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Pathak AK, Kural S, Singh S, Kumar L, Yadav M, Gupta M, Das P, Jain G. Development of a robust and generalizable algorithm "gQuant" for accurate normalizer gene selection in qRT-PCR analysis. Sci Rep 2024; 14:18774. [PMID: 39138232 PMCID: PMC11322313 DOI: 10.1038/s41598-024-66770-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2024] [Accepted: 07/03/2024] [Indexed: 08/15/2024] Open
Abstract
The emergent role of nucleic acid-based biomarkers-microRNAs(miRNAs), long non-coding RNAs(lncRNAs), and messenger RNAs(mRNAs), is becoming increasingly prominent in disease diagnostics and risk assessment. qRT-PCR is the primary analytical method for quantitative measurement of biomarkers. Yet, the relative infancy of non-coding RNAs recognition as biomarkers poses a challenge due to the absence of a consensus on a universally accepted normalizer gene, an absolute requirement for accurate quantification. Current tools normalizer selection are fraught with statistical limitations and suboptimal graphical user interface for data visualisation. These deficiencies underscore the necessity for a balanced tool tailored to handle qRT-PCR datasets. Addressing the identified challenges, we have developed 'gQuant' tool crafted to address these limitations. We employed voting classifiers that combine predictions from multiple statistical methods. Tool's efficacy was validated through different available and in house data derived from urinary exosomal miRNAs datasets. Comparative analysis with existing tools revealed that their integrated methodologies could skew the ranking of normalizer genes, whereas 'gQuant' consistently yielded rankings characterised by lower standard-deviation, reduced covariance, and enhanced kernel density estimation values. Given 'gQuant's' promising performance, normalizer gene identification will be greatly improved, improving precision of gene expression quantification in a variety of research scenarios. The gQuant tool developed for this study is available for public use and can be accessed at [ https://github.com/ABHAYHBB/gQuant-Tool ]."
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Affiliation(s)
- Abhay Kumar Pathak
- DST-CIMS, Institute of Science, Banaras Hindu University, Varanasi, India
| | - Sukhad Kural
- Department of Urology, Institute of Medical Sciences, Banaras Hindu University, Varanasi, India
| | - Shweta Singh
- Centre for Genetic Disorders, Institute of Science, Banaras Hindu University, Varanasi, India
| | - Lalit Kumar
- Department of Urology, Institute of Medical Sciences, Banaras Hindu University, Varanasi, India
| | - Mahima Yadav
- Department of Pathology, Institute of Medical Sciences, Banaras Hindu University, Varanasi, India
| | - Manjari Gupta
- DST-CIMS, Institute of Science, Banaras Hindu University, Varanasi, India
| | - Parimal Das
- Centre for Genetic Disorders, Institute of Science, Banaras Hindu University, Varanasi, India
| | - Garima Jain
- Centre for Genetic Disorders, Institute of Science, Banaras Hindu University, Varanasi, India.
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2
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Smith TAD. Gene Abnormalities and Modulated Gene Expression Associated with Radionuclide Treatment: Towards Predictive Biomarkers of Response. Genes (Basel) 2024; 15:688. [PMID: 38927624 PMCID: PMC11202453 DOI: 10.3390/genes15060688] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2024] [Revised: 05/22/2024] [Accepted: 05/23/2024] [Indexed: 06/28/2024] Open
Abstract
Molecular radiotherapy (MRT), also known as radioimmunotherapy or targeted radiotherapy, is the delivery of radionuclides to tumours by targeting receptors overexpressed on the cancer cell. Currently it is used in the treatment of a few cancer types including lymphoma, neuroendocrine, and prostate cancer. Recently reported outcomes demonstrating improvements in patient survival have led to an upsurge in interest in MRT particularly for the treatment of prostate cancer. Unfortunately, between 30% and 40% of patients do not respond. Further normal tissue exposure, especially kidney and salivary gland due to receptor expression, result in toxicity, including dry mouth. Predictive biomarkers to select patients who will benefit from MRT are crucial. Whilst pre-treatment imaging with imaging versions of the therapeutic agents is useful in demonstrating tumour binding and potentially organ toxicity, they do not necessarily predict patient benefit, which is dependent on tumour radiosensitivity. Transcript-based biomarkers have proven useful in tailoring external beam radiotherapy and adjuvant treatment. However, few studies have attempted to derive signatures for MRT response prediction. Here, transcriptomic studies that have identified genes associated with clinical radionuclide exposure have been reviewed. These studies will provide potential features for seeding multi-component biomarkers of MRT response.
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Affiliation(s)
- Tim A D Smith
- Nuclear Futures Institute, School of Computer Science and Engineering, Bangor University, Dean Street, Bangor LL57 1UT, UK
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3
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Cheng S, Yu X. CTPC, a combined transcriptome data set of human prostate cancer cell lines. Prostate 2023; 83:158-161. [PMID: 36207780 PMCID: PMC9771918 DOI: 10.1002/pros.24448] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/28/2022] [Revised: 09/13/2022] [Accepted: 09/26/2022] [Indexed: 12/24/2022]
Abstract
BACKGROUND Cell lines are the most used model system in cancer research. The transcriptomic data of established prostate cancer (PCa) cell lines help researchers explore differential gene expressions across the various PCa cell lines. METHODS Through large scale datamining, we established a curated Combined Transcriptome dataset of PCa Cell lines (CTPC) which contains the transcriptomic data of 1840 samples of 9 commonly used PCa cell lines including LNCaP, LNCaP-95, LNCaP-abl, C4-2, VCaP, 22Rv1, PC3, DU145, and NCI-H660. RESULTS The CTPC dataset provides an opportunity for researchers to not only compare gene expression across different PCa cell lines but also retrieve the experiment information and associate the differential gene expression data with meta data, such as gene manipulation and drug treatment information. Additionally, based on the CTPC dataset, we built a platform for users to visualize the data (https://pcatools.shinyapps.io/CTPC_V2/). CONCLUSIONS It is our hope that the combined CTPC dataset and the user-friendly platform are of great service to the PCa research community.
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Affiliation(s)
- Siyuan Cheng
- Department of Biochemistry & Molecular Biology, LSU Health Shreveport
- Feist Weiller Cancer Center, LSU Health Shreveport
| | - Xiuping Yu
- Department of Biochemistry & Molecular Biology, LSU Health Shreveport
- Department of Urology, LSU Health Shreveport
- Feist Weiller Cancer Center, LSU Health Shreveport
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4
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Xu J, Yang M, Shao AZ, Pan HW, Fan YX, Chen KP. Identification and Validation of Common Reference Genes for Normalization of Esophageal Squamous Cell Carcinoma Gene Expression Profiles. BIOMED RESEARCH INTERNATIONAL 2022; 2022:9125242. [PMID: 36467891 PMCID: PMC9711964 DOI: 10.1155/2022/9125242] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/20/2022] [Revised: 09/29/2022] [Accepted: 09/30/2022] [Indexed: 09/04/2024]
Abstract
Esophageal squamous cell carcinoma (ESCC) is one of the subtypes of esophageal cancer with Chinese characteristics, and its five-year survival rate is less than 20%. Early diagnosis is beneficial to improving the survival rate of ESCC significantly. Quantitative Real-Time Polymerase Chain Reaction is a high-throughput technique that can quantify tumor-related genes for early diagnosis. Its accuracy largely depends on the stability of the reference gene. There is no systematic scientific basis to demonstrate which reference gene expression is stable in ESCC and no consensus on the selection of internal reference. Therefore, this research used four software programs (The comparative delta-Ct method, GeNorm, NormFinder, and BestKeeper) to evaluate the expression stability of eight candidate reference genes commonly used in other tumor tissues and generated a comprehensive analysis by RefFinder. Randomly selected transcriptome sequencing analysis confirmed the SPP1 gene is closely related to ESCC. It was found that the expression trend of SPP1 obtained by RPS18 and PPIA as internal reference genes were the same as that of sequencing. The results show that RPS18 and PPIA are stable reference genes, and PPIA + RPS18 are a suitable reference gene combination. This is a reference gene report that combines transcriptome sequencing analysis and only focuses on ESCC, which makes the quantification more precise, systematic, and standardized, and promotes gene regulation research and the early diagnosis of ESCC in the future.
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Affiliation(s)
- Jia Xu
- School of Life Sciences, Jiangsu University, Zhenjiang, China
| | - Ming Yang
- Department of General Surgery, Fifth People's Hospital of Huaian City, Huaian, China
- School of Food and Biological Engineering, Jiangsu University, Zhenjiang, China
| | - Ai-zhong Shao
- Department of Cardiothorac Surgery, Affiliated People's Hospital of Jiangsu University, Zhenjiang, China
| | - Hui-wen Pan
- Department of Cardiothoracic Surgery, Affiliated People's Hospital of Jiangsu University, Zhenjiang, Jiangsu Province, China
| | - Yi-xuan Fan
- School of Life Sciences, Jiangsu University, Zhenjiang, China
| | - Ke-ping Chen
- School of Life Sciences, Jiangsu University, Zhenjiang, China
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5
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Transcriptomic and Proteomic Profiles for Elucidating Cisplatin Resistance in Head-and-Neck Squamous Cell Carcinoma. Cancers (Basel) 2022; 14:cancers14225511. [PMID: 36428603 PMCID: PMC9688094 DOI: 10.3390/cancers14225511] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2022] [Revised: 11/03/2022] [Accepted: 11/07/2022] [Indexed: 11/12/2022] Open
Abstract
To identify the novel genes involved in chemoresistance in head and neck squamous cell carcinoma (HNSCC), we explored the expression profiles of the following cisplatin (CDDP) resistant (R) versus parental (sensitive) cell lines by RNA-sequencing (RNA-seq): JHU029, HTB-43 and CCL-138. Using the parental condition as a control, 30 upregulated and 85 downregulated genes were identified for JHU029-R cells; 263 upregulated and 392 downregulated genes for HTB-43-R cells, and 154 upregulated and 68 downregulated genes for CCL-138-R cells. Moreover, we crossed-checked the RNA-seq results with the proteomic profiles of HTB-43-R (versus HTB-43) and CCL-138-R (versus CCL-138) cell lines. For the HTB-43-R cells, 21 upregulated and 72 downregulated targets overlapped between the proteomic and transcriptomic data; whereas in CCL-138-R cells, four upregulated and three downregulated targets matched. Following an extensive literature search, six genes from the RNA-seq (CLDN1, MAGEB2, CD24, CEACAM6, IL1B and ISG15) and six genes from the RNA-seq and proteomics crossover (AKR1C3, TNFAIP2, RAB7A, LGALS3BP, PSCA and SSRP1) were selected to be studied by qRT-PCR in 11 HNSCC patients: six resistant and five sensitive to conventional therapy. Interestingly, the high MAGEB2 expression was associated with resistant tumours and is revealed as a novel target to sensitise resistant cells to therapy in HNSCC patients.
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6
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Moes-Sosnowska J, Skupinska M, Lechowicz U, Szczepulska-Wojcik E, Skronska P, Rozy A, Stepniewska A, Langfort R, Rudzinski P, Orlowski T, Popiel D, Stanczak A, Wieczorek M, Chorostowska-Wynimko J. FGFR1-4 RNA-Based Gene Alteration and Expression Analysis in Squamous Non-Small Cell Lung Cancer. Int J Mol Sci 2022; 23:ijms231810506. [PMID: 36142417 PMCID: PMC9505002 DOI: 10.3390/ijms231810506] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2022] [Revised: 08/27/2022] [Accepted: 09/02/2022] [Indexed: 02/07/2023] Open
Abstract
While fibroblast growth factor receptors (FGFRs) are involved in several biological pathways and FGFR inhibitors may be useful in the treatment of squamous non-small cell lung cancer (Sq-NSCLC), FGFR aberrations are not well characterized in Sq-NSCLC. We comprehensively evaluated FGFR expression, fusions, and variants in 40 fresh-frozen primary Sq-NSCLC (stage IA3−IV) samples and tumor-adjacent normal tissues using real-time PCR and next-generation sequencing (NGS). Protein expression of FGFR1−3 and amplification of FGFR1 were also analyzed. FGFR1 and FGFR4 median gene expression was significantly (p < 0.001) decreased in tumors compared with normal tissue. Increased FGFR3 expression enhanced the recurrence risk (hazard ratio 4.72, p = 0.029), while high FGFR4 expression was associated with lymph node metastasis (p = 0.036). Enhanced FGFR1 gene expression was correlated with FGFR1 protein overexpression (r = 0.75, p = 0.0003), but not with FGFR1 amplification. NGS revealed known pathogenic FGFR2,3 variants, an FGFR3::TACC3 fusion, and a novel TACC1::FGFR1 fusion together with FGFR1,2 variants of uncertain significance not previously reported in Sq-NSCLC. These findings expand our knowledge of the Sq-NSCLC molecular background and show that combining different methods increases the rate of FGFR aberrations detection, which may improve patient selection for FGFRi treatment.
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MESH Headings
- Carcinoma, Non-Small-Cell Lung/pathology
- Carcinoma, Squamous Cell/genetics
- Carcinoma, Squamous Cell/pathology
- Humans
- Lung Neoplasms/genetics
- Lung Neoplasms/pathology
- Microtubule-Associated Proteins
- Receptor, Fibroblast Growth Factor, Type 1/genetics
- Receptor, Fibroblast Growth Factor, Type 2/genetics
- Receptor, Fibroblast Growth Factor, Type 3/genetics
- Receptor, Fibroblast Growth Factor, Type 4/genetics
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Affiliation(s)
- Joanna Moes-Sosnowska
- Department of Genetics and Clinical Immunology, National Institute of Tuberculosis and Lung Diseases, 01-138 Warsaw, Poland or
| | - Monika Skupinska
- Preclinical Development Department, Celon Pharma S.A, Research & Development Centre, 05-152 Kazun Nowy, Poland
| | - Urszula Lechowicz
- Department of Genetics and Clinical Immunology, National Institute of Tuberculosis and Lung Diseases, 01-138 Warsaw, Poland or
| | - Ewa Szczepulska-Wojcik
- Department of Pathology, National Institute of Tuberculosis and Lung Diseases, 01-138 Warsaw, Poland
| | - Paulina Skronska
- Department of Genetics and Clinical Immunology, National Institute of Tuberculosis and Lung Diseases, 01-138 Warsaw, Poland or
| | - Adriana Rozy
- Department of Genetics and Clinical Immunology, National Institute of Tuberculosis and Lung Diseases, 01-138 Warsaw, Poland or
| | - Aneta Stepniewska
- Department of Genetics and Clinical Immunology, National Institute of Tuberculosis and Lung Diseases, 01-138 Warsaw, Poland or
| | - Renata Langfort
- Department of Pathology, National Institute of Tuberculosis and Lung Diseases, 01-138 Warsaw, Poland
| | - Piotr Rudzinski
- Department of Surgery, National Institute of Tuberculosis and Lung Diseases, 01-138 Warsaw, Poland
| | - Tadeusz Orlowski
- Department of Surgery, National Institute of Tuberculosis and Lung Diseases, 01-138 Warsaw, Poland
| | - Delfina Popiel
- Preclinical Development Department, Celon Pharma S.A, Research & Development Centre, 05-152 Kazun Nowy, Poland
| | - Aleksandra Stanczak
- Clinical Development Department, Celon Pharma S.A., Research & Development Centre, 05-152 Kazun Nowy, Poland
| | - Maciej Wieczorek
- Preclinical Development Department, Celon Pharma S.A, Research & Development Centre, 05-152 Kazun Nowy, Poland
- Clinical Development Department, Celon Pharma S.A., Research & Development Centre, 05-152 Kazun Nowy, Poland
| | - Joanna Chorostowska-Wynimko
- Department of Genetics and Clinical Immunology, National Institute of Tuberculosis and Lung Diseases, 01-138 Warsaw, Poland or
- Correspondence: or
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7
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Köhler SA, Brandl L, Strissel PL, Gloßner L, Ekici AB, Angeloni M, Ferrazzi F, Bahlinger V, Hartmann A, Beckmann MW, Eckstein M, Strick R. Improved Bladder Tumor RNA Isolation from Archived Tissues Using Methylene Blue for Normalization, Multiplex RNA Hybridization, Sequencing and Subtyping. Int J Mol Sci 2022; 23:ijms231810267. [PMID: 36142180 PMCID: PMC9499321 DOI: 10.3390/ijms231810267] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2022] [Revised: 08/26/2022] [Accepted: 09/02/2022] [Indexed: 12/02/2022] Open
Abstract
Methylene blue (MB) is a dye used for histology with clinical importance and intercalates into nucleic acids. After MB staining of formalin fixed paraffin embedded (FFPE) muscle invasive bladder cancer (MIBC) and normal urothelium, specific regions could be microdissected. It is not known if MB influences RNA used for gene expression studies. Therefore, we analyzed MIBC using five different RNA isolation methods comparing patient matched FFPE and fresh frozen (FF) tissues pre-stained with or without MB. We demonstrate a positive impact of MB on RNA integrity with FF tissues using real time PCR with no interference of its chemical properties. FFPE tissues showed no improvement of RNA integrity, which we propose is due to formalin induced nucleotide crosslinks. Using direct multiplex RNA hybridization the best genes for normalization of MIBC and control tissues were identified from 34 reference genes. In addition, 5SrRNA and 5.8SrRNA were distinctive reference genes detecting <200 bp fragments important for mRNA analyses. Using these normalized RNAs from MB stained MIBC and applying multiplex RNA hybridization and mRNA sequencing, a minimal gene expression panel precisely identified luminal and basal MIBC tumor subtypes, important for diagnosis, prognosis and chemotherapy response.
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Affiliation(s)
- Stefanie A. Köhler
- Laboratory for Molecular Medicine, Department of Gynecology and Obstetrics, University Hospital Erlangen, Friedrich-Alexander Universität Erlangen-Nürnberg, Universitaetsstrasse 21-23, 91054 Erlangen, Germany
- Comprehensive Cancer Center Erlangen-EMN (CCC ER-EMN), University Hospital Erlangen, Östliche Stadtmauerstrasse 30, 91054 Erlangen, Germany
| | - Lisa Brandl
- Comprehensive Cancer Center Erlangen-EMN (CCC ER-EMN), University Hospital Erlangen, Östliche Stadtmauerstrasse 30, 91054 Erlangen, Germany
- Institute of Pathology, University Hospital Erlangen, Friedrich-Alexander Universität Erlangen-Nürnberg, Krankenhausstrasse 8-10, 91054 Erlangen, Germany
| | - Pamela L. Strissel
- Laboratory for Molecular Medicine, Department of Gynecology and Obstetrics, University Hospital Erlangen, Friedrich-Alexander Universität Erlangen-Nürnberg, Universitaetsstrasse 21-23, 91054 Erlangen, Germany
- Comprehensive Cancer Center Erlangen-EMN (CCC ER-EMN), University Hospital Erlangen, Östliche Stadtmauerstrasse 30, 91054 Erlangen, Germany
- Institute of Pathology, University Hospital Erlangen, Friedrich-Alexander Universität Erlangen-Nürnberg, Krankenhausstrasse 8-10, 91054 Erlangen, Germany
| | - Laura Gloßner
- Comprehensive Cancer Center Erlangen-EMN (CCC ER-EMN), University Hospital Erlangen, Östliche Stadtmauerstrasse 30, 91054 Erlangen, Germany
- Institute of Pathology, University Hospital Erlangen, Friedrich-Alexander Universität Erlangen-Nürnberg, Krankenhausstrasse 8-10, 91054 Erlangen, Germany
| | - Arif B. Ekici
- Institute of Human Genetics, University Hospital Erlangen, Friedrich-Alexander Universität Erlangen-Nürnberg, 91054 Erlangen, Germany
| | - Miriam Angeloni
- Comprehensive Cancer Center Erlangen-EMN (CCC ER-EMN), University Hospital Erlangen, Östliche Stadtmauerstrasse 30, 91054 Erlangen, Germany
- Institute of Pathology, University Hospital Erlangen, Friedrich-Alexander Universität Erlangen-Nürnberg, Krankenhausstrasse 8-10, 91054 Erlangen, Germany
| | - Fulvia Ferrazzi
- Comprehensive Cancer Center Erlangen-EMN (CCC ER-EMN), University Hospital Erlangen, Östliche Stadtmauerstrasse 30, 91054 Erlangen, Germany
- Institute of Pathology, University Hospital Erlangen, Friedrich-Alexander Universität Erlangen-Nürnberg, Krankenhausstrasse 8-10, 91054 Erlangen, Germany
- Department of Nephropathology, Institute of Pathology, University Hospital Erlangen, Friedrich-Alexander Universität Erlangen-Nürnberg, Krankenhausstrasse 8-10, 91054 Erlangen, Germany
| | - Veronika Bahlinger
- Comprehensive Cancer Center Erlangen-EMN (CCC ER-EMN), University Hospital Erlangen, Östliche Stadtmauerstrasse 30, 91054 Erlangen, Germany
- Institute of Pathology, University Hospital Erlangen, Friedrich-Alexander Universität Erlangen-Nürnberg, Krankenhausstrasse 8-10, 91054 Erlangen, Germany
| | - Arndt Hartmann
- Comprehensive Cancer Center Erlangen-EMN (CCC ER-EMN), University Hospital Erlangen, Östliche Stadtmauerstrasse 30, 91054 Erlangen, Germany
- Institute of Pathology, University Hospital Erlangen, Friedrich-Alexander Universität Erlangen-Nürnberg, Krankenhausstrasse 8-10, 91054 Erlangen, Germany
| | - Matthias W. Beckmann
- Laboratory for Molecular Medicine, Department of Gynecology and Obstetrics, University Hospital Erlangen, Friedrich-Alexander Universität Erlangen-Nürnberg, Universitaetsstrasse 21-23, 91054 Erlangen, Germany
- Comprehensive Cancer Center Erlangen-EMN (CCC ER-EMN), University Hospital Erlangen, Östliche Stadtmauerstrasse 30, 91054 Erlangen, Germany
| | - Markus Eckstein
- Comprehensive Cancer Center Erlangen-EMN (CCC ER-EMN), University Hospital Erlangen, Östliche Stadtmauerstrasse 30, 91054 Erlangen, Germany
- Institute of Pathology, University Hospital Erlangen, Friedrich-Alexander Universität Erlangen-Nürnberg, Krankenhausstrasse 8-10, 91054 Erlangen, Germany
| | - Reiner Strick
- Laboratory for Molecular Medicine, Department of Gynecology and Obstetrics, University Hospital Erlangen, Friedrich-Alexander Universität Erlangen-Nürnberg, Universitaetsstrasse 21-23, 91054 Erlangen, Germany
- Comprehensive Cancer Center Erlangen-EMN (CCC ER-EMN), University Hospital Erlangen, Östliche Stadtmauerstrasse 30, 91054 Erlangen, Germany
- Correspondence: ; Tel.: +49-91318536671
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8
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Smith TAD, Lane B, More E, Valentine H, Lunj S, Abdelkarem OA, Irlam-Jones J, Shabbir R, Vora S, Denley H, Reeves KJ, Hoskin PJ, Choudhury A, West CML. Comparison of multiple gene expression platforms for measuring a bladder cancer hypoxia signature. Mol Med Rep 2022; 26:261. [PMID: 35730624 DOI: 10.3892/mmr.2022.12777] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2022] [Accepted: 04/25/2022] [Indexed: 11/05/2022] Open
Abstract
Tumour hypoxia status provides prognostic information and predicts response to hypoxia‑modifying treatments. A previous study by our group derived a 24‑gene signature to assess hypoxia in bladder cancer. The objectives of the present study were to compare platforms for generating signature scores, identify cut‑off values for prospective studies, assess intra‑tumour heterogeneity and confirm hypoxia relevance. Briefly, RNA was extracted from prospectively collected diagnostic biopsies of muscle invasive bladder cancer (51 patients), and gene expression was measured using customised Taqman Low Density Array (TLDA) cards, NanoString and Clariom S arrays. Cross‑platform transferability of the gene signature was assessed using regression and concordance analysis. The cut‑off values were the cohort median expression values. Intra‑ and inter‑tumour variability were determined in a retrospective patient cohort (n=51) with multiple blocks (2‑18) from the same tumour. To demonstrate relevance, bladder cancer cell lines were exposed to hypoxia (0.1% oxygen, 24 h), and extracted RNA was run on custom TLDA cards. Hypoxia scores (HS) values showed good agreement between platforms: Clariom S vs. TLDA (r=0.72, P<0.0001; concordance 73%); Clariom S vs. NanoString (r=0.84, P<0.0001; 78%); TLDA vs. NanoString (r=0.80, P<0.0001; 78%). Cut‑off values were 0.047 (TLDA), 7.328 (NanoString) and 6.667 (Clariom S). Intra‑tumour heterogeneity in gene expression and HS (coefficient of variation 3.9%) was less than inter‑tumour (7.9%) variability. HS values were higher in bladder cancer cells exposed to hypoxia compared with normoxia (P<0.02). In conclusion, the present study revealed that application of the 24‑gene bladder cancer hypoxia signature was platform agnostic, cut‑off values determined prospectively can be used in a clinical trial, intra‑tumour heterogeneity was low and the signature was sensitive to changes in oxygen levels in vitro.
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Affiliation(s)
- Tim A D Smith
- Translational Radiobiology Group, Division of Cancer Sciences, University of Manchester, Manchester M20 4GJ, UK
| | - Brian Lane
- Translational Radiobiology Group, Division of Cancer Sciences, University of Manchester, Manchester M20 4GJ, UK
| | - Elisabet More
- Translational Radiobiology Group, Division of Cancer Sciences, University of Manchester, Manchester M20 4GJ, UK
| | - Helen Valentine
- Translational Radiobiology Group, Division of Cancer Sciences, University of Manchester, Manchester M20 4GJ, UK
| | - Sapna Lunj
- Translational Radiobiology Group, Division of Cancer Sciences, University of Manchester, Manchester M20 4GJ, UK
| | - Omneya A Abdelkarem
- Chemical Pathology Department, Medical Research Institute, Alexandria University, Alexandria 21561, Egypt
| | - J Irlam-Jones
- Translational Radiobiology Group, Division of Cancer Sciences, University of Manchester, Manchester M20 4GJ, UK
| | - Rekaya Shabbir
- Translational Radiobiology Group, Division of Cancer Sciences, University of Manchester, Manchester M20 4GJ, UK
| | - Shrushti Vora
- Translational Radiobiology Group, Division of Cancer Sciences, University of Manchester, Manchester M20 4GJ, UK
| | - Helen Denley
- Pathology Centre, Shrewsbury and Telford NHS Trust, Royal Shrewsbury Hospital, Shrewsbury SY3 8XQ, UK
| | - Kimberley J Reeves
- Translational Radiobiology Group, Division of Cancer Sciences, University of Manchester, Manchester M20 4GJ, UK
| | - Peter J Hoskin
- Translational Radiobiology Group, Division of Cancer Sciences, University of Manchester, Manchester M20 4GJ, UK
| | - Ananya Choudhury
- Translational Radiobiology Group, Division of Cancer Sciences, University of Manchester, Manchester M20 4GJ, UK
| | - Catharine M L West
- Translational Radiobiology Group, Division of Cancer Sciences, University of Manchester, Manchester M20 4GJ, UK
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9
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Salameh L, Bhamidimarri PM, Saheb Sharif-Askari N, Dairi Y, Hammoudeh SM, Mahdami A, Alsharhan M, Tirmazy SH, Rawat SS, Busch H, Hamid Q, Al Heialy S, Hamoudi R, Mahboub B. In Silico Bioinformatics Followed by Molecular Validation Using Archival FFPE Tissue Biopsies Identifies a Panel of Transcripts Associated with Severe Asthma and Lung Cancer. Cancers (Basel) 2022; 14:cancers14071663. [PMID: 35406434 PMCID: PMC8996975 DOI: 10.3390/cancers14071663] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2022] [Revised: 03/07/2022] [Accepted: 03/14/2022] [Indexed: 12/04/2022] Open
Abstract
Simple Summary The present study identified a panel of transcripts involved in the pathogenesis of both severe asthma and lung cancer. The genes identified using publicly available transcriptomics data were validated on cell lines, plasma samples, and archival tissue biopsies from asthmatic and lung cancer patients. The functional roles of the identified markers in both the diseases were ascertained from the literature. These molecular markers might be useful for diagnosing lung cancer at early stages. Abstract Severe asthma and lung cancer are both heterogeneous pathological diseases affecting the lung tissue. Whilst there are a few studies that suggest an association between asthma and lung cancer, to the best of our knowledge, this is the first study to identify common genes involved in both severe asthma and lung cancer. Publicly available transcriptomic data for 23 epithelial brushings from severe asthmatics and 55 samples of formalin-fixed paraffin-embedded (FFPE) lung cancer tissue at relatively early stages were analyzed by absolute gene set enrichment analysis (GSEA) in comparison to 37 healthy bronchial tissue samples. The key pathways enriched in asthmatic patients included adhesion, extracellular matrix, and epithelial cell proliferation, which contribute to tissue remodeling. In the lung cancer dataset, the main pathways identified were receptor tyrosine kinase signaling, wound healing, and growth factor response, representing the early cancer pathways. Analysis of the enriched genes derived from the pathway analysis identified seven genes expressed in both the asthma and lung cancer sets: BCL3, POSTN, PPARD, STAT1, MYC, CD44, and FOSB. The differential expression of these genes was validated in vitro in the cell lines retrieved from different lung cancer and severe asthma patients using real-time PCR. The effect of the expression of the seven genes identified in the study on the overall survival of lung cancer patients (n = 1925) was assessed using a Kaplan–Meier plot. In vivo validation performed in the archival biopsies obtained from patients diagnosed with both the disease conditions provided interesting insights into the pathogenesis of severe asthma and lung cancer, as indicated by the differential expression pattern of the seven transcripts in the mixed group as compared to the asthmatics and lung cancer samples alone.
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Affiliation(s)
- Laila Salameh
- Sharjah Institute for Medical Research, College of Medicine, University of Sharjah, Sharjah 27272, United Arab Emirates; (L.S.); (P.M.B.); (N.S.S.-A.); (S.M.H.); (A.M.); (Q.H.)
- Dubai Health Authority, Dubai 4545, United Arab Emirates; (Y.D.); (M.A.); (S.H.T.); (B.M.)
| | - Poorna Manasa Bhamidimarri
- Sharjah Institute for Medical Research, College of Medicine, University of Sharjah, Sharjah 27272, United Arab Emirates; (L.S.); (P.M.B.); (N.S.S.-A.); (S.M.H.); (A.M.); (Q.H.)
| | - Narjes Saheb Sharif-Askari
- Sharjah Institute for Medical Research, College of Medicine, University of Sharjah, Sharjah 27272, United Arab Emirates; (L.S.); (P.M.B.); (N.S.S.-A.); (S.M.H.); (A.M.); (Q.H.)
| | - Youssef Dairi
- Dubai Health Authority, Dubai 4545, United Arab Emirates; (Y.D.); (M.A.); (S.H.T.); (B.M.)
| | - Sarah Musa Hammoudeh
- Sharjah Institute for Medical Research, College of Medicine, University of Sharjah, Sharjah 27272, United Arab Emirates; (L.S.); (P.M.B.); (N.S.S.-A.); (S.M.H.); (A.M.); (Q.H.)
| | - Amena Mahdami
- Sharjah Institute for Medical Research, College of Medicine, University of Sharjah, Sharjah 27272, United Arab Emirates; (L.S.); (P.M.B.); (N.S.S.-A.); (S.M.H.); (A.M.); (Q.H.)
| | - Mouza Alsharhan
- Dubai Health Authority, Dubai 4545, United Arab Emirates; (Y.D.); (M.A.); (S.H.T.); (B.M.)
| | - Syed Hammad Tirmazy
- Dubai Health Authority, Dubai 4545, United Arab Emirates; (Y.D.); (M.A.); (S.H.T.); (B.M.)
| | - Surendra Singh Rawat
- Collage of Medicine, Mohammed Bin Rashid University of Medicine and Health Sciences, Dubai 505055, United Arab Emirates; (S.S.R.); (S.A.H.)
| | - Hauke Busch
- Lübeck Institute of Experimental Dermatology, University of Lübeck, Lübeck 23562, Germany;
| | - Qutayba Hamid
- Sharjah Institute for Medical Research, College of Medicine, University of Sharjah, Sharjah 27272, United Arab Emirates; (L.S.); (P.M.B.); (N.S.S.-A.); (S.M.H.); (A.M.); (Q.H.)
- Meakins-Christie Laboratories, Research Institute of the McGill University Healthy Center, Faculty of Medicine, Montreal, QC H3A 0G4, Canada
| | - Saba Al Heialy
- Collage of Medicine, Mohammed Bin Rashid University of Medicine and Health Sciences, Dubai 505055, United Arab Emirates; (S.S.R.); (S.A.H.)
- Meakins-Christie Laboratories, Research Institute of the McGill University Healthy Center, Faculty of Medicine, Montreal, QC H3A 0G4, Canada
| | - Rifat Hamoudi
- Sharjah Institute for Medical Research, College of Medicine, University of Sharjah, Sharjah 27272, United Arab Emirates; (L.S.); (P.M.B.); (N.S.S.-A.); (S.M.H.); (A.M.); (Q.H.)
- Division of Surgery and Interventional Science, University College London, London NW3 2QG, UK
- Correspondence: ; Tel.: +971-6505-7758
| | - Bassam Mahboub
- Dubai Health Authority, Dubai 4545, United Arab Emirates; (Y.D.); (M.A.); (S.H.T.); (B.M.)
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Gorji-Bahri G, Moradtabrizi N, Vakhshiteh F, Hashemi A. Validation of common reference genes stability in exosomal mRNA-isolated from liver and breast cancer cell lines. Cell Biol Int 2021; 45:1098-1110. [PMID: 33501690 DOI: 10.1002/cbin.11556] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2020] [Revised: 01/02/2021] [Accepted: 01/24/2021] [Indexed: 12/12/2022]
Abstract
Accurate relative gene expression analysis by reverse transcription-quantitative polymerase chain reaction relies on the usage of suitable reference genes for data normalization. The RNA content of small extracellular vesicles including exosomes is growingly considered as cancer biomarkers. So, reliable relative quantification of exosomal messenger RNA (mRNA) is essential for cancer diagnosis and prognosis applications. However, suitable reference genes for accurate normalization of a target gene in exosomes derived from cancer cells are not depicted yet. Here, we analyzed the expression and stability of eight well-known reference genes namely GAPDH, B2M, HPRT1, ACTB, YWHAZ, UBC, RNA18S, and TBP in exosomes-isolated from the liver (Huh7, HepG2, PLC/PRF/5) and breast (SK-BR-3) cancer cell lines using five different algorithms including geNorm, BestKeeper, Delta Ct, NormFinder, and RefFinder. Our results showed that ACTB, TBP, and HPRT1 were not expressed in exosomes-isolated from studied liver and breast cancer cell lines. The geNorm and BestKeeper algorithms indicated GAPDH and UBC as the most stable candidates. Moreover, Delta Ct and NormFinder algorithms showed YWHAZ as the most stable reference genes. Comprehensive ranking calculated by the RefFinder algorithm also pointed out GAPDH, YWHAZ, and UBC as the first three stable reference genes. Taken together, this study validated the common reference genes stability in exosomal mRNA derived from liver and breast cancer cell lines for the first time. We believe that this study would be the first step in finding more stable reference genes in exosomes that triggers more accurate detection of exosomal biomarkers.
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Affiliation(s)
- Gilar Gorji-Bahri
- Department of Pharmaceutical Biotechnology, School of Pharmacy, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Niloofar Moradtabrizi
- Department of Pharmaceutical Biotechnology, School of Pharmacy, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Faezeh Vakhshiteh
- Nanotechnology Research Center, Faculty of Pharmacy, Tehran University of Medical Sciences, Tehran, Iran
| | - Atieh Hashemi
- Department of Pharmaceutical Biotechnology, School of Pharmacy, Shahid Beheshti University of Medical Sciences, Tehran, Iran
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