Abstract
Background/Aim: Long non-coding RNAs (lncRNAs) are emerging as significant regulators of gene expression and a novel promising biomarker for cancer diagnosis and prognosis. This study identified a novel, differentially expressed lncRNA in advanced gastric cancer (AGC), Inc-ATMIN-4:2, and evaluated its clinicopathological and prognostic significance. Patients and Methods: Whole transcriptome sequencing was performed to identify differentially expressed lncRNAs in AGC tissue samples. We also analyzed lnc-ATMIN-4:2 expression in 317 patients with AGC using RNA in situ hybridization. Results: High (>30 dots) lnc-ATMIN-4:2 expression significantly correlated with younger age, poorly differentiated histology, diffuse type, deeper invasion depth, perineural invasion, lymph node metastasis, and higher stage group. In addition, high lnc-ATMIN-4:2 expression was significantly associated with worse overall survival in patients with AGC. Conclusion: This study elucidated the significance of lncRNAs in AGC and indicated the value of lnc-ATMIN-4:2 expression as a predictive biomarker for the overall survival of patients with AGC.
- Stomach cancer
- advanced gastric cancer
- long non-coding RNA
- lnc-ATMIN-4:2
- whole transcriptome sequencing
- RNA in situ hybridization
- prognosis
Gastric cancer is the fifth most common malignancy and the fourth leading cause of cancer death worldwide (1). According to global cancer statistics, gastric cancer accounted for over one million new cases (5.6% of all cancer diagnosed) and approximately 769,000 deaths in 2020 (2, 3). Even though advanced treatment approaches such as molecular-targeted therapies and immunotherapy exist, the standard treatment for gastric cancer is perioperative chemotherapy or surgery followed by postoperative chemotherapy (4). The prognosis of patients with gastric cancer remains unfavorable, with five-year overall survival (OS) rates of approximately 30% in Western countries (5). More than 70% of patients with gastric cancer fail to develop specific symptoms during the early stages, and the disease is diagnosed only in the advanced stages (4), denying the patients an opportunity to undergo the most effective surgical treatment (6). Owing to metastases to distant organs, the five-year OS rate of patients with gastric cancer diagnosed in advanced stages is <5% (7). Therefore, identifying potential biomarkers and drug targets is essential for providing novel diagnostic and therapeutic strategies and improving the clinical course and survival rate of patients with advanced gastric cancer (AGC).
With the advent of high-throughput sequencing technologies, most of the human genome was found to be actively transcribed into non-coding RNAs (8). Even though non-coding RNAs, including microRNAs and long non-coding RNAs (lncRNAs), do not encode any proteins, they play significant regulatory functions in the expression of other protein-coding genes (9). LncRNAs are a recently discovered class of non-coding RNAs ranging in length from 200 nucleotides to 100 kilobases (10) and play an essential role in the epigenetic, transcriptional, and post-transcriptional regulation of genes (11, 12). Functional in vitro studies and animal models have indicated that lncRNAs regulate various biological processes, including differentiation and development (13, 14). Interestingly, dysregulated lncRNAs were identified in various tumor tissues compared to corresponding normal tissues, implicating their crucial role in tumorigenesis, progression, and metastasis (15-19). Depending on the fold difference, genes differentially expressed in the normal and tumor tissues are considered candidate genes for biomarkers (20). Moreover, lncRNAs demonstrate cell-, tissue-, and disease-specific expression profiles than any protein-coding genes, suggesting the possible role of lncRNAs as promising biomarkers for cancer diagnosis and prognosis. Increasing evidence also reports a direct correlation between the expression of lncRNAs and the tumor status much better than that of protein-coding genes (21-26).
However, few studies have clinically validated lncRNA signature in AGC. This study compared the lncRNA expression profiles of AGC and normal gastric tissues. We conducted bioinformatic analyses to identify a novel lncRNA among the differentially expressed lncRNAs (DElncRNAs). In addition, we examined the expression of lnc-ATMIN-4:2, a novel lncRNA, in a large number of AGC tissue samples using tissue microarray (TMA) and RNA in situ hybridization (ISH) techniques. Finally, we assessed the clinicopathological and prognostic significance of the expression status of lnc-ATMIN-4:2 in patients with AGC. This study identified and clinically validated the novel lncRNA, lnc-ATMIN-4:2, which could be a candidate prognostic biomarker for patients with AGC.
Materials and Methods
Case selection for whole-transcriptome sequencing. The study protocol was approved by The Korea University Hospital Institutional Review Board (approval number: 2019AN0381). Six tissue samples, including three AGC and the corresponding three non-tumorous gastric tissues, were obtained from the Korea University Anam Hospital Biobank. The non-tumorous tissues were sampled at a significant distance from the tumor (>2 cm). The mean age of the patients with AGC was 65.3 years, with no history of preoperative treatment. Table I summarizes their clinicopathological characteristics. One patient (normal versus tumor 1; NvT 1) was a 75-year-old man whose tumor was a 5.1-cm AGC involving the subserosa. He did not develop distant metastasis or local recurrence. The other two patients (NvT 2 and 3) had bulky tumors measuring >10 cm, pathological tumor stage (pT) of pT4, and demonstrated lymphovascular space invasion and distant metastasis.
Clinicopathological information of three patients with advanced gastric cancer whose tissue samples were used for whole transcriptome sequencing.
RNA isolation, library preparation, and whole transcriptome sequencing. Total RNA was isolated using TRIzol Reagent (Invitrogen, Waltham, MA, USA). RNA quality was assessed by Agilent 2100 Bioanalyzer System (Agilent Technologies, Santa Clara, CA, USA) and RNA 6000 Nano Kit (Agilent Technologies). RNA quantification was performed using NanoDrop 2000 Spectrophotometer (Thermo Fisher Scientific, Waltham, MA, USA). Libraries were prepared from the total RNA using NEBNext Ultra II Directional RNA Library Prep Kit (New England Biolabs, Ipswich, MA, USA). Ribosomal RNA (rRNA) was removed using RiboCop rRNA Depletion Kit (Lexogen, Vienna, Austria). The rRNA-depleted RNAs were used for cDNA synthesis and shearing. Indexing was performed using Index Primer Set 1-12 (Illumina, San Diego, CA, USA). The enrichment step was conducted using polymerase chain reaction (PCR). Subsequently, libraries were analyzed using High Sensitivity DNA Kit (Agilent Technologies) to evaluate the mean fragment size. Quantification was performed using Collibri Library Quantification Kit (Invitrogen) and StepOne Real-Time PCR System (Thermo Fisher Scientific). High-throughput sequencing was conducted as paired-end 100 sequencing bp using NovaSeq 6000 Sequencing System (Illumina).
Sequencing data processing. Quality control of raw sequencing data was performed using FastQC (Babraham Institute, Cambridge, UK). Adapter and low-quality reads (<Q20) were removed using FASTX-Toolkit (Hannon Laboratory, Cold Spring Harbor Laboratory, Huntington, NY, USA) and BBMap (Joint Genome Institute, Berkeley, CA, USA). The trimmed reads were mapped to the reference genome using TopHat (Center for Bioinformatics and Computational Biology, College Park, MD, USA) (27). The expression levels of genes, isoforms, and lncRNAs were estimated using Cufflinks based fragments per kb of transcript per million mapped fragment (FPKM) values (28). The FPKM values were normalized based on the quantile normalization method using edgeR. Data mining was performed using ExDEGA (Ebiogen, Seoul, Republic of Korea). The lncRNAs were selected for further analysis if their log2 fold changes were ≥2.0 or <0.5 and if normalized data were ≥2.0.
Gene Expression Omnibus (GEO) dataset collection for novel lncRNA validation. Microarray datasets from the GEO database (National Institutes of Health, Bethesda, MD, USA) were collected and used to assess the differential expression of lnc-ATMIN-4:2 (also known as NONHSAT143937.2, NONHSAG020094.2, ENST00000501068, and ENSG00000245059). The normalized probe-level intensity files (GSE50710, GSE53137, GSE109476, GSE95667, and GSE93512) were generated by Human Version 2.0 LncRNA Array (Arraystar, Rockville, MD, USA). A total of 27 gastric cancer samples and non-tumorous tissues were collected.
Case selection for TMA construction and RNA ISH. The study protocol was approved by The Korea University Hospital Institutional Review Board (approval number: 2020AN0544). We retrospectively retrieved all surgically resected cases of AGC between January 2009 and December 2012. Patients who received neoadjuvant chemotherapy were excluded from the study. A total of 317 cases of histologically confirmed AGC were included in this study. The following clinicopathological information was collected: age, sex, histological differentiation, Lauren classification, tumor size, pT, lymphovascular invasion, perineural invasion, lymph node metastasis, distant metastasis, local recurrence, and stage group. The latter was determined according to the eighth edition of the American Joint Committee on Cancer Staging Manual (29).
TMA construction. We constructed TMA blocks using AGC tissues as previously described (30). All available hematoxylin and eosin-stained slides were reviewed by two board-certified pathologists, and in each case, the most representative slide areas were marked on the corresponding formalin-fixed paraffin-embedded tissue (FFPE) block. For each case, two 3 mm-diameter cores were extracted from the FFPE block and manually arrayed into recipient TMA blocks. The percentage tumor volume in each core was >70%.
RNA ISH. Single-color RNA ISH was performed using RNAscope 2.5 HD Reagent Kit-RED (Advanced Cell Diagnostics, Newark, CA, USA). Briefly, 4 μm-thick TMA sections were deparaffinized in xylene, followed by dehydration in ethanol. Samples were incubated in citrate buffer, rinsed in water, and treated with Protease Plus (Advanced Cell Diagnostics) at 40°C for 30 min in a HybEZ Hybridization Oven (Advanced Cell Diagnostics). Samples were then incubated with a custom-designed sample probe, followed by Amplifier 1 (30 min), Amplifier 2 (15 min), Amplifier 3 (30 min), and Amplifier 4 (15 min) at 40°C. Amplifiers 5 (30 min) and 6 (15 min) were applied at room temperature. Chromogenic detection was performed using Fast Red dye, followed by counterstaining with hematoxylin. The stained sections were mounted with VectaMount Mounting Medium (Vector Laboratories, Burlingame, CA, USA). The control slide consisted of Human Hela Cell Pellet, and the probes used included a customized 7 ZZ probe named Hs-NONHSAT1439372 (Advanced Cell Diagnostics). Positive and negative control probes were hs-PPIB and dapB (Advanced Cell Diagnostics), respectively.
RNA ISH interpretation. The stained slides were scanned using PANNORAMIC 1000 digital slide scanner (3DHISTECH, Budapest, Hungary). Virtual slide files were opened using CaseViewer (3DHISTECH). Two microscopic areas showing the highest expression were captured at high-power magnification (400×) for each case, and the number of tumor cells and red dots were counted using CellProfiler Version 4.1.3 (Broad Institute, Cambridge, MA, USA). We calculated the number of red dots per 500 tumor cells in two high-power fields. A mean number of red dots was determined as the cut-off value for the dichotomizing lnc-ATMIN-4:2 expression. The case showing >30 dots was classified as a high lnc-ATMIN-4:2 expression group. A ‘very’ high lnc-ATMIN-4:2 expression was defined as >100 dots.
Statistical analysis. The chi-square and Fisher’s exact test were used to examine the association between lnc-ATMIN-4:2 expression and clinicopathological parameters. The Kaplan–Meier plot and log-rank test were used to assess the difference in OS according to the lnc-ATMIN-4:2 expression status. The Cox proportional hazards regression analysis was also used to evaluate the prognostic significance of lnc-ATMIN-4:2 expression. A p-value <0.05 was considered statistically significant. These statistical analyses were performed using IBM SPSS Statistics for Windows, Version 27.0 (IBM, Armonk, NY, USA). Additionally, we used R software Version 4.1.1 (R Foundation for Statistical Computing, Vienna, Austria) and the DEGseq Version 1.48.0 (R Foundation for Statistical Computing), an R package to identify differentially expressed genes or isoforms from different samples, to reveal DElncRNAs in the GEO database and our sequencing data (31-33). When identifying overlapped DElncRNAs in our data, a p-value <0.001 was considered statistically significant.
Results
Identification of DElncRNAs. To identify DElncRNAs, we analyzed the whole transcriptomes of three AGCs and the matched normal gastric tissue samples (NvT 1, NvT 2, and NvT 3) and identified approximately 47,000 lncRNAs in each sample. A Venn diagram was constructed to illustrate the common and exclusive lncRNAs in three samples (Figure 1A), and our results identified fourteen up-regulated and three down-regulated lncRNAs in common. Heatmaps and hierarchical clustering revealed the expression profiles of these 17 commonly dysregulated lncRNAs (Figure 1B). Table II, Table III, and Table IV summarize the differential expression of lncRNAs in AGCs compared to normal controls in NvT 1, NvT 2, and NvT 3, respectively. In particular, three DElncRNAs, including NONHSAT143937.2, NONHSAT158405.1, and NONHSAT222425.1, were overlapped in all samples and were considered candidates for validation (Table V). The latter, a contra-regulated lncRNA, was excluded from further analysis. Two pT4 AGCs with unfavorable clinicopathological features, including larger tumor size, higher invasion depth, lymphovascular invasion, and distant metastasis, showed higher fold changes (15.769 and 15.619 in NvT 2 and NvT 3, respectively) of NONHSAT143937.2 than pT3 AGC tumor (NvT 1, 4.638). In contrast, the fold changes of NONHSAT158405.1 in NvT 3 (5.903) were lower than that in NvT 1 (10.346). The differences in fold changes of NONHSAT143937.2 better reflected the oncogenic behavior in NvT 1, NvT 2, and NvT 3 than NONHSAT158405.1.
Overview of long non-coding RNAs (lncRNAs) identified in advanced gastric cancer (AGC). (A) Venn diagram illustrating the number of dysregulated lncRNAs in three AGC tissue samples (NvT 1-3). A total of 47 lncRNAs were found to overlap in all samples. Among these, 14 lncRNAs were up-regulated (red), and three were down-regulated (green). (B) Heatmap representing the expression profiles of the 17 overlapped lncRNAs across the samples. We found a novel lncRNA NONHSAT143937.2 (red), also known as lnc-ATMIN-4:2.
A list of differentially expressed long non-coding RNAs in patient NvT 1.
A list of differentially expressed long non-coding RNAs in patient NvT 2.
A list of differentially expressed long non-coding RNAs in patient NvT 3.
Three overlapped differentially expressed long non-coding RNAs.
Bioinformatic analysis for lnc-ATMIN-4:2 validation. We identified NONHSAT143937.2 as lnc-ATMIN-4:2 (LNCipedia transcript ID), lnc-ATMIN-4 (LNCipedia gene ID), ENSG000 00245059 (Ensembl gene ID), and ENST00000501068 (Ensembl transcript ID), and validated the novel lncRNA using GEO database (National Institutes of Health). The results showed five datasets, including GSE50710, GSE53137, GSE109476, GSE95667, and GSE93512, containing 27 pairs of gastric cancer and normal gastric tissues. As shown in Table VI, in 10 of the 27 cases (37.0%), gastric cancer tissues showed higher lnc-ATMIN-4:2 expression than normal tissues.
Differential expression of lnc-ATMIN-4:2 in gastric cancer data obtained from the Gene Expression Omnibus database.
Patient demographics. This study included 205 males (64.7%) and 112 females (35.3%). The mean age of patients was 60.3 years (range=26-87). Twenty-nine (9.1%), 107 (33.8%), and 181 (57.1%) patients were diagnosed with well, moderately, and poorly differentiated adenocarcinoma, respectively. According to the Lauren classification, 166 (52.4%) cases were diffuse type. Tumors measuring >6 cm were in 124 (39.1%) cases. Seventy-one (22.4%) cases were pT2 tumors, 155 (48.9%) were pT3, and 91 (28.7%) were pT4. Eighty-eight (27.8%) and 188 (59.3%) cases showed perineural and lymphovascular invasion, respectively. Two hundred and 29 patients (72.2%) had lymph node metastases. Nineteen patients (6.0%) developed distant metastases. The median follow-up time was 43 months (range=1-99).
Clinicopathological and prognostic significance of lnc-ATMIN-4:2. RNA ISH was performed to examine the lnc-ATMIN-4:2 expression and to evaluate its clinicopathological and prognostic significance in 317 patients with AGC. The mean number of lnc-ATMIN-4:2-positive red dots per 500 tumor cells ranged 0.4-295.1 (mean=32.2 dots). Low lnc-ATMIN-4:2 expression (≤30 dots) was identified in 221 cases of AGC (69.7%; Figure 2A), while 96 cases (30.3%) exhibited high lnc-ATMIN-4:2 expression (>30 dots; Figure 2B). Among these, very high expression of lnc-ATMIN-4:2 expression (>100 dots) was observed in 25 cases (7.8%). High lnc-ATMIN-4:2 expression was significantly associated with younger age (p=0.007) and unfavorable clinicopathological parameters, including poorly differentiated histology (p=0.047), diffuse type (p=0.012), deeper invasion depth (p=0.002), presence of perineural invasion (p=0.017), lymph node metastasis (p=0.012), and higher stage group (p=0.004) (Table VII).
lnc-ATMIN-4:2 expression evaluated by RNA in situ hybridization and its prognostic significance in patients with advanced gastric cancer (AGC). (A-B) Representative images of hematoxylin-and-eosin-stained AGC sections obtained from the tissue microarray blocks (inset in the right lower corner). Original magnification: 100×. Representative RNA in situ hybridization images of (C) low lnc-ATMIN-4:2 expression and (D) high lnc-ATMIN-4:2 expression visualized as punctate red dots. Original magnification: 400×. (E) Kaplan–Meier plots showing a significantly lower overall survival rate of patients with AGC whose tumors exhibit high lnc-ATMIN-4:2 than that of lnc-ATMIN-4:2-low AGC patients (p=0.034). (F) Kaplan–Meier plots showing significant differences (p=0.024) in overall survival between patients with AGC exhibiting low, high, and very high lnc-ATMIN-4:2 expression.
Clinicopathological significance of lnc-ATMIN-4:2 expression status in advanced gastric cancer.
OS of patients with AGC whose tumors showed high lnc-ATMIN-4:2 expression was significantly lower than that of lnc-ATMIN-4:2-low AGC patients (p=0.034; Figure 2C). When the cases were classified into very high, high, and low expression subgroups, the difference in OS was also significant (p=0.024; Figure 2D). Cox regression analysis revealed that AGCs showing high lnc-ATMIN-4:2 expression had significantly worse OS than those with low expression [hazard ratio (HR)=1.678; 95% confidence interval (CI)=1.034-2.724; p=0.036]. Other clinicopathological parameters associated with worse OS were diffuse type (HR=1.865; 95% CI=1.136-3.062; p=0.014), larger tumor size (HR=2.843; 95% CI=1.761-4.588; p<0.001), higher pT (HR=3.702; 95% CI=2.279-6.013; p<0.001), lymphovascular invasion (HR=2.675; 95% CI=1.544-4.634; p<0.001), perineural invasion (HR=2.242; 95% CI=1.378-3.650; p =0.001), lymph node metastasis (HR=2.301; 95% CI=1.255-4.219; p=0.007), and higher stage group (HR=3.453; 95% CI=1.966-6.062; p<0.001).
Discussion
With the high-throughput sequencing technologies of the whole human mammalian transcriptomes, it became evident that only 20,000 genes (<2%) are protein-coding, while at least 75% are actively transcribed into non-coding RNAs (34-37). Identifying aberrant expression of specific lncRNAs could be exploited to develop novel diagnostic biomarkers and may be associated with aggressive oncogenic behavior and poor patient outcomes (38). Therefore, an in-depth understanding of the mechanisms of lncRNA dysregulation may providea better therapeutic strategy. According to a recent meta-analysis on lncRNAs, in a total of 6,095 gastric cancer patients (39), the expression of 19 lncRNAs is documented in 51 articles. Most of these candidate lncRNAs efficiently predicted the prognosis of patients with AGCs, and included actin filament-associated protein 1 antisense RNA 1 (AFAP-AS1), colon cancer-associated transcript 2 (CCAT2), homeobox A transcript antisense RNA (HOTAIR), homeobox A transcript cluster distal transcript antisense RNA (HOTTIP), long intergenic non-protein-coding RNA 673 (LINC00673), metastasis-associated lung adenocarcinoma transcript 1 (MALAT1), promoter of cyclin-dependent kinase inhibitor 1A antisense DNA damage activated RNA (PANDAR), plasmacytoma variant translocation 1, (PVT1) sex-determining region Y-box 2 overlapping transcript (Sox2ot), zinc finger E-box binding homeobox 1-antisense RNA 1 (ZEB1-AS1), zinc finger nuclear transcription factor, and X box binding, and 1-type containing 1 antisense RNA 1 (ZFAS1) (35, 39-41). However, the smaller sample size available for the validation and the lack of reliability in the prognostic prediction of AGC pose a concern and are considered limitations. To the best of our knowledge, we identified for the first time a novel lncRNA, lnc-ATMIN-4:2, in AGC. We performed RNA ISH to determine the expression of lnc-ATMIN-4:2 in 317 AGC tissue samples and demonstrated its clinicopathological and prognostic significance. We observed that high lnc-ATMIN-4:2 expression significantly correlated with younger age, diffuse type of Lauren classification, deeper invasion depth, perineural invasion, lymph node metastasis, and higher stage group. Survival analysis revealed that patients with AGC, whose tumors exhibit high and a “very” high lnc-ATMIN-4:2 expression, had significantly worse OS than patients with lnc-ATMIN-4:2-low AGC.
The lnc-ATMIN-4:2 is located on chromosome 16q23.2, and its biological function remains largely unknown. Nevertheless, DIANA-LncBase Version 3.0 (https://diana.e-ce.uth.gr/lncbasev3; University of Thessaly, Volos, Greece) suggested a potential miRNA-lncRNA interaction between microRNA-34a (miR-34a) and lnc-ATMIN-4:2 in human colorectal carcinoma cell line HCT116 (42). The lncRNAs are known to interact with DNA and proteins, alter gene expression, and play a vital role in tumorigenesis (43, 44). Dysregulated miR-34a has been associated with epithelial–mesenchymal transition, tumor progression, and metastasis in many types of human cancers (45, 46). Moreover, miR-34a has been reported to have the potential to serve as diagnostic and prognostic biomarker in various human cancers, including gastric (47-50) and breast cancers (51, 52). In this study, however, we failed to observe any evidence of miR-34a dysregulation or its interaction with lncRNA in our sequencing data. Further investigation is essential to validate the mechanism of lncRNA:miR regulation in AGC associated with lnc-ATMIN-4:2.
To understand the lncRNA-protein molecular interactions, we sought for proteins potentially interacting with lnc-ATMIN-4:2 using RNAct, a database of the RNA–protein interactome, and catRAPID, a computationally expensive method for predicting potential lncRNA-protein interactions (53). The following seven protein-coding genes were implicated in strong positive prediction and expressed aberrantly in human cancers: nischarin (NISCH), retinoblastoma 1 (RB1)-inducible coiled-coil 1 (RB1CC1), ATP-binding cassette, sub-family C member 9 (ABCC9), damage-specific DNA binding protein 1 and cullin 4-associated factor 8 like 2 (DCAF8L2), DnaJ heat shock protein family member C5 beta (DNAJC5B), zinc finger CCHC-type containing 6 (ZCCHC6), and bromodomain-containing protein 4-interacting chromatin remodeling complex-associated protein (BICRA). NISCH, a tumor suppressor gene, was significantly down-regulated in advanced-stage ovarian cancer (49). RB1CC1 is also a tumor suppressor gene that regulates RB1 protein expression and activates the p16 promoter to enhance the RB1 pathway (54). The immunohistochemical expression of nuclear RB1CC1 protein significantly correlated with RB1 expression in breast cancer tissue samples (55). ABCC9 expression varied among different tissues and organs. High ABCC9 expression was significantly associated with poor prognosis in gastric cancer patients (53), while this gene was significantly down-regulated in prostate (56), ovarian (57), and breast cancers (58). The DCAF8L2, DNAJC5, ZCCHC6, and BICRA genes were aberrantly over-expressed in various human cancers (59-62). Further experimental and molecular verifications for these cancer-related genes are required to disclose the potential RNA-protein interactions and their mechanisms.
Our study had a few limitations. First, we investigated DElncRNAs in three AGCs and matched normal gastric tissue samples. The small number of cases for whole-transcriptome sequencing may be a limit to reliable results. However, to compensate for this limitation, we collected the data on lnc-ATMIN-4:2 expression in gastric cancer from the GEO database. Analysis of the five GEO datasets revealed high lnc-ATMIN-4:2 expression in 10 of the 27 gastric cancer cases (37.0%). Second, the GEO datasets did not consist exclusively of AGC cases. Even though the cases labeled as early gastric cancer were eliminated, we could not completely rule out the possible presence of early-stage disease due to the insufficient clinical information. To validate the up-regulated lnc-ATMIN-4:2 expression in AGC, we performed RNA ISH using TMA blocks containing more than 300 cases of AGC. We observed 30.3% (96/317) of the cases displaying high lnc-ATMIN-4:2 expression, which was a similar percentage to that observed in the result of GEO database analysis. Significant associations of high lnc-ATMIN-4:2 expression with adverse clinicopathological parameters and worse survival of patients with AGC were noted.
In conclusion, we identified a novel lncRNA, lnc-ATMIN-4:2, in AGC tissues. Further, we demonstrated that high lnc-ATMIN-4:2 expression determined by RNA ISH was associated with unfavorable clinicopathological parameters and could predict the OS of patients with AGC. Our observations suggest that lnc-ATMIN-4:2 expression status could be used as a novel prognostic biomarker for patients with AGC. Further studies are warranted to clarify the biological function of lnc-ATMIN-4:2 in gastric cancer.
Acknowledgements
This research was supported by the Bio and Medical Technology Development Program of the National Research Foundation (NRF) funded by the Korean government (MSIT) (2019M3E5D1A02068558) and a grant of the Korea health Technology R&D Project through the Korea Health Industry Development Institute (KHIDI) funded by Ministry of Health & Welfare, Republic of Korea (HR20C0025).
Footnotes
Authors’ Contributions
All Authors made substantial contributions to the conceptualization and design of the study; the acquisition, analysis, interpretation, and validation of the data; drafting of the article; critical revision of the article for important intellectual content; and the final approval of the version to be published.
Conflicts of Interest
The Authors have no conflicts of interest to declare.
Data Availability
The dataset has been deposited to the National Center for Biotechnology Information (NCBI) Gene Expression Omnibus (GEO) located at: <https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE210909>
- Received August 8, 2022.
- Revision received September 21, 2022.
- Accepted September 26, 2022.
- Copyright © 2022 The Author(s). Published by the International Institute of Anticancer Research.
This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY-NC-ND) 4.0 international license (https://creativecommons.org/licenses/by-nc-nd/4.0).
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