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

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.

Pharmacological reactivation of p53 in the era of precision anticancer medicine

p53, which is encoded by the most frequently mutated gene in cancer, TP53, is an attractive target for novel cancer therapies. Despite major challenges associated with this approach, several compounds that either augment the activity of wild-type p53 or restore all, or some, of the wild-type functions to p53 mutants are currently being explored. In wild-type TP53 cancer cells, p53 function is often abrogated by overexpression of the negative regulator MDM2, and agents that disrupt p53-MDM2 binding can trigger a robust p53 response, albeit potentially with induction of p53 activity in non-malignant cells. In TP53-mutant cancer cells, compounds that promote the refolding of missense mutant p53 or the translational readthrough of nonsense mutant TP53 might elicit potent cell death. Some of these compounds have been, or are being, tested in clinical trials involving patients with various types of cancer. Nonetheless, no p53-targeting drug has so far been approved for clinical use. Advances in our understanding of p53 biology provide some clues as to the underlying reasons for the variable clinical activity of p53-restoring therapies seen thus far. In this Review, we discuss the intricate interactions between p53 and its cellular and microenvironmental contexts and factors that can influence p53's activity. We also propose several strategies for improving the clinical efficacy of these agents through the complex perspective of p53 functionality.

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.

The cancer glycocode as a family of diagnostic biomarkers, exemplified by tumor-associated gangliosides

One unexploited family of cancer biomarkers comprise glycoproteins, carbohydrates, and glycolipids (the Tumor Glycocode).A class of glycolipid cancer biomarkers, the tumor-marker gangliosides (TMGs) are presented here as potential diagnostics for detecting cancer, especially at early stages, as the biological function of TMGs makes them etiological. We propose that a quantitative matrix of the Cancer Biomarker Glycocode and artificial intelligence-driven algorithms will expand the menu of validated cancer biomarkers as a step to resolve some of the challenges in cancer diagnosis, and yield a combination that can identify a specific cancer, in a tissue-agnostic manner especially at early stages, to enable early intervention. Diagnosis is critical to reducing cancer mortality but many cancers lack efficient and effective diagnostic tests, especially for early stage disease. Ideal diagnostic biomarkers are etiological, samples are preferably obtained via non-invasive methods (e.g. liquid biopsy of blood or urine), and are quantitated using assays that yield high diagnostic sensitivity and specificity for efficient diagnosis, prognosis, or predicting response to therapy. Validated biomarkers with these features are rare. While the advent of proteomics and genomics has led to the identification of a multitude of proteins and nucleic acid sequences as cancer biomarkers, relatively few have been approved for clinical use. The use of multiplex arrays and artificial intelligence-driven algorithms offer the option of combining data of known biomarkers; however, for most, the sensitivity and the specificity are below acceptable criteria, and clinical validation has proven difficult. One strategic solution to this problem is to expand the biomarker families beyond those currently exploited. One unexploited family of cancer biomarkers comprise glycoproteins, carbohydrates, and glycolipids (the Tumor Glycocode). Here, we focus on a family of glycolipid cancer biomarkers, the tumor-marker gangliosides (TMGs). We discuss the diagnostic potential of TMGs for detecting cancer, especially at early stages. We include prior studies from the literature to summarize findings for ganglioside quantification, expression, detection, and biological function and its role in various cancers. We highlight the examples of TMGs exhibiting ideal properties of cancer diagnostic biomarkers, and the application of GD2 and GD3 for diagnosis of early stage cancers with high sensitivity and specificity. We propose that a quantitative matrix of the Cancer Biomarker Glycocode and artificial intelligence-driven algorithms will expand the menu of validated cancer biomarkers as a step to resolve some of the challenges in cancer diagnosis, and yield a combination that can identify a specific cancer, in a tissue-agnostic manner especially at early stages, to enable early intervention.

Locally performed postoperative circulating tumour DNA testing performed during routine clinical care to predict recurrence of colorectal cancer

BACKGROUND

Identifying patients at high risk for colorectal cancer recurrence is essential for improving prognosis. In the postoperative period, circulating tumour DNA (ctDNA) has been demonstrated as a significant prognostic indicator of recurrence. These results have been obtained under the strict rigours of clinical trials, but not validated in a real-world setting using in-house testing. We report the outcomes of locally performed postoperative ctDNA testing conducted during routine clinical care and the association with the recurrence of colorectal cancer.

METHODS

We recruited 36 consecutive patients with newly diagnosed colorectal cancer between 2018 and 2020. Postoperative plasma samples were collected at the first outpatient review following resection. Tumour-informed ctDNA analysis was performed using droplet digital polymerase chain reaction or targeted next-generation sequencing.

RESULTS

At the time of surgery, there were 24 patients (66.7%) with localized cancer, nine (25%) with nodal spread, and three (8.3%) with metastatic disease. The median time from surgery to plasma sample donation was 22 days (IQR 20-28 days). At least one somatic mutation was identified in primary tumour tissue for 28 (77.8%) patients. Postoperative ctDNA was detected in five patients (13.9%). The median duration of follow-up was 32.0 months (IQR 27.2-38.1 months). Two patients (5.56%) developed metastatic recurrence. However, neither had detectable postoperative ctDNA. There were no instances of loco-regional recurrence.

CONCLUSION

Analysis of postoperative ctDNA testing can be performed locally, however this study did not reproduce the adverse association between detectable postoperative ctDNA and the development of colorectal cancer recurrence seen in clinical trials.

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.