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Identification of Immunotherapy-Related Biomarkers for Gynecological Cancers

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A special issue of Medicina (ISSN 1648-9144). This special issue belongs to the section "Oncology".

Deadline for manuscript submissions: closed (31 July 2023) | Viewed by 10916

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Special Issue Editors

Dr. Jinhui Liu

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Guest Editor

Department of Gynecology, the First Affiliated Hospital of Nanjing Medical University, Nanjing, China
Interests: tumor immunology; bioinformatics; biomarker; multi-omics analysis; tumor microenvironment

Dr. Peixin Dong

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Guest Editor

Department of Obstetrics and Gynecology, Hokkaido University, Sapporo, Japan
Interests: genetic and epigenetic mechanisms contributing to metastasis and cancer therapy resistance; non-coding RNAs as regulators of cancer stemness, EMT and cancer therapy resistance; CRISPR/Cas9 genome editing system in cancer research and treatment; immune checkpoint proteins as new targets for anti-cancer therapy
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Special Issue Information

Dear Colleagues,

Great progress has been made in the prevention and treatment of gynecological tumors in recent years, especially with immunotherapy becoming a powerful clinical cancer treatment strategy. However, there is still a lack of effective therapeutic methods for advanced disease and the clinical results of immunotherapy are heterogeneous among patients, which seriously threatens women's health. Therefore, it is necessary to identify effective biomarkers for the early screening of cancer patients and to promote the development of precision therapy and immunotherapy. In addition, molecular-targeted anticancer therapies are constantly emerging, but their application is limited due to the lack of effective strategies to evaluate targeted drugs. Biomarkers that can reliably identify patients who are most likely to benefit from specific therapeutics are needed to evaluate these novel therapeutics and accelerate drug development. These biomarkers can be of different types, such as host genome factors, serum proteins, and nucleic acids (DNA or RNA molecules) in tumor cells and their microenvironment. Identification of ideal biomarkers can help gynecological cancer patients achieve better treatment goals and bring clinical benefits.

In the past decade, a variety of tumor biomarkers has been verified and widely used in clinics. However, new strategies still need to be developed to improve the efficiency and accuracy of cancer treatment by identifying more reliable biomarkers. Multi-omics, proteomics, oncomics, genomics, and other emerging methods have been applied in the identification of tumor-cell-specific markers for early cancer diagnosis and immunotherapy. Identifying multiple immune checkpoint markers is crucial to developing therapeutic targets and will have a great impact on personalized medicine.

The purpose of this research topic is to explore novel diagnostic and prognostic biomarkers to screen patients with gynecological cancer in its early stage and to promote the development of precision medicine and immunotherapy. We welcome submissions of original research, reviews, hypotheses and theory, opinions, and clinical trials, focusing on, but not limited to, the following topics:

Identification and application of diagnostic and prognostic biomarkers for gynecological tumors;
Identification and application of biomarkers for predicting recurrence and metastasis of gynecological tumors;
Identification and application of cell-type-specific biomarkers for gynecological tumors;
Temporal and spatial heterogeneity of biomarkers and their regulation mechanisms;
Tumor immune microenvironment phenotype-related biomarkers for gynecological tumors;
Novel methods to improve the accuracy in identifying biomarkers of gynecological tumors.

Dr. Jinhui Liu
Dr. Peixin Dong
Guest Editors

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Keywords

ovarian cancer
cervical cancer
endometrial cancer
tumor immune microenvironment
biomarkers

Published Papers (6 papers)

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Research

15 pages, 15933 KiB

Open AccessArticle

Pan-Cancer Analysis Reveals PPRC1 as a Novel Prognostic Biomarker in Ovarian Cancer and Hepatocellular Carcinoma

by Xingqiu Ruan, Guoliang Cui, Changyu Li and Zhiguang Sun

Medicina 2023, 59(4), 784; https://0-doi-org.brum.beds.ac.uk/10.3390/medicina59040784 - 17 Apr 2023

Cited by 1 | Viewed by 1474

Abstract

Background and Objectives: As is well understood, peroxisome proliferator-activated receptor gamma cofactor-related 1 (PPRC1) plays a central role in the transcriptional control of the mitochondrial biogenesis and oxidative phosphorylation (OXPHOS) process, yet its critical role in pan-cancer remains unclear. Materials and Methods: In this paper, the expression levels of PPRC1 in different tumor tissues and corresponding adjacent normal tissues were analyzed based on four databases: The Genotype-Tissue Expression (GTEx), Cancer Cell Line Encyclopedia (CCLE), The Cancer Genome Atlas (TCGA), and Tumor Immune Estimation Resource (TIMER). Meanwhile, the prognostic value of PPRC1 was inferred using Kaplan–Meier plotter and forest-plot studies. In addition, the correlation between PPRC1 expression and tumor immune cell infiltration, immune checkpoints, and the tumor-stemness index was analyzed using TCGA and TIMER databases. Results: According to our findings, the expression level of PPRC1 was found to be different in different cancer types and there was a positive correlation between PPRC1 expression and prognosis in several tumor types. In addition, PPRC1 expression was found to be significantly correlated with immune cell infiltration, immune checkpoints, and the tumor-stemness index in both ovarian and hepatocellular carcinoma. Conclusions: PPRC1 demonstrated promising potential as a novel biomarker in pan-cancer due to its potential association with immune cell infiltration, expression of immune checkpoints, and the tumor-stemness index. Full article

(This article belongs to the Special Issue Identification of Immunotherapy-Related Biomarkers for Gynecological Cancers)

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13 pages, 4132 KiB

Open AccessArticle

Infiltration by Intratumor and Stromal CD8 and CD68 in Cervical Cancer

by Polina Dimitrova, Mariela Vasileva-Slaveva, Velizar Shivarov, Ihsan Hasan and Angel Yordanov

Medicina 2023, 59(4), 728; https://0-doi-org.brum.beds.ac.uk/10.3390/medicina59040728 - 07 Apr 2023

Cited by 1 | Viewed by 1573

Abstract

Background and Objectives: The tumor microenvironment (TME) plays a major role in neoplastic development. Various types of cells can be found in the TME. These cells can be classified into two groups, immunosuppressive and immunostimulatory types, depending on the function they perform in the antitumor immune response (IR). By interacting both with each other and with tumor cells, different immune mechanisms are activated or inhibited, which can suppress or promote the development and progression of cervical cancer (CC). Our aim was to investigate some of the main components of the cellular immune response in TME—tumor-infiltrating cytotoxic T cells (Tc, CD8+) and tumor-associated macrophages (TAMs, CD68+)—in patients with CC. Materials and Methods: We analyzed 72 paraffin-embedded tumor tissues of patients diagnosed and treated at Medical University Pleven, Bulgaria. Patients were classified according to the 2018 FIGO (International Federation of Gynaecology and Obstetrics) classification. From each patient, we selected one histological slide with hematoxylin eosin staining. In a microscopic evaluation, CD8+ T lymphocytes and CD68+-positive macrophages were counted in the tumor and stroma of five randomly selected fields at ×40 magnification (HPF). We analyzed the relationship between intratumoral and stromal CD8 and CD68 expression and FIGO stage and N status. Results: There was no significant association between the expression levels of intratumoral and stromal CD68+ cells in the different FIGO stages and according to the lymph nodes’ involvement. For CD8+ cells, the association of stromal infiltration was also not found, but T intratumor infiltration was associated with a higher FIGO stage, despite the fact that the results did not reach significance (p = 0.063, Fisher test). Intratumoral CD8+ cells were significantly associated with positive N status, (p = 0.035). Discussion: The separation of tumor-infiltrating cytotoxic T cells and tumor-associated macrophages into intratumoral and stromal is inconsequential. In our study, the level of infiltration of CD68+ cells in tumors and stromata was not significantly associated with tumor progression or lymph node involvement. The results were different for CD8+ cells, in which levels of infiltration were associated with lymph nodes’ statuses. Conclusions: The separate evaluation of CD68+ immune cells in the TME as intratumoral and stromal is not beneficial for defining prognoses, since the presence of these cells is not associated with the patient’s stage. In our study, the presence of CD8+ cells was significantly associated with lymph node metastases. The prognostic value of the obtained results can be enriched with an additional study of the lymphocyte phenotype, including B and other subtypes of T lymphocytes, NK cells, as well as molecules involved in the immune response, such as HLA subtypes. Full article

(This article belongs to the Special Issue Identification of Immunotherapy-Related Biomarkers for Gynecological Cancers)

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9 pages, 1468 KiB

Open AccessArticle

A Clinical Prediction Model of Overall Survival for Patients with Cervical Cancer Aged 25–69 Years

by Wenli Fan, Qin Lu and Guokun Liu

Medicina 2023, 59(3), 600; https://0-doi-org.brum.beds.ac.uk/10.3390/medicina59030600 - 17 Mar 2023

Cited by 4 | Viewed by 1364

Abstract

Aims: This study aims to develop a prediction tool for the overall survival of cervical cancer patients. Methods: We obtained 4116 female patients diagnosed with cervical cancer aged 25–69 during 2008–2019 from the Surveillance, Epidemiology, and End Results Program. The overall survival between groups was illustrated by the Kaplan–Meier method and compared by a log-rank test adjusted by the Bonferroni–Holm method. We first performed the multivariate Cox regression analysis to evaluate the predictive values of the variables. A prediction model was created using cox regression based on the training set, and the model was presented as a nomogram. The proposed nomogram was designed to predict the 1-year, 3-year, and 5-year overall survival of patients with cervical cancer. Besides the c-index, time-dependent receiver operating curves, and calibration curves were created to evaluate the accuracy of the nomogram at the timepoint of one year, three years, and five years. Results: With a median follow-up of 54 (28, 92) months, 1045 (25.39%) patients were deceased. Compared with alive individuals, the deceased were significantly older and the primary site was more likely to be the cervix uteri site, large tumor size, higher grade, and higher combined summary stage (all p values < 0.001). In the multivariate Cox regression, age at diagnosis, race, tumor size, grade, combined summary stage, pathology, and surgery treatment were significantly associated with the all-cause mortality for patients with cervical cancer. The proposed nomogram showed good performance with a C-index of 0.82 in the training set. The 1-year, 3-year, and 5-year areas under the curves (with 95% confidence interval) of the receiver operating curves were 0.88 (0.84, 0.91), 0.84 (0.81, 0.87), and 0.83 (0.80, 0.86), respectively. Conclusions: This study develops a prediction nomogram model for the overall survival of cervical cancer patients with a good performance. Further studies are required to validate the prediction model further. Full article

(This article belongs to the Special Issue Identification of Immunotherapy-Related Biomarkers for Gynecological Cancers)

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12 pages, 1620 KiB

Open AccessArticle

Correlation of INHBA Overexpression with Pathological Features, Antitumor Immune Response and Clinical Prognosis in Cervical Cancer

by Lin Zeng and Xingwang Sun

Medicina 2023, 59(3), 495; https://0-doi-org.brum.beds.ac.uk/10.3390/medicina59030495 - 02 Mar 2023

Cited by 1 | Viewed by 1481

Abstract

Background and Objectives: Cervical cancer (CC) is a malignant tumor occurring in the cervical epithelium, which is one of the most common cancer-caused deaths in females. Inhibin β A (INHBA) is the most widely expressed biomarker of the transforming growth factor-β (TGF-β) family in tumor cells, and has predictive value for tumor development and prognosis. In this study, the expression of INHBA in CC tissue was examined to analyze the relationship between INHBA expression and pathological characteristics, anti-tumor immune response and clinical prognosis of CC. In addition, the factors affecting the prognosis of CC patients were explored. Materials and Methods: 84 patients with CC, who underwent surgical resection in our hospital from March 2016 to August 2017, were retrospectively picked. The tumor tissues and normal adjacent tissues of patients with CC were collected, and the expression of INHBA in CC tissues and adjacent tissues was detected using immunohistochemistry (IHC). The relationship between INHBA expression and clinicopathological characteristics of CC patients was analyzed. The relationship between INHBA expression and clinical prognosis was analyzed using the Kaplan–Meier (K–M) survival curve. The levels of anti-tumor immune-response-related factors (interferon-γ (IFN-γ), interleukin-10 (IL-10), tumor necrosis factor- α (TNF-α) and IL-2) were evaluated in patients with negative and positive expressions of INHBA. The patients were followed up for 60 months and were graded as a good prognosis group and poor prognosis group according to whether the patients died or had recurrence and metastasis. Relevant factors affecting the prognosis of the patients were analyzed. Results: INHBA was localized in the cytoplasm of cancer tissues. The positive expression rate in cancer tissues was 67.86%, which was much higher than the 28.57% in normal adjacent tissues (p < 0.05). Expression of INHBA was closely correlated with Federation of Gynecology and Obstetrics (FIGO) staging, differentiation and lymph node metastasis (p < 0.05). Compared with INHBA-negative expression group, the contents of IFN-γ, TNF-α and IL-2 were much lower, while the level of IL-10 was strongly elevated in the INHBA-positive expression group (p < 0.01). Eighty-four patients with CC were followed up for 36 months. The K–M survival curve showed that the patients with a positive expression of INHBA had a significantly shorter survival period than the patients with a negative expression of INHBA (p < 0.05). There were significant differences in FIGO staging, differentiation, lymph node metastasis and INHBA expression between patients with a good prognosis and poor prognosis (p < 0.05). Logistic regression analysis showed that FIGO stage, differentiation degree, lymph node metastasis and INHBA were the factors influencing the poor prognosis of patients with CC (p < 0.05). Conclusion: The abnormally high expression of INHBA in patients with CC was related to the pathological characteristics, anti-tumor immune response and survival time, and leaded to a poor prognosis. It was speculated that INHBA exerted an important reference role in tumor invasion and clinical prognosis evaluation, which could act as a new target for anti-tumor treatment of CC. Full article

(This article belongs to the Special Issue Identification of Immunotherapy-Related Biomarkers for Gynecological Cancers)

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18 pages, 5705 KiB

Open AccessArticle

by Tiankuo Luan, Daqiang Song, Jiazhou Liu, Yuxian Wei, Rui Feng, Xiaoyu Wang, Lin Gan, Jingyuan Wan, Huiying Fang, Hongzhong Li and Xia Gong

Medicina 2023, 59(3), 424; https://0-doi-org.brum.beds.ac.uk/10.3390/medicina59030424 - 21 Feb 2023

Viewed by 1659

Abstract

Background and Objectives. The prognostic role of adjacent nontumor tissue in patients with breast cancer (BC) is still unclear. The activity changes in immunologic and hallmark gene sets in normal tissues adjacent to BC may play a crucial role in predicting the prognosis of BC patients. The aim of this study was to identify BC subtypes and ribosome-associated prognostic genes based on activity changes of immunologic and hallmark gene sets in tumor and adjacent nontumor tissues to improve patient prognosis. Materials and Methods. Gene set variation analysis (GSVA) was applied to assess immunoreactivity changes in the overall sample and three immune-related BC subtypes were identified by non-negative matrix factorization (NMF). KEGG (Kyoto Encyclopedia of Genes and Genomes) and GO (Gene Ontology) analyses were after determining the prognostic gene set using the least absolute shrinkage and selection operator (LASSO) method. Ribosome-related genes were identified by PPI (protein-protein interaction) analysis, and finally a prognostic risk model was constructed based on the expression of five ribosomal genes (RPS18, RPL11, PRLP1, RPL27A, and RPL38). Results. A comprehensive analysis of immune and marker genomic activity changes in normal breast tissue and BC tissue identified three immune-related BC subtypes. BC subtype 1 has the best prognosis, and subtype 3 has the worst overall survival rate. We identified a prognostic gene set in nontumor tissue by the least absolute shrinkage and selection operator (LASSO) method. We found that the results of both KEGG and GO analyses were indistinguishable from those of ribosome-associated genes. Finally, we determined that genes associated with ribosomes exhibit potential as a reliable predictor of overall survival in breast cancer patients. Conclusions. Our research provides an important guidance for the treatment of BC. After a mastectomy, the changes in gene set activity of both BC tissues and the nontumor tissues adjacent to it should be thoroughly evaluated, with special attention to changes in ribosome-related genes in the nontumor tissues. Full article

(This article belongs to the Special Issue Identification of Immunotherapy-Related Biomarkers for Gynecological Cancers)

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21 pages, 9542 KiB

Open AccessArticle

Identification and Validation of the Anoikis-Related Gene Signature as a Novel Prognostic Model for Cervical Squamous Cell Carcinoma, Endocervical Adenocarcinoma, and Revelation Immune Infiltration

by Qin-Qin Jin, Jie Mei, Lin Hong, Rui Wang, Shuang-Yue Wu, Sen-Lin Wang, Xi-Ya Jiang, Yin-Ting Yang, Hui Yao, Wei-Yu Zhang, Yu-Ting Zhu, Jie Ying, Lu Tian, Guo Chen and Shu-Guang Zhou

Medicina 2023, 59(2), 358; https://0-doi-org.brum.beds.ac.uk/10.3390/medicina59020358 - 13 Feb 2023

Cited by 1 | Viewed by 1880

Abstract

Background and Objectives: Cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC) are malignant disorders with adverse prognoses for advanced patients. Anoikis, which is involved in tumor metastasis, facilitates the survival and separation of tumor cells from their initial site. Unfortunately, it is rarely studied, and in the literature, studies have only addressed the prognosis character of anoikis for patients with CESC. Materials and Methods: We utilized anoikis-related genes (ANRGs) to construct a prognostic signature in CESC patients that were selected from the Genecards and Harmonizome portals. Furthermore, we revealed the underlying clinical value of this signature for clinical maneuvers by providing clinical specialists with an innovative nomogram on the basis of ANRGs. Finally, we investigated the immune microenvironment and drug sensitivity in different risk groups. Results: We screened six genes from fifty-eight anoikis-related differentially expressed genes in the TCGA-CESC cohort, and we constructed a prognostic signature. Then, we built a nomogram combined with CESC clinicopathological traits and risk scores, which demonstrated that this model may improve the prognosis of CESC patients in clinical therapy. Next, the prognostic risk scores were confirmed to be an independent prognostic indicator. Additionally, we programmed a series of analyses, which included immune infiltration analysis, therapy-related analysis, and GSVA enrichment analysis, to identify the functions and mechanisms of the prognostic models during the progression of cancer in CESC patients. Finally, we performed quantitative reverse transcription polymerase chain reaction (qRT-PCR) to verify the six ANRGs. Conclusions: The present discovery verified that the predictive 6-anoikis-related gene (6-ANRG) signature and nomogram serve as imperative factors that might notably impact a CESC patient’s prognosis, and they may be able to provide new clinical evidence to assume the role of underlying biological biomarkers and thus become indispensable indicators for prospective diagnoses and advancing therapy. Full article

(This article belongs to the Special Issue Identification of Immunotherapy-Related Biomarkers for Gynecological Cancers)

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