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microarray analysis of gene expression in lung tissues of indium-exposed rats: possible roles of S100 proteins in lung diseases

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ARCHIVES OF TOXICOLOGY 2025年第1期99卷 245-258页

作者： Hiraku, Yusuke Tanaka, Akiyo Yamamoto, Masato Nakatani, Minori Kobayashi, Mayu Kimura, Eiki Ahmed, Sharif Murata, Mariko Univ Fukui Sch Med Sci Dept Environm Hlth Eiheiji Fukui 9101193 Japan Mie Univ Grad Sch Med Dept Environm & Mol Med Tsu Mie Japan Kyushu Univ Ctr Plasma Nanointerface Engn Fukuoka Japan Suzuka Univ Med Sci Grad Sch Hlth Sci Suzuka Mie Japan

Indium compounds are used in manufacturing displays of mobile phones and televisions. These compounds cause interstitial pneumonia in workers and lung cancer in animals, but their precise mechanisms are unclear. In this study, we performed microarray analysis of gene expression in lung tissues of indium-exposed rats. Male Wistar rats (8-week-old) were exposed to indium oxide (In2O3, mean particle diameter 0.14 mu m) and indium-tin oxide (ITO, mean particle diameter 0.95 mu m) by intratracheal instillation (10 mg indium/kg body weight/instillation) twice a week and five times in total. These rats were sacrificed immediately, 3 weeks and 12 weeks after the last instillation. Hematoxylin and eosin and Masson's trichrome staining showed that indium compounds induced infiltration of neutrophils and macrophages into alveolar space, and fibrosis around bronchial epithelium and in alveolar wall. microarray analysis revealed that In2O3 and ITO significantly upregulated 233 and 676 genes at 12 weeks, respectively (> twofold, p < 0.05 by ANOVA + Tukey's test). In2O3 and ITO largely upregulated Lcn2 (lipocalin-2) (49.4- and 91.8-fold), S100a9 (30.2- and 46.5-fold) and S100a8 (11.5- and 22.0-fold), respectively. Metascape database predicted that these genes participate in immunomodulatory and inflammatory responses. Real-time PCR confirmed that these genes were upregulated by indium compounds throughout the experiments. In Western blotting, S100A9 expression was significantly increased by indium exposure, whereas LCN2 expression was only slightly increased. Fluorescent immunohistochemistry revealed that S100A9 and S100A8 were expressed in alveolar epithelial cells and neutrophils in indium-exposed rats. These results suggest that S100 proteins contribute to indium-induced lung diseases via neutrophil-mediated inflammatory responses.

关键词： Indium microarray S100 proteins Inflammation Lung disease

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MicroRNAs Associated with Keloids Identified by microarray Analysis and In Vitro Experiments

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MOLECULAR BIOTECHNOLOGY 2025年第1期67卷 356-367页

作者： Chen, Sichao Zhang, Wenchao Xia, Zenan Xie, Jiangmiao Li, Zhijin Liu, Zeming Yu, Nanze Wang, Xiaojun Chinese Acad Med Sci & Peking Union Med Coll Peking Union Med Coll Hosp Dept Plast & Reconstruct Surg Beijing Peoples R China Huazhong Univ Sci & Technol Tongji Hosp Tongji Med Coll Dept Plast & Cosmet Surg Wuhan Peoples R China Chinese Acad Med Sci & Peking Union Med Coll Dept Int Med Serv Beijing Peoples R China

MicroRNAs (miRNAs) play a crucial role in gene regulation and the development of keloid. This research aimed to identify and verify miRNAs associated with keloids by microarray analysis and in vitro experiments, shedding light on seeking for potential therapeutic molecular targets. In this study, the weighted gene co-expression network analysis was performed based on the GSE113620. The key miRNA module most relevant to the keloid was further screened to identify hub miRNAs, and then hub miRNAs was verified by the microarray analysis and qRT-PCR experiments. Additionally, targeted genes of hub miRNAs were predicted and verified. Gene ontology (GO) analysis and KEGG enrichment analysis were also conducted. Five miRNA modules were divided, and the blue module exhibited the highest correlation with keloids. Then, hsa-miR-127-3p, hsa-miR-214-3p, hsa-miR-155-5p, hsa-miR-409-5p, and hsa-miR-542-5p were identified as the hub miRNAs. Subsequently, the microarray analysis and qRT-PCR results demonstrated that the expression of five miRNAs were upregulated in keloid tissues. The GO analysis revealed that the target genes of these miRNAs were mainly enriched in biological processes including gene transcription, protein phosphorylation and the MAPK (mitogen-activated protein kinase) cascade, and the KEGG pathway enrichment analysis showed that the PI3K-AKT signaling pathway were significantly enriched. In conclusion, these five miRNAs (hsa-miR-127-3p, hsa-miR-155-5p, hsa-miR-214-3p, hsa-miR-409-5p, and hsa-miR-542-5p) play vital roles in the pathogenesis of keloid and might be potential therapeutic targets. These miRNAs might regulate genes enriched in gene transcription, protein phosphorylation, the MAPK cascade, and the PI3K-Akt signaling pathway.

关键词： Keloid WGCNA MicroRNA Epigenetics microarray

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Re-Analysis of Non-Small Cell Lung Cancer and Drug Resistance microarray Datasets with Machine Learning

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CYBERNETICS AND SYSTEMS 2025年第1期56卷 69-80页

作者： Erol, Cigdem Bawa, Tchare Adnaane Ozkan, Yalcin Istanbul Univ Dept Informat Istanbul Turkiye Istanbul Univ Fac Sci Dept Biol Div Bot Istanbul Turkiye Istanbul Univ Inst Sci Div Informat Istanbul Turkiye Istinye Univ Fac Econ Adm & Social Sci Dept Management Informat Syst Istanbul Turkiye Istanbul Univ Dept Informat TR-34134 Istanbul Turkiye

Non-small cell lung cancer is the most common type of lung cancer. Identification of genes associated with this disease may contribute to the treatment of the disease. Therefore, a lot of work is being done. In some of these studies, genetic data is obtained by microarray analysis and shared publicly in databases such as NCBI Gene Expression Omnibus. In today's big data era, machine learning algorithms are frequently used to access valuable information from data stacks. Within the scope of this study, all (6 pieces) microarray datasets related to NSCLC and drug resistance in the NCBI GEO database were analyzed by R Studio. With support vector machine, k nearest neighbor, naive Bayes, random forest, C5.0 decision tree, multilayer perceptron, and artificial neural network algorithms with principal component step, the datasets were analyzed separately and related genes were determined through the caret package, and the top 10 genes for each algorithm were given in the findings section in order of importance. In this resulting gene table, ELOVL7, HMGA2, SAT1, RRM1, IER3, SLC7A11, and U2AF1 genes are included in at least 2 different datasets. These identified genes are recommended to researchers working in a wet laboratory environment to be validated experimentally.

关键词： Machine learning microarray non-small cell lung cancer NSCLC reanalysis of dataset

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Analysis of microarray and single-cell RNA-seq identifies gene co-expression, cell-cell communication, and tumor environment associated with metabolite interconversion enzyme in prostate cancer

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DISCOVER ONCOLOGY 2025年第1期16卷 1-28页

作者： Karoii, Danial Hashemi Abroudi, Ali Shakeri Forghani, Nadia Bavandi, Sobhan Djamali, Melika Baghaei, Hamoon Shafaeitilaki, Sana Hasanzadeh, Ehsan Univ Tehran Coll Sci Sch Biol Dept Cell & Mol Biol Tehran Iran Islamic Azad Univ Fac Adv Sci & Technol Dept Cellular & Mol Biol Tehran Med Sci Tehran Iran Univ Verona Dept Biotechnol Verona Italy Islamic Azad Univ Dept Biol Qaemshahr Branch Qaemshahr Iran Univ Tehran Dept Biol Fac Sci Tehran Iran Univ Tehran Med Sci Childrens Med Ctr Gene Cell & Tissue Res Inst Pediat Urol & Regenerat Med Res Ctr 62 Dr Gharibs StKeshavarz Blvd Tehran *** Iran Islamic Azad Univ Dept Cellular & Mol Biol Sari Branch Sari Iran Islamic Azad Univ Hlth Reprod Res Ctr Sari Branch Sari Iran

BackgroundProstate cancer (PCa) is the second most common malignant neoplasm in males and is the fifth leading cause of cancer-related mortality. Due to the use of prostate-specific antigen (PSA) screening and improved biopsy techniques, persons identified with early-stage prostate cancer often have a positive prognosis after comprehensive treatment. Nonetheless, prostate cancer is a latent illness that may present as an asymptomatic tumor in individuals aged 20-30. The overall survival (OS) of men with advanced PCa is significantly diminished. Consequently, there is an immediate want for innovative, accurate biomarkers to detect early prostate *** research analyzed the interaction network of differentially expressed genes (DEGs) related to metabolite interconversion enzymes in PCa by gene expression microarray data, single-cell RNA sequencing, oncogenes, and tumor suppressor genes (TSGs) utilizing bioinformatics techniques. This kind of analysis has not been documented in prior *** then used a dataset acquired by the Cancer Genome Atlas (TCGA) to confirm our findings. Genes including CYP3A5, PDE8B, AOX1, BNIPL, FADS2, RRM2, ALDH3B2, and GSTM2 may be significant in the diagnosis and treatment of *** objective was to provide new perspectives on the molecular properties and pathways of DEGs in PCa and to uncover potential biomarkers that play a crucial role in the genesis and progression of PCa.

关键词： Prostate cancer Metabolite interconversion enzyme Cell-cell communication microarray

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Clinical significance of a new early diagnostic model for bladder cancer based on genome-wide microarray profiling of serum exosomal lncRNAs

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INTERNATIONAL UROLOGY AND NEPHROLOGY 2025年第6期57卷 1771-1783页

作者： Zhao, Liming Tian, Guang Wang, Xiaohua Li, Luning Gao, Yongli Gao, Yisheng Wang, Jinfeng Shandong Second Med Univ Linyi Peoples Hosp Dept Nucl Med 27 Jiefang Rd Linyi 276003 Shandong Peoples R China Shandong Second Med Univ Linyi Peoples Hosp Dept Gen Internal Med Linyi Shandong Peoples R China Shandong Second Med Univ Linyi Peoples Hosp Dept Gastroenterol Linyi Shandong Peoples R China Shandong Second Med Univ Linyi Peoples Hosp Dept Oncol Linyi Shandong Peoples R China Shandong Second Med Univ Linyi Peoples Hosp Dept Urol Linyi Shandong Peoples R China

Purpose The aim of our report was to recognize bladder cancer (BC)-specific serum exosome-derived long non-coding RNAs (lncRNAs) profile for early diagnosis of BC. Methods Potential BC-specific exosomal lncRNA indicators were discerned by genome-wide microarray profiling analysis of serum exosomes from 10 healthy participants and 10 early stage BC patients (Ta and T1), followed by multi-stage validation through quantitative real-time PCR (qRT-PCR) in BC cells, culture solution as well as 200 serum specimens and 50 tissue specimens from non-muscle-invasive bladder cancer (NMIBC) patients. The diagnostic panel was established using logistic regression and evaluated by receiver-operating characteristic (ROC) curve. Results In the training stage, a diagnostic panel was constructed based on three up-regulated exosomal lncRNAs (G023016, RP11-553N19.1, and LINC0087) in NMIBC patients compared with healthy controls, yielding an area under ROC curve (AUC) of 0.827. We verified tumor-derived origin of these three lncRNAs which existed steadily in serum because of being enclosed in exosomes. The three-lncRNA panel was demonstrated to perform well in terms of NMIBC diagnosis, revealing AUC values of 0.809 and 0.812, respectively, in the following expanded validation stage and double-blind stage which was demonstrated to be significantly superior to that of urine cytology in double-blind stage (AUC = 0.630) (P < 0.0001). Moreover, serum exosome-derived G023016 significantly associated with tumor grade and TNM stage (P = 0.006 and P < 0.001, respectively), and LINC0087 significantly associated with TNM stage (P = 0.023). Conclusion The three-exosomal lncRNA signature could function as qualified blood-based non-invasive indicator for early diagnosis of BC.

关键词： Serum exosome Long non-coding RNA microarray Logistic regression Non-muscle-invasive bladder cancer

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Identification of novel cytoskeleton protein involved in spermatogenic cells and sertoli cells of non-obstructive azoospermia based on microarray and bioinformatics analysis

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BMC MEDICAL GENOMICS 2025年第1期18卷 1-26页

作者： Karoii, Danial Hashemi Azizi, Hossein Darvari, Maryam Qorbanee, Ali Hawezy, Dawan Jamal Univ Tehran Coll Sci Sch Biol Dept Cell & Mol Biol Tehran Iran Amol Univ Special Modern Technol Fac Biotechnol Amol Iran Islamic Azad Univ Dept Cellular & Mol Biol Ghaemshahr Branch Ghaemshahr Iran Islamic Azad Univ Hlth Reprod Res Ctr Sari Branch Koya KOY45 Sari Iran Koya Univ Fac Gen Med Dept Surg KOY45 Koya Kurdistan Iraq

BackgroundDuring mammalian spermatogenesis, the cytoskeleton system plays a significant role in morphological changes. Male infertility such as non-obstructive azoospermia (NOA) might be explained by studies of the cytoskeletal system during *** cytoskeleton, scaffold, and actin-binding genes were analyzed by microarray and bioinformatics (771 spermatogenic cellsgenes and 774 Sertoli cell genes). To validate these findings, we cross-referenced our results with data from a single-cell genomics *** the microarray analyses of three human cases with different NOA spermatogenic cells, the expression of TBL3, MAGEA8, KRTAP3-2, KRT35, VCAN, MYO19, FBLN2, SH3RF1, ACTR3B, STRC, THBS4, and CTNND2 were upregulated, while expression of NTN1, ITGA1, GJB1, CAPZA1, SEPTIN8, and GOLGA6L6 were downregulated. There was an increase in KIRREL3, TTLL9, GJA1, ASB1, and RGPD5 expression in the Sertoli cells of three human cases with NOA, whereas expression of DES, EPB41L2, KCTD13, KLHL8, TRIOBP, ECM2, DVL3, ARMC10, KIF23, SNX4, KLHL12, PACSIN2, ANLN, WDR90, STMN1, CYTSA, and LTBP3 were downregulated. A combined analysis of Gene Ontology (GO) and STRING, were used to predict proteins' molecular interactions and then to recognize master pathways. Functional enrichment analysis showed that the biological process (BP) mitotic cytokinesis, cytoskeleton-dependent cytokinesis, and positive regulation of cell-substrate adhesion were significantly associated with differentially expressed genes (DEGs) in spermatogenic cells. Moleculare function (MF) of DEGs that were up/down regulated, it was found that tubulin bindings, gap junction channels, and tripeptide transmembrane transport were more significant in our analysis. An analysis of GO enrichment findings of Sertoli cells showed BP and MF to be common DEGs. Cell-cell junction assembly, cell-matrix adhesion, and regulation of SNARE complex assembly were significantly correlated with common DEGs for BP. In the

关键词： Non-obstructive azoospermia microarray Spermatogenic cells Sertoli cell Cytoskeleton protein

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New Machine Learning Method for Medical Image and microarray Data Analysis for Heart Disease Classification

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JOURNAL OF IMAGING INFORMATICS IN MEDICINE 2025年 1-24页

作者： Guo, Jinglan Liao, Jue Chen, Yuanlian Wen, Lisha Cheng, Song Southwest Med Univ Dept Med Lab Affiliated Hosp Lu Zhou 646000 Si Chuan Peoples R China Southwest Med Univ Sch Basic Med Sci Lu Zhou 646000 Si Chuan Peoples R China Jiangyang Dist Maternal & Child Hlth Hosp Family Planning Serv Ctr Lu Zhou 646000 Sichuan Peoples R China

microarray technology has become a vital tool in cardiovascular research, enabling the simultaneous analysis of thousands of gene expressions. This capability provides a robust foundation for heart disease classification and biomarker discovery. However, the high dimensionality, noise, and sparsity of microarray data present significant challenges for effective analysis. Gene selection, which aims to identify the most relevant subset of genes, is a crucial preprocessing step for improving classification accuracy, reducing computational complexity, and enhancing biological interpretability. Traditional gene selection methods often fall short in capturing complex, nonlinear interactions among genes, limiting their effectiveness in heart disease classification tasks. In this study, we propose a novel framework that leverages deep neural networks (DNNs) for optimizing gene selection and heart disease classification using microarray data. DNNs, known for their ability to model complex, nonlinear patterns, are integrated with feature selection techniques to address the challenges of high-dimensional data. The proposed method, DeepGeneNet (DGN), combines gene selection and DNN-based classification into a unified framework, ensuring robust performance and meaningful insights into the underlying biological mechanisms. Additionally, the framework incorporates hyperparameter optimization and innovative U-Net segmentation techniques to further enhance computational performance and classification accuracy. These optimizations enable DGN to deliver robust and scalable results, outperforming traditional methods in both predictive accuracy and interpretability. Experimental results demonstrate that the proposed approach significantly improves heart disease classification accuracy compared to other methods. By focusing on the interplay between gene selection and deep learning, this work advances the field of cardiovascular genomics, providing a scalable and interpretable framework f

关键词： microarray Gene selection Heart disease classification Neural networks

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An updated comparison of microarray and RNA-seq for concentration response transcriptomic study: case studies with two cannabinoids, cannabichromene and cannabinol

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BMC GENOMICS 2025年第1期26卷 1-20页

作者： Gao, Xiugong Yourick, Miranda R. Campasino, Kayla Zhao, Yang Sepehr, Estatira Vaught, Cory Sprando, Robert L. Yourick, Jeffrey J. US Food & Drug Adm FDA Div Toxicol Off Lab Operat & Appl Sci OLOAS Off Chem & Toxicol OCTHuman Foods Program HFP Laurel MD 20708 USA

BackgroundTranscriptomic benchmark concentration (BMC) modeling provides quantitative toxicogenomic information that is increasingly being used in regulatory risk assessment of data poor chemicals. Over the past decade, RNA sequencing (RNA-seq) is gradually replacing microarray as the major platform for transcriptomic applications due to its higher precision, wider dynamic range, and capability of detecting novel transcripts. However, it is unclear whether RNA-seq offers substantial advantages over microarray for concentration response transcriptomic *** provide an updated comparison between microarray and RNA-seq using two cannabinoids, cannabichromene (CBC) and cannabinol (CBN), as case studies. The two platforms revealed similar overall gene expression patterns with regard to concentration for both CBC and CBN. However, in spite of the many varieties of non-coding RNA transcripts and larger numbers of differentially expressed genes (DEGs) with wider dynamic ranges identified by RNA-seq, the two platforms displayed equivalent performance in identifying functions and pathways impacted by compound exposure through gene set enrichment analysis (GSEA). Furthermore, transcriptomic point of departure (tPoD) values derived by the two platforms through BMC modeling were on the same levels for both CBC and *** the relatively low cost, smaller data size, and better availability of software and public databases for data analysis and interpretation, microarray is still a viable method of choice for traditional transcriptomic applications such as mechanistic pathway identification and concentration response modeling.

关键词： microarray RNA-seq Toxicogenomics Concentration response BMC modeling In vitro Cannabinoid Cannabichromene Cannabinol

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Immuno-μSARS2 Chip: A Peptide-Based microarray to Assess COVID-19 Prognosis Based on Immunological Fingerprints

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ACS PHARMACOLOGY & TRANSLATIONAL SCIENCE 2025年第3期8卷 871-884页

作者： Guercetti, Julian Alorda, Marc Sappia, Luciano Galve, Roger Duran-Corbera, Macarena Pulido, Daniel Berardi, Ginevra Royo, Miriam Lacoma, Alicia Munoz, Jose Padilla, Eduardo Castaneda, Silvia Sendra, Elena Horcajada, Juan P. Gutierrez-Galvez, Agustin Marco, Santiago Salvador, J. -Pablo Marco, M. -Pilar IQAC CSIC Inst Quim Avanzada Cataluna Nanobiotechnol Diagnost Grp Barcelona 08034 Spain IQAC CSIC Inst Quim Avanzada Cataluna Multivalent Syst Nanomed (MS4N) Barcelona 08034 Spain Inst Salud Carlos III CIBER Bioingn Biomat & Nanomed CIBER BBN Madrid 28029 Spain Hosp Univ Germans Trias i Pujol Inst Germans Trias i Pujol Serv Microbiol Badalona 08916 Spain Inst Salud Carlos III CIBER Enfermedades Respiratorias CIBERES Madrid 28029 Spain Serv Microbiol Lab Referencia Catalunya Barcelona 08820 Spain Hosp Mar Barcelona Serv Enfermedades Infecciosas COVID MAR Grp Barcelona 08003 Spain Inst Salud Carlos III CIBER Enfermedades Infecciosas CIBERINFEC Madrid 28029 Spain Barcelona Inst Sci & Technol Inst Bioengn Catalonia IBEC Barcelona 08028 Spain Univ Barcelona Dept Elect & Biomed Engn Barcelona 08028 Spain

A multiplexed microarray chip (Immuno-mu SARS2) aiming at providing information on the prognosis of the COVID-19 has been developed. The diagnostic technology records information related to the profile of the immunological response of patients infected by the SARS-CoV-2 virus. The diagnostic technology delivers information on the avidity of the sera against 28 different peptide epitopes and 7 proteins printed on a 25 mm2 area of a glass slide. The peptide epitopes (12-15 mer) derived from structural proteins (Spike and Nucleocapsid) have been rationally designed, synthesized, and used to develop Immuno-mu SARS2 as a multiplexed and high-throughput fluorescent microarray platform. The analysis of 755 human serum samples (321 from PCR+ patients;288 from PCR- patients;115 from prepandemic individuals and classified as hospitalized, admitted to intensive-care unit (ICU), and exitus) from three independent cohorts has shown that the chips perform with a 98% specificity and 91% sensitivity identifying RT-PCR+ patients. Computational analysis utilized to correlate the immunological signatures of the samples analyzed indicate significant prediction rates against exitus conditions with 82% accuracy, ICU admissions with 80% accuracy, and 73% accuracy over hospitalization requirement compared to asymptomatic patients' fingerprints. The miniaturized microarray chip allows simultaneous determination of 96 samples (24 samples/slide) in 90 min and requires only 10 mu L of sera. The diagnostic approach presented for the first time here could have a great value in assisting clinicians in decision-making based on the information provided by the Immuno-mu SARS2 regarding progression of the disease and could be easily implemented in diagnostics of other infectious diseases.

关键词： microarray High-throughput Serological signature Peptide epitopes Multiplexation Machine learning Clinical diagnostic Severity prediction SARS-CoV-2

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Multiplex analysis of ovarian cancer patients using glycan microarray

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ANALYTICAL BIOCHEMISTRY 2025年 701卷 115806页

作者： Pokrovsky, Vadim S. Qoura, Louay Abo Tikhonov, Aleksei A. Rubina, Alla Yu Kushlinskii, Nikolai E. Minist Hlth Russian Federat NN Blokhin Natl Med Res Ctr Oncol Moscow 115478 Russia Peoples Friendship Univ Russia Res Inst Mol & Cellular Med RUDN Univ Moscow 117198 Russia Russian Acad Sci Engelhardt Inst Mol Biol Moscow 119991 Russia

Investigation of tumor-associated glycan antigens (TAGs) could be helpful for the development of sensitive cancer diagnostics and novel therapies. Glycan microarrays are effective methods for analyzing glycans and antiglycan antibodies, which are immobilized arrays of oligo- or poly-saccharides on different substrates, making them a promising class of oncological biomarkers. Blood serum samples from patients (n = 203) with ovarian cancer (OvaCan) and healthy volunteers were analyzed using a glycan microarray containing 63 immobilized glycans to determine changes in anti-glycan IgG and IgM antibody profiles in OvaCan. Levels of anti-glycan IgG and IgM antibodies in OvaCan statistically differed from levels in healthy donors: the most prominent statistically significant difference for anti-glycan IgG antibodies was found for 6-O-su-Lec (AUC = 0.657, Se = 48.0 %, and Sp = 73.3 %). The AUC values for certain glycans investigated in diagnosing OvaCan indicated a fingerprint consisting of IgM antibodies to specific glycans, and the most specific anti-glycan IgM antibodies were Ley (AUC = 0.625, Se = 98.0 % and Sp = 45.0 %). The potential of these serological biomarkers to distinguish between OvaCan and other malignancies is still an unresolved issue that requires more large-scale studies to confirm and validate the use of these biomarkers in the diagnosis of different types of cancer.

关键词： Anti-Glycan antibody tumor-associated glycans Biomarkers Glycan array microarray

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