MicroRNA-449a Plays an Indicative Role in Diagnosing Lung Cancer

MicroRNA-449a Plays an Indicative Role in Diagnosing Lung Cancer | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Primary research MicroRNA -449a Plays an Indicative Role in Diagnosing Lung Cancer Jun Yang, Hua Zhong, Qinghui Yang, Jian Yu, Cailing Jin, Xiaorui Li This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-91596/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background: Lung cancer is one of the most common causes of cancer death among all the malignancies worldwide. Evidences suggest that the incidence and mortality of lung cancer has been on the rise. MicroRNA-449a ( miR-449a ) as one important member of microRNAs, has been demonstrated acting as a tumor suppressor in lung cancer. In this study, we sought to assess the relationship between miR-449a expression level and diagnostic value of lung cancer. Methods: In this present research, quantitative Real-Time PCR was applied to detect the miR-449a expression in 116 lung cancer patients and 41 healthy volunteers. The diagnostic value of miR-449a in lung cancer patients was determined by receiver operating characteristic (ROC) curve. Results: MiR-449a was significantly down-regulated in lung cancer patients compared with healthy control ( P <0.05). In addition, miR-449a expression was associated with sex ( P =0.004), tumor size ( P =0.000), TNM stage ( P =0.006) and metastasis ( P =0.036). However, there was no correlation with age, smoking history and histological type of lung cancer patients (all P ＞0.05). In the ROC analysis, the results showed that the area under the ROC curve (AUC) was 0.902 with the sensitivity of 94.8% and specificity of 78.0%, and the optimum cutoff value was 2.255. Conclusion: MiR-449a expression was down-regulated in lung cancer patients, and it could be an efficient diagnostic biomarker in lung cancer patients. Cancer Biology MiR-449a Diagnose Lung cancer Figures Figure 1 Figure 2 Background Lung cancer is one of the leading causes of cancer related death around the world, and has an increasing incidence and mortality [ 1 ]. There is no obvious clinical symptoms at the early stage of lung cancer, with the evidences suggest that almost 75% of lung cancer patients are already at an advanced stage at the time of diagnosis [ 2 , 3 ]. However, few effective test methods of lung cancer are available so far. Several protein markers, such as carcinoembryonic antigen, cytokeratin 19 fragment, cancer-associated antigen (CA) 125, CA 19-9, neuron-specific enolase, and tissue polypeptide specific antigen have been used to diagnose lung cancer without a surgical procedure , but the sensitivity is limited [ 3 , 4 ]. Therefore, novel sensitive and specific diagnostic biomarkers are needed for the detection of lung cancer. MicroRNAs (miRNAs) are endogenous non-coding RNA molecules of 22 nucleotides in length, which play important roles in regulation of pathological and biological processes [ 5 ]. Cellular miRNAs are released into different body fluids, such as blood [ 6 ]. They are presented in human serum in a highly stable form that is resistant to harsh conditions and RNase digestion [ 7 , 8 ]. It is generally considered that miRNAs target the 3’-untranslated region (3’-UTR) of the targeted mRNAs, causing translation inhibiting or degradation of the mRNA. There are approximately half of miRNA genes are located at genomic regions which frequently amplified or deleted in cancer [ 9-11 ]. Recently studies have found that miRNAs possess regulatory functions in tumorigenesis and closely correlated with tumor differentiation [ 12-15 ]. MicroRNA-449a ( miR-449a ) is one of these miRNAs, which expressed in wide types of cancers, such as ovarian cancer, gastric carcinoma, bladder cancer and lung cancer [ 16-20 ]. Recent evidences suggest that miR-449a performs suppression role in non-small cell lung cancer (NSCLC), which could inhibit tumor cell proliferation and promote tumor cell apoptosis [ 21 ]. However, no related studies have reported the diagnostic value of miR-449a in lung cancer. In this present study, we examined the expression level of miR-449a in lung cancer patients with Quantitative Real-Time PCR (qRT-PCR) method and further evaluated the diagnostic potential of miR-449a for lung cancer patients. Methods Patients and serum specimens’ collection The study was approved by Ethics Committee of the The First Affiliated Hospital of Xinxiang Medical University. All the serum specimens and clinical materials in this research were obtained with the informed consents of all the participants. Serum specimens were obtained from 116 cases with lung cancer and 41 healthy control cases without any malignancy before the study. These serum specimens were collected from patients on the day of diagnosis and before tumor surgery and therapy. All samples taken from lung cancer patients and healthy volunteers were put into blood collection tube of EDTA and stored at -80℃ until RNA extraction. At the same time, clinicopathological features, which including age, sex, smoking history, histological type, tumor size, TNM stage and metastasis were also collected. Plasma preparation and RNA extraction A volume of 5 ml of EDTA-anticoagulated blood was obtained from each participant. Serum was separated by centrifugation. Total RNA, including miRNA, was extracted from the serum using TRIzol reagent (Invitrogen, Carlsbad, CA, USA) according to the manufacturer’s instructions. The RNA with OD A260/A280 ratio closed to 2.0 was subsequently used, which suggested that the RNA were pure. Quantitative Real-Time PCR (qRT-PCR) The RNA was reverse transcribed into cDNA by AMV reverse transcription system (Promega, USA) and stored at -20℃. Quantitative real-time PCR was performed to evaluate the expression level of miR-449a using SYBR Green PCR master mix (Applied Biosystems, USA) by the 7300 Real-Time PCR System (Applied Biosystems, USA). Glyceraldehyde 3-phosphate dehydrogenase (GAPDH) mRNA was used as the endogenous control. Primer sequences were as follow, miR-449a forward: 5’-TGCGGTGGCAGTGTATTGTTAGC-3’, reverse: 5’-CCAGTGCAGGGTCCGAGGT-3’; GAPDH forward: 5’-TGCACCACCAACTGCTTAGC-3’ reverse: 5’-GGCATGCACTGTGGTCATGAG-3’ [ 22 ]. After the reaction, all the data were quantitated with 2 −ΔΔCt method. Statistical analysis Statistical analysis was performed using SPSS 19.0 software. Measurement data were expressed as means ± SD. T-test was used to compare the expression of miR-449a between the lung cancer patients and the healthy group. Chi-square test was used to analyze the differences between miR-449a expression and various clinicopathological characteristics. The diagnostic value of miR-449a in distinguishing lung cancer patients from healthy controls was performed using receiver operating characteristic (ROC) analysis. All tests with P values <0.05 were considered as statistically significant. Results The expression level of miR-449a The present analysis used qRT-PCR to estimate the miR-449a expression level in 116 lung cancer patients and 41 healthy volunteers. The result showed that the expression of miR-449a was significantly reduced in lung cancer patients compared with the healthy controls ( P ＜0.05; Figure 1 ). Relationship between miR-449a and clinicopathological characteristics of lung cancer In this study, we used statistical analysis to explore the relationship between miR-449a expression level and the clinicopathological data of lung cancer patients. In Table 1, the analysis results showed that miR-449a expression was associated with sex ( P=0.004 ), tumor size ( P=0.000 ), TNM stage ( P=0.006 ) and metastasis ( P=0.036 ). However, there was no significant association between miR-449a expression and age, smoking history as well as histological type of lung cancer patients (all P ＞ 0.05 ). Diagnostic value of miR-449a for lung cancer ROC curves were constructed to evaluate the diagnostic value of miR-449a expression level in lung cancer patients. In Figure 2, the ROC curve showed that the lung cancer patients were distinguished from the healthy volunteers with sensitivity of 94.8%, specificity of 78.0% and associated area under the curve (AUC) value of 0.902. The cutoff value for miR-449a expression level is 2.255. This result indicated that the miR-449a expression has efficient diagnostic value for lung cancer. Discussion Lung cancer, as a major death cause, is reported to be with no clinically apparent symptoms until it has reached an advanced stage [ 23 ]. Recently evidences demonstrated that the incidence and mortality of lung cancer has been on the rise [ 9 ]. The development of lung cancer is a complicated process that involves multiple genes, factors and pathways. Although there are several biomarkers for lung cancer such as SCC antigen, carcinoembryonic antigen and pro-gastrin-releasing peotide, none of them are perfect in terms of sensitivity or specificity. Therefore, we sought to find an efficient biomarker to achieve the earlier diagnosis for lung cancer patients. MiRNAs are a class of small noncoding RNAs. There are several researches find that miRNAs are associated with a wide range of cellular processes, such as cellular proliferation, differentiation, apoptosis, and play a critical role in cancer [ 24-26 ]. Recently, miR-449a as a member of miRNAs has been found down-regulated in several types of cancers including prostate cancer, gastric cancer, bladder cancer as well as lung cancer [ 17 , 19 , 27-29 ]. These studies have showed that miR-449a is an important miRNA that has been identified as tumor suppressor, and it plays important roles in the occurrence, development, and prognosis of multiple malignancies. However, the role of miR-449a in the diagnosis of lung cancer still needs to be explored. In our study, we observed that the miR-449a expression level was lower in lung cancer patients than that in healthy volunteers. This finding is consistent with previous reports. For example, Ding et al . demonstrated that the miR-449a expression levels in non-small cell lung cancer are significantly lower than those in the surrounding tissue [ 21 ]. Ren et al . confirmed that miR-449a acts as a tumor suppressor and is mostly down-regulated in lung cancer patients [ 29 ]. In addition, the present study assessed the relationship between miR-449a expression and the clinicalpathological features of lung cancer patients and found that the expression of miR-449a was significantly associated with sex, tumor size, TNM stage and metastasis. However, there were no relation with age, smoking history and histological type of the lung cancer patients. Luo et al. [ 30 ] have proved that low expression level of miR-449a appeared to be correlated with various clinical features such as advanced pathological stage, and lymph node metastasis. What’s more, they also suggested that miR-449a might be a useful prognostic predictor for NSCLC patients. In the present study, we evaluated the diagnostic value of miR-449a in lung cancer patients, and the results of ROC analysis showed that down-regulation of miR-449a might serve as a novel biomarker to diagnose lung cancer. Currently, the molecular mechanisms for the expression of miR-449a in tumors still remain unclear. According to the previous reports, single miRNAs with multiple functions are potential candidates for gene therapy. For example, Noonan et al. [ 28 ] have showed that HDAC1 was a target of miR-449a and miR-449a regulates cell growth and viability in part by repressing the expression of HDAS-1. Moreover, in the study of Jeon HS et al. [ 20 ] showed that the down expression of miR-449a might be one mechanism for over-expression of HDAC1 in lung cancer, and miR-449a could be a potential therapeutic candidate in lung cancer patients. Conclusions In summary, the results provided evidences that miR-449a was significantly down-regulated in lung cancer patients compared with the healthy controls. The ROC curves indicated that the down-regulation of miR-449a could be used as a novel biomarker to distinguish patients with lung cancer from the healthy ones. However, there are still some limitations, for example, the sample size is small and we did not give subdivision of lung cancer. Therefore, more detailed research will be needed in the further studies. List Of Abbreviations MicroRNA-449a (miR-449a) Receiver operating characteristic (ROC) Cancer-associated antigen (CA) MicroRNAs (miRNAs) 3’-untranslated region (3’-UTR) Non-small cell lung cancer (NSCLC) Quantitative Real-Time PCR (qRT-PCR) Area under the curve (AUC) Declarations Ethics approval and consent to participate This study was supported by the Ethics Committee of The First Affiliated Hospital of Xinxiang Medical University and also has been carried out in accordance with the World Medical Association Declaration of Helsinki. The subjects had been informed the objective. Certainly, written consents were signed by every subject in this study. Consent for publication We obtaining permission from participants to publish their data. Availability of data and materials All data generated or analysed during this study are included in this published article. Competing interests The authors declare that they have no competing interests. Funding Not applicable. Authors’ contributions Jun.Y design of the work; H.Z. and X.L. the acquisition, analysis, Q.Y. interpretation of data; Jian.Y. the creation of new software used in the work; C.J. have drafted the work or substantively revised it. All authors read and approved the final manuscript. Acknowledgements Not applicable. References Dillman RO, McClure SE: Steadily improving survival in lung cancer . Clinical lung cancer 2014, 15 (5):331-337. Siegel R, Naishadham D, Jemal A: Cancer statistics, 2012 . CA: a cancer journal for clinicians 2012, 62 (1):10-29. Wang P, Yang D, Zhang H, Wei X, Ma T, Cheng Z, Hong Q, Hu J, Zhuo H, Song Y et al : Early Detection of Lung Cancer in Serum by a Panel of MicroRNA Biomarkers . Clinical lung cancer 2015, 16 (4):313-319 e311. Tarro G, Perna A, Esposito C: Early diagnosis of lung cancer by detection of tumor liberated protein . Journal of cellular physiology 2005, 203 (1):1-5. Hennessey PT, Sanford T, Choudhary A, Mydlarz WW, Brown D, Adai AT, Ochs MF, Ahrendt SA, Mambo E, Califano JA: Serum microRNA biomarkers for detection of non-small cell lung cancer . PloS one 2012, 7 (2):e32307. Weber JA, Baxter DH, Zhang S, Huang DY, Huang KH, Lee MJ, Galas DJ, Wang K: The microRNA spectrum in 12 body fluids . Clinical chemistry 2010, 56 (11):1733-1741. Shen J, Todd NW, Zhang H, Yu L, Lingxiao X, Mei Y, Guarnera M, Liao J, Chou A, Lu CL et al : Plasma microRNAs as potential biomarkers for non-small-cell lung cancer . Laboratory investigation; a journal of technical methods and pathology 2011, 91 (4):579-587. Mitchell PS, Parkin RK, Kroh EM, Fritz BR, Wyman SK, Pogosova-Agadjanyan EL, Peterson A, Noteboom J, O'Briant KC, Allen A et al : Circulating microRNAs as stable blood-based markers for cancer detection . Proceedings of the National Academy of Sciences of the United States of America 2008, 105 (30):10513-10518. Saito M, Schetter AJ, Mollerup S, Kohno T, Skaug V, Bowman ED, Mathe EA, Takenoshita S, Yokota J, Haugen A et al : The association of microRNA expression with prognosis and progression in early-stage, non-small cell lung adenocarcinoma: a retrospective analysis of three cohorts . Clinical cancer research : an official journal of the American Association for Cancer Research 2011, 17 (7):1875-1882. Lin PY, Yang PC: Circulating miRNA signature for early diagnosis of lung cancer . EMBO molecular medicine 2011, 3 (8):436-437. Calin GA, Sevignani C, Dumitru CD, Hyslop T, Noch E, Yendamuri S, Shimizu M, Rattan S, Bullrich F, Negrini M et al : Human microRNA genes are frequently located at fragile sites and genomic regions involved in cancers . Proceedings of the National Academy of Sciences of the United States of America 2004, 101 (9):2999-3004. Lu J, Getz G, Miska EA, Alvarez-Saavedra E, Lamb J, Peck D, Sweet-Cordero A, Ebert BL, Mak RH, Ferrando AA et al : MicroRNA expression profiles classify human cancers . Nature 2005, 435 (7043):834-838. Mishra PJ, Merlino G: MicroRNA reexpression as differentiation therapy in cancer . The Journal of clinical investigation 2009, 119 (8):2119-2123. Schmittgen TD: Regulation of microRNA processing in development, differentiation and cancer . Journal of cellular and molecular medicine 2008, 12 (5B):1811-1819. Tsuchiya S, Okuno Y, Tsujimoto G: MicroRNA: biogenetic and functional mechanisms and involvements in cell differentiation and cancer . Journal of pharmacological sciences 2006, 101 (4):267-270. Li X, Li H, Zhang R, Liu J: MicroRNA-449a inhibits proliferation and induces apoptosis by directly repressing E2F3 in gastric cancer . Cellular physiology and biochemistry : international journal of experimental cellular physiology, biochemistry, and pharmacology 2015, 35 (5):2033-2042. Bou Kheir T, Futoma-Kazmierczak E, Jacobsen A, Krogh A, Bardram L, Hother C, Gronbaek K, Federspiel B, Lund AH, Friis-Hansen L: miR-449 inhibits cell proliferation and is down-regulated in gastric cancer . Molecular cancer 2011, 10 :29. Zhou Y, Chen Q, Qin R, Zhang K, Li H: MicroRNA-449a reduces cell survival and enhances cisplatin-induced cytotoxicity via downregulation of NOTCH1 in ovarian cancer cells . Tumour biology : the journal of the International Society for Oncodevelopmental Biology and Medicine 2014, 35 (12):12369-12378. Chen H, Lin YW, Mao YQ, Wu J, Liu YF, Zheng XY, Xie LP: MicroRNA-449a acts as a tumor suppressor in human bladder cancer through the regulation of pocket proteins . Cancer letters 2012, 320 (1):40-47. Jeon HS, Lee SY, Lee EJ, Yun SC, Cha EJ, Choi E, Na MJ, Park JY, Kang J, Son JW: Combining microRNA-449a/b with a HDAC inhibitor has a synergistic effect on growth arrest in lung cancer . Lung Cancer 2012, 76 (2):171-176. Ding M, Qiu TF, Zhou PG: microRNA-449a suppresses non-small cell lung cancer . Cell biochemistry and biophysics 2015, 71 (2):1255-1259. You J, Zhang Y, Liu B, Li Y, Fang N, Zu L, Li X, Zhou Q: MicroRNA-449a inhibits cell growth in lung cancer and regulates long noncoding RNA nuclear enriched abundant transcript 1 . Indian journal of cancer 2014, 51 Suppl 3 :e77-81. Walker BL, Williamson C, Regis SM, McKee AB, D'Agostino RS, Hesketh PJ, Lamb CR, Flacke S, Wald C, McKee BJ: Surgical Outcomes in a Large, Clinical, Low-Dose Computed Tomographic Lung Cancer Screening Program . The Annals of thoracic surgery 2015, 100 (4):1218-1223. Rehbein G, Schmidt B, Fleischhacker M: Extracellular microRNAs in bronchoalveolar lavage samples from patients with lung diseases as predictors for lung cancer . Clinica chimica acta; international journal of clinical chemistry 2015, 450 :78-82. Banwait JK, Bastola DR: Contribution of bioinformatics prediction in microRNA-based cancer therapeutics . Advanced drug delivery reviews 2015, 81 :94-103. Zhang WC, Liu J, Xu X, Wang G: The role of microRNAs in lung cancer progression . Med Oncol 2013, 30 (3):675. Noonan EJ, Place RF, Basak S, Pookot D, Li LC: miR-449a causes Rb-dependent cell cycle arrest and senescence in prostate cancer cells . Oncotarget 2010, 1 (5):349-358. Noonan EJ, Place RF, Pookot D, Basak S, Whitson JM, Hirata H, Giardina C, Dahiya R: miR-449a targets HDAC-1 and induces growth arrest in prostate cancer . Oncogene 2009, 28 (14):1714-1724. Ren XS, Yin MH, Zhang X, Wang Z, Feng SP, Wang GX, Luo YJ, Liang PZ, Yang XQ, He JX et al : Tumor-suppressive microRNA-449a induces growth arrest and senescence by targeting E2F3 in human lung cancer cells . Cancer letters 2014, 344 (2):195-203. Luo W, Huang B, Li Z, Li H, Sun L, Zhang Q, Qiu X, Wang E: MicroRNA-449a is downregulated in non-small cell lung cancer and inhibits migration and invasion by targeting c-Met . PloS one 2013, 8 (5):e64759. Tables Table 1. The expression of miR-449a and clinicopathological features in lung cancer patients Features No. N=116 MiR-449a expression P values Low (n=76) High (n=40) Age (years) 0.053 <60 64 37 27 ≧60 52 39 13 Sex 0.004 Male 65 50 15 Female 51 26 25 Smoking history 0.390 Yes 32 19 13 No 84 57 27 Tumor size 0.000 <3cm 47 21 26 ≧3cm 69 55 14 Histologic type 0.633 Adenocarcinoma 90 60 30 Squamous carcinoma 8 4 4 Others 18 12 6 TNM stage 0.006 I-II 52 41 11 III-IV 64 35 29 Metastasis 0.036 Yes 73 53 20 No 43 23 20 Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-91596","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Primary research","associatedPublications":[],"authors":[{"id":3420078,"identity":"46309a61-336b-4863-aff9-918e39879961","order_by":0,"name":"Jun Yang","email":"","orcid":"","institution":"The First Affiliated Hospital of Xinxiang Medical University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Jun","middleName":"","lastName":"Yang","suffix":""},{"id":3420079,"identity":"3dd72e0d-455b-41e9-90e7-03ea887cff47","order_by":1,"name":"Hua Zhong","email":"","orcid":"","institution":"The First Affiliated Hospital of Xinxiang Medical University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Hua","middleName":"","lastName":"Zhong","suffix":""},{"id":3420080,"identity":"9706373e-e972-476e-b4d0-cafe80aa64f8","order_by":2,"name":"Qinghui Yang","email":"","orcid":"","institution":"The First Affiliated Hospital of Xinxiang Medical University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Qinghui","middleName":"","lastName":"Yang","suffix":""},{"id":3420081,"identity":"0377c869-2993-4ffd-ae38-3d5ebdcbe6b9","order_by":3,"name":"Jian Yu","email":"","orcid":"","institution":"The First Affiliated Hospital of Xinxiang Medical University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Jian","middleName":"","lastName":"Yu","suffix":""},{"id":3420082,"identity":"65f223ce-157f-4dd8-8d02-7ab8af1e8f7e","order_by":4,"name":"Cailing Jin","email":"","orcid":"","institution":"The First Affiliated Hospital of Xinxiang Medical University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Cailing","middleName":"","lastName":"Jin","suffix":""},{"id":3420083,"identity":"5be657f4-4e11-4419-a95f-0f6de3c7ff96","order_by":5,"name":"Xiaorui Li","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAu0lEQVRIiWNgGAWjYLCCChtmOTb25gMkaDmTxmzMx3MsgTQtifMkchSIUy3vfvbwiwMJ1ultDDkMDD8qthHWYngmL83iQEJ6bhvD2QOMPWduE6FlBo+Z8ccfh3PbGPsSmBnbiNRicCDhcDobM48BcVrkJXiMHwC1JLCxEavFgCfHjAHoF8M2HraEg0T5Rb79jPEHYIjJy89/fPDBjwpibDnAwCYB4xwgrB5kSwMD8weiVI6CUTAKRsHIBQBl3TzGPDn/TgAAAABJRU5ErkJggg==","orcid":"https://orcid.org/0000-0003-2600-5988","institution":"Department of Oncology, The First Affiliated Hospital of Xinxiang Medical University, Xinxiang 453000, Henan, China","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Xiaorui","middleName":"","lastName":"Li","suffix":""}],"badges":[],"createdAt":"2020-10-12 19:09:12","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-91596/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-91596/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":3002414,"identity":"36a0a3ed-d854-488a-a937-5cab416db298","added_by":"auto","created_at":"2020-10-15 15:18:50","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":25101,"visible":true,"origin":"","legend":"Serum miR-449a expression levels was evaluated by qRT-PCR in lung cancer patients (n=116) and healthy controls (n=41) *, P\u003c0.05.","description":"","filename":"Fig1.JPG","url":"https://assets-eu.researchsquare.com/files/rs-91596/v1/1d172cd4b18aa84c929be3f0.JPG"},{"id":3002415,"identity":"dce9bc04-67e1-4e0f-9901-d5e866984d61","added_by":"auto","created_at":"2020-10-15 15:18:50","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":28192,"visible":true,"origin":"","legend":"ROC analysis based on serum miR-449a expression for lung cancer patients. ROC: receiver operating characteristic, AUC: area under the curve.","description":"","filename":"Fig2.JPG","url":"https://assets-eu.researchsquare.com/files/rs-91596/v1/8f97b1870f071d32060ab84b.JPG"},{"id":15669252,"identity":"d8d2b265-27ba-4a68-b267-e9f9ad22477b","added_by":"auto","created_at":"2021-11-18 13:52:22","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":854214,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-91596/v1/f3d96221-9e7a-4ea3-967f-b20dc452961b.pdf"}],"financialInterests":"","formattedTitle":"\u003cp\u003e\u003cem\u003eMicroRNA\u003c/em\u003e-449a Plays an Indicative Role in Diagnosing Lung Cancer\u003c/p\u003e","fulltext":[{"header":"Background","content":"\u003cp\u003eLung cancer is one of the leading causes of cancer related death around the world, and has an increasing incidence and mortality [\u003ca href=\"#_ENREF_1\"\u003e1\u003c/a\u003e]. There is no obvious clinical symptoms at the early stage of lung cancer, with the evidences suggest that almost 75% of lung cancer patients are already at an advanced stage at the time of diagnosis [\u003ca href=\"#_ENREF_2\"\u003e2\u003c/a\u003e, \u003ca href=\"#_ENREF_3\"\u003e3\u003c/a\u003e]. However, few effective test methods of lung cancer are available so far. Several protein markers, such as carcinoembryonic antigen, cytokeratin 19 fragment, cancer-associated antigen (CA) 125, CA 19-9, neuron-specific enolase, and tissue polypeptide specific antigen have been used to diagnose lung cancer without a surgical procedure , but the sensitivity is limited [\u003ca href=\"#_ENREF_3\"\u003e3\u003c/a\u003e, \u003ca href=\"#_ENREF_4\"\u003e4\u003c/a\u003e]. Therefore, novel sensitive and specific diagnostic biomarkers are needed for the detection of lung cancer.\u003c/p\u003e\n\u003cp\u003eMicroRNAs (miRNAs) are endogenous non-coding RNA molecules of 22 nucleotides in length, which play important roles in regulation of pathological and biological processes [\u003ca href=\"#_ENREF_5\"\u003e5\u003c/a\u003e]. Cellular miRNAs are released into different body fluids, such as blood [\u003ca href=\"#_ENREF_6\"\u003e6\u003c/a\u003e]. They are presented in human serum in a highly stable form that is resistant to harsh conditions and RNase digestion [\u003ca href=\"#_ENREF_7\"\u003e7\u003c/a\u003e, \u003ca href=\"#_ENREF_8\"\u003e8\u003c/a\u003e]. It is generally considered that miRNAs target the 3\u0026rsquo;-untranslated region (3\u0026rsquo;-UTR) of the targeted mRNAs, causing translation inhibiting or degradation of the mRNA. There are approximately half of miRNA genes are located at genomic regions which frequently amplified or deleted in cancer [\u003ca href=\"#_ENREF_9\"\u003e9-11\u003c/a\u003e]. Recently studies have found that miRNAs possess regulatory functions in tumorigenesis and closely correlated with tumor differentiation [\u003ca href=\"#_ENREF_12\"\u003e12-15\u003c/a\u003e]. \u003cem\u003eMicroRNA-449a\u003c/em\u003e (\u003cem\u003emiR-449a\u003c/em\u003e) is one of these miRNAs, which expressed in wide types of cancers, such as ovarian cancer, gastric carcinoma, bladder cancer and lung cancer [\u003ca href=\"#_ENREF_16\"\u003e16-20\u003c/a\u003e]. Recent evidences suggest that \u003cem\u003emiR-449a\u003c/em\u003e performs suppression role in non-small cell lung cancer (NSCLC), which could inhibit tumor cell proliferation and promote tumor cell apoptosis [\u003ca href=\"#_ENREF_21\"\u003e21\u003c/a\u003e]. However, no related studies have reported the diagnostic value of \u003cem\u003emiR-449a\u003c/em\u003e in lung cancer.\u003c/p\u003e\n\u003cp\u003eIn this present study, we examined the expression level of \u003cem\u003emiR-449a\u003c/em\u003e in lung cancer patients with Quantitative Real-Time PCR (qRT-PCR) method and further evaluated the diagnostic potential of \u003cem\u003emiR-449a\u003c/em\u003e for lung cancer patients.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cstrong\u003ePatients and serum specimens\u0026rsquo; collection\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study was approved by Ethics Committee of the The First Affiliated Hospital of Xinxiang Medical University. All the serum specimens and clinical materials in this research were obtained with the informed consents of all the participants.\u003c/p\u003e\n\u003cp\u003eSerum specimens were obtained from 116 cases with lung cancer and 41 healthy control cases without any malignancy before the study. These serum specimens were collected from patients on the day of diagnosis and before tumor surgery and therapy. All samples taken from lung cancer patients and healthy volunteers were put into blood collection tube of EDTA and stored at -80℃ until RNA extraction. At the same time, clinicopathological features, which including age, sex, smoking history, histological type, tumor size, TNM stage and metastasis were also collected.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePlasma preparation and RNA extraction\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA volume of 5 ml of EDTA-anticoagulated blood was obtained from each participant. Serum was separated by centrifugation. Total RNA, including miRNA, was extracted from the serum using TRIzol reagent (Invitrogen, Carlsbad, CA, USA) according to the manufacturer\u0026rsquo;s instructions. The RNA with OD A260/A280 ratio closed to 2.0 was subsequently used, which suggested that the RNA were pure.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eQuantitative Real-Time PCR (qRT-PCR)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe RNA was reverse transcribed into cDNA by AMV reverse transcription system (Promega, USA) and stored at -20℃. Quantitative real-time PCR was performed to evaluate the expression level of \u003cem\u003emiR-449a\u003c/em\u003e using SYBR Green PCR master mix (Applied Biosystems, USA) by the 7300 Real-Time PCR System (Applied Biosystems, USA). Glyceraldehyde 3-phosphate dehydrogenase (GAPDH) mRNA was used as the endogenous control. Primer sequences were as follow, \u003cem\u003emiR-449a\u003c/em\u003e forward: 5\u0026rsquo;-TGCGGTGGCAGTGTATTGTTAGC-3\u0026rsquo;, reverse: 5\u0026rsquo;-CCAGTGCAGGGTCCGAGGT-3\u0026rsquo;; GAPDH forward: 5\u0026rsquo;-TGCACCACCAACTGCTTAGC-3\u0026rsquo; reverse: 5\u0026rsquo;-GGCATGCACTGTGGTCATGAG-3\u0026rsquo; [\u003ca href=\"#_ENREF_22\"\u003e22\u003c/a\u003e]. After the reaction, all the data were quantitated with 2\u003csup\u003e\u0026minus;\u0026Delta;\u0026Delta;Ct\u003c/sup\u003e method.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eStatistical analysis was performed using SPSS 19.0 software. Measurement data were expressed as means \u0026plusmn; SD. T-test was used to compare the expression of \u003cem\u003emiR-449a\u003c/em\u003e between the lung cancer patients and the healthy group. Chi-square test was used to analyze the differences between \u003cem\u003emiR-449a\u003c/em\u003e expression and various clinicopathological characteristics. The diagnostic value of \u003cem\u003emiR-449a\u003c/em\u003e in distinguishing lung cancer patients from healthy controls was performed using receiver operating characteristic (ROC) analysis. All tests with \u003cem\u003eP\u003c/em\u003e values \u0026lt;0.05 were considered as statistically significant.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003eThe expression level of miR-449a\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe present analysis used qRT-PCR to estimate the miR-449a expression level in 116 lung cancer patients and 41 healthy volunteers. The result showed that the expression of \u003cem\u003emiR-449a\u003c/em\u003e was significantly reduced in lung cancer patients compared with the healthy controls (\u003cem\u003eP\u003c/em\u003e＜0.05; \u003cstrong\u003eFigure 1\u003c/strong\u003e).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRelationship between miR-449a and clinicopathological characteristics of lung cancer\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn this study, we used statistical analysis to explore the relationship between miR-449a expression level and the clinicopathological data of lung cancer patients. In Table 1, the analysis results showed that miR-449a expression was associated with sex (\u003cem\u003eP=0.004\u003c/em\u003e), tumor size (\u003cem\u003eP=0.000\u003c/em\u003e), TNM stage (\u003cem\u003eP=0.006\u003c/em\u003e) and metastasis (\u003cem\u003eP=0.036\u003c/em\u003e). However, there was no significant association between miR-449a expression and age, smoking history as well as histological type of lung cancer patients (all \u003cem\u003eP\u003c/em\u003e\u003cem\u003e＞\u003c/em\u003e\u003cem\u003e0.05\u003c/em\u003e).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDiagnostic value of miR-449a for lung cancer\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eROC curves were constructed to evaluate the diagnostic value of miR-449a expression level in lung cancer patients. In Figure 2, the ROC curve showed that the lung cancer patients were distinguished from the healthy volunteers with sensitivity of 94.8%, specificity of 78.0% and associated area under the curve (AUC) value of 0.902. The cutoff value for miR-449a expression level is 2.255. This result indicated that the miR-449a expression has efficient diagnostic value for lung cancer.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eLung cancer, as a major death cause, is reported to be with no clinically apparent symptoms until it has reached an advanced stage [\u003ca href=\"#_ENREF_23\"\u003e23\u003c/a\u003e]. Recently evidences demonstrated that the incidence and mortality of lung cancer has been on the rise [\u003ca href=\"#_ENREF_9\"\u003e9\u003c/a\u003e]. The development of lung cancer is a complicated process that involves multiple genes, factors and pathways. Although there are several biomarkers for lung cancer such as SCC antigen, carcinoembryonic antigen and pro-gastrin-releasing peotide, none of them are perfect in terms of sensitivity or specificity. Therefore, we sought to find an efficient biomarker to achieve the earlier diagnosis for lung cancer patients.\u003c/p\u003e\n\u003cp\u003eMiRNAs are a class of small noncoding RNAs. There are several researches find that miRNAs are associated with a wide range of cellular processes, such as cellular proliferation, differentiation, apoptosis, and play a critical role in cancer [\u003ca href=\"#_ENREF_24\"\u003e24-26\u003c/a\u003e]. Recently, \u003cem\u003emiR-449a\u003c/em\u003e as a member of miRNAs has been found down-regulated in several types of cancers including prostate cancer, gastric cancer, bladder cancer as well as lung cancer [\u003ca href=\"#_ENREF_17\"\u003e17\u003c/a\u003e, \u003ca href=\"#_ENREF_19\"\u003e19\u003c/a\u003e, \u003ca href=\"#_ENREF_27\"\u003e27-29\u003c/a\u003e]. These studies have showed that \u003cem\u003emiR-449a\u003c/em\u003e is an important miRNA that has been identified as tumor suppressor, and it plays important roles in the occurrence, development, and prognosis of multiple malignancies. However, the role of \u003cem\u003emiR-449a\u003c/em\u003e in the diagnosis of lung cancer still needs to be explored.\u003c/p\u003e\n\u003cp\u003eIn our study, we observed that the \u003cem\u003emiR-449a\u003c/em\u003e expression level was lower in lung cancer patients than that in healthy volunteers. This finding is consistent with previous reports. For example, Ding\u003cem\u003e et al\u003c/em\u003e. demonstrated that the \u003cem\u003emiR-449a\u003c/em\u003e expression levels in non-small cell lung cancer are significantly lower than those in the surrounding tissue [\u003ca href=\"#_ENREF_21\"\u003e21\u003c/a\u003e]. Ren \u003cem\u003eet al\u003c/em\u003e. confirmed that \u003cem\u003emiR-449a\u003c/em\u003e acts as a tumor suppressor and is mostly down-regulated in lung cancer patients [\u003ca href=\"#_ENREF_29\"\u003e29\u003c/a\u003e]. In addition, the present study assessed the relationship between \u003cem\u003emiR-449a\u003c/em\u003e expression and the clinicalpathological features of lung cancer patients and found that the expression of \u003cem\u003emiR-449a\u003c/em\u003e was significantly associated with sex, tumor size, TNM stage and metastasis. However, there were no relation with age, smoking history and histological type of the lung cancer patients. Luo et al. [\u003ca href=\"#_ENREF_30\"\u003e30\u003c/a\u003e] have proved that low expression level of \u003cem\u003emiR-449a\u003c/em\u003e appeared to be correlated with various clinical features such as advanced pathological stage, and lymph node metastasis. What\u0026rsquo;s more, they also suggested that \u003cem\u003emiR-449a\u003c/em\u003e might be a useful prognostic predictor for NSCLC patients. In the present study, we evaluated the diagnostic value of \u003cem\u003emiR-449a \u003c/em\u003ein lung cancer patients, and the results of ROC analysis showed that down-regulation of \u003cem\u003emiR-449a\u003c/em\u003e might serve as a novel biomarker to diagnose lung cancer.\u003c/p\u003e\n\u003cp\u003eCurrently, the molecular mechanisms for the expression of \u003cem\u003emiR-449a\u003c/em\u003e in tumors still remain unclear. According to the previous reports, single miRNAs with multiple functions are potential candidates for gene therapy. For example, Noonan et al. [\u003ca href=\"#_ENREF_28\"\u003e28\u003c/a\u003e] have showed that HDAC1 was a target of \u003cem\u003emiR-449a\u003c/em\u003e and \u003cem\u003emiR-449a\u003c/em\u003e regulates cell growth and viability in part by repressing the expression of HDAS-1. Moreover, in the study of Jeon HS et al. [\u003ca href=\"#_ENREF_20\"\u003e20\u003c/a\u003e] showed that the down expression of \u003cem\u003emiR-449a\u003c/em\u003e might be one mechanism for over-expression of HDAC1 in lung cancer, and \u003cem\u003emiR-449a\u003c/em\u003e could be a potential therapeutic candidate in lung cancer patients.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eIn summary, the results provided evidences that \u003cem\u003emiR-449a\u003c/em\u003e was significantly down-regulated in lung cancer patients compared with the healthy controls. The ROC curves indicated that the down-regulation of \u003cem\u003emiR-449a\u003c/em\u003e could be used as a novel biomarker to distinguish patients with lung cancer from the healthy ones. However, there are still some limitations, for example, the sample size is small and we did not give subdivision of lung cancer. Therefore, more detailed research will be needed in the further studies.\u003c/p\u003e"},{"header":"List Of Abbreviations","content":"\u003cp\u003eMicroRNA-449a (miR-449a)\u003c/p\u003e\n\u003cp\u003eReceiver operating characteristic (ROC)\u003c/p\u003e\n\u003cp\u003eCancer-associated antigen (CA)\u003c/p\u003e\n\u003cp\u003eMicroRNAs (miRNAs)\u003c/p\u003e\n\u003cp\u003e3\u0026rsquo;-untranslated region (3\u0026rsquo;-UTR)\u003c/p\u003e\n\u003cp\u003eNon-small cell lung cancer (NSCLC)\u003c/p\u003e\n\u003cp\u003eQuantitative Real-Time PCR (qRT-PCR)\u003c/p\u003e\n\u003cp\u003eArea under the curve (AUC)\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was supported by the Ethics Committee of The First Affiliated Hospital of Xinxiang Medical University and also has been carried out in accordance with the World Medical Association Declaration of Helsinki.\u003c/p\u003e\n\u003cp\u003eThe subjects had been informed the objective. Certainly, written consents were signed by every subject in this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe obtaining permission from participants to publish their data.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll data generated or analysed during this study are included in this published article.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eJun.Y design of the work; H.Z. and X.L. the acquisition, analysis, Q.Y. interpretation of data; Jian.Y. the creation of new software used in the work; C.J. have drafted the work or substantively revised it. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eDillman RO, McClure SE: \u003cstrong\u003eSteadily improving survival in lung cancer\u003c/strong\u003e. \u003cem\u003eClinical lung cancer \u003c/em\u003e2014, \u003cstrong\u003e15\u003c/strong\u003e(5):331-337.\u003c/li\u003e\n\u003cli\u003eSiegel R, Naishadham D, Jemal A: \u003cstrong\u003eCancer statistics, 2012\u003c/strong\u003e. \u003cem\u003eCA: a cancer journal for clinicians \u003c/em\u003e2012, \u003cstrong\u003e62\u003c/strong\u003e(1):10-29.\u003c/li\u003e\n\u003cli\u003eWang P, Yang D, Zhang H, Wei X, Ma T, Cheng Z, Hong Q, Hu J, Zhuo H, Song Y\u003cem\u003e et al\u003c/em\u003e: \u003cstrong\u003eEarly Detection of Lung Cancer in Serum by a Panel of MicroRNA Biomarkers\u003c/strong\u003e. \u003cem\u003eClinical lung cancer \u003c/em\u003e2015, \u003cstrong\u003e16\u003c/strong\u003e(4):313-319 e311.\u003c/li\u003e\n\u003cli\u003eTarro G, Perna A, Esposito C: \u003cstrong\u003eEarly diagnosis of lung cancer by detection of tumor liberated protein\u003c/strong\u003e. \u003cem\u003eJournal of cellular physiology \u003c/em\u003e2005, \u003cstrong\u003e203\u003c/strong\u003e(1):1-5.\u003c/li\u003e\n\u003cli\u003eHennessey PT, Sanford T, Choudhary A, Mydlarz WW, Brown D, Adai AT, Ochs MF, Ahrendt SA, Mambo E, Califano JA: \u003cstrong\u003eSerum microRNA biomarkers for detection of non-small cell lung cancer\u003c/strong\u003e. \u003cem\u003ePloS one \u003c/em\u003e2012, \u003cstrong\u003e7\u003c/strong\u003e(2):e32307.\u003c/li\u003e\n\u003cli\u003eWeber JA, Baxter DH, Zhang S, Huang DY, Huang KH, Lee MJ, Galas DJ, Wang K: \u003cstrong\u003eThe microRNA spectrum in 12 body fluids\u003c/strong\u003e. \u003cem\u003eClinical chemistry \u003c/em\u003e2010, \u003cstrong\u003e56\u003c/strong\u003e(11):1733-1741.\u003c/li\u003e\n\u003cli\u003eShen J, Todd NW, Zhang H, Yu L, Lingxiao X, Mei Y, Guarnera M, Liao J, Chou A, Lu CL\u003cem\u003e et al\u003c/em\u003e: \u003cstrong\u003ePlasma microRNAs as potential biomarkers for non-small-cell lung cancer\u003c/strong\u003e. \u003cem\u003eLaboratory investigation; a journal of technical methods and pathology \u003c/em\u003e2011, \u003cstrong\u003e91\u003c/strong\u003e(4):579-587.\u003c/li\u003e\n\u003cli\u003eMitchell PS, Parkin RK, Kroh EM, Fritz BR, Wyman SK, Pogosova-Agadjanyan EL, Peterson A, Noteboom J, O'Briant KC, Allen A\u003cem\u003e et al\u003c/em\u003e: \u003cstrong\u003eCirculating microRNAs as stable blood-based markers for cancer detection\u003c/strong\u003e. \u003cem\u003eProceedings of the National Academy of Sciences of the United States of America \u003c/em\u003e2008, \u003cstrong\u003e105\u003c/strong\u003e(30):10513-10518.\u003c/li\u003e\n\u003cli\u003eSaito M, Schetter AJ, Mollerup S, Kohno T, Skaug V, Bowman ED, Mathe EA, Takenoshita S, Yokota J, Haugen A\u003cem\u003e et al\u003c/em\u003e: \u003cstrong\u003eThe association of microRNA expression with prognosis and progression in early-stage, non-small cell lung adenocarcinoma: a retrospective analysis of three cohorts\u003c/strong\u003e. \u003cem\u003eClinical cancer research : an official journal of the American Association for Cancer Research \u003c/em\u003e2011, \u003cstrong\u003e17\u003c/strong\u003e(7):1875-1882.\u003c/li\u003e\n\u003cli\u003eLin PY, Yang PC: \u003cstrong\u003eCirculating miRNA signature for early diagnosis of lung cancer\u003c/strong\u003e. \u003cem\u003eEMBO molecular medicine \u003c/em\u003e2011, \u003cstrong\u003e3\u003c/strong\u003e(8):436-437.\u003c/li\u003e\n\u003cli\u003eCalin GA, Sevignani C, Dumitru CD, Hyslop T, Noch E, Yendamuri S, Shimizu M, Rattan S, Bullrich F, Negrini M\u003cem\u003e et al\u003c/em\u003e: \u003cstrong\u003eHuman microRNA genes are frequently located at fragile sites and genomic regions involved in cancers\u003c/strong\u003e. \u003cem\u003eProceedings of the National Academy of Sciences of the United States of America \u003c/em\u003e2004, \u003cstrong\u003e101\u003c/strong\u003e(9):2999-3004.\u003c/li\u003e\n\u003cli\u003eLu J, Getz G, Miska EA, Alvarez-Saavedra E, Lamb J, Peck D, Sweet-Cordero A, Ebert BL, Mak RH, Ferrando AA\u003cem\u003e et al\u003c/em\u003e: \u003cstrong\u003eMicroRNA expression profiles classify human cancers\u003c/strong\u003e. \u003cem\u003eNature \u003c/em\u003e2005, \u003cstrong\u003e435\u003c/strong\u003e(7043):834-838.\u003c/li\u003e\n\u003cli\u003eMishra PJ, Merlino G: \u003cstrong\u003eMicroRNA reexpression as differentiation therapy in cancer\u003c/strong\u003e. \u003cem\u003eThe Journal of clinical investigation \u003c/em\u003e2009, \u003cstrong\u003e119\u003c/strong\u003e(8):2119-2123.\u003c/li\u003e\n\u003cli\u003eSchmittgen TD: \u003cstrong\u003eRegulation of microRNA processing in development, differentiation and cancer\u003c/strong\u003e. \u003cem\u003eJournal of cellular and molecular medicine \u003c/em\u003e2008, \u003cstrong\u003e12\u003c/strong\u003e(5B):1811-1819.\u003c/li\u003e\n\u003cli\u003eTsuchiya S, Okuno Y, Tsujimoto G: \u003cstrong\u003eMicroRNA: biogenetic and functional mechanisms and involvements in cell differentiation and cancer\u003c/strong\u003e. \u003cem\u003eJournal of pharmacological sciences \u003c/em\u003e2006, \u003cstrong\u003e101\u003c/strong\u003e(4):267-270.\u003c/li\u003e\n\u003cli\u003eLi X, Li H, Zhang R, Liu J: \u003cstrong\u003eMicroRNA-449a inhibits proliferation and induces apoptosis by directly repressing E2F3 in gastric cancer\u003c/strong\u003e. \u003cem\u003eCellular physiology and biochemistry : international journal of experimental cellular physiology, biochemistry, and pharmacology \u003c/em\u003e2015, \u003cstrong\u003e35\u003c/strong\u003e(5):2033-2042.\u003c/li\u003e\n\u003cli\u003eBou Kheir T, Futoma-Kazmierczak E, Jacobsen A, Krogh A, Bardram L, Hother C, Gronbaek K, Federspiel B, Lund AH, Friis-Hansen L: \u003cstrong\u003emiR-449 inhibits cell proliferation and is down-regulated in gastric cancer\u003c/strong\u003e. \u003cem\u003eMolecular cancer \u003c/em\u003e2011, \u003cstrong\u003e10\u003c/strong\u003e:29.\u003c/li\u003e\n\u003cli\u003eZhou Y, Chen Q, Qin R, Zhang K, Li H: \u003cstrong\u003eMicroRNA-449a reduces cell survival and enhances cisplatin-induced cytotoxicity via downregulation of NOTCH1 in ovarian cancer cells\u003c/strong\u003e. \u003cem\u003eTumour biology : the journal of the International Society for Oncodevelopmental Biology and Medicine \u003c/em\u003e2014, \u003cstrong\u003e35\u003c/strong\u003e(12):12369-12378.\u003c/li\u003e\n\u003cli\u003eChen H, Lin YW, Mao YQ, Wu J, Liu YF, Zheng XY, Xie LP: \u003cstrong\u003eMicroRNA-449a acts as a tumor suppressor in human bladder cancer through the regulation of pocket proteins\u003c/strong\u003e. \u003cem\u003eCancer letters \u003c/em\u003e2012, \u003cstrong\u003e320\u003c/strong\u003e(1):40-47.\u003c/li\u003e\n\u003cli\u003eJeon HS, Lee SY, Lee EJ, Yun SC, Cha EJ, Choi E, Na MJ, Park JY, Kang J, Son JW: \u003cstrong\u003eCombining microRNA-449a/b with a HDAC inhibitor has a synergistic effect on growth arrest in lung cancer\u003c/strong\u003e. \u003cem\u003eLung Cancer \u003c/em\u003e2012, \u003cstrong\u003e76\u003c/strong\u003e(2):171-176.\u003c/li\u003e\n\u003cli\u003eDing M, Qiu TF, Zhou PG: \u003cstrong\u003emicroRNA-449a suppresses non-small cell lung cancer\u003c/strong\u003e. \u003cem\u003eCell biochemistry and biophysics \u003c/em\u003e2015, \u003cstrong\u003e71\u003c/strong\u003e(2):1255-1259.\u003c/li\u003e\n\u003cli\u003eYou J, Zhang Y, Liu B, Li Y, Fang N, Zu L, Li X, Zhou Q: \u003cstrong\u003eMicroRNA-449a inhibits cell growth in lung cancer and regulates long noncoding RNA nuclear enriched abundant transcript 1\u003c/strong\u003e. \u003cem\u003eIndian journal of cancer \u003c/em\u003e2014, \u003cstrong\u003e51 Suppl 3\u003c/strong\u003e:e77-81.\u003c/li\u003e\n\u003cli\u003eWalker BL, Williamson C, Regis SM, McKee AB, D'Agostino RS, Hesketh PJ, Lamb CR, Flacke S, Wald C, McKee BJ: \u003cstrong\u003eSurgical Outcomes in a Large, Clinical, Low-Dose Computed Tomographic Lung Cancer Screening Program\u003c/strong\u003e. \u003cem\u003eThe Annals of thoracic surgery \u003c/em\u003e2015, \u003cstrong\u003e100\u003c/strong\u003e(4):1218-1223.\u003c/li\u003e\n\u003cli\u003eRehbein G, Schmidt B, Fleischhacker M: \u003cstrong\u003eExtracellular microRNAs in bronchoalveolar lavage samples from patients with lung diseases as predictors for lung cancer\u003c/strong\u003e. \u003cem\u003eClinica chimica acta; international journal of clinical chemistry \u003c/em\u003e2015, \u003cstrong\u003e450\u003c/strong\u003e:78-82.\u003c/li\u003e\n\u003cli\u003eBanwait JK, Bastola DR: \u003cstrong\u003eContribution of bioinformatics prediction in microRNA-based cancer therapeutics\u003c/strong\u003e. \u003cem\u003eAdvanced drug delivery reviews \u003c/em\u003e2015, \u003cstrong\u003e81\u003c/strong\u003e:94-103.\u003c/li\u003e\n\u003cli\u003eZhang WC, Liu J, Xu X, Wang G: \u003cstrong\u003eThe role of microRNAs in lung cancer progression\u003c/strong\u003e. \u003cem\u003eMed Oncol \u003c/em\u003e2013, \u003cstrong\u003e30\u003c/strong\u003e(3):675.\u003c/li\u003e\n\u003cli\u003eNoonan EJ, Place RF, Basak S, Pookot D, Li LC: \u003cstrong\u003emiR-449a causes Rb-dependent cell cycle arrest and senescence in prostate cancer cells\u003c/strong\u003e. \u003cem\u003eOncotarget \u003c/em\u003e2010, \u003cstrong\u003e1\u003c/strong\u003e(5):349-358.\u003c/li\u003e\n\u003cli\u003eNoonan EJ, Place RF, Pookot D, Basak S, Whitson JM, Hirata H, Giardina C, Dahiya R: \u003cstrong\u003emiR-449a targets HDAC-1 and induces growth arrest in prostate cancer\u003c/strong\u003e. \u003cem\u003eOncogene \u003c/em\u003e2009, \u003cstrong\u003e28\u003c/strong\u003e(14):1714-1724.\u003c/li\u003e\n\u003cli\u003eRen XS, Yin MH, Zhang X, Wang Z, Feng SP, Wang GX, Luo YJ, Liang PZ, Yang XQ, He JX\u003cem\u003e et al\u003c/em\u003e: \u003cstrong\u003eTumor-suppressive microRNA-449a induces growth arrest and senescence by targeting E2F3 in human lung cancer cells\u003c/strong\u003e. \u003cem\u003eCancer letters \u003c/em\u003e2014, \u003cstrong\u003e344\u003c/strong\u003e(2):195-203.\u003c/li\u003e\n\u003cli\u003eLuo W, Huang B, Li Z, Li H, Sun L, Zhang Q, Qiu X, Wang E: \u003cstrong\u003eMicroRNA-449a is downregulated in non-small cell lung cancer and inhibits migration and invasion by targeting c-Met\u003c/strong\u003e. \u003cem\u003ePloS one \u003c/em\u003e2013, \u003cstrong\u003e8\u003c/strong\u003e(5):e64759.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003e\u003cstrong\u003eTable 1.\u003c/strong\u003e The expression of \u003cem\u003emiR-449a\u003c/em\u003e and clinicopathological features in lung cancer patients\u003c/p\u003e\n\u003ctable border=\"1\"\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd rowspan=\"2\" width=\"159\"\u003e\n\u003cp\u003eFeatures\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"2\" width=\"104\"\u003e\n\u003cp\u003eNo.\u003c/p\u003e\n\u003cp\u003eN=116\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" width=\"263\"\u003e\n\u003cp\u003e\u003cem\u003eMiR-449a\u003c/em\u003e expression\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"2\" width=\"131\"\u003e\n\u003cp\u003e\u003cem\u003eP\u003c/em\u003e values\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"131\"\u003e\n\u003cp\u003eLow (n=76)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"131\"\u003e\n\u003cp\u003eHigh (n=40)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"159\"\u003e\n\u003cp\u003eAge (years)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"104\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"131\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"131\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"3\" width=\"131\"\u003e\n\u003cp\u003e0.053\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"159\"\u003e\n\u003cp\u003e\u0026lt;60\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"104\"\u003e\n\u003cp\u003e64\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"131\"\u003e\n\u003cp\u003e37\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"131\"\u003e\n\u003cp\u003e27\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"159\"\u003e\n\u003cp\u003e≧60\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"104\"\u003e\n\u003cp\u003e52\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"131\"\u003e\n\u003cp\u003e39\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"131\"\u003e\n\u003cp\u003e13\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"159\"\u003e\n\u003cp\u003eSex\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"104\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"131\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"131\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"3\" width=\"131\"\u003e\n\u003cp\u003e0.004\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"159\"\u003e\n\u003cp\u003eMale\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"104\"\u003e\n\u003cp\u003e65\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"131\"\u003e\n\u003cp\u003e50\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"131\"\u003e\n\u003cp\u003e15\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"159\"\u003e\n\u003cp\u003eFemale\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"104\"\u003e\n\u003cp\u003e51\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"131\"\u003e\n\u003cp\u003e26\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"131\"\u003e\n\u003cp\u003e25\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"159\"\u003e\n\u003cp\u003eSmoking history\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"104\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"131\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"131\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"3\" width=\"131\"\u003e\n\u003cp\u003e0.390\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"159\"\u003e\n\u003cp\u003eYes\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"104\"\u003e\n\u003cp\u003e32\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"131\"\u003e\n\u003cp\u003e19\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"131\"\u003e\n\u003cp\u003e13\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"159\"\u003e\n\u003cp\u003eNo\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"104\"\u003e\n\u003cp\u003e84\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"131\"\u003e\n\u003cp\u003e57\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"131\"\u003e\n\u003cp\u003e27\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"159\"\u003e\n\u003cp\u003eTumor size\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"104\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"131\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"131\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"3\" width=\"131\"\u003e\n\u003cp\u003e0.000\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"159\"\u003e\n\u003cp\u003e\u0026lt;3cm\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"104\"\u003e\n\u003cp\u003e47\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"131\"\u003e\n\u003cp\u003e21\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"131\"\u003e\n\u003cp\u003e26\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"159\"\u003e\n\u003cp\u003e≧3cm\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"104\"\u003e\n\u003cp\u003e69\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"131\"\u003e\n\u003cp\u003e55\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"131\"\u003e\n\u003cp\u003e14\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"159\"\u003e\n\u003cp\u003eHistologic type\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"104\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"131\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"131\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"4\" width=\"131\"\u003e\n\u003cp\u003e0.633\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"159\"\u003e\n\u003cp\u003eAdenocarcinoma\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"104\"\u003e\n\u003cp\u003e90\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"131\"\u003e\n\u003cp\u003e60\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"131\"\u003e\n\u003cp\u003e30\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"159\"\u003e\n\u003cp\u003eSquamous carcinoma\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"104\"\u003e\n\u003cp\u003e8\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"131\"\u003e\n\u003cp\u003e4\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"131\"\u003e\n\u003cp\u003e4\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"159\"\u003e\n\u003cp\u003eOthers\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"104\"\u003e\n\u003cp\u003e18\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"131\"\u003e\n\u003cp\u003e12\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"131\"\u003e\n\u003cp\u003e6\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"159\"\u003e\n\u003cp\u003eTNM stage\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"104\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"131\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"131\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"3\" width=\"131\"\u003e\n\u003cp\u003e0.006\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"159\"\u003e\n\u003cp\u003eI-II\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"104\"\u003e\n\u003cp\u003e52\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"131\"\u003e\n\u003cp\u003e41\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"131\"\u003e\n\u003cp\u003e11\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"159\"\u003e\n\u003cp\u003eIII-IV\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"104\"\u003e\n\u003cp\u003e64\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"131\"\u003e\n\u003cp\u003e35\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"131\"\u003e\n\u003cp\u003e29\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"159\"\u003e\n\u003cp\u003eMetastasis\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"104\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"131\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"131\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"3\" width=\"131\"\u003e\n\u003cp\u003e0.036\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"159\"\u003e\n\u003cp\u003eYes\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"104\"\u003e\n\u003cp\u003e73\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"131\"\u003e\n\u003cp\u003e53\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"131\"\u003e\n\u003cp\u003e20\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"159\"\u003e\n\u003cp\u003eNo\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"104\"\u003e\n\u003cp\u003e43\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"131\"\u003e\n\u003cp\u003e23\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"131\"\u003e\n\u003cp\u003e20\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"MiR-449a, Diagnose, Lung cancer","lastPublishedDoi":"10.21203/rs.3.rs-91596/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-91596/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground: \u003c/strong\u003eLung cancer is one of the most common causes of cancer death among all the malignancies worldwide. Evidences suggest that the incidence and mortality of lung cancer has been on the rise. \u003cem\u003eMicroRNA-449a\u003c/em\u003e (\u003cem\u003emiR-449a\u003c/em\u003e) as one important member of microRNAs, has been demonstrated acting as a tumor suppressor in lung cancer. In this study, we sought to assess the relationship between \u003cem\u003emiR-449a\u003c/em\u003e expression level and diagnostic value of lung cancer.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e In this present research, quantitative Real-Time PCR was applied to detect the \u003cem\u003emiR-449a\u003c/em\u003e expression in 116 lung cancer patients and 41 healthy volunteers. The diagnostic value of \u003cem\u003emiR-449a\u003c/em\u003e in lung cancer patients was determined by receiver operating characteristic (ROC) curve.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eResults: \u003c/strong\u003e\u003cem\u003eMiR-449a\u003c/em\u003e was significantly down-regulated in lung cancer patients compared with healthy control (\u003cem\u003eP\u003c/em\u003e\u0026lt;0.05). In addition, \u003cem\u003emiR-449a\u003c/em\u003e expression was associated with sex (\u003cem\u003eP\u003c/em\u003e=0.004), tumor size (\u003cem\u003eP\u003c/em\u003e=0.000), TNM stage (\u003cem\u003eP\u003c/em\u003e=0.006) and metastasis (\u003cem\u003eP\u003c/em\u003e=0.036). However, there was no correlation with age, smoking history and histological type of lung cancer patients (all \u003cem\u003eP\u003c/em\u003e＞0.05). In the ROC analysis, the results showed that the area under the ROC curve (AUC) was 0.902 with the sensitivity of 94.8% and specificity of 78.0%, and the optimum cutoff value was 2.255.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eConclusion: \u003c/strong\u003e\u003cem\u003eMiR-449a\u003c/em\u003e expression was down-regulated in lung cancer patients, and it could be an efficient diagnostic biomarker in lung cancer patients.\u003c/p\u003e","manuscriptTitle":"MicroRNA-449a Plays an Indicative Role in Diagnosing Lung Cancer","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2020-10-15 15:18:49","doi":"10.21203/rs.3.rs-91596/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"d3d4feb5-b0a9-4a3e-994e-0e85ce9aba66","owner":[],"postedDate":"October 15th, 2020","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":791424,"name":"Cancer Biology"}],"tags":[],"updatedAt":"2020-10-15T15:18:50+00:00","versionOfRecord":[],"versionCreatedAt":"2020-10-15 15:18:49","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-91596","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-91596","identity":"rs-91596","version":["v1"]},"buildId":"7rjqhiLT3MXkJMwkYKINL","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}