A prospective study on prediction of efficacy of preoperative chemotherapy for patients with liver metastases from colorectal cancer using liquid biopsy
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ABSTRACT:
DISEASE(S): Colorectal Cancer With Liver Metastasis
PROVIDER: 2661314 | ecrin-mdr-crc |
REPOSITORIES: ECRIN MDR
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Project description:Primary outcome(s): The correlation of the dose of ctDNA and exosome DNA during treatment and the survival.
| 2661312 | ecrin-mdr-crc
Project description:INTRODUCTION. Liquid biopsies are a minimally invasive collection of a patient body fluid sample. In oncology, they offer several advantages compared to traditional tissue biopsies. However, potential of this method in endometrial cancer (EC) remains poorly explored. We studied the utility of tumor educated platelets (TEPs) and circulating tumor DNA (ctDNA) for preoperative EC diagnosis, including histology determination. MATERIALS AND METHODS. TEPs from 297 subjects (53 EC patients, 40 patients with benign gynecologic conditions and 204 healthy women) were RNA-sequenced. DNA sequencing was performed in 519 primary tumor tissue samples and in16 plasma samples. Artificial intelligence was applied to sample classification. RESULTS. Platelet-dedicated classifier yielded AUC of 93.1% in test set when discriminating between healthy subjects and cancer patients. However, the discrimination between endometrial cancer and benign gynecologic conditions was relatively low, with AUC of 60.7%. ctDNA-dedicated classifier discriminated primary tumor tissue samples with AUC of 91.4% and ctDNA blood samples with AUC of 87.5%. CONCLUSIONS Liquid biopsies show potential in EC diagnosis. Both TEPs and ctDNA profiles coupled with artificial intelligence constitute a source of useful information. Further work, involving more cases, is warranted.
2021-12-01 | GSE184904 | GEO
Project description:The purpose of SIBYL is to generate clinical validity data for the ability of a future version of Guardant360 developed by Guardant Health to measure response to systemic therapy in patients with unresectable advanced solid tumors. It is necessary to collect clinical data points and treatment outcomes in order to demonstrate clinical validity for longitudinal monitoring with ctDNA and correlation of ctDNA dynamics with therapeutic response, as evaluated by standard methods, including RECIST 1.1 and CT scan measurements.
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Project description:Medulloblastoma (MB) is an embryonal tumor of the cerebellum and a highly malignant childhood brain tumor. Cell-free circulating tumor DNA (ctDNA) from the cerebrospinal fluid (CSF) of patients with brain tumors faithfully represent genomic alterations of brain tumors. Distinct epigenetic signatures among subgroups of MB allow us to detect epigenetic alterations in CSF to aid classify and guide therapy of MB tumors. Here, we evaluate DNA methylation and hydroxymethylation of ctDNA derived from small amount of CSF (200 µL) and matched tumor DNA from 3 MB patients. We find highly concordance of DNA methylation and hydroxymethylation between CSF ctDNA and tumor DNA, especially in CpG islands. Importantly, CSF ctDNA can mostly recapitulate the dynamic changes of DNA methylation and hydroxymehtylation in tumor species compared to healthy cerebellums. Those MB tumor signature CpGs’ DNA methylation status are recovered in CSF ctDNA can clearly distinguish MB subgroups by utilizing public large cohort data. We further identified potential diagnostic and prognostic DNA methylation markers in CSF ctDNA. Our results show that CSF ctNDA methylation and hydroxymethylation can be a minimal invasive method to assess epigenetic alterations of MB, which is complementary to current diagnoses of MB tumors.
2020-10-28 | GSE142241 | GEO
Project description:Primary outcome(s): Diagnostic accuracy of colorectal cancer by liquid biopsy
Study Design: Observational Study Model : Case-control, Time Perspective : Cross-sectional, Enrollment : 500, Biospecimen Retention : Collect & Archive- Sample with DNA, Biospecimen Description : Whole blood, colon tissue
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Project description:BackgroundThe American College of Radiology Breast Imaging Reporting and Data System (ACR BI-RADS) used with ultrasonography cannot guide the individual management of solid breast tumors, but preoperative core biopsy categories (CBCs) can. We aimed to use machine learning to analyze clinical and ultrasonic features for predicting CBCs and to aid in the development of a new ultrasound (US) imaging reporting system for solid tumors of the breast.MethodsThis retrospective study included women with solid breast tumors who underwent US-guided core needle biopsy from March 1, 2019, to December 31, 2019. All patients were randomly assigned to a training or validation cohort (7:3 ratio). CBC was predicted using 5 machine learning models: random forest (RF), support vector machine (SVM), k-nearest-neighbor (KNN), multilayer perceptron (MLP), and ridge regression (RR). In the validation cohort, the area under the curve (AUC) and accuracy were ascertained for every algorithm. Based on AUC values, the optimal algorithm was determined, and the features' importance was depicted.ResultsA total of 1,082 female patients were included (age range, 12-96 years; mean age ± standard deviation, 42.22±13.37 years). The proportion of the 4 CBCs was 4% (44/1,185) for the B1 group, 60% (714/1,185) for the B2 group, 5% (57/1,185) for the B3 group, and 31% (370/1,185) for the B5 group. In the validation cohort, AUCs of the optimal algorithm constructed RF were 0.78, 0.88, 0.64, and 0.92 for B1, B2, B3, and B5, respectively, with an accuracy of 0.82.ConclusionsMachine learning could strongly predict CBC, particularly in B2 and B5 categories of solid breast tumors, with RF being the optimal machine learning model.
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Project description:Methylome of tumor cell-free DNA (cfDNA) has emerged as a powerful non-invasive technique for cancer subtyping and prognosis. However, its application is frequently hampered by the quality and total cfDNA yield. Here we demonstrate the feasibility of very low-input cfDNA for whole-methylome and copy-number profiling studies using enzymatic conversion of unmethylated cysteines (EMSEQ) to better preserve DNA integrity. We demonstrate that cfDNA methylation of our cohort was comparable with in situ cohorts and built a model that accurately predict MYCN amplification or 11q deletion in validation cohorts. RASSF1A methylation precedes this divergent methylome signature, supporting common and different epigenetic origins. After stratification by 11q, eight CpG methylations show additional prognostic value and two reveal known preclinical targets (CSF1R, CCR7). Methylation in CSF1R and CCR7 associated with differential expression levels and poorer prognosis. Noteworthy, haploinsufficiency of genes located on 11q that repair DNA double-strand breaks display reduced expression by a mechanism independent of promoter methylation. Conclusions: RASSF1A is an early hypermethylation defect that may predispose to later genetic and epigenetic alterations specific to MYCN-amplified or 11q-deleted high-risk neuroblastomas. CSF1R and CCR7 hypermethylation are a hallmark of high-risk 11q-deleted neuroblastomas that could be exploited therapeutically with immunomodulators to override immunosupression and relapse. Our novel findings provide support for use of liquid biopsy as an optimal strategy to assess methylomes of neuroblastoma patients for a precision medicine approach.
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Project description:Identify DNA methylation change in retinoblastoma using aqueous humor cfDNA
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2020-01-03 | GSE111258 | GEO
Project description:Non-invasive detection of aberrant DNA methylation could provide invaluable biomarkers for earlier detection of triple negative breast cancer (TNBC) which could help clinicians for easier and more efficient treatment options. We evaluated genome-wide DNA methylation data derived from TNBC and normal breast tissues, peripheral blood of TNBC cases and controls, and reference samples of sorted blood and mammary cells. Differentially methylated regions (DMRs) between TNBC and normal breast tissues were stringently selected, verified, and externally validated. A machine learning algorithm was applied to select the top DMRs, which then were evaluated on plasma-derived circulating cell-free DNA (cfDNA) samples of TNBC patients and healthy controls. We identified 23 DMRs accounting for the methylation profile of blood cells and reference mammary cells and then selected six top DMRs for cfDNA analysis. We quantified un-/methylated copies of these DMRs by droplet digital PCR analysis in a plasma test set from TNBC patients and healthy controls and confirmed our findings obtained on tissues. Differential cfDNA methylation was confirmed in an independent validation set of plasma samples. A methylation score combining signatures of the top three DMRs overlapping with the SPAG6, LINC10606, and TBCD/ZNF750 genes had the best capability to discriminate TNBC patients from controls (AUC=0.74 in test set and AUC=0.77 in validation set). Our findings demonstrate the usefulness of cfDNA-based methylation signatures as non-invasive liquid biopsy markers for diagnosis of TNBC.
2022-11-23 | GSE207998 | GEO