Specificity For Cancer Detection Research Articles

Abstract 1266: Development and performance of a multi-cancer early detection test utilizing plasma cfDNA fragmentomics: A large-scale, prospective, multicenter study

Abstract Background: The implementation of the multi-cancer early detection (MCED) test offers a valuable adjunct to existing screening methods, enabling more efficient detection of cancer and potentially leading to improved treatment outcomes and prognoses for patients. Here, we report on the performance of an MCED test, which utilizes plasma cfDNA and leverages genome-wide fragmentomics-based characteristics to identify cancer signals and predict the signal origin across a diverse range of cancer types. Methods: Plasma cfDNA from evaluable blood samples was analyzed using an MCED blood test called MERCURY, a robust machine learning classifier leveraging the low-coverage whole-genome sequencing and a comprehensive set of genome-wide features derived from cfDNA fragmentomics. A carefully selected cohort of 3076 cancer patients representing 13 cancer types, in addition to 3477 healthy controls, were pre-specified into the training and internal validation sets to train and internally validate the models to assess cancer and tissue of origin (TOO). The classifier was trained to a target specificity of 99% and locked before analysis of the independent validation set. The independent validation was enrolled prospectively and consists of 1465 participants (cancer: n= 732; non-cancer: n= 733). Results: The performance metrics in the internal validation set demonstrated that the sensitivity and specificity for cancer detection were 0.865 (95% CI [0.840, 0.887]) and 0.989 (95% CI [0.980, 0.994]), respectively. These impressive results were further substantiated in the independent validation set, where the overall sensitivity and specificity were found to be 0.874 (95% CI [0.848, 0.897]) and 0.978 (95% CI [0.965, 0.987]) respectively. Notably, the sensitivity showed an incremental increase with the stage of cancer (Stage I: 0.769, 95% CI [0.708, 0.821]; Stage II: 0.840, 95% CI [0.784, 0.886]; Stage III: 0.923, 95% CI [0.874, 0.954]; Stage IV: 0.971, 95% CI [0.901, 0.995]. Regarding the TOO model, a total of 10 cancer types with more than 100 patients in the model construction cohort were considered. The TOO model achieved a prediction accuracy of 83.5% (95% CI [80.7%, 86.6%]) and 91.8% (95% CI [89.6%, 94.1%]) for the top predicted origin and the top two predicted origins, respectively, amongst the true positive cases in the independent validation set. Conclusions: In this pre-specified, large-scale study, the MCED test, utilizing cfDNA fragmentomics, demonstrates its remarkable ability to assess cancer signal with an elevated level of sensitivity and specificity across 13 distinct types of cancer. Moreover, it displays noteworthy accuracy in predicting the tissue of origin. The performances are to be further validated in a prospective cohort study (NCT06011694). Citation Format: Hua Bao, Xiaoxi Chen, Min Wu, Shiting Tang, Xuxiaochen Wu, Wanxiangfu Tang, Dongqin Zhu, Shanshan Yang, Shuang Chang, Peng He, Xiuxiu Xu, JinPeng Zhang, Yi Shen, Shuyu Wu, Ya Jiang, Sisi Liu, Xian Zhang, Xue Wu, Yang Shao. Development and performance of a multi-cancer early detection test utilizing plasma cfDNA fragmentomics: A large-scale, prospective, multicenter study [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 1266.

Abstract 5025: Extracellular vesicle DNA as a potential biomarker for cancer detection: A comparative analysis with ctDNA

Abstract Background: Liquid biopsy testing has been implemented in clinical practice because of recent advancements in detecting and characterizing circulating tumor DNA (ctDNA). The Food and Drug Administration (FDA) has approved three ctDNA liquid biopsy tests that detect mutations in cancers, which can aid clinicians in choosing the most effective treatments. While ctDNA has been validated for clinical applications, the same is not true for extracellular vesicle (EV)-associated DNA, which is another promising biomarker. Previously, our laboratory developed the Extracellular Vesicle-Associated DNA Database (EV-ADD) to provide validated experimental details and data extracted from peer-reviewed published literature on EV-DNA. The aim of our study was to investigate the potential clinical utility of EV-DNA in liquid biopsy for tumor detection by surveying studies on EV-ADD that compared ctDNA and EV-DNA. Methods: We searched the entire EV-ADD to selectively identify studies that compared cell-free DNA (cfDNA) or ctDNA and EV-DNA in cancer patients (inclusion criteria). The sensitivity and specificity of cancer detection, the concentrations of DNA, and the methods of detection were compared between ct/cfDNA and EV-DNA. We define sensitivity as the ability to detect mutations in ctDNA/EV-DNA from patient blood when the mutations are known. Specificity is defined as the proportion of true negatives from the sum of true negatives and false positives. A true negative case occurs when no driver mutation is detected in ctDNA/EV-DNA of a patient whose tumor does not have the mutation either. A false positive case occurs when a driver mutation is detected in ctDNA/EV-DNA of a patient whose tumor does not have the mutation. Results: Of 97 studies in the database, 20 met our inclusion criteria. From 12 studies that matched our definition of sensitivity, the sensitivity of EV-DNA and ctDNA ranged from 19% to 95% and 14% to 97%, respectively. From the same 12 studies, the specificity of EV-DNA and ctDNA ranged from 89% to 100% and 80% to 100%, respectively. Other studies that met our inclusion criteria but did not match our definition of sensitivity either calculated sensitivity differently (2 studies), calculated sensitivity the same way in pleural effusions (2 studies), in bronchoalveolar lavage fluid (2 studies), analyzed mitochondrial DNA (1 study), or did not calculate sensitivity (1 study). The concentrations of EV-DNA and ctDNA in blood ranged from 0.8 - 118.4 ng/ml and 4.0 - 236.5 ng/ml, respectively. Digital droplet PCR (ddPCR) and sequencing were the most common methods (45% and 35%, respectively) for detecting cancer mutations. Conclusions: Since EV-DNA performed comparably to ctDNA in detecting cancer DNA in the blood of patients, EV-DNA should be seriously considered as a potential biomarker and complementary tool for detecting and monitoring cancer tumors. Citation Format: Tad Wu, Thupten Tsering, Yunxi Chen, Amélie Nadeau, Julia V. Burnier. Extracellular vesicle DNA as a potential biomarker for cancer detection: A comparative analysis with ctDNA [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 5025.

Real-time Histological Evaluation of Gastric Cancer Tissue by Using a Confocal Laser Endomicroscopic System.

The need for instant histological evaluation of fresh tissue, especially in cancer treatment, remains paramount. The conventional frozen section technique has inherent limitations, prompting the exploration of alternative methods. A recently developed confocal laser endomicroscopic system provides real-time imaging of the tissue without the need for glass slide preparation. Herein, we evaluated its applicability in the histologic evaluation of gastric cancer tissues. A confocal laser endomicroscopic system (CLES) with a Lissajous pattern laser scanning, was developed. Fourteen fresh gastric cancer tissues and the same number of normal gastric tissues were obtained from advanced gastric cancer patients. Fluorescein sodium was used for staining. Five pathologists interpreted 100 endomicroscopic images and decided their histologic location and the presence of cancer. Following the review of matched hematoxylin and eosin (H&E) slides, their performance was evaluated with another 100 images. CLES images mirrored gastric tissue histology. Pathologists were able to detect the histologic location of the images with 65.7% accuracy and differentiate cancer tissue from normal with 74.7% accuracy. The sensitivity and specificity of cancer detection were 71.9% and 76.1%. Following the review of matched H&E images, the accuracy of identifying the histologic location was increased to 92.8% (p<0.0001), and that of detecting cancer tissue was also increased to 90.9% (p<0.001). The sensitivity and specificity of cancer detection were enhanced to 89.1% and 93.2% (p<0.0001). High-quality histological images were immediately acquired by the CLES. The operator training enabled the accurate detection of cancer and histologic location raising its potential applicability as a real-time tissue imaging modality.

Optimizing Drug Delivery Systems for Enhanced Therapeutic Efficacy in Cancer Treatment: A Multidisciplinary Approach

This research aims to develop an early detection method for breast cancer through the analysis of specific biomarkers. The method leverages advanced drug delivery technology to enhance the efficacy of cancer therapy. Employing a multidisciplinary approach, this study integrates medical and pharmaceutical sciences to achieve optimal results. Specific biomarkers utilized in this research will be identified to improve the sensitivity and specificity of cancer detection. The findings of this research are anticipated to make a significant contribution to enhancing early breast cancer detection capabilities and optimizing therapy utilization in patients.

Laser-scribing graphene-based electrochemical biosensing devices for simultaneous detection of multiple cancer biomarkers

In this study, a graphene electrochemical sensor based on laser graphene polymer material was proposed to induce graphene formation on polyimide substrates via fiber laser. The laser produces stable power and results to achieve the benefits of consistency, conductivity, and flexibility. The electrochemical three-electrodes were manufactured on polyimide to replace the traditional three-electrodes by achieving small size and portability. An electrode activation is the modification of laser-scribed graphene electrodes (LSG) to facilitate the binding of liver cancer sites. The evaluation is performed by differential pulse Voltammetry (DPV) to detect cancer proteins in the phosphate buffer saline (PBS) buffer and serum. In a serum environment, the concentrations of alpha-fetoprotein (AFP) and Carcinoembryonic antigen (CEA) were detected from 0.75 ng ml−1 to 100 ng ml−1, AFP and CEA electrodes have a good linear range (R2 = 0.96 and R2 = 0.98), indicating the sensor's sensitivity and specificity for cancer detection. In addition, two types of carcinogenic proteins were monitored in the PBS and successfully detected in this experiment. Based on the results, the appropriate LSG sensor may be used for monitoring with limited resources. Electrode manufacturing is simple, fast, low-cost, small in size, convenient to carry, stable, instant detection, and flexible.

Comparison of Amritsar scoring system using quantitative contrast enhanced ultrafast magnetic resonance mammography and diffusion technique with conventional Kaiser scoring system

Background: Magnetic resonance imaging (MRI) mammography has been recommended as a problem solving tool in patients with breast lump for which newer imaging protocols like abbreviated, ultrafast MRI and diffusion MRI are now available. For interpretation lexicons like BIRADS and Kaiser score system are available but there is a scope for improvement of results and need for newer lexicons.Methods: Retrospective study of 175 patients of breast lump who had MRI mammography was done. The lesions were labelled as malignant by Kaiser score system (KSS) and a newer scoring system “Amritsar score system” (AMSS). Final diagnoses was confirmed by histological examination with hormone and Her2neu receptor studies. Statistical analysis was done for correlation, sensitivity, specificity and accuracy along with area under curves and the results compared.Results: Study comprised 32/175 patients with malignant nodules. Mean age of 47.2 (range: 44.2-49.6) years with mean nodule size of 2.2 cm (range 1.8-5.5 cm). ADC and Ktrans, Kep, TTE, MS and IAUC60 showed high correlation with size of malignant nodule. Sensitivity of detection was 87.4%, 87.5%, 88.6%, 71.8% and 80% respectively for ADC, Ktrans, Kep, TTE, MS and IAUC60 while specificities were 94, 88.7, 88.7% 90% and 90% respectively. The sensitivity, specificity and accuracy for KSS and AMSS were 62.5%, 88.9%, 72% and 96.5%, 90% and 94% respectively.Conclusions: AMSS is more accurate than KSS and improves the sensitivity and specificity of cancer detection. Ktrans and ADC imaging parameters not only show high sensitivity for cancer detection but also have a good correlation with the size and nuclear grade to be used as imaging biomarkers.

Unsupervised Super Resolution Network for Hyperspectral Histologic Imaging.

Hyperspectral imaging (HSI) has many advantages in microscopic applications, including high sensitivity and specificity for cancer detection on histological slides. However, acquiring hyperspectral images of a whole slide with a high image resolution and a high image quality can take a long scanning time and require a very large data storage. One potential solution is to acquire and save low-resolution hyperspectral images and reconstruct the high-resolution ones only when needed. The purpose of this study is to develop a simple yet effective unsupervised super resolution network for hyperspectral histologic imaging with the guidance of RGB digital histology images. High-resolution hyperspectral images of hemoxylin & eosin (H&E) stained slides were obtained at 10× magnification and down-sampled 2×, 4×, and 5× to generate low-resolution hyperspectral data. High-resolution digital histologic RGB images of the same field of view (FOV) were cropped and registered to the corresponding high-resolution hyperspectral images. A neural network based on a modified U-Net architecture, which takes the low-resolution hyperspectral images and high-resolution RGB images as inputs, was trained with unsupervised methods to output high-resolution hyperspectral data. The generated high-resolution hyperspectral images have similar spectral signatures and improved image contrast than the original high-resolution hyperspectral images, which indicates that the super resolution network with RGB guidance can improve the image quality. The proposed method can reduce the acquisition time and save storage space taken up by hyperspectral images without compromising image quality, which will potentially promote the use of hyperspectral imaging technology in digital pathology and many other clinical applications.

EMT-NET: EFFICIENT MULTITASK NETWORK FOR COMPUTER-AIDED DIAGNOSIS OF BREAST CANCER.

Deep learning-based computer-aided diagnosis has achieved unprecedented performance in breast cancer detection. However, most approaches are computationally intensive, which impedes their broader dissemination in real-world applications. In this work, we propose an efficient and light-weighted multitask learning architecture to classify and segment breast tumors simultaneously. We incorporate a segmentation task into a tumor classification network, which makes the backbone network learn representations focused on tumor regions. Moreover, we propose a new numerically stable loss function that easily controls the balance between the sensitivity and specificity of cancer detection. The proposed approach is evaluated using a breast ultrasound dataset with 1511 images. The accuracy, sensitivity, and specificity of tumor classification is 88.6%, 94.1%, and 85.3%, respectively. We validate the model using a virtual mobile device, and the average inference time is 0.35 seconds per image.

High performance methylated DNA markers for detection of colon adenocarcinoma

BackgroundColon cancer (CC) is treatable if detected in its early stages. Improved CC detection assays that are highly sensitive, specific, and available at point of care are needed. In this study, we systematically selected and tested methylated markers that demonstrate high sensitivity and specificity for detection of CC in tissue and circulating cell-free DNA.MethodsHierarchical analysis of 22 candidate CpG loci was conducted using The Cancer Genome Atlas (TCGA) COAD 450K HumanMethylation database. Methylation of 13 loci was analyzed using quantitative multiplex methylation-specific PCR (QM-MSP) in a training set of fresh frozen colon tissues (N = 53). Hypermethylated markers were identified that were highest in cancer and lowest in normal colon tissue using the 75th percentile in Mann–Whitney analyses and the receiver operating characteristic (ROC) statistic. The cumulative methylation status of the marker panel was assayed in an independent test set of fresh frozen colon tissues (N = 52) using conditions defined and locked in the training set. A minimal marker panel of 6 genes was defined based on ROC area under the curve (AUC). Plasma samples (N = 20 colorectal cancers, stage IV and N = 20 normal) were tested by cMethDNA assay to evaluate marker performance in liquid biopsy.ResultsIn the test set of samples, compared to normal tissue, a 6-gene panel showed 100% sensitivity and 90% specificity for detection of CC, and an AUC of 1.00 (95% CI 1.00, 1.00). In stage IV colorectal cancer plasma versus normal, an 8-gene panel showed 95% sensitivity, 100% specificity, and an AUC of 0.996 (95% CI 0.986, 1.00) while a 5-gene subset showed 100% sensitivity, 100% specificity, and an AUC of 1.00 (95% CI 1.00, 1.00), highly concordant with our observations in tissue.ConclusionsWe identified high performance methylated DNA marker panels for detection of CC. This knowledge has set the stage for development and implementation of novel, automated, self-contained CC detection assays in tissue and blood which can expeditiously and accurately detect colon cancer in both developed and underdeveloped regions of the world, enabling optimal use of limited resources in low- and middle-income countries.

Loop-Mediated Isothermal Amplification Assay for Detecting Tumor Markers and Human Papillomavirus: Accuracy and Supplemental Diagnostic Value to Endovaginal MRI in Cervical Cancer.

ObjectiveTo establish the sensitivity and specificity of a human papillomavirus (HPV) and tumor marker DNA/mRNA assay for detecting cervical cancer that is transferrable to a Lab-on-a-chip platform and determine its diagnostic benefit in early stage disease when used in conjunction with high-resolution endovaginal magnetic resonance imaging (MRI).MethodsForty-one patients (27 with Stage1 cervical cancer [Group1] and 14 non-cancer HPV negative controls [Group2]) had DNA and RNA extracted from cervical cytology swab samples. HPV16, HPV18, hTERT, TERC/GAPDH and MYC/GAPDH concentration was established using a loop mediated isothermal amplification (LAMP) assay. Thresholds for tumor marker detection for Group1 were set from Group2 analysis (any hTERT, TERC/GAPDH 3.12, MYC/GAPDH 0.155). Group 1 participants underwent endovaginal MRI. Sensitivity and specificity for cancer detection by LAMP and MRI individually and combined was documented by comparison to pathology.ResultsSensitivity and specificity for cancer detection was 68.8% and 77.8% if any tumor marker was positive regardless of HPV status (scenario1), and 93.8% and 55.8% if tumor marker or HPV were positive (scenario 2). Adding endovaginal MRI improved specificity to 88.9% in scenario 1 (sensitivity 68.8%) and to 77.8%% in scenario2 (sensitivity 93.8%).ConclusionSpecificity for cervical cancer detection using a LAMP assay is superior with tumor markers; low sensitivity is improved by HPV detection. Accuracy for early stage cervical cancer detection is optimal using a spatially multiplexed tumor marker/HPV LAMP assay together with endovaginal MRI.

Diagnosis of transition zone prostate cancer by multiparametric MRI: added value of MR spectroscopic imaging with sLASER volume selection

BackgroundCurrent multiparametric MRI (mp-MRI) in routine clinical practice has poor-to-moderate diagnostic performance for transition zone prostate cancer. The aim of this study was to evaluate the potential diagnostic performance of novel 1H magnetic resonance spectroscopic imaging (MRSI) using a semi-localized adiabatic selective refocusing (sLASER) sequence with gradient offset independent adiabaticity (GOIA) pulses in addition to the routine mp-MRI, including T2-weighted imaging (T2WI), diffusion-weighted imaging (DWI) and quantitative dynamic contrast enhancement (DCE) for transition zone prostate cancer detection, localization and grading.MethodsForty-one transition zone prostate cancer patients underwent mp-MRI with an external phased-array coil. Normal and cancer regions were delineated by two radiologists and divided into low-risk, intermediate-risk, and high-risk categories based on TRUS guided biopsy results. Support vector machine models were built using different clinically applicable combinations of T2WI, DWI, DCE, and MRSI. The diagnostic performance of each model in cancer detection was evaluated using the area under curve (AUC) of the receiver operating characteristic diagram. Then accuracy, sensitivity and specificity of each model were calculated. Furthermore, the correlation of mp-MRI parameters with low-risk, intermediate-risk and high-risk cancers were calculated using the Spearman correlation coefficient.ResultsThe addition of MRSI to T2WI + DWI and T2WI + DWI + DCE improved the accuracy, sensitivity and specificity for cancer detection. The best performance was achieved with T2WI + DWI + MRSI where the addition of MRSI improved the AUC, accuracy, sensitivity and specificity from 0.86 to 0.99, 0.83 to 0.96, 0.80 to 0.95, and 0.85 to 0.97 respectively. The (choline + spermine + creatine)/citrate ratio of MRSI showed the highest correlation with cancer risk groups (r = 0.64, p < 0.01).ConclusionThe inclusion of GOIA-sLASER MRSI into conventional mp-MRI significantly improves the diagnostic accuracy of the detection and aggressiveness assessment of transition zone prostate cancer.

Post Covid-19 Bio-Imaging: Cancer Detection &amp; Secured Procurement through Dual Neurons Genetic Key (DNGK) in Advanced Medical Sciences

Cancer is one of the highly-rated causes that lead to human mortality. Nowadays with the greater affect of the COVID-19 pandemic, co-morbid patients are at the dual risk of death. Therefore, the main aim of this paper is the specific detection of the cancer cells using nanoparticles further, report analysis using Artificial intelligence, and then the transmission of the medical report is to be done in a neural secured procurement. A simple mechanism to detect cancerous cells through Artificial Neural Networks (ANN) has been proposed here. Moreover, secure attainment of the patients’ medical data has been shown here with the help of Dual Neurons Genetic Key (DNGK). Structural and functionally equivalent ANNs have been iterated to generate the DNGK. In addition, genetic operations were included to make the session key more secured from the opponents. Nanoparticles are frequently used for specific cancer detection on the human body. A revolution in the form of telemedicine in the advanced medical sciences has emerged with the cameo of novel coronavirus things (IoT). It has helped to curtail the coronavirus chain through remote treatments. An Artificial Neural Network will be trained to detect the cancerous cells of the human body. The decision generated by ANN would be encrypted through the AES algorithm and DHNK before procured to the network. The Artificial Neural Network had been trained on different bio-images so that it generates an automated decision. Thus, prompt, safe, and automated cancer detection may be done using this proposed technique. Results derived from different tests on the proposed technique were evaluated and thus, validating the entire proposed technique. Thus, loads of societal development would happen in the fields of Medical Sciences, especially during these post-COVID-19 crisis hours.

Histologic validation of auto-contoured dominant intraprostatic lesions on [18F] DCFPyL PSMA-PET imaging

BackgroundPSMA-PET11Prostate-specific membrane antigen positron-emission tomography. has shown good concordance with histology, but there is a need to investigate the ability of PSMA-PET to delineate DIL22Dominant intraprostatic lesion. boundaries for guided biopsy and focal therapy planning. ObjectiveTo determine threshold and margin combinations that satisfy the following criteria: ≥95% sensitivity with max specificity and ≥95% specificity with max sensitivity. Design, setting and participantsWe registered pathologist-annotated whole-mount mid-gland prostatectomy histology sections cut in 4.4 mm intervals from 12 patients to pre-surgical PSMA-PET/MRI by mapping histology to ex-vivo imaging to in-vivo imaging. We generated PET-derived tumor volumes using boundaries defined by thresholded PET volumes from 1–100% of SUV33Standard uptake value.max in 1% intervals. At each interval, we applied margins of 0–30 voxels in one voxel increments, giving 3000 volumes/patient. Outcome measurementsMean and standard deviation of sensitivity and specificity for cancer detection within the 2D oblique histologic planes that intersected with the 3D PET volume for each patient. Results and limitationsA threshold of 67% SUV max with an 8.4 mm margin achieved a (mean ± std.) sensitivity of 95.0 ± 7.8% and specificity of 76.4 ± 14.7%. A threshold of 81% SUV max with a 5.1 mm margin achieved sensitivity of 65.1 ± 28.4% and specificity of 95.1 ± 5.2%. ConclusionsPreliminary evidence of thresholding and margin expansion of PSMA-PET images targeted at DILs validated with histopathology demonstrated excellent mean sensitivity and specificity in the setting of focal therapy/boosting and guided biopsy. These parameters can be used in a larger validation study supporting clinical translation.

Highly accurate NGS-based multi-gene testing in the diagnosis of thyroid nodules with indeterminate cytology.

e13579 Background: Thyroid nodules are highly prevalent, Fine-needle aspiration (FNA) is the standard pre-operative tool for diagnosis. However, some of the samples are classified as indeterminate, which leads to unnecessary surgery. BRAF V600E mutation is often used as a diagnostic marker for thyroid cancer, and it is highly specific for papillary thyroid carcinoma (PTC). But BRAF mutation is rarely occurred in thyroid nodules with indeterminate cytology. To diagnose the indeterminate thyroid nodules precisely, some NGS-based multi-gene testing panel has been developed and clinically used in America and Europe, but rare research was reported in China. In this study, we evaluated the value of a next-generation sequencing (NGS) panel to cancer diagnosis in indeterminate thyroid nodules. Methods: From February 2018 to September 2018, 360 patients with thyroid nodules who underwent FNA at Peking University Cancer Hospital were enrolled. And the FNA samples with indeterminate cytology were evaluated using a next-generation sequencing (NGS) assay, including 16 genes analyzed for point mutations and 26 types of gene fusions. Diagnostic performance of this multi-gene testing panel was compared with BRAF V600E single gene mutation analysis. Results: 141 nodules were cytologically indeterminate among 360 patients on FNA biopsy, 72 of which were resected and analyzed by NGS successfully. Histologic analysis after surgery revealed 41 (56.9%) cancers in these 72 patients. The multi-gene testing assay could classify 30/41 cancers correctly, showing a sensitivity of 73.2%, specificity of 96.8%, positive predictive value of 96.8%, and negative predictive value of 73.2%. The diagnostic accuracy of the multi-gene testing was significantly higher than the BRAF V600E mutation analysis (83.3% vs 73.6%, x2= 31.588, p &lt; 0.01). Conclusions: Our study demonstrated that the multi-gene testing provided both high sensitivity and high specificity for cancer detection in thyroid nodules with indeterminate cytology, and its accuracy was much higher than BRAF V600E mutation test.

N-glycan structures of target cancer biomarker characterized by two-dimensional gel electrophoresis and mass spectrometry

Glycoproteins are important biomarkers for cancers, while most glycoproteomics biomarkers suffering from low sensitivity and specificity due to their uncharacterized glycan structures. AZGP1 is a potential biomarker for salivary diagnostics of lung cancer, which is used as a model glycoprotein in this study for method development. We initially analyzed salivary N-glycoproteome by using lectin affinity chromatography and more than 300 N-glycoproteins were identified, including AZGP1. 7 gel spots of AZGP1 were resolved by two-dimensional gel electrophoresis and further confirmed by two-dimensional western blot as well as mass spectrometry. The isomeric glycan structures of AZGP1 in these spots were systematically characterized both at composition level and at structure level. Our results revealed 10 glycan compositions for salivary AZGP1, including core fucosylated glycans on Asn128 and sialylated glycans on Asn109 and Asn112. We further compared the glycan structures of salivary AZGP1 from lung cancer group and control group. Accordingly, 14 and 7 potential glycan structures were successfully revealed, respectively. In total, 15 glycan compositions and 22 potential glycan structures were identified and characterized for AZGP1, including some different structures with the same compositions. In particular, 5 potential glycan structures were identified as lung cancer unique signatures. Our developed strategy holds promise for thorough identification of glycan structures on a target glycoprotein biomarker. In-depth characterization of its glycan structures will ultimately enhance its sensitivity and specificity for cancer detection.

Real time ultrasound molecular imaging of prostate cancer with PSMA-targeted nanobubbles

Contrast-enhanced ultrasound with microbubbles has shown promise in detection of prostate cancer (PCa), but sensitivity and specificity remain challenging. Targeted nanoscale-contrast agents with improved capability to accumulate in tumors may result in prolonged signal enhancement and improved detection of PCa with ultrasound. Here we report nanobubbles (NB) that specifically targets prostate specific membrane antigen (PSMA) overexpressed in PCa. The PSMA-targeted-NB (PSMA-NB) were utilized to simultaneously image dual-flank PCa (PSMA-positive PC3pip and PSMA-negative PC3flu) to examine whether the biomarker can be successfully detected and imaged in a mouse model. Results demonstrate that active targeting rapidly and selectively enhances tumor accumulation and tumor retention. Importantly, these processes could be visualized and quantified, in real-time, with clinical ultrasound. Such demonstration of the immense yet underutilized potential of ultrasound in the molecular imaging area can open the door to future opportunities for improving sensitivity and specificity of cancer detection using parametric NB-enhanced ultrasound imaging.

Cancer Control Continuum in Korean American Community Newspapers: What Is the Association with Source Nationality-US vs. Korea?

Prior research suggests that cancer information obtained from Korean American community media, which are the primary health information sources among the population, does not connect to Korean Americans' increased cancer knowledge or cancer protective/detective behavior. We aim to identify the reason by analyzing cancer type, cancer control continuum, and cancer topic presented in Korean American community newspapers. The nationality of news source, US and Korea, and its association with the cancer coverage were examined. We found that among articles that cited any source, nearly one third used a source from Korea. The source nationality was associated with cancer coverage. In particular, cancer risk factors and screening were more likely to be discussed when a US source was cited as compared to when no source was cited. Korean sources were never or rarely observed in articles focusing on a few cancer sites (e.g., breast and prostate, which Korean Americans have higher risks compared to native Koreans), cancer preventive behaviors (diet, physical activity, no smoking), and specific cancer detection methods (mammogram, pap-smear). We suggest Korean American media to reflect the cancer priority and information needs among Korean Americans, which are varied from native Koreans, and to acknowledge the differences in cancer prevention and detection guidelines between the U.S. and Korean healthcare system. Also, the U.S. government should disseminate cancer screening and prevention guidelines, customized to racial/ethnic groups' cancer prevalence and communication preference.

DNA Methylation Cancer Biomarkers: Translation to the Clinic.

Carcinogenesis is accompanied by widespread DNA methylation changes within the cell. These changes are characterized by a globally hypomethylated genome with focal hypermethylation of numerous 5’-cytosine-phosphate-guanine-3’ (CpG) islands, often spanning gene promoters and first exons. Many of these epigenetic changes occur early in tumorigenesis and are highly pervasive across a tumor type. This allows DNA methylation cancer biomarkers to be suitable for early detection and also to have utility across a range of areas relevant to cancer detection and treatment. Such tests are also simple in construction, as only one or a few loci need to be targeted for good test coverage. These properties make cancer-associated DNA methylation changes very attractive for development of cancer biomarker tests with substantive clinical utility. Across the patient journey from initial detection, to treatment and then monitoring, there are several points where DNA methylation assays can inform clinical practice. Assays on surgically removed tumor tissue are useful to determine indicators of treatment resistance, prognostication of outcome, or to molecularly characterize, classify, and determine the tissue of origin of a tumor. Cancer-associated DNA methylation changes can also be detected with accuracy in the cell-free DNA present in blood, stool, urine, and other biosamples. Such tests hold great promise for the development of simple, economical, and highly specific cancer detection tests suitable for population-wide screening, with several successfully translated examples already. The ability of circulating tumor DNA liquid biopsy assays to monitor cancer in situ also allows for the ability to monitor response to therapy, to detect minimal residual disease and as an early biomarker for cancer recurrence. This review will summarize existing DNA methylation cancer biomarkers used in clinical practice across the application domains above, discuss what makes a suitable DNA methylation cancer biomarker, and identify barriers to translation. We discuss technical factors such as the analytical performance and product-market fit, factors that contribute to successful downstream investment, including geography, and how this impacts intellectual property, regulatory hurdles, and the future of the marketplace and healthcare system.

Performance Analysis of Various Nanocontrast Agents and CAD Systems for Cancer Diagnosis.

Cancer is a disease which involves the abnormal cell growth that has the potential of dispersal to other parts of the body. Among various conventional anatomical imaging techniques for cancer diagnosis, Magnetic Resonance Imaging (MRI) provides the best spatial resolution and is noninvasive. Current efforts are directed at enhancing the capabilities of MRI in oncology by adding contrast agents. Recently, the superior properties of nanomaterials (extremely smaller in size, good biocompatibility and ease in chemical modification) allow its application as a contrast agent for early and specific cancer detection through the MRI. The precise detection of cancer region from any imaging modality will lead to a thriving treatment for cancer patients. The better localization of radiation dose can be attained from MRI by using suitable image processing algorithms. As there are many works that have been proposed for automatic detection for cancers, the effort is also put in to provide an effective survey of Computer Aided Diagnosis (CAD) system for different types of cancer detection with increased efficiency based on recent research works. Even though there are many surveys on MRI contrast agents, they only focused on a particular type of cancer. This study deeply presents the use of nanocontrast agents in MRI for different types of cancer diagnosis. The main aim of this paper is to critically review the available compounds used as nanocontrast agents in MRI modality for different types of cancers. It also includes the review of different methods for cancer cell detection and classification. A comparative analysis is performed to analyze the effect of different CAD systems.

Non-contrast MRI for breast screening: preliminary study on detectability of benign and malignant lesions in women with dense breasts.

The importance of breast cancer screening has long been known. Unfortunately, there is no imaging modality for screening women with dense breasts that is both sensitive and without concerns regarding potential side effects. The purpose of this study is to explore the possibility of combined diffusion-weighted imaging and turbo inversion recovery magnitude MRI (DWI + TIRM) to overcome the difficulty of detection sensitivity and safety. One hundred and seventy-six breast lesions from 166 women with dense breasts were retrospectively evaluated. The lesion visibility, area under the curve (AUC), sensitivity and specificity of cancer detection by MG, DWI + TIRM, and clinical MRI were evaluated and compared. MG plus clinical MRI served as the gold standard for lesion detection and pathology served as the gold standard for cancer detection. Lesion visibility of DWI + TIRM (96.6%) was significantly superior to MG (67.6%) in women with dense breasts (p < 0.001). There was no significant difference compared with clinical MRI. DWI + TIRM showed higher accuracy (AUC = 0.935) and sensitivity (93.68%) for breast cancer detection than MG (AUC = 0.783, sensitivity = 46.32%), but was comparable to clinical MRI (AUC = 0.944, sensitivity = 93.68%). The specificity of DWI + TIRM (83.95%) was lower than MG (98.77%), but higher than clinical MRI (77.78%). DWI combined with TIRM could be a safe, sensitive, and practical alternative for screening women with dense breasts.