Identification and validation of novel circulating biomarkers for early diagnosis of lung cancer

Hsa_circ_0001480 affects osteosarcoma progression by regulating the miR-363-3p/IBSP pathway

Osteosarcoma (OS) is a malignant bone tumor that commonly affects young individuals. Circular RNAs (circRNAs) are associated with OS progression. In this study, we aimed to determine the role of hsa_circ_0001480 (circ_0001480) in OS development. OS cell invasion, viability, and colony numbers were assessed via transwell, cell counting kit-8, and colony formation assays, respectively. Tumor growth in vivo was also assessed using an OS mouse model. Additionally, targeted associations among the integrin-binding sialoprotein (IBSP), microRNA (miR)-363-3p, and circ_0001480 were evaluated via RNA immunoprecipitation and dual luciferase reporter assays, whereas their expression levels in OS cells and tissues were determined via quantitative reverse transcription-polymerase chain reaction and western blotting. Loss of circ_0001480 or IBSP significantly inhibited the proliferation and invasion of OS cells, but this effect was reversed by miR-363-3p downregulation. Moreover, circ_0001480 knockdown inhibited neoplasm growth in vivo. circ_0001480 directly bound to miR-363-3p, which further modulated IBSP. Both circ_0001480 and IBSP levels were high, whereas miR-363-3p levels were low in OS cells. Furthermore, low miR-363-3p levels attenuated the suppressive effects of circ_0001480 silencing on the proliferation and invasion of OS cells; however, loss of IBSP partially reversed these effects. Overall, our findings revealed circ_0001480 an oncogenic circRNA stimulating OS progression by modulating the miR-363-3p/IBSP pathway, suggesting its potential for OS treatment.

A Cell-free DNA Blood-Based Test for Colorectal Cancer Screening

BACKGROUND

Colorectal cancer is the third most diagnosed cancer in adults in the United States. Early detection could prevent more than 90% of colorectal cancer-related deaths, yet more than one third of the screening-eligible population is not up to date with screening despite multiple available tests. A blood-based test has the potential to improve screening adherence, detect colorectal cancer earlier, and reduce colorectal cancer-related mortality.

METHODS

We assessed the performance characteristics of a cell-free DNA (cfDNA) blood-based test in a population eligible for colorectal cancer screening. The coprimary outcomes were sensitivity for colorectal cancer and specificity for advanced neoplasia (colorectal cancer or advanced precancerous lesions) relative to screening colonoscopy. The secondary outcome was sensitivity to detect advanced precancerous lesions.

RESULTS

The clinical validation cohort included 10,258 persons, 7861 of whom met eligibility criteria and were evaluable. A total of 83.1% of the participants with colorectal cancer detected by colonoscopy had a positive cfDNA test and 16.9% had a negative test, which indicates a sensitivity of the cfDNA test for detection of colorectal cancer of 83.1% (95% confidence interval [CI], 72.2 to 90.3). Sensitivity for stage I, II, or III colorectal cancer was 87.5% (95% CI, 75.3 to 94.1), and sensitivity for advanced precancerous lesions was 13.2% (95% CI, 11.3 to 15.3). A total of 89.6% of the participants without any advanced colorectal neoplasia (colorectal cancer or advanced precancerous lesions) identified on colonoscopy had a negative cfDNA blood-based test, whereas 10.4% had a positive cfDNA blood-based test, which indicates a specificity for any advanced neoplasia of 89.6% (95% CI, 88.8 to 90.3). Specificity for negative colonoscopy (no colorectal cancer, advanced precancerous lesions, or nonadvanced precancerous lesions) was 89.9% (95% CI, 89.0 to 90.7).

CONCLUSIONS

In an average-risk screening population, this cfDNA blood-based test had 83% sensitivity for colorectal cancer, 90% specificity for advanced neoplasia, and 13% sensitivity for advanced precancerous lesions. (Funded by Guardant Health; ECLIPSE ClinicalTrials.gov number, NCT04136002.).

Integrated models of blood protein and metabolite enhance the diagnostic accuracy for Non-Small Cell Lung Cancer

BACKGROUND

For early screening and diagnosis of non-small cell lung cancer (NSCLC), a robust model based on plasma proteomics and metabolomics is required for accurate and accessible non-invasive detection. Here we aim to combine TMT-LC-MS/MS and machine-learning algorithms to establish models with high specificity and sensitivity, and summarize a generalized model building scheme.

METHODS

TMT-LC-MS/MS was used to discover the differentially expressed proteins (DEPs) in the plasma of NSCLC patients. Plasma proteomics-guided metabolites were selected for clinical evaluation in 110 NSCLC patients who were going to receive therapies, 108 benign pulmonary diseases (BPD) patients, and 100 healthy controls (HC). The data were randomly split into training set and test set in a ratio of 80:20. Three supervised learning algorithms were applied to the training set for models fitting. The best performance models were evaluated with the test data set.

RESULTS

Differential plasma proteomics and metabolic pathways analyses revealed that the majority of DEPs in NSCLC were enriched in the pathways of complement and coagulation cascades, cholesterol and bile acids metabolism. Moreover, 10 DEPs, 14 amino acids, 15 bile acids, as well as 6 classic tumor biomarkers in blood were quantified using clinically validated assays. Finally, we obtained a high-performance screening model using logistic regression algorithm with AUC of 0.96, sensitivity of 92%, and specificity of 89%, and a diagnostic model with AUC of 0.871, sensitivity of 86%, and specificity of 78%. In the test set, the screening model achieved accuracy of 90%, sensitivity of 91%, and specificity of 90%, and the diagnostic model achieved accuracy of 82%, sensitivity of 77%, and specificity of 86%.

CONCLUSIONS

Integrated analysis of DEPs, amino acid, and bile acid features based on plasma proteomics-guided metabolite profiling, together with classical tumor biomarkers, provided a much more accurate detection model for screening and differential diagnosis of NSCLC. In addition, this new mathematical modeling based on plasma proteomics-guided metabolite profiling will be used for evaluation of therapeutic efficacy and long-term recurrence prediction of NSCLC.

The value of artificial intelligence in the diagnosis of lung cancer: A systematic review and meta-analysis

Lung cancer is a common malignant tumor disease with high clinical disability and death rates. Currently, lung cancer diagnosis mainly relies on manual pathology section analysis, but the low efficiency and subjective nature of manual film reading can lead to certain misdiagnoses and omissions. With the continuous development of science and technology, artificial intelligence (AI) has been gradually applied to imaging diagnosis. Although there are reports on AI-assisted lung cancer diagnosis, there are still problems such as small sample size and untimely data updates. Therefore, in this study, a large amount of recent data was included, and meta-analysis was used to evaluate the value of AI for lung cancer diagnosis. With the help of STATA16.0, the value of AI-assisted lung cancer diagnosis was assessed by specificity, sensitivity, negative likelihood ratio, positive likelihood ratio, diagnostic ratio, and plotting the working characteristic curves of subjects. Meta-regression and subgroup analysis were used to investigate the value of AI-assisted lung cancer diagnosis. The results of the meta-analysis showed that the combined sensitivity of the AI-aided diagnosis system for lung cancer diagnosis was 0.87 [95% CI (0.82, 0.90)], specificity was 0.87 [95% CI (0.82, 0.91)] (CI stands for confidence interval.), the missed diagnosis rate was 13%, the misdiagnosis rate was 13%, the positive likelihood ratio was 6.5 [95% CI (4.6, 9.3)], the negative likelihood ratio was 0.15 [95% CI (0.11, 0.21)], a diagnostic ratio of 43 [95% CI (24, 76)] and a sum of area under the combined subject operating characteristic (SROC) curve of 0.93 [95% CI (0.91, 0.95)]. Based on the results, the AI-assisted diagnostic system for CT (Computerized Tomography), imaging has considerable diagnostic accuracy for lung cancer diagnosis, which is of significant value for lung cancer diagnosis and has greater feasibility of realizing the extension application in the field of clinical diagnosis.

The expression and significance of efferocytosis and immune checkpoint related molecules in pancancer samples and the correlation of their expression with anticancer drug sensitivity

Background: The efferocytosis-related molecules have been considered to be correlated with the resistance to cancer chemotherapy. The aim of this study was to investigate the expression and significance of efferocytosis-related molecules in cancers and the correlation of their expression with anticancer drug sensitivity, and provide new potential targets and treatment options for cancers.

Methods: We investigated the differential expression of 15 efferocytosis-related molecules (Axl, Tyro3, MerTK, CX3CL1, Tim-4, BAI1, Stab2, Gas6, IDO1, Rac1, MFGE8, ICAM-1, CD47, CD31, and PD-L1) and other 12 common immune checkpoint-related molecules in tumor and normal tissues, the correlation between their expression and various clinicopathological features in 16 types of cancers using publicly available pancancer datasets in The Cancer Genome Atlas. We also analyzed the correlation of the expression of efferocytosis and immune checkpoint related molecules with 126 types of anticancer drugs sensitivity using drug-RNA-seq data.

Results: There is a panel of circulating molecules among the 27 molecules. Based on the results of differential expression and correlation with various clinicopathological features of efferocytosis-related molecules in cancers, we identified new potential therapeutic targets for anticancer therapy, such as Axl for kidney renal clear cell carcinoma, Tyro3 for liver hepatocellular carcinoma, and IDO1 for renal papillary cell carcinoma. Except for BAI1, CD31, and MerTK, the enhanced expressions of Axl, Tyro3, Gas6, MFGE8, Stab2, Tim-4, CX3CL1, IDO1, Rac1, and PD-L1 were associated with decreased sensitivity of the cancer cells to many anti-cancer drugs; however, for other common immune checkpoint-related molecules, only enhanced expressions of PD-1, CD28, CTLA4, and HVEM were associated with decreased sensitivity of the cancer cells to a few drugs.

Conclusion: The efferocytosis-related molecules were significantly associated with clinical outcomes in many types of cancers and played important roles in resistance to chemotherapy. Combination therapy targeting efferocytosis-related molecules and other immune checkpoint-related molecules is necessary to reduce resistance to chemotherapy.

Dried blood sample analysis by antibody array across the total testing process

Dried blood samples (DBSs) have many advantages; yet, impediments have limited the clinical utilization of DBSs. We developed a novel volumetric sampling device that collects a precise volume of blood, which overcomes the heterogeneity and hematocrit issues commonly encountered in a traditional DBS card collection as well as allowing for more efficient extraction and processing procedures and thus, more efficient quantitation, by using the entire sample. We also provided a thorough procedure validation using this volumetric DBS collection device with an established quantitative proteomics analysis method, and then analyzed 1000 proteins using this approach in DBSs concomitantly with serum for future consideration of utility in clinical applications. Our data provide a first step in the establishment of a DBS database for the broad application of this sample type for widespread use in clinical proteomic and other analyses applications.

Upconversion nanoparticle-assisted single-molecule assay for detecting circulating antigens of aggressive prostate cancer

Sensitive and quantitative detection of molecular biomarkers is crucial for the early diagnosis of diseases like metabolic syndrome and cancer. Here we present a single-molecule sandwich immunoassay by imaging the number of single nanoparticles to diagnose aggressive prostate cancer. Our assay employed the photo-stable upconversion nanoparticles (UCNPs) as labels to detect the four types of circulating antigens in blood circulation, including glypican-1 (GPC-1), leptin, osteopontin (OPN), and vascular endothelial growth factor (VEGF), as their serum concentrations indicate aggressive prostate cancer. Under a wide-field microscope, a single UCNP doped with thousands of lanthanide ions can emit sufficiently bright anti-Stokes' luminescence to become quantitatively detectable. By counting every single streptavidin-functionalized UCNP which specifically labeled on each sandwich immune complex across multiple fields of views, we achieved the Limit of Detection (LOD) of 0.0123 ng/ml, 0.2711 ng/ml, 0.1238 ng/ml, and 0.0158 ng/ml for GPC-1, leptin, OPN and VEGF, respectively. The serum circulating level of GPC-1, leptin, OPN, and VEGF in a mixture of 10 healthy normal human serum was 25.17 ng/ml, 18.04 ng/ml, 11.34 ng/ml, and 1.55 ng/ml, which was within the assay dynamic detection range for each analyte. Moreover, a 20% increase of GPC-1 and OPN was observed by spiking the normal human serum with recombinant antigens to confirm the accuracy of the assay. We observed no cross-reactivity among the four biomarker analytes, which eliminates the false positives and enhances the detection accuracy. The developed single upconversion nanoparticle-assisted single-molecule assay suggests its potential in clinical usage for prostate cancer detection by monitoring tiny concentration differences in a panel of serum biomarkers.

Decreased Thrombospondin-1 and Bone Morphogenetic Protein-4 Serum Levels as Potential Indices of Advanced Stage Lung Cancer

Introduction: Lung cancer belongs to the most common carcinoma worldwide and is the leading cause of cancer-related death. Bone morphogenetic protein-4 (BMP-4) is extracellular signaling molecule involved in many important processes, including cell proliferation and mobility, apoptosis and angiogenesis. Thrombospondin-1 (TSP-1) belongs to the extracellular matrix proteins. It participates in the cell-to-cell and cell-to-matrix interactions and thus plays important role in tumor microenvironment for cancer development and metastasis formation. Aim: To investigate serum levels of TSP-1 and BMP-4 together with BMP-4 polymorphism in lung cancer patients. Material and Methods: A total of 111 patients (76 men) with newly diagnosed lung cancer, including 102 patients with non-small cell lung cancer and 9 patients with small-cell lung cancer. Advanced stage of lung cancer was diagnosed in 99 (89%) of patients: stage IV—in 48, stage IIIB—in 33, stage IIIA—in 18 patients; there were six patients with stage II and six patients with stage I. The control group consisted of 61 healthy persons. In all the subjects, serum levels of BMP-4 and TSP-1 were measured by ELISA. With a Real-Time PCR system genotyping of BMP-4 was performed. Results: BMP-4 and TSP-1 serum levels were significantly lower in the patients with lung cancer than in the controls (TSP-1:10,109.2 ± 9581 ng/mL vs. 11,415.09 ± 9781 ng/mL, p < 0.05; BMP-4: 138.35 ± 62.59 pg/mL vs. 226.68 ± 135.86 pg/mL p < 0.001). In lung cancer patients TSP-1 levels were lower in advanced stages (9282.07 ± 4900.78 ng/mL in the stages III-IV vs. 16,933.60 ± 6299.02 ng/mL in the stages I-II, p < 0.05) and in the patients with than without lymph nodes involvement (10,000.13 ± 9021.41 ng/mL vs. 18,497.75 ± 12,548.25 ng/mL, p = 0.01). There was no correlation between TSP-1 and BMP-4 serum levels. BMP-4 gene polymorphism did not influence the results of the study. Conclusion: Decreased levels of TSP-1 and BMP-4 may serve as potential indices of lung cancer, with additional importance of low TSP-1 level as a marker of advanced stage of the disease.

A sensitive fluorescent probe for β-galactosidase activity detection and application in ovarian tumor imaging

The development of non-invasive and sensitive optical probes for in vivo bioimaging of cancer-related enzymes is desirable for early diagnosis and effective cancer therapy. β-galactosidase (β-gal) is regarded as a key ovarian cancer biomarker, owing to its overexpression in primary ovarian cancer. Herein, we designed a sensitive near-infrared (NIR) probe (DCMCA-βgal) for the detection and real-time imaging of β-gal activity in ovarian tumors, thereby achieving the visualization of ovarian tumors by β-gal activity detection. DCMCA-β-gal could be triggered by β-gal, resulting in the release of a NIR chromophore, DCM-NH₂; the linear range of fluorescent response to β-gal concentration was 0-1.2 U with a low detection limit of 1.26 × 10^-3 U mL^-1. We used DCMCA-β-gal to detect and visualize β-gal activity in SKOV3 human ovarian cancer cells, as well as for real-time imaging of β-gal activity in ovarian cancer mouse models. DCMCA-β-gal possessed high sensitivity, "turn-on" NIR emission, a large spectral shift, and high photostability in a dynamic living system and thus could serve as a highly sensitive sensor for real-time tracking of β-gal activity in vivo and ovarian tumor imaging.

Ultrasensitive electrochemical detection of neuron-specific enolase based on spiny core-shell Au/CuxO@CeO2 nanocubes

As a specific biomarker, neuron-specific enolase (NSE) is an essential clinical indicator for diagnosing small cell lung cancer. In this paper, a sandwich-type electrochemical immunosensor was designed for the quantitative detection of NSE. AuPt nanoblock spherical nanoarchitectonics (AuPt NSNs), a bimetallic nanoparticle with a rugged morphology, were utilized as the substrate, which could enhance the electronic conduction and increase the immobilization capacity of the primary antibody (Ab₁). Moreover, through a simple hydrothermal method, Au/Cu_xO@CeO₂ was prepared as a spiny core-shell nanocube with cerium dioxide (CeO₂) and gold nanoparticles (Au NPs) loading. The combination of Cu₂O, CuO, and CeO₂ showed favorable catalytic activity toward hydrogen peroxide (H₂O₂). Furthermore, the deposition of Au NPs on the spiny surface structure enhanced the specific surface area and biocompatibility, thereby rendering it more effective for loading the second antibody (Ab₂). As the label material, the Au/Cu_xO@CeO₂ achieved signal amplification and sensitive detection with the immunosensor. Under optimal conditions, the designed immunosensor possessed a broad linear range of 50 fg mL^-1 to 100 ng mL^-1 and a limit of detection of 31.3 fg mL^-1, along with satisfactory performance in sensitivity, selectivity, and stability.

Downregulation of histone-lysine N-methyltransferase EZH2 inhibits cell viability and enhances chemosensitivity in lung cancer cells

Histone-lysine N-methyltransferase EZH2 (EZH2) is the principle component of the polycomb repressive complex 2 (PRC2)/embryonic ectoderm development protein-EZH2 complex, which promotes tumorigenesis by repressing transcription of tumor suppressor genes. EZH2 is considered a key marker in several types of cancer, such as colorectal and prostate cancer. However, the molecular mechanisms and clinical value of EZH2 in lung cancer have not yet been fully investigated. The aim of the present study was to investigate the functions of EZH2 in lung cancer progression and to determine whether treatment with an EZH2 inhibitor enhanced the chemosensitivity of lung cancer cells to cisplatin (CDDP). At the logarithmic growth phase, A549 cells were treated with a small interfering (si)RNA-EZH2, and cell viability was detected using an MTT assay. The degree of apoptosis and cell cycle were detected using flow cytometry. Cell migration and invasion were detected via wound healing and Transwell Matrigel assays. According to information from the Gene Expression Omnibus database, the results of the present study demonstrated that EZH2 was upregulated in lung cancer. Furthermore, overexpression of EZH2 was associated with poor patient prognosis, while EZH2 knockdown inhibited cell viability and migration, and enhanced apoptosis and chemosensitivity in a lung cancer cell line. EZH2 knockdown and treatment of A549 cells using EZH2 inhibitor elevated the inhibitory effects of CDDP on cell viability and apoptosis. Western blot and reverse transcription-quantitative PCR analyses were performed to assess the expression levels of relative protein and mRNA, respectively, in A549 cells treated with siRNA-EZH2 or with CDDP. Overall, the results of the present study demonstrated that high EZH2 expression was associated with poor prognosis, accompanied with a potential impairment of migration and viability in lung cancer cells. These findings suggest that EZH2 may act as a candidate molecular target for gene therapy, and treatment with EZH2 inhibitor may be used to increase chemosensitivity to CDDP agents in lung cancer.

Detection of miR-155-5p and imaging lung cancer for early diagnosis: in vitro and in vivo study

Purpose

Currently, the routine screening program has insufficient capacity for the early diagnosis of lung cancer. Therefore, a type of chitosan-molecular beacon (CS-MB) probe was developed to recognize the miR-155-5p and image the lung cancer cells for the early diagnosis.

Methods

Based on the molecular beacon (MB) technology and nanotechnology, the CS-MB probe was synthesized self-assembly. There are four types of cells—three kinds of animal models and one type of histopathological sections of human lung cancer were utilized as models, including A549, SPC-A1, H446 lung cancer cells, tumor-initiating cells (TICs), subcutaneous and lung xenografts mice, and lox-stop-lox(LSL) K-ras G12D transgenic mice. The transgenic mice dynamically displayed the process from normal lung tissues to atypical hyperplasia, adenoma, carcinoma in situ, and adenocarcinoma. The different miR-155-5p expression levels in these cells and models were measured by quantitative real-time polymerase chain reaction (qRT-PCR). The CS-MB probe was used to recognize the miR-155-5p and image the lung cancer cells by confocal microscopy in vitro and by living imaging system in vivo.

Results

The CS-MB probe could be used to recognize the miR-155-5p and image the lung cancer cells significantly in these cells and models. The fluorescence intensity trends detected by the CS-MB probe were similar to the expression levels trends of miR-155 tested by qRT-PCR. Moreover, the fluorescence intensity showed an increasing trend with the tumor progression in the transgenic mice model, and the occurrence and development of lung cancer were dynamically monitored by the differen fluorescence intensity. In addition, the miR-155-5p in human lung cancer tissues could be detected by the miR-155-5p MB.

Conclusion

Both in vivo and in vitro experiments demonstrated that the CS-MB probe could be utilized to recognize the miR-155-5p and image the lung cancer cells. It provided a novel experimental and theoretical basis for the early diagnosis of the disease. Also, the histopathological sections of human lung cancer research laid the foundation for subsequent preclinical studies. In addition, different MBs could be designed to detect other miRNAs for the early diagnosis of other tumors.

The Matrix Revolution: Matricellular Proteins and Restructuring of the Cancer Microenvironment

The extracellular matrix (ECM) surrounding cells is indispensable for regulating their behavior. The dynamics of ECM signaling are tightly controlled throughout growth and development. During tissue remodeling, matricellular proteins (MCP) are secreted into the ECM. These factors do not serve classical structural roles, but rather regulate matrix proteins and cell-matrix interactions to influence normal cellular functions. In the tumor microenvironment, it is becoming increasingly clear that aberrantly expressed MCPs can support multiple hallmarks of carcinogenesis by interacting with various cellular components that are coupled to an array of downstream signals. Moreover, MCPs also reorganize the biomechanical properties of the ECM to accommodate metastasis and tumor colonization. This realization is stimulating new research on MCPs as reliable and accessible biomarkers in cancer, as well as effective and selective therapeutic targets.