Early Cancer Screening Research Articles

From the International Association for the Study of Lung Cancer Early Detection and Screening Committee: Terminology Issues in Screening and Early Detection of Lung Cancer—International Association for the Study of Lung Cancer Early Detection and Screening Committee Expert Group Recommendations

IntroductionTo facilitate global implementation of lung cancer (LC) screening and early detection in a quality assured and consistent manner, common terminology is needed. Researchers and clinicians within different specialties may use the same terms but with different meanings or different terms for the same intended meanings. MethodsThe Diagnostics Working Group of the International Association for the Study of Lung Cancer Early Detection and Screening Committee has analyzed and discussed relevant terms used on a regular basis and suggests recommendations for consensus definitions of terminology applicable in this setting. We explored how to reach consensus to define relevant and unambiguous terminology for use by health care providers, researchers, patients, screening participants, and family. ResultsTerms and definitions for epidemiologic and health-economical purposes included the following: standardized incidence and mortality rates, LC-specific survival, long-term survival and cure rates, overdiagnosis, overtreatment, and undertreatment. Terms and definitions for defining screening findings included the following: positive, false-positive, negative, false-negative, and indeterminate findings and additional and incidental findings. Terms and definitions for describing parameters in screening programs included the following: opportunistic versus programmatic screening, screening rounds, interval or interim diagnoses, and invasive and minimally invasive procedures. Terms and definitions for shared decision-making included the following: LC screening—possible harms and risks and LC risk and modifiers prior and posterior to a measure. ConclusionsA common set of terminology with standard definitions is recommended for describing clinical LC screening programs, the discussion about effectiveness and outcomes, or the clinical setting. The use of the terms should be clearly defined and explained.

Disparities and Determinants of Testing for Early Detection of Cervical Cancer among Nepalese Women: Evidence from a Population-Based Survey.

Cervical cancer presents a considerable challenge in South Asia, notably in Nepal, where screening remains limited. Past research in Nepal lacked national representation and a thorough exploration of factors influencing cervical cancer screening, such as educational and socioeconomic disparities. This study aims to measure these gaps and identify associated factors in testing for early detection of cervical cancer among Nepalese women. Data from the 2019 Nepal Noncommunicable Disease Risk Factors survey (World Health Organization STEPwise approach to noncommunicable risk factor surveillance), involving 2,332 women aged 30 to 69 years, were used. Respondents were asked if they had undergone cervical cancer testing through visual inspection with acetic acid, Pap smear, or human papillomavirus test ever or in the past 5 years. The slope index of inequality (SII) and relative concentration index were used to measure socioeconomic and education-based disparities in cervical cancer test uptake. Only 7.1% [95% confidence interval (CI): 5.1-9.9] Nepalese women had ever undergone cervical cancer testing, whereas 5.1% (95% CI: 3.4-7.5) tested within the last 5 years. The ever uptake of cervical cancer testing was 5.1 percentage points higher (SII: 5.1, 95% CI: -0.1 to 10.2) among women from the richest compared with the poorest households. Education-based disparities were particularly pronounced, with a 13.9 percentage point difference between highly educated urban residents and their uneducated counterparts (SII: 13.9, 95% CI: 5.8-21.9). Less than one in ten women in Nepal had a cervical cancer testing, primarily favoring higher educated and wealthier individuals. Targeted early detection and cervical cancer screening interventions are necessary to address these disparities and improve access and uptake.

Cost-Effectiveness of Low-Dose Computed Tomography Screenings for Lung Cancer in High-Risk Populations: A Markov Model.

Domestic and foreign studies on lung cancer have been oriented to the medical efficacy of low-dose computed tomography (LDCT), but there is a lack of studies on the costs, value and cost-effectiveness of the treatment. There is a scarcity of conclusive evidence regarding the cost-effectiveness of LDCT within the specific context of Taiwan. This study is designed to address this gap by conducting a comprehensive analysis of the cost-effectiveness of LDCT and chest X-ray (CXR) as screening methods for lung cancer. Markov decision model simulation was used to estimate the cost-effectiveness of biennial screening with LDCT and CXR based on a health provider perspective. Inputs are based on probabilities, health status utility (quality-adjusted life years (QALYs)), costs of lung cancer screening, diagnosis, and treatment from the literatures, and expert opinion. A total of 1,000 simulations and five cycles of Markov bootstrapping simulations were performed to compare the incremental cost-utility ratio (ICUR) of these two screening strategies. Probability and one-way sensitivity analyses were also performed. The ICUR of early lung cancer screening compared LDCT to CXR is $-24,757.65/QALYs, and 100% of the probability agree to adopt it under a willingness-to-pay (WTP) threshold of the Taiwan gross domestic product (GDP) per capita ($35,513). The one-way sensitivity analysis also showed that ICUR depends heavily on recall rate. Based on the prevalence rate of 39.7 lung cancer cases per 100,000 people in 2020, it could be estimated that LDCT screening for high-risk populations could save $17,154,115. LDCT can detect more early lung cancers, reduce mortality and is cost-saving than CXR in a long-term simulation of Taiwan's healthcare system. This study provides valuable insights for healthcare decision-makers and suggests analyzing cost-effectiveness for additional variables in future research.

Label-Free Surface-Enhanced Raman Spectroscopy with Machine Learning for the Diagnosis of Thyroid Cancer by Using Fine-Needle Aspiration Liquid Samples.

The incidence of thyroid cancer is increasing worldwide. Fine-needle aspiration (FNA) cytology is widely applied with the use of extracted biological cell samples, but current FNA cytology is labor-intensive, time-consuming, and can lead to the risk of false-negative results. Surface-enhanced Raman spectroscopy (SERS) combined with machine learning algorithms holds promise for cancer diagnosis. In this study, we develop a label-free SERS liquid biopsy method with machine learning for the rapid and accurate diagnosis of thyroid cancer by using thyroid FNA washout fluids. These liquid supernatants are mixed with silver nanoparticle colloids, and dispersed in quartz capillary for SERS measurements to discriminate between healthy and malignant samples. We collect Raman spectra of 36 thyroid FNA samples (18 malignant and 18 benign) and compare four classification models: Principal Component Analysis-Linear Discriminant Analysis (PCA-LDA), Random Forest (RF), Support Vector Machine (SVM), and Convolutional Neural Network (CNN). The results show that the CNN algorithm is the most precise, with a high accuracy of 88.1%, sensitivity of 87.8%, and the area under the receiver operating characteristic curve of 0.953. Our approach is simple, convenient, and cost-effective. This study indicates that label-free SERS liquid biopsy assisted by deep learning models holds great promise for the early detection and screening of thyroid cancer.

Terraced compression method with automated threshold selection using GMM algorithm for heterogeneous bodies detection

Breast tumors threaten women’s health. Multispectral transmission imaging shows potential in early breast cancer screening, but images have a low signal-to-noise ratio due to tissue absorption and scattering. Frame accumulation improves quality but leads to data redundancy. Existing terraced compression methods (TCM) address this but rely on subjective, inefficient threshold selection. This paper presents an improved TCM that requires only the input of the desired heterogeneity size, with optimal thresholds adaptively determined by analyzing grayscale values and their distribution. By applying compression to each wavelength image and using the GMM algorithm for multidimensional image clustering, results show the Dice coefficient improved by 12.49 %, and the recognition rate of deeper heterogeneity increased by 29.09 % compared to the existing TCM. This validates the TCM’s effectiveness and threshold selection accuracy. Additionally, the method distinguishes heterogeneous bodies of different depths and effectively recognizes various kinds, providing a reliable reference for early breast cancer screening.

Chest wall resections for non-small cell lung cancer: a literature review.

The development of early screening for lung cancer has led to improved overall survival in patients with non-small cell lung cancer (NSCLC). However, the management of NSCLC patients with resectable and potentially resectable chest wall invasion (CWI) requires attention. The purpose of this review is to summarize the role of surgery (chest wall resections) in NSCLC patients with CWI. A literature search and review from three databases (PubMed, Embase, and ScienceDirect) comprised the last 39 years. This review was focused on the treatment of NSCLC patients with CWI, mainly including the preoperative evaluation, principles of treatment and strategic decision-making, surgical complications, and prognostic factors. Through the collection of relevant literature on NSCLC that invades the chest wall, this narrative review describes the actual role in clinical practice and future developments of chest wall resections. Preoperative treatment requires the multidisciplinary team (MDT) team to conduct accurate clinical staging of the patient and pay attention to the patient's lymph node status and rib invasion status. The successful implementation of chest wall resection and possible chest wall reconstruction requires refined individualized treatment based on the patient's clinical characteristics, supplemented by possible postoperative systemic treatment. Surgery plays an important role in treating NSCLC patients with CWI, and a collaborative, experienced MDT is an essential component of the successful treatment of CWI with lung cancer. In the future, more high-quality clinical research is needed to focus on CWI patients so that patients can receive more effective treatment options and better clinical prognosis.

Simultaneous targeting and monitoring of free antigen and in-situ membrane antigen in prostate cancer cells via an aggregation-induced emission-based bifunctional probe

The precise clinical diagnosis of prostate cancer still presents inherent challenges, and usually a monitoring of multiple biomarkers is required. In this study, a new aggregation-induced emission (AIE)-based bifunctional strategy was developed for the simultaneous detection of prostate cancer-specific in situ membrane antigens (PSMA) and free antigens (PSA). First, a bifunctional fluorescent probe with double sensing sites (a PSA-specific sensing site and a PSMA-targeted ligand) was constructed. In the presence of PSA, it specifically binds to the PSA-specific sensing site of the probe, resulting in the restoration of the fluorescence signal, enabling linear sensing of PSA. For the detection of PSMA, the PSMA-targeted ligand modified on the probe can specifically recognize PSMA, inducing the aggregation of the AIE material and resulting in an enhanced fluorescence signal. Moreover, a liposome-based artificial cell was developed to simulate the real prostate cancer cell, and it was used to investigate the feasibility of monitoring the two types of antigens. Utilizing this bifunctional fluorescent strategy, a dual-analysis of free serum antigen biomarker of PSA and in-situ membrane antigen of PSMA was achieved. The assay exhibited a wide linearity range for PSA detection from 0.0001 to 0.1 μg/mL, with a low limit of detection (LOD) of 6.18 pg/mL. For PSMA, the obtained LOD is 8.79 pg/mL, with a linearity range from 0.0001 to 0.1 μg/mL. This strategy allows us to simultaneously assess the levels of two types of biomarkers in living human prostatic cancer cells, providing a highly accurate and selective tool for early screening and monitoring of prostatic cancer.

Leap-Type Response of Redox/Photo-Active Lanthanide-Based Metal-Organic Frameworks for Early and Accurate Screening of Prostate Cancer.

The development of high-accuracy technologies to distinguish the quite tiny concentration change of tumor markers between negative and positive is of vital significance for early screening and diagnosis of cancers, but is still a great challenge for the conventional biosensors because of their "gradual" detection mode. Herein, a unique "leap-type" responsive lanthanide MOF-based biosensor (designated as Tb-CeMOF-X) with defect-mediated redox-/photo-activities is developed for precisely identifying acid phosphatase (ACP), an early pathological marker of prostate cancer (PCa) in serum. The engineered Tb-CeMOF-X probe achieves a bursting switch-on luminescence at the critical concentration of ACP (9 U·L-1), while keeping silent below this threshold, undergoing a qualitative signal change from "zero" to "one" between negative and positive indicators and thus significantly improving the identification precision. Significantly, such "leap-type" response performance can be further edited and amplified by rational defect engineering in the crystal structure to improve the accessibility of active centers, consequently maximizing the detection sensitivity toward ACP in the complex biological media. This study proposes the first paradigm for the development of "leap-type" biosensors with ultra-sensitive differentiation capability between negative and positive,and provides a potentially valuable tool for early and accurate screening of PCa.

Understanding the Landscape of Multi-Cancer Detection Tests: The Current Data and Clinical Considerations.

Multi-cancer detection (MCD) tests are blood-based assays that screen for multiple cancers concurrently and offer a promising approach to improve early cancer detection and screening uptake. To date, there have been two prospective interventional studies evaluating MCD tests as a screening tool in human subjects. No MCD tests are currently approved by the FDA, but there is one commercially available MCD test. Ongoing trials continue to assess the efficacy, safety, and cost implications of MCD tests. In this review, we discuss the performance of CancerSEEK and Galleri, two leading MCD platforms, and discuss the clinical consideration for the broader application of this new technology.

SERS biosensors based on catalytic hairpin self-assembly and hybridization chain reaction cascade signal amplification strategies for ultrasensitive microRNA-21 detection.

A highly sensitive surface-enhanced Raman scattering (SERS) biosensor has been developedfor the detection of microRNA-21 (miR-21) using an isothermal enzyme-free cascade amplification method involving catalytic hairpin assembly (CHA) and hybridization chain reaction (HCR). The CHA reaction is triggered by the target miR-21, which causes hairpin DNA (C1 and C2) to self-assemble into CHA products. After AgNPs@Capture captures the resulting CHA product, the HCR reaction is started, forming long-stranded DNA on the surface of AgNPs. A strong SERS signal is generated due to the presence of a large amount of the Raman reporter methylene blue (MB) in the vicinity of the SERS "hot spot" on the surface of AgNPs. The monitoring of the SERS signal changes of MB allows for the highly sensitive and specific detection of miR-21. In optimal conditions, the biosensor exhibits a satisfactory linear range and a low detection limit for miR-21 of 42.3 fM. Additionally, this SERS biosensor shows outstanding selectivity and reproducibility. The application of this methodology to clinical blood samples allows for the differentiation of cancer patients from healthy controls. As a result, the CHA-HCR amplification strategy used in this SERS biosensor could be a useful tool for miRNA detection and early cancer screening.

Machine Learning for Early Discrimination Between Lung Cancer and Benign Nodules Using Routine Clinical and Laboratory Data.

Lung cancer poses a global health threat necessitating early detection and precise staging for improved patient outcomes. This study focuses on developing and validating a machine learning-based risk model for early lung cancer screening and staging, using routine clinical data. Two medical center, observational, retrospective studies were conducted, involving 2312 lung cancer patients and 653 patients with benign nodules. Machine learning techniques, including differential analysis and feature selection, were employed to identify key factors for modeling. The study focused on variables such as nodule density, carcinoembryonic antigen (CEA), age, and lifestyle habits. The Logistic Regression model was utilized for early diagnoses, and the XGBoost model was utilized for staging based on selected features. For early diagnoses, the Logistic Regression model achieved an area under the curve (AUC) of 0.716 (95% confidence interval [CI] 0.607-0.826), with 0.703 sensitivity and 0.654 specificity. The XGBoost model excelled in distinguishing late-stage from early-stage lung cancer, exhibiting an AUC of 0.913 (95% CI 0.862-0.963), with 0.909 sensitivity and 0.814 specificity. These findings highlight the model's potential for enhancing diagnostic accuracy and staging in lung cancer. This study introduces a novel machine learning-based risk model for early lung cancer screening and staging, leveraging routine clinical information and laboratory data. The model shows promise in enhancing accuracy, mitigating overdiagnosis, and improving patient outcomes.

Urinary Metabolite Diagnostic and Prognostic Liquid Biopsy Biomarkers of Lung Cancer in Nonsmokers and Tobacco Smokers.

Nonsmokers account for 10% to 13% of all lung cancer cases in the United States. Etiology is attributed to multiple risk factors including exposure to secondhand smoking, asbestos, environmental pollution, and radon, but these exposures are not within the current eligibility criteria for early lung cancer screening by low-dose CT (LDCT). Urine samples were collected from two independent cohorts comprising 846 participants (exploratory cohort) and 505 participants (validation cohort). The cancer urinary biomarkers, creatine riboside (CR) and N-acetylneuraminic acid (NANA), were analyzed and quantified using liquid chromatography-mass spectrometry to determine if nonsmoker cases can be distinguished from sex and age-matched controls in comparison with tobacco smoker cases and controls, potentially leading to more precise eligibility criteria for LDCT screening. Urinary levels of CR and NANA were significantly higher and comparable in nonsmokers and tobacco smoker cases than population controls in both cohorts. Receiver operating characteristic analysis for combined CR and NANA levels in nonsmokers of the exploratory cohort resulted in better predictive performance with the AUC of 0.94, whereas the validation cohort nonsmokers had an AUC of 0.80. Kaplan-Meier survival curves showed that high levels of CR and NANA were associated with increased cancer-specific death in nonsmokers as well as tobacco smoker cases in both cohorts. Measuring CR and NANA in urine liquid biopsies could identify nonsmokers at high risk for lung cancer as candidates for LDCT screening and warrant prospective studies of these biomarkers.

Blood-Derived Extracellular Vesicles as a Promising Liquid Biopsy Diagnostic Tool for Early Cancer Detection.

Cancer poses a significant public health challenge worldwide, and timely screening has the potential to mitigate cancer progression and reduce mortality rates. Currently, early identification of most tumors relies on imaging techniques and tissue biopsies. However, the use of low-cost, highly sensitive, non-invasive detection methods for early cancer screening has become more attractive. Extracellular Vesicles (EVs) released by all living cells contain distinctive biological components, such as nucleic acids, proteins, and lipids. These vesicles play crucial roles in the tumor microenvironment and intercellular communication during tumor progression, rendering liquid biopsy a particularly suitable method for diagnosis. Nevertheless, challenges related to purification methods and validation of efficacy currently hinder its widespread clinical implementation. These limitations underscore the importance of refining isolation techniques and conducting comprehensive investigations on EVs. This study seeks to evaluate the potential of liquid biopsy utilizing blood-derived EVs as a practical, cost-effective, and secure approach for early cancer detection.

Enhancing registration precision of multispectral breast images by fusing multi-wavelength information based on an improved gradient descent method

Multispectral transmission imaging is widely recognized as a developmental approach for early breast cancer screening. However, a persistent challenge exists in image registration, particularly in processing human images, where registration often relies solely on single-wavelength information, leading to inadequate accuracy. This paper purposes a novel image registration method that involves summing pixel values from three color channels at identical pixel coordinates and utilizes an improved gradient descent algorithm to achieve image registration. Multispectral maps at wavelengths of 445 nm, 520 nm, and 620 nm serve as examples for testing and evaluation, with frames summed for registered images at each wavelength. Experimental results demonstrate the superior registration accuracy of this method compared to registering images of a single-wavelength independently. This advancement enhances the accuracy and reliability of multispectral transmission imaging in the early detection of breast cancer.

Highly Sensitive 3D‐Nanoplasmonic‐Based Epidermal Growth Factor Receptor Mutation Multiplex Assay Chip for Liquid Biopsy

Economical mutation detection method with high analytical and clinical sensitivity is necessary for early cancer diagnosis and screening. In this study, a novel 3D‐nanoplasmonic‐based multiplex mutation assay chip is developed to detect epidermal growth factor receptor (EGFR) mutations. This assay kit comprises a 3D‐nanoplasmonic substrate immobilized with capture probes and primer–probe sets for recombinase polymerase amplification, wild‐type inhibition, and fluorescence detection, enabling multiplex detection of EGFR exon 19 deletions, exon 20 insertions, and exon 21 L858R point mutations. The strategy facilitates the detection of all deletions and insertions within the target region with extremely high analytical sensitivity, detecting as low as 1 × 10−9% mutation frequency, implying three copies/reactions and 100 zM. The synergistic effects of plasmon‐enhanced fluorescence from the 3D‐nanoplasmonic substrate and wild‐type inhibitor contribute to this high analytical sensitivity. Moreover, the developed chip exhibits 100% accuracy in the clinical testing of plasma samples from normal individuals and patients with benign lung tumor and malignant lung tumor. With high sensitivity and multiplexing capabilities, this assay operates at a low reaction temperature (around 37 °C) and requires a short processing time, ≈70 min post‐cell‐free DNA extraction. These features make the chip a valuable tool for easy and widespread cancer screening.

Chinese expert consensus on the guidance of anti-tumor drugs for patients with tumor combined chronic kidney disease (2024 edition)

The incidence of malignant tumors has steadily increased year by year in China in recent decades. The emergence of innovative anti-cancer drugs has bolstered the prognosis of cancer patients, making it a chronic disease. Kidney injuries are frequent complications of cancer treatment clinically manifested as acute kidney injury (AKI), chronic kidney disease (CKD), proteinuria, and electrolyte disorders, etc. Although kidney injuries affect up to 50% of the patients, there is a lack of professional management guidance for anti-cancer drug dosage adjustment. The clinical pharmacology branch of the Chinese Medical Association has initiated the "Chinese expert consensus on the guidance of anti-tumor drugs for patients with tumor combined chronic kidney disease (2024 edition)". We unified national multidisciplinary experts to analyze clinical evidence with the Delphi method, and conducted expert interviews and seminars focusing on kidney function assessment, anti-tumor drug dosage adjustment for kidney disease patients. We make recommendations on selection and dose adjustment of anti-tumor drugs (chemotherapy, small molecules and antibodies) according to chemotherapeutic drug classifications, providing practical and feasible scientific guidance for clinicians.

Accurate Early Detection and EGFR Mutation Status Prediction of Lung Cancer Using Plasma cfDNA Coverage Patterns: A Proof-of-Concept Study.

Lung cancer is a major global health concern with a low survival rate, often due to late-stage diagnosis. Liquid biopsy offers a non-invasive approach to cancer detection and monitoring, utilizing various features of circulating cell-free DNA (cfDNA). In this study, we established two models based on cfDNA coverage patterns at the transcription start sites (TSSs) from 6X whole-genome sequencing: an Early Cancer Screening Model and an EGFR mutation status prediction model. The Early Cancer Screening Model showed encouraging prediction ability, especially for early-stage lung cancer. The EGFR mutation status prediction model exhibited high accuracy in distinguishing between EGFR-positive and wild-type cases. Additionally, cfDNA coverage patterns at TSSs also reflect gene expression patterns at the pathway level in lung cancer patients. These findings demonstrate the potential applications of cfDNA coverage patterns at TSSs in early cancer screening and in cancer subtyping.

Advances in Nanoplasmonic Biosensors: Optimizing Performance for Exosome Detection Applications.

The development of sensitive and specific exosome detection tools is essential because they are believed to provide specific information that is important for early detection, screening, diagnosis, and monitoring of cancer. Among the many detection tools, surface-plasmon resonance (SPR) biosensors are analytical devices that offer advantages in sensitivity and detection speed, thereby making the sample-analysis process faster and more accurate. In addition, the penetration depth of the SPR biosensor, which is <300 nm, is comparable to the size of the exosome, making the SPR biosensor ideal for use in exosome research. On the other hand, another type of nanoplasmonic sensor, namely a localized surface-plasmon resonance (LSPR) biosensor, has a shorter penetration depth of around 6 nm. Structural optimization through the addition of supporting layers and gap control between particles is needed to strengthen the surface-plasmon field. This paper summarizes the progress of the development of SPR and LSPR biosensors for detecting exosomes. Techniques in signal amplification from two sensors will be discussed. There are three main parts to this paper. The first two parts will focus on reviewing the working principles of each sensor and introducing several methods that can be used to isolate exosomes. This article will close by explaining the various sensor systems that have been developed and the optimizations carried out to obtain sensors with better performance. To illustrate the performance improvements in each sensor system discussed, the parameters highlighted include the detection limit, dynamic range, and sensitivity.

Plasma metabolomics and lipidomics reveal potential novel biomarkers in early gastric cancer: An explorative study.

Early identification and therapy can significantly improve the outcome for gastric cancer. However, there is still no perfect biomarker available for the detection of early gastric cancer. This study aimed to investigate the alterations in the plasma metabolites of early gastric cancer using metabolomics and lipidomics based on high-performance liquid chromatography-mass spectrometry (HPLC-MS), which detected potential biomarkers that could be used for clinical diagnosis. To investigate the changes in metabolomics and lipidomics, a total of 30 plasma samples were collected, consisting of 15 patients with early gastric cancer and 15 healthy controls. Extensive HPLC-MS-based untargeted metabolomic and lipidomic investigations were conducted. Differential metabolites and metabolic pathways were uncovered through the utilization of statistical analysis and bioinformatics analysis. Candidate biomarker screening was performed using support vector machine-based multivariate receiver operating characteristic analysis. A disturbance was observed in a combined total of 19 metabolites and 67 lipids of the early gastric cancer patients. The analysis of KEGG pathways showed that the early gastric cancer patients experienced disruptions in the arginine biosynthesis pathway, the pathway for alanine, aspartate, and glutamate metabolism, as well as the pathway for glyoxylate and dicarboxylate metabolism. Plasma metabolomics and lipidomics have identified multiple biomarker panels that can effectively differentiate early gastric cancer patients from healthy controls, exhibiting an area under the curve exceeding 0.9. These metabolites and lipids could potentially serve as biomarkers for the screening of early gastric cancer, thereby optimizing the strategy for the detection of early gastric cancer. The disrupted pathways implicated in early gastric cancer provide new clues for additional understanding of gastric cancer's pathogenesis. Nonetheless, large-scale clinical data are required to prove our findings.

Detection of MicroRNA-155 based on lambda exonuclease selective digestion and CRISPR/cas12a-assisted amplification

In numerous malignancies, miRNA-155 is overexpressed and has oncogenic activity because it is one of the most efficient microRNAs for inhibiting apoptosis in human cancer cells. As a result, the highest sensitive detection of the miRNA-155 gene is a technological instrument that can enable early cancer screening. In this study, a miRNA-155 biosensor was created to create a hairpin probe that can bind to the miRNA-155 gene using lambda nucleic acid exonuclease, which can cut the 5′ phosphorylated double strand, and by the DNA probe is recognized by the Cas12a enzyme, which then activates Cas12a to catalyze trans-cutting produces strong fluorescence. Research finding, the target concentration's logarithm and corresponding fluorescence intensity have a strong linear connection, and the limit of detection (LOD) of the sensing system was determined to be 8.3 pM. In addition, the biosensor displayed exceptional specificity, low false-positive signal, and high sensitivity in detecting the miRNA-155 gene in serum samples. This study's creation of a biosensor that has high sensitivity, good selectivity, and is simple to operate provides promising opportunities for research into biosensor design and early cancer detection.