Identifying key inflammatory genes in psoriasis via weighted gene co-expression network analysis: Potential targets for therapy.

Psoriasis is a globally prevalent chronic inflammatory skin disease. This study aimed to scrutinize the hub genes related to inflammation and potential molecular mechanisms in psoriasis. Utilizing mRNA expression profiles from public datasets GSE13355, GSE78097, and GSE14905, we set up a comprehensive analysis. Initially, we selected differentially expressed genes (DEGs) from psoriasis and control samples in GSE13355, followed by calculating inflammatory indices using genomic set variation analysis (GSVA). Weighted gene co-expression network analysis (WGCNA) was then applied to link significant modules with the inflammatory index. This process helped us identify differentially expressed inflammation-related genes (DE-IRGs). A protein-protein interaction (PPI) network was established, with the molecular complex detection (MCODE) plug-in pinpointing six chemokine genes (CCR7, CCL2, CCL19, CXCL8, CXCL1, and CXCL2) as central hub genes. These genes demonstrated pronounced immunohistochemical staining in psoriatic tissues compared to normal skin. Notably, the CCR7 gene exhibited the highest potential for m6A modification sites. Furthermore, we constructed transcription factor-microRNA-mRNA networks, identifying 139 microRNAs and 52 transcription factors associated with the hub genes. For the LASSO logistic regression model, the area under the curve (AUC) in the training set was 1, and in the two validation cohorts GSE78097 and GSE14905 were 1 and 0.872, respectively. In conclusion, our study highlights six chemokine genes (CCR7, CCL2, CCL19, CXCL8, CXCL1, and CXCL2) as potential biomarkers in psoriasis, providing insights into the immune and inflammatory responses as pivotal instances in disease pathogenesis. These findings pave the way for exploring new therapeutic targets, particularly focusing on chemokine-associated pathways in psoriasis treatment.

An ultrasensitive method for detecting mutations from short and rare cell-free DNA.

Circulating tumor DNA (ctDNA) was short and rare, making the detection performance of the current targeted sequencing methods unsatisfying. We developed the One-PrimER Amplification (OPERA) system and examined its performance in detecting mutations of low variant allelic frequency (VAF) in various samples with short-sized DNA fragments. In cell line-derived samples containing sonication-sheared DNA fragments with 50-150 bp, OPERA was capable of detecting mutations as low as 0.0025% VAF, while CAPP-Seq only detected mutations of >0.03% VAF. Both single nucleotide variant and insertion/deletion can be detected by OPERA. In synthetic fragments as short as 80 bp with low VAF (0.03%-0.1%), the detection sensitivity of OPERA was significantly higher compared to that of droplet digital polymerase chain reaction. The error rate was 5.9×10-5 errors per base after de-duplication in plasma samples collected from healthy volunteers. By suppressing "single-strand errors", the error rate can be further lowered by >5 folds in EGFR T790M hotspot. In plasma samples collected from lung cancer patients, OPERA detected mutations in 57.1% stage I patients with 100% specificity and achieved a sensitivity of 30.0% in patients with tumor volume of less than 1 cm3. OPERA can effectively detect mutations in rare and highly-fragmented DNA.

A novel microRNA-182/Interleukin-8 regulatory axis controls osteolytic bone metastasis of lung cancer.

Bone metastasis is one of the main complications of lung cancer and most important factors that lead to poor life quality and low survival rate in lung cancer patients. However, the regulatory mechanisms underlying lung cancer bone metastasis are still poor understood. Here, we report that microRNA-182 (miR-182) plays a critical role in regulating osteoclastic metastasis of lung cancer cells. We found that miR-182 was significantly upregulated in both bone-metastatic human non-small cell lung cancer (NSCLC) cell line and tumor specimens. We further demonstrated that miR-182 markedly enhanced the ability of NSCLC cells for osteolytic bone metastasis in nude mice. Mechanistically, miR-182 promotes NSCLC cells to secrete Interleukin-8 (IL-8) and in turn facilitates osteoclastogenesis via activating STAT3 signaling in osteoclast progenitor cells. Importantly, systemically delivered IL-8 neutralizing antibody inhibits NSCLC bone metastasis in nude mice. Collectively, our findings identify the miR-182/IL-8/STAT3 axis as a key regulatory pathway in controlling lung cancer cell-induced osteolytic bone metastasis and suggest a promising therapeutic strategy that targets this regulatory axis to interrupt lung cancer bone metastasis.

Stable LiF-Rich Electrode-Electrolyte Interface toward High-Voltage and High-Energy-Density Lithium Metal Solid Batteries.

Lithium-rich layered oxide (LRLO) materials have attracted significant attention due to their high specific capacity, low cost, and environmental friendliness. However, owing to its unique capacity activation mechanism, the release of lattice oxygen during the first charge process leads to a series of problems, such as severe voltage decay, poor cycle stability, and poor rate performance. Herein, a fluorinated quasi-solid-state electrolyte (QSSE) via a simple thermal polymerization method toward lithium metal batteries with LRLO materials is reported. The well-designed QSSE exhibits an ionic conductivity of 6.4 × 10-4 S cm-1 at 30 °C and a wide electrochemical stable window up to 5.6 V. Most importantly, XPS spectra demonstrate the generation of a LiF-rich electrode-electrolyte interface (EEI), where the in situ generated LiF provides strong protection against the structural degradation of LRLO materials and directs the uniform plating/stripping behaviors of lithium-ions to inhibit the formation of lithium dendrites. As a result, LRLO/QSSE/Li batteries exhibit excellent rate performance and demonstrate a large initial capacity for 209.7 mA h g-1 with a capacity retention of 80.8% after 200 cycles at 0.5C. This work provides a new insight for the LiF-rich EEI design of safe, high-performance quasi-solid-state lithium metal batteries.

Regulation of probe density on upconversion nanoparticles enabling high-performance lateral flow assays.

Upconversion nanoparticles (UCNPs)-based fluorescence probes have shown great potential in point-of-care testing (POCT) applications, due to UCNPs' features of high photostability and background-free fluorescence. Ceaseless improvements of UCNPs-probes have been carried out to increase detection sensitivity and to broaden detection range of UCNPs-based POCT. In this paper, we optimized UCNPs-probes by regulating probe density. The optimization was verified by a traditional lateral flow assay (LFA) platform for C-reactive protein (CRP) detection. Further, the optimized UCNPs-LFA integrating with a home-made benchtop fluorescence analyzer holds the capability to achieve high-performance POCT. Finally, nearly a 20 times sensitivity enhancement with a limit of detection of 0.046 ng/mL and a broad detection range of 0.2-300 ng/mL for CRP detection was obtained. Moreover, the optimized UCNPs-LFA was applied to detecting CRP in clinical serum samples and the detection results were consistent with the clinical test, validating its clinical practicability. The proposed optimization method is also expected to optimize other nanoparticles-based bio-probes for wider POCT application.

Comparative analysis of QS3D versus droplet digital PCR for quantitative measures of EGFR T790M mutation from identical plasma.

Objectives: The capacity of QuantStudio™ 3D (QS3D) and droplet digital PCR (dPCR) for the detection of plasma Epidermal Growth Factor Receptor (EGFR) mutations have been widely reported. Few comparative studies on the quantitative test of the identical DNA material, however, are carried out. Here we compared the performance of the two methods in detecting EGFR T790M mutation in cell-free DNA (cfDNA) from the same lung cancer patients. Methods: We recruited 72 non-small cell lung cancer (NSCLC) patients who initially respond to tyrosine kinase inhibitor treatment but subsequently developed resistance. Two tubes of 10mL anticoagulant blood were collected and cfDNA was isolated from plasma. Identical cfDNA samples were analyzed for T790M mutation using QS3D and droplet dPCR in parallel. Results: T790M mutation was detected in 15 and 21 cfDNA samples by QS3D and droplet digital PCR, respectively. The 6 discordant samples showed low mutation abundance (∼0.1%) and the discrepancy is caused by the stricter threshold settings for QS3D dPCR. The overall agreement between the two methods was 91.7% (66/72). The median allele frequencies for QS3D dPCR and droplet dPCR to detect T790M mutation was 2.01% and 2.62%, respectively. There was no significance in mutation abundance detected by both methods. Both methods are highly correlated with allele frequencies and copy numbers in T790M wild type and mutant, with R2 of 0.98, 0.92 and 0.95, respectively. Conclusion: Our study demonstrated that QS3D dPCR are highly consistent with droplet PCR for quantitative determination of EGFR T790M mutation in plasma cfDNA.

Integrative Serum Metabolic Fingerprints Based Multi-Modal Platforms for Lung Adenocarcinoma Early Detection and Pulmonary Nodule Classification.

Identification of novel non-invasive biomarkers is critical for the early diagnosis of lung adenocarcinoma (LUAD), especially for the accurate classification of pulmonary nodule. Here, a multiplexed assay is developed on an optimized nanoparticle-based laser desorption/ionization mass spectrometry platform for the sensitive and selective detection of serum metabolic fingerprints (SMFs). Integrative SMFs based multi-modal platforms are constructed for the early detection of LUAD and the classification of pulmonary nodule. The dual modal model, metabolic fingerprints with protein tumor marker neural network (MP-NN), integrating SMFs with protein tumor marker carcinoembryonic antigen (CEA) via deep learning, shows superior performance compared with the single modal model Met-NN (p < 0.001). Based on MP-NN, the tri modal model MPI-RF integrating SMFs, tumor marker CEA, and image features via random forest demonstrates significantly higher performance than the clinical models (Mayo Clinic and Veterans Affairs) and the image artificial intelligence in pulmonary nodule classification (p < 0.001). The developed platforms would be promising tools for LUAD screening and pulmonary nodule management, paving the conceptual and practical foundation for the clinical application of omics tools.

Integrated microfluidic single-cell immunoblotting chip enables high-throughput isolation, enrichment and direct protein analysis of circulating tumor cells.

Effective capture and analysis of a single circulating tumor cell (CTC) is instrumental for early diagnosis and personalized therapy of tumors. However, due to their extremely low abundance and susceptibility to interference from other cells, high-throughput isolation, enrichment, and single-cell-level functional protein analysis of CTCs within one integrated system remains a major challenge. Herein, we present an integrated multifunctional microfluidic system for highly efficient and label-free CTC isolation, CTC enrichment, and single-cell immunoblotting (ieSCI). The ieSCI-chip is a multilayer microfluidic system that combines an inertia force-based cell sorter with a membrane filter for label-free CTC separation and enrichment and a thin layer of a photoactive polyacrylamide gel with microwell arrays at the bottom of the chamber for single-cell immunoblotting. The ieSCI-chip successfully identified a subgroup of apoptosis-negative (Bax-negative) cells, which traditional bulk analysis did not detect, from cisplatin-treated cells. Furthermore, we demonstrated the clinical application of the ieSCI-chip with blood samples from breast cancer patients for personalized CTC epithelial-to-mesenchymal transition (EMT) analysis. The expression level of a tumor cell marker (EpCAM) can be directly determined in isolated CTCs at the single-cell level, and the therapeutic response to anticancer drugs can be simultaneously monitored. Therefore, the ieSCI-chip provides a promising clinical translational tool for clinical drug response monitoring and personalized regimen development.

A large-scale, multicentered trial evaluating the sensitivity and specificity of digital PCR versus ARMS-PCR for detecting ctDNA-based EGFR p.T790M in non-small-cell lung cancer patients.

BACKGROUND: Developing liquid biopsy technology with higher sensitivity and specificity especially for low-frequency mutations remains crucial. This study demonstrated superior performance of the newly developed digital PCR (dPCR) kit for ctDNA-based EGFR p.T790M detection in metastatic non-small-cell lung cancer (NSCLC) against ARMS-PCR. METHODS: This large-scale, multi-centered diagnostic study recruited 1,045 patients including 1,029 patients diagnosed with advanced NSCLC and 16 patients with specific samples between April 1st 2018 and November 30th 2019. EGFR p.T790M in plasma samples from mNSCLC patients were tested using dPCR with ADx-ARMS PCR and Cobas® EGFR Mutation Test V2 as comparator assays to confirm cut-off value for dPCR and evaluate its performance against ARMS-PCR-based assays. Efficacy was evaluated for patients with EGFR p.T790M detected by dPCR or ARMS-PCR, who underwent Osimertinib treatment. RESULTS: The sensitivity, specificity, and concordance of dPCR against ADx-ARMS PCR was 98.15%, 88.66% and 90.16%, respectively for 1,026 plasma samples. Additional 9.26% patients were detected positive by dPCR. The majority of those samples had a mutation allele frequency between 0.1% and 1%. In 45 paired tissue and plasma samples, the sensitivity improved from 30.77% to 53.85% by dPCR with the specificity over 90%. The response of Osimertinib in 74 EGFR p.T790M-positive patients detected by dPCR, including 26 determined as negative by ARMS-PCR, were evaluated to have an ORR of 44.59% and a DCR of 90.54%. CONCLUSIONS: dPCR is a sensitive and accurate tool for ctDNA-based EGFR p.T790M detection due to its significantly improved sensitivity without compromising specificity, and dPCR is equivalent to ARMS-PCR as a companion diagnostic tool while benefiting more patients under Osimertinib treatment. TRIAL REGISTRATION: Chinese Clinical Trial Registry identifier: ChiCTR2100043147.

Non-small cell lung cancer cell-derived exosomal miR-17-5p promotes osteoclast differentiation by targeting PTEN.

Aberrant activity of bone resorbing osteoclasts plays a key role in the development of osteoporosis and cancer bone metastasis. The identification of novel and specific targets will be helpful for the development of new therapeutic strategies for bone metastasis in lung cancer. Herein, we examined microRNAs in tumor cell-derived exosomes to investigate the communication between the bone environment and tumor cells. TCGA database analysis showed that the level of miR-17-5p increased in non-small cell lung cancer tissues compared with non-tumor tissues. To investigate the function of exosomes in inducing osteoclastogenesis, osteoclast precursors were incubated with exosomes isolated from non-small cell lung cancer cell line, as well as receptor activator of NF-KB ligand and M-CSF to induce osteoclastogenesis. We found that exosomal miR-17-5p is upregulated in a non-small cell lung cancer cell line with bone metastasis compared with the original cell line. Overexpression of miR-17-5p enhanced the osteoclastogenesis of RAW264.7 cells. PTEN was identified as a direct target of miR-17-5p and showed negative effects on osteoclastogenesis. Importantly, treatment of LY294002 (an inhibitor of the PI3K/Akt pathway) attenuated miR-17-5p-mediated osteoclastogenesis effects. Taken together, our findings demonstrated that miR-17-5p promotes osteoclastogenesis through the PI3K/Akt pathway via targeting PTEN in lung cancer.

Performance comparison of commercial kits for isolating and detecting circulating tumor DNA.

Circulating tumor DNA (ctDNA), a fraction of cell-free DNA (cfDNA) in the circulatory system, is released from tumor cells and thus carries tumor-specific genetic signatures. Using blood-derived ctDNA to detect somatic mutations has shown great value in guiding cancer targeted therapy. Isolation and detection efficiencies are the key factors affecting the performance of ctDNA detection. To optimize and standardize our clinical practice, in this study, we analyzed the isolation efficiency of four commercial cfDNA purification kits: QIAamp circulating nucleic acid kit, AmoyDx® Circulating DNA kits, Microdiag® circulating DNA isolation kit, and MagMAX cell-free DNA isolation kit; and the detection efficiency of two mainstream domestic EGFR gene mutation detection kits: MicroDiag EGFR gene mutation detection kit and Fluorometric real-time PCR Detection Kit for the analysis of EGFR gene mutations. Reference materials and plasma samples collected from lung cancer patients and healthy volunteers were used for the analysis. Our results showed that QIAamp circulating nucleic acid kit and Microdiag® circulating DNA kit had the highest recovery rate (up to 21.25 ng/mL) for short DNA fragments of about 173 bp which is the peak length of ctDNA. For ctDNA detection, the MicroDiag® EGFR gene mutation detection kit showed the highest detection rate and sensitivity for detecting EGFR mutations at a mutant frequency of 0.5%. This work provides a reliable choice of commercial kits for the clinical application of ctDNA.

Simplified ARCHITECT microfluidic chip through a dual-flip strategy enables stable and versatile tumoroid formation combined with label-free quantitative proteomic analysis.

Recent years, microfluidic three-dimensional (3D) tumor culture technique has made great progress in tumor microenvironment simulation and drug screening. Meanwhile, as their functionality and complexity increase, it is more difficult for current chip models to selectively collect specific-layer cells from tumoroids for further analysis. Moreover, a simplified and robust method for tumoroid formation with highly consistent size and repeatable 3D morphology is relatively ncessary. Here, we report an ARCHITECT (ARtificial CHIp for Tumor Enables Confocal Topography observation) chip, through a dual-flip strategy to implement straightforward tumoroid establishment. This platform guarantees stable batch-to-batch tumoroids formation and allows high resolution confocal imaging. Moreover, an initial cell density as low as 65 cells per chamber is efficient to deliver a tumoroid. With this ARCHITECT chip, different-layer cells of interest could be collected from tumoroid for label-free quantitative (LFQ) proteomic analysis. For application demonstration, we mainly verified this platform for lung carcinoma (A549) tumoroid construction and proteomic analysis at out layer. Our data indicate that the out-layer cells of A549 tumoroid show extensively distinct proteomic expressions compared to two-dimensional cultured A549 cells. The up-regulated proteins are mainly related to tumorigenicity, proliferation and metastasis. And the differentially expressed proteins are mainly relevant to lipid metabolism pathway which is essential to tumor progression and proliferation. This platform provides a simplified yet robust technique to connect microfluidic tumoroid construction and LFQ proteomic analysis. The simplicity of this technique should open the way to numerous applications such as discovering the innovative targets for cancer treatment, and studying the mophological and proteomic heterogeneity of different-layer cells across the tumoroid.

Label-free Separation of Circulating Tumor Cells Using a Self-Amplified Inertial Focusing (SAIF) Microfluidic Chip.

Circulating tumor cells (CTCs) are rare cells existing in the bloodstream with a relatively low number, which facilitate as a predictor of cancer progress. However, it is difficult to obtain highly purified intact CTCs with desired viability due to the low percentage of CTCs among blood cells. In this work, we demonstrate a novel self-amplified inertial focused (SAIF) microfluidic chip that enables size-based, high-throughput, label-free separation of CTCs from a patient's blood. The SAIF chip introduced in this study demonstrated the feasibility of an extremely narrow zigzag channel (with 40 µm channel width) connected with two expansion regions to effectively separate different-sized cells with amplified separation distance. The chip performance was optimized with different-sized polystyrene (PS) particles and blood cells spiked with three different types of cancer cells. The separation efficiencies for blood cells and spiked cancer cells are higher than 80%. Recovery rates of cancer cells were tested by spiking 1500 lung cancer cells (A549), breast cancer cells (MCF-7), and cervical cancer cells (HeLa) separately to 3 mL 0.09% saline with 3 × 106 white blood cells (WBCs). The recovery rates for larger cells (MCF-7 and HeLa) were 79.1 and 85.4%, respectively. Viabilities of the cells harvested from outlets were all higher than 97% after culturing for 24, 48, and 72 h. The SAIF chip performance was further confirmed using the real clinical patient blood samples from four lung cancer patients. Theoretical force balance analysis in physics, computational simulations, and experimental observations indicate that the SAIF chip is simple but effective, and high-throughput separation CTCs can be readily achieved without complex structures.

Machine learning of serum metabolic patterns encodes early-stage lung adenocarcinoma.

Early cancer detection greatly increases the chances for successful treatment, but available diagnostics for some tumours, including lung adenocarcinoma (LA), are limited. An ideal early-stage diagnosis of LA for large-scale clinical use must address quick detection, low invasiveness, and high performance. Here, we conduct machine learning of serum metabolic patterns to detect early-stage LA. We extract direct metabolic patterns by the optimized ferric particle-assisted laser desorption/ionization mass spectrometry within 1 s using only 50 nL of serum. We define a metabolic range of 100-400 Da with 143 m/z features. We diagnose early-stage LA with sensitivity~70-90% and specificity~90-93% through the sparse regression machine learning of patterns. We identify a biomarker panel of seven metabolites and relevant pathways to distinguish early-stage LA from controls (p < 0.05). Our approach advances the design of metabolic analysis for early cancer detection and holds promise as an efficient test for low-cost rollout to clinics.

Diagnosis and prognosis of myocardial infarction on a plasmonic chip.

Cardiovascular diseases lead to 31.5% of deaths globally, and particularly myocardial infarction (MI) results in 7.4 million deaths per year. Diagnosis of MI and monitoring for prognostic use are critical for clinical management and biomedical research, which require advanced tools with accuracy and speed. Herein, we developed a plasmonic gold nano-island (pGold) chip assay for diagnosis and monitoring of MI. On-chip microarray analysis of serum biomarkers (e.g., cardiac troponin I) afforded up to 130-fold enhancement of near-infrared fluorescence for ultra-sensitive and quantitative detection within controlled periods, using 10 µL of serum only. The pGold chip assay achieved MI diagnostic sensitivity of 100% and specificity of 95.54%, superior to the standard chemiluminescence immunoassay in cardiovascular clinics. Further, we monitored biomarker concentrations regarding percutaneous coronary intervention for prognostic purpose. Our work demonstrated a designed approach using plasmonic materials for enhanced diagnosis and monitoring for prognostic use towards point-of-care testing.

High Expression of Long Noncoding RNA PCNA-AS1 Promotes Non-Small-Cell Lung Cancer Cell Proliferation and Oncogenic Activity via Upregulating CCND1.

Accumulating evidences showed that aberrantly expressed long noncoding RNAs (lncRNAs) have critical roles in many cancers. However, the expression and roles of a poorly studied lncRNA PCNA-AS1 in non-small-cell lung cancer (NSCLC) remain unknown. In this study, we investigated the expression, clinical significance, biological roles, and functional mechanism of PCNA-AS1 in NSCLC. Our results showed that PCNA-AS1 was upregulated in NSCLC tissues and cell lines, and correlated with TNM stages. Functional experiments showed that overexpression of PCNA-AS1 promoted NSCLC cell proliferation and cell cycle progression. Depletion of PCNA-AS1 inhibited NSCLC cell proliferation and cell cycle progression, and also inhibited NSCLC tumor growth in vivo. Mechanistically, we found that PCNA-AS1 upregulated CCND1 expression. The expression of PCNA-AS1 was positively correlated with that of CCND1 in NSCLC tissues. Moreover, depletion of CCND1 abrogated the oncogenic roles of PCNA-AS1 in NSCLC. In conclusion, highly expressed PCNA-AS1 promotes NSCLC cell proliferation and oncogenic activity via upregulating CCND1. Our results imply that PCNA-AS1 might serve as a therapeutic target for NSCLC.

Nanotechnology Strategies for the Analysis of Circulating Tumor DNA: A Review.

Circulating tumor DNA (ctDNA) describes the fragmented DNA released from tumor cells into the blood. The ctDNA may have the same genetic changes as the primary tumor. Currently, ctDNA has become a popular biomarker for diagnosis, treatment, real-time clinical response monitoring, and prognosis, for solid tumors. Detection of ctDNA is minimally invasive, and repeat sampling can easily be performed. However, due to its low quality and short DNA fragment length, ctDNA detection still faces challenges and requires highly sensitive analytical techniques. Recently, liquid biopsies for the analysis of circulating tumor cells (CTCs) and circulating tumor-derived exosomes have been studied, and nanotechnology techniques have rapidly developed. Compared to traditional analytical methods, these nanotechnology-based platforms have the advantages of sensitivity, multiplex detection, simplicity, miniaturization, and automation, which support their potential use in clinical practice. This review aims to discuss the recent nanotechnological strategies for ctDNA analysis and the design of reliable techniques for ctDNA detection and to identify the potential clinical applications.

Diagnosis and prognosis for exercise-induced muscle injuries: from conventional imaging to emerging point-of-care testing.

With the development of modern society, we have witnessed a significant increase of people who join in sport exercises, which also brings significantly increasing exercise-induced muscle injuries, resulting in reduction and even cessation of participation in sports and physical activities. Although severely injured muscles can hardly realize full functional restoration, skeletal muscles subjected to minor muscle injuries (e.g., tears, lacerations, and contusions) hold remarkable regeneration capacity to be healed without therapeutic interventions. However, delayed diagnosis or inappropriate prognosis will cause exacerbation of the injuries. Therefore, timely diagnosis and prognosis of muscle injuries is important to the recovery of injured muscles. Here, in this review, we discuss the definition and classification of exercise-induced muscle injuries, and then analyze their underlying mechanism. Subsequently, we provide detailed introductions to both conventional and emerging techniques for evaluation of exercise-induced muscle injuries with focus on emerging portable and wearable devices for point-of-care testing (POCT). Finally, we point out existing challenges and prospects in this field. We envision that an integrated system that combines physiological and biochemical analyses is anticipated to be realized in the future for assessing muscle injuries.

miR-93 activates ERK pathway to promote proliferation and migration of NSCLC cells via targeting EphA4 / 中国肿瘤生物治疗杂志

@#[Abstract] Objective: To investigate the effect of miR-93/EphA4 (Eph receptor A4) axis on the proliferation and migration of nonsmall cell lung cancer (NSCLC) H460 and H1299 cells via regulating extracellular regulated protein kinases (ERK) pathway. Methods: The expression levels of miR-93 in H460 and H1299 cells was detected by qPCR. miR-93 mimics and EphA4 overexpression plasmids were transfected into H460 cells and miR-93 inhibitor was transfected into H1299 cells respectively, after which MTT assay and Transwell assay were used to detect the effects of miR-93 on proliferation and migration of transfected cells. The targeted regulatory relationship betweenmiR-93andEphA4wasverifiedbyDual-luciferasereportergeneassay.Theexpression levels of PCNA(proliferating cell nuclear antigen), EphA4, ERK and p-ERK were detected by Westernblotting.The effects of simultaneous overexpression of miR-93 and EphA4 on proliferation and migration of H460 cells were detected by MTT assay and Transwell assay. Results: The expression of miR-93 in H1299 cells was higher than that in H460 cells (P<0.01). Overexpression of miR-93 promoted proliferation and migration of H460 cells (all P<0.01), and knockdown of miR-93 inhibited proliferation and migration of H1299 cells (all P<0.01). The Dualluciferase reporter gene assay confirmed that miR-93 could target EphA4. Overexpression of miR-93 down-regulated the mRNA and protein expression levels of EphA4(allP<0.05), and promoted proliferation and migration of H460 cells through targeted regulation of EphA4 and activation of ERK pathway (all P<0.01). Conclusion: miR-93 promotes the proliferation and migration of NSCLC cells, and its mechanism may be related to the targeted regulation of EphA4 and activation of the ERK pathway.

Histone-Related Genes Are Hypermethylated in Lung Cancer and Hypermethylated HIST1H4F Could Serve as a Pan-Cancer Biomarker.

Lung cancer is the leading cause of cancer-related deaths worldwide. Cytologic examination is the current "gold standard" for lung cancer diagnosis, however, this has low sensitivity. Here, we identified a typical methylation signature of histone genes in lung cancer by whole-genome DNA methylation analysis, which was validated by The Cancer Genome Atlas (TCGA) lung cancer cohort (n = 907) and was further confirmed in 265 bronchoalveolar lavage fluid samples with specificity and sensitivity of 96.7% and 87.0%, respectively. More importantly, HIST1H4F was universally hypermethylated in all 17 tumor types from TCGA datasets (n = 7,344), which was further validated in nine different types of cancer (n = 243). These results demonstrate that HIST1H4F can function as a universal-cancer-only methylation (UCOM) marker, which may aid in understanding general tumorigenesis and improve screening for early cancer diagnosis. SIGNIFICANCE: These findings identify a new biomarker for cancer detection and show that hypermethylation of histone-related genes seems to persist across cancers.