Comprehensive Gene Mutation Profiling of Circulating Tumor DNA in Ovarian Cancer: Its Pathological and Prognostic Impact

Radiation therapy with phenotypic medicine: towards N-of-1 personalization

In current clinical practice, radiotherapy (RT) is prescribed as a pre-determined total dose divided over daily doses (fractions) given over several weeks. The treatment response is typically assessed months after the end of RT. However, the conventional one-dose-fits-all strategy may not achieve the desired outcome, owing to patient and tumor heterogeneity. Therefore, a treatment strategy that allows for RT dose personalization based on each individual response is preferred. Multiple strategies have been adopted to address this challenge. As an alternative to current known strategies, artificial intelligence (AI)-derived mechanism-independent small data phenotypic medicine (PM) platforms may be utilized for N-of-1 RT personalization. Unlike existing big data approaches, PM does not engage in model refining, training, and validation, and guides treatment by utilizing prospectively collected patient's own small datasets. With PM, clinicians may guide patients' RT dose recommendations using their responses in real-time and potentially avoid over-treatment in good responders and under-treatment in poor responders. In this paper, we discuss the potential of engaging PM to guide clinicians on upfront dose selections and ongoing adaptations during RT, as well as considerations and limitations for implementation. For practicing oncologists, clinical trialists, and researchers, PM can either be implemented as a standalone strategy or in complement with other existing RT personalizations. In addition, PM can either be used for monotherapeutic RT personalization, or in combination with other therapeutics (e.g. chemotherapy, targeted therapy). The potential of N-of-1 RT personalization with drugs will also be presented.

Circulating tumor DNA as a biomarker for predicting progression-free survival and overall survival in patients with epithelial ovarian cancer: a systematic review and meta-analysis

OBJECTIVES

Circulating tumor DNA (ctDNA) is emerging as a potential prognostic biomarker in multiple tumor types. However, despite the many studies available on small series of patients with ovarian cancer, a recent systematic review and meta-analysis is lacking. The objective of this study was to determine the association of ctDNA with progression-free-survival and overall survival in patients with epithelial ovarian cancer.

METHODS

An electronic search was conducted using PubMed (MEDLINE), Embase, CENTRAL (Cochrane Library), and CINAHL-Complete from January 2000 to September 15, 2023. To be included in the analysis the studies had to meet the following pre-specified inclusion criteria: (1) evaluable ctDNA; (2) progression-free-survival and overall survival reported as hazard ratio (HR); and (3) the patient population had epithelial ovarian cancer at the time of ctDNA detection. We evaluated the association of ctDNA with progression-free survival and overall survival. Secondary outcomes focused on sub-group analysis of genomic alterations and international Federation of Gynecology and Obstetrics (FIGO) stage.

RESULTS

A total of 26 studies reporting on 1696 patients with epithelial ovarian cancer were included. The overall concordance rate between plasma-based and tissue-based analyses was approximately 62%. We found that a high level of ctDNA in epithelial ovarian cancer was associated with worse progression-free survival (HR 5.31, 95% CI 2.14 to 13.17, p<0.001) and overall survival (HR 2.98, 95% CI 1.86 to 4.76, p<0.0001). The sub-group analysis showed a greater than threefold increase in the risk of relapse in patients with positive HOXA9 meth-ctDNA (HR 3.84, 95% CI 1.57 to 9.41, p=0.003).

CONCLUSIONS

ctDNA was significantly associated with worse progression-free survival and overall survival in patients with epithelial ovarian cancer. Further prospective studies are needed.

PROSPERO REGISTRATION NUMBER

CRD42023469390.

Serial Circulating Tumor DNA Analysis with a Tumor-Naïve Next-Generation Sequencing Panel Detects Minimal Residual Disease and Predicts Outcome in Ovarian Cancer

Circulating tumor DNA (ctDNA) may aid in personalizing ovarian cancer therapeutic options. Here, we aimed to assess the clinical utility of serial ctDNA testing using tumor-naïve, small-sized next-generation sequencing (NGS) panels. A total of 296 patients, including 201 with ovarian cancer and 95 with benign or borderline disease, were enrolled. Samples were collected at baseline (initial diagnosis or surgery) and every 3 months after that, resulting in a total of 811 blood samples. Patients received adjuvant therapy based on the current standard of care. Cell-free DNA was extracted and sequenced using an NGS panel of 9 genes: TP53, BRCA1, BRCA2, ARID1A, CCNE1, KRAS, MYC, PIK3CA, and PTEN. Pathogenic somatic mutations were identified in 69.2% (139/201) of patients with ovarian cancer at baseline but not in those with benign or borderline disease. Detection of ctDNA at baseline and/or at 6 months follow-up was predictive of progression-free survival (PFS). PFS was significantly poorer in patients with detectable pathogenic mutations at baseline that persisted at follow-up than in patients that converted from having detectable ctDNA at baseline to being undetectable at follow-up; survival did not differ between patients without pathogenic ctDNA mutations in baseline or follow-up samples and those that converted from ctDNA positive to negative. Disease recurrence was also detected earlier with ctDNA than with conventional radiologic assessment or CA125 monitoring. These findings demonstrate that serial ctDNA testing could effectively monitor patients and detect minimal residual disease, facilitating early detection of disease progression and tailoring of adjuvant therapies for ovarian cancer treatment.

SIGNIFICANCE

In ovarian cancer, serial circulating tumor DNA testing is a highly predictive marker of patient survival, with a significantly improved recurrence detection lead time compared with conventional monitoring tools.

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.

Preoperative ctDNA Levels Are Associated With Poor Overall Survival in Patients With Ovarian Cancer

BACKGROUND/AIM

Circulating tumor DNA (ctDNA), which is shed from cancer cells into the bloodstream, offers a potential minimally invasive approach for cancer diagnosis and monitoring. This research aimed to assess the preoperative ctDNA levels in ovarian tumors patients' plasma and establish correlations with clinicopathological parameters and patient prognosis.

PATIENTS AND METHODS

Tumor DNA was extracted from ovarian tumor tissue from 41 patients. Targeted sequencing using a panel of 127 genes recurrently mutated in cancer was performed to identify candidate somatic mutations in the tumor DNA. SAGAsafe digital PCR (dPCR) assays targeting the candidate mutations were used to measure ctDNA levels in patient plasma samples, obtained prior to surgery, to evaluate ctDNA levels in terms of mutant copy number/ml and variant allele frequency.

RESULTS

Somatic mutations were found in 24 tumor samples, 17 of which were from ovarian cancer patients. The most frequently mutated gene was TP53. Preoperative plasma ctDNA levels were detected in 14 of the 24 patients. With higher stage, plasma ctDNA mutant concentration increased (p for trend <0.001). The overall survival of cancer patients with more than 10 ctDNA mutant copies/ml in plasma was significantly worse (p=0.008).

CONCLUSION

Pre-operative ctDNA measurement in ovarian cancer patients' plasma holds promise as a predictive biomarker for tumor staging and prognosis.

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.

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.

Identification of TP53 mutations in circulating tumour DNA in high grade serous ovarian carcinoma using next generation sequencing technologies

Plasma circulating tumour DNA (ctDNA) has been suggested to be a viable biomarker of response to treatment in patients with high grade serous ovarian carcinoma (HGSOC). TP53 mutations are present in more than 90% of HGSOCs but somatic variants are distributed across all exonic regions of the gene, requiring next generation sequencing (NGS) technologies for mutational analysis. In this study, we compared the suitability of the Accel (Swift) and Oncomine (ThermoFisher) panels for identification of TP53 mutations in ctDNA of HGSOC patients (N = 10). Only 6 patients (60%) were found to have TP53 mutations using the ACCEL panel but the addition of molecular tags in the Oncomine panel improved ctDNA detection with at least one mutation detected in all cases (100%). Orthogonal validation of the 14 somatic variants found by Oncomine, using droplet digital PCR, confirmed 79% (11/14) of the identified mutations. Overall, the Oncomine panel with unique molecular identifiers (UMI) appears more useful for ctDNA analysis in HGSOC.

Targeted-sequence of normal urothelium and tumor of patients with non-muscle invasive bladder cancer

During tumorigenesis, certain tissues are colonized by mutant clones with oncogenic driver mutations as precancer lesions. These mutations can facilitate clonal expansion and may contribute to malignant transformation. The molecular features of low-grade non-muscle invasive bladder cancer (NMIBC) and high-grade bladder cancer are so distinct that they are thought to follow different evolutionary tumorigenesis pathways. Although NMIBC accounts for most bladder tumors, the somatic mutation patterns in “precancer” urothelium of patients with NMIBC remain unclear. Here, we analyzed specimens of normal urothelium and bladder tumors from patients with low-grade and high-grade NMIBC and investigated the genomic evolution of the cancer. Somatic mutations were analyzed using 50 oncogene-targeted sequences and droplet digital polymerase chain reaction for TERT promoter mutations. Somatic mutations in TERT promoter, FGFR3, and CDKN2A were characteristically identified in the normal urothelium of patients with NMIBC. These mutations, consistently identified in both tumor and normal specimens, likely affect clonal expansion during the malignant transformation of NMIBC. Though larger samples and comprehensive study are warranted to confirm our results, the difference in mutational landscape of the precancerous urothelium of patients with bladder cancer could offer deeper understandings of genomic evolution in bladder tumorigenesis.

Detection of ESR1 Mutations in Primary Tumors and Plasma Cell-Free DNA in High-Grade Serous Ovarian Carcinoma Patients

Simple Summary

In the present study we evaluated the frequency and the clinical relevance of ESR1 mutations in high-grade serous ovarian cancer (HGSOC). Drop-off droplet digital PCR (ddPCR) was first used to screen for ESR1 mutations in primary tumors (formalin-fixed paraffin-embedded, FFPEs) from HGSOC patients and plasma cell-free DNA (cfDNA) samples from advanced and metastatic ovarian cancer patients. We further used the recently developed ESR1-NAPA assay to detect individual ESR1 mutations in drop-off ddPCR-positive samples. We report for the first time the presence of ESR1 mutations in 15% of FFPEs and in 13.8% of plasma cfDNA samples from advanced and metastatic ovarian cancer patients.

Abstract

ESR1 mutations have been recently associated with resistance to endocrine therapy in metastatic breast cancer and their detection has led to the development and current evaluation of novel, highly promising therapeutic strategies. In ovarian cancer there have been just a few reports on the presence of ESR1 mutations. The aim of our study was to evaluate the frequency and the clinical relevance of ESR1 mutations in high-grade serous ovarian cancer (HGSOC). Drop-off droplet digital PCR (ddPCR) was first used to screen for ESR1 mutations in 60 primary tumors (FFPEs) from HGSOC patients and in 80 plasma cell-free DNA (cfDNA) samples from advanced and metastatic ovarian cancer patients. We further used our recently developed ESR1-NAPA assay to identify individual ESR1 mutations in drop-off ddPCR-positive samples. We report for the first time the presence of ESR1 mutations in 15% of FFPEs and in 13.8% of plasma cfDNA samples from advanced and metastatic ovarian cancer patients. To define the clinical significance of this finding, our results should be further validated in a large and well-defined cohort of ovarian cancer patients.

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.

Cell-free DNA methylation markers for differential diagnosis of hepatocellular carcinoma

BACKGROUND

Aberrant DNA methylation may offer opportunities in revolutionizing cancer screening and diagnosis. We sought to identify a non-invasive DNA methylation-based screening approach using cell-free DNA (cfDNA) for early detection of hepatocellular carcinoma (HCC).

METHODS

Differentially, DNA methylation blocks were determined by comparing methylation profiles of biopsy-proven HCC, liver cirrhosis, and normal tissue samples with high throughput DNA bisulfite sequencing. A multi-layer HCC screening model was subsequently constructed based on tissue-derived differentially methylated blocks (DMBs). This model was tested in a cohort consisting of 120 HCC, 92 liver cirrhotic, and 290 healthy plasma samples including 65 hepatitis B surface antigen-seropositive (HBsAg+) samples, independently validated in a cohort consisting of 67 HCC, 111 liver cirrhotic, and 242 healthy plasma samples including 56 HBsAg+ samples.

RESULTS

Based on methylation profiling of tissue samples, 2321 DMBs were identified, which were subsequently used to construct a cfDNA-based HCC screening model, achieved a sensitivity of 86% and specificity of 98% in the training cohort and a sensitivity of 84% and specificity of 96% in the independent validation cohort. This model obtained a sensitivity of 76% in 37 early-stage HCC (Barcelona clinical liver cancer [BCLC] stage 0-A) patients. The screening model can effectively discriminate HCC patients from non-HCC controls, including liver cirrhotic patients, asymptomatic HBsAg+ and healthy individuals, achieving an AUC of 0.957(95% CI 0.939-0.975), whereas serum α-fetoprotein (AFP) only achieved an AUC of 0.803 (95% CI 0.758-0.847). Besides detecting patients with early-stage HCC from non-HCC controls, this model showed high capacity for distinguishing early-stage HCC from a high risk population (AUC=0.934; 95% CI 0.905-0.963), also significantly outperforming AFP. Furthermore, our model also showed superior performance in distinguishing HCC with normal AFP (< 20ng ml-1) from high risk population (AUC=0.93; 95% CI 0.892-0.969).

CONCLUSIONS

We have developed a sensitive blood-based non-invasive HCC screening model which can effectively distinguish early-stage HCC patients from high risk population and demonstrated its performance through an independent validation cohort.

TRIAL REGISTRATION

The study was approved by the ethic committee of The Second Xiangya Hospital of Central South University (KYLL2018072) and Chongqing University Cancer Hospital (2019167). The study is registered at ClinicalTrials.gov(# NCT04383353 ).

Circulating tumor DNA: a noninvasive biomarker for tracking ovarian cancer

Ovarian cancer is the fifth leading cause of cancer-related mortality in women worldwide. Despite the development of technologies over decades to improve the diagnosis and treatment of patients with ovarian cancer, the survival rate remains dismal, mainly because most patients are diagnosed at a late stage. Traditional treatment methods and biomarkers such as cancer antigen-125 as a cancer screening tool lack specificity and cannot offer personalized combinatorial therapy schemes. Circulating tumor DNA (ctDNA) is a promising biomarker for ovarian cancer and can be detected using a noninvasive liquid biopsy. A wide variety of ctDNA applications are being elucidated in multiple studies for tracking ovarian carcinoma during diagnostic and prognostic evaluations of patients and are being integrated into clinical trials to evaluate the disease. Furthermore, ctDNA analysis may be used in combination with multiple "omic" techniques to analyze proteins, epigenetics, RNA, nucleosomes, exosomes, and associated immune markers to promote early detection. However, several technical and biological hurdles impede the application of ctDNA analysis. Certain intrinsic features of ctDNA that may enhance its utility as a biomarker are problematic for its detection, including ctDNA lengths, copy number variations, and methylation. Before the development of ctDNA assays for integration in the clinic, such issues are required to be resolved since these assays have substantial potential as a test for cancer screening. This review focuses on studies concerning the potential clinical applications of ctDNA in ovarian cancer diagnosis and discusses our perspective on the clinical research aimed to treat this daunting form of cancer.

Diagnostic and Prognostic Value of Circulating Cell-Free DNA for Cholangiocarcinoma

The analysis of cfDNA has been applied as a liquid biopsy in several malignancies. However, its value in the diagnosis and prognosis of cholangiocarcinoma (CCA) have not been well defined. We aimed to investigate the diagnostic and prognostic values of cfDNA level and tumor-specific mutation in circulating DNA (ctDNA) in CCA. The plasma cfDNA levels from 62 CCA patients, 33 benign biliary disease (BBD) patients and 30 normal controls were quantified by fluorescent assay. Targeted probe-based sequencing of 60 genes was applied for mutation profiling in 10 ctDNA samples and their corresponding treatment-naïve tissues. cfDNA levels in CCA were significantly higher than those in BBD and normal controls. We found that cfDNA levels at 0.2175 and 0.3388 ng/µL significantly discriminated CCA from healthy controls and BBD with 88.7 and 82.3% sensitivity and 96.7 and 57.6% specificity, respectively. cfDNA levels showed superior diagnostic efficacy in detecting CCA compared to CEA and CA19-9. ARID1A (30%), PBRM1 (30%), MTOR (30%), and FGFR3 (30%) mutations were the most common. Using nine frequently mutated genes in the ctDNA samples, the diagnostic accuracy of cfDNA sequencing was 90.8%, with 96.7% average sensitivity and 72.4% specificity. This study supports the use of cfDNA as a diagnosis and prognostic biomarker for CCA.

How Does Endometriosis Lead to Ovarian Cancer? The Molecular Mechanism of Endometriosis-Associated Ovarian Cancer Development

Numerous epidemiological and histopathological studies support the notion that clear cell and endometrioid carcinomas derive from ovarian endometriosis. Accordingly, these histologic types are referred to as "endometriosis-associated ovarian cancer" (EAOC). Although the uterine endometrium is also considered an origin of endometriosis, the molecular mechanism involved in transformation of the uterine endometrium to EAOC via ovarian endometriosis has not yet been clarified. Recent studies based on high-throughput sequencing technology have revealed that cancer-associated gene mutations frequently identified in EAOC may exist in the normal uterine endometrial epithelium and ovarian endometriotic epithelium. The continuum of genomic alterations from the uterine endometrium to endometriosis and EAOC has been described, though the significance of cancer-associated gene mutations in the uterine endometrium or endometriosis remains unclear. In this review, we summarize current knowledge regarding the molecular characteristics of the uterine endometrium, endometriosis, and EAOC and discuss the molecular mechanism of cancer development from the normal endometrium through endometriosis in an effort to prevent EAOC.