Non-invasive Cancer Diagnosis Research Articles

Development and validation of an artificial neural network model for non-invasive gastric cancer screening and diagnosis

Non-invasive and cost-effective diagnosis of gastric cancer is essential to improve outcomes. Aim of the study was to establish a neural network model based on patient demographic data and serum biomarker panels to aid gastric cancer diagnosis. A total of 295 patients hospitalized in Nanjing Drum Tower hospital diagnosed with gastric cancer based on tissue biopsy, and 423 healthy volunteers were included in the study. Demographical information and tumor biomarkers were obtained from Hospital Information System (HIS) as original data. Pearson's correlation analysis was applied on 574 individuals’ data (training set, 229 patients and 345 healthy volunteers) to analyze the relationship between each variable and the final diagnostic result. And independent sample t test was used to detect the differences of the variables. Finally, a neural network model based on 14 relevant variables was constructed. The model was tested on the validation set (144 individuals including 66 patients and 78 healthy volunteers). The predictive ability of the proposed model was compared with other common machine learning models including logistic regression and random forest. Tumor markers contributing significantly to gastric cancer screening included CA199, CA125, AFP, and CA242 were identified, which might be considered as important inspection items for gastric cancer screening. The accuracy of the model on validation set was 86.8% and the F1-score was 85.0%, which were better than the performance of other models under the same condition. A non-invasive and low-cost artificial neural network model was developed and proved to be a valuable tool to assist gastric cancer diagnosis.

Construction of broom-like Ag@N,O-C sensing interface for electrochemical detection of circulating tumor DNA using entropy-driven DNA walker

In human peripheral blood, circulating tumor DNA (ctDNA) is an excellent tumor biomarker for noninvasive diagnosis, therapy and prognosis of cancer. Herein, an innovative enzyme-free electrochemical sensor sensitized with broom-like Ag@N,O-C hierarchical nanomaterials and entropy-driven DNA walker was designed for PIK3CA E545K ctDNA assay. In this work, N, O-doped carbon layers were used to completely coat Ag nanoparticles, and then were assembled into three-dimensional broom-like nanomaterials with hierarchical structure. The application of Ag@N,O-C broom-like hierarchical nanomaterials (Ag@N,O-C BLHS) as electrode material not only facilitated electron transfer, but also increased functional active sites for a high-density assembly of DNA walking substrates. Via the entropy-driven catalytic reaction of DNA walker, one target ctDNA initiated the dissociation of abundant electroactive tags from the electrode surface, achieving a one-to-multiple amplification effect. By measuring electrochemical responses, PIK3CA E545K ctDNA was quantified with 10 aM detection limit. Additionally, the enzyme-free amplified sensing interface achieved the direct detection of ctDNA in plasma samples from breast cancer patients and healthy human. Overall, the good selectivity, reproducibility and practical application ability confirmed a promising potential of the sensor for disease diagnosis.

Islamic and Scientific Views on The Law of Using Urine Samples as Candidates for Early Detection of Cancer

Abstract
 The growing prevalence of cancer patients is a significant obstacle to global human growth. Prostate carcinoma is one of the types of cancer that kills the most men. The second most frequently diagnosed kind of carcinoma is prostate cancer (Pca), which is also the sixth biggest cause of death in males globally. Urine can be a candidate for early diagnosis of non-invasive cancer, however the rule on the use of urine as a sample in Islam has not yet been thoroughly addressed. Prostate cancer testing is still an intrusive procedure. The goal of this study was to ascertain the legality of using urine samples as potential candidates for the early identification of cancer from both an Islamic and scientific standpoint. Meta-analysis is combined with a qualitative methodology. According to the study's findings, urine may be a candidate for the early detection of cancer. Legally speaking, urine can be used as long as it is not applied directly to patients either topically or orally in order to prevent it from becoming haram. This is because the authors were unable to find any evidence to support the prohibition of using urine on patients.
 

Indocyanine Green-Conjugated Superparamagnetic Iron Oxide Nanoworm for Multimodality Breast Cancer Imaging.

Breast cancer is the leading cause of cancer-associated deaths among women. Techniques for non-invasive breast cancer detection and imaging are urgently needed. Multimodality breast cancer imaging is attractive since it can integrate advantages from several modalities, enabling more accurate cancer detection. In order to accomplish this, indocyanine green (ICG)-conjugated superparamagnetic iron oxide nanoworm (NW-ICG) has been synthesized as a contrast agent. When evaluated in a spontaneous mouse breast cancer model, NW-ICG gave a large tumor to normal tissue contrasts in multiple imaging modalities including magnetic particle imaging, near-infrared fluorescence imaging, and photoacoustic imaging, providing more comprehensive detection and imaging of breast cancer. Thus, NW-ICGs are an attractive platform for non-invasive breast cancer diagnosis.

Magneto-Nanomechanical Array Biosensor for Ultrasensitive Detection of Oncogenic Exosomes for Early Diagnosis of Cancers.

Exosomes are a class of nanoscale vesicles secreted by cells, which contain abundant information closely related to parental cells. The ultrasensitive detection of cancer-derived exosomes is highly significant for early non-invasive diagnosis of cancer. Here, an ultrasensitive nanomechanical sensor is reported, which uses a magnetic-driven microcantilever array to selectively detect oncogenic exosomes. A magnetic force, which can produce a far greater deflection of microcantilever than that produced by the intermolecular interaction force even with very low concentrations of target substances, is introduced. This method reduced the detection limit to less than 10 exosomes mL-1 . Direct detection of exosomes in the serum of patients with breast cancer and in healthy people showed a significant difference. This work improved the sensitivity by five orders of magnitude as compared to that of traditional nanomechanical sensing based on surface stress mode. This method can be applied parallelly for highly sensitive detection of other microorganisms (such as bacteria and viruses) by using different probe molecules, which can provide a supersensitive detection approach for cancer diagnosis, food safety, and SARS-CoV-2 infection.

In Vitro and In Vivo Evaluation of Anti-Tumor Biological Functions of Enolase Targeted Peptide Modified Oxaliplatin-Loaded Fe3O4 Nanoparticles Alongside with Photothermal Radiotherapy

The goal of this research is to explore the anticancer effects of α-enolase targeted peptide (ETP) modified oxaliplatin-loaded Fe3O4 nanoparticles (ETP-PtFe NPs) and their synthesis, characterization, biological function, and characterization on breast cancer. The ETP-PtFe NPs were studied using transmission electron microscopy, dynamic light scattering, zeta potential analysis, and ultraviolet absorption spectroscopy. Nanocomplexes’ cytotoxicity and cell cycle distribution were studied utilizing flow cytometry tests in a total of eight trials. A unilateral subcutaneous tumor-bearing rat was created to test the anticancer effects of ETP-PtFe NPs In Vivo. In combination with near-infrared light irradiation, ETP-PtFe suppressed the proliferation of 4TI and MDA-MB-231 breast cancer cells much more than the pure material group in the CCK8 experiment. ETP-PtFe and NIR light irradiation significantly suppressed 4TI and MDA-MB-231 breast cancer cells in the G2/M phase of the cell cycle compared to the pure material group. This study found that ETP-PtFe combination with near infrared light irradiation was more effective In Vivo against tumors in mice with unilateral subcutaneous tumors than normal saline combined with near infrared light irradiation. The anticancer and photothermal effects of the ETP-PtFe nanocomposite In Vitro and In Vivo provide a promising notion and technique for non-invasive early diagnosis and non-surgical treatment of breast cancer’s primary tumor.

Urinary analysis based on surface-enhanced Raman scattering for the noninvasive screening of lung cancer

• The AuNPs-based SERS probes were developed for the detection of adenosine • The platform can identify adenosine, uric acid, guanine and creatinine in urine • The assay was successfully applied for the noninvasive screening of lung cancer We developed a reliable simple analysis of adenosine, creatinine and other nucleosides (cytidine and guanosine) with single measurement based on surface-enhanced Raman spectroscopy (SERS) using DSP-AuNPs with Cu 2+ ions probe and applied it to achieve noninvasive screening of lung cancer. The gold nanoparticles (AuNPs) were modified with 3,3′-dithiodipropionic acid di (N-hydroxysuccinimide ester) (DSP), which could react with above mentioned molecules followed with the aggregation of AuNPs at the presence of Cu 2+ , thus form the plasmonic hot spots to dramatically increase their fingerprint Raman signal. The probe of DSP-AuNPs was applied for the detail analysis of urinary adenosine of healthy people and lung cancer patients. The SERS measurement indicated a higher concentration of urinary adenosine for lung cancer patients than that of healthy people, which was consistent with the results measured by high-performance liquid chromatography (HPLC). In combination of Raman spectroscopy with the orthogonal partial least squares discriminant analysis (OPLS-DA) model, we are able to discriminate the lung cancer patients from healthy people with the urinary test. The results indicated that besides of adenosine, other metabolites including uric acid, guanine and creatinine may also be the potential tumor markers in urine for the noninvasive lung cancer diagnosis. Such a method paves a way for the noninvasive cancer screening and it can be further modified for the detection of other molecules on medical diagnosis.

Pre-clinical and clinical importance of miR-21 in human cancers: Tumorigenesis, therapy response, delivery approaches and targeting agents

The field of non-coding RNA (ncRNA) has made significant progress in understanding the pathogenesis of diseases and has broadened our knowledge towards their targeting, especially in cancer therapy. ncRNAs are a large family of RNAs with microRNAs (miRNAs) being one kind of endogenous RNA which lack encoded proteins. By now, miRNAs have been well-coined in pathogenesis and development of cancer. The current review focuses on the role of miR-21 in cancers and its association with tumor progression. miR-21 has both oncogenic and onco-suppressor functions and most of the experiments are in agreement with the tumor-promoting function of this miRNA. miR-21 primarily decreases PTEN expression to induce PI3K/Akt signaling in cancer progression. Overexpression of miR-21 inhibits apoptosis and is vital for inducing pro-survival autophagy. miR-21 is vital for metabolic reprogramming and can induce glycolysis to enhance tumor progression. miR-21 stimulates EMT mechanisms and increases expression of MMP-2 and MMP-9 thereby elevating tumor metastasis. miR-21 is a target of anti-cancer agents such as curcumin and curcumol and its down-regulation impairs tumor progression. Upregulation of miR-21 results in cancer resistance to chemotherapy and radiotherapy. Increasing evidence has revealed the role of miR-21 as a biomarker as it is present in both the serum and exosomes making them beneficial biomarkers for non-invasive diagnosis of cancer.

Developments and Clinical Applications of Noninvasive Optical Technologies for Skin Cancer Diagnosis.

Skin cancer has shown a sharp increase in prevalence over the past few decades and currently accounts for one-third of all cancers diagnosed. The most lethal form of skin cancer is melanoma, which develops in 4% of individuals. The rising prevalence and increased number of fatalities of skin cancer put a significant burden on healthcare resources and the economy. However, early detection and treatment greatly improve survival rates for patients with skin cancer. Since the rising rates of both the incidence and mortality have been particularly noticeable with melanoma, significant resources have been allocated to research aimed at earlier diagnosis and a deeper knowledge of the disease. Dermoscopy, reflectance confocal microscopy, optical coherence tomography, multiphoton-excited fluorescence imaging, and dermatofluorescence are only a few of the optical modalities reviewed here that have been employed to enhance noninvasive diagnosis of skin cancer in recent years. This review article discusses the methodology behind newly emerging noninvasive optical diagnostic technologies, their clinical applications, and advantages and disadvantages of these techniques, as well as the potential for their further advancement in the future.

Ultramultiplex NaLnF4 Nanosatellites Combined with ICP-MS for Exosomal Multi-miRNA Analysis and Cancer Classification.

Quantification of exosomal multi-miRNA can reveal the initiation, progression, and metastasis of tumors, which is conducive to the noninvasive early diagnosis of cancer. However, low-sensitivity and single-plex detection characteristics of traditional methods seriously hinder the accuracy and specificity of exosomal miRNAs in cancer diagnosis. Herein, we design an ultramultiplexing strategy that enables simultaneous and sensitive detection of multiple exosomal miRNAs by nanosatellites (magnetic beads (MBs) @ NaLnF4) and catalytic hairpin assembly (CHA) amplification in combination with inductively coupled plasma-mass spectrometry (ICP-MS) to diagnose cancer accurately. The competitive binding of target exosomal miRNAs with the recognition sequences on nanosatellites triggers the drop of NaLnF4 from MBs, followed by a CHA reaction that releases more NaLnF4 labels for ICP-MS detection. This method is used to detect ten types of miRNAs simultaneously with a detection limit of 0.01 fM, which is one order of magnitude lower than the quantitative reverse transcription polymerase chain reaction (qRT-PCR) method. Linear discriminant analysis as a machine learning algorithm is subsequently applied to analyze the signals of exosomal multi-miRNA, and the discrimination accuracy of ten cell exosomes reaches 98.6%. In a clinical cohort of 42 patients, including five cancer types and healthy controls, exosomal multi-miRNA analysis achieves accurate cancer diagnosis and classification with 100% accuracy. Our results show that the combination of nanosatellites, CHA, and ICP-MS provides a universal biosensing platform for simultaneous and ultrasensitive detection of multiple targets.

Circulatory RNA based non-invasive detection and diagnosis of breast cancer

Breast carcinoma is the most prevalent and lethal form of carcinoma in women, as well as the most prominent source of cancer-related mortality in women. The most widespread form of non-invasive breast carcinoma is ductal carcinoma in situ (DCIS). Early detection of breast carcinoma improves the chances of rehabilitation and survival, lowering mortality rates. Limitations of mammography as a screening test have made it imperative to develop new, non-invasive, and more convenient alternatives for the prognosis of breast carcinoma. Circulatory RNAs (miRNAs) have been included in a novel category of non-coding, endogenous, small RNA fragments that can be considered gene expression regulators, influencing key processes in cancer development. Peculiar expressions and firmness of circulatory RNAs exhibit a promising possibility of their use as biomarkers in the prognosis of mammary tumor.

An electrochemical genosensing platform for the relative quantification of the circulating long noncoding RNA CCAT1 to aid in the diagnosis of colorectal cancer

Long noncoding RNAs (lncRNAs) are promising biomarkers for the noninvasive diagnosis of colorectal cancer, but detection of cancer-associated changes in their expression levels is now restricted to the use of RT-qPCR. To extend the clinical applicability of these biomarkers, we developed an electrochemical platform, integrated by two different sandwich genosensors, for the relative quantification of a lncRNA called colon cancer associated transcript-1 (CCAT1) with respect to the mRNA GAPDH as an endogenous control. To achieve highly sensitive detection, and in contrast to previous sensors of this class, we use multiple fluorescein-tagged hybridization assistant probes allowing the incorporation of multiple redox enzymes per target molecule, in turn favoring the selective capture of these highly-structured targets onto the sensing platform. The resultant biosensors show high sensitivity (9.7 ± 0.3 µA nM−1 for CCAT1 and 7.3 ± 0.1 µA nM−1 for GAPDH) and low limits of detection (990 fM and 1830 fM for CCAT1 and GAPDH, respectively). Coupled to a PCR assay, we detect the lncRNA at clinically relevant concentrations. Preliminary results using total RNA extracted from the colorectal cancer cell line HT29 and spiked plasma samples from healthy individuals suggest that this new sensing architecture is sensitive and selective enough to obtain the expression level of CCAT1 simply from the ratio of outputs from the two platform sensors. We envision that the same design could be applied to detect other lncRNAs associated to various malignancies, facilitating early cancer diagnosis.

Plasma-Methylated SEPT9 for the Noninvasive Diagnosis of Gastric Cancer.

Gastric cancer (GC) is one of the most prevalent cancers globally. This study was designed to evaluate the potential performance of plasma SEPT9 methylation (mSEPT9) as a noninvasive biomarker for the diagnosis of GC. A total of 182 participants, i.e., 60 patients with GC, 39 with chronic superficial gastritis (CSG), 27 with chronic atrophic gastritis (CAG), 30 with gastric ulcer (GU), and 26 with gastric polys (GP), were recruited. The mSEPT9 level was measured using real-time polymerase chain reaction. As a diagnostic target, mSEPT9 (1/3 algorithm) had a sensitivity of 48.33 (95% confidence interval (CI): 35.40-61.48%) and a specificity of 86.89% (95% CI: 79.28-92.09%), and mSEPT9 (2/3 algorithm) had a sensitivity of 33.33 (95% CI: 22.02-46.79%) and a specificity of 98.36% (95% CI: 93.61-99.72%). The area under the receiver operating characteristic curve (ROC) curve of mSEPT9 was 0.698 (95% CI: 0.609-0.787) for the differentiation of GC from benign gastric diseases. The effectiveness of mSEPT9 (1/3 algorithm) was superior to that of CEA, CA19-9, and CA72-4. mSEPT9 was positively correlated with T, N, M, and the clinical stage of GC. Plasma mSEPT9 might serve as a useful and noninvasive biomarker for the diagnosis of GC.

Integrated Tissue and Blood miRNA Expression Profiles Identify Novel Biomarkers for Accurate Non-Invasive Diagnosis of Breast Cancer: Preliminary Results and Future Clinical Implications.

We aimed to identify miRNAs that were closely related to breast cancer (BRCA). By integrating several methods including significance analysis of microarrays, fold change, Pearson's correlation analysis, t test, and receiver operating characteristic analysis, we developed a decision-tree-based scoring algorithm, called Optimized Scoring Mechanism for Primary Synergy MicroRNAs (O-PSM). Five synergy miRNAs (hsa-miR-139-5p, hsa-miR-331-3p, hsa-miR-342-5p, hsa-miR-486-5p, and hsa-miR-654-3p) were identified using O-PSM, which were used to distinguish normal samples from pathological ones, and showed good results in blood data and in multiple sets of tissue data. These five miRNAs showed accurate categorization efficiency in BRCA typing and staging and had better categorization efficiency than experimentally verified miRNAs. In the Protein-Protein Interaction (PPI) network, the target genes of hsa-miR-342-5p have the most regulatory relationships, which regulate carcinogenesis proliferation and metastasis by regulating Glycosaminoglycan biosynthesis and the Rap1 signaling pathway. Moreover, hsa-miR-342-5p showed potential clinical application in survival analysis. We also used O-PSM to generate an R package uploaded on github (SuFei-lab/OPSM accessed on 22 October 2021). We believe that miRNAs included in O-PSM could have clinical implications for diagnosis, prognostic stratification and treatment of BRCA, proposing potential significant biomarkers that could be utilized to design personalized treatment plans in BRCA patients in the future.

A Portable Fluorescence Sensor with Improved Performance for Aniline Monitoring

AbstractAniline is an important biomarker in human exhaled breath for lung cancer, thus aniline sensing is of paramount importance. However, highly sensitive and selective detection of aniline in high moisture environment of exhaled breath is still challenging. In this work, a new fluorescence sensor for aniline with ultrahigh sensitivity is constructed. The o‐carborane modified pyromellitic diimide derivative (CB‐PMI) is designed and prepared as the sensitive layer for the fluorescence sensor. As‐prepared sensing films exhibit a highly improved response toward aniline vapor. The good sensing performance of the fluorescence films in terms of response speed, selectivity, and reusability is also realized, and the detection limit can be as low as 0.1 ppt. The detection linear slope ranges from 1 to 50 ppt. In addition, a homemade portable sensing platform is successfully constructed, which may be a promising prototype for the future detection of modulating breath samples. The reported fluorescence sensor offers a new paradigm for the simple, low cost, and noninvasive diagnosis of lung cancer.

MicroRNA-125a-3p, -4530, and -92a as a Potential Circulating MicroRNA Panel for Noninvasive Pancreatic Cancer Diagnosis.

MicroRNA (miRNA) expression dysregulations in pancreatic ductal adenocarcinoma (PDAC) have been studied widely for their diagnostic and prognostic utility. By the use of bioinformatics-based methods, in our previous study, we identified some potential miRNA panels for diagnosis of pancreatic cancer patients from noncancerous controls (the screening stage). In this report, we used 142 plasma samples from people with and without pancreatic cancer (PC) to conduct RT-qPCR differential expression analysis to assess the strength of the first previously proposed diagnostic panel (consisting of miR-125a-3p, miR-4530, and miR-92a-2-5p). As the result, we identified significant upregulation for all the three considered miRNAs in the serum of PC patients. After that, a three-miRNA panel in serum was developed. The area under the receiver operating characteristic curves (AUC) for the panel were 0.850, 0.910, and 0.86, respectively, indicating that it had a higher diagnostic value than individual miRNAs. Therefore, we detected a promising three-miRNA panel in the plasma for noninvasive PC diagnosis (miR-125a-3p, miR-4530, and miR-92a-2-5p).

Plasma Methylated RNF180 for Noninvasive Diagnosis of Gastric Cancer.

Background RNF180 is a tumor suppressor gene involved in cell development, proliferation, and apoptosis. Methylation of RNF180 (mRNF180) leads to low expression of RNF180, which is closely related to the occurrence and development of gastric cancer (GC). This study was designed to evaluate the potential performance of plasma mRNF180 as noninvasive biomarker for the diagnosis of GC. Methods A total of 156 participants, including 60 patients with GC, 39 with chronic superficial gastritis (CSG), 27 with chronic atrophic gastritis (CAG), and 30 with gastric ulcer (GU) were recruited for this study. Plasma mRNF180 level was measured using real-time polymerase chain reaction. Results As a diagnostic target, mRNF180 had a sensitivity of 71.67% (95% CI: 58.36%–82.18%) and specificity of 59.38% (95% CI: 48.85%–69.14%). The area under the ROC curve value of mRNF180 was 0.731 (95% CI: 0.648%–0.813%) for differentiation of GC from benign gastric diseases (BGD). The effectiveness of mRNF180 was superior to that of CEA, CA199, and CA724. mRNF180 was positively correlated with age, tumor size, T stage, N stage, M stage, and clinical stage of patients with GC. Conclusions Plasma mRNF180 might serve as a useful and noninvasive biomarker for the diagnosis of GC and can be used to evaluate its prognosis.

Lung Cancer Nodules Detection via an Adaptive Boosting Algorithm Based on Self-Normalized Multiview Convolutional Neural Network.

Lung cancer is the deadliest cancer killing almost 1.8 million people in 2020. The new cases are expanding alarmingly. Early lung cancer manifests itself in the form of nodules in the lungs. One of the most widely used techniques for both lung cancer early and noninvasive diagnosis is computed tomography (CT). However, the intensive workload of radiologists to read a large number of scans for nodules detection gives rise to issues like false detection and missed detection. To overcome these issues, we proposed an innovative strategy titled adaptive boosting self-normalized multiview convolution neural network (AdaBoost-SNMV-CNN) for lung cancer nodules detection across CT scans. In AdaBoost-SNMV-CNN, MV-CNN function as a baseline learner while the scaled exponential linear unit (SELU) activation function normalizes the layers by considering their neighbors' information and a special drop-out technique (α-dropout). The proposed method was trained and tested using the widely Lung Image Database Consortium and Image Database Resource Initiative (LIDC-IDRI) and Early Lung Cancer Action Program (ELCAP) datasets. AdaBoost-SNMV-CNN achieved an accuracy of 92%, sensitivity of 93%, and specificity of 92% for lung nodules detection on the LIDC-IDRI dataset. Meanwhile, on the ELCAP dataset, the accuracy for detecting lung nodules was 99%, sensitivity 100%, and specificity 98%. AdaBoost-SNMV-CNN outperformed the majority of the model in accuracy, sensitivity, and specificity. The multiviews confer the model's good generalization and learning ability for diverse features of lung nodules, the model architecture is simple, and has a minimal computational time of around 102 minutes. We believe that AdaBoost-SNMV-CNN has good accuracy for the detection of lung nodules and anticipate its potential application in the noninvasive clinical diagnosis of lung cancer. This model can be of good assistance to the radiologist and will be of interest to researchers involved in the designing and development of advanced systems for the detection of lung nodules to accomplish the goal of noninvasive diagnosis of lung cancer.

Diagnostic Accuracy of Liquid Biomarkers for the Non-Invasive Diagnosis of Endometrial Cancer: A Systematic Review and Meta-Analysis.

Simple SummaryEndometrial cancer is common amongst women and rates are increasing annually. The diagnosis of this condition for women with bleeding after the menopause is invasive and often painful with many more women undergoing investigation than needed. A simple, non-invasive blood or urine test for the diagnosis of endometrial cancer is being sought. This review summarizes the current research on blood and urine tests and their diagnostic accuracy for detecting endometrial cancer. Whilst many blood and urine tests have been assessed there is currently no test that has a similar accuracy to biopsy of the uterine lining. However, this review demonstrates that there are some potential candidates which need to be explored by larger studies and on bigger groups of women. Endometrial cancer rates are increasing annually due to an aging population and rising rates of obesity. Currently there is no widely available, accurate, non-invasive test that can be used to triage women for diagnostic biopsy whilst safely reassuring healthy women without the need for invasive assessment. The aim of this systematic review and meta-analysis is to evaluate studies assessing blood and urine-based biomarkers as a replacement test for endometrial biopsy or as a triage test in symptomatic women. For each primary study, the diagnostic accuracy of different biomarkers was assessed by sensitivity, specificity, likelihood ratio and area under ROC curve. Forest plots of summary statistics were constructed for biomarkers which were assessed by multiple studies using data from a random-effect models. All but one study was of blood-based biomarkers. In total, 15 studies reported 29 different exosomal biomarkers; 34 studies reported 47 different proteomic biomarkers. Summary statistic meta-analysis was reported for micro-RNAs, cancer antigens, hormones, and other proteomic markers. Metabolites and circulating tumor materials were also summarized. For the majority of biomarkers, no meta-analysis was possible. There was a low number of small, heterogeneous studies for the majority of evaluated index tests. This may undermine the reliability of summary estimates from the meta-analyses. At present there is no liquid biopsy that is ready to be used as a replacement test for endometrial biopsy. However, to the best of our knowledge this is the first study to report and meta-analyze the diagnostic accuracy of different classes of blood and urine biomarkers for detection of endometrial cancer. This review may thus provide a reference guide for those wishing to explore candidate biomarkers for further research.

High in-vivo stability in preclinical and first-in-human experiments with [18F]AlF-RESCA-MIRC213: a 18F-labeled nanobody as PET radiotracer for diagnosis of HER2-positive cancers.

[18F]AlF-RESCA was introduced as a core particularly useful for 18F-labeling of heat-sensitive biomolecules. However, no translational studies have been reported up to now. Herein, we reported the first-in-human evaluation of an 18F-labeled anti-HER2 nanobody MIRC213 as a PET radiotracer for imaging HER2-positive cancers. MIRC213 was produced by E. coli and conjugated with ( ±)-H3RESCA-Mal. [18F]AlF-RESCA-MIRC213 was prepared at room temperature. Its radiochemical purity and stability of were determined by radio-HPLC with the size-exclusion chromatographic column. Cell uptake was performed in NCI-N87 (HER2 +) and MCF-7 (HER2-) cells and the cell-binding affinity was verified in SK-OV-3 (HER2 +) cells. Small-animal PET/CT was performed using SK-OV-3, NCI-N87, and MCF-7 tumor-bearing mice at 30min, 1h, and 2h post-injection. For blocking experiment, excess MIRC213 was co-injected with radiotracer. Biodistribution were performed on SKOV-3 and MCF-7 tumor-bearing mice at 2h post-injection. For clinical study, PET/CT images were acquired at 2h and 4h after injection of [18F]AlF-RESCA-MIRC213 (1.85-3.7MBq/kg) in six breast cancer patients (3 HER2-positive and 3 HER2-negative). All patients underwent [18F]-FDG PET/CT within a week for tissue selection purpose. Distribution and dosimetry were calculated. Standardized uptake values (SUV) were measured in tumors and normal organs. MIRC213 was produced with > 95% purity and modified with RESCA to obtain RESCA-MIRC213. [18F]AlF-RESCA-MIRC213 was prepared within 20min at room temperature with the radiochemical yield of 50.48 ± 7.6% and radiochemical purity of > 98% (n > 10), and remained stable in both PBS (88%) and 5% HSA (92%) after 6h. The 2h cellular uptake of [18F]AlF-RESCA-MIRC213 in NCI-N87 cells was 11.22 ± 0.60 AD%/105 cells. Its binding affinity Kd value was determined to be 1.23 ± 0.58nM. Small-animal PET/CT with [18F]AlF-RESCA-MIRC213 can clearly differentiate SK-OV-3 and NCI-N87 tumors from MCF-7 tumors and background with a high uptake of 4.73 ± 1.18 ID%/g and substantially reduced to 1.70 ± 0.13 ID%/g for the blocking group (p < 0.05) in SK-OV-3 tumors at 2h post-injection. No significant bone radioactivity was seen in the tumor-bearing animals. In all six breast cancer patients, there was no adverse reaction during study. The uptake of [18F]AlF-RESCA-MIRC213 was mainly in lacrimal gland, parotid gland, submandibular gland, thyroid gland, gallbladder, kidneys, liver, and intestines. There was no significant bone radioactivity accumulation in cancer patients. [18F]AlF-RESCA-MIRC213 had significantly higher tumor uptake in lesions from HER2-positive patients than that lesions from HER2-negative patients (SUVmax of 3.62 ± 1.56 vs. 1.41 ± 0.41, p = 0.0012) at 2h post-injection. The kidneys received the highest radiation dose of 2.42 × 10-1mGy/MBq, and the effective dose was 1.56 × 10-2mSv/MBq. [18F]AlF-RESCA-MIRC213 could be prepared with high radiolabeling yield under mild conditions. [18F]AlF-RESCA-MIRC213 has relatively high stability both in vitro and in vivo. The results from clinical transformation suggest that [18F]AlF-RESCA-MIRC213 PET/CT is a safe procedure with favorable pharmacokinetics and dosimetry profile, and it is a promising new PET radiotracer for noninvasive diagnosis of HER2-positive cancers.