Multicancer screening test based on the detection of circulating non haematological proliferating atypical cells
Ontology highlight
ABSTRACT:
SUBMITTER: Malara N
PROVIDER: S-EPMC10863189 | biostudies-literature | 2024 Jan
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:Improved biomarkers are needed for early cancer detection, risk stratification, treatment selection, and monitoring treatment response. Although proteins can be useful blood-based biomarkers, many have limited sensitivity or specificity for these applications. Long INterspersed Element-1 (LINE-1) open reading frame 1 protein (ORF1p) is a transposable element protein overexpressed in carcinomas and high-risk precursors during carcinogenesis with negligible expression in normal tissues, suggesting ORF1p could be a highly specific cancer biomarker. To explore ORF1p as a blood-based biomarker, we engineered ultrasensitive digital immunoassays that detect mid-attomolar (10-17 mol/L) ORF1p concentrations in plasma across multiple cancers with high specificity. Plasma ORF1p shows promise for early detection of ovarian cancer, improves diagnostic performance in a multianalyte panel, provides early therapeutic response monitoring in gastroesophageal cancers, and is prognostic for overall survival in gastroesophageal and colorectal cancers. Together, these observations nominate ORF1p as a multicancer biomarker with potential utility for disease detection and monitoring.SignificanceThe LINE-1 ORF1p transposon protein is pervasively expressed in many cancers and is a highly specific biomarker of multiple common, lethal carcinomas and their high-risk precursors in tissue and blood. Ultrasensitive ORF1p assays from as little as 25 μL plasma are novel, rapid, cost-effective tools in cancer detection and monitoring. See related commentary by Doucet and Cristofari, p. 2502. This article is featured in Selected Articles from This Issue, p. 2489.
| S-EPMC10773488 | biostudies-literature
Project description:BackgroundCancer screening trials have required large sample sizes and long time-horizons to demonstrate cancer mortality reductions, the primary goal of cancer screening. We examine assumptions and potential power gains from exploiting information from testing control-arm specimens, which we call the "intended effect" (IE) analysis that we explain in detail herein. The IE analysis is particularly suited to tests that can be conducted on stored specimens in the control arm, such as stored blood for multicancer detection (MCD) tests.MethodsWe simulated hypothetical MCD screening trials to compare power and sample size for the standard vs IE analysis. Under two assumptions that we detail herein, we projected the IE analysis for 3 existing screening trials (National Lung Screening Trial [NLST], Minnesota Colon Cancer Control Study [MINN-FOBT-A], and Prostate, Lung, Colorectal, Ovarian Cancer Screening Trial-colorectal component [PLCO-CRC]).ResultsCompared with the standard analysis for the 3 existing trials, the IE design could have reduced cancer-specific mortality P values 5-fold (NLST), 33-fold (MINN-FOBT-A), or 14 160-fold (PLCO-CRC) or, alternately, reduced sample size (90% power) by 26% (NLST), 48% (MINN-FOBT-A), or 59% (PLCO-CRC). For potential MCD trial designs requiring 100 000 subjects per arm to achieve 90% power for multicancer mortality for the standard analysis, the IE analysis achieves 90% power for only 37 500-50 000 per arm, depending on assumptions concerning control-arm test-positives.ConclusionsTesting stored specimens in the control arm of screening trials to conduct the IE analysis could substantially increase power to reduce sample size or accelerate trials and could provide particularly strong power gains for MCD tests.
| S-EPMC11308171 | biostudies-literature
Project description:BackgroundThe NHS-Galleri Trial has demonstrated feasibility of a trial design in which all participants provide a "sample" for screening, but only samples from the intervention arm are tested and acted upon during the trial. We assessed the efficiency of analysis methods when the control arm may be retrospectively tested at the time of analysis.MethodsAnalyses considered were (1) the traditional method (random allocation, with all events included), (2) the "intended-effect" method (nested in those individuals who tested positive in both arms and all events therein), and (3) the targeted method (by random allocation but with an endpoint "test-positive event"). These methods are compared using approximate statistical methods and scenario analysis.ResultsProvided that the number of individuals who die from cancer after a test-positive sample is a small fraction of the total number who die from cancer, intended-effect and targeted analyses require a much smaller sample size to evaluate cancer-specific mortality than the traditional approach. Intended-effect analysis has a smaller sample size requirement than targeted analysis does. This gain is substantial only when the risk of cancer death in individuals testing positive is high.ConclusionIntended-effect or targeted analysis may substantially reduce the sample size needed to evaluate cancer-specific mortality in blood-based screening trials. Targeted analysis requires many fewer retrospective tests and avoids potential problems arising from the need to inform those individuals whose stored samples test positive. Trialists should consider the trade-off of costs between sample size and retrospective testing requirements when choosing the analysis method.
| S-EPMC11884843 | biostudies-literature
Project description:BackgroundDetermining whether screening with multicancer detection (MCD) tests saves lives requires randomized controlled trials (RCTs). To inform RCT design, we estimated cancer-mortality outcomes from hypothetical MCD RCTs.MethodsWe used the Hu-Zelen model, previously used to plan the National Lung Screening Trial (NLST), to estimate mortality reductions, sample size, and power for 9 cancers for different RCT design parameters and MCD test parameters.ResultsOur base-case RCT with 5 yearly screens and 100 000 people ages 60-74 in each arm, who also undergo standard-of-care screens, has 87%-89% power to detect a 9%-10% mortality reduction (Number Needed to Screen [NNS] = 578-724) over 7-9 years. The majority of prevented deaths were from lung cancers (base-case [64%-66%] and all sensitivity analyses), 8%-10% from colorectal cancer, and 26% from the other 7 cancers, mostly from stomach or ovary or esophagus (due to excellent stage 1 survival) and less from liver or pancreas (poor stage 1 survival) or head and neck or lymphoma (excellent stage 4 survival). There was limited power for mortality reductions at most individual cancer sites. Base-case findings were sensitive to test sensitivity, stage shifts, and mean sojourn times in the preclinical state (especially for lung cancer), but 90% power could be recovered by recruiting a substantially higher risk population.ConclusionsLarge-scale MCD RCTs would have 89% power to detect an approximate 10% cancer mortality reduction over a relatively short 7-9 year timeframe from trial entry. The estimated NNS for MCD RCTs compares favorably with mammographic screening. Most prevented cancer deaths in a well-powered MCD RCT would likely be from lung cancer. Non-lung and non-colorectal cancer sites could be a meaningful proportion of prevented cancer deaths, but power is insufficient to isolate non-lung-cancer mortality reductions.
| S-EPMC11807432 | biostudies-literature
Project description:Liquid biopsy has been emerging for early screening and treatment monitoring at each cancer stage. However, the current blood-based diagnostic tools in breast cancer have not been sufficient to understand patient-derived molecular features of aggressive tumors individually. Herein, we aimed to develop a blood test for the early detection of breast cancer with cost-effective and high-throughput considerations in order to combat the challenges associated with precision oncology using mRNA-based tests. We prospectively evaluated 719 blood samples from 404 breast cancer patients and 315 healthy controls, and identified 10 mRNA transcripts whose expression is increased in the blood of breast cancer patients relative to healthy controls. Modeling of the tumor-associated circulating transcripts (TACTs) is performed by means of four different machine learning techniques (artificial neural network (ANN), decision tree (DT), logistic regression (LR), and support vector machine (SVM)). The ANN model had superior sensitivity (90.2%), specificity (80.0%), and accuracy (85.7%) compared with the other three models. Relative to the value of 90.2% achieved using the TACT assay on our test set, the sensitivity values of other conventional assays (mammogram, CEA, and CA 15-3) were comparable or much lower, at 89%, 7%, and 5%, respectively. The sensitivity, specificity, and accuracy of TACTs were appreciably consistent across the different breast cancer stages, suggesting the potential of the TACTs assay as an early diagnosis and prediction of poor outcomes. Our study potentially paves the way for a simple and accurate diagnostic and prognostic tool for liquid biopsy.
| S-EPMC9409068 | biostudies-literature
Project description:The emergence of multicancer early detection (MCED) tests holds promise for improving early cancer detection and public health outcomes. However, positive MCED test results require confirmation through recommended cancer diagnostic imaging modalities. To address these challenges, we have developed a consultation and work-up protocol for definitive diagnostic results post MCED testing, named SPOT-MAS. Developed through circulating tumor DNA (ctDNA) analysis and in line with professional guidelines and advisory board consensus, this protocol standardizes information to aid general practitioners in accessing, interpreting and managing SPOT-MAS results. Clinical effectiveness is demonstrated through a series of identified cancer cases. Our research indicates that the protocol could empower healthcare professionals to confidently interpret circulating tumor DNA test results for 5 common types of cancer, thereby facilitating the clinical integration of MCED tests.
| S-EPMC11389743 | biostudies-literature
Project description:The ability to detect several types of cancer using a non-invasive, blood-based test holds the potential to revolutionize oncology screening. We mined tumor methylation array data from the Cancer Genome Atlas (TCGA) covering 14 cancer types and identified two novel, broadly-occurring methylation markers at TLX1 and GALR1. To evaluate their performance as a generalized blood-based screening approach, along with our previously reported methylation biomarker, ZNF154, we rigorously assessed each marker individually or combined. Utilizing TCGA methylation data and applying logistic regression models within each individual cancer type, we found that the three-marker combination significantly increased the average area under the ROC curve (AUC) across the 14 tumor types compared to single markers (p = 1.158 × 10-10; Friedman test). Furthermore, we simulated dilutions of tumor DNA into healthy blood cell DNA and demonstrated increased AUC of combined markers across all dilution levels. Finally, we evaluated assay performance in bisulfite sequenced DNA from patient tumors and plasma, including early-stage samples. When combining all three markers, the assay correctly identified nine out of nine lung cancer plasma samples. In patient plasma from hepatocellular carcinoma, ZNF154 alone yielded the highest combined sensitivity and specificity values averaging 68% and 72%, whereas multiple markers could achieve higher sensitivity or specificity, but not both. Altogether, this study presents a comprehensive pipeline for the identification, testing, and validation of multi-cancer methylation biomarkers with a considerable potential for detecting a broad range of cancer types in patient blood samples.
| S-EPMC10571530 | biostudies-literature
Project description:BackgroundTET enzymes mediate DNA demethylation by oxidizing 5-methylcytosine (5mC) in DNA to 5-hydroxymethylcytosine (5hmC), 5-formylcytosine (5fC), and 5-carboxylcytosine (5caC). Since these oxidized methylcytosines (oxi-mCs) are not recognized by the maintenance methyltransferase DNMT1, DNA demethylation can occur through "passive," replication-dependent dilution when cells divide. A distinct, replication-independent ("active") mechanism of DNA demethylation involves excision of 5fC and 5caC by the DNA repair enzyme thymine DNA glycosylase (TDG), followed by base excision repair.ResultsHere by analyzing inducible gene-disrupted mice, we show that DNA demethylation during primary T cell differentiation occurs mainly through passive replication-dependent dilution of all three oxi-mCs, with only a negligible contribution from TDG. In addition, by pyridine borane sequencing (PB-seq), a simple recently developed method that directly maps 5fC/5caC at single-base resolution, we detect the accumulation of 5fC/5caC in TDG-deleted T cells. We also quantify the occurrence of concordant demethylation within and near enhancer regions in the Il4 locus. In an independent system that does not involve cell division, macrophages treated with liposaccharide accumulate 5hmC at enhancers and show altered gene expression without DNA demethylation; loss of TET enzymes disrupts gene expression, but loss of TDG has no effect. We also observe that mice with long-term (1 year) deletion of Tdg are healthy and show normal survival and hematopoiesis.ConclusionsWe have quantified the relative contributions of TET and TDG to cell differentiation and DNA demethylation at representative loci in proliferating T cells. We find that TET enzymes regulate T cell differentiation and DNA demethylation primarily through passive dilution of oxi-mCs. In contrast, while we observe a low level of active, replication-independent DNA demethylation mediated by TDG, this process does not appear to be essential for immune cell activation or differentiation.
| S-EPMC8218415 | biostudies-literature
Project description:ObjectiveMulticancer early detection panels have recently become available to patients with healthcare provider prescriptions and available funds. These tests utilize circulating tumor DNA (ctDNA) to screen more than 50 cancers using a single blood sample. However, perspectives and data on how the deployment of these tests may impact the practices of primary care providers in terms of implementation, interpretation, documentation, and costs are limited. This study aimed to assess the perspectives of primary care providers regarding the integration of multicancer early detection panels into clinical practice.MethodsWe used a survey to assess the opinions and perspectives of primary care providers, including physicians, nurse practitioners, and physician assistants, across a multistate, tertiary healthcare system. We used a single form consisting of novel questions on familiarity with multi-cancer early detection panels, cost, healthcare equity, documentation, medicolegal, and other concerns. The subgroup analysis was consistent with stratification based on familiarity with ctDNA-based tests and their roles in clinical practice.ResultsMost respondents were unfamiliar with multicancer early detection panels and had not used ctDNA-based tests. Most primary care providers suggested that they would reorder multicancer early detection panel testing at 1- to 5-year intervals and prefer subspecialists for both ordering multicancer early detection panels as well as interpreting their results. Relative concerns differed between physicians and nonphysicians.ConclusionThe integration of multicancer early detection panels into primary care practice requires careful planning and consideration for the management of increased clinical load, interpretation of results, and cost management.
| S-EPMC11323832 | biostudies-literature
Project description:Emerging CRISPR-based nucleic acid detection shows great promise in molecular diagnosis of diseases. CRISPR-Cas12a can sensitively and specifically detect human papillomavirus (HPV) DNA in anal swabs. However, the current CRISPR-Cas12a system needs auxiliary and expensive equipment, which limit its application as a point-of-care (POC) diagnostic tool. This study aimed to develop CRISPR-Cas12a as a POC test to directly target plasma for circulating HPV DNA detection by immediately reading results with naked eyes. Cell-cultured supernatants of either HPV16- or 18-positive cancer cells were treated with lysis buffer followed by isothermal amplification without DNA isolation. Cas12a, crRNA, and fluorescent-biotin reporters were incubated with the lysates. Our data showed that integrating CRISPR-Cas12a with lateral-flow strips could directly and specifically detect HPV16 and 18 in the liquid samples with the same limit of detection (0.24 fM) as did polymerase chain reaction but requiring less time. Furthermore, the CRISPR-Cas12a system could rapidly detect presence of HPV16 and HPV18 in plasma samples of 13 of 14 and 3 of 10 the patients with histopathological diagnosis of cervical cancer, respectively. Therefore, a CRISPR-Cas12a-based POC system was developed for conveniently detecting circulating nuclei acid targets in body fluids without requiring technical expertise and ancillary machineries.
| S-EPMC6807067 | biostudies-literature