Detection Of Gastrointestinal Cancers Research Articles

One-step reverse transcriptase-free miRNA detection system and its application for detection of gastrointestinal cancers

MicroRNAs (miRNAs) play pivotal roles in gene regulation and their dysregulation is implicated in various diseases, including cancer. Current methods for miRNA analysis often involve complex procedures and high costs, limiting their clinical utility. Therefore, there is a critical need for the development of simpler and more cost-effective miRNA detection techniques to enable early disease diagnosis. In this study, we introduce a novel one-enzyme for miRNA one-step detection method using Taq DNA polymerase, termed OSMOS-qPCR. We optimized the PCR buffer, PCR program, Taq DNA Polymerase concentrations and reverse PCR primer concentrations, resulted in a wide linear range from 100 fM to 0.001 fM (R2 > 0.98 for each miRNA), the detection limit for OSMOS-qPCR was 0.0025 fM. Furthermore, OSMOS-qPCR demonstrates excellent specificity to differentiation of less than 0.1 % nonspecific signal. Finally, we demonstrated the robust amplification efficiency, enabling the detection of trace amounts of cell-free miRNA in serum samples, and the excellent discrimination ability between gastrointestinal cancers and control subjects (AUC value = 1.0) if combined two miRNAs. The development of OSMOS-qPCR offering a simpler, cost-effective, and efficient detection method, has the potential to be non-invasive strategy for early detection of gastrointestinal cancers.

Harbor seal whiskers optimization algorithm with deep learning-based medical imaging analysis for gastrointestinal cancer detection.

Gastrointestinal (GI) cancer detection includes the detection of cancerous or potentially cancerous lesions within the GI tract. Earlier diagnosis is critical for increasing the success of treatment and improving patient outcomes. Medical imaging plays a major role in diagnosing and detecting GI cancer. CT scans, endoscopy, MRI, ultrasound, and positron emission tomography (PET) scans can help detect lesions, abnormal masses, and changes in tissue structure. Artificial intelligence (AI) and machine learning (ML) methods are being gradually applied to medical imaging for cancer diagnosis. ML algorithms, including deep learning methodologies like convolutional neural network (CNN), are applied frequently for cancer diagnosis. These models learn features and patterns from labelled datasets to discriminate between normal and abnormal areas in medical images. This article presents a new Harbor Seal Whiskers Optimization Algorithm with Deep Learning based Medical Imaging Analysis for Gastrointestinal Cancer Detection (HSWOA-DLGCD) technique. The goal of the HSWOA-DLGCD algorithm is to explore the GI images for the cancer diagnosis. In order to accomplish this, the HSWOA-DLGCD system applies bilateral filtering (BF) approach for the removal of noise. In addition, the HSWOA-DLGCD technique makes use of HSWOA with Xception model for feature extraction. For cancer recognition, the HSWOA-DLGCD technique applies extreme gradient boosting (XGBoost) model. Finally, the parameters compared with the XGBoost system can be selected by moth flame optimization (MFO) system. The experimental results of the HSWOA-DLGCD technique could be verified on the Kvasir database. The simulation outcome demonstrated a best possible solution of the HSWOA-DLGCD method than other recent methods.

Detection of early-stage gastrointestinal cancers by micronuclei DNA from erythrocytes.

382 Background: Gastrointestinal (GI) cancers account for over a third of cancer deaths. However, their early detection remains a challenge. Micronuclei (MN) are extranuclear bodies containing damaged chromosome segments indicative of genomic instability. Increased MN frequency in hematopoietic cells is observed in patients with solid tumors. We have developed a method (WO2021/228246 A1) for purifying and characterizing micronuclei DNA (mnDNA) in erythrocytes from peripheral blood. Here, we evaluated the potential of mnDNA for early-stage GI cancer detection, including colorectal (CC) and gastric (GC) cancers. Methods: Peripheral blood (1 ml) was collected from healthy donors (HD) and cancer patients mnDNA isolation and purification from erythrocytes. Participants were randomly divided into training, validation and independent test cohorts in a 7:2:1 ratio, maintaining similar cancer types, CC/GC/HD ratio, gender and age distribution. Distinct mnDNA features between cancer patients and HDs were identified using sequencing data. Logistic regression algorithms were applied using these features for cancer detection. Results: The study enrolled 1046 participants, including 419 HDs, 366 CC and 261 GC cases. Of these, over half were diagnosed with early-stage diseases; TNM stage I accounted for 38.7%, stage II for 22.8%, stage III for 30.5% and stage IV for 8.0%. The cancer detection model with mnDNA features yielded an overall accuracy of 84.8%, with a sensitivity of 84.1% and specificity of 85.7%. For individual caner types, sensitivity was 89.2% for CC and 76.9% for GC. For early-stage (stage I-II) CC and GC, the model demonstrated sensitivities of 88.9% and 76.5%, respectively, at 85.7% specificity. Conclusions: Unlike cell-free DNA, mnDNA are chromosomal fragments in the cytoplasm. The abundance of erythrocytes in peripheral blood provides an easily accessible source for mnDNA enrichment. This pilot study illustrates the potential of mnDNA as a tool for early GI cancer detection, contributing to large-scale efforts towards developing an effective GI cancer screening test.

Gastrointestinal Cancer Detection and Classification Using African Vulture Optimization Algorithm With Transfer Learning

Gastrointestinal Cancer Detection and Classification Using African Vulture Optimization Algorithm With Transfer Learning

The Role of Pentraxin 3 in Gastrointestinal Cancers.

Gastrointestinal cancers have become a huge problem worldwide as the number of new cases continues to increase. Due to the growing need to explore new biomarkers and therapeutic targets for the detection and treatment of cancerous lesions, we sought to elucidate the role of Pentraxin-3 in the progression of cancerous lesions, as it is involved in the process of angiogenesis and inflammation. Statistically significant changes in the concentration of this parameter have emerged in many gastrointestinal cancer patients. Moreover, it is related to the advancement of cancer, as well as processes leading to the development of those changes. In the case of studies concerning tissue material, both increased and decreased tissue expression of the tested parameter were observed and were dependent on the type of cancer. In the case of cell lines, both human and animal, a significant increase in Pentraxin 3 gene expression was observed, which confirmed the changes observed at the protein level. In conclusion, it can be assumed that PTX3, both at the level of gene expression and protein concentrations, is highly useful in the detection of gastrointestinal cancers, and its use as a biomarker and/or therapeutic target may be useful in the future.

A sensitive and robust plasma-based DNA methylation panel for early detection of target gastrointestinal cancers

BackgroundTarget gastrointestinal cancers (GICs), encompassing esophageal cancer (EC), gastric cancer (GC), and colorectal cancer (CRC), originate within a single readily accessible luminal organ system and are diagnosable using endoscopy. However, endoscopy is an invasive procedure with low compliance and no plasma-based DNA methylation assay for the early detection of GICs. MethodsNine potential DNA methylation markers were identified and evaluated in tissue (n=60) and plasma (n=155) cohorts to select the most suitable markers. A training cohort (n=244) and a validation cohort (n=199), including GICs patients, benign tumors, gastrointestinal polyps, and controls, were enrolled to develop and validate a DNA methylation panel. An independent prospective cohort (n=158) was used to validate the panel's performance and compare it with blood protein tumor markers. ResultsSix out of nine candidate methylation markers with excellent discrimination abilities in both tissue and plasma cohorts were selected for the DNA methylation panel. The panel demonstrated high AUC values of 0.937 (EC), 0.968 (GC), and 0.987 (CRC) in training cohort, and achieved AUC values of 0.921 (EC), 0.921 (GC), and 0.959 (CRC) in validation cohort. Notably, it achieved impressive AUC values of 0.971 and 0.843 for identifying stage I GICs in the training and validation cohorts, respectively. In the prospective cohort, the six-marker panel showed comparable AUC values to CEA, AFP, and CA19-9 (0.935, 0.769, 0.663, and 0.668, respectively). ConclusionThis study successfully developed and validated a novel, robust, sensitive, and specific plasma-based DNA methylation panel, offering a promising strategy for the early detection of GICs.

S352 Detection of Gastrointestinal Cancer in Individuals Without Clinical Suspicion of Cancer Using a Multi-Cancer Early Detection Test in the PATHFINDER Study

S352 Detection of Gastrointestinal Cancer in Individuals Without Clinical Suspicion of Cancer Using a Multi-Cancer Early Detection Test in the PATHFINDER Study

Potential Diagnostic Utility of microRNAs in Gastrointestinal Cancers.

Early detection of gastrointestinal cancers is beneficial for patient survival and prognosis. MiRNAs have been shown to be potential cancer biomarkers that can be used to diagnose cancers. MiRNAs are single-stranded, small non-coding RNAs that are involved in the post-transcriptional regulation of the expression of different oncogenes. Cancer tissues contain miRNAs that play a special role in the etiology of cancer development or limiting cancer suppression. Dysregulation of miRNAs occurs in a variety of malignancies, including gastrointestinal cancers. MiRNAs are stable and protected against degradation by RNase, which enables their detection in tissues and biological fluids. The results of many studies suggest that miRNAs have a relatively higher diagnostic efficiency in distinguishing cancer patients from healthy people. The researchers have identified many miRNA signature in the blood for the detection of gastrointestinal cancers. This review focuses on the role and potential utility of miRNAs in the early detection, prognosis and evaluation of the treatment effectiveness of gastrointestinal cancers.

A novel non-invasive multi-target stool DNA methylation assay for early detection of gastrointestinal cancers.

41 Background: Gastrointestinal (GI) cancers accounts for one-third of the world’s cancer burden. Liquid biopsies such as SEPT9 methylation and Cologuard have been approved by the Food and Drug Administration for early detection of colorectal cancer (CRC), but not for other GI cancers. In addition, although CancerSEEK can be employed in the detecting of multiple GI cancers, it has low sensitivity and without localization. Stool is a promising sample for GI cancer detection because it contains the host’s exfoliated cells and circulating free DNA derived from GI cancer cells. Thus, we aimed to develop a sensitive and non-invasive multi-target stool DNA methylation test for early detection and localization of GI cancers. Methods: We prospectively enrolled 124 patients histologically diagnosed with GI cancer without treatment and 92 healthy controls who underwent GI cancer-related examinations every 3 years. Stool DNA was extracted from the supernatant of a mixture containing 5 g fresh stool and 25 ml preservative solution using the stool DNA extraction kit. The samples were subjected to bisulfite conversion using the EZ DNA Methylation Kit, and the treated with stool DNA multi-target methylation assay kit to detect the methylation levels of 3 target regions of stool DNA (PDX1, COL4A2-1, and FGF5) with qPCR. Based on the guidelines of the protocol, positive result was defined as ΔCt value (ΔCt = Ct (target gene) - Ct (GAPDH))＜10 for any three genes. Multiple logistic regression (MLR) models for single GI cancers were constructed including the ΔCt value of each gene to adjust for tissue of origin (TOO) of GI cancers. This study was approved by the Clinical Research Ethics Committee of Guangdong Second Provincial General Hospital (2021-KZ-138-03). Results: Overall, 98 of 124 patients (79%) tested positive, and 88 of 92 healthy controls (96%) tested negative. For each GI cancer type, the positivity rates were 71%, 83%, 75%, 81% and 91% for CRC (24/34), gastric cancer (GC, 19/23), esophageal cancer (EC, 18/24), pancreatic cancer (PC, 17/21) and ampullary cancer (AC, 20/22), respectively. Interestingly, among 4 positive healthy controls, 3 were diagnosed as advanced adenomas and one case was a pregnant woman. For the MLR model, the sensitivity of CRC was 88% (30/34), that of GC was 91% (21/23), EC was 88% (21/24), PC was 90% (19/21), and AC was 95% (21/22). Conclusions: The multi-target stool DNA methylation assay allowed early and accurate detection and identification of tissue of origin of GI cancers. [Table: see text]

Detection and localization of gastrointestinal cancers based on multi-dimentional signatures from a single cfDNA targeted sequencing assay.

4169 Background: Five major gastrointestinal (GI) cancers - colorectal (CRC), gastric (GC), liver (LC), esophageal (EC), and pancreatic cancer (PC) - are responsible for hundreds of thousands of mortalities annually worldwide. Unfortunately, there is a lack of cost-effective, blood-based screening method for their early detection. To address this issue, we aimed to develop GutSeer, a noninvasive, targeted methylation sequencing-based test by leveraging methylation and fragmentomic signatures carried by cell-free DNA (cfDNA). Methods: The panel of GutSeer consists of 1656 target regions which were either differentially methylated between healthy and cancer samples, or distinctively methylated in a specific GI cancer. Cancer and healthy participants were recruited and randomly divided into a training and a validation cohort. Their plasma DNA samples were analyzed to generate DNA methylation and fragmentomic features. These multi-dimensional features were integrated to build ensemble stacked machine learning models to differentiate cancer against healthy, and to determine the tissue-of-origin (TOO) of the cancer. Results: A total of 1844 cases (787 healthy, 342 LC, 239 GC, 209 EC, 180 CRC, and 87 PC cases) were recruited for this study. A cancer- vs-healthy model achieved an AUC of 0.94 and 0.95 (sensitivity of 77.7% and 77.1% under the specificity around 96%) using either methylation or fragmentomic features only, respectively. Combining both methylation and fragmentomic features further improved performances, achieving an AUC of 0.96 (sensitivity = 86.2% at a specificity of 96.7%). For individual type of cancer, GutSeer has a sensitivity of 93.3% for CRC, 81.1% for EC, 70.3% for GC, 96.5% for LC, and 86.4% for PC. An independent test using 629 benign cases as controls achieved a specificity of 87.1%. A separate TOO model was built using all features and achieved an overall accuracy of 82% for all cancer cases (66.7% for CRC, 87.0% for GC and EC combined, 89.0% for LC, and 63.2% for PC). Same as the cancer detection model, using multi-dimensional features in TOO prediction yielded higher accuracy than when models using only methylation or fragmentomics features (accuracy = 75.6% or 75.4%, respectively). When compared with whole-genome sequencing (WGS) based approaches, GutSeer showed a comparable performance in cancer detection but a higher accuracy in TOO identification, further confirming its effectiveness for detection of GI cancers. Conclusions: GutSeer, a non-invasive test integrating multi-dimensional features, was demonstrated to detect and localize the 5 main types of GI cancer with high accuracy. Our results further showed that a reasonably sized panel can perform comparably or even better than WGS-based methods in cancer detection and TOO localization, indicating GutSeer may be a low-cost solution for blood-based early screening for GI cancers.

Circulating metabolites as potential biomarkers for the early detection and prognosis surveillance of gastrointestinal cancers

Background and aimsTwo of the most lethal gastrointestinal (GI) cancers, gastric cancer (GC) and colon cancer (CC), are ranked in the top five cancers that cause deaths worldwide. Most GI cancer deaths can be reduced by earlier detection and more appropriate medical treatment. Unlike the current “gold standard” techniques, non-invasive and highly sensitive screening tests are required for GI cancer diagnosis. Here, we explored the potential of metabolomics for GI cancer detection and the classification of tissue-of-origin, and even the prognosis management.MethodsPlasma samples from 37 gastric cancer (GC), 17 colon cancer (CC), and 27 non-cancer (NC) patients were prepared for metabolomics and lipidomics analysis by three MS-based platforms. Univariate, multivariate, and clustering analyses were used for selecting significant metabolic features. ROC curve analysis was based on a series of different binary classifications as well as the true-positive rate (sensitivity) and the false-positive rate (1-specificity).ResultsGI cancers exhibited obvious metabolic perturbation compared with benign diseases. The differentiated metabolites of gastric cancer (GC) and colon cancer (CC) were targeted to same pathways but with different degrees of cellular metabolism reprogramming. The cancer-specific metabolites distinguished the malignant and benign, and classified the cancer types. We also applied this test to before- and after-surgery samples, wherein surgical resection significantly altered the blood-metabolic patterns. There were 15 metabolites significantly altered in GC and CC patients who underwent surgical treatment, and partly returned to normal conditions.ConclusionBlood-based metabolomics analysis is an efficient strategy for GI cancer screening, especially for malignant and benign diagnoses. The cancer-specific metabolic patterns process the potential for classifying tissue-of-origin in multi-cancer screening. Besides, the circulating metabolites for prognosis management of GI cancer is a promising area of research.

Early detection and localization of major gastrointestinal cancers by combining DNA methylation and fragmentomic signatures generated from a single cfDNA targeted sequencing assay.

330 Background: Gastrointestinal (GI) cancers totally account for more than one third of the cancerous deaths, yet there is no cost-effective blood-based assay for the early detection of GI cancers. We sought to develop GutSeer, a noninvasive test based on cell-free DNA (cfDNA) methylation and fragmentation signatures derived from one single targeted DNA methylation sequencing panel, for early detection and localization of five major GI cancers, including colorectal (CC), gastric (GC), liver (LC), esophageal (EC), and pancreatic cancer (PC). Methods: A DNA methylation targeted sequencing panel with 1656 target regions was designed. It was then verified in a large cohort of retrospective cancer and control plasma samples for feature selection and modeling. The participants were randomly divided into a training cohort and a validation cohort in a 1:1 ratio. DNA methylation and fragmentomic features were calculated based on GutSeer sequencing data. An ensemble stacked machine learning approach was built to classify cancer and healthy samples in training cohort and tested in validation cohort. We also constructed a TOO model to predict the tissue of origin of detected cancer samples. Results: To develop GutSeer assay, we have enrolled and tested a total of 1844 retrospective plasma samples (787 healthy, 342 LC, 239 GC, 209 EC, 180 CC, and 87 PC), over half of the cancer samples were diagnosed with early-stage disease (TNM stage I 35.6%; stage II 23.3%; stage III 21.7%; stage IV 12.5%). Cancer- vs-healthy model was built on training cohort and tested in validation cohort, achieving an AUC of 0.94 (sensitivity=77.7%, specificity=96.4%) with methylation features, and 0.95 (sensitivity=77.1%, specificity=95.9%) with fragmentomic features. Combining these features could achieve AUC of 0.963 (sensitivity = 86.2%, specificity = 96.7%). For individual cancer types, the sensitivity was 93.3% (CC), 81.1% (EC), 70.3% (GC), 96.5% (LC) and 86.4% (PC), respectively. For predicted cancer samples, we achieved an 82% top-one (66.7% CC, 87.0% GC/EC, 89.0% LC, 63.2% PC) and 95.2% top-two (86,9% CC, 98.2% GC/EC, 97.6% LC, 89.5% PC) TOO accuracy (ACC, accuracy of predicting the most likely, and the top 2 most likely tissue or organ types where the identified cancer was located, respectively) in validation cohort with TOO model combined all features. Conclusions: Based on a single targeted DNA methylation sequencing assay, GutSeer, which combined cfDNA methylation and fragmentomic signatures, could detect and localize the major five GI cancers with high accuracy but low cost. Although this is a pilot study with limited sample size, GutSeer demonstrated the potential to be further optimized into non-invasive diagnostics for blood-based early screening and diagnosis for GI cancers.

The effect of oral anticoagulants on the detection of gastrointestinal cancers

The effect of oral anticoagulants on the detection of gastrointestinal cancers

Endoscopy demand among county people in southeast China: A cross-sectional study

ObjectiveThe popularization of gastroenteroscopy and the introduction of comfortable medical care have further promoted the growth of people's demand, especially the demand for painless endoscopy. This cross-sectional study aims to investigate the current situation and change in county people's demand for endoscopy to promote the development of endoscopy centers in county hospitals in southeast China. MethodsFrom October to December 2021, patients and their family members who came to the Gastroenterology Department in Suichang County People's Hospital of Zhejiang Province were randomly selected to complete the questionnaire. A total of 838 valid questionnaires were collected. Additionally, the original software data of the Endoscopy Center were sampled and retrieved (from October to December every year from 2018 to 2021) for statistical analysis of real-world data. Those who would choose painless endoscopy the next time in the valid questionnaires were included in the painless endoscopy group, while those who would choose ordinary endoscopy the next time were included in the ordinary endoscopy group. ResultsThe stepwise forward binary logistic regression model analysis showed that, patients with “secondhand smoke exposure” were more willing to choose painless endoscopy (OR = 1.459, 95% CI: 1.050–2.028, p = 0.025). However, patients with an education level of “primary and below” and “junior high school”, and patients who are suffering from “currently experiencing abdominal distension”, were more willing to choose ordinary endoscopy (OR = 0.270, 95% CI: 0.149–0.488, p < 0.001; OR = 0.528, 95% CI: 0.330–0.845, p = 0.008; OR = 0.536, 95% CI: 0.334–0.861, p = 0.010). Patients with previous experience in painless endoscopy tended to choose painless endoscopy the next time, while patients with previous experience in ordinary endoscopy tended to choose ordinary endoscopy the next time (χ2 = 140.97, p < 0.001). From 2018 to 2021, the proportion of painless endoscopy has increased yearly (p < 0.001). Most patients indicated that they would “regularly review gastroenteroscopy” (477/838, 56.9%). ConclusionsWith Suichang County of Zhejiang Province as the representative, the demand for painless endoscopy for people's gastrointestinal cancer detection in southeast China has been increasing yearly. The development of endoscopy centers in county-level hospitals can basically meet the demand growth. Meanwhile, advanced concepts such as comfortable medical care and regular follow-up are gradually popularized at the grassroots level in southeast China.

Optical-resolution functional gastrointestinal photoacoustic endoscopy based on optical heterodyne detection of ultrasound

Photoacoustic endoscopy shows promise in the detection of gastrointestinal cancer, inflammation, and other lesions. High-resolution endoscopic imaging of the hemodynamic response necessitates a small-sized, high-sensitivity ultrasound sensor. Here, we utilize a laser ultrasound sensor to develop a miniaturized, optical-resolution photoacoustic endoscope. The sensor can boost the acoustic response by a gain factor of ωo/Ω (the frequency ratio of the signal light and measured ultrasound) by measuring the acoustically induced optical phase change. As a result, we achieve a noise-equivalent pressure density (NEPD) below 1.5 mPa·Hz-1/2 over the measured range of 5 to 25 MHz. The heterodyne phase detection using dual-frequency laser beams of the sensor can offer resistance to thermal drift and vibrational perturbations. The endoscope is used to in vivo image a rat rectum and visualize the oxygen saturation changes during acute inflammation, which can hardly be observed with other imaging modalities.

Robotic large‐area optical biopsy imaging for automated detection of gastrointestinal cancers tested in tissue phantoms and ex vivo porcine bowel

AbstractGastrointestinal endoscopy is a subjective procedure that frequently requires tissue samples for diagnosis. Contact optical biopsy (OB) techniques have the aim of providing direct diagnosis of endoscopic areas without excising tissue samples but lack the wide‐area coverage required for locating and resecting lesions. This article presents a large‐area robotically deployed OB imaging platform for endoscopic detection of colorectal cancer as an add‐on for conventional endoscopes. In vitro, in silicon colon phantoms, the platform achieves an optical resolution of 0.5 line pairs per millimeter, while resolving simulated cancer lesions down to 0.75 mm diameter across large‐area images (55‐103 cm2). Large‐area OB images were generated in an ex vivo porcine colon. The platform allows centimeter‐sized large‐area OB imaging in vitro and ex vivo with submillimeter resolution, including automatic data segmentation of simulated cancer areas. The ability for robotic actuation and spectrum collection is also shown for ex vivo animal colon. If successful, this technology could widen access to user‐independent high‐quality endoscopy and early detection of gastrointestinal cancers.

Риск-ориентированные подходы к эндоскопической диагностике рака ЖКТ в медицинских организациях первичного звена (на примере ГАУЗ СО ГБ № 1 г. Нижний Тагил)

Early detection of gastrointestinal cancer is an actual public health problem. The implementation of the modern endoscopic diagnostic methods based on the progressive digital technologies significantly reduce the risks of diagnostic errors and contributes to the effective solution of that problem. P u r p o s e : to clarify the possibilities of the early detection of gastrointestinal cancer by equipping the endoscopy unit of the city district hospital with the modern digital endoscopes, including devices with zoom functions – ZOOM. M a t e r i a l s a n d m e t h o d s . The article analyzes the statistical data of the work of the endoscopy unit of Nizniy Tagil State city hospital № 1 from 2013 to 2022 (except 2020–21, when the hospital was completely redesigned as a COVID-hospital). R e s u l t s . A clear relationship between the increase in the number of detected oncopathologies of the gastrointestinal tract and the modern technical equipment of the endoscopic units under the modernization of primary health care program in the Sverdlovsk region in 2021 is presented. Based on risk-based approaches and evidence-based medicine data, the importance expert-class equipment in the routine endoscopic practice in the primary healthcare district hospital for diagnosing gastrointestinal cancer at an early stage is shown. Modern approaches to optical endoscopic diagnostics are analyzed, as well as the potential risks of diagnostic errors associated with technical equipment and possible measures to reduce these risks for further improvement of primary endoscopic diagnostics aimed at detecting gastrointestinal cancer in the early stages are determined, the expediency of equipping endoscopic units of primary care medical organizations with endoscopes inreached magnification functions – ZOOM, as well as photo and video recording of digital images with the possibility of archiving, color printing and further expert analysis of endoscopic images. C o n s e q u e n c e . From the presented statistical data, it is clearly seen how with the improvement of the equipment quality, the detection of gastrointestinal cancer of various localizations is growing.

Clinical performance of a liquid biopsy test based on the detection of multiple DNA methylation biomarkers for early detection of gastrointestinal cancers.

e16096 Background: Gastrointestinal cancers (colorectal cancer, gastric cancer and esophageal cancer) are the most prevalent malignant tumors in China, resulting in 975,537 new cases and 958,675 deaths in 2020. Currently, the gold standard for the early detection of these cancers remains to be gastrointestinal endoscopy. However, the invasiveness, low throughput and high cost of these procedures have prevented its wide acceptance by Chinese population. The objective of this study was to develop a liquid biopsy test based on the detection of multiple DNA methylation biomarkers (SpecGastro test) and evaluate its clinical performance for early detection of gastrointestinal cancers. Methods: Two hundred and eighty-two gastrointestinal cancer patients (98 colorectal cancers, 136 gastric cancers and 48 esophageal cancers) and 195 control subjects were included. Ten milliliters of peripheral blood was drawn and 3.5 mL plasma was separated for cell-free DNA extraction and bisulfite conversion. The converted DNA was subsequently examined by SpecGastro test, a multiplex qPCR assay that detected six methylation biomarkers and one internal control. Results: Overall sensitivity for SpecGastro test was 76.6% (95% CI: 71.1-81.3%) with a specificity of 89.2% (95% CI: 83.8-93.1%). Sensitivities for colorectal cancer, gastric cancer and esophageal cancer were 87.8% (95% CI: 79.2-93.2%), 69.9% (95% CI: 61.3-77.3%) and 72.9% (95% CI: 57.9-84.3%), respectively. A high AUC of 0.903 (95% CI: 0.873-0.928) indicated that SpecGastro test distinguished gastrointestinal cancer patients from control subjects with high accuracy. Conclusions: Our analysis demonstrated the utility of SpecGastro test to detect three types of gastrointestinal cancers with high sensitivity and specificity. These results supported the feasibility of this blood-based SpecGastro test as a complementary tool to the existing single-cancer early detection tests.

Cell-free DNA liquid biopsy for early detection of gastrointestinal cancers: A systematic review.

BACKGROUNDGastrointestinal tumors are among the most common cancer types, and early detection is paramount to improve their management. Cell-free DNA (cfDNA) liquid biopsy raises significant hopes for non-invasive early detection.AIMTo describe current applications of this technology for gastrointestinal cancer detection and screening.METHODSA systematic review of the literature was performed across the PubMed database. Articles reporting the use of cfDNA liquid biopsy in the screening or diagnosis of gastrointestinal cancers were included in the analysis.RESULTSA total of 263 articles were screened for eligibility, of which 13 articles were included. Studies investigated colorectal cancer (5 studies), pancreatic cancer (2 studies), hepatocellular carcinoma (3 studies), and multi-cancer detection (3 studies), including gastric, oesophageal, or bile duct cancer, representing a total of 4824 patients. Test sensitivities ranged from 71% to 100%, and specificities ranged from 67.4% to 100%. Pre-cancerous lesions detection was less performant with a sensitivity of 16.9% and a 100% specificity in one study. Another study using a large biobank demonstrated a 94.9% sensitivity in detecting cancer up to 4 years before clinical symptoms, with a 61% accuracy in tissue-of-origin identification. CONCLUSIONcfDNA liquid biopsy seems capable of detecting gastrointestinal cancers at an early stage of development in a non-invasive and repeatable manner and screening simultaneously for multiple cancer types in a single blood sample. Further trials in clinically relevant settings are required to determine the exact place of this technology in gastrointestinal cancer screening and diagnosis strategies.

EpiPanGI Dx: A Cell-free DNA Methylation Fingerprint for the Early Detection of Gastrointestinal Cancers.

DNA methylation alterations have emerged as front-runners in cell-free DNA (cfDNA) biomarker development. However, much effort to date has focused on single cancers. In this context, gastrointestinal (GI) cancers constitute the second leading cause of cancer-related deaths worldwide; yet there is no blood-based assay for the early detection and population screening of GI cancers. Herein, we performed a genome-wide DNA methylation analysis of multiple GI cancers to develop a pan-GI diagnostic assay. By analyzing DNA methylation data from 1,781 tumor and adjacent normal tissues, we first identified differentially methylated regions (DMR) between individual GI cancers and adjacent normal, as well as across GI cancers. We next prioritized a list of 67,832 tissue DMRs by incorporating all significant DMRs across various GI cancers to design a custom, targeted bisulfite sequencing platform. We subsequently validated these tissue-specific DMRs in 300 cfDNA specimens and applied machine learning algorithms to develop three distinct categories of DMR panels RESULTS: We identified three distinct DMR panels: (i) cancer-specific biomarker panels with AUC values of 0.98 (colorectal cancer), 0.98 (hepatocellular carcinoma), 0.94 (esophageal squamous cell carcinoma), 0.90 (gastric cancer), 0.90 (esophageal adenocarcinoma), and 0.85 (pancreatic ductal adenocarcinoma); (ii) a pan-GI panel that detected all GI cancers with an AUC of 0.88; and (iii) a multi-cancer (tissue of origin) prediction panel, EpiPanGI Dx, with a prediction accuracy of 0.85-0.95 for most GI cancers. Using a novel biomarker discovery approach, we provide the first evidence for a cfDNA methylation assay that offers robust diagnostic accuracy for GI cancers.