Circulating tumor DNA: a noninvasive biomarker for tracking ovarian cancer

Clinical relevance of circulating tumor DNA in ovarian cancer: current issues and future opportunities

Ovarian cancer (OC) is the most lethal gynecologic malignancy worldwide. Due to the lack of effective screening and early detection strategies, many patients with OC are diagnosed with advanced disease, where treatment is rarely curative. Moreover, OC is characterized by high intratumor heterogeneity, which represents a major barrier to the development of effective treatments. Conventional tumor biopsy and blood-based biomarkers, such as cancer antigen 125 (CA125), have different limitations. Liquid biopsy has recently emerged as an attractive and promising area of investigation in oncology, due to its minimally invasive, safe, comprehensive, and real-time dynamic nature. Preliminary evidence suggests a potential role of liquid biopsy to refine OC management, by improving screening, early diagnosis, assessment of response to treatment, detection, and profiling of drug resistance. The current knowledge and the potential clinical value of liquid biopsy in OC is discussed in this review to provide an overview of the clinical settings in which its use might support and improve diagnosis and treatment.

Techniques, procedures, and applications in host genetic analysis

This chapter overviews genetic techniques' fundamentals and methodological features, including different approaches, analyses, and applications that have contributed to advancing health and disease. The aim is to describe laboratory methodologies and analyses employed to understand the genetic landscape of different biological contexts, from conventional techniques to cutting-edge technologies. Besides describing detailed aspects of the polymerase chain reaction (PCR) and derived types as one of the principles for many novel techniques, we also discuss microarray analysis, next-generation sequencing, and genome editing technologies such as transcription activator-like effector nucleases (TALENs) and the clustered regularly interspaced short palindromic repeats (CRISPR) and CRISPR-associated (Cas) systems. These techniques study several phenotypes, ranging from autoimmune disorders to viral diseases. The significance of integrating diverse genetic methodologies and tools to understand host genetics comprehensively and addressing the ethical, legal, and social implications (ELSI) associated with using genetic information is highlighted. Overall, the methods, procedures, and applications in host genetic analysis provided in this chapter furnish researchers and practitioners with a roadmap for navigating the dynamic landscape of host-genome interactions.

Current strategies for early epithelial ovarian cancer detection using miRNA as a potential tool

Ovarian cancer is one of the most aggressive and significant malignant tumor forms in the female reproductive system. It is the leading cause of death among gynecological cancers owing to its metastasis. Since its preliminary disease symptoms are lacking, it is imperative to develop early diagnostic biomarkers to aid in treatment optimization and personalization. In this vein, microRNAs, which are short sequence non-coding molecules, displayed great potential as highly specific and sensitive biomarker. miRNAs have been extensively advocated and proven to serve an instrumental part in the clinical management of cancer, especially ovarian cancer, by promoting the cancer cell progression, invasion, delayed apoptosis, epithelial-mesenchymal transition, metastasis of cancer cells, chemosensitivity and resistance and disease therapy. Here, we cover our present comprehension of the most up-to-date microRNA-based approaches to detect ovarian cancer, as well as current diagnostic and treatment strategies, the role of microRNAs as oncogenes or tumor suppressor genes, and their significance in ovarian cancer progression, prognosis, and therapy.

Unlocking the potential of oncology biomarkers: advancements in clinical theranostics

INTRODUCTION

Cancer biomarkers have revolutionized the field of oncology by providing valuable insights into tumor changes and aiding in screening, diagnosis, prognosis, treatment prediction, and risk assessment. The emergence of "omic" technologies has enabled biomarkers to become reliable and accurate predictors of outcomes during cancer treatment.

CONTENT

In this review, we highlight the clinical utility of biomarkers in cancer identification and motivate researchers to establish a personalized/precision approach in oncology. By extending a multidisciplinary technology-based approach, biomarkers offer an alternative to traditional techniques, fulfilling the goal of cancer therapeutics to find a needle in a haystack.

SUMMARY AND OUTLOOK

We target different forms of cancer to establish a dynamic role of biomarkers in understanding the spectrum of malignancies and their biochemical and molecular characterization, emphasizing their prospective contribution to cancer screening. Biomarkers offer a promising avenue for the early detection of human cancers and the exploration of novel technologies to predict disease severity, facilitating maximum survival and minimum mortality rates. This review provides a comprehensive overview of the potential of biomarkers in oncology and highlights their prospects in advancing cancer diagnosis and treatment.

Current Applications and Challenges of Next-Generation Sequencing in Plasma Circulating Tumour DNA of Ovarian Cancer

Circulating tumour DNA (ctDNA) facilitates longitudinal study of the tumour genome, which, unlike tumour tissue biopsies, globally reflects intratumor and intermetastatis heterogeneity. Despite its costs, next-generation sequencing (NGS) has revolutionised the study of ctDNA, ensuring a more comprehensive and multimodal approach, increasing data collection, and introducing new variables that can be correlated with clinical outcomes. Current NGS strategies can comprise a tumour-informed set of genes or the entire genome and detect a tumour fraction as low as 10-5. Despite some conflicting studies, there is evidence that ctDNA levels can predict the worse outcomes of ovarian cancer (OC) in both early and advanced disease. Changes in those levels can also be informative regarding treatment efficacy and tumour recurrence, capable of outperforming CA-125, currently the only universally utilised plasma biomarker in high-grade serous OC (HGSOC). Qualitative evaluation of sequencing shows that increasing copy number alterations and gene variants during treatment may correlate with a worse prognosis in HGSOC. However, following tumour clonality and emerging variants during treatment poses a more unique opportunity to define treatment response, select patients based on their emerging resistance mechanisms, like BRCA secondary mutations, and discover potential targetable variants. Sequencing of tumour biopsies and ctDNA is not always concordant, likely as a result of clonal heterogeneity, which is better captured in the plasma samples than it is in a large number of biopsies. These incoherences may reflect tumour clonality and reveal the acquired alterations that cause treatment resistance. Cell-free DNA methylation profiles can be used to distinguish OC from healthy individuals, and NGS methylation panels have been shown to have excellent diagnostic capabilities. Also, methylation signatures showed promise in explaining treatment responses, including BRCA dysfunction. ctDNA is evolving as a promising new biomarker to track tumour evolution and clonality through the treatment of early and advanced ovarian cancer, with potential applicability in prognostic prediction and treatment selection. While its role in HGSOC paves the way to clinical applicability, its potential interest in other histological subtypes of OC remains unknown.

Proteomic analysis of exosomes secreted during the epithelial-mesenchymal transition and potential biomarkers of mesenchymal high-grade serous ovarian carcinoma

BACKGROUND

The epithelial-mesenchymal transition (EMT) promotes cell signaling and morphology alterations, contributing to cancer progression. Exosomes, extracellular vesicles containing proteins involved in cell-cell communication, have emerged as a potential source of biomarkers for several diseases.

METHODS

Our aim was to assess the proteome content of exosomes secreted after EMT-induction to identify potential biomarkers for ovarian cancer classification. EMT was induced in the ovarian cancer cell line CAOV3 by treating it with EGF (10 ng/mL) for 96 h following 24 h of serum deprivation. Subsequently, exosomes were isolated from the supernatant using selective centrifugation after decellularization, and their characteristics were determined. The proteins present in the exosomes were extracted, identified, and quantified using Label-Free-Quantification (LFQ) via Liquid Chromatography-Tandem Mass Spectrometry (LC-MS/MS). To identify potential biomarkers, the obtained proteomic data was integrated with the TGGA database for mRNA expression using principal component analysis and a conditional inference tree.

RESULTS

The exosomes derived from CAOV3 cells exhibited similar diameter and morphology, measuring approximately 150 nm, regardless of whether they were subjected to EMT stimulation or not. The proteomic analysis of proteins from CAOV3-derived exosomes revealed significant differential regulation of 157 proteins, with 100 showing upregulation and 57 downregulation upon EMT induction. Further comparison of the upregulated proteins with the TCGA transcriptomic data identified PLAU, LAMB1, COL6A1, and TGFB1 as potential biomarkers of the mesenchymal HGSOC subtype.

CONCLUSIONS

The induction of EMT, the isolation of exosomes, and the subsequent proteomic analysis highlight potential biomarkers for an aggressive ovarian cancer subtype. Further investigation into the role of these proteins is warranted to enhance our understanding of ovarian cancer outcomes.

The role of inflammatory factors and T-cell subsets in the diagnosis of recurrence in epithelial ovarian cancer patients and the effect of olaparin treatment on them

BACKGROUND

The aim of the study is to investigate the role of serum inflammatory factors and T-cell subsets in the diagnosis of recurrence in epithelial ovarian cancer patients and the effect of olaparib on inflammatory factor and T-lymphocyte subsets in patients with recurrent epithelial ovarian cancer.

METHODS

In this study, 100 patients diagnosed as recurrent epithelial ovarian cancer in our hospital and 100 patients without recurrent epithelial ovarian cancer in the same period were selected. According to the treatment plan, the recurrent patients were divided into conventional therapy group (Paclitaxel and Carboplatin) and combined therapy group (Paclitaxel, Carboplatin, and olaparib). The levels of serum inflammatory factors were evaluated by enzyme-linked immunosorbent assay. The peripheral blood T-lymphocyte subsets in each group were detected by flow cytometry.

RESULTS

Compared with nonrecurrent patients, recurrent patients have higher serum interleukin-6 (IL-6) and tumor necrosis factor-α (TNF-α) levels (p < .05), and lower interferon-γ (IFN-γ) level and the CD4+/CD8+ ratio. After adjusting for confounding factors, the results showed that the serum IL-6, IFN-γ, and TNF-α levels were influencing factors of recurrence in epithelial ovarian cancer patients. The area under the receiver operating curve and the sensitivity of serum TNF-α in predicting ovarian cancer recurrence were higher than those of IL-6 and IFN-γ. After secondary chemotherapy and/or olaparib maintenance treatment, the IL-6 (p < .001) and TNF-α (p < .001) levels in combined therapy group were lower than those in the conventional therapy, whereas the IFN-γ level (p < .001), the CD4+ T-cell proportion (p = .0069) and the CD4+/CD8+ ratio (p = .0201) were higher than those in the conventional therapy.

CONCLUSION

The serum IL-6, TNF-α, and IFN-γ levels were closely related to the recurrence of ovarian cancer. Olaparib maintenance treatment can significantly decrease the IL-6 and TNF-α level, and increase IFN-γ level and the CD4+/CD8+ ratio in patients with recurrent ovarian cancer.

Potential applications of DNA methylation testing technology in female tumors and screening methods

DNA methylation is a common epigenetic modification, and the current commonly used methods for DNA methylation detection include methylation-specific PCR, methylation-sensitive restriction endonuclease-PCR, and methylation-specific sequencing. DNA methylation plays an important role in genomic and epigenomic studies, and combining DNA methylation with other epigenetic modifications, such as histone modifications, may lead to better DNA methylation. DNA methylation also plays an important role in the development of disease, and analyzing changes in individual DNA methylation patterns can provide individualized diagnostic and therapeutic solutions. Liquid biopsy techniques are also increasingly well established in clinical practice and may provide new methods for early cancer screening. It is important to find new screening methods that are easy to perform, minimally invasive, patient-friendly, and affordable. DNA methylation mechanisms are thought to have an important role in cancer and have potential applications in the diagnosis and treatment of female tumors. This review discussed early detection targets and screening methods for common female tumors such as breast, ovarian, and cervical cancers and discussed advances in the study of DNA methylation in these tumors. Although existing screening, diagnostic, and treatment modalities exist, the high morbidity and mortality rates of these tumors remain challenging.

Identification of potential key genes of TGF-beta signaling associated with the immune response and prognosis of ovarian cancer based on bioinformatics analysis

Background

TGF-beta signaling is a key regulator of immunity and multiple cellular behaviors in cancer. However, the prognostic and therapeutic role of TGF-beta signaling-related genes in ovarian cancer (OV) remains unexplored.

Methods

Data of OV used in the current study were sourced from TCGA and GEO databases. Consensus clustering was applied to classify OV patients into different clusters using TGF-beta signaling-related genes. Differentially expressed genes (DEGs) between different clusters were screened by the "limma" R package. Prognostic genes were screened from DEGs by univariate Cox regression, followed by the construction of the TGF-beta signaling-related score. The prognostic value of TGF-beta signaling-related score was evaluated in both training and testing OV cohorts. Moreover, the immune status, GSEA and therapeutic response between low- and high-score groups were performed to further reveal the potential mechanisms.

Results

By consensus clustering, OV patients were classified into two clusters with different tumor immune environments. After differential expression and univariate Cox regression analyses, GMPR, PIEZO1, EMP1, CXCL13, GADD45B, SORCS2, FOSL2, PODN, LYNX1 and SLC38A5 were selected as prognostic genes. Using PCA algorithm, the TGF-beta signaling-related score of OV patients was calculated based on prognostic genes. Then OV patients were divided into low- and high-TGF-beta signaling-related score groups. We observed that the two score groups had significantly different survivals, tumor immune environments and expressions of immune checkpoints. In addition, GSEA results showed that immune-related pathways and biological processes, like chemokine signaling pathway, TNF signaling pathway and T cell migration were significantly enriched in the low-score group. Moreover, patients in the low- and high-score groups had remarkably different sensitivity to chemo- and immunotherapy.

Conclusion

For the first time, our study identified ten prognostic genes associated with TGF-beta signaling, constructed a prognostic TGF-beta signaling-related score and investigated the effect of TGF-beta signaling-related score on OV immunity and therapy. These findings may enrich our knowledge of the TGF-beta signaling in OV prognosis and help to improve the prognosis prediction and treatment strategies in OV.

Advances in application of circulating tumor DNA in ovarian cancer

Ovarian cancer is the third most common gynecologic cancer worldwide and has the highest mortality rate among gynecologic cancers. Identifying timely and effective biomarkers at different stages of the disease is the key to improve the prognosis of ovarian cancer patients. Circulating tumor DNA (ctDNA) is a fragment of free DNA produced by tumor cells in the blood. Current techniques for detecting ctDNA mainly include quantitative polymerase chain reaction (PCR), targeted next-generation sequencing (NGS), and non-targeted NGS (such as whole exon or whole genome sequencing). As a non-invasive liquid biopsy technique, ctDNA has a good application prospect in the ovarian cancer diagnosis, monitoring of treatment response and efficacy evaluation, detection of reverse mutation and related medication guidance, and prognosis evaluation. This article reviews the advances in application of ctDNA in ovarian cancer.

An Overview: Genetic Tumor Markers for Early Detection and Current Gene Therapy Strategies

Genomic instability is considered a fundamental factor involved in any neoplastic disease. Consequently, the genetically unstable cells contribute to intratumoral genetic heterogeneity and phenotypic diversity of cancer. These genetic alterations can be detected by several diagnostic techniques of molecular biology and the detection of alteration in genomic integrity may serve as reliable genetic molecular markers for the early detection of cancer or cancer-related abnormal changes in the body cells. These genetic molecular markers can detect cancer earlier than any other method of cancer diagnosis, once a tumor is diagnosed, then replacement or therapeutic manipulation of these cancer-related abnormal genetic changes can be possible, which leads toward effective and target-specific cancer treatment and in many cases, personalized treatment of cancer could be performed without the adverse effects of chemotherapy and radiotherapy. In this review, we describe how these genetic molecular markers can be detected and the possible ways for the application of this gene diagnosis for gene therapy that can attack cancerous cells, directly or indirectly, which lead to overall improved management and quality of life for a cancer patient.

Plasma Thioredoxin Reductase as a Potential Biomarker for Gynecologic Cancer

BACKGROUND

According to previous literatures, plasma thioredoxin reductase (TrxR) level was significantly elevated in various malignant tumors and serve as a potential biomarker for diagnosis and prognostic prediction. However, there is little awareness of the clinical value of plasma TrxR in gynecologic malignancies. In the present study, we aim to evaluate the diagnostic accuracy of plasma TrxR in gynecologic cancer and explore its role in treatment surveillance.

METHODS

We retrospectively enrolled 134 patients with gynecologic cancer and 79 patients with benign gynecologic disease. The difference of plasma TrxR activity and tumor markers level between two groups was compared using Mann-Whitney U test. By detecting pretreatment and post-treatment level of TrxR and conventional tumor markers, we further assessed the change trend of them with the Wilcoxon signed-ranks test.

RESULTS

Compared with benign control [5.7 (5, 6.6) U/mL], statistically significant increase of TrxR activity was observed in gynecologic cancer group [8.4 (7.25, 9.825) U/mL] (P < .0001), regardless of age and stage. On the basis of receiver operating characteristic (ROC) curves, we found plasma TrxR shows the highest diagnostic efficacy for distinguishing malignancy with benign disease, with an area under the curve (AUC) of 0.823 (95% confidence interval [CI] = 0.767-0.878), in the whole cohort. Besides, patients receiving treatment previously [8 (6.5, 9) U/mL] had a decreased TrxR level relative to treatment-native patients [9.9 (8.6, 10.85) U/mL]. Furthermore, follow-up data showed that plasma TrxR level would be evidently decreased after two courses of antitumor therapy (P < .0001), which is consistent with the downward trend of conventional tumor markers.

CONCLUSION

Collectively, all these results demonstrated plasma TrxR is an effective parameter for gynecologic cancer diagnosis and concurrently acts as a promising biomarker for treatment response assessment.

The application of circulating tumor cell and cell-free DNA liquid biopsies in ovarian cancer

Ovarian cancer is the deadliest gynecological cancer. 70% of the cases are diagnosed at late stages with already developed metastases due to the absence of easily noticeable symptoms. Early-stage ovarian cancer has a good prognosis with a 5-year survival rate reaching 95%, hence the identification of effective biomarkers for early diagnosis is important. Advances in liquid biopsy-based methods can have a significant impact not just on the development of an efficient screening strategy, but also in clinical decision-making with additional molecular profiling and genetic alterations linked to therapy resistance. Despite the well-known advantages of liquid biopsy, there are still challenges that need to be addressed before its routine use in clinical practice. Various liquid biopsy-based biomarkers have been investigated in ovarian cancer; however, in this review, we are concentrating on the current use of cell-free DNA (cfDNA) and circulating tumor cells (CTCs) in disease management, focusing on their emerging importance in clinical practice. We also discuss the technical aspects of these workflows. The analysis of cfDNA is often chosen for the detection of mutations, copy number aberrations, and DNA methylation changes, whereas CTC analysis provides a unique opportunity to study whole cells, thus allowing DNA, RNA, and protein-based molecular profiling as well as in vivo studies. Combined solutions which merge the strengths of cfDNA and CTC approaches should be developed to maximize the potential of liquid biopsy technology.

Nectin-4 as Blood-Based Biomarker Enables Detection of Early Ovarian Cancer Stages

Ovarian cancer is the third most common gynecological malignancy and has the highest mortality rate. Owing to unspecific symptoms, ovarian cancer is not detected until an advanced stage in about two-thirds of cases. Therefore, it is crucial to establish reliable biomarkers for the early stages to improve the patients’ prognosis. The aim of this study is to investigate whether the ADAM17 substrates Nectin-4, Heparin-binding EGF-like growth factor (HB-EGF) and Amphiregulin (AREG) could function as potential tumor markers for ovarian cancer. In this study a set of 231 sera consisting of 131 ovarian cancer patients and 100 healthy age-matched controls were assembled. Nectin-4, HB-EGF and AREG levels of preoperatively collected sera were determined by enzyme-linked immunosorbent assay (ELISA). Our analysis revealed that Nectin-4 and HB-EGF were significantly increased compared to the age-matched control group (p < 0.0001, p = 0.016). Strikingly, significantly higher Nectin-4 and HB-EGF levels were detected in early-stage FIGO I/II (p <0.001; p = 0.025) compared to healthy controls. Eighty-four percent (16/19) of patients with low Ca-125 levels showed increased Nectin-4 levels. Our study proposes Nectin-4 and HB-EGF as promising blood-based biomarkers for the detection of early stages of ovarian cancer patients that would not have been detected by Ca-125.

BRCA Mutations in Ovarian and Prostate Cancer: Bench to Bedside

Simple Summary

DNA damage is one of the hallmarks of cancer. Epithelial ovarian cancer (EOC) —especially the high-grade serous subtype—harbors a defect in at least one DNA damage response (DDR) pathway. Defective DDR results from a variety of lesions affecting homologous recombination (HR) and nonhomologous end joining (NHEJ) for double strand breaks, base excision repair (BER), and nucleotide excision repair (NER) for single strand breaks and mismatch repair (MMR). Apart from the EOC, mutations in the DDR genes, such as BRCA1 and BRCA2, are common in prostate cancer as well. Among them, BRCA2 lesions are found in 12% of metastatic castration-resistant prostate cancers, but very rarely in primary prostate cancer. Better understanding of the DDR pathways is essential in order to optimize the therapeutic choices, and has led to the design of biomarker-driven clinical trials. Poly(ADP-ribose) polymerase (PARP) inhibitors are now a standard therapy for EOC patients, and more recently have been approved for the metastatic castration-resistant prostate cancer with alterations in DDR genes. They are particularly effective in tumours with HR deficiency.

Abstract

DNA damage repair (DDR) defects are common in different cancer types, and these alterations can be exploited therapeutically. Epithelial ovarian cancer (EOC) is among the tumours with the highest percentage of hereditary cases. BRCA1 and BRCA2 predisposing pathogenic variants (PVs) were the first to be associated with EOC, whereas additional genes comprising the homologous recombination (HR) pathway have been discovered with DNA sequencing technologies. The incidence of DDR alterations among patients with metastatic prostate cancer is much higher compared to those with localized disease. Genetic testing is playing an increasingly important role in the treatment of patients with ovarian and prostate cancer. The development of poly (ADP-ribose) polymerase (PARP) inhibitors offers a therapeutic strategy for patients with EOC. One of the mechanisms of PARP inhibitors exploits the concept of synthetic lethality. Tumours with BRCA1 or BRCA2 mutations are highly sensitive to PARP inhibitors. Moreover, the synthetic lethal interaction may be exploited beyond germline BRCA mutations in the context of HR deficiency, and this is an area of ongoing research. PARP inhibitors are in advanced stages of development as a treatment for metastatic castration-resistant prostate cancer. However, there is a major concern regarding the need to identify reliable biomarkers predictive of treatment response. In this review, we explore the mechanisms of DDR, the potential for genomic analysis of ovarian and prostate cancer, and therapeutics of PARP inhibitors, along with predictive biomarkers.

Mutation analysis of circulating tumor DNA and paired ascites and tumor tissues in ovarian cancer

Circulating tumor DNA (ctDNA) is one conventional type of liquid biopsy that can be collected to dynamically monitor disease status. However, its potential clinical value and concordance with ascites samples or tumor biopsy needs to be evaluated further for patients with ovarian cancer. Therefore, the present study compared the mutation profiles among ctDNA, paired tumor tissue and ascites samples to explore their possible clinical value in ovarian cancer. Targeted next-generation sequencing was used to screen for mutations in 18 peripheral blood samples, six paired ascites samples and eight paired tumor tissues collected from patients with ovarian cancer. Functional analyses were performed using public databases. WebGestalt was used to perform Gene Ontology and pathway enrichment analyses. The cBioPortal for Cancer Genomics was used to assess therapeutic targets. Chilibot and Search Tool for the Retrieval of Interacting Genes/Proteins were used to obtain key genes and their functional interactions. Comparative analysis was performed among the three types of samples using Venn diagram. A total of 104 cancer-associated mutant genes in ctDNA samples, 95 genes in tumor tissues and 44 genes in ascites samples were found. A cluster covering 10 genes, namely NOTCH2, NOTCH3, lysine methyltransferase 2A, PTEN, androgen receptor, DNA-activated protein kinase catalytic subunit, hepatocyte nuclear factor 1 homeobox A, SRC, insulin receptor substrate 2 and SRY-box transcription factor 10, was obtained by Chilibot analysis. This gene panel may have the potential to monitor metastasis and identify therapeutic targets in ovarian cancer. Taken together, the present study focused on the mutant genes in ctDNA, ascites and tumor tissues, and suggested that the integrated information of different samples could be examined to comprehensively reflect the mutational landscape in ovarian cancer. However, procedures and protocols to interpret and utilize the integrated information obtained from various forms of liquid biopsies will require optimization prior to their use for future clinical applications.