Cell-free DNA analysis in current cancer clinical trials: a review

Cell-free DNA (cfDNA) analysis represents a promising method for the diagnosis, treatment selection and clinical follow-up of cancer patients. Although its general methodological feasibility and usefulness has been demonstrated, several issues related to standardisation and technical validation must be addressed for its routine clinical application in cancer. In this regard, most cfDNA clinical applications are still limited to clinical trials, proving its value in several settings. In this paper, we review the current clinical trials involving cfDNA/ctDNA analysis and highlight those where it has been useful for patient stratification, treatment follow-up or development of novel approaches for early diagnosis. Our query included clinical trials, including the terms ‘cfDNA’, ‘ctDNA’, ‘liquid biopsy’ AND ‘cancer OR neoplasm’ in the FDA and EMA public databases. We identified 1370 clinical trials (FDA = 1129, EMA = 241) involving liquid-biopsy analysis in cancer. These clinical trials show promising results for the early detection of cancer and confirm cfDNA as a tool for real-time monitoring of acquired therapy resistance, accurate disease-progression surveillance and improvement of treatment, situations that result in a better quality of life and extended overall survival for cancer patients.

Role of ctDNA in Breast Cancer

Breast cancer is currently classified by immunohistochemistry. However, technological advances in the detection of circulating tumor DNA (ctDNA) have made new options available for diagnosis, classification, biological knowledge, and treatment selection. Breast cancer is a heterogeneous disease and ctDNA can accurately reflect this heterogeneity, allowing us to detect, monitor, and understand the evolution of the disease. Breast cancer patients have higher levels of circulating DNA than healthy subjects, and ctDNA can be used for different objectives at different timepoints of the disease, ranging from screening and early detection to monitoring for resistance mutations in advanced disease. In early breast cancer, ctDNA clearance has been associated with higher rates of complete pathological response after neoadjuvant treatment and with fewer recurrences after radical treatments. In metastatic disease, ctDNA can help select the optimal sequencing of treatments. In the future, thanks to new bioinformatics tools, the use of ctDNA in breast cancer will become more frequent, enhancing our knowledge of the biology of tumors. Moreover, deep learning algorithms may also be able to predict breast cancer evolution or treatment sensitivity. In the coming years, continued research and the improvement of liquid biopsy techniques will be key to the implementation of ctDNA analysis in routine clinical practice.

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.

Rational Development of Liquid Biopsy Analysis in Renal Cell Carcinoma

Renal cell carcinoma (RCC) is known for its variable clinical behavior and outcome, including heterogeneity in developing relapse or metastasis. Recent data highlighted the potential of somatic mutations as promising biomarkers for risk stratification in RCC. Likewise, the analysis of circulating tumor DNA (ctDNA) for such informative somatic mutations (liquid biopsy) is considered an important advance for precision oncology in RCC, allowing to monitor molecular disease evolution in real time. However, our knowledge about the utility of ctDNA analysis in RCC is limited, in part due to the lack of RCC-appropriate assays for ctDNA analysis. Here, by interrogating different blood compartments in xenograft models, we identified plasma cell-free (cf) DNA and extracellular vesicles (ev) DNA enriched for RCC-associated ctDNA. Additionally, we developed sensitive targeted sequencing and bioinformatics workflows capable of detecting somatic mutations in RCC-relevant genes with allele frequencies ≥ 0.5%. Applying this assay to patient-matched tumor and liquid biopsies, we captured tumor mutations in cf- and ev-DNA fractions isolated from the blood, highlighting the potentials of both fractions for ctDNA analysis. Overall, our study presents an RCC-appropriate sequencing assay and workflow for ctDNA analysis and provides a proof of principle as to the feasibility of detecting tumor-specific mutations in liquid biopsy in RCC patients.

Dynamic recurrence risk and adjuvant chemotherapy benefit prediction by ctDNA in resected NSCLC

Accurately evaluating minimal residual disease (MRD) could facilitate early intervention and personalized adjuvant therapies. Here, using ultradeep targeted next-generation sequencing (NGS), we evaluate the clinical utility of circulating tumor DNA (ctDNA) for dynamic recurrence risk and adjuvant chemotherapy (ACT) benefit prediction in resected non-small cell lung cancer (NSCLC). Both postsurgical and post-ACT ctDNA positivity are significantly associated with worse recurrence-free survival. In stage II-III patients, the postsurgical ctDNA positive group benefit from ACT, while ctDNA negative patients have a low risk of relapse regardless of whether or not ACT is administered. During disease surveillance, ctDNA positivity precedes radiological recurrence by a median of 88 days. Using joint modeling of longitudinal ctDNA analysis and time-to-recurrence, we accurately predict patients’ postsurgical 12-month and 15-month recurrence status. Our findings reveal longitudinal ctDNA analysis as a promising tool to detect MRD in NSCLC, and we show pioneering work of using postsurgical ctDNA status to guide ACT and applying joint modeling to dynamically predict recurrence risk, although the results need to be further confirmed in future studies.

Circulating Tumor DNA and Minimal Residual Disease (MRD) in Solid Tumors: Current Horizons and Future Perspectives

Circulating tumor DNA (ctDNA) is cell-free DNA (cfDNA) fragment in the bloodstream that originates from malignant tumors or circulating tumor cells. Recently, ctDNA has emerged as a promising non-invasive biomarker in clinical oncology. Analysis of ctDNA opens up new avenues for individualized cancer diagnosis and therapy in various types of tumors. Evidence suggests that minimum residual disease (MRD) is closely associated with disease recurrence, thus identifying specific genetic and molecular alterations as novel MRD detection targets using ctDNA has been a research focus. MRD is considered a promising prognostic marker to identify individuals at increased risk of recurrence and who may benefit from treatment. This review summarizes the current knowledge of ctDNA and MRD in solid tumors, focusing on the potential clinical applications and challenges. We describe the current state of ctDNA detection methods and the milestones of ctDNA development and discuss how ctDNA analysis may be an alternative for tissue biopsy. Additionally, we evaluate the clinical utility of ctDNA analysis in solid tumors, such as recurrence risk assessment, monitoring response, and resistance mechanism analysis. MRD detection aids in assessing treatment response, patient prognosis, and risk of recurrence. Moreover, this review highlights current advancements in utilizing ctDNA to monitor the MRD of solid tumors such as lung cancer, breast cancer, and colon cancer. Overall, the clinical application of ctDNA-based MRD detection can assist clinical decision-making and improve patient outcomes in malignant tumors.

Cell-Free Tumor DNA Dominant Clone Allele Frequency (DCAF) Is Associated With Poor Outcomes In Advanced Biliary Cancers Treated With Platinum-Based Chemotherapy

PURPOSE: This investigation sough to evaluate the prognostic value of pre-treatment ctDNA in metastatic biliary tract cancers (BTC) treated with platinum based first-line chemotherapy treatment. METHODS: We performed a retrospective analysis of 67 patients who underwent ctDNA testing before platinum-based chemotherapy for first-line treatment for metastatic BTC. For analysis we considered the detected gene with highest variant allele frequency (VAF) as the dominant clone allele frequency (DCAF). Results of ctDNA analysis were correlated with patients demographics, progression-free survival (PFS) and overall survival (OS). RESULTS: The median age of patients was 67 years (27-90). 54 (80.6%) of 67 patients evaluated had intrahepatic cholangiocarcinoma; seven had extrahepatic cholangiocarcinoma and six gallbladder cancers. 46 (68.6%) of the patients were treated with cisplatin plus gemcitabine, 16.4% of patients received gemcitabine and other platinum (carboplatin or oxaliplatin) combinations while 15% of patients were treated on a clinical trial with gemcitabine and cisplatin plus additional agents (CX4945, PEGPH20 or nab-paclitaxel). TP53, KRAS, FGFR2, ARID1A, STK11 and IDH1 were the genes with highest frequency as DCAF. Median DCAF was 3% (0-97%). DCAF >3% was associated with worse OS (median OS: 10.8 vs. 18.8 months, p=0.032). Stratifying DCAF in quartiles, DCAF>10% was significantly related to worse PFS (median PFS: 3 months, p=0.014) and worse OS (median OS: 7.0 months, p=0.001). Each 1% increase in ctDNA was associated with a hazard ratio of 13.1 in OS when adjusting for subtypes, metastatic sites, size of largest tumor, age, sex, and CA19-9. CONCLUSION: DCAF at diagnosis of advanced BTC can stratify patients who have worse outcomes when treated with upfront platinum-based chemotherapy. Each increase in %ctDNA decrease survival probabilities.

Next Generation Sequencing of Tumor and Matched Plasma Samples: Identification of Somatic Variants in ctDNA From Ovarian Cancer Patients

Genetic testing to detect somatic alterations is usually performed on formalin-fixed paraffin-embedded tumor samples. However, tumor molecular profiling through ctDNA analysis may be particularly interesting with the emergence of targeted therapies for ovarian cancer (OC), mainly when tumor is not available and biopsy is not viable, also allowing representation of multiple neoplastic subclones. Using a custom panel of 27 genes, next-generation sequencing (NGS) was performed on tumor and matched plasma samples from 96 OC patients, which were combined in two groups (treatment naive and post-treatment). Overall, at least one somatic variant present in the tumor sample was also detected in the matched plasma sample in 35.6% of the patients, a percentage that increased to 69.6% of the treatment naive patients and 83.3% of those with stage IV disease, showing the potential of ctDNA analysis as an alternative to identify somatic variants in these patients, namely those that have predictive value for targeted therapy. In fact, of the two treatment-naive patients with somatic BRCA1 variants identified in tumor samples, in one of them we detected in ctDNA a BRCA1 somatic variant that was present in the tumor with a VAF of 53%, but not in the one that had a VAF of 5.4%. We also showed that ctDNA analysis has a complementary role to molecular unraveling of inter- and intra-tumor heterogeneity, as exemplified by one patient diagnosed with bilateral OC in which different somatic variants from both tumors were detected in ctDNA. Interestingly, as these bilateral tumors shared a rare combination of two of the three variants identified in ctDNA, we could conclude that these morphologically different tumors were clonally related and not synchronous independent neoplasias. Moreover, in the post-treatment group of patients with plasma samples collected after surgery, those with detectable somatic variants had poor prognosis when compared with patients with no detectable somatic variants, highlighting the potential of ctDNA analysis to identify patients at higher risk of recurrence. Concluding, this study demonstrated that somatic variants can be detected in plasma samples of a significant proportion of OC patients, supporting the use of NGS-based ctDNA testing for noninvasive tumor molecular profiling and to stratify patients according to prognosis.