Barriers in early detection of colorectal cancer and exploring potential solutions

This editorial discusses the literature review article by Tonini and Zanni,the paper was published in January 2024,and the authors provided very interesting conclusions regarding existing barriers to the early diagnosis of colon cancer.Many cancers do not have identifiable precursors,or there are currently no screening tests to find them.Therefore,these cancers do not have preventive screening options.Early detection is crucial for reducing mortality rates by identifying cancer at an earlier stage through screening,as opposed to no screening.Colorectal cancer develops from precancerous lesions,which can be detected early and potentially prevented and cured.Early detection leads to improved survival rates,decreased complications,and reduced healthcare expenses.This editorial provides a brief description of the biology of colon cancer,emphasizing the contrast in outcomes between early detection and late detection.We also describe screening programs around the globe and examine the barriers in each program.Finally,we explore potential future solutions to enhance inclusion in screening programs and improve patient compliance.

Prospects in the application of ultrasensitive chromosomal aneuploidy detection in precancerous lesions of gastric cancer

Gastric cancer(GC)is a prevalent malignant tumor within the digestive system,with over 40%of new cases and deaths related to GC globally occurring in China.Despite advancements in treatment modalities,such as surgery supplemented by adjuvant radiotherapy or chemotherapeutic agents,the prognosis for GC remains poor.New targeted therapies and immunotherapies are currently under invest-igation,but no significant breakthroughs have been achieved.Studies have indicated that GC is a heterogeneous disease,encompassing multiple subtypes with distinct biological characteristics and roles.Consequently,personalized treatment based on clinical features,pathologic typing,and molecular typing is crucial for the diagnosis and management of precancerous lesions of gastric cancer(PLGC).Current research has categorized GC into four subtypes:Epstein-Barr virus-positive,microsatellite instability,genome stability,and chromosome instability(CIN).Technologies such as multi-omics analysis and gene sequencing are being employed to identify more suitable novel testing methods in these areas.Among these,ultrasensitive chromosomal aneuploidy detection(UCAD)can detect CIN at a genome-wide level in subjects using low-depth whole genome sequencing technology,in conjunction with bioinformatics analysis,to achieve qualitative and quantitative detection of chromosomal stability.This editorial reviews recent research advancements in UCAD technology for the diagnosis and management of PLGC.

Revisiting the standards of cancer detection and therapy alongside their comparison to modern methods

In accordance with the World Health Organization data,cancer remains at the forefront of fatal diseases.An upward trend in cancer incidence and mortality has been observed globally,emphasizing that efforts in developing detection and treatment methods should continue.The diagnostic path typically begins with learning the medical history of a patient;this is followed by basic blood tests and imaging tests to indicate where cancer may be located to schedule a needle biopsy.Prompt initiation of diagnosis is crucial since delayed cancer detection entails higher costs of treatment and hospitalization.Thus,there is a need for novel cancer detection methods such as liquid biopsy,elastography,synthetic biosensors,fluorescence imaging,and reflectance confocal microscopy.Conventional therapeutic methods,although still common in clinical practice,pose many limitations and are unsatisfactory.Nowadays,there is a dynamic advancement of clinical research and the development of more precise and effective methods such as oncolytic virotherapy,exosome-based therapy,nanotechnology,dendritic cells,chimeric antigen receptors,immune checkpoint inhibitors,natural product-based therapy,tumor-treating fields,and photodynamic therapy.The present paper compares available data on conventional and modern methods of cancer detection and therapy to facilitate an understanding of this rapidly advancing field and its future directions.As evidenced,modern methods are not without drawbacks;there is still a need to develop new detection strategies and therapeutic approaches to improve sensitivity,specificity,safety,and efficacy.Nevertheless,an appropriate route has been taken,as confirmed by the approval of some modern methods by the Food and Drug Administration.

Esophageal cancer screening,early detection and treatment:Current insights and future directions

Esophageal cancer ranks among the most prevalent malignant tumors globally,primarily due to its highly aggressive nature and poor survival rates.According to the 2020 global cancer statistics,there were approximately 604000 new cases of esophageal cancer,resulting in 544000 deaths.The 5-year survival rate hovers around a mere 15%-25%.Notably,distinct variations exist in the risk factors associated with the two primary histological types,influencing their worldwide incidence and distribution.Squamous cell carcinoma displays a high incidence in specific regions,such as certain areas in China,where it meets the cost-effect-iveness criteria for widespread endoscopy-based early diagnosis within the local population.Conversely,adenocarcinoma(EAC)represents the most common histological subtype of esophageal cancer in Europe and the United States.The role of early diagnosis in cases of EAC originating from Barrett's esophagus(BE)remains a subject of controversy.The effectiveness of early detection for EAC,particularly those arising from BE,continues to be a debated topic.The variations in how early-stage esophageal carcinoma is treated in different regions are largely due to the differing rates of early-stage cancer diagnoses.In areas with higher incidences,such as China and Japan,early diagnosis is more common,which has led to the advancement of endoscopic methods as definitive treatments.These techniques have demonstrated remarkable efficacy with minimal complications while preserving esophageal functionality.Early screening,prompt diagnosis,and timely treatment are key strategies that can significantly lower both the occurrence and death rates associated with esophageal cancer.

Microstrip Patch Antenna with an Inverted T-Type Notch in the Partial Ground for Breast Cancer Detections

This study designs a microstrip patch antenna with an inverted T-type notch in the partial ground to detect tumorcells inside the human breast.The size of the current antenna is small enough(18mm×21mm×1.6mm)todistribute around the breast phantom.The operating frequency has been observed from6–14GHzwith a minimumreturn loss of−61.18 dB and themaximumgain of current proposed antenna is 5.8 dBiwhich is flexiblewith respectto the size of antenna.After the distribution of eight antennas around the breast phantom,the return loss curveswere observed in the presence and absence of tumor cells inside the breast phantom,and these observations showa sharp difference between the presence and absence of tumor cells.The simulated results show that this proposedantenna is suitable for early detection of cancerous cells inside the breast.

Early diagnosis of esophageal cancer:How to put“early detection”into effect?

This editorial comments on the article by Qu et al in a recent edition of World Journal of Gastrointestinal Oncology,focusing on the importance of early diagnosis in managing esophageal cancer and strategies for achieving“early detection”.The five-year age-standardized net survival for esophageal cancer patients falls short of expectations.Early detection and accurate diagnosis are critical strategies for improving the treatment outcomes of esophageal cancer.While advancements in endoscopic technology have been significant,there seems to be an excessive emphasis on the latest high-end endoscopic devices and various endoscopic resection techniques.Therefore,it is imperative to redirect focus towards proactive early detection strategies for esophageal cancer,investigate the most cost-effective screening methods suitable for different regions,and persistently explore practical solutions to improve the five-year survival rate of patients with esophageal cancer.

Iterative Signal Detection Based Soft Interference Cancellation for Satellite-Terrestrial Downlink NOMA Systems

To improve the bit error rate(BER)performance of multi-user signal detection in satelliteterrestrial downlink non-orthogonal multiple access(NOMA)systems,an iterative signal detection algorithm based on soft interference cancellation with optimal power allocation is proposed.Given that power allocation has a significant impact on BER performance,the optimal power allocation is obtained by minimizing the average BER of NOMA users.According to the allocated powers,successive interference cancellation(SIC)between NOMA users is performed in descending power order.For each user,an iterative soft interference cancellation is performed,and soft symbol probabilities are calculated for soft decision.To improve detection accuracy and without increasing the complexity,the aforementioned algorithm is optimized by adding minimum mean square error(MMSE)signal estimation before detection,and in each iteration soft symbol probabilities are utilized for soft-decision of the current user and also for the update of soft interference of the previous user.Simulation results illustrate that the optimized algorithm i.e.MMSE-IDBSIC significantly outperforms joint multi-user detection and SIC detection by 7.57dB and 8.03dB in terms of BER performance.

Endoscopic detection and diagnostic strategies for minute gastric cancer:A real-world observational study

BACKGROUND Minute gastric cancers(MGCs)have a favorable prognosis,but they are too small to be detected by endoscopy,with a maximum diameter≤5 mm.AIM To explore endoscopic detection and diagnostic strategies for MGCs.METHODS This was a real-world observational study.The endoscopic and clinicopathological parameters of 191 MGCs between January 2015 and December 2022 were retrospectively analyzed.Endoscopic discoverable opportunity and typical neoplastic features were emphatically reviewed.RESULTS All MGCs in our study were of a single pathological type,97.38%(186/191)of which were differentiated-type tumors.White light endoscopy(WLE)detected 84.29%(161/191)of MGCs,and the most common morphology of MGCs found by WLE was protruding.Narrow-band imaging(NBI)secondary observation detected 14.14%(27/191)of MGCs,and the most common morphology of MGCs found by NBI was flat.Another three MGCs were detected by indigo carmine third observation.If a well-demarcated border lesion exhibited a typical neoplastic color,such as yellowish-red or whitish under WLE and brownish under NBI,MGCs should be diagnosed.The proportion with high diagnostic confidence by magnifying endoscopy with NBI(ME-NBI)was significantly higher than the proportion with low diagnostic confidence and the only visible groups(94.19%>56.92%>32.50%,P<0.001).CONCLUSION WLE combined with NBI and indigo carmine are helpful for detection of MGCs.A clear demarcation line combined with a typical neoplastic color using nonmagnifying observation is sufficient for diagnosis of MGCs.MENBI improves the endoscopic diagnostic confidence of MGCs.

Colorectal cancer screening:The value of early detection and modern challenges

The screening of colorectal cancer(CRC)is pivotal for both the prevention and treatment of this disease,significantly improving early-stage tumor detection rates.This advancement not only boosts survival rates and quality of life for patients but also reduces the costs associated with treatment.However,the adoption of CRC screening methods faces numerous challenges,including the technical limitations of both noninvasive and invasive methods in terms of sensitivity and specificity.Moreover,socioeconomic factors such as regional disparities,economic conditions,and varying levels of awareness affect screening uptake.The coronavirus disease 2019 pandemic further intensified these challenges,leading to reduced screening participation and increased waiting periods.Additionally,the growing prevalence of early-onset CRC necessitates innovative screening approaches.In response,research into new methodologies,including artificial intelligence-based systems,aims to improve the precision and accessibility of screening.Proactive measures by governments and health organizations to enhance CRC screening efforts are underway,including increased advocacy,improved service delivery,and international cooperation.The role of technological innovation and global health collaboration in advancing CRC screening is undeniable.Technologies such as artificial intelligence and gene sequencing are set to revolutionize CRC screening,making a significant impact on the fight against this disease.Given the rise in early-onset CRC,it is crucial for screening strategies to continually evolve,ensuring their effectiveness and applicability.

Integrating Transformer and Bidirectional Long Short-Term Memory for Intelligent Breast Cancer Detection from Histopathology Biopsy Images

Breast cancer is a significant threat to the global population,affecting not only women but also a threat to the entire population.With recent advancements in digital pathology,Eosin and hematoxylin images provide enhanced clarity in examiningmicroscopic features of breast tissues based on their staining properties.Early cancer detection facilitates the quickening of the therapeutic process,thereby increasing survival rates.The analysis made by medical professionals,especially pathologists,is time-consuming and challenging,and there arises a need for automated breast cancer detection systems.The upcoming artificial intelligence platforms,especially deep learning models,play an important role in image diagnosis and prediction.Initially,the histopathology biopsy images are taken from standard data sources.Further,the gathered images are given as input to the Multi-Scale Dilated Vision Transformer,where the essential features are acquired.Subsequently,the features are subjected to the Bidirectional Long Short-Term Memory(Bi-LSTM)for classifying the breast cancer disorder.The efficacy of the model is evaluated using divergent metrics.When compared with other methods,the proposed work reveals that it offers impressive results for detection.

Turbo Message Passing Based Burst Interference Cancellation for Data Detection in Massive MIMO-OFDM Systems

This paper investigates the fundamental data detection problem with burst interference in massive multiple-input multiple-output orthogonal frequency division multiplexing(MIMO-OFDM) systems. In particular, burst interference may occur only on data symbols but not on pilot symbols, which means that interference information cannot be premeasured. To cancel the burst interference, we first revisit the uplink multi-user system and develop a matrixform system model, where the covariance pattern and the low-rank property of the interference matrix is discussed. Then, we propose a turbo message passing based burst interference cancellation(TMP-BIC) algorithm to solve the data detection problem, where the constellation information of target data is fully exploited to refine its estimate. Furthermore, in the TMP-BIC algorithm, we design one module to cope with the interference matrix by exploiting its lowrank property. Numerical results demonstrate that the proposed algorithm can effectively mitigate the adverse effects of burst interference and approach the interference-free bound.

Advancements and Challenges in Biomarkers for Colorectal Cancer Detection:A Comprehensive Review

This study provides an overview of the current landscape of biomarkers for colorectal cancer(CRC)detection,focusing on genetic,proteomic,circulating microRNA(miRNA),and metabolomic biomarkers.CRC remains a significant global health challenge,ranking among the most prevalent cancers worldwide and being a leading cause of cancer-related deaths.Despite advancements in screening methods such as colonoscopy,sigmoidoscopy,and fecal occult blood tests(FOBT),the asymptomatic nature of early-stage CRC often results in late diagnoses,negatively impacting patient outcomes.Genetic biomarkers like APC,KRAS,TP53,and microsatellite instability(MSI)play critical roles in CRC pathogenesis and progression.These biomarkers,detectable through polymerase chain reaction,next-generation sequencing,and other advanced techniques,guide early detection and personalized treatment decisions.Proteomic biomarkers such as CEA,CA 19-9,and novel signatures offer insights into CRC’s physiological changes and disease status,aiding prognosis and treatment response assessments through enzyme-linked immunosorbent assay and mass spectrometry.Circulating miRNAs,including miR-21 and miR-92a,present promising non-invasive biomarkers that can be detected in blood and stool samples,reflecting CRC presence,progression,and therapeutic response.Metabolomic biomarkers,encompassing amino acids,lipids,and TCA cycle intermediates,provide further insights into CRC-associated metabolic alterations,which are crucial for early detection and treatment monitoring using mass spectrometry and nuclear magnetic resonance.Despite these advancements,challenges such as biomarker validation,standardization,and clinical utility remain.Future research directions include integrating multi-omics approaches and leveraging technologies like liquid biopsies and AI for enhanced biomarker discovery and clinical application.By addressing these challenges and advancing research in biomarker development,CRC screening and management could potentially be revolutionized,improving patient outcomes and reducing the global burden of this disease.

Breast Cancer Detection Based on Multi-Slotted Patch Antenna at ISM Band

The present work designed and investigated a 3D basic model for breast cancer detection at the ISM band. The model consists of two multi-slotted rectangular patch antennas and a three-layer breast phantom containing two tumors. A multi-slotted antenna was designed at 2.45 GHz using CST STUDIO SUITE 2018, where the simulated results showed a return loss better than -35 dB and attended more than 77 MHz bandwidth. The diagnosis approach is based on exploiting the electrical properties (frequency dependent) of breast tissues, i.e., mass density, relative permittivity, and conductivity. Once the proposed slotted antenna radiates electromagnetic signals toward the breast model (with and without tumors), the radiation properties in terms of the scattering parameters (S11 and S21), the electrical field, the power flow, the current density, and the power loss density were altered. As a result, the values of these radiation parameters increased when tumors were implanted inside the breast model, informing the presence of cancerous tissues. Moreover, the specific absorption rate (SAR) was estimated as a function of input powers, where the proposed antenna showed a set of low SAR values compared to the IEEE standard of 1.6 W/kg, validating its potential use for diagnosing purposes. The simulated results indicated the prospective use of two slotted antennas (in the first instance) to detect multiple tumors which could be a challenging task using a single-element antenna, where the ultimate goal is to realize a compact antenna array to detect multi-tumors.

Novel biomarkers for early detection of gastric cancer

Gastric cancer(GC)remains a leading cause of cancer-related death worldwide.Less than half of GC cases are diagnosed at an advanced stage due to its lack of early symptoms.GC is a heterogeneous disease associated with a number of genetic and somatic mutations.Early detection and effective monitoring of tumor progression are essential for reducing GC disease burden and mortality.The current widespread use of semi-invasive endoscopic methods and radiologic approaches has increased the number of treatable cancers:However,these approaches are invasive,costly,and time-consuming.Thus,novel molecular noninvasive tests that detect GC alterations seem to be more sensitive and specific compared to the current methods.Recent technological advances have enabled the detection of blood-based biomarkers that could be used as diagnostic indicators and for monitoring postsurgical minimal residual disease.These biomarkers include circulating DNA,RNA,extracellular vesicles,and proteins,and their clinical applications are currently being investigated.The identification of ideal diagnostic markers for GC that have high sensitivity and specificity would improve survival rates and contribute to the advancement of precision medicine.This review provides an overview of current topics regarding the novel,recently developed diagnostic markers for GC.

Microcantilever sensors for biochemical detection

Microcantilever is one of the most popular miniaturized structures in micro-electromechanical systems(MEMS).Sensors based on microcantilever are ideal for biochemical detection,since they have high sensitivity,high throughput,good specification,fast response,thus have attracted extensive attentions.A number of devices that are based on static deflections or shifts of resonant frequency of the cantilevers responding to analyte attachment have been demonstrated.This review comprehensively presents state of art of microcantilever sensors working in gaseous and aqueous environments and highlights the challenges and opportunities of microcantilever biochemical sensors.

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

BACKGROUND Gastrointestinal 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.AIM To describe current applications of this technology for gastrointestinal cancer detection and screening.METHODS A 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.RESULTS A 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.CONCLUSION cfDNA 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.

Efficacy of ctDNA methylation combined with traditional detection modality to detect liver cancer among high-risk patients:A multicenter diagnostic trial

Objective:Circulating tumor DNA(ctDNA)and alpha-fetoprotein(AFP)plus ultrasound(US)have been considered to have high diagnostic accuracy for cancer detection,however,the efficacy of ctDNA methylation combined with the traditional detection modality of liver cancer has not been tested in a Chinese independent cohort.Methods:The high-risk individuals aged between 35 and 70 years who were diagnosed with liver cirrhosis or had moderate and severe fatty liver were eligible for inclusion.All participants were invited to receive a traditional examination[referring to AFP plus US],and ctDNA methylation,respectively.The sensitivity and specificity of different diagnostic tools were calculated.The logistic regression model was applied to estimate the area under the curve(AUC),which was further validated by 10-fold internal cross-validation.Results:A total of 1,205 individuals were recruited in our study,and 39 participants were diagnosed with liver cancer.The sensitivity of AFP,US,US plus AFP,and the combination of US,AFP,and ctDNA methylation was33.33%,56.41%,66.67%,and 87.18%,respectively.The corresponding specificity of AFP,US,US plus AFP,and the combination of all modalities was 98.20%,99.31%,97.68%,and 97.68%,respectively.The AUCs of AFP,US,US plus AFP,and the combination of AFP,US,and ctDNA methylation were 65.77%,77.86%,82.18%,and92.43%,respectively.The internally validated AUCs of AFP,US,US plus AFP,and the combination of AFP,US,and ctDNA methylation were 67.57%,83.26%,86.54%,and 93.35%,respectively.Conclusions:The ctDNA methylation is a good complementary to AFP and US for the detection of liver cancer.

Performance Analysis of Breast Cancer Detection Method Using ANFIS Classification Approach

Breast cancer is one of the deadly diseases prevailing in women.Earlier detection and diagnosis might prevent the death rate.Effective diagnosis of breast cancer remains a significant challenge,and early diagnosis is essential to avoid the most severe manifestations of the disease.The existing systems have computational complexity and classification accuracy problems over various breast cancer databases.In order to overcome the above-mentioned issues,this work introduces an efficient classification and segmentation process.Hence,there is a requirement for developing a fully automatic methodology for screening the cancer regions.This paper develops a fully automated method for breast cancer detection and segmenta-tion utilizing Adaptive Neuro Fuzzy Inference System(ANFIS)classification technique.This proposed technique comprises preprocessing,feature extraction,classifications,and segmentation stages.Here,the wavelet-based enhancement method has been employed as the preprocessing method.The texture and statistical features have been extracted from the enhanced image.Then,the ANFIS classification algorithm is used to classify the mammogram image into normal,benign,and malignant cases.Then,morphological processing is performed on malignant mam-mogram images to segment cancer regions.Performance analysis and comparisons are made with conventional methods.The experimental result proves that the pro-posed ANFIS algorithm provides better classification performance in terms of higher accuracy than the existing algorithms.

An Improved Fully Automated Breast Cancer Detection and Classification System

More than 500,000 patients are diagnosed with breast cancer annually.Authorities worldwide reported a death rate of 11.6%in 2018.Breast tumors are considered a fatal disease and primarily affect middle-aged women.Various approaches to identify and classify the disease using different technologies,such as deep learning and image segmentation,have been developed.Some of these methods reach 99%accuracy.However,boosting accuracy remains highly important as patients’lives depend on early diagnosis and specified treatment plans.This paper presents a fully computerized method to detect and categorize tumor masses in the breast using two deep-learning models and a classifier on different datasets.This method specifically uses ResNet50 and AlexNet,convolutional neural networks(CNNs),for deep learning and a K-Nearest-Neighbor(KNN)algorithm to classify data.Various experiments have been conducted on five datasets:the Mammographic Image Analysis Society(MIAS),Breast Cancer Histopathological Annotation and Diagnosis(BreCaHAD),King Abdulaziz University Breast Cancer Mammogram Dataset(KAU-BCMD),Breast Histopathology Images(BHI),and Breast Cancer Histopathological Image Classification(BreakHis).These datasets were used to train,validate,and test the presented method.The obtained results achieved an average of 99.38%accuracy,surpassing other models.Essential performance quantities,including precision,recall,specificity,and F-score,reached 99.71%,99.46%,98.08%,and 99.67%,respectively.These outcomes indicate that the presented method offers essential aid to pathologists diagnosing breast cancer.This study suggests using the implemented algorithm to support physicians in analyzing breast cancer correctly.

Diagnostic value of matrix metalloproteinases 2, 7 and 9 in urine for early detection of colorectal cancer

BACKGROUND A noninvasive biomarker with high diagnostic performance is urgently needed for the early diagnosis of colorectal cancer(CRC).AIM To evaluate the diagnostic value of matrix metalloproteinases(MMPs)2,7 and 9 in urine for CRC.METHODS Of 59 healthy controls,47 patients with colon polyps and 82 patients with CRC were included in this study.Carcinoembryonic antigen(CEA)in serum and MMP2,MMP7,and MMP9 in urine were detected.The combined diagnostic model of the indicators was established by binary logistic regression.The receiver operating characteristic curve(ROC)of the subjects was used to evaluate the independent and combined diagnostic value of the indicators.RESULTS The MMP2,MMP7,MMP9,and CEA levels in the CRC group differed significantly from levels in the healthy controls(P<0.05).The levels of MMP7,MMP9,and CEA also differed significantly between the CRC group and the colon polyps group(P<0.05).The area under the curve(AUC)distinguishing between the healthy control and the CRC patients using the joint model with CEA,MMP2,MMP7 and MMP9 was 0.977,and the sensitivity and specificity were 95.10%and 91.50%,respectively.For early-stage CRC,the AUC was 0.975,and the sensitivity and specificity were 94.30%and 98.30%,respectively.For advanced stage CRC,the AUC was 0.979,and the sensitivity and specificity were 95.70%and 91.50%,respectively.Using CEA,MMP7 and MMP9 to jointly established a model distinguishing the colorectal polyp group from the CRC group,the AUC was 0.849,and the sensitivity and specificity were 84.10%and 70.20%,respectively.For early-stage CRC,the AUC was 0.818,and the sensitivity and specificity were 76.30%and 72.30%,respectively.For advanced stage CRC,the AUC was 0.875,and the sensitivity and specificity were 81.80%and 72.30%,respectively.CONCLUSION MMP2,MMP7 and MMP 9 may exhibit diagnostic value for the early detection of CRC and may serve as auxiliary diagnostic markers for CRC.