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11 pages, 1498 KiB

Open AccessArticle

No Racial Disparities Observed Using Point-of-Care Genetic Counseling and Testing for Endometrial and Ovarian Cancer in a Diverse Patient Population: A Retrospective Cohort Study

by Michael Kim, Judy Hayek, Cheyenne Acker, Anjile An, Peilin Zhang, Constantine Gorelick and Margaux J. Kanis

Cancers 2024, 16(8), 1598; https://doi.org/10.3390/cancers16081598 - 22 Apr 2024

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Abstract

We investigated genetic counseling and testing rates for patients with gynecologic malignancy at a tertiary care center with a large minority population. Our retrospective cohort included newly diagnosed epithelial ovarian, fallopian tube, peritoneal, or endometrial cancer patients between January 2014 and June 2022. [...] Read more.

We investigated genetic counseling and testing rates for patients with gynecologic malignancy at a tertiary care center with a large minority population. Our retrospective cohort included newly diagnosed epithelial ovarian, fallopian tube, peritoneal, or endometrial cancer patients between January 2014 and June 2022. For endometrial cancer, 373 patients were identified. A total of 207 (55%) patients were screened using mismatch repair immunohistochemistry (MMR IHC). A total of 82 (40%) had MMR deficiencies on IHC. Of these, 63 (77%) received genetic counseling. A total of 62 (98%) underwent genetic testing, and ultimately, 7 (11%) were diagnosed with Lynch syndrome (LS). The overall rate of LS was 1.9%. MMR IHC testing increased steadily, reaching 100% in 2022. For ovarian cancer, 144 patients were identified. A total of 104 (72%) patients received genetic counseling, and 99 (95%) underwent genetic testing. Rates were not influenced by race, ethnicity, insurance type, or family history of cancer. They were significantly different by cancer stage (p < 0.01). The proportion of patients who received genetic counseling increased from 47% in 2015 to 100% in 2022 (p < 0.01). Most counseling was performed by a gynecologic oncologist (93%) as opposed to a genetic counselor (6.7%). Overall, 12 (8.3%) patients were BRCA+. High rates of counseling and testing were observed with few disparities. Full article

(This article belongs to the Special Issue Innovations in Diagnosis, Prognostic Evaluation, and Therapeutic Management of Gynecologic Tumors)

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15 pages, 2678 KiB

Open AccessArticle

Machine Learning Applied to Pre-Operative Computed-Tomography-Based Radiomic Features Can Accurately Differentiate Uterine Leiomyoma from Leiomyosarcoma: A Pilot Study

by Miriam Santoro, Vladislav Zybin, Camelia Alexandra Coada, Giulia Mantovani, Giulia Paolani, Marco Di Stanislao, Cecilia Modolon, Stella Di Costanzo, Andrei Lebovici, Gloria Ravegnini, Antonio De Leo, Marco Tesei, Pietro Pasquini, Luigi Lovato, Alessio Giuseppe Morganti, Maria Abbondanza Pantaleo, Pierandrea De Iaco, Lidia Strigari and Anna Myriam Perrone

Cancers 2024, 16(8), 1570; https://doi.org/10.3390/cancers16081570 - 19 Apr 2024

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Abstract

Background: The accurate discrimination of uterine leiomyosarcomas and leiomyomas in a pre-operative setting remains a current challenge. To date, the diagnosis is made by a pathologist on the excised tumor. The aim of this study was to develop a machine learning algorithm using [...] Read more.

Background: The accurate discrimination of uterine leiomyosarcomas and leiomyomas in a pre-operative setting remains a current challenge. To date, the diagnosis is made by a pathologist on the excised tumor. The aim of this study was to develop a machine learning algorithm using radiomic data extracted from contrast-enhanced computed tomography (CECT) images that could accurately distinguish leiomyosarcomas from leiomyomas. Methods: Pre-operative CECT images from patients submitted to surgery with a histological diagnosis of leiomyoma or leiomyosarcoma were used for the region of interest identification and radiomic feature extraction. Feature extraction was conducted using the PyRadiomics library, and three feature selection methods combined with the general linear model (GLM), random forest (RF), and support vector machine (SVM) classifiers were built, trained, and tested for the binary classification task (malignant vs. benign). In parallel, radiologists assessed the diagnosis with or without clinical data. Results: A total of 30 patients with leiomyosarcoma (mean age 59 years) and 35 patients with leiomyoma (mean age 48 years) were included in the study, comprising 30 and 51 lesions, respectively. Out of nine machine learning models, the three feature selection methods combined with the GLM and RF classifiers showed good performances, with predicted area under the curve (AUC), sensitivity, and specificity ranging from 0.78 to 0.97, from 0.78 to 1.00, and from 0.67 to 0.93, respectively, when compared to the results obtained from experienced radiologists when blinded to the clinical profile (AUC = 0.73 95%CI = 0.62–0.84), as well as when the clinical data were consulted (AUC = 0.75 95%CI = 0.65–0.85). Conclusions: CECT images integrated with radiomics have great potential in differentiating uterine leiomyomas from leiomyosarcomas. Such a tool can be used to mitigate the risks of eventual surgical spread in the case of leiomyosarcoma and allow for safer fertility-sparing treatment in patients with benign uterine lesions. Full article

(This article belongs to the Special Issue Innovations in Diagnosis, Prognostic Evaluation, and Therapeutic Management of Gynecologic Tumors)

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15 pages, 2918 KiB

Open AccessArticle

Modulation of sHLA-G, PD-1, and PD-L1 Expression in Cervical Lesions Following Imiquimod Treatment and Its Association with Treatment Success

by Andrej Cokan, Neila Caroline Henrique da Silva, Rajko Kavalar, Igor But, Maja Pakiž, Sheilla Andrade de Oliveira, Fabiana Oliveira dos Santos Gomes, Rodrigo Soares da Silva, Christina Alves Peixoto and Norma Lucena-Silva

Cancers 2024, 16(7), 1272; https://doi.org/10.3390/cancers16071272 - 25 Mar 2024

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Abstract

(1) Background: Cervical intraepithelial neoplasia (CIN) is a precancerous condition linked to human papillomavirus (HPV) infection, often necessitating surgical interventions carrying the risk of subsequent preterm births. This study explores the potential of imiquimod (IMQ), as a non-invasive alternative treatment. The focus is [...] Read more.

(1) Background: Cervical intraepithelial neoplasia (CIN) is a precancerous condition linked to human papillomavirus (HPV) infection, often necessitating surgical interventions carrying the risk of subsequent preterm births. This study explores the potential of imiquimod (IMQ), as a non-invasive alternative treatment. The focus is on understanding IMQ impact on immune checkpoint molecules, particularly PD-1, PD-L1, and sHLA-G, which play pivotal roles in shaping immune responses and cancer progression. (2) Methods: Forty-three patients diagnosed with a high-risk squamous intraepithelial lesion (HSIL, p16-positive) self-applied 5% IMQ encapsulated in sachets containing 250 g of cream into the vaginal cavity three times a week for 16 weeks. The impact of IMQ therapy on cervical lesion regression was assessed through immunohistochemistry (IHC), examining changes in sHLA-G, PD-L1, and PD-1 levels. The antiviral activity of IMQ was evaluated through HPV-E7 immunofluorescence. Ethical considerations were adhered to, and the research methods were based on a previously approved clinical trial (clinicaltrials.gov Identifier: NCT04859361). (3) Results: IMQ treatment demonstrated efficacy, leading to lesion regression. sHLA-G levels in CIN before starting IMQ application were associated with unsuccessful treatment (p = 0.0036). IMQ did not significantly alter the expression of PD-1. We observed a decrease in PD-L1 levels in those who were successfully treated (p = 0.0509) and a reduction in HPV burden. (4) Conclusions: IMQ exhibits promise as a non-invasive treatment for CIN, emphasising its potential to modulate the immune microenvironment. Baseline sHLA-G levels emerge as potential predictors of treatment response. Understanding the nuanced dynamics of immune checkpoints sheds light on IMQ mechanism of action. Further exploration is warranted to decipher the intricate mechanisms underlying IMQ treatment in the context of cervical lesions. Full article

(This article belongs to the Special Issue Innovations in Diagnosis, Prognostic Evaluation, and Therapeutic Management of Gynecologic Tumors)

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14 pages, 848 KiB

Open AccessArticle

Sarcopenic Obesity in Cervical Carcinoma: A Strong and Independent Prognostic Factor beyond the Conventional Predictors (ESTHER Study—AFRAID Project)

by Federica Medici, Martina Ferioli, Silvia Cammelli, Ludovica Forlani, Viola Laghi, Johnny Ma, Savino Cilla, Milly Buwenge, Gabriella Macchia, Francesco Deodato, Maria Vadalà, Claudio Malizia, Luca Tagliaferri, Anna Myriam Perrone, Pierandrea De Iaco, Lidia Strigari, Alberto Bazzocchi, Stefania Rizzo, Alessandra Arcelli and Alessio Giuseppe Morganti

Cancers 2024, 16(5), 929; https://doi.org/10.3390/cancers16050929 - 25 Feb 2024

Viewed by 696

Abstract

Locally advanced cervical cancer represents a significant treatment challenge. Body composition parameters such as body mass index, sarcopenia, and sarcopenic obesity, defined by sarcopenia and BMI ≥ 30 kg/m², have been identified as potential prognostic factors, yet their overall impact remains [...] Read more.

Locally advanced cervical cancer represents a significant treatment challenge. Body composition parameters such as body mass index, sarcopenia, and sarcopenic obesity, defined by sarcopenia and BMI ≥ 30 kg/m², have been identified as potential prognostic factors, yet their overall impact remains underexplored. This study assessed the relationship between these anthropometric parameters alongside clinical prognostic factors on the prognosis of 173 cervical cancer patients. Survival outcomes in terms of local control (LC), distant metastasis-free survival (DMFS), disease-free survival (DFS), and overall survival (OS) were analyzed using Kaplan regression methods—Meier and Cox. Older age, lower hemoglobin levels, higher FIGO (International Federation of Gynecology and Obstetrics) stages, and lower total radiation doses were significantly associated with worse outcomes. Univariate analysis showed a significant correlation between BMI and the outcomes examined, revealing that normal-weight patients show higher survival rates, which was not confirmed by the multivariate analysis. Sarcopenia was not correlated with any of the outcomes considered, while sarcopenic obesity was identified as an independent negative predictor of DFS (HR: 5.289, 95% CI: 1.298–21.546, p = 0.020) and OS (HR: 2.645, 95% CI: 1.275–5.488, p = 0.009). This study highlights the potential of sarcopenic obesity as an independent predictor of clinical outcomes. These results support their inclusion in prognostic assessments and treatment planning for patients with advanced cervical cancer. Full article

(This article belongs to the Special Issue Innovations in Diagnosis, Prognostic Evaluation, and Therapeutic Management of Gynecologic Tumors)

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15 pages, 953 KiB

Open AccessArticle

Decoding the Complexity of Systemic Inflammation Predictors in Locally Advanced Cervical Cancer, with Hemoglobin as the Hidden Key (the ESTHER Study)

by Federica Medici, Martina Ferioli, Ludovica Forlani, Viola Laghi, Johnny Ma, Savino Cilla, Milly Buwenge, Gabriella Macchia, Francesco Deodato, Maria Vadalà, Claudio Malizia, Luca Tagliaferri, Anna Myriam Perrone, Pierandrea De Iaco, Lidia Strigari, Alessandra Arcelli and Alessio Giuseppe Morganti

Cancers 2023, 15(20), 5056; https://doi.org/10.3390/cancers15205056 - 19 Oct 2023

Cited by 1 | Viewed by 895

Abstract

Locally advanced cervical cancer (LACC) is treated with concurrent chemoradiation (CRT). Predictive models could improve the outcome through treatment personalization. Several factors influence prognosis in LACC, but the role of systemic inflammation indices (IIs) is unclear. This study aims to assess the correlation [...] Read more.

Locally advanced cervical cancer (LACC) is treated with concurrent chemoradiation (CRT). Predictive models could improve the outcome through treatment personalization. Several factors influence prognosis in LACC, but the role of systemic inflammation indices (IIs) is unclear. This study aims to assess the correlation between IIs and prognosis in a large patient cohort considering several clinical data. We retrospectively analyzed pretreatment IIs (NLR, PLR, MLR, SII, LLR, COP-NLR, APRI, ALRI, SIRI, and ANRI) in 173 LACC patients. Patient, tumor, and treatment characteristics were also considered. Univariate and multivariate Cox’s regressions were conducted to assess associations between IIs and clinical factors with local control (LC), distant metastasis-free survival (DMFS), disease-free survival (DFS), and overall survival (OS). Univariate analysis showed significant correlations between age, HB levels, tumor stage, FIGO stage, and CRT dose with survival outcomes. Specific pretreatment IIs (NLR, PLR, APRI, ANRI, and COP-NLR) demonstrated associations only with LC. The multivariate analysis confirmed Hb levels, CRT dose, and age as significant predictors of OS, while no II was correlated with any clinical outcome. The study findings contradict some prior research on IIs in LACC, emphasizing the need for comprehensive assessments of potential confounding variables. Full article

(This article belongs to the Special Issue Innovations in Diagnosis, Prognostic Evaluation, and Therapeutic Management of Gynecologic Tumors)

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15 pages, 2607 KiB

Open AccessArticle

Metaplastic Breast Carcinoma in U.S. Population: Racial Disparities, Survival Benefit of Adjuvant Chemoradiation and Future Personalized Treatment with Genomic Landscape

by Asad Ullah, Jaffar Khan, Abdul Qahar Khan Yasinzai, Katharine Tracy, Tena Nguyen, Bisma Tareen, Andrea Agualimpia Garcia, Saleh Heneidi and Sheila E. Segura

Cancers 2023, 15(11), 2954; https://doi.org/10.3390/cancers15112954 - 28 May 2023

Cited by 3 | Viewed by 1713

Abstract

Purpose: In this population-based study, we aim to identify factors that are influential on the survival outcome in MBC and investigate novel molecular approaches in personalized disease management. Methods: The data of this study were collected from the SEER database from 2000–2018. A [...] Read more.

Purpose: In this population-based study, we aim to identify factors that are influential on the survival outcome in MBC and investigate novel molecular approaches in personalized disease management. Methods: The data of this study were collected from the SEER database from 2000–2018. A total of 5315 cases were extracted from the database. The data were evaluated for demographics, tumor characteristics, metastasis, and treatment. Survival analysis was completed by using SAS software for multivariate analysis, univariate analysis, and non-parametric survival analysis. The molecular data with the most common mutations in MBC were extracted from the Catalogue of Somatic Mutations in Cancer (COSMIC) database. Results: The mean age at the time of presentation was 63.1 with a standard deviation (SD) of 14.2 years. Most patients were White (77.3%) with 15.7% Black patients, 6.1% Asian or Pacific Islander, and 0.5% American Indian. Histologically, most of the reported tumors were grade III (74.4%); 37% of the cases were triple negative (ER-, PR- and HER2-), whereas the hormone status was unknown in 46% of the cases. Spread was localized in 67.3% of patients while 26.3% had regional spread and 6.3% had distant metastases. Most tumors were unilateral (99.9%) and between 20–50 mm in size (50.6%). The lungs were the most common site for distant metastasis at diagnosis (3.42%) followed by bone (1.94%), liver (0.98%), and brain (0.56%). A combination of surgery, chemotherapy, and radiation therapy was the most common treatment with a cause-specific survival rate of 78.1% (95% CI = 75.4–80.4). The overall survival rate at 5 years was 63.6% (95% confidence interval (CI) = 62.0–65.1) with a cause-specific survival of 71.1% (95% CI = 69.5–72.6). Cause-specific survival was found to be 63.2% (95% CI = 58.9–67.1) in Black patients as compared to 72.4% (95% CI = 70.1–74.1) in White patients. Black patients also presented with higher rates of grade III disease, distant metastasis, and larger tumor size. On multivariate analysis, age > 60, grade III+, metastasis, and tumor size > 50 mm were associated with worse survival. The most common mutations in MBC identified in COSMIC data were TP53, PIK3CA, LRP1B, PTEN, and KMT2C. Conclusion: Though rare, MBC is aggressive, with poor prognosis associated with high-grade tumors, metastasis, tumor size over 50 mm, and advanced age at the time of presentation. Overall, Black women had worse clinical outcomes. MBC is difficult to treat and carries a poor prognosis that affects various races disproportionately. Continued enhancement of treatment strategies to foster more individualized care as well as continued enrollment in clinical trials are needed to improve outcomes among patients with MBC. Full article

(This article belongs to the Special Issue Innovations in Diagnosis, Prognostic Evaluation, and Therapeutic Management of Gynecologic Tumors)

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Review

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37 pages, 1192 KiB

Open AccessReview

Human Papillomavirus Infections and the Role Played by Cervical and Cervico-Vaginal Microbiota—Evidence from Next-Generation Sequencing Studies

by Maria Głowienka-Stodolak, Katarzyna Bagińska-Drabiuk, Sebastian Szubert, Ewa E. Hennig, Agnieszka Horala, Michalina Dąbrowska, Martyna Micek, Michał Ciebiera and Natalia Zeber-Lubecka

Cancers 2024, 16(2), 399; https://doi.org/10.3390/cancers16020399 - 17 Jan 2024

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Abstract

This comprehensive review encompasses studies examining changes in the cervical and cervico-vaginal microbiota (CM and CVM) in relation to human papillomavirus (HPV) using next-generation sequencing (NGS) technology. HPV infection remains a prominent global health concern, with a spectrum of manifestations, from benign lesions [...] Read more.

This comprehensive review encompasses studies examining changes in the cervical and cervico-vaginal microbiota (CM and CVM) in relation to human papillomavirus (HPV) using next-generation sequencing (NGS) technology. HPV infection remains a prominent global health concern, with a spectrum of manifestations, from benign lesions to life-threatening cervical cancers. The CM and CVM, a unique collection of microorganisms inhabiting the cervix/vagina, has emerged as a critical player in cervical health. Recent research has indicated that disruptions in the CM and CVM, characterized by a decrease in Lactobacillus and the overgrowth of other bacteria, might increase the risk of HPV persistence and the progression of cervical abnormalities. This alteration in the CM or CVM has been linked to a higher likelihood of HPV infection and cervical dysplasia. NGS technology has revolutionized the study of the cervical microbiome, providing insights into microbial diversity, dynamics, and taxonomic classifications. Bacterial 16S rRNA gene sequencing, has proven invaluable in characterizing the cervical microbiome, shedding light on its role in HPV infections and paving the way for more tailored strategies to combat cervical diseases. NGS-based studies offer personalized insights into an individual’s cervical microbiome. This knowledge holds promise for the development of novel diagnostic tools, targeted therapies, and preventive interventions for cervix-related conditions, including cervical cancer. Full article

(This article belongs to the Special Issue Innovations in Diagnosis, Prognostic Evaluation, and Therapeutic Management of Gynecologic Tumors)

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14 pages, 708 KiB

Open AccessReview

Update on Prognostic and Predictive Markers in Mucinous Ovarian Cancer

by Fulvio Borella, Marco Mitidieri, Stefano Cosma, Chiara Benedetto, Luca Bertero, Stefano Fucina, Isabelle Ray-Coquard, Annalisa Carapezzi and Domenico Ferraioli

Cancers 2023, 15(4), 1172; https://doi.org/10.3390/cancers15041172 - 12 Feb 2023

Cited by 2 | Viewed by 2558

Abstract

This review includes state-of-the-art prognostic and predictive factors of mucinous ovarian cancer (MOC), a rare tumor. Clinical, pathological, and molecular features and treatment options according to prognosis are comprehensively discussed. Different clinical implications of MOC are described according to the The International Federation [...] Read more.

This review includes state-of-the-art prognostic and predictive factors of mucinous ovarian cancer (MOC), a rare tumor. Clinical, pathological, and molecular features and treatment options according to prognosis are comprehensively discussed. Different clinical implications of MOC are described according to the The International Federation of Gynecology and Obstetrics (FIGO) stage: early MOC (stage I-II) and advanced MOC (stage III-IV). Early MOC is characterized by a good prognosis. Surgery is the mainstay of treatment. Fertility-sparing surgery could be performed in patients who wish to become pregnant and that present low recurrence risk of disease. Adjuvant chemotherapy is not recommended, except in patients with high-risk clinical and pathological features. Regarding the histological features, an infiltrative growth pattern is the major prognostic factor of MOC. Furthermore, novel molecular biomarkers are emerging for tailored management of early-stage MOC. In contrast, advanced MOC is characterized by poor survival. Radical surgery is the cornerstone of treatment and adjuvant chemotherapy is recommended, although the efficacy is limited by the intrinsic chemoresistance of these tumors. Several molecular hallmarks of advanced MOC have been described in recent years (e.g., HER2 amplification, distinct methylation profiles, peculiar immunological microenvironment), but target therapy for these rare tumors is not available yet. Full article

(This article belongs to the Special Issue Innovations in Diagnosis, Prognostic Evaluation, and Therapeutic Management of Gynecologic Tumors)

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44 pages, 1344 KiB

Open AccessEditor’s ChoiceReview

DNA Damage Response Alterations in Ovarian Cancer: From Molecular Mechanisms to Therapeutic Opportunities

by María Ovejero-Sánchez, Rogelio González-Sarmiento and Ana Belén Herrero

Cancers 2023, 15(2), 448; https://doi.org/10.3390/cancers15020448 - 10 Jan 2023

Cited by 8 | Viewed by 3938

Abstract

The DNA damage response (DDR), a set of signaling pathways for DNA damage detection and repair, maintains genomic stability when cells are exposed to endogenous or exogenous DNA-damaging agents. Alterations in these pathways are strongly associated with cancer development, including ovarian cancer (OC), [...] Read more.

The DNA damage response (DDR), a set of signaling pathways for DNA damage detection and repair, maintains genomic stability when cells are exposed to endogenous or exogenous DNA-damaging agents. Alterations in these pathways are strongly associated with cancer development, including ovarian cancer (OC), the most lethal gynecologic malignancy. In OC, failures in the DDR have been related not only to the onset but also to progression and chemoresistance. It is known that approximately half of the most frequent subtype, high-grade serous carcinoma (HGSC), exhibit defects in DNA double-strand break (DSB) repair by homologous recombination (HR), and current evidence indicates that probably all HGSCs harbor a defect in at least one DDR pathway. These defects are not restricted to HGSCs; mutations in ARID1A, which are present in 30% of endometrioid OCs and 50% of clear cell (CC) carcinomas, have also been found to confer deficiencies in DNA repair. Moreover, DDR alterations have been described in a variable percentage of the different OC subtypes. Here, we overview the main DNA repair pathways involved in the maintenance of genome stability and their deregulation in OC. We also recapitulate the preclinical and clinical data supporting the potential of targeting the DDR to fight the disease. Full article

(This article belongs to the Special Issue Innovations in Diagnosis, Prognostic Evaluation, and Therapeutic Management of Gynecologic Tumors)

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18 pages, 754 KiB

Open AccessReview

Epigenetic Mechanisms and Therapeutic Targets in Chemoresistant High-Grade Serous Ovarian Cancer

by Bayley G. Matthews, Nikola A. Bowden and Michelle W. Wong-Brown

Cancers 2021, 13(23), 5993; https://doi.org/10.3390/cancers13235993 - 29 Nov 2021

Cited by 16 | Viewed by 3069

Abstract

High-grade serous ovarian cancer (HGSOC) is the most common ovarian cancer subtype, and the overall survival rate has not improved in the last three decades. Currently, most patients develop recurrent disease within 3 years and succumb to the disease within 5 years. This is an [...] Read more.

High-grade serous ovarian cancer (HGSOC) is the most common ovarian cancer subtype, and the overall survival rate has not improved in the last three decades. Currently, most patients develop recurrent disease within 3 years and succumb to the disease within 5 years. This is an important area of research, as the major obstacle to the treatment of HGSOC is the development of resistance to platinum chemotherapy. The cause of chemoresistance is still largely unknown and may be due to epigenetics modifications that are driving HGSOC metastasis and treatment resistance. The identification of epigenetic changes in chemoresistant HGSOC enables the development of epigenetic modulating drugs that may be used to improve outcomes. Several epigenetic modulating drugs have displayed promise as drug targets for HGSOC, such as demethylating agents azacitidine and decitabine. Others, such as histone deacetylase inhibitors and miRNA-targeting therapies, demonstrated promising preclinical results but resulted in off-target side effects in clinical trials. This article reviews the epigenetic modifications identified in chemoresistant HGSOC and clinical trials utilizing epigenetic therapies in HGSOC. Full article

(This article belongs to the Special Issue Innovations in Diagnosis, Prognostic Evaluation, and Therapeutic Management of Gynecologic Tumors)

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