Hypoxia-Related lncRNA Correlates with Prognosis and Immune Microenvironment in Uveal Melanoma

doi:10.21203/rs.3.rs-3896628/v1

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Research Article

Hypoxia-Related lncRNA Correlates with Prognosis and Immune Microenvironment in Uveal Melanoma

https://doi.org/10.21203/rs.3.rs-3896628/v1

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Journal Publication

published 09 Oct, 2024

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Background

Genes related to hypoxia are correlated to the prognosis of a variety of solid malignant tumors. However, How hypoxia related lncRNA function in Uveal Melanoma is still rare.

Methods

From TCGA database, eighty UVM samples were incorporated. Prognostic HRL was screened by COX univariate analysis and Pearson correlation analysis. HRL characteristics were constructed using Lasso analysis. Gene enrichment analysis revealed the linkage of HRLs to immune features. CCK8 assay was adopted to measure the propagation of MuM2B cells, while tumor invasion and migration were appraised by Transwell and Wound-healing experiments. Inflammatory factors and macrophage polarization were evaluated by qPCR.

Results

621 prognostic HRLs were screened and was constructed in 12 HRLs. Risk score showed salient correlation with survival time of UVM patients. In addition, HRL was correlated with diverse key immune checkpoints, revealing possible targets for immunotherapy. Immune-related pathways were highly enriched in high-risk group. Protective HRL, LINC02367, was saliently associated with microenvironment and survival time of UVM patients. In vitro assays demonstrated LINC02367 significantly affected the propogation and migration of MuM2B. LINC02367 modulates macrophage polarization through inflammatory factor levels thereby affecting the immune microenvironment

Conclusions

In our study, a novel HRL signature was developed to predict the prognosis of UVM patients. HRLs are potential biomarkers and therapeutic targets for UVM.

UVM

Risk model

RNA-seq

Prognosis

Immune microenvironment

Originating from the melanocytes of the choroid of the eye, Uveal melanoma is highly malignant [1], with incredibly high fatality rate and fairly short median overall survival(OS)[2, 3]. Uveal melanoma tends to metastasis which promptly leads to death[4, 5]. Upon metastasis occurred, very few treatments are effective[6]. Therefore, novel markers to anticipate the occurrence and progression of the UVM is quite necessary to be explored.

Hypoxic environment is thought to be associated with malignant tumor progression[7, 8]. In UVM, hypoxia has been shown to promote tumor invasion and progression through activation of Notch and MAPK pathways [9, 10]. Moreover, HRGs were associated with the prognosis of UVM[11]. Thus, hypoxia is critical in UVM progression.

Long-noncoding RNAs (lncRNAs) participate in diverse biological processes mainly through regulating the expression of mRNA [12–14]. In UVM, lncRNA played roles in regulation of immune infiltration, metabolism, tumourigenesis, proliferation, apoptosis and so on[15–18].

A foregoing study represented that HRGs were correlated with immune microenvironment and survival time in UVM[11]. Nevertheless, How HRLs function in UVM was still undefined. Here, we make use of data from TCGA database to validate HRLs and a novel HRLs signature was developed, objective to investigate the effect of HRLs in prognosis and immune features of UVM.

Data Extraction

Totally 80 uveal melanoma samples were incorporated. The RNA-seq and clinical information were extracted from TCGA database (https://portal.gdc.cancer.gov/). The scRNA-seq data was extracted from GEO database (https://www.ncbi.nlm.nih.gov/geo/). The characteristics of samples were concluded in Table 1.

Identification of HRLs

Twenty-six HRGs were identified by previous studies[19]. From TCGA database we totally extracted 16882 lncRNAs. Among these, lncRNAs closely related with those 26 HRGs (|r|>0.5 and p < 0.001) were regarded as HRLs.

Single Cell RNA Data Processing and Dimensionality Reduction

11 samples from GSE139829 were processed. Cells with nFeature_RNA < 2500, nFeature_RNA > 200 and percent_mt < 5 were initially incorporated. Using “harmony” R package to consolidate and batch these 11 samples. Then cells in all samples were dimensionalized and clustered as visualized by UMAP. Each cluster was annotated according to the 10 genes with the highest expression, respectively.

Bioinformatic Analyses

GSVA was adopted to evaluated Gene Ontology biological processes of each UVM sample[20]. Between two risk groups, differentially expressed genes were selected and GSEA analysis was executed. We utilized “clusterprofiler” R package to perform KEGG and GO enrichment analyses. Employing “rms” and “regplot” R packages, the nomogram and calibration curve were established. “Oncopredict” R package was adopted that the sensitivity of UVM samples to 545 common antitumor drugs and their association with the risk signature was conducted. SNP mutation analyses was also performed to assess differences in mutated genes that saliently influence the progression of UVM between risk groups. The waterfall plot was constructed by “waterfalls” and “oncoplot” R packages.

Appraisal of Immune Features

We employed "estimate" R package to calculate stromal scores, tumor purity and immune scores for each patient [21]. The infiltration of immune cells was appraised utilizing ssGSEA algorithm from low to high risk. Further, CIBERSORT, TIMER as well as EPIC algorithms were adopted to evaluate the relative abundance of immune cells [22–25].

Establishment of Risk Signature

The LASSO algorithm was conducted by which risk score for each patient was calculated:

Risk Score =∑_iⁿ Coefficient i ∗ Gene i

Construction of Competing Endogenous RNA Network

ENCORI webtool was utilized to predict the target miRNAs of LINC02367 (http://starbase.sysu.edu.cn/). Further, we used mirDIP webtools (http://ophid.utoronto.ca/mirDIP/) to predict potential target mRNAs of these miRNAs. Then, mRNAs correlated with LINC02367 with p < 0.01 calculated by Pearson analysis were identified as potential mRNA targets of LINC02367. Cytoscape 3.9.1. were utilized to establish the lncRNA-miRNA-mRNA network.

Cell Transfection of siRNA

Human uveal melanoma cells (MuM2B) was used in this study. We cultured MuM2B in complete RPMI-1640 medium added with 10% FBS (, China). 4 specific siRNAs targeting LINC02367 were devised and produced by GenePharma. SiRNA utilized in our study were listed below: LINC02367-Homo-1387: F, GCACAGACACAGUAUCAUATT; R, UAUGAUACUGUGUCUGUGCTT. LINC02367-Homo-1472: F, GGAAAUAACUUUGUAGCAATT; R, UUGCUACAAAGUUAUUUCCTT. LINC02367-Homo-2391: F, GCUUCUUAACCUGAUGUAUTT; R, AUACAUCAGGUUAAGAAGCTT. LINC02367-Homo-2593: F, GCCCUUGAAAGUCGAUGUATT; R, UACAUCGACUUUCAAGGGCTT. Lipofectamine 3000 (Invitrogen, USA) was utilized for siRNA transfection.

RNA extraction and qPCR implementation

TRIzol reagent was utilized for extraction of total RNA (Invitrogen, Carlsbad, CA, USA). Using The PrimeScript RT reagent Kit (RR047A, Takara) to remove gDNA and perform reverse transcription in two steps. Then we used TB Green Fast qPCR Mix (RR430S, Takara) for quantitative Real-Time PCR with GAPDH applied as endogenous reference. Primers utilized in our study were summarized below: GAPDH: F, GAACGGGAAGCTCACTGG; R, GCCTGCTTCACCACCTTCT. LINC02367: F, TTGCAAGTTCTGGCTTTGTG; R, GCAGTTGAACTTGTGCCAGA. IL6: F, TACCCCCAGGAGAAGATTCC; R, TTTTCTGCCAGTGCCTCTTT. IFN-:α: F, GCAAGCCCAGAAGTATCTGC; R, ACTGGTTGCCATCAAACTCC. IFN-γ: F, tcccatgggttgtgtgttta; R, aagcaccaggcatgaaatct. TGF-β, F: gggactatccacctgcaaga; R: cctccttggcgtagtagtcg. TNF-α: F, tccttcagacaccctcaacc; R, aggccccagtttgaattctt. CD86: F, acagatgtcctacgggaacg; R, atcccaccttagagccaggt.

Cell Counting Kit-8 Assay

After transfection, MuM2B was planted into 96-well plates according to cell density of 2×103 per well, and continued to culture for 24, 48, 72, and 96h, respectively. Then, each well were added with 10 ul CCK-8 reagent (DOJINDO, Japan) then placed at 37℃ for 1 hour, then measured the 450nm absorbance. Recording to the outcomes of qPCR and CCK8 assays, LINC02367-Homo-1387 and LINC02367-Homo-2593 were used as follow-up experiments.

Cell Invasion Experiment

We performed Transwell experiments to appaise MuM2B cell invasion capability. MuM-2B cells were starved for 24h, then digested 4-6h after transfection, suspended with serum-free culture and inoculated into each upper chamber of the transwell plate at 2×10^5/ml for 24h. 600ml of RPMI-1640 culture with 20% serum was infused into the lower chamber to attract MuM2B movement through the transwell plate. Matrigel (Basement Membrane Matrix) was utilized to precoat the upper chamber or not to assess cell invasion and migration, respectively. The proportion of cells traverse was recorded from five independently random scopes.

Wound-Healing experiment

We inoculated MuM2B cells into six-well plates till the cell fusion degree of more than 90%. After transfection, MuM2B cells was starved for 24 hours in serum-free medium. The MuM2B cells were removed with a single wire design using the tip of a 20ul pipette to form a cell-free gap. Scratch healing at 0 and 24 hours was recorded. The proportion of cells migration was recorded from five independently random scopes.

Macrophage polarization

THP1 cells were planted in six-well plates, cultured with RPMI-1640 medium involving 100 ng/ml PMA for 24h to differentiate into M0 macrophages. We collected culture supernatants of MuM2B cells knocked down with LINC02367 at 1 d, 2 d and 3 d, respectively. For the supernatant collection, we first inoculated the same numbers (10^6 cells) of MuM2B cells in each of the six-well plates with complete medium till cells grew to 70–80% fusion, then they were transfected with si-LINC02367 or si-Control. After cultured for 1 d, 2 d and 3 d, the supernatant was gathered and purified using 0.22 µm filters (Millipore). The supernatant was then sequentially added to THP-1 cell medium and the culture of M0 THP1 cells was continued. After 3 days, we collected THP1 cells, then extracted total RNA, and detected the relative expression of CD86 and CD206.

Data statistics and analysis

R version 4.2.1 as well as GraphPad Prism version 8.2.1. were utilized to process data and plots. For the survival time of samples between risk groups, K-M analysis and log-rank test were performed. Pearson analysis was applied to validate the correlation of HRLs with other traits. analysis over time We also constructed ROC curves by which the predicted ability of risk signature was appraised. Bilateral p < 0.05 was taken for significant statistically.

Single Cell RNA Analysis Revealed Distribution of Hypoxia Related Genes

After dimensionality reduction, UVM cells from 11 samples were finally clustered into 7 clusters, which were tumor cells, photoreceptors, NKT cells, Monocytes and Macrophages, T cells, Plasma cells and B cells, respectively (Fig. 1A). After univariate COX analysis, 9 hypoxia-related genes proved to have prognostic value were distributed in both tumor clusters and immune cell clusters (Fig. 1B, C). This suggests that hypoxia may function vitally in tumor progression by influencing both the tumor itself and the tumor's immune microenvironment, especially T cell and macrophages.

Validation of Hypoxia-related lncRNAs in TCGA dataset

Totally 16882 lncRNAs and 26 HRGs in TCGA dataset were identified and incorporated into this study (Fig. 2A). 3128 HRLs were screened using Pearson correlation algorithm (|r|>0.5 and p < 0.01) (Table S1). Univariate Cox algorithm following Lasso algorithm validated 12 HRLs selected to construct risk signature (Fig. 2B). To be specific, five lncRNAs (AC006115.2, AC008555.1, AC104825.1, AP000808.1 and LINC02367) were protective factors in UVM, while other seven lncRNAs played aggravating roles (p < 0.05) (Fig. 2C). These 12 selected lncrnas were closely related to 26 HRGs (Fig. 2D).

Table 1

The clinical information of 80 samples from TCGA dataset
Features	TCGA(n = 80)
Age
≥60	44
< 60	36
Gender
Male	45
Female	35
Stage
Stage II	36
Stage III	40
Stage IV	4
N
N0	76
NX	4
M
M0	73
MX	7
T
T2	14
T3	32
T4	34
Metastasis
Yes	26
No	54

HRL Model Predicted UVM prognosis precisely

HRL signature was constructed to validate the prognostic role of HRLs in Uveal Melanoma. The coefficient of five lncRNAs (AC006115.2, AC008555.1, AC104825.1, AP000808.1 and LINC02367) was negative

while others were positive (Fig. 3A). Each UVM patient was confered a score according to the expression and coefficients of 12 HRLs. The hypoxic score calculated using ssGSEA differed apparently between risk groups (Fig. 3C). Further, according to the medium of risk scores, UVM samples were distributed to two groups. Overall survival time of patients was saliently shorter with in high-risk group (Fig. 3B). We applied ‘caret’ R package to randomly allocate 80 samples into two inner validation groups (n = 40). The AUC regarding risk score in anticipating 1-, 2-, 3-, 4- and 5-year OS of all UVM patients exhibited 0.89, 0.92, 0.96, 0.92 and 0.92 (Fig. 3B). For two validation groups, AUC in predicting 1-, 2- and 3-year survival were 0.87, 0.91, 0.97 and 0.92, 0.91, 0.90, respectively. (Fig. 3C, D). Five protective lncRNAs expressed statistically higher in low-risk group, while other lncRNAs showed the opposite pattern (Fig. 3F, G). Our HRL signature accorded to a high degree with modules validated by Robertson AG, et al[26]. Meanwhile, risk score in samples with metastasis saliently manifested as higher (p < 0.05) (Fig. 3E). These outcomes revealed that HRL risk signature correlated closely with prognostic traits of UVM.

Risk Score Independently Predict UVM Prognosis

A nomogram model and a calibration plot for anticipating 3-year overall survival were constructed (Fig. 4A, B). UVM samples were allocated to diverse subgroups to determine survival anticipating value of HRL signature in detail, namely Stage II or III, Male or Female, Age ≤ 60 or > 60 and T3 or T4. For each subgroup, samples in high-risk group owned a shorter OS, while low-risk represented better prognosis (p < 0.05) (Fig. 4C-F). Above outcomes suggested risk score as a potentially prognostic marker of UVM patients.

Figure 4 | Risk score independently predict prognosis of UVM samples. (A) Nomogram model of mRNA_Cluster, lncRNA_ Cluster, Paradigm_ Cluster, Metastasis and stage and risk score. (B) Calibration curve model regarding 1- ,2- and 3-year survival aimed at confirming the prognostic value of HRLs. (C) K-M analysis of patients in two risk groups in age ≥ 60 and < 60. (D) K-M analysis of patients in two risk groups in female and male. (E) K-M analysis of patients in two risk groups in stageII and stageIII. (F) K-M analysis of patients in two risk groups in T3 and T4.

Risk Score associated with the Immune Checkpoint

Despite uveal melanoma unsensitive to immunotherapy, we endeavored to explore the relationship of the effectiveness of ICIs with

Figure 5 | Risk score was associated with the effectiveness of ICIs in UVM patients. (A) The relative level of multiple immune checkpoints between risk groups. (B) The relative level of several ligand receptors between risk groups. (C) The relationship of risk score with immune checkpoints. (D) The relative expression of HLA between risk groups. (E) K-M algorithm of overall survival in 4 groups constructed by risk score and relative expression of LAG3.

HRL signature[27]. In high-risk group, several vital immune checkpoints (CTLA-4, IDO1, TIGHT, LAYN and LAG3) showed relatively higher levels (p < 0.05) (Fig. 5A). Moreover, abundant receptor ligands and HLA genes showed the same tendency, suggesting the effects of immunotherapy may differ in two groups (Fig. 5B, D). Further, LAG3 was identified to be most closely correlated with risk score using Pearson analysis, in line with the research by Michael A. Durante et al[28] that the most sensitive immune checkpoint for UVM may be LAG3 (Fig. 5C). Patients owing lower risk score and higher LAG3 level manifested better prognosis than those owing higher risk score and lower LAG3 level (p < 0.05) (Fig. 5E).

Risk Groups Showed Disparate Immune Peculiarities

Potential pathways were validated to explain the difference between two groups. We identified differentially expressed genes (DEGs) between risk groups (Fig. S1). GO enrichment analysis showed salient enrichment of various immune pathways, like macrophages, T cells and antigen presenting related pathways (Fig. 6B).

Figure 6 | HRL signature revealed disparate immune traits. (A) KEGG enrichment analysis. (B) GO enrichment analysis. (C, D) GSEA of whole RNA-seq data in (C) immune signaling pathways between risk groups in GO term and (D) hypoxic signaling pathway in HALLMARK term. (E, F) Immune and hypoxic signaling pathways between two risk groups shown by GSVA in (E) GO term and (F) KEGG term.

Moreover, DEGs saliently enriched in neurodegenerative diseases, oxidative phosphorylation, and reactive oxygen species associated pathways, all of which were associated with cellular and tissue hypoxia (Fig. 6A). Genes with relatively higher level in high-risk group were overtly enriched in immune signaling pathways, like antigen response, B-cell and T-cell-related pathways shown by GSEA. HALLMARK-Hypoxia pathway also showed salient differences between two groups(P < 0.05) (Fig. 6C, D). GSVA also revealed hypoxic signaling pathways as well as immune signaling pathways differed apparently between risk groups (Fig. 6E, F).

Risk Score Reveal Difference in Immune Infiltration and Tumor Purity

The prognosis od UVM was saliently impacted by peripheral immune infiltration [29, 30], thus, we aimed to probe into the relationship between HRL signature and immune microenvironment in UVM.

Figure 7 | Risk signature reveal difference in tumor purity and immune infiltration (A) The 22 immune cells assessed by CIBERSORT algorithm between risk groups. (B) The 8 immune cells assessed by EIPC algorithm between two risk groups. (C) The 6 immune cells assessed by TIMER algorithm between two risk groups. (D) The association between risk score and stromal score, immune score, estimate score and tumor purity. (E) The abundance of 28 immune cells estimated by ssGSEA algorithm between two risk groups. (F) The association between risk score and 9 immune cells assessed by TIMER and CIBERSORT algorithm.

CD8 + T cells and M1 macrophages were highly enriched in high-risk group calculated by CIBERSORT algorithm (p < 0.05) (Fig. 7A). Besides, ssGSEA, EPIC and TIMER algorithms containing twenty-eight, eight and six immune cells, respectively were applied. High-risk group represented significant higher level of Macrophages and CD8 + T cells (Fig. 7B, C, E). Tumor purity, which is valued according to ESTIMATE score, showed saliently related to risk score negatively, indicating hypoxia played roles mainly around tumor microenvironment (p < 0.05) (Fig. 7D). Additionally, relationship between risk score and Macrophages and CD8 + T cells were confirmed again by Pearson analysis (p < 0.05) (Fig. 7F). This is consistent with previous findings that UVM samples representing higher infiltration of CD8 + T cells have a poorer prognosis and abundant CD8 + T cells were seen in distant metastatic lesion[28, 31]. These findings indicated the sturdy relationship between HRL and immune infiltration, partly explained its risk function.

Prognostic HRL LINC02367 Was Correlated with Clinical and Immune Characteristics

LINC02367 was chosen for further exploration, since it has never been reported and its 95%CI is narrowest in 12 HRLs, representing a relatively stable effect. Relative level of CD8 + T cells and M1 macrophages were saliently higher in low-LINC02367 group compared to high-LINC02367 group, meanwhile, M2 macrophages infiltration showed the opposite trend (Fig. 8A). Pearson algorithm also confirmed the positive correlation of LINC02367 with M2 macrophages (r = 0.29, p < 0.05) while negative correlation with M1 macrophages (r=-0.34, p < 0.05) and CD8 + T cells (r=-0.40, p < 0.05) (Fig. 8B). We also compared abundance of LINC02367 with modules validated by Robertson AG, et al. The regularity of LINC02367 in these modules was completely opposite to that of risk signature (Fig. 8C). Besides, the median overall survival of samples in high-LINC02367 group was saliently higher compared to low-LINC02367 group (Fig. 8D). Additionally, patients with metastasis showed significantly lower LINC02367 levels (Fig. 8E). Therefore, LINC02367 functioned as a prognostic factor which was both saliently correlated with clinical and immune characteristics in UVM.

HRLs Combined with Drug Sensitivity Analysis Revealed Potential Therapeutic Agents for UVM

From Cancer Therapeutics Response Portal (CTRP), Multiple drugs having statistically significant associations with both risk score and

Figure 9 | LINC02367 was associated with the drug sensitivity in UVM. (A) The abundance of 27 anti-tumor drugs saliently associated with risk score between LINC02367 groups. (B) The association between BRD.K07442505 and risk score and LINC02367. (C) The abundance of 27 anti-tumor drugs significantly associated with risk score in two risk groups. (D) K-M algorithm of overall survival among four sample groups constructed by HRL signature and relative predict value of BRD.K07442505.

LINC02367 was screened (|r|>0.5, p < 0.001) (Fig. 9A, C). Lower predict value represented more sensitive the tumor is to the drug. BRD.K07442505 is a pan-cancer targeting agent. High-risk group samples showed more sensitivity to BRD.K07442505 (r=-0.59, p < 0.001) and the predict value of BRD.K07442505 was positively associated with LINC02367 (Fig. 9B). K-M analysis showed that the group less sensitive to BRD.K07442505 with higher risk scores had the worst prognosis, while the group more sensitive to BRD.K07442505 with low risk scores owned the relatively best prognosis (Fig. 9D). Above represented the latent therapeutic function of BRD.K07442505 in UVM patients, especially those at high risk.

HRLs Related to The Mutation Rate of Key Genes of Uveal Melanoma

Genes with the top20 mutation frequencies in two risk groups was screened, respectively. Genes with the highest mutation rate of the two groups were highly overlapped, like GANQ, GAN11, BAP1, SF3B1 and EIF1AX that have been validated critical in progression of UVM[32] (Fig. 10A, B).

Figure 10 | HRLs signature was associated with the vital single nucleotide polymorphisms (SNPs) in UVM. (A, B) The frequency and type of mutation of top twenty genes that mutate most frequently in (A) high-risk and (B) low-risk group, respectively. (C) Compared of tumor mutation burden (TMB) between two groups. (D-F) Risk score of each patient in (D) BAP1 mutation group, (E) EIF1AX mutation group and (F) SF3B1 mutation group.

Perhaps due to UVM's lack of sensitivity to immune checkpoints, no difference in tumor mutation burden (TMB) was observed between two risk groups (Fig. 10C). Moreover, BAP1 mutation group showed saliently higher risk score than non-mutation group, whereas SF3B1 and EIF1AX showed contrary tendency (p < 0.05) (Fig. 10D-F). It’s consistent with the fact that patients with poorer prognosis have higher levels of BAP1 mutations and those with better prognosis have higher levels of SF3B1 and EIF1AX mutations[26].

Bioinformatic Analysis of Potential Molecular Mechanisms of LINC02367

LncRNAs may function in tumor progression as ceRNAs. Thus, we identified the potential miRNA and mRNA targets of LINC02367, then co-expressed mRNAs of LINC02367 was screened by Pearson analysis to finally determine the target mRNA. The lncRNA-miRNA-mRNA network was constructed (Fig. 11A). LINC02367-targeting mRNAs were highly enriched in neuronal connections and synapses pathways (Fig. 11B). DEGs were sifted according to median expression of LINC02367. Hypoxia, glycolysis as well as DNA repair signaling pathways were highly enriched in high-LINC02367 group, whereas several inflammatory pathways like inflammatory response, IFNα, IFNγ and IL6 signaling pathways exhibited high enrichment in low-LINC02367 group (Fig. 11C, D).

These results indicated that LINC02367 might carry into effect on progression of UVM cells by regulating tumor immune microenvironment.

LINC02367 Effected on Proliferation and Migration of UVM Cells Through Immune Microenvironment Shift

In Vitro trials were implemented to determine the pathogenic function of LINC02367 to uveal melanoma cells. Four siRNAs were transfected in MuM2B cells to knock down LINC02367, in which si-LINC02367#1387 and si-LINC02367#2593 were selected owing to higher efficacy (p < 0.05) (Fig. 12A). The knockout of LINC02367 significantly prompted the multiplication of uveal melanoma cells as shown in CCK8 assay (p < 0.05) (Fig. 12B). As shown by Wound-healing assay, inhibition of LINC02367 saliently promoted the migration of MuM2B cells (Fig. 12C). Moreover, transwell experiments with or without Matrigel also confirmed that the knockout of LINC02367 saliently promoted the proportion of MuM2B cells migrating or invading through the upper chamber (Fig. 12E). Therefore, LINC02367 was related with the propagation and migration of UVM and was latently intervenable target for UVM. To further validate the possible mechanism of LINC02367, we conducted supplementary experiments targeting inflammatory factors and macrophages. IL6 plays a central role in inflammation and immune activation[33], but we observed no statistical change of IL6 in cells between si-LINC02367 groups and the si-Control group. Meanwhile, compared with the si-Control group, three inflammatory factors, including TNF-α, TGF-β1 and IFN-α in both si-LINC02367 groups were increased to varying degrees. While IFN-γ only increased in si-LINC02367-2593 group. (Fig. 12G).

Figure 12 | LINC02367 functioned negatively on the propagation of MuM2B. (A) Relative level of LINC02367 after transfection of four siRNAs. (B) CCK8 assay of MuM2B cells after knockdown of LINC02367. (C) Wound-healing assay of MuM2B cells after knockdown of LINC02367. (D) Transwell assay of MuM2B cells after knockdown of LINC02367. (E) The expression of five inflammatory factors of MuM2B cells after knockdown of LINC02367. (F) The expression of Macrophages type 1 marker CD206 of THP1 cells after co-cultured with cell supertanant of MuM2B cells after knockdown of LINC02367.

Among them, TNF-α, IFN-α and IFN-γ are thought to function importantly in the polarization of macrophages and the activation and migration of pro-inflammatory cells[34, 35]. Pearson analysis showed a positive correlation of LINC02367 with the expression of such four inflammatory factors (Fig. S2). Above outcomes suggest that a proinflammatory microenvironment probably function dominatingly in UVM where LINC02367 is inhibited. Further, we focused our attention on macrophage polarization, given that IFN related pathway may have an impact on M0 to M1-type polarization. THP1 cells incubated with supernatants from the si-LINC02367-treated group showed significantly higher expression values of the M1-type macrophage marker CD86 than those from the NC group, suggesting LINC02367 functioned in macrophage polarization (Fig. 12H). It has been reported in the literature that high PMA treatment fails to up-regulate M2-type macrophage markers[36], but we failed to detect CT values for CD206 markers in THP1 cells by qPCR, even though the concentration of PMA was down-regulated to 10 ng and the cDNA was not diluted. This may be due to the overall pro-inflammatory microenvironment of MuM2B and the bias of macrophages to differentiate toward the M1 type. Therefore, LINC02367 might shift immune features of UVM through inhibiting the activation of pro-inflammatory cells and altering macrophage polarization, thereby reducing tumor distant metastasis and affecting prognosis.

Hypoxic environment and long non-coding RNA have both been demonstrated crucial for progression of uveal melanoma[37, 38]. Here, we identified 620 HRLs affecting the prognosis of UVM and constructed a novel risk signature through LASSO algorithm comprising 12 HRLs in TCGA database. There existed a salient relationship between risk score and prognosis of UVM patients. In addition, relative level of several vital immune checkpoints, especially LAG3, differed apparently between risk groups, which represented HRLs as latent indicators for anticipating the effectiveness of immunotherapy. Functional analysis proved in high-risk group substantial enrichment of immune signaling pathways, while hypoxia pathway also showed statistical differences, confirming the correlation of HRL with immune features of UVM. In vitro experiments showed that knockout of LINC02367 significantly facilitated the propagation and movement of UVM cells. Inflammatory response and activation of IFN signaling pathways probably functioned vitally in this process. This study developed a novel signature according to HRL as a predictor of UVM prognosis and that LINC02367 may be an effective target for clinical intervention. Hypoxic environment has been revealed markedly impacted on manifold malignant tumors, like hepatocellular carcinoma, carcinoma of bladder, carcinoma of lungs and glioma[39–42]. In bladder cancer, an 8-gene hypoxia signature accurately predict patient prognosis and showed a significant correlation with immune infiltration[43]. In lung cancer, another 6-gene hypoxia signature also proved that hypoxic environment exhibited independent prognostic worth[44]. Besides, HRGs were saliently correlated with undesirable prognosis and high recurrence in liver cancer. At the same time, hypoxic-related model can correctly distinguish hepatocellular carcinoma, normal samples and nodular tissue. More importantly, hypoxia-related features can positively modulate the immune response[45]. In this project, 26 hypoxia-related genes (HRGs) were optioned to correlate and screen hypoxia-related lncRNAs (HRLs). The selected HRL was strongly correlated with HRG, and each had significant prognostic value. Among HRGs, TPI1 and FOSL1 were apparently correlated with the vast majority of HRLs. Univariable Cox algorithm demonstrated the tight relevance of TPI1 and FOSL1 with worse prognosis in UVM patients, and both TPI1 and FOSL1 were significantly negatively correlated with LINC02367. Then, a risk signature according to 12 HRLs were established. Then bioinformatics analysis showed risk scores accurately predicted prognostic information in patients with uveal melanoma. Survival analyses of different subgroups also demonstrated a tight relevance of higher risk score with worse prognosis and short-lived OS. Though incorporated with other clinical characteristics, risk score still represented a standalone value in prognosis of UVM patients. Hence, this project reveals a novel HRL signature which may be a potential prognostic marker of UVM.

Recently, the pivotal impacts of the immune microenvironment in tumorous progression have been continuously confirmed. Different from other solid tumors, pro-inflammatory microenvironment around UVM was generally related to undesirable prognosis and distant metastases. A meta-analysis demonstrated that merely higher abundance of B cells represented a better prognosis. Others like M1 macrophages, NKT as well as CD8 + T cells, all predicted a worse prognosis for UVM[46]. Moreover, it has been speculated that activation of the T cell response is necessary for distant metastasis of UVM due to the special immune characteristics of the eyes[46]. Macrophages also functioned critically in secretion of inflammatory factors also immune microenvironment remodeling and are associated with a worse prognosis[29]. Elevated expression of inflammatory factors such as IFN-γ have were associated with metastasis of uveal melanoma[47]. Herein, our study uncovered that elevated risk score was saliently related to IFN-γ and immune response pathways. The DEGs were apparently enriched in hypoxia and immune-related pathways. Moreover, higher infiltration of M1 macrophages and CD8 + T cell existed in high-risk group, which may be related to the characteristics of hypoxia. However, the relevance of hypoxia and immune characteristics is not completely clear. Whether immune microenvironment remodeling is a direct result of hypoxia needs further experimental verification. The contradiction of immune infiltration in UVM and other cancers is also a critical problem to be settled. That means, in most cancers, higher proportion of cytotoxic immune cells like M1 macrophages and CD8 + T cells suppressed the development of tumor, but not UVM. A pan-cancer analysis of 32 tumor types revealed that gliomas and uveal melanomas showed similar immune infiltration characteristics, that high immune infiltration represents a worse prognosis[48]. And Xu S et al. disclosed a strong relevance of activated CD8 + T cells with high risk in LGG, along with poorer immunoefficacy, and an elevated TIDE score, suggesting a crosstalk between ICIs and immune infiltration[49]. We also noticed this phenomenon in our research. ssGSEA showed that CD8 + T cells were significantly enriched in the high-risk group. Given this, the prospect for immunotherapy of uveal melanoma seems bleak.

lncRNAs have been reported to be biomarkers or potential therapeutic targets for a variety of diseases[50, 51]. lncRNA-associated signatures have also demonstrated valuable prognostic value in diverse tumors. A 19-HRL signature precisely predicted the prognosis of LGG also identified the strong relevance of hypoxic environment with immune infiltration[49]. Besides, Chen et al. developed a novel molecular model of lncRNA related to fatty acid metabolism, which showed significant prognostic potential in hepatocellular carcinoma and tightly related to the efficacy of immunotherapy[52]. As for uveal melanoma, several signatures composed on lncRNA have been reported. Jin Y et al. constructed a molecular model of Ferroptosis related lncRNA, exhibiting powerful relationship with prognosis of UVM samples and tumor immune microenvironment[53]. A 6-lncRNA signature associated with autophagy accurately predicted prognosis of UVM, and high enrichment in high-risk group of cytoplasmic component cycling, energy metabolism and apoptosis signaling pathways were observed[54]. Nevertheless, to our knowledge, no researches have revealed the latent impact of HRLs on clinical and immune features of uveal melanoma. Herein, we established a 12- HRL signature that accurately predicted the prognosis of UVM samples. Further, LINC02367, a protective lncRNA, was chosen to represent this HRL signature. Subsequent analyses manifested LINC02367 was remarkably correlated with the prognosis and immune environment in UVM. We indicated that knockout of LINC02367 observably promoted the multiplication, migration and invasion of UVM cells, with activation of inflammatory factors and shift of polarization of macrophages. The cytoskeleton was in relevance of the progression, migration of uveal melanoma and the susceptibility of the UVM tumor cells to treatment[55, 56]. Besides, a study showed that antibodies targeting tumor immune synapses may benefit overall survival in patients with metastatic uveal melanoma[57]. After construction of ceRNA network, LINC02367 were found to function in cell skeleton and synapse. Moreover, inflammatory pathways, such as completement, interferon response and interleukin 6 signaling pathways were markedly enriched in high-LINC02367 group. Given that inflammatory response and cytokines like IFN were demonstrated to play a profound role in UVM progression[58, 59], decreased expression of LINC02367 may activate the inflammatory response by activating IFN or other cytokines and worsen prognosis of UVM. Thus, LINC02367 may be a potential target for UVM intervene.

In general, this study established a novel HRL signature that predicted UVM prognosis and was significantly correlated with the immune microenvironment. HRL may be a novel biomarker for predicting UVM progression and a potential target for UVM treatment.

Data Availability

The original contributions to this study are included in the main body and supplementary materials. Further reasonable inquiries and requests may be directed to the corresponding author.

Authors' contributions

Y.C. completed bioinformatics analysis and in vitro experiments and wrote the manuscript. S.C. participated in transwell and wound-healing experiments. Q.C. guided the writing of the manuscript. D.J. funded and supervised this project and edited the manuscript. All authors have read and agreed to the submission of this manuscript.

Funding

This work was funded by grants from the National Natural Science Foundation of China (Grant no. 82271091) and National key research and development program of China (2021YFA1101200 & 2021YFA1101202).

Ethics approval and consent to participate.

Not applicable.

Consent for publication.

Not applicable.

Competing interests.

The authors declare that they have no competing interests.

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Table 1 is available in the Supplementary Files section.

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Hypoxia-Related lncRNA Correlates with Prognosis and Immune Microenvironment in Uveal Melanoma

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