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. 2025 Aug 21;11(1):2547557. doi: 10.1080/20565623.2025.2547557

LINC00313 functions as an oncogenic propellant and immunosuppressive marker in lung adenocarcinoma

Wen Wang a, Yanhui Cui b, Jianfu Heng c, Jingjing Li d, Guoli Li e,f,g,✉
PMCID: PMC12372514  PMID: 40838586

Abstract

Background

Despite advances in treatments, the prognosis for lung adenocarcinoma (LUAD) remains poor, underscoring the urgent need to identify novel therapeutic strategies. This study was conducted to investigate the potential role of LINC00313 as a biomarker and therapeutic target for LUAD.

Methods

Databases GEPIA2 and GEO were used to analyze LINC00313 expression and prognosis. Analyses of pathways associated with LINC00313, and its relationships with immune infiltration, checkpoint therapy response and drug response were conducted using different bioinformatics tools. siRNA transfection, qRT-PCR, transwell and colony formation assays were performed on LUAD cells (A549).

Results

LINC00313 is significantly upregulated in LUAD, and its expression is associated with high-grade cancer, poor prognosis and metastasis. In vitro studies showed that silencing LINC00313 reduced LUAD cell migration, invasion, and colony formation. Bioinformatics analyses indicated that LINC00313 expression was negatively associated with immune cell infiltration and the efficacy of immune checkpoint inhibitor therapy. Sensitivity analysis of chemotherapeutic drugs found that high expression of LINC00313 attenuated the effect of chemotherapeutic drugs like cisplatin, dabrafenib and lapatinib on LUAD.

Conclusions

In conclusion, LINC00313 holds potential as a valuable biomarker and therapeutic target for the treatment of LUAD. However, further research is warranted to fully elucidate its clinical applications.

Keywords: Lung adenocarcinoma, long non-coding RNAs, LINC00313, tumor immunology therapy, biomarker

PLAIN LANGUAGE SUMMARY

Lung adenocarcinoma (LUAD) is the most common type of lung cancer, but survival rates remain low despite many available treatments. This study investigated a molecule called LINC00313 to see if it could be used as a marker or target for treating LUAD. We used databases like GEPIA2 and GEO to look at how much LINC00313 is present in LUAD tissues compared to normal lung tissues. We also used computer tools to study how LINC00313 might affect cancer cell behavior, immune responses, and drug effectiveness. In the lab, we tested how silencing LINC00313 affected the growth and spread of LUAD cells. Our results showed that LINC00313 is much higher in LUAD tissues than in normal tissues. High levels of LINC00313 were linked to more aggressive cancer, worse outcomes, and spread to other parts of the body. When we turned off LINC00313 in the lab, the cancer cells were less able to move, invade, and form colonies. Our analysis also suggested that LINC00313 affects cell adhesion and immune signals, and it seems to make LUAD cells less responsive to certain chemotherapy drugs. Overall, LINC00313 could be a useful marker or target for treating LUAD, but more research is needed to fully understand how it can be used in the clinic.

ARTICLE HIGHLIGHTS

  • LINC00313 is significantly overexpressed in LUAD tissues compared to normal tissues, correlating strongly with high-grade cancer, poor patient prognosis, and metastasis.

  • Silencing of LINC00313 in LUAD cells significantly reduces cell migration, invasion, and colony formation in vitro.

  • Bioinformatics analyses link LINC00313 overexpression to dysregulation of cell adhesion-related signals and immune-related signaling pathways, potentially driving tumor progression.

  • High LINC00313 expression is associated with reduced immune cell infiltration, poorer response to immune checkpoint inhibitor therapy, and attenuated efficacy of chemotherapeutic drugs.

  • These findings strongly support LINC00313 as a promising biomarker for prognosis and a potential therapeutic target for LUAD.

Introduction

Lung cancer is the leading cause of cancer-related deaths worldwide [1]. Of all lung cancer cases, nearly 85% are non-small-cell lung carcinoma (NSCLC), and nearly 15% are small-cell lung carcinoma (SCLC) [2]. Lung adenocarcinoma (LUAD) belongs to NSCLC and is considered the most common primary lung cancer, accounting for nearly 40% of all lung cancer cases [3]. LUAD is thought to originate from either alveolar type II epithelial cells or Clara cells, which are located in the bronchiole [4]. Although tobacco smoking is the most important risk factor for lung cancer, other factors, including cooking fume exposure, mental stress, and high-fat diets, have also been proposed [5]. LUAD can be treated with surgical resection, radiotherapy, immunotherapy, and systemic therapy [2]. Nevertheless, despite these treatment options, the overall survival (OS) rate for LUAD is, in general, very poor, underscoring the necessity of further research to find new predictive markers and therapeutic approaches.

Over the past 15 years, researchers have identified various oncogenic drivers of LUAD that have contributed to the paradigm shift in treatment approaches [6]. Long non-coding RNAs (lncRNAs) are one of the most exciting molecules that can be employed for therapeutic purposes [7]. LncRNAs are defined as transcripts > 200 nucleotides in length with non-protein-coding potential, typically ranging from 1,000 to 10,000 nucleotides, representing a subgroup of non-coding RNAs (ncRNAs) [8]. More than 20000 annotated lncRNAs have been identified in the human genome [9]. Previous studies have indicated that lncRNA exhibits tissue-specific expression [9]. To date, over 700 lncRNAs have been implicated in cancer, with at least 2,500 lncRNAs exhibiting altered expression levels in tumors compared to their matched normal tissues [7].

LINC00313 was one of the lncRNAs located on chromosome 21 at the 21q22.3 region [10]. Previous studies have found that it was highly expressed in several cancers [11–14]. However, the exact role of LINC00313 as a prognostic biomarker and therapeutic target for LUAD has not been fully characterized. Herein, the current study aims to elucidate the role of LINC00313 in the malignant behaviors of LUAD and its potential as a predictor for immunotherapy outcomes in LUAD patients.

Methods

LINC00313 expression assay and prognostic analysis

The Gene Expression Profiling Interactive Analysis (GEPIA2, http://gepia2.cancer-pku.cn/#index) were used to analyze the expression levels of LINC00313 in lung squamous cell carcinoma (LUSC), LUAD, and normal lung tissues. A differential LINC00313 expression analysis of tissue RNA-sequencing data was obtained from the GEPIA2 sourced from TCGA and the GTEx databases. The analytical strategies were performed as previously described [15]. A differential LINC00313 expression analysis of tissue array-based data was obtained from the lnCAR sourced from the Gene Expression Omnibus (GEO) database (LUAD #GSE43458, LUAD #GSE43767, LUSC #GSE33479, NSCLC #GSE33532, and NSCLC #GSE51852). The latest retrieval time of GEPIA and GEO databases was up to May 17, 2024, and the analytical strategies were performed on as previously described [16]. Given that the abundance of LINC00313 is relatively low, we did not set the threshold for significant difference based on |logFC| >1 and p < 0.05. Instead, we conducted the analysis in the GEPIA2 and GEO databases solely using p < 0.05 as the criterion. BEST online tool (https://rookieutopia.com/app_direct/BEST/) was used to analyze the correlation between LINC00313 expression and LUAD stage and lymph node metastasis. The differential LINC00313 expression analysis of the lung tissue single-cell RNA-sequencing data (matrix data and metadata) was obtained from the GEO database (#GSE131907) and analyzed using the Seurat package of R software. The “DotPlot” function and “VlnPlot” function were used to visualize. To validate the prognostic value of LINC00313, the Kaplan-Meier Plotter (http://kmplot.com/analysis/index.php?p= background) platform was used to assess the effect of LINC00313 on survival in LUAD. Sources for the databases included GEO, EGA, and TCGA. The relationships between the LINC00313 expression and patient prognosis, such as the overall survival (OS) and relapse-free survival (RFS), were assessed as previously described [17].

Cell culture and transfection

The human LUAD cell line, A549, was purchased from ATCC (Manassas, VA, USA) and cultured in Dulbecco’s Modified Eagle Medium (DMEM) (Gbico) supplemented with 10% fetal bovine serum (FBS), and this was maintained in an incubator supplemented with 5% CO2 at 37 °C. The LINC00313-targeted small interfering RNA (siRNA) was used to knock down the LINC00313 expression level in A549, and this was purchased from RiboBio (Guangzhou, China). Cell transfection was performed as previously described [18]. The sequences of LINC00313-targeted siRNA were as follows: LINC00313-siRNA-1: GCTTCCTGGATTGCATAAA; LINC00313-siRNA-2: GGCTCCTTCTCCTTACATA.

qRT-PCR analysis

The total RNA was extracted from the A549 cells using TRIzol reagent (Invitrogen) and then converted into cDNA. qRT-PCR was performed as per the manual of the Transcriptor First-strand cDNA synthesis Kit (Roche, USA). The relative gene expression was calculated as per the 2−ΔΔCt method.

Transwell assay

To assess the migration and invasion ability of the LINC00313-silenced cells, the A549 cells (2 × 104 cells per well) were plated into the upper chamber supplemented with RPMI1640 containing 2% FBS after 48 h of transfection of the LINC00313-targeted siRNA. A total of 800 μL of RPMI1640 supplemented with 12% FBS was plated into the lower chamber and added to the complete medium. The bottom of the upper chamber was an 8-μm pore transwell apparatus coated with or without Matrigel (Corning Incorporated, Corning, NY). After 24 h, the number of migrated cells was counted under a microscope. The cells were fixed and stained with 0.5% crystal violet.

Colony formation assay

The transfected cells were planted at 1,000 cells/well into the 6-well plates, cultured in DMEM supplemented with 10% FBS. Two weeks later, the cells were fixed with 4% paraformaldehyde and stained with 0.5% crystal violet. The number of colonies was counted under a microscope.

Analysis of LINC00313-related signaling pathways

Using the ASSISTANT for Clinical Bioinformatics (https://www.aclbi.com/static/index.html#/) online tool, the samples were divided into LINC00313 high-expression group and low-expression group based on TCGA LUAD data, differential analysis was performed, and volcano plot and heat map of differential genes were drawn. Also based on this tool, GO and KEGG enrichment analysis of differential genes was performed. The co-expressed genes of the LINC00313 analysis of the tissue array-based data were obtained from the lnCAR sourced from the GEO database. The analytical strategies were performed as previously described [16]. The co-expressed genes of LINC00313 were visualized using lnCAR software. The lncLocator online tool (http://www.csbio.sjtu.edu.cn/bioinf/lncLocator/#) was used to predict the sub-cellular localization of LINC00313 [19]. The analytical strategies and functional enrichment analysis were performed as previously described [20].

Immune-related analysis

The immune cell infiltration analysis was conducted using the TIMER algorithm via the ASSISTANT tool (https://www.aclbi.com/static/index.html#/) [21]. This tool was used to predict the correlation between LINC00313 expression and immune cell infiltration of the subtype of immune cells (B cells, CD4+ T cells, CD8+ T cells, neutrophils, macrophages, and dendritic cells) as well as immune checkpoint molecules based on the TCGA LUAD cohort. The abundance levels of each immune cell type and the expression levels of LINC00313 were separately log2-transformed. The correlation between immune cell abundance and LINC00313 expression was analyzed using the Spearman correlation coefficient. The significance of differences in immune cells and immune checkpoint genes between the G1 and G2 groups was assessed using the Wilcoxon rank – sum test. The ImmLnc platform was used to predict the correlation between LINC00313 and immune-related signaling pathways (http://bio-bigdata.hrbmu.edu.cn/ImmLnc/index.jsp). The analytical strategies were performed as previously described [22]. ASSISTANT for Clinical Bioinformatics was used to assess the predictive value of LINC00313 in the immune therapeutic reaction, and the data were sourced from the TCGA database. Kaplan–Meier Plotter (http://kmplot.com/analysis/index.php?p= background) platform was used to assess the effect of LINC00313 on survival in immunotherapy cohort.

Analysis of the anticancer drug response

The ASSISTANT for Clinical Bioinformatics (https://www.aclbi.com/static/index.html#/) online tool was used to evaluate LINC00313 expression in the responder tissue or in the non-responder tissue after immune checkpoint inhibitors, and it is based on the TCGA database (LUAD datasets). The differences in genomic variation and chemotherapeutic drug susceptibility between samples from the high-expression group and the low-expression group of LINC00313 were also completed by ASSISTANT for Clinical Bioinformatics https://www.aclbi.com/static/index.html#/) online tool. The Tumor Immune Dysfunction and Exclusion (TIDE) module was used to evaluate the therapeutic efficacy of immune checkpoint inhibitors.

Statistical analysis

The data are shown as means ± standard deviations from three independent replicates. A t-test was performed to compare the difference between the two controls and the LINC00313-silenced group. P values <0.05 were regarded as significant. For comparisons between two groups of samples, a t-test was used; for comparisons among three or more groups of samples, the Kruskal–Wallis test was employed. The Log-Rank test was used for comparing survival rates between two groups. Correlation analysis was performed using Spearman’s Rank Correlation Coefficient. The chi-square test was used for comparing the proportions between two groups of samples. The Wilcoxon test was employed for comparing the data distribution between two groups of samples.

Results

LINC00313 was upregulated and displayed a prognostic value in LUAD

A total of 1078 (LUAD: 483 tumor cases vs. normal 59 cases; LUSC: 486 tumor cases vs. 50 normal cases) RNA-sequencing datasets derived from the GEPIA2 were used to assess the expression of LINC00313. We found that LINC00313 was significantly upregulated in the LUAD tissues as compared to normal lung tissues, while there was no significant difference observed between the LUSC tissues and normal lung tissues (Figure 1(A)). The array-based data were obtained from the GEO database and visualized using lnCAR. We also found that LINC00313 was significantly upregulated in the LUAD tissues as compared to the normal lung tissues (Figure 1(B) and Supplementary Fig. 1(A and B)), whereas no significant difference was observed in the LUSC tissues as well as in the NSCLC tissues (Figure 1(C) and Supplementary Fig. 1(C and D)). We calculated the ratio of LINC00313 expression in the high-grade cancer to the LINC00313 expression in the low-grade cancer, and found that, among the 18 cancer types, the ratio was greater than one only in the LUAD tissues (Figure 1(D)). In addition, the expression of LINC00313 was increased with the stage in LUAD patients (GSE13213, GSE72094, Figure 1(E)) and increased with the number of metastatic lymph nodes in LUAD patients (GSE13213, TCGA LUAD, Figure 1(F)). Although it did not reach the statistically significant level in the TCGA LUAD dataset, the trend is there. These findings indicated that LINC00313 may be involved in tumorigenesis and in the development of LUAD.

Figure 1.

Figure 1.

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LINC00313 was upregulated and displayed a prognostic value in LUAD. (A) LINC00313 was significantly upregulated in LUAD as compared to the normal lung tissues, while there was no significant difference observed in the LUSC tissues and normal lung tissues. (B) LINC00313 was significantly upregulated in LUAD tissues (#GSE43458 and #GSE43767). (C) there was no significant difference in LINC00313 expression in the LUSC tissues (#GSE33479) and the NSCLC tissues (#GSE33532 and #GSE51852). (D) The ratio of LINC00313 expression in the high-grade cancer to the LINC00313 expression in the low-grade cancer. The darker the green, the smaller the value; The darker the orange, the larger the value. (E) The expression of LINC00313 was increased with the stage in LUAD patients (GSE13213, GSE72094). (F) The expression of LINC00313 was increased with the number of metastatic lymphonodus in LUAD patients (GSE13213, TCGA_LUAD). LUAD, Lung adenocarcinoma; LUSC, Lung squamous cell carcinoma. Based on the RNA-sequencing datasets in TCGA, high LINC00313 expression was associated with a shorter OS time in all the LUAD patients (G) and in female LUAD patients (H), but was not associated with OS time in male LUAD patients (I).

The prognostic value of LINC00313 in LUAD was assessed using the Kaplan-Meier Plotter. We found that a high LINC00313 expression was associated with shorter OS time in all of the LUAD RNA-sequencing datasets (Figure 1(G); HR = 1.54, 95% CI = 1.13–2.08, log-rank P = 0.0052). Notably, a high LINC00313 expression was significantly associated with poor prognosis in female patients with LUAD (Figure 1(H); OS HR = 2.05, 95% CI = 1.34–3.12, log-rank P = 0.00067). However, LINC00313 expression was not significantly associated with poor prognosis in male patients with LUAD (Figure 1(I); OS HR = 1.25, 95% CI = 0.8–1.94, log-rank P = 0.32). The array-based data were obtained from the GEO database and visualized using the Kaplan–Meier Plotter. This showed that a high LINC00313 expression was associated with a short OS time in LUAD (Supplementary Fig. 2A; HR = 1.44, 95% CI = 1.11–1.85, log-rank P = 0.0049). Similarly, a high LINC00313 expression was significantly associated with a poor prognosis in female patients with LUAD (Supplementary Fig. 2B; OS HR = 2.03, 95% CI = 1.33–3.1, log-rank P = 0.00082), whereas high LINC00313 expression was not significantly associated with poor prognosis in male patients with LUAD (Supplementary Fig. 2C; OS HR = 0.73, 95% CI = 0.52–1.03, log-rank P = 0.074).

Knockdown of LINC00313 inhibits cell migration, invasion, and colony formation

The expression of LINC00313 at the single-cell level was assessed using the LUAD tissue single-cell RNA-sequencing data (#GSE131907). This showed that LINC00313 was highly enriched in the epithelial cells (Figure 2(A)). We further analyzed the sub-type of the epithelial cell in detail based on its origin, revealing that the highest levels of LINC00313 were observed in the lung tumor cells (Figure 2(B)). To investigate whether the downregulation of LINC00313 favored the transformed phenotype, the ability of migration and colony formation was assessed in vitro. We performed qRT-PCR, and this showed that the A549 cells expressed significantly low levels of LINC00313 after transfection with LINC00313-targeted siRNA1 (Figure 2(C)). When the LINC00313-silenced A549 cells were plated into the transwell upper chamber, they presented a decreased ability to migrate and invade (Figure 2(D)). To test the colony formation capacity of the LINC00313-silenced A549 cells, the number of the colony formations was counted under a microscope. We found that the colony formation capacity was reduced when LINC00313 was silenced in the A549 cells (Figure 2(E)). The number of colony formations was significantly reduced in the LINC00313-silenced A549 cells as compared to the control cells (Figure 2(F)).

Figure 2.

Figure 2.

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Knockdown of LINC00313 inhibited the aggressiveness of the A549 cells. (A) LINC00313 was most enriched in the epithelial cells according to the single-cell RNA sequencing data. (B) The highest level of LINC00313 was observed in lung tumor cells. mBrain: brain metastases. mLN: lymph node metastases. nlung: normal tissues from lungs. PE: pleural fluids. tL/B: cancer tissue − derived whole cells from lymph node. tlung: cancer tissue − derived whole cells from lung. (C) A549 cells expressed significantly low levels of the LINC00313 after transfection of LINC00313-targeted siRNA1, as evidenced by qRT-PCR. (D) Representative images of migrating cells (upper) and invading cells (below). The number of migrating and invading cells was counted from the images of five random fields per transwell. (E) Representative images of colony formation assays. (F) The number of colonies formed was counted under a microscope. *P < 0.05, ***P < 0.001.

LINC00313 was negatively associated with immune cell infiltration

By analyzing the related genes and signaling pathways of LINC00313 (Figure 3(A and B)), we found that the effect of LINC00313 on the migration and invasion of LUAD may be due to the regulation on cell adhesion-related signals and many immune-related signaling pathways (Figure 3(C)). Besides, the results also indicated that LINC00313 promoted the progression of LUAD, which may be involved in immune cell infiltration (Figure 3(D)).

Figure 3.

Figure 3.

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LINC00313-related genes and signaling pathways. Based on the TCGA LUAD cohort data, the ASSISTANT for Clinical Bioinformatics online tool were used to analyze the differential genes of LUAD grouped by LINC00313 high and low. (A–B) Volcano map (A) and Heatmap (B) shows the LINC00313-associated differential genes. G1: high LINC00313 expression; G2: low LINC00313 expression. (C–D) KEGG enrichment analysis (C) and GO enrichment analysis (D) of differential genes.

Immune cell infiltration is beneficial to improve the prognosis of cancer patients. To investigate the roles of LINC00313 in immune regulation, correlation analyses were conducted based on the LUAD datasets using the ASSISTANT for Clinical Bioinformatics and ImmLnc online tools. We assessed the correlation between six tumor-infiltrating immune cells (B cells, CD4+ T cells, CD8+ T cells, neutrophils, macrophages, and dendritic cells) and LINC00313 expression, showing that the LINC00313 expression was significantly negatively associated with B cells, CD4+ T cells, CD8+ T cells, neutrophils, macrophages, and dendritic cells in LUAD (Figure 4(A)), and low TIMER score in B cells, CD4+ T cells, CD8+ T cells, neutrophils, macrophages, and dendritic cells was present in high LINC00313 expression group (Figure 4(B)). Additionally, immune checkpoint molecules expression was significantly low in high LINC00313 expression group (Figure 4(C)). These results were also confirmed in GEO dataset GSE72094 (Supplementary Fig. 3).

Figure 4.

Figure 4.

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LINC00313 correlates with immune cell infiltration and immunotherapy response in LUAD. Based on the TCGA LUAD data, the ASSISTANT for Clinical Bioinformatics online tool were used to analyze the correlation between LINC00313 and the abundance of immune cells (A), the abundance of immune cells (TIMER score) (B), and the difference in the expression of immune checkpoint molecules (C) in the LINC00313 high expression group (G1) and low expression group (G2) samples. (D) Based on TCGA LUAD data, the relationship between LINC00313 expression and immunotherapy response was analyzed using the ASSISTANT for Clinical Bioinformatics online tool. LINC00313 shows a significantly lower expression in the LUAD tissues after treatment with the immune checkpoint inhibitors. TIDE: Tumor Immune Dysfunction and Exclusion. Based on Anti-PD1 cohort data, the Kaplan-Meier Plotter online tool was used to analyze the correlation between LINC00313 expression and the immune checkpoint inhibitors. Relationship between overall survival (E) and progression-free survival (F) in this cohort of patients was shown.

Immune checkpoint inhibitors, molecular targeted agents, and chemotherapeutic drugs are the most effective methods for treating LUAD. As expect, the LINC00313 expression was significantly correlated with multiple immune-related pathways based on the LUAD datasets (Supplementary Fig. 4). We found that LINC00313 showed significantly lower expression in the responder LUAD tissues as compared to the non-responder LUAD tissues after treatment with immune checkpoint inhibitors (Figure 4(D)). Based on the cohort data of anti-PD1, we found that the overall survival rate and progression-free survival rate of LINC00313 high expression group in LUAD patients treated with anti-PD1 were significantly lower than those of LINC00313 low expression group (Figure 4(E and F)), suggesting that LINC00313 may be a predictive marker of immunotherapy outcome in LUAD patients.

LINC00313 was associated with the anticancer drug response

Based on the TCGA LUAD data, we used the ASSISTANT for Clinical Bioinformatics online tool to analyze the gene variation profiles of the LINC00313 high-expression group and low-expression group samples. It was found that there were significant differences in the mutation frequencies of several genes between the two groups of samples (Figure 5(A and B)). For example, the mutation frequencies of KRAS and STK11 were higher in the LINC00313 high expression group (Figure 5(C and D)). Sensitivity analysis of chemotherapeutic drugs found that the IC50 of cisplatin, dabrafenib and lapatinib were higher in the LINC00313 high expression group (Figure 5(E)), suggesting that the high expression of LINC00313 attenuated the effect of chemotherapeutic drugs on LUAD. These results also suggest that LINC00313 has great value for judging drug sensitivity in LUAD.

Figure 5.

Figure 5.

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The relationship between LINC00313 and the drug sensitivity of LUAD. (A–B) Based on TCGA LUAD data, the ASSISTANT for Clinical Bioinformatics online tool were used to analyze the gene variation profiles in the LINC00313 high-expression group and low-expression group. Significant differences were found in the mutation frequencies of multiple genes between the two groups of samples. (C–D) The mutation frequencies of KRAS and STK11 in LINC00313 high expression group were higher than in LINC00313 low expression group. (E) The IC50 of chemotherapeutic drugs (cisplatin, dabrafenib and Lapatinib) in the LINC00313 high expression (G1) group was significantly higher than that in the LINC00313 low expression group (G2).

Discussion

It is well known that non-coding RNA species account for a large fraction of the total transcripts. Emerging evidence suggests that lncRNAs are involved in multiple cancer types, including osteosarcoma [23], breast cancer [24], hepatocellular carcinoma [25], and lung cancer [26,27]. In the current study, we found LINC00313 with high differential expression in LUAD tissues compared to normal lung tissues, whereas no significant difference in LINC00313 expression was observed between LUSC tissues and normal lung tissues. A high expression of LINC00313 was associated with a shorter OS rate for patients with LUAD. These findings suggest that LINC00313 is specifically highly expressed in LUAD and not in other lung cancer subtypes. LINC00313 has been reported to be over-expressed and correlated with a poor prognosis in multiple cancer types [13,14, 28–31]. Consistent with our fundings in LUAD, Chen et al. [28] also reported that a high LINC00313 expression was also associated with tumor size, TNM stage, metastasis and the poor outcome in osteosarcoma. In this study, we discovered that the high expression of LINC00313 was only significantly associated with the prognosis of female patients, but not male patients (Figure 1(H and I) and Supplementary Fig. 2). In fact, it has been recognized for a long time that LUAD frequently occurs in women who do not smoke [32]. Moreover, significant differences in treatment response and prognosis are observed between male and female patients with LUAD [33,34]. We believe that there may be two main reasons for this phenomenon. First, the sex hormones of males and females are different. Both estrogen and androgen are almost involved in the progression of tumors [35]. Second, the lifestyle habits of males and females are quite different. Among lung cancer patients, the proportion of smokers is relatively lower in females than in males. Both factors may affect the function of LINC00313. These findings support that LINC00313 may serve as a valuable biomarker for LUAD diagnosis and prognosis prediction.

In addition to its role in diagnosis and prognosis, our findings also suggested that LINC00313 has therapeutic significance in LUAD. As lncRNAs have multifunction in various biological processes in tumor progression, and identification of tumor associated lncRNAs offers opportunities for personalized treatments for cancer [7,36]. Presently, a growing number of lncRNAs have been established as LUAD-related lncRNAs, such as LINC00467 [18], LINC00665 [37], LINC00312 [38], LINC00152 [39,40], lncRNA GAS5 [41], LINC00460 [42], and LINC00892 [27]. Though different mechanisms, such as functioning as ceRNA, direct binding to transcription factor, maintaining protein stability, suppressing gene transcription, and/or competitively binding miRNA, these lncRNAs promotes LUAD proliferation or metastasis. In the present study, we found that LINC00313 was associated with immune cell infiltration, the efficacy of immune checkpoint inhibitor and chemotherapeutic drug therapy on LUAD. To date, only one study has previously investigated the role of LINC00313 in LUAD [29]. It found that LINC00313 may contribute to osimertinib resistance via the PI3K/Akt pathway, offering new insights into the mechanisms of acquired osimertinib resistance in LUAD. This previous results together with our findings indicate that LINC00313 holds promise as a potential biomarker for both predicting chemotherapeutic drug therapy and immunotherapy response in LUAD.

It is well known that the tumor microenvironment of LUAD is composed of several heterogenetic cells, including tumor epithelial cells, stromal cells, and immune cells [43]. These cells may exhibit heterogeneity in expression patterns. Therefore, it is especially critical to know exactly the expression pattern of each individual cells in the surrounding microenvironment [44]. We here found that LINC00313 was closely associated with immune cell infiltration, suggesting that LINC00313 plays a key role in the tumor microenvironments of LUAD. To investigate the roles of LINC00313 in LUAD, LINC00313-targeted siRNAs were used to establish LINC00313-silenced A549 cells. LINC00313-silenced A549 cells presented a decreased ability to migrate, invade, and form colonies, which is the observable characteristics with 30% off LINC000313 expression. Previous studies have reported that LINC00313 plays a cancer-promotion role in osteosarcoma [28], papillary thyroid cancer (PTC) [30], and cervical carcinoma [31], showing that the downregulation of LINC00313 inhibits malignant phenotypes of tumor cells, which was consistent with our findings. However, the exact mechanism underlying the tumor-promoting action of LINC00313 remains unknown. Emerging evidence suggests that immune system dysregulation can be a major cause of tumor progression [22]. In this study, we found that a high LINC00313 expression was significantly negatively associated with tumor-infiltrating immune cells in LUAD, including B cells, CD4+ T cells, CD8+ T cells, neutrophils, macrophages, and dendritic cells. Moreover, LINC00313 was significantly positively associated with several immune checkpoints, as well as with multiple immune-related pathways. These findings collectively indicate that LINC00313 may play a pivotal role in the immunological regulation of LUAD.

Nevertheless, it is important to acknowledge that our study also has certain limitations, including the absence of in vivo experiments and a relatively small sample size. Further validation at the in vivo level, along with an increase in sample size, would significantly advance the clinical application of our research conclusions. Despite these limitations, our data in summary reveal that LINC00313 may serve as a valuable prognostic biomarker and therapeutic target for LUAD treatment.

Supplementary Material

Supplemental Material
IFSO_A_2547557_SM1403.pptx (538.9KB, pptx)
Supplemental Material
IFSO_A_2547557_SM1400.pptx (274.7KB, pptx)

Funding Statement

This study was supported by the National Natural Science Foundation of China (No. 82300825), the Natural Science Foundation of Hunan Province (No. 2023JJ40376, No. 2023JJ60311 and No. 2023JJ60461) and Scientific Research Projects of the Health Commission of Hunan Province (No. 202203050006).

Ethics statements

No human and animal studies are presented in this manuscript such that no ethics approval is needed.

Author contributions

Conceptualization: Guoli Li and Jingjing Li conceived the study and developed the research design. Methodology: Guoli Li and Wen Wang were responsible for the methodology and experimental design. Data Collection: Wen Wang and Yanhui Cui conducted the data collection. Data Analysis: Guoli Li and Jianfu Heng performed the statistical analysis and interpretation of the data. Writing – Original Draft: Wen Wang wrote the initial draft of the manuscript. Writing – Review & Editing: Jingjing Li and Guoli Li reviewed and edited the manuscript for important intellectual content. Funding Acquisition: Wen Wang, Jianfu Heng and Guoli Li secured funding for the project. All authors have read and approved the final manuscript and agree with the order of authorship.

Disclosure statement

Financial disclosure

The authors have no relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript. This includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or pending, or royalties.

Writing disclosure

This manuscript was written independently, with no other aid.

Data availability statement

This paper analyzes existing, publicly available data. These accession numbers for the datasets are listed in method details. This paper does not report original code. Any additional information required to reanalyze the data reported in this paper is available from the lead contact upon request.

References

Papers of special note have been highlighted as either of interest (•) or of considerable interest (••) to readers.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supplemental Material
IFSO_A_2547557_SM1403.pptx (538.9KB, pptx)
Supplemental Material
IFSO_A_2547557_SM1400.pptx (274.7KB, pptx)

Data Availability Statement

This paper analyzes existing, publicly available data. These accession numbers for the datasets are listed in method details. This paper does not report original code. Any additional information required to reanalyze the data reported in this paper is available from the lead contact upon request.

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