Pan-cancer analysis identifies AL365181.3 as a novel prognostic biomarker for lung adenocarcinoma

Pan-cancer analysis identifies AL365181.3 as a novel prognostic biomarker for lung adenocarcinoma | 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 Research Article Pan-cancer analysis identifies AL365181.3 as a novel prognostic biomarker for lung adenocarcinoma Xiaoying Liu, Jinlong Liu, Yingou Zeng, Di Qiao, Qiang Wang This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4019953/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 As a lncRNA, AL365181.3 is aberrantly expressed in multiple cancer types, including lung adenocarcinoma (LUAD). However, the biological process underlying the ability of AL365181.3 to promote the progression of LUAD is unclear. Here, the pancancer expression level of AL365181.3 was analyzed using the TCGA and GTEx databases, as well as its clinical characteristics and prognostic value. Finally, the in vitro and in vivo biological functions of AL365181.3 in LUAD were revealed by using various functional assays. We found that AL365181.3 was significantly more highly expressed in many types of cancer tissues, including LUAD tissues, than in adjacent normal tissues. LUAD patients with high AL365181.3 expression had poor prognoses. Functional enrichment analyses indicated that AL365181.3 is involved in the regulation of metabolism, MAPK signaling and other tumor regulatory signaling pathways.Finally, we found that knockdown of AL365181.3 reduced the proliferation and migratory capacity of LUAD cells, and knockdown of AL365181.3 resulted in a reduced in vivo tumorigenic capacity of LUAD cells. These findings provide a comprehensive understanding of the role of AL365181.3 in LUAD. AL365181.3 LUAD prognostic marker proliferation migration Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Introduction Lung cancer is a leading cause of cancer-related mortality worldwide[ 1 ], and its incidence and mortality rates have been increasing annually. Lung cancer has an insidious onset, and most lung cancer patients have already developed distant metastases by the time of diagnosis, limiting the typical 5-year survival rate of individuals with lung cancer to no more than 25%[ 2 ]. Among these subtypes, lung adenocarcinoma (LUAD) is the most common molecular subtype of non-small cell lung cancer (NSCLC), and its proportion of NSCLC is gradually increasing to almost 50% of lung cancers[ 3 ]. Although considerable progress has been made in the past several decades in various treatments for lung cancer[ 4 ], the morbidity and mortality of LUAD remain high[ 5 ]. Hence, there is an immediate need for more effective markers for LUAD prevention and therapeutic targets for improved diagnosis and treatment. A kind of noncoding RNA molecule longer than 200 nucleotides that does not have an open reading frame to encode proteins is known as a long noncoding RNA (lncRNA)[ 6 ], and these molecules play a critical regulatory role in the development of cancers[ 7 ]. The rich variety of lncRNAs, their spatial and temporal specific expression and diverse regulatory mechanisms make them unique diagnostic and prognostic markers and molecular targets. Recent studies on the functions, mechanisms of action and clinical significance of lncRNAs in various tumors are increasing annually. LncRNAs have been demonstrated to be involved in the regulation of tumor cell proliferation, apoptosis, cell cycle progression, invasion, metastasis, tumor stem cell stemness maintenance, the tumor microenvironment and metabolism and play important roles in tumor development and resistance to radiotherapy[ 8 – 11 ]. Recent studies have identified a series of lncRNAs, such as iron death-associated lncRNAs[ 12 , 13 ], scorch death-associated lncRNAs[ 14 , 15 ] and methylation-driven lncRNAs, as prognostic markers for LUAD[ 16 ]. These studies suggest that lncRNAs not only are potential biomarkers for the clinical treatment of LUAD but are also expected to be targets for molecularly targeted therapies in LUAD, with important clinical translational value. Consequently, the study of the mechanism of lncRNA-related molecules has become a hotspot of research in the field of oncology. In this investigation, we integrated and analyzed the transcriptome sequencing data of the TCGA cohort and successfully identified many new DEGs, and the lncRNA AL365181.3 was one of these DEGs. However, the possible role and therapeutic value of AL365181.3 in LUAD are unclear. In the present investigation, we showed that in patients with LUAD, abnormal expression of AL365181.3 was linked to a poor clinical outcome. Moreover, we mined TCGA data to identify the downstream targets of AL365181.3 and to determine the potential regulatory signaling pathways involved in LUAD. Finally, CCK8, colony formation, wound healing and Transwell assays were used to confirm the biological function of AL365181.3 in LUAD progression. In conclusion, our findings suggest a potential role for AL365181.3 in regulating tumor development and in the diagnostic assessment of LUAD. Materials and methods Analysis of clinical information, prognosis, and expression status The tumor AL365181.3 expression, prognosis, and clinical information were analyzed using the following databases: TCGA, Kaplan‒Meier plotter[ 17 ], and GEPIA[ 18 ]. Receiver operating characteristic (ROC) curve analysis We utilized the pROC function from the R package to determine the area under the curve (AUC) of the receiver operating characteristic (ROC) curves produced by screening signature genes. Cell culture conditions Purchased from the Chinese Academy of Sciences Cell Bank, H1299 and A549 cells were grown in RPMI 1640 media supplemented with 10% fetal bovine serum (FBS) and 1% penicillin/streptomycin at 37°C and 5% CO 2 . Transfection In 6-well plates, the cells were incubated with serum-free medium, which was changed at 70% confluence. siRNA and the transfection reagent LipofectamineTM 3000 were mixed at the recommended ratios, the transfection complex was usually added dropwise to the 6-well plates, and the dishes were gently shaken to ensure homogeneous mixing; after 4–6 h, the complete medium was replaced. After 24–48 hours, subsequent experiments were carried out. The siRNAs for AL365181.3-1 (si-AL365181.3-1#1: 5’- GCAAGAGAAUUGAAGGUUAGACUAC-3’; si-AL365181.3-1#2: 5’- CUAAUAGUUACUGAUGUCUACCUGA-3’) were synthesized by Gene Pharma (Shanghai, China). qRT‒PCR Total RNA was extracted using TRIzol reagent. cDNA was subsequently reverse transcribed. We performed the amplification reaction according to the instructions provided in the Green qPCR Supermix on top of the trans starter. In addition, we quantified mRNA expression using the 2 −ΔΔCt method. The following are primer sequences: q-AL365181.3-F: AGGTCTCTCTCTCTCTCT, q-AL365181.3-R: CCCTAAGGCCCTGCTTATATTG; q-18S-F: CTTCGGGGCTTCGGGG; and q-18S-R: CATAGGAATCCTTCTGACC. CCK8, colony formation assay Cell viability and growth were measured in 96-well plates with a CCK8 assay. Sample cells were inoculated in 96-well plates and incubated with CCK8 solution at a fixed time point for 1 h. The absorbance was measured at 450 nm with a spectrophotometer. For the colony formation experiments, the cells were inoculated in 6-well plates and cultured for 10 to 14 days. The solidified cells were stained and then photographed. Apoptosis analysis A FITC Annexin V Apoptosis Detection Kit I was used to detect apoptosis. After being disrupted by EDTA-free trypsin and rinsed with ice-cold PBS, the cells were incubated with PI and Alexa Fluor 488 annexin V for 15 minutes. Afterward, the cells were examined using a NovoCyte flow cytometer. Wound healing assay A monolayer of cells was scratched along a straight line to form a wound. To determine the gap width, the isolated cells were cleaned with PBS, and images of the scratches were taken at predetermined intervals. Transwell migration and invasion assays In transwell experiments, 5×104 cells were inoculated in the upper chamber of a small chamber containing serum-free medium, and medium containing 15% FBS was added to the lower chamber. Cells that crossed the membrane of the chambers were counted after 24 h of incubation. Xenograft model studies Female BALB/c nude mice aged 4 weeks were obtained from GemPharmatech Technology (Jiangsu, China). A total of 4 × 10 6 A549 cells were injected into the left flank of each mouse. Six injections of either si-NC or siRNA (20 nmol) were given to eight mice at intervals of three days using 0.1 mL of saline buffer. Xenograft models were split into two groups (n = 4) after fifteen days, when the tumors had grown to a size of approximately 5 mm by 5 mm. After being anesthetized with isoflurane, the tumor-bearing mice were sacrificed via cervical dislocation on day 30. The tumors from the xenografts were removed, weighed, and imaged with a camera. IHC Following the methods described earlier, immunohistochemistry (IHC) was performed [ 19 ]. For an overnight incubation at 4°C, primary antibodies against Ki67 (sc-23900, Santa Cruz) were applied to the xenograft sections of nude mice. The secondary antibody was then administered. Statistical analysis The two sets of data were compared for significance using Student’s t test. A P value less than 0.05 was considered to indicate statistical significance. *P < 0.05; **P < 0.01; ***P < 0.001. Results Molecular characteristics analysis According to the lnCAR database, AL365181.3 is an intronless transcript of 3222 nucleotides (nt)[20]. Figure S1A shows the genomic information for AL365181.3. AL365181.3 is located at chr1:156641666.156644887. According to the online database, AL365181.3 did not exhibit coding potential (Fig. S1B-C). Furthermore, we found that LUAD cells contain AL365181.3, which is located primarily in the cytoplasm (Fig. S1D). The expression of AL365181.3 varies in human tumors To validate the involvement of AL365181.3 in regulating human tumor development, we verified the RNA expression pattern of AL365181.3 in a variety of cancers and showed that the expression level of AL365181.3 varied greatly among different tumors, with AL365181.3 RNA being significantly highly expressed in 15 cancers in the TCGA database (Fig. 1A). We also confirmed that AL365181.3 was highly expressed in 13 paired adjacent normal tissues (Fig. 1B). These findings suggest that AL365181.3 can play a procancer role in different types of tumors. Prognostic value of AL365181.3 in human tumors AL365181.3 expression differs among different types of cancer, so its prognostic value in human cancer was investigated. We found that the expression level of AL365181.3 was related to the overall survival (OS) time of patients with four kinds of tumors (Figure 2A), disease-specific survival (DSS) of patients with 4 kinds of tumors (Figure 2B) and progression-free interval (PFI) of patients with 8 kinds of tumors (Figure 2C). ROC curve analysis of AL365181.3 in human tumors We investigated whether AL365181.3 can serve as a biomarker for human tumors. According to the ROC curve analysis, AL365181.3 could be used to diagnose 20 types of tumors with high sensitivity and specificity (AUC > 0.75) (Fig. S2A-E). AL365181.3 is highly expressed in LUAD tissues and is correlated with adverse clinical parameters in LUAD patients Using AL365181.3 expression data from TCGA, we examined AL365181.3 expression in LUAD, and we found that AL365181.3 was more highly expressed in LUAD (Fig. 3A-B). Moreover, Gene Expression Omnibus (GEO) data provided similar results (Fig. 3C-D). We also examined the clinical relevance of AL365181.3 in LUAD using the TCGA LUAD dataset. The pathological stage and TNM stage were significantly correlated with AL365181.3 expression (Fig. 3E-H, Table 1). Importantly, in LUAD patients with many clinical features, including TNM stage, pathological stage, residual tumor, cancer location, anatomic neoplasm subdivision, age, smoking status, and number of peak years smoked, those with high AL365181.3 expression had significantly worse OS (Fig. 3I-R). A nomogram was also constructed using the TCGA-LUAD cohort to predict OS, DSS, and the PFI. The prognostic indicators in the nomogram included AL365181.3 expression and pathological stage (Fig. 4A–C). LUAD OS, DSS, and the PFI were reliably predicted by the nomogram based on calibration curves (Figure 4D–F). In conclusion, AL365181.3 can be used as a sensitive diagnostic indicator and can be used as a promising biomarker for LUAD. Analysis of the AL365181.3-related signaling pathways in LUAD Using the “clusterProfiler” R package, we performed functional annotation of the AL365181.3-associated differentially expressed genes (DEGs) in LUAD patients to elucidate the mechanism of the effect of AL365181.3, and 418 DEGs (mRNAs and lncRNAs) were identified with threshold values of |log2-fold change (FC)|>2 and adjusted p value < 0.05; these genes included 29 upregulated and 282 downregulated lncRNAs and 71 upregulated and 36 downregulated mRNAs (Fig. S3A–B). The KEGG enrichment results showed that the DEGs were involved mainly in pentose and glucuronate interconversions, steroid hormone biosynthesis, ascorbate and aldarate metabolism, drug metabolism-cytochrome P450, and metabolism of xenobiotics by cytochrome P450 (Fig. S3C). Next, we performed Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis of the GEO dataset. The results revealed that AL365181.3 is involved in the regulation of metabolic metabolism, MAPK signaling and other tumor regulatory signaling pathways (Fig. S3D-E). GSEA indicated that AL365181.3 was involved mainly in arginine and proline metabolism, phenylalanine metabolism and other pathways, other enzymes involved in drug metabolism, fructose and mannose metabolism, glycosaminoglycan degradation, the pentose phosphate pathway, the metabolism of cytochromes to xenobiotics, linoleic acid metabolism, the pentose phosphate pathway, nicotinic acid and nicotinamide metabolism, phenylalanine metabolism, retinol metabolism, ascorbic and aldehyde metabolism, and steroid hormone biosynthesis and tyrosine metabolism (Fig. 5). The enrichment of hallmark genes indicated the following: early estrogen response, late estrogen response, glycolysis, heme metabolism, reactive oxygen species pathway, xenobiotic metabolism, and pancreatic beta cells (Fig. 6). These findings strongly demonstrated that AL365181.3 is involved mainly in the regulation of LUAD metabolism-related pathways. AL365181.3 knockdown inhibits the proliferation of LUAD cells in vitro The above results suggest that AL365181.3 expression is significantly upregulated in LUAD tissues and that AL365181.3 may affect the progression of LUAD. To investigate the biological function of AL365181.3 in LUAD, two siRNA sequences targeting AL365181.3, named siRNA-AL365181.3#1 and siRNA-AL365181.3#2, were designed and synthesized, and random nonsense siRNA sequences were selected as negative controls. The target cells were transfected separately by RNAi, and the knockdown efficiency of the transfected cell lines was examined via qRT‒PCR analysis (Fig. 7A). CCK8 and cell colony formation assays confirmed that in both A549 and H1299 cells, AL365181.3 knockdown reduced the proliferative capacity (Fig. 7B-C). In addition, knocking down AL365181.3 enhanced LUAD cell apoptosis (Fig. 7D). AL365181.3 knockdown inhibits the migration and invasion of LUAD cells The effect of AL365181.3 on the metastasis of LUAD cells was subsequently confirmed. Transwell and wound healing assays demonstrated that cell migration was markedly inhibited by downregulation of AL365181.3 expression (Fig. 7E-F). In conclusion, these results demonstrated that AL365181.3 has an essential function in regulating the migratory capacity of LUAD cells. AL365181.3 knockdown inhibits LUAD cell xenograft tumor growth Using a xenograft tumor model, we examined the effect of AL365181.3 on LUAF in vivo. Beginning on day 15, the mice were injected with NC or AL365181.3 siRNA every three days, and on day 30, they were euthanized. Compared to those of the NC cells, the tumors of the A549 cells grown with lower AL365181.3 concentrations grew at a significantly slower rate (Fig. 8A-C). Compared with those in the NC group, the weights of the si-AL365181.3#2-treated xenograft tumors were lower (Fig. 8D). qPCR revealed that AL365181.3 levels were significantly lower in si-AL365181.3-injected xenograft tumors than in control tumors (Fig. 8E). Compared with those in the NC group, the injection of si-AL365181.3#2 into xenograft tumors resulted in a decrease in the level of Ki67 expression, as observed through IHC staining (Fig. 8F). These results suggest that AL365181.3 could contribute to the oncogenic impact of LUAD. Discussion LncRNAs are characterized by abundant species and spatial and temporal specificity; are widely involved in the regulation of cell apoptosis, immunity and other physiological and pathological processes; and have unique advantages as disease markers and therapeutic targets, which are of great value in clinical diagnosis and prognosis assessment[ 21 ]. In tandem with the advancements of bioinformatics and sequencing technologies, research on lncRNAs has also been increasing. Studies have shown that lncRNAs not only have potential as diagnostic and prognostic markers for LUAD but also play important regulatory roles in malignant phenotypes, such as LUAD proliferation, invasion, metastasis and chemoresistance. For example, the lncRNA DARS-AS1 enhances LUAD cell growth and metastasis through the miR-188-5p/KLF12 axis[ 22 ]. The lncRNA FAM83A-AS1 enhances tumor cell proliferation and migration in LUAD through the HIF-1α/glycolysis axis[ 23 ]. The lncRNA GAS6-AS1 inhibits LUAD progression and reprogramming of glucose metabolism by suppressing E2F1-mediated expression of the glucose transporter protein GLUT1[ 24 ]. The m6A-regulated lncRNA LCAT3 plays a pro-oncogenic role in LUAD by binding to FUBP1 to activate c-MYC[ 25 ]. The lncRNA SNHG7 enhances doxorubicin resistance in LUAD cells by inducing autophagy and macrophage M2 polarization[ 26 ]. Through epigenetic suppression of LATS2 expression, the m6A methyltransferase METTL3-induced lncRNA SNHG17 enhances LUAD gefitinib resistance[ 27 ]. These studies suggest that lncRNAs have significant clinical translational value and may be useful as biomarkers in the clinical diagnosis of LUAD. In our study, we analyzed AL365181.3 in human cancers and found that the level of AL365181.3 varied greatly among different tumors, and AL365181.3 RNA was significantly upregulated in 15 cancers in the TCGA database; moreover, AL365181.3 was increased in 13 cancers compared to paired adjacent normal tissues. Further studies revealed that AL365181.3 expression was increased in LUAD tissue specimens and that high AL365181.3 expression was negatively correlated with LUAD pathological stage and TNM stage, suggesting that AL365181.3 expression may be related to LUAD progression. Previous studies revealed that lncRNAs have clinical predictive value in many tumors[ 28 – 31 ]. At present, we found that high AL365181.3 expression had a significant detrimental effect on OS and DSS in LUAD patients. Furthermore, the ROC curve demonstrated an AUC greater than 0.75 for AL365181.3. These findings imply that AL365181.3 could function as a diagnostic and prognostic LUAD biomarker. To date, no studies have focused on the function of AL365181.3. In this study, we explored the regulatory mechanism of AL365181.3 in LUAD development. Functional enrichment analysis indicated that AL365181.3 is involved mainly in the regulation of metabolism, MAPK signaling and other tumor regulatory signaling pathways. Finally, we also showed that AL365181.3 knockdown significantly reduced LUAD cell proliferation and metastasis. This finding has enhanced our understanding of the relationship between LUAD and AL365181.3. However, there are still some limitations. However, the main molecular mechanism through which AL365181.3 affects the development of LUAD needs to be further investigated. Conclusion This discovery offers the first proof of the biological role and clinical importance of AL365181.3 in LUAD. Improved LUAD survival was closely correlated with a decreased AL365181.3 expression. AL365181.3 knockdown also inhibited LUAD cell proliferation and migration and in vivo tumorigenicity. For individuals with LUAD, AL365181.3 is a potential biomarker for both diagnosis and prognosis. Abbreviations ACC Adrenocortical carcinoma BLCA Bladder Urothelial Carcinoma BRCA Breast invasive carcinoma CESC Cervical squamous cell carcinoma and endocervical adenocarcinoma CHOL Cholangiocarcinoma COAD Colon adenocarcinoma DLBC Lymphoid Neoplasm Diffuse Large B-cell Lymphoma ESCA Esophageal carcinoma GBM Glioblastoma multiforme HNSC Head and Neck squamous cell carcinoma KICH Kidney Chromophobe KIRC Kidney renal clear cell carcinoma KIRP Kidney renal papillary cell carcinoma LAML Acute Myeloid Leukemia LGG Brain Lower Grade Glioma LIHC Liver hepatocellular carcinoma LUAD Lung adenocarcinoma LUSC Lung squamous cell carcinoma MESO Mesothelioma OV Ovarian serous cystadenocarcinoma PAAD Pancreatic adenocarcinoma PCPG Pheochromocytoma and Paraganglioma PRAD Prostate adenocarcinoma READ Rectum adenocarcinoma SARC Sarcoma STAD Stomach adenocarcinoma SKCM Skin Cutaneous Melanoma TGCT Testicular Germ Cell Tumors THCA Thyroid carcinoma THYM Thymoma UCEC Uterine Corpus Endometrial Carcinoma UCS Uterine Carcinosarcoma UVM Uveal Melanoma GSEA Gene set enrichment analysis OS Overall survival DSS Disease special survival PFI Progression-free interval LncRNA long non-coding RNA Declarations Ethics approval and consent to participate This study was conducted in compliance with the ARRIVE guidelines (https://arriveguidelines.org) for the ethical conduct of research involving animals. This study was authorized by the Institutional Ethics Committees of the Shanghai University of Medicine & Health Sciences Affiliated Zhoupu Hospital (Approval notice: 2023-C-225-E01) and abided by the Declaration of Helsinki. Consent for publication Not applicable. Availability of Data and Materials The data and material used to support the findings of this study are available from the corresponding author upon request. Competing interests The authors declare no competing interests. Funding This research was supported by the Shanghai Pudong New Area Zhoupu Hospital discipline construction introduction talent project (ZP-XK-2019B-1), and the Medical Discipline Construction Project of Pudong Health Committee of Shanghai (PWZzb2022-26). Authors contribution Conceptualization, Qiang Wang; methodology, Xiaoying Liu; formal analysis, Xiaoying Liu and Jinlong Liu; writing—original draft preparation, Xiaoying Liu; investigation: Xiaoying Liu, Yingou Zeng, and Di Qiao; methodology: Xiaoying Liu and Jinlong Liu; writing—review and editing, Qiang Wang, Xiaoying Liu, Yingou Zeng, and Di Qiao; Acknowledgments We thank all the individuals in the databases who participated in this study. References Sung H, Ferlay J, Siegel RL, Laversanne M, Soerjomataram I, Jemal A, et al. Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries. CA Cancer J Clin. 2021;71(3):209-49. https://doi.org/10.3322/caac.21660. Siegel RL, Miller KD, Fuchs HE, Jemal A. Cancer Statistics, 2021. CA Cancer J Clin. 2021;71(1):7-33. https://doi.org/10.3322/caac.21654. Kadara H, Choi M, Zhang J, Parra ER, Rodriguez-Canales J, Gaffney SG, et al. 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Cuproptosis-related lncRNA predict prognosis and immune response of lung adenocarcinoma. World J Surg Oncol. 2022;20(1):275. https://doi.org/10.1186/s12957-022-02727-7. Mai S, Liang L, Mai G, Liu X, Diao D, Cai R, et al. Development and Validation of Lactate Metabolism-Related lncRNA Signature as a Prognostic Model for Lung Adenocarcinoma. Front Endocrinol (Lausanne). 2022;13:829175. https://doi.org/10.3389/fendo.2022.829175. Wang L, Li Y, Wang Y, Li J, Sun Y, Chen J, et al. Identification of cuproptosis-related lncRNAs for prognosis and immunotherapy in glioma. J Cell Mol Med. 2022;26(23):5820-31. https://doi.org/10.1111/jcmm.17603. Table Table 1. Correlation of AL365181.3 expression with clinicopathologic features in LUAD patients. Characteristics Low expression of AL365181.3 High expression of AL365181.3 p n 269 270 Pathologic T stage, n (%) 0.009 T1&T2 244 (45.5%) 224 (41.8%) T3&T4 24 (4.5%) 44 (8.2%) Pathologic N stage, n (%) 0.007 N0 187 (35.8%) 163 (31.2%) N1&N2&N3 71 (13.6%) 102 (19.5%) Pathologic M stage, n (%) 0.066 M0 186 (47.7%) 179 (45.9%) M1 8 (2.1%) 17 (4.4%) Pathologic stage, n (%) <0.001 Stage I 172 (32.4%) 124 (23.4%) Stage II 47 (8.9%) 78 (14.7%) Stage III&Stage IV 47 (8.9%) 63 (11.9%) Additional Declarations No competing interests reported. Supplementary Files Supplementalfigure.docx 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. 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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-4019953","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":276686744,"identity":"e6e63275-78cd-4f4c-9b77-d0c8302ee3b1","order_by":0,"name":"Xiaoying Liu","email":"","orcid":"","institution":"Xinxiang Medical University","correspondingAuthor":false,"prefix":"","firstName":"Xiaoying","middleName":"","lastName":"Liu","suffix":""},{"id":276686745,"identity":"2696d495-00af-4c03-8507-dffd4b0ab2cd","order_by":1,"name":"Jinlong Liu","email":"","orcid":"","institution":"Xinxiang Medical University","correspondingAuthor":false,"prefix":"","firstName":"Jinlong","middleName":"","lastName":"Liu","suffix":""},{"id":276686746,"identity":"f310542c-6a4e-4c3f-8165-fb7852e97c24","order_by":2,"name":"Yingou Zeng","email":"","orcid":"","institution":"Shanghai University of Medicine \u0026 Health Sciences Affiliated Zhoupu Hospital","correspondingAuthor":false,"prefix":"","firstName":"Yingou","middleName":"","lastName":"Zeng","suffix":""},{"id":276686747,"identity":"1d4b6c52-7d58-45ea-8fe9-145ebfec1085","order_by":3,"name":"Di Qiao","email":"","orcid":"","institution":"Shanghai University of Medicine \u0026 Health Sciences Affiliated Zhoupu Hospital","correspondingAuthor":false,"prefix":"","firstName":"Di","middleName":"","lastName":"Qiao","suffix":""},{"id":276686748,"identity":"1a787ea0-b183-4457-abf3-1a4715a925d5","order_by":4,"name":"Qiang Wang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA6UlEQVRIie3RsQrCMBCA4SuFTlddUxR9hUgwIBR8lYjQqYiTqwXBtauCDyEIzpUOLhXXQCdxcegguIoaHRxT3QTzQ0IyfOEgACbT7+ZjVe3265x8RoK6F31JUp8mnxK63aWnAmxk+6y9Gl6hUZHCugx1JBsEnQU4yGXI8/kUmCeFXZtpCE9CzhBQEeS5G0FvKYVjo47siychyOKM53iFcTmRITsiUKSgBkMHBC0jXVlwawECiQxGuTslrXl2mNR0xItDdi7g3q3G6VoN5jcr2/7moiMqh7i394WoZUV6oD7wXPKmyWQy/XsPzKRH5IhCD5IAAAAASUVORK5CYII=","orcid":"","institution":"Shanghai University of Medicine \u0026 Health Sciences Affiliated Zhoupu Hospital","correspondingAuthor":true,"prefix":"","firstName":"Qiang","middleName":"","lastName":"Wang","suffix":""}],"badges":[],"createdAt":"2024-03-06 08:16:56","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4019953/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4019953/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":52189157,"identity":"b24635b5-4d06-4288-bd72-4a62c548d9b9","added_by":"auto","created_at":"2024-03-07 19:02:31","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":182118,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eExpression of AL365181.3 in tumor and normal tissues.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e(A) \u003c/strong\u003eAnalysis of AL365181.3 expression across cancers from the TCGA.\u003cstrong\u003e (B) \u003c/strong\u003eAnalysis of AL365181.3 expression in cancer tissues and adjacent paired normal tissues from the TCGA.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-4019953/v1/05a6fdad6ef7731d08912d7e.png"},{"id":52189159,"identity":"034fd359-10de-43fb-bb7b-1507e32c8a31","added_by":"auto","created_at":"2024-03-07 19:02:31","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":309347,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eThe prognostic value of AL365181.3 across cancers.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e(A)\u003c/strong\u003eThe impact of AL365181.3 expression on the OS rate of patients with LAML, LUAF, MESO, or UVM.\u003cstrong\u003e (B) \u003c/strong\u003eDSS of LUAD, MESO, OV, and UVM patients treated with AL365181.3. \u003cstrong\u003e(C)\u003c/strong\u003e The PFI for AL365181.3 in the CESC, KIRC, KIRP, MESO, PAAD, STAD, THYM, and UVM cohorts.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-4019953/v1/a386304696723389f5bc7204.png"},{"id":52187605,"identity":"2e523e73-020e-4c41-9bef-d7b3fe952b6f","added_by":"auto","created_at":"2024-03-07 18:54:31","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":308743,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eThe expression and prognosis of AL365181.3 in LUAD.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e(A-B) \u003c/strong\u003eThe expression of AL365181.3 in the TCGA cohort. \u003cstrong\u003e(C-D) \u003c/strong\u003eThe expression of AL365181.3 in the GEO database. \u003cstrong\u003e(E-H) \u003c/strong\u003eCorrelation of AL365181.3 expression with TNM stage and pathological stage. Correlations between AL365181.3 and OS according to pathological T stage\u003cstrong\u003e (I)\u003c/strong\u003e, pathological N stage \u003cstrong\u003e(J)\u003c/strong\u003e, pathological M stage race \u003cstrong\u003e(K)\u003c/strong\u003e, pathological stage \u003cstrong\u003e(L),\u003c/strong\u003eresidual tumor\u003cstrong\u003e \u003c/strong\u003elocation \u003cstrong\u003e(M)\u003c/strong\u003e, anatomic neoplasm subdivision\u003cstrong\u003e (N)\u003c/strong\u003e, age \u003cstrong\u003e(O)\u003c/strong\u003e, smoking status \u003cstrong\u003e(P)\u003c/strong\u003e, and number of pack-years smoked \u003cstrong\u003e(Q) \u003c/strong\u003ein LUAD patients.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-4019953/v1/244fe77221952875af62f3b5.png"},{"id":52190437,"identity":"ee79f4f1-2299-48ed-a508-3f69b476792d","added_by":"auto","created_at":"2024-03-07 19:10:31","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":220633,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eConstruction and evaluation of the nomogram.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNomogram for predicting the OS \u003cstrong\u003e(A)\u003c/strong\u003e, DSS \u003cstrong\u003e(B)\u003c/strong\u003e, and PFI \u003cstrong\u003e(C)\u003c/strong\u003eof LUAD patients. The calibration curve and Hosmer–Lemeshow test of the nomograms in the TCGA-LUAD cohort for OS \u003cstrong\u003e(D)\u003c/strong\u003e, DSS \u003cstrong\u003e(E)\u003c/strong\u003e, and PFI \u003cstrong\u003e(F)\u003c/strong\u003e.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-4019953/v1/14db2ab13add8cbab665c73c.png"},{"id":52187603,"identity":"038140a7-26d2-46b9-a24f-b6780f2d97b9","added_by":"auto","created_at":"2024-03-07 18:54:31","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":310789,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eGSEA identification of AL365181.3-related signaling pathways\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-4019953/v1/c254c2ac45622575185f7d5a.png"},{"id":52187601,"identity":"cdbb71d2-a9bc-4691-8af8-c99093ea9fb9","added_by":"auto","created_at":"2024-03-07 18:54:31","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":149786,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eThe hallmark characteristic enrichment results for AL365181.3 expression.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-4019953/v1/30aae0663f427416683d7c3f.png"},{"id":52189161,"identity":"4d6337af-c648-4cd5-842b-b800cdea7f11","added_by":"auto","created_at":"2024-03-07 19:02:31","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":390203,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAL365181.3 knockdown regulates LUAD cell proliferation and migration ability in vitro.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e(A) \u003c/strong\u003eRT‒PCR was used to verify the efficiency of AL365181.3 knockdown. (\u003cstrong\u003eB-C) \u003c/strong\u003eKnockdown of AL365181.3 reduced the proliferation of cells, as determined by CCK-8 and colony formation assays. (\u003cstrong\u003eD) \u003c/strong\u003eApoptotic cells were detected by flow cytometry.\u003c/p\u003e\n\u003cp\u003e(E) Knockdown of AL365181.3 reduced cell migration and invasion ability according to Transwell assays. (F) Knockdown of AL365181.3 reduced cell migration, as determined by wound healing assay.\u003c/p\u003e","description":"","filename":"7.png","url":"https://assets-eu.researchsquare.com/files/rs-4019953/v1/0160a1091788551b0caf129c.png"},{"id":52187610,"identity":"f2bd12bb-27dd-4a13-8dbd-7e74bc8ad38f","added_by":"auto","created_at":"2024-03-07 18:54:31","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":186280,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAL365181.3 knockdown inhibits LUAD cell xenograft tumor growth\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e(A-C)\u003c/strong\u003eRepresentative images and tumor growth chart 15 days after the injection of si-AL365181.3#2 or NC in the LUAD xenograft model. \u003cstrong\u003e(D)\u003c/strong\u003e Xenograft tumor weights were measured and graphed 15 days after the injection. \u003cstrong\u003e(E) \u003c/strong\u003eAL365181.3 expression in xenograft tumors was validated by qPCR.\u003cstrong\u003e (F) \u003c/strong\u003eIHC staining was used to examine the alterations in the levels of Ki-67 in xenograft tumors. Representative images are shown. Scale bars, 20 μm.\u003c/p\u003e","description":"","filename":"8.png","url":"https://assets-eu.researchsquare.com/files/rs-4019953/v1/4991999354f49ceeb13bd10f.png"},{"id":52545396,"identity":"78a5093c-bbd3-4a6b-8bf8-eb8dce0647d3","added_by":"auto","created_at":"2024-03-12 18:21:07","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2531883,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4019953/v1/8672d13f-0611-4b10-a9d0-cecd06a63e45.pdf"},{"id":52187608,"identity":"2ea26550-08d6-4ac1-b5bd-4439d423dc67","added_by":"auto","created_at":"2024-03-07 18:54:31","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":943187,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementalfigure.docx","url":"https://assets-eu.researchsquare.com/files/rs-4019953/v1/e4664f4ed48071d3fe9c9c4d.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Pan-cancer analysis identifies AL365181.3 as a novel prognostic biomarker for lung adenocarcinoma","fulltext":[{"header":"Introduction","content":"\u003cp\u003eLung cancer is a leading cause of cancer-related mortality worldwide[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e], and its incidence and mortality rates have been increasing annually. Lung cancer has an insidious onset, and most lung cancer patients have already developed distant metastases by the time of diagnosis, limiting the typical 5-year survival rate of individuals with lung cancer to no more than 25%[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Among these subtypes, lung adenocarcinoma (LUAD) is the most common molecular subtype of non-small cell lung cancer (NSCLC), and its proportion of NSCLC is gradually increasing to almost 50% of lung cancers[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Although considerable progress has been made in the past several decades in various treatments for lung cancer[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e], the morbidity and mortality of LUAD remain high[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Hence, there is an immediate need for more effective markers for LUAD prevention and therapeutic targets for improved diagnosis and treatment.\u003c/p\u003e \u003cp\u003eA kind of noncoding RNA molecule longer than 200 nucleotides that does not have an open reading frame to encode proteins is known as a long noncoding RNA (lncRNA)[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e], and these molecules play a critical regulatory role in the development of cancers[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. The rich variety of lncRNAs, their spatial and temporal specific expression and diverse regulatory mechanisms make them unique diagnostic and prognostic markers and molecular targets. Recent studies on the functions, mechanisms of action and clinical significance of lncRNAs in various tumors are increasing annually. LncRNAs have been demonstrated to be involved in the regulation of tumor cell proliferation, apoptosis, cell cycle progression, invasion, metastasis, tumor stem cell stemness maintenance, the tumor microenvironment and metabolism and play important roles in tumor development and resistance to radiotherapy[\u003cspan additionalcitationids=\"CR9 CR10\" citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Recent studies have identified a series of lncRNAs, such as iron death-associated lncRNAs[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e], scorch death-associated lncRNAs[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e] and methylation-driven lncRNAs, as prognostic markers for LUAD[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. These studies suggest that lncRNAs not only are potential biomarkers for the clinical treatment of LUAD but are also expected to be targets for molecularly targeted therapies in LUAD, with important clinical translational value. Consequently, the study of the mechanism of lncRNA-related molecules has become a hotspot of research in the field of oncology.\u003c/p\u003e \u003cp\u003eIn this investigation, we integrated and analyzed the transcriptome sequencing data of the TCGA cohort and successfully identified many new DEGs, and the lncRNA AL365181.3 was one of these DEGs. However, the possible role and therapeutic value of AL365181.3 in LUAD are unclear. In the present investigation, we showed that in patients with LUAD, abnormal expression of AL365181.3 was linked to a poor clinical outcome. Moreover, we mined TCGA data to identify the downstream targets of AL365181.3 and to determine the potential regulatory signaling pathways involved in LUAD. Finally, CCK8, colony formation, wound healing and Transwell assays were used to confirm the biological function of AL365181.3 in LUAD progression. In conclusion, our findings suggest a potential role for AL365181.3 in regulating tumor development and in the diagnostic assessment of LUAD.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eAnalysis of clinical information, prognosis, and expression status\u003c/h2\u003e \u003cp\u003eThe tumor AL365181.3 expression, prognosis, and clinical information were analyzed using the following databases: TCGA, Kaplan‒Meier plotter[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e], and GEPIA[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eReceiver operating characteristic (ROC) curve analysis\u003c/h2\u003e \u003cp\u003eWe utilized the pROC function from the R package to determine the area under the curve (AUC) of the receiver operating characteristic (ROC) curves produced by screening signature genes.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eCell culture conditions\u003c/h2\u003e \u003cp\u003ePurchased from the Chinese Academy of Sciences Cell Bank, H1299 and A549 cells were grown in RPMI 1640 media supplemented with 10% fetal bovine serum (FBS) and 1% penicillin/streptomycin at 37\u0026deg;C and 5% CO\u003csub\u003e2\u003c/sub\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eTransfection\u003c/h2\u003e \u003cp\u003eIn 6-well plates, the cells were incubated with serum-free medium, which was changed at 70% confluence. siRNA and the transfection reagent LipofectamineTM 3000 were mixed at the recommended ratios, the transfection complex was usually added dropwise to the 6-well plates, and the dishes were gently shaken to ensure homogeneous mixing; after 4\u0026ndash;6 h, the complete medium was replaced. After 24\u0026ndash;48 hours, subsequent experiments were carried out. The siRNAs for AL365181.3-1 (si-AL365181.3-1#1: 5\u0026rsquo;- GCAAGAGAAUUGAAGGUUAGACUAC-3\u0026rsquo;; si-AL365181.3-1#2: 5\u0026rsquo;- CUAAUAGUUACUGAUGUCUACCUGA-3\u0026rsquo;) were synthesized by Gene Pharma (Shanghai, China).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eqRT‒PCR\u003c/h2\u003e \u003cp\u003eTotal RNA was extracted using TRIzol reagent. cDNA was subsequently reverse transcribed. We performed the amplification reaction according to the instructions provided in the Green qPCR Supermix on top of the trans starter. In addition, we quantified mRNA expression using the 2\u003csup\u003e\u0026minus;ΔΔCt\u003c/sup\u003e method. The following are primer sequences: q-AL365181.3-F: AGGTCTCTCTCTCTCTCT, q-AL365181.3-R: CCCTAAGGCCCTGCTTATATTG; q-18S-F: CTTCGGGGCTTCGGGG; and q-18S-R: CATAGGAATCCTTCTGACC.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eCCK8, colony formation assay\u003c/h2\u003e \u003cp\u003eCell viability and growth were measured in 96-well plates with a CCK8 assay. Sample cells were inoculated in 96-well plates and incubated with CCK8 solution at a fixed time point for 1 h. The absorbance was measured at 450 nm with a spectrophotometer. For the colony formation experiments, the cells were inoculated in 6-well plates and cultured for 10 to 14 days. The solidified cells were stained and then photographed.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eApoptosis analysis\u003c/h2\u003e \u003cp\u003e \u003cb\u003eA\u003c/b\u003e FITC Annexin V Apoptosis Detection Kit I was used to detect apoptosis. After being disrupted by EDTA-free trypsin and rinsed with ice-cold PBS, the cells were incubated with PI and Alexa Fluor 488 annexin V for 15 minutes. Afterward, the cells were examined using a NovoCyte flow cytometer.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eWound healing assay\u003c/h2\u003e \u003cp\u003eA monolayer of cells was scratched along a straight line to form a wound. To determine the gap width, the isolated cells were cleaned with PBS, and images of the scratches were taken at predetermined intervals.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eTranswell migration and invasion assays\u003c/h2\u003e \u003cp\u003eIn transwell experiments, \u003csup\u003e5\u0026times;104\u003c/sup\u003e cells were inoculated in the upper chamber of a small chamber containing serum-free medium, and medium containing 15% FBS was added to the lower chamber. Cells that crossed the membrane of the chambers were counted after 24 h of incubation.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eXenograft model studies\u003c/h2\u003e \u003cp\u003eFemale BALB/c nude mice aged 4 weeks were obtained from GemPharmatech Technology (Jiangsu, China). A total of 4 \u0026times; 10\u003csup\u003e6\u003c/sup\u003e A549 cells were injected into the left flank of each mouse. Six injections of either si-NC or siRNA (20 nmol) were given to eight mice at intervals of three days using 0.1 mL of saline buffer. Xenograft models were split into two groups (n\u0026thinsp;=\u0026thinsp;4) after fifteen days, when the tumors had grown to a size of approximately 5 mm by 5 mm. After being anesthetized with isoflurane, the tumor-bearing mice were sacrificed via cervical dislocation on day 30. The tumors from the xenografts were removed, weighed, and imaged with a camera.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eIHC\u003c/h2\u003e \u003cp\u003eFollowing the methods described earlier, immunohistochemistry (IHC) was performed [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. For an overnight incubation at 4\u0026deg;C, primary antibodies against Ki67 (sc-23900, Santa Cruz) were applied to the xenograft sections of nude mice. The secondary antibody was then administered.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eThe two sets of data were compared for significance using Student\u0026rsquo;s t test. A P value less than 0.05 was considered to indicate statistical significance. *P\u0026thinsp;\u0026lt;\u0026thinsp;0.05; **P\u0026thinsp;\u0026lt;\u0026thinsp;0.01; ***P\u0026thinsp;\u0026lt;\u0026thinsp;0.001.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003eMolecular characteristics analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAccording to the\u0026nbsp;lnCAR database, AL365181.3 is an\u0026nbsp;intronless transcript of 3222 nucleotides (nt)[20]. Figure S1A shows the genomic information for AL365181.3. AL365181.3 is located\u0026nbsp;at\u0026nbsp;chr1:156641666.156644887. According to\u0026nbsp;the online database, AL365181.3\u0026nbsp;did\u0026nbsp;not exhibit coding potential (Fig. S1B-C).\u0026nbsp;Furthermore, we found that LUAD cells contain AL365181.3, which is located\u0026nbsp;primarily in\u0026nbsp;the\u0026nbsp;cytoplasm (Fig. S1D).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eThe expression of AL365181.3 varies in human tumors\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo validate the involvement of AL365181.3 in regulating human tumor development, we verified the RNA expression pattern of AL365181.3 in a variety of cancers and showed that the expression level of AL365181.3 varied greatly among different tumors, with AL365181.3 RNA being significantly\u0026nbsp;highly expressed\u0026nbsp;in 15 cancers in the TCGA database (Fig. 1A). We also confirmed that AL365181.3 was\u0026nbsp;highly expressed\u0026nbsp;in 13 paired adjacent normal tissues (Fig. 1B).\u0026nbsp;These findings\u0026nbsp;suggest that AL365181.3 can play a\u0026nbsp;procancer\u0026nbsp;role in different types of tumors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePrognostic\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003evalue\u0026nbsp;of AL365181.3 in human tumors\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAL365181.3 expression\u0026nbsp;differs among\u0026nbsp;different types of cancer, so its prognostic value in human cancer was investigated. We found that the expression level of AL365181.3 was related to the overall survival (OS)\u0026nbsp;time of patients with four kinds of tumors (Figure 2A),\u0026nbsp;disease-specific survival (DSS) of patients with 4 kinds of tumors (Figure 2B) and\u0026nbsp;progression-free interval (PFI) of patients with 8 kinds of tumors (Figure 2C).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eROC curve analysis of AL365181.3 in human tumors\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe investigated\u0026nbsp;whether AL365181.3 can serve as a biomarker for human tumors. According to the ROC curve analysis, AL365181.3\u0026nbsp;could\u0026nbsp;be used to diagnose 20 types of tumors with high sensitivity and specificity (AUC \u0026gt; 0.75) (Fig. S2A-E).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAL365181.3\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;is highly expressed in LUAD tissues and\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eis correlated\u0026nbsp;with adverse clinical parameters in LUAD patients\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eUsing\u0026nbsp;AL365181.3 expression data from TCGA, we examined AL365181.3 expression in LUAD,\u0026nbsp;and we found that AL365181.3 was more\u0026nbsp;highly expressed\u0026nbsp;in LUAD (Fig. 3A-B). Moreover,\u0026nbsp;Gene Expression Omnibus\u0026nbsp;(GEO) data provided similar results (Fig.\u0026nbsp;3C-D). We also examined the clinical relevance of AL365181.3 in LUAD\u0026nbsp;using the TCGA LUAD dataset. The pathological stage and TNM stage were significantly correlated with AL365181.3 expression (Fig.\u0026nbsp;3E-H, Table 1). Importantly, in\u0026nbsp;LUAD patients with many clinical features, including TNM stage,\u0026nbsp;pathological\u0026nbsp;stage, residual tumor, cancer location, anatomic neoplasm subdivision, age,\u0026nbsp;smoking status, and number\u0026nbsp;of peak years smoked, those with high AL365181.3\u0026nbsp;expression had significantly worse OS\u0026nbsp;(Fig. 3I-R).\u003c/p\u003e\n\u003cp\u003eA nomogram was also constructed using the TCGA-LUAD cohort to predict OS, DSS, and\u0026nbsp;the PFI.\u0026nbsp;The prognostic\u0026nbsp;indicators in the nomogram included AL365181.3 expression and pathological stage\u0026nbsp;(Fig. 4A–C). LUAD OS, DSS, and\u0026nbsp;the PFI were reliably predicted by the nomogram based on calibration curves (Figure\u0026nbsp;4D–F). In conclusion, AL365181.3 can be used as a sensitive\u0026nbsp;diagnostic indicator and can be used as a promising biomarker for LUAD.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAnalysis of the AL365181.3-related signaling pathways in LUAD\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eUsing the “clusterProfiler” R package, we performed functional\u0026nbsp;annotation\u0026nbsp;of\u0026nbsp;the AL365181.3-associated differentially expressed genes (DEGs) in LUAD patients to elucidate the mechanism of\u0026nbsp;the\u0026nbsp;effect of AL365181.3, and 418 DEGs (mRNAs\u0026nbsp;and\u0026nbsp;lncRNAs) were\u0026nbsp;identified\u0026nbsp;with threshold values of |log2-fold change (FC)|\u0026gt;2 and adjusted p value \u0026lt; 0.05; these genes included\u0026nbsp;29 upregulated and 282 downregulated\u0026nbsp;lncRNAs\u0026nbsp;and 71 upregulated and 36 downregulated\u0026nbsp;mRNAs\u0026nbsp;(Fig. S3A–B). The KEGG enrichment results showed that the DEGs were involved\u0026nbsp;mainly in pentose and glucuronate interconversions, steroid hormone biosynthesis, ascorbate and aldarate metabolism, drug metabolism-cytochrome P450, and metabolism of xenobiotics by cytochrome P450 (Fig. S3C). Next, we performed\u0026nbsp;Kyoto Encyclopedia of Genes and Genomes (KEGG)\u0026nbsp;enrichment\u0026nbsp;analysis of\u0026nbsp;the GEO dataset. The results revealed that AL365181.3 is involved in the regulation of metabolic metabolism, MAPK\u0026nbsp;signaling and other tumor regulatory signaling pathways (Fig. S3D-E).\u003c/p\u003e\n\u003cp\u003eGSEA indicated that AL365181.3 was involved\u0026nbsp;mainly\u0026nbsp;in arginine and proline metabolism, phenylalanine metabolism and other pathways, other enzymes\u0026nbsp;involved in\u0026nbsp;drug metabolism, fructose and mannose metabolism, glycosaminoglycan degradation, the pentose phosphate pathway, the metabolism of cytochromes to xenobiotics, linoleic acid metabolism, the pentose phosphate pathway, nicotinic acid and nicotinamide metabolism, phenylalanine metabolism, retinol metabolism, ascorbic and aldehyde metabolism, and steroid hormone biosynthesis and tyrosine metabolism (Fig. 5).\u003c/p\u003e\n\u003cp\u003eThe enrichment of hallmark genes\u0026nbsp;indicated the following: early\u0026nbsp;estrogen response,\u0026nbsp;late estrogen response, glycolysis, heme metabolism,\u0026nbsp;reactive oxygen species pathway, xenobiotic metabolism, and\u0026nbsp;pancreatic\u0026nbsp;beta cells (Fig. 6). These\u0026nbsp;findings\u0026nbsp;strongly\u0026nbsp;demonstrated\u0026nbsp;that AL365181.3 is\u0026nbsp;involved mainly in the regulation of LUAD metabolism-related pathways.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAL365181.3 knockdown inhibits the proliferation of LUAD cells in vitro\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe above results suggest that AL365181.3 expression is significantly\u0026nbsp;upregulated\u0026nbsp;in LUAD tissues and that AL365181.3 may affect the progression of LUAD.\u0026nbsp;To\u0026nbsp;investigate the biological function\u0026nbsp;of AL365181.3 in LUAD, two siRNA sequences targeting AL365181.3, named siRNA-AL365181.3#1 and siRNA-AL365181.3#2, were designed and synthesized, and random nonsense siRNA sequences were selected as negative controls. The target cells were transfected separately by RNAi,\u0026nbsp;and the knockdown efficiency of the transfected cell lines was examined\u0026nbsp;via qRT‒PCR\u0026nbsp;analysis (Fig. 7A). CCK8 and cell\u0026nbsp;colony formation\u0026nbsp;assays confirmed that in both A549 and H1299 cells,\u0026nbsp;AL365181.3\u0026nbsp;knockdown reduced\u0026nbsp;the proliferative capacity (Fig. 7B-C). In addition, knocking down AL365181.3\u0026nbsp;enhanced\u0026nbsp;LUAD cell apoptosis (Fig. 7D).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAL365181.3 knockdown inhibits the migration and invasion of LUAD cells\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe\u0026nbsp;effect of AL365181.3 on\u0026nbsp;the metastasis of LUAD cells was\u0026nbsp;subsequently confirmed. Transwell and wound healing\u0026nbsp;assays demonstrated that\u0026nbsp;cell migration\u0026nbsp;was markedly\u0026nbsp;inhibited\u0026nbsp;by downregulation of AL365181.3 expression (Fig. 7E-F). In conclusion, these results\u0026nbsp;demonstrated\u0026nbsp;that AL365181.3 has an essential function in regulating the migratory capacity of LUAD cells.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAL365181.3 knockdown inhibits LUAD\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003ecell\u0026nbsp;xenograft tumor growth\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eUsing a xenograft tumor model, we examined the effect of AL365181.3 on LUAF in vivo. Beginning on day 15, the mice were injected with NC or AL365181.3 siRNA every three days, and on day 30, they were euthanized. Compared to those of the NC cells, the tumors of the A549 cells grown with lower AL365181.3 concentrations grew at a significantly slower rate (Fig. 8A-C). Compared with those in the NC group, the weights of the si-AL365181.3#2-treated xenograft tumors were lower (Fig. 8D). qPCR revealed that AL365181.3 levels were significantly lower in si-AL365181.3-injected xenograft tumors than in control tumors (Fig. 8E). Compared with those in the NC group, the injection of si-AL365181.3#2 into xenograft tumors resulted in a decrease in the level of Ki67 expression, as observed through IHC staining (Fig. 8F). These results suggest that AL365181.3 could contribute to the oncogenic impact of LUAD.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eLncRNAs are characterized by abundant species and spatial and temporal specificity; are widely involved in the regulation of cell apoptosis, immunity and other physiological and pathological processes; and have unique advantages as disease markers and therapeutic targets, which are of great value in clinical diagnosis and prognosis assessment[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. In tandem with the advancements of bioinformatics and sequencing technologies, research on lncRNAs has also been increasing. Studies have shown that lncRNAs not only have potential as diagnostic and prognostic markers for LUAD but also play important regulatory roles in malignant phenotypes, such as LUAD proliferation, invasion, metastasis and chemoresistance. For example, the lncRNA DARS-AS1 enhances LUAD cell growth and metastasis through the miR-188-5p/KLF12 axis[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. The lncRNA FAM83A-AS1 enhances tumor cell proliferation and migration in LUAD through the HIF-1α/glycolysis axis[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. The lncRNA GAS6-AS1 inhibits LUAD progression and reprogramming of glucose metabolism by suppressing E2F1-mediated expression of the glucose transporter protein GLUT1[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. The m6A-regulated lncRNA LCAT3 plays a pro-oncogenic role in LUAD by binding to FUBP1 to activate c-MYC[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. The lncRNA SNHG7 enhances doxorubicin resistance in LUAD cells by inducing autophagy and macrophage M2 polarization[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Through epigenetic suppression of LATS2 expression, the m6A methyltransferase METTL3-induced lncRNA SNHG17 enhances LUAD gefitinib resistance[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. These studies suggest that lncRNAs have significant clinical translational value and may be useful as biomarkers in the clinical diagnosis of LUAD.\u003c/p\u003e \u003cp\u003eIn our study, we analyzed AL365181.3 in human cancers and found that the level of AL365181.3 varied greatly among different tumors, and AL365181.3 RNA was significantly upregulated in 15 cancers in the TCGA database; moreover, AL365181.3 was increased in 13 cancers compared to paired adjacent normal tissues. Further studies revealed that AL365181.3 expression was increased in LUAD tissue specimens and that high AL365181.3 expression was negatively correlated with LUAD pathological stage and TNM stage, suggesting that AL365181.3 expression may be related to LUAD progression. Previous studies revealed that lncRNAs have clinical predictive value in many tumors[\u003cspan additionalcitationids=\"CR29 CR30\" citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. At present, we found that high AL365181.3 expression had a significant detrimental effect on OS and DSS in LUAD patients. Furthermore, the ROC curve demonstrated an AUC greater than 0.75 for AL365181.3. These findings imply that AL365181.3 could function as a diagnostic and prognostic LUAD biomarker.\u003c/p\u003e \u003cp\u003eTo date, no studies have focused on the function of AL365181.3. In this study, we explored the regulatory mechanism of AL365181.3 in LUAD development. Functional enrichment analysis indicated that AL365181.3 is involved mainly in the regulation of metabolism, MAPK signaling and other tumor regulatory signaling pathways. Finally, we also showed that AL365181.3 knockdown significantly reduced LUAD cell proliferation and metastasis. This finding has enhanced our understanding of the relationship between LUAD and AL365181.3. However, there are still some limitations. However, the main molecular mechanism through which AL365181.3 affects the development of LUAD needs to be further investigated.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis discovery offers the first proof of the biological role and clinical importance of AL365181.3 in LUAD. Improved LUAD survival was closely correlated with a decreased AL365181.3 expression. AL365181.3 knockdown also inhibited LUAD cell proliferation and migration and in vivo tumorigenicity. For individuals with LUAD, AL365181.3 is a potential biomarker for both diagnosis and prognosis.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eACC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eAdrenocortical carcinoma\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eBLCA\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eBladder Urothelial Carcinoma\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eBRCA\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eBreast invasive carcinoma\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCESC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eCervical squamous cell carcinoma and endocervical adenocarcinoma\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCHOL\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eCholangiocarcinoma\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCOAD\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eColon adenocarcinoma\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eDLBC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eLymphoid Neoplasm Diffuse Large B-cell Lymphoma\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eESCA\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eEsophageal carcinoma\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eGBM\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eGlioblastoma multiforme\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eHNSC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eHead and Neck squamous cell carcinoma\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eKICH\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eKidney Chromophobe\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eKIRC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eKidney renal clear cell carcinoma\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eKIRP\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eKidney renal papillary cell carcinoma\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eLAML\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eAcute Myeloid Leukemia\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eLGG\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eBrain Lower Grade Glioma\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eLIHC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eLiver hepatocellular carcinoma\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eLUAD\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eLung adenocarcinoma\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eLUSC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eLung squamous cell carcinoma\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eMESO\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eMesothelioma\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eOV\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eOvarian serous cystadenocarcinoma\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePAAD\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ePancreatic adenocarcinoma\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePCPG\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ePheochromocytoma and Paraganglioma\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePRAD\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eProstate adenocarcinoma\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eREAD\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eRectum adenocarcinoma\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eSARC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eSarcoma\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eSTAD\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eStomach adenocarcinoma\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eSKCM\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eSkin Cutaneous Melanoma\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eTGCT\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eTesticular Germ Cell Tumors\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eTHCA\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eThyroid carcinoma\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eTHYM\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eThymoma\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eUCEC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eUterine Corpus Endometrial Carcinoma\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eUCS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eUterine Carcinosarcoma\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eUVM\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eUveal Melanoma\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eGSEA\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eGene set enrichment analysis\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eOS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eOverall survival\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eDSS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eDisease special survival\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePFI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eProgression-free interval\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eLncRNA\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003elong non-coding RNA\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was conducted in compliance with the ARRIVE guidelines (https://arriveguidelines.org) for the ethical conduct of research involving animals. This study was authorized by the Institutional Ethics Committees of the Shanghai University of Medicine \u0026amp; Health Sciences Affiliated Zhoupu Hospital (Approval notice: 2023-C-225-E01) and abided by the Declaration of Helsinki.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of Data and Materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data and material used to support the findings of this study are available from the corresponding author upon request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research was supported by the Shanghai Pudong New Area Zhoupu Hospital discipline construction introduction talent project (ZP-XK-2019B-1), and the Medical Discipline Construction Project of Pudong Health Committee of Shanghai (PWZzb2022-26).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors contribution\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eConceptualization, Qiang Wang; methodology, Xiaoying Liu; formal analysis, Xiaoying Liu and Jinlong Liu; writing—original draft preparation, Xiaoying Liu; investigation: Xiaoying Liu, Yingou Zeng, and Di Qiao; methodology: Xiaoying Liu and Jinlong Liu; writing—review and editing, Qiang Wang, Xiaoying Liu, Yingou Zeng, and Di Qiao;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe thank all the\u0026nbsp;individuals in the databases\u0026nbsp;who\u0026nbsp;participated in this study.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eSung H, Ferlay J, Siegel RL, Laversanne M, Soerjomataram I, Jemal A, et al. Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries. CA Cancer J Clin. 2021;71(3):209-49. https://doi.org/10.3322/caac.21660.\u003c/li\u003e\n\u003cli\u003eSiegel RL, Miller KD, Fuchs HE, Jemal A. Cancer Statistics, 2021. CA Cancer J Clin. 2021;71(1):7-33. https://doi.org/10.3322/caac.21654.\u003c/li\u003e\n\u003cli\u003eKadara H, Choi M, Zhang J, Parra ER, Rodriguez-Canales J, Gaffney SG, et al. Whole-exome sequencing and immune profiling of early-stage lung adenocarcinoma with fully annotated clinical follow-up. Ann Oncol. 2017;28(1):75-82. https://doi.org/10.1093/annonc/mdw436.\u003c/li\u003e\n\u003cli\u003eJonna S, Subramaniam DS. Molecular diagnostics and targeted therapies in non-small cell lung cancer (NSCLC): an update. Discov Med. 2019;27(148):167-70. \u003c/li\u003e\n\u003cli\u003eMartin P, Leighl NB. 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LncRNA SNHG1 contributes to the cisplatin resistance and progression of NSCLC via miR-330-5p/DCLK1 axis. Exp Mol Pathol. 2021;120:104633. https://doi.org/10.1016/j.yexmp.2021.104633.\u003c/li\u003e\n\u003cli\u003eHe L, Tang L, Wang R, Liu L, Zhu P, Jiang K, et al. Long noncoding RNA KB-1980E6.3 promotes breast cancer progression through the PI3K/AKT signalling pathway. Pathol Res Pract. 2022;234:153891. https://doi.org/10.1016/j.prp.2022.153891.\u003c/li\u003e\n\u003cli\u003eZhang Y, Mao Q, Xia Q, Cheng J, Huang Z, Li Y, et al. Noncoding RNAs link metabolic reprogramming to immune microenvironment in cancers. J Hematol Oncol. 2021;14(1):169. https://doi.org/10.1186/s13045-021-01179-y.\u003c/li\u003e\n\u003cli\u003eLu L, Liu LP, Zhao QQ, Gui R, Zhao QY. Identification of a Ferroptosis-Related LncRNA Signature as a Novel Prognosis Model for Lung Adenocarcinoma. Front Oncol. 2021;11:675545. https://doi.org/10.3389/fonc.2021.675545.\u003c/li\u003e\n\u003cli\u003eYao J, Chen X, Liu X, Li R, Zhou X, Qu Y. Characterization of a ferroptosis and iron-metabolism related lncRNA signature in lung adenocarcinoma. Cancer Cell Int. 2021;21(1):340. https://doi.org/10.1186/s12935-021-02027-2.\u003c/li\u003e\n\u003cli\u003eHuang H, Shi Z, Li Y, Zhu G, Chen C, Zhang Z, et al. Pyroptosis-Related LncRNA Signatures Correlate With Lung Adenocarcinoma Prognosis. Front Oncol. 2022;12:850943. https://doi.org/10.3389/fonc.2022.850943.\u003c/li\u003e\n\u003cli\u003eZhou S, Cai Y, Xu Z, Peng B, Liang Q, Peng J, et al. Identification of a pyroptosis-related lncRNA signature in the regulation of prognosis, metabolism signals and immune infiltration in lung adenocarcinoma. Front Endocrinol (Lausanne). 2022;13:964362. https://doi.org/10.3389/fendo.2022.964362.\u003c/li\u003e\n\u003cli\u003eLi R, Yang YE, Yin YH, Zhang MY, Li H, Qu YQ. Methylation and transcriptome analysis reveal lung adenocarcinoma-specific diagnostic biomarkers. J Transl Med. 2019;17(1):324. https://doi.org/10.1186/s12967-019-2068-z.\u003c/li\u003e\n\u003cli\u003eL\u0026aacute;nczky A, Győrffy B. Web-Based Survival Analysis Tool Tailored for Medical Research (KMplot): Development and Implementation. J Med Internet Res. 2021;23(7):e27633. https://doi.org/10.2196/27633.\u003c/li\u003e\n\u003cli\u003eTang Z, Li C, Kang B, Gao G, Li C, Zhang Z. GEPIA: a web server for cancer and normal gene expression profiling and interactive analyses. Nucleic Acids Res. 2017;45(W1):W98-98W102. https://doi.org/10.1093/nar/gkx247.\u003c/li\u003e\n\u003cli\u003eWu Y, Guo Y, Wang Q. USP21 accelerates the proliferation and glycolysis of esophageal cancer cells by regulating the STAT3/FOXO1 pathway. Tissue Cell. 2022;79:101916. https://doi.org/10.1016/j.tice.2022.101916.\u003c/li\u003e\n\u003cli\u003eZheng Y, Xu Q, Liu M, Hu H, Xie Y, Zuo Z, et al. lnCAR: A Comprehensive Resource for lncRNAs from Cancer Arrays. Cancer Res. 2019;79(8):2076-83. https://doi.org/10.1158/0008-5472.CAN-18-2169.\u003c/li\u003e\n\u003cli\u003eMattick JS, Amaral PP, Carninci P, Carpenter S, Chang HY, Chen LL, et al. Long non-coding RNAs: definitions, functions, challenges and recommendations. Nat Rev Mol Cell Biol. 2023;24(6):430-47. https://doi.org/10.1038/s41580-022-00566-8.\u003c/li\u003e\n\u003cli\u003eLiu Y, Liang L, Ji L, Zhang F, Chen D, Duan S, et al. Potentiated lung adenocarcinoma (LUAD) cell growth, migration and invasion by lncRNA DARS-AS1 via miR-188-5p/ KLF12 axis. Aging (Albany NY). 2021;13(19):23376-92. https://doi.org/10.18632/aging.203632.\u003c/li\u003e\n\u003cli\u003eChen Z, Hu Z, Sui Q, Huang Y, Zhao M, Li M, et al. LncRNA FAM83A-AS1 facilitates tumor proliferation and the migration via the HIF-1\u0026alpha;/ glycolysis axis in lung adenocarcinoma. Int J Biol Sci. 2022;18(2):522-35. https://doi.org/10.7150/ijbs.67556.\u003c/li\u003e\n\u003cli\u003eLuo J, Wang H, Wang L, Wang G, Yao Y, Xie K, et al. lncRNA GAS6-AS1 inhibits progression and glucose metabolism reprogramming in LUAD via repressing E2F1-mediated transcription of GLUT1. Mol Ther Nucleic Acids. 2021;25:11-24. https://doi.org/10.1016/j.omtn.2021.04.022.\u003c/li\u003e\n\u003cli\u003eQian X, Yang J, Qiu Q, Li X, Jiang C, Li J, et al. LCAT3, a novel m6A-regulated long non-coding RNA, plays an oncogenic role in lung cancer via binding with FUBP1 to activate c-MYC. J Hematol Oncol. 2021;14(1):112. https://doi.org/10.1186/s13045-021-01123-0.\u003c/li\u003e\n\u003cli\u003eZhang K, Chen J, Li C, Yuan Y, Fang S, Liu W, et al. Exosome-mediated transfer of SNHG7 enhances docetaxel resistance in lung adenocarcinoma. Cancer Lett. 2022;526:142-54. https://doi.org/10.1016/j.canlet.2021.10.029.\u003c/li\u003e\n\u003cli\u003eZhang H, Wang SQ, Wang L, Lin H, Zhu JB, Chen R, et al. m6A methyltransferase METTL3-induced lncRNA SNHG17 promotes lung adenocarcinoma gefitinib resistance by epigenetically repressing LATS2 expression. Cell Death Dis. 2022;13(7):657. https://doi.org/10.1038/s41419-022-05050-x.\u003c/li\u003e\n\u003cli\u003eZhang G, Sun J, Zhang X. A novel Cuproptosis-related LncRNA signature to predict prognosis in hepatocellular carcinoma. Sci Rep. 2022;12(1):11325. https://doi.org/10.1038/s41598-022-15251-1.\u003c/li\u003e\n\u003cli\u003eWang F, Lin H, Su Q, Li C. Cuproptosis-related lncRNA predict prognosis and immune response of lung adenocarcinoma. World J Surg Oncol. 2022;20(1):275. https://doi.org/10.1186/s12957-022-02727-7.\u003c/li\u003e\n\u003cli\u003eMai S, Liang L, Mai G, Liu X, Diao D, Cai R, et al. Development and Validation of Lactate Metabolism-Related lncRNA Signature as a Prognostic Model for Lung Adenocarcinoma. Front Endocrinol (Lausanne). 2022;13:829175. https://doi.org/10.3389/fendo.2022.829175.\u003c/li\u003e\n\u003cli\u003eWang L, Li Y, Wang Y, Li J, Sun Y, Chen J, et al. Identification of cuproptosis-related lncRNAs for prognosis and immunotherapy in glioma. J Cell Mol Med. 2022;26(23):5820-31. https://doi.org/10.1111/jcmm.17603.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Table","content":"\u003cp\u003e\u003cstrong\u003eTable 1.\u0026nbsp;\u003c/strong\u003eCorrelation of AL365181.3 expression with clinicopathologic features in LUAD patients.\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"565\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.858657243816253%\"\u003e\n \u003cp\u003eCharacteristics\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.441696113074205%\"\u003e\n \u003cp\u003eLow expression of AL365181.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.681978798586574%\"\u003e\n \u003cp\u003eHigh expression of AL365181.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.017667844522968%\" colspan=\"2\"\u003e\n \u003cp\u003ep\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.911504424778762%\"\u003e\n \u003cp\u003en\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.486725663716815%\"\u003e\n \u003cp\u003e269\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.734513274336283%\"\u003e\n \u003cp\u003e270\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.274336283185841%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"1.592920353982301%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.911504424778762%\"\u003e\n \u003cp\u003ePathologic T stage, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.486725663716815%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"29.734513274336283%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"13.274336283185841%\"\u003e\n \u003cp\u003e0.009\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"1.592920353982301%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.911504424778762%\"\u003e\n \u003cp\u003eT1\u0026amp;T2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.486725663716815%\"\u003e\n \u003cp\u003e244 (45.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.734513274336283%\"\u003e\n \u003cp\u003e224 (41.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.274336283185841%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"1.592920353982301%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.911504424778762%\"\u003e\n \u003cp\u003eT3\u0026amp;T4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.486725663716815%\"\u003e\n \u003cp\u003e24 (4.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.734513274336283%\"\u003e\n \u003cp\u003e44 (8.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.274336283185841%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"1.592920353982301%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.911504424778762%\"\u003e\n \u003cp\u003ePathologic N stage, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.486725663716815%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"29.734513274336283%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"13.274336283185841%\"\u003e\n \u003cp\u003e0.007\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"1.592920353982301%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.911504424778762%\"\u003e\n \u003cp\u003eN0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.486725663716815%\"\u003e\n \u003cp\u003e187 (35.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.734513274336283%\"\u003e\n \u003cp\u003e163 (31.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.274336283185841%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"1.592920353982301%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.911504424778762%\"\u003e\n \u003cp\u003eN1\u0026amp;N2\u0026amp;N3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.486725663716815%\"\u003e\n \u003cp\u003e71 (13.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.734513274336283%\"\u003e\n \u003cp\u003e102 (19.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.274336283185841%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"1.592920353982301%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.911504424778762%\"\u003e\n \u003cp\u003ePathologic M stage, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.486725663716815%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"29.734513274336283%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"13.274336283185841%\"\u003e\n \u003cp\u003e0.066\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"1.592920353982301%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.911504424778762%\"\u003e\n \u003cp\u003eM0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.486725663716815%\"\u003e\n \u003cp\u003e186 (47.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.734513274336283%\"\u003e\n \u003cp\u003e179 (45.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.274336283185841%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"1.592920353982301%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.911504424778762%\"\u003e\n \u003cp\u003eM1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.486725663716815%\"\u003e\n \u003cp\u003e8 (2.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.734513274336283%\"\u003e\n \u003cp\u003e17 (4.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.274336283185841%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"1.592920353982301%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.911504424778762%\"\u003e\n \u003cp\u003ePathologic stage, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.486725663716815%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"29.734513274336283%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"13.274336283185841%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"1.592920353982301%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.911504424778762%\"\u003e\n \u003cp\u003eStage I\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.486725663716815%\"\u003e\n \u003cp\u003e172 (32.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.734513274336283%\"\u003e\n \u003cp\u003e124 (23.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.274336283185841%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"1.592920353982301%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.911504424778762%\"\u003e\n \u003cp\u003eStage II\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.486725663716815%\"\u003e\n \u003cp\u003e47 (8.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.734513274336283%\"\u003e\n \u003cp\u003e78 (14.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.274336283185841%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"1.592920353982301%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.911504424778762%\"\u003e\n \u003cp\u003eStage III\u0026amp;Stage IV\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.486725663716815%\"\u003e\n \u003cp\u003e47 (8.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.734513274336283%\"\u003e\n \u003cp\u003e63 (11.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.274336283185841%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"1.592920353982301%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"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":"AL365181.3, LUAD, prognostic marker, proliferation, migration","lastPublishedDoi":"10.21203/rs.3.rs-4019953/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4019953/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eAs a lncRNA, AL365181.3 is aberrantly expressed in multiple cancer types, including lung adenocarcinoma (LUAD). However, the biological process underlying the ability of AL365181.3 to promote the progression of LUAD is unclear. Here, the pancancer expression level of AL365181.3 was analyzed using the TCGA and GTEx databases, as well as its clinical characteristics and prognostic value. Finally, the in vitro and in vivo biological functions of AL365181.3 in LUAD were revealed by using various functional assays. We found that AL365181.3 was significantly more highly expressed in many types of cancer tissues, including LUAD tissues, than in adjacent normal tissues. LUAD patients with high AL365181.3 expression had poor prognoses. Functional enrichment analyses indicated that AL365181.3 is involved in the regulation of metabolism, MAPK signaling and other tumor regulatory signaling pathways.Finally, we found that knockdown of AL365181.3 reduced the proliferation and migratory capacity of LUAD cells, and knockdown of AL365181.3 resulted in a reduced in vivo tumorigenic capacity of LUAD cells. These findings provide a comprehensive understanding of the role of AL365181.3 in LUAD.\u003c/p\u003e","manuscriptTitle":"Pan-cancer analysis identifies AL365181.3 as a novel prognostic biomarker for lung adenocarcinoma","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-03-07 18:54:26","doi":"10.21203/rs.3.rs-4019953/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":"1dcb60e4-9f16-4e05-a991-701b6fdc7d47","owner":[],"postedDate":"March 7th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-06-11T01:16:22+00:00","versionOfRecord":[],"versionCreatedAt":"2024-03-07 18:54:26","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4019953","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4019953","identity":"rs-4019953","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}