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Datasets from "Circulating miRNA and Lung Cancer: - a More Comprehensive Analysis of Available Data"

A collection of datasets on miRNA and lung cancer used in Berg, O.F.B.: Circulating miRNA and Lung Cancer: - a More Comprehensive Analysis of Available Data. NTNU Open (2022)   The datasets in this collection are processed and normalized from available raw datasets. The processing code that was used can be found on <a href="https://github.com/OleFredrik1/masterthesis">https://github.com/OleFredrik1/masterthesis</a>. The raw datasets are: Asakura2020: Asakura, K., Kadota, T., Matsuzaki, J., Yoshida, Y., Yamamoto, Y., Nakagawa, K., Takizawa, S., Aoki, Y., Nakamura, E., Miura, J., Sakamoto, H., Kato, K., Watanabe, S.-i., and Ochiya, T. (2020). A miRNA-based diagnostic model predicts resectable lung cancer in humans with high accuracy. Communications Biology, 3(1):1–9. Accession ID: GSE137140 Link: <a href="https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE137140">https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE137140</a>   Bianchi2011: Bianchi, F., Nicassio, F., Marzi, M., Belloni, E., Dall’Olio, V., Bernard, L., Pelosi, G., Maisonneuve, P., Veronesi, G., and Di Fiore, P. P. (2011). A serum circulating miRNA diagnostic test to identify asymptomatic high-risk individuals with early stage lung cancer. EMBO Molecular Medicine, 3(8):495–503. Link: <a href="https://www.embopress.org/action/downloadSupplement?doi=10.1002%2Femmm.201100154&file=emmm_201100154_sm_suppdata2.xls">https://www.embopress.org/action/downloadSupplement?doi=10.1002%2Femmm.201100154&file=emmm_201100154_sm_suppdata2.xls</a>   Chen2019: Accession ID: GSE71661 Link: <a href="https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE71661">https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE71661</a>   Duan2021: Duan, X., Qiao, S., Li, D., Li, S., Zheng, Z., Wang, Q., and Zhu, X. (2021). Circulating miRNAs in Serum as Biomarkers for Early Diagnosis of Non-small Cell Lung Cancer. Frontiers in Genetics, 12:987. Accession ID: GSE137140 Link: <a href="https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE137140">https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE137140</a>   Fehlmann2020: Fehlmann, T., Kahraman, M., Ludwig, N., Backes, C., Galata, V., Keller, V., Geffers, L., Mercaldo, N., Hornung, D., Weis, T., Kayvanpour, E., Abu-Halima, M., Deuschle, C., Schulte, C., Suenkel, U., von Thaler, A.-K., Maetzler, W., Herr, C., Fähndrich, S., Vogelmeier, C., Guimaraes, P., Hecksteden, A., Meyer, T., Metzger, F., Diener, C., Deutscher, S., Abdul-Khaliq, H., Stehle, I., Haeusler, S., Meiser, A., Groesdonk, H. V., Volk, T., Lenhof, H.-P., Katus, H., Balling, R., Meder, B., Kruger, R., Huwer, H., Bals, R., Meese, E., and Keller, A. (2020). Evaluating the Use of Circulating MicroRNA Profiles for Lung Cancer Detection in Symptomatic Patients. JAMA oncology, 6(5):714–723. Accession ID: E-MTAB-8026 Link: <a href="https://www.ebi.ac.uk/arrayexpress/experiments/E-MTAB-8026/">https://www.ebi.ac.uk/arrayexpress/experiments/E-MTAB-8026/</a>   Halvorsen2016: Halvorsen, A. R., Bjaanæs, M., LeBlanc, M., Holm, A. M., Bolstad, N., Rubio, L., Peñalver, J. C., Cervera, J., Mojarrieta, J. C., López-Guerrero, J. A., Brustugun, O. T., and Helland, Å. (2016). A unique set of 6 circulating microRNAs for early detection of non-small cell lung cancer. Oncotarget, 7(24):37250–37259. Accession ID: GSE70080 Link: <a href="https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE70080">https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE70080</a>   Jin2017: Jin, X., Chen, Y., Chen, H., Fei, S., Chen, D., Cai, X., Liu, L., Lin, B., Su, H., Zhao, L., Su, M., Pan, H., Shen, L., Xie, D., and Xie, C. (2017). Evaluation of Tumor-Derived Exosomal miRNA as Potential Diagnostic Biomarkers for Early-Stage Non–Small Cell Lung Cancer Using Next-Generation Sequencing. Clinical Cancer Research, 23(17):5311–5319. Link: <a href="https://aacrjournals.org/clincancerres/article/23/17/5311/123048/Evaluation-of-Tumor-Derived-Exosomal-miRNA-as">https://aacrjournals.org/clincancerres/article/23/17/5311/123048/Evaluation-of-Tumor-Derived-Exosomal-miRNA-as</a> (table s1)   Keller2009: Keller, A., Leidinger, P., Borries, A., Wendschlag, A., Wucherpfennig, F., Scheffler, M., Huwer, H., Lenhof, H.-P., and Meese, E. (2009). miRNAs in lung cancer - Studying complex fingerprints in patient’s blood cells by microarray experiments. BMC Cancer, 9(1):353. Accession ID: GSE17681 Link: <a href="https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE17681">https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE17681</a>   Keller2014: Keller, A., Leidinger, P., Vogel, B., Backes, C., ElSharawy, A., Galata, V., Mueller, S. C., Marquart, S., Schrauder, M. G., Strick, R., Bauer, A., Wischhusen, J., Beier, M., Kohlhaas, J., Katus, H. A., Hoheisel, J., Franke, A., Meder, B., and Meese, E. (2014). miRNAs can be generally associated with human pathologies as exemplified for miR-144*. BMC Medicine, 12(1):224. Accession ID: GSE61741 Link: <a href="https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE61741">https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE61741</a>   Keller2020: Keller, A., Fehlmann, T., Backes, C., Kern, F., Gislefoss, R., Langseth, H., Rounge, T. B., Ludwig, N., and Meese, E. (2020). Competitive learning suggests circulating miRNA profiles for cancers decades prior to diagnosis. RNA Biology, 17(10):1416–1426. Link: <a href="https://www.tandfonline.com/doi/full/10.1080/15476286.2020.1771945">https://www.tandfonline.com/doi/full/10.1080/15476286.2020.1771945</a> (Supplemental Table 9)   Kryczka2021: Kryczka, J., Migdalska-Sęk, M., Kordiak, J., Kiszałkiewicz, J. M., PastuszakLewandoska, D., Antczak, A., and Brzeziańska-Lasota, E. (2021). Serum Extracellular Vesicle-Derived miRNAs in Patients with Non-Small Cell Lung Cancer—Search for Non-Invasive Diagnostic Biomarkers. Diagnostics, 11(3):425. Link: <a href="https://www.mdpi.com/2075-4418/11/3/425/s1">https://www.mdpi.com/2075-4418/11/3/425/s1</a>   Leidinger2011: Leidinger, P., Keller, A., Borries, A., Huwer, H., Rohling, M., Huebers, J., Lenhof, H.-P., and Meese, E. (2011). Specific peripheral miRNA profiles for distinguishing lung cancer from COPD. Lung Cancer, 74(1):41–47. Accession ID: GSE24709 Link: <a href="https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE24709">https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE24709</a>   Leidinger2014: Leidinger, P., Backes, C., Dahmke, I. N., Galata, V., Huwer, H., Stehle, I., Bals, R., Keller, A., and Meese, E. (2014). What makes a blood cell based miRNA expression pattern disease specific? - A miRNome analysis of blood cell subsets in lung cancer patients and healthy controls. Oncotarget, 5(19):9484–9497. Accession ID: GSE55993 Link: <a href="https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE55993">https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE55993</a>   Leidinger2016: Leidinger, P., Brefort, T., Backes, C., Krapp, M., Galata, V., Beier, M., Kohlhaas, J., Huwer, H., Meese, E., and Keller, A. (2016). High-throughput qRT-PCR validation of blood microRNAs in non-small cell lung cancer. Oncotarget, 7(4):4611–4623. Link: <a href="https://www.oncotarget.com/article/6566/text/">https://www.oncotarget.com/article/6566/text/</a> (supplementary files)   Li2017: Li, L.-L., Qu, L.-L., Fu, H.-J., Zheng, X.-F., Tang, C.-H., Li, X.-Y., Chen, J., Wang, W.-X., Yang, S.-X., Wang, L., Zhao, G.-H., Lv, P.-P., Zhang, M., Lei, Y.-Y., Qin, H.-F., Wang, H., Gao, H.-J., and Liu, X.-Q. (2017). Circulating microRNAs as novel biomarkers of ALK-positive non-small cell lung cancer and predictors of response to crizotinib therapy. Oncotarget, 8(28):45399–45414. Accession ID: GSE94536 Link: <a href="https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE94536">https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE94536</a>   Marzi2016: Marzi, M. J., Montani, F., Carletti, R. M., Dezi, F., Dama, E., Bonizzi, G., Sandri, M. T., Rampinelli, C., Bellomi, M., Maisonneuve, P., Spaggiari, L., Veronesi, G., Bianchi, F., Di Fiore, P. P., and Nicassio, F. (2016). Optimization and Standardization of Circulating MicroRNA Detection for Clinical Application: The miR-Test Case. Clinical Chemistry, 62(5):743–754 Accession ID: GSE76462 Link: <a href="https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE76462">https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE76462</a>   Nigita2018: Nigita, G., Distefano, R., Veneziano, D., Romano, G., Rahman, M., Wang, K., Pass, H., Croce, C. M., Acunzo, M., and Nana-Sinkam, P. (2018). Tissue and exosomal miRNA editing in Non-Small Cell Lung Cancer. Scientific Reports, 8(1):10222. Accession ID: GSE114711 Link: <a href="https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE114711">https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE114711</a>   Patnaik2012: Patnaik, S. K., Yendamuri, S., Kannisto, E., Kucharczuk, J. C., Singhal, S., and Vachani, A. (2012). MicroRNA Expression Profiles of Whole Blood in Lung Adenocarcinoma. PLOS ONE, 7(9):e46045. Accession ID: GSE27486 Link: <a href="https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE27486">https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE27486</a>   Patnaik2017: Patnaik, S. K., Kannisto, E. D., Mallick, R., Vachani, A., and Yendamuri, S. (2017). Whole blood microRNA expression may not be useful for screening non-small cell lung cancer. PLOS ONE, 12(7):e0181926. Accession ID: GSE40738 Link: <a href="https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE40738">https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE40738</a>   Qu2017: Qu, L., Li, L., Zheng, X., Fu, H., Tang, C., Qin, H., Li, X., Wang, H., Li, J., Wang, W., Yang, S., Wang, L., Zhao, G., Lv, P., Lei, Y., Zhang, M., Gao, H., Song, S., and Liu, X. (2017). Circulating plasma microRNAs as potential markers to identify EGFR mutation status and to monitor epidermal growth factor receptor-tyrosine kinase inhibitor treatment in patients with advanced non-small cell lung cancer. Oncotarget, 8(28):45807–45824. Accession ID: GSE93300 Link: <a href="https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE93300">https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE93300</a>   Reis2020: Reis, P. P., Drigo, S. A., Carvalho, R. F., Lopez Lapa, R. M., Felix, T. F., Patel, D., Cheng, D., Pintilie, M., Liu, G., and Tsao, M.-S. (2020). Circulating miR-16-5p, miR-92a-3p, and miR-451a in Plasma from Lung Cancer Patients: Potential Application in Early Detection and a Regulatory Role in Tumorigenesis Pathways. Cancers, 12(8):2071. Accession ID: GSE152702 Link: <a href="https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE152702">https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE152702</a>   Wozniak2015: Wozniak, M. B., Scelo, G., Muller, D. C., Mukeria, A., Zaridze, D., and Brennan, P. (2015). Circulating MicroRNAs as Non-Invasive Biomarkers for Early Detection of Non-Small-Cell Lung Cancer. PLOS ONE, 10(5):e0125026. Accession ID: GSE64591 Link: <a href="https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE64591">https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE64591</a>   Yao2019: Yao, B., Qu, S., Hu, R., Gao, W., Jin, S., Liu, M., and Zhao, Q. (2019). A panel of miRNAs derived from plasma extracellular vesicles as novel diagnostic biomarkers of lung adenocarcinoma. FEBS Open Bio, 9(12):2149–2158. Accession ID: GSE111803 Link: <a href="https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE111803">https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE111803</a>   Zaporozhchenko2018: Zaporozhchenko, I. A., Morozkin, E. S., Ponomaryova, A. A., Rykova, E. Y., Cherdyntseva, N. V., Zheravin, A. A., Pashkovskaya, O. A., Pokushalov, E. A., Vlassov, V. V., and Laktionov, P. P. (2018). Profiling of 179 miRNA Expression in Blood Plasma of Lung Cancer Patients and Cancer-Free Individuals. Scientific Reports, 8(1):6348. Accession ID: E-MTAB-6304 Link: <a href="https://www.ebi.ac.uk/arrayexpress/experiments/E-MTAB-6304/">https://www.ebi.ac.uk/arrayexpress/experiments/E-MTAB-6304/</a>   The Abdollahi2019 and Boeri2011 datasets are not included as I recived them by email and I did not recieve conformation that they were OK with me publishing the datasets.

ShareScore

40/100

Overall dataset sharing score

Score breakdown

These five areas show where the dataset supports — or may limit — practical reuse.

Stewardship: 4
Harmonization: 8
Access: 20
Reuse readiness: 8
Engagement: 0