determining patient prognosis in metastatic luminal BC, for monitoring disease, and for treatment selection. This review outlines the different studies performed using liquid biopsy in patients with HR+ metastatic BC treated with CDKi plus endocrine therapy. We mainly focus on those studies that describe the possible resistance mechanisms in circulating tumour-derived material. Full article
(This article belongs to the Special Issue Personalized Medicine in Women's Cancer)
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8 pages, 514 KiB  
Review
Proton Therapy for Partial Breast Irradiation: Rationale and Considerations
by J. Isabelle Choi, Jana Fox, Richard Bakst, Shaakir Hasan, Robert H. Press, Arpit M. Chhabra, Brian Yeh, Charles B. Simone II and Oren Cahlon
J. Pers. Med. 2021, 11(4), 289; https://doi.org/10.3390/jpm11040289 - 9 Apr 2021
Cited by 3 | Viewed by 3132
Abstract
In an era of continued advancements in personalized medicine for the treatment of breast cancer, select patients with early stage breast cancer may be uniquely poised to benefit from partial breast irradiation (PBI) delivered with proton therapy. PBI presents an opportunity to improve [...] Read more.
In an era of continued advancements in personalized medicine for the treatment of breast cancer, select patients with early stage breast cancer may be uniquely poised to benefit from partial breast irradiation (PBI) delivered with proton therapy. PBI presents an opportunity to improve quality of life during treatment with a significantly shorter treatment duration. By targeting less non-target breast tissue, excess radiation exposure and resulting toxicities are also reduced. Proton therapy represents a precision radiotherapy technology that builds on these advantages by further limiting the normal tissue exposure to unnecessary radiation dose not only to uninvolved breast tissue but also the underlying thoracic organs including the heart and lungs. Herein, we present a concise review of the rationale for the use of proton therapy for PBI, evidence available to date, and practical considerations in the implementation and use of proton therapy for this indication. Full article
(This article belongs to the Special Issue Personalized Medicine in Women's Cancer)
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14 pages, 4639 KiB  
Review
Contrast-Enhanced Ultrasonography in the Diagnosis and Treatment Modulation of Breast Cancer
by Ioana Boca (Bene), Sorin M. Dudea and Anca I. Ciurea
J. Pers. Med. 2021, 11(2), 81; https://doi.org/10.3390/jpm11020081 - 30 Jan 2021
Cited by 28 | Viewed by 4041
Abstract
The aim of this paper is to highlight the role of contrast-enhanced ultrasound in breast cancer in terms of diagnosis, staging and follow-up of the post-treatment response. Contrast-enhanced ultrasound (CEUS) is successfully used to diagnose multiple pathologies and has also clinical relevance in [...] Read more.
The aim of this paper is to highlight the role of contrast-enhanced ultrasound in breast cancer in terms of diagnosis, staging and follow-up of the post-treatment response. Contrast-enhanced ultrasound (CEUS) is successfully used to diagnose multiple pathologies and has also clinical relevance in breast cancer. CEUS has high accuracy in differentiating benign from malignant lesions by analyzing the enhancement characteristics and calculating the time-intensity curve’s quantitative parameters. It also has a significant role in axillary staging, especially when the lymph nodes are not suspicious on clinical examination and have a normal appearance on gray-scale ultrasound. The most significant clinical impact consists of predicting the response to neoadjuvant chemotherapy, which offers the possibility of adjusting the therapy by dynamically evaluating the patient. CEUS is a high-performance, feasible, non-irradiating, accessible, easy-to-implement imaging method and has proven to be a valuable addition to breast ultrasound. Full article
(This article belongs to the Special Issue Personalized Medicine in Women's Cancer)
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23 pages, 1932 KiB  
Review
Metabolomics for Diagnosis and Prognosis of Uterine Diseases? A Systematic Review
by Janina Tokarz, Jerzy Adamski and Tea Lanišnik Rižner
J. Pers. Med. 2020, 10(4), 294; https://doi.org/10.3390/jpm10040294 - 21 Dec 2020
Cited by 23 | Viewed by 5154
Abstract
This systematic review analyses the contribution of metabolomics to the identification of diagnostic and prognostic biomarkers for uterine diseases. These diseases are diagnosed invasively, which entails delayed treatment and a worse clinical outcome. New options for diagnosis and prognosis are needed. PubMed, OVID, [...] Read more.
This systematic review analyses the contribution of metabolomics to the identification of diagnostic and prognostic biomarkers for uterine diseases. These diseases are diagnosed invasively, which entails delayed treatment and a worse clinical outcome. New options for diagnosis and prognosis are needed. PubMed, OVID, and Scopus were searched for research papers on metabolomics in physiological fluids and tissues from patients with uterine diseases. The search identified 484 records. Based on inclusion and exclusion criteria, 44 studies were included into the review. Relevant data were extracted following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analysis) checklist and quality was assessed using the QUADOMICS tool. The selected metabolomics studies analysed plasma, serum, urine, peritoneal, endometrial, and cervico-vaginal fluid, ectopic/eutopic endometrium, and cervical tissue. In endometriosis, diagnostic models discriminated patients from healthy and infertile controls. In cervical cancer, diagnostic algorithms discriminated patients from controls, patients with good/bad prognosis, and with/without response to chemotherapy. In endometrial cancer, several models stratified patients from controls and recurrent from non-recurrent patients. Metabolomics is valuable for constructing diagnostic models. However, the majority of studies were in the discovery phase and require additional research to select reliable biomarkers for validation and translation into clinical practice. This review identifies bottlenecks that currently prevent the translation of these findings into clinical practice. Full article
(This article belongs to the Special Issue Personalized Medicine in Women's Cancer)
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