A novel m7G methylation-related miRNA signature for overall survival prediction in thyroid cancer

doi:10.21203/rs.3.rs-1669490/v1

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Research Article

A novel m7G methylation-related miRNA signature for overall survival prediction in thyroid cancer

https://doi.org/10.21203/rs.3.rs-1669490/v1

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posted 26 May, 2022

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Background

Thyroid cancer (THCA) is an extremely heterogeneous malignancy with different prognoses.A variety of miRNAs affect the process of tumor through different mechanisms.However, the m⁷G methylation-related miRNA expression in THCA and their associations with prognostic results remain elusive.

Methods

Based on the miRNA expression data from TCGA, differentially expressed miRNAs were screened out.Then, a 7-miRNA prognostic signature was established through LASSO Cox regression.Eventually, our team performed functional enrichment and immune activity analysis.

Results

A total of 47 differently expressed miRNAs were screened out, 7 of which exhibited a significant correlation with overall survival (OS) (P < 0.05).A 7-miRNA signature was developed, exhibiting an excellent forecast power. Patients were classfied into high- and low-risk groups on the basis of the mid-value of the risk score regarding our signature.The cases in High risk patients displayed a remarkably higher mortality than low risk patients (P < 0.001). The risk scoring was an independent prediction factor for OS based on multivariable Cox regressive analyses (P < 0.05). The receiver operating characteristic(ROC) analyses validated the prediction ability of the signature.Immune activity analyses revealed that the immune status of the two risk groups was different.The differentially expressed genes in the risk score and immune score showed a strong association with immune cells and immune pathways.

Conclusion

A novel miRNA prediction model was established for THCA and these miRNAs could be potential therapeutic targets.

m7G

miRNA，thyroid cancer

overall survival，risk signature，prognosis.

THCA is the most commonly seen malignant cancer of the endocrine system and its prevalence has risen evidently over the last few years[1].Although a large proportion of THCA patients have satisfactory prognostic results with a 10-year OS of 80–90% through standard treatments, whereas substantial patients exhibit an increasing mortality due to local recurrence and metastases,with a 5-year OS of 25% and a 10-year OS of 10%[2–4]. The broad prognostic range of THCA makes the prognosis forecast difficult[5].In addition, given the insufficient methods for local recurrence and metastases,it is ugrent to develop novel prognostic models and biomarkers to facilitate clinical reaetment and prognosis prediction for thyroid cancer patients.

The 7-methylguanosine (m⁷G) modification is the most common type of tRNA modification,which is critical for the progression of many cancers,such as cervical cancer and colon cancer[6, 7].MicroRNA (miRNA) is a small molecule encoded by the genome of advanced eukaryotes, and it it’s a negative genetic modulator[8]. The up- and down-regulation of miRNA expression facilitates the developmental process of tumor via different causal links.MiRNA-58-5p has been reported to inhibit the progression of papillary thyroid cancer through Bax/Caspase-3 [9]. A recent study has revealed that miRNA148a can inhibit the growth of papillary thyroid cancer by targeting the PI3K/AKT pathway[10].In addition,another research indicated that miRNA-214 could promote the progression of thyroid cancer[11].However, it remains unclear whether the m⁷G methylation-related miRNAs are associated with the prognoses of THCA patients.

In our study, a systematic research was completed to screen out the differentially expressed miRNAs related to m⁷G methylation,and a novel predictive signature was established based on these miRNAs.Ultimately, our team completed function enrichment analyses to investigate the latent causal links and immune status.

Data Collection

The data of mRNA(58 normal and 510 tumor) and miRNA(59 normal and 514 tumor) of thyroid cancer and related clinical data were acquired from the TCGA data base (https://portal.gdc.cancer.gov/).Then, we selected 2 genes(METTL1 and WDR4), which were discovered to be vital for cancer through m⁷G methylation, to predict the relevant miRNAs through the TargetScan data base.Eventually, we extracted the expression matrix of m⁷G methylation-related miRNAs, and performed data matching, data filtering and data correction for subsequent analysis. Ethical review was not required as the entire data herein were publicly available.

Development of a Prognostic m⁷G Methylation-Related miRNA Signature

We contrasted the expressing levels of m⁷G methylation-related miRNAs between tumor and normal specimens to detect differentially expressed miRNAs through the “limma”and“edgeR”R packages, with a false discovery rate (FDR) < 0.05 and |log2FC| ≥ 1[12].Then, we conducted univariable cox analyses of OS to filter m⁷G methylation-associated miRNAs with

prognosis significance. Benjamini-Hochberg was used to modify p-values. Our team finished LASSO Cox regressive analyses to identify if significant miRNAs could predict the OS and THCA patients' status with the "glmnet" R package[13].The risk score of the prognostic signature =esum (the normalised expressing level of every miRNA× its regressive coefficient). Subsequently, our research group utilized the mid-value of the risk scoring as the criterion to classify sufferers into the risk_high and risk_low groups.On the foundation of the expressing levels of miRNAs in our signature,we performed PCA and t-SNE to delineate the distribution in diverse groups through the "stats" and "Rtsne" R packages[14].Besides,we applied the "surv cutpoint" function of the "survminer" R package to analyze the survival based on the model and each miRNA, and the "survivalROC" R package was employed to finish the time-reliant ROC curve analysis to assess the prediction ability of our hallmark[15].Afterwards, univariable and multivariate Cox regressive analyses were utilized to identify if the risk scoring could predict OS independently.Eventually, we formulated nomograms based on the outcomes of multivariable analyses via the “regplot” and “rms” R packages. These nomograms were treated with 1000 bootstrap resampling for inner validation. The calibration of the nomogram for1-, 3-, and 5-years OS was completed via the contrast between the identified OS and the forecasted OS.

Functional Enrichment Analysis

Our research group initially utilized the “limma”and“edgeR”R packages to acquire the DEGs between the risk_high and risk_low groups.Then,the same R packages were employed to screen the DEGs according to the immune score downloaded from ESTIMATE: Disease (mdanderson.org). The standards of DEGs were FDR < 0. 05 and |log2FC | ≥ 1. The DEGs in both risk score and imuune score were selected to complete the GO and KEGG for the sake of revealing the biofunctions and pathways related to the risk scoring and immunity scoring with the "cluster Profiler" R package[16].

Immune Activity Analysis

The "gsva" R package was utilized for the ssGSEA to acquire the enrichment scoring of immunocytes and immunity-related pathways[17].Besides,we further evaluated the correlation between immunocytes and the correlation between the immunity-associated pathways.

Relationship among Prognostic DEGs and Immunocytes and Immunity-associated pathways

For the sake of evaluating the relationship among prognostic DEGs and immune cells and functions,the univariable cox analyses of OS were carried out to screen out the prognosis DEGs(P＜0.001).Afterwards, our team leveraged the “psych” R package to describe the relationship among prognostic DEGs and immune cells and functions.

Statistics

Student's t-test was utilized to contrast the expressing levels of miRNA and mRNA between tumor samples and paracancer samples. Our team completed the Mann-Whitney test to contrast the scoring of immunocytes and immunity-associated paths between these 2 groups. The K-M analysis and the log-rank test were completed to study the survival curves. Our team afterwards finished Cox regressive analyses to identify the factors which could forecast OS. The entire statistic assay was completed in R 4.0.3. A two-tailed P < 0.05 was the threshold of statistically significant difference. The flowchart of our research is displayed by Fig. 1.

Development of a Prognostic m⁷G Methylation-Related miRNA Signature

Overall, 792 m⁷G methylation-related miRNAs were isolated from the TargetScan database,47 of which were differently expressed miRNAs(28 upregulated and 19 downregulated). The volcano plot of miRNA differential expression and the heatmap of the top 20 miRNA differential expression were displayed by Fig. 2a-2b. To identify the survival-related miRNAs, miRNA differential expression was assessed via univariable COX analyses. Eventually, 7 miRNAs(hsa-miR-146b-3p, hsa-miR-181a-2-3p, hsa-miR-6860, hsa-miR-221-5p, hsa-miR-96-5p, hsa-miR-214-3p, hsa-miR-612) were highly correlated with OS (P < 0.05) (Fig. 3a).Then, these 7 miRNAs were involved in multivariable COX analyses,and the results showed that hsa−miR−214−3p and hsa−miR−612 were significant (P < 0.05) (Fig. 3b). These 7 miRNAs were utilized to construct a prognosis model through LASSO Cox regressive analyses and the model was constructed on the basis of the optimum score of λ (Fig. 3c-3d). Thus, the equation of our signature was: Risk Score = (-0.00001043 × expression ^{hsa-miR-146b-3p}) + (-0.000038×expression^{hsa-miR-181a-2-3p}) + (-0.07251 × expression^hsa-miR-6860)+(-0.004331 × expression ^{hsa-miR-221-5p})+(0.004627 × expression^{hsa-miR-96-5p})+(0.0251 × expression ^{hsa-miR-214-3p})+(0.3026 × expression^hsa-miR-612).The risk scoring of all sufferers was computed, and on the basis of the mid-value of risk scoring,we classfied sufferers into the risk_high and risk_low groups(Fig. 3e).The results of PCA and t-SNE analyses revealed that the cases in diverse groups had 2 diverse distribution(Fig. 4a-4b).Risk_high sufferers exhibited a greater mortality vs risk_low sufferers (Fig. 4c).Consistently, the Kaplan-Meier (K-M) curve analyses revealed that risk_high sufferers displayed a remarkably inferior OS vs risk_low sufferers(Fig. 4d, P < 0.001). The prediction ability of the OS risk scoring of THCA patients was assessed via time-reliant ROC curves,and the the region below the curve (AUC) was 0.743, 0.802, and 0.887 of 1-,3-, 5- years, separately(Fig. 4e). Meanwhile,the influence of the expression of 7 miRNAs on the prognosis of patients was analyzed by the Kaplan-Meier curve. The outcomes unveiled that the expressing levels of hsa−miR−214−3p and hsa−miR−612 considerably affected the OS(Fig. 5a-5b),which coincided with the outcomes of multivariable COX analyses.

Independent Prognostic Value of the Risk Signature

For the purpose of determining if the risk scoring can predict the OS independently, univariable and multivariable Cox regressive analyses were utilized.In univariable Cox regressive analyses, the risk scoring(HR= 23.5262, 95% CI =3.0887-179.1961, P=0.0023),age(HR= 1.1528, 95% CI =1.0951-1.2135, P＜0.0001), stage (HR= 7.2139, 95% CI =2.3137-22.4922, P=0.0007) were tightly correlated with OS ( Fig. 6a). Likewise, in multivariable Cox regressive analyses,the risk scoring (HR= 12.9671, 95% CI =1.6444-102.2522, P=0.015) and age(HR= 1.1387, 95% CI =1.0796-1.2010, P＜0.001) were tightly correlated with OS( Fig. 6b). The prognosis nomograph integrating independent factors of OS was displayed by Fig. 6c.The C-indexes for OS forecast were 0.959 (95%CI, 0.939‐0.979).The correction plot of the predictive ability at 1-, 3-, 5-years showed a good consistency bewteen the observed overall survival and nomogram−predicted overall survival( Fig. 6d).

Functional Analyses based on Risk Score and Immune Score

To unveil the biofunctions and paths related to the risk scoring and immunity scoring,our research group initially find out the DEGs between the risk_high and risk_low groups, and the DEGs between high immune score and low immune score were also analyzed. The DEGs existing in both the risk scoring and immunity scoring were selected to complete the GO and KEGG analyses.A total of 555 DEGs in the risk score and 1028 DEGs in the immune score were acquired, among which 270 DEGs were significant in both groups( Fig. 7a). Figure 7b displays the the top 10 BP terms, CC terms, and MF terms, the primary sponged Go terms were muscle filament sliding, actin-myosin filament sliding, muscle system process, contractile fiber, and hormone metabolic process. Unfortunately, no pathways were observed based on the KEGG analysis.

Comparison of Immune Activity

The enrichment scoring of immunocytes and immunity-associated pathways was caculated by ssGSEA.The heatmap showed the enrichment scoring of each immunocyte and immune pathway( Fig. 8a).Then, the relationship between immunocytes and immunity-associated pathways was studied.Among immunocytes, TIL and Th1 cells showed the strongest positive correlation, and TIL and Tfh also showed a strong positive correlation( Fig. 8b).Among immunity-associated pathways, CCR and Check-point showed the strongest positive correlation, and T_cell_co−inhibition also showed a strong positive correlation with check-point( Fig. 8c).Eventually, our team contrasted the immune status between the risk_high and risk_low groups.B cells, DCs, iDCs, Neutrophilic cells, Tfh, Th2_cells, and Treg were remarkably diverse between these 2 groups(P＜0.05, Fig. 9a). APC_co_stimulation and Type_II_IFN_reponse also demonstrated a notable diversity(P＜0.05, Fig. 9b).

Relationship among Prognostic DEGs and Immunocytes and Immunity-associated pathways

A total of 10 DEGs (FABP4, DPP6, PKHD1L1, TNNT3, EPYC, MYH2, MYL1, SLC25A15, TNNI2, ACTA1) were screened out throuth univariate cox analyses. EPYC, TNNT3, and TNNI2 displayed a strong positive relationship with immunocytes and immunity-associated pathways.Meanwhile, FABP4, DPP6, PKHD1L1 and SLC25A15 showed a negative correlation with immunocytes and immunity-associated pathways( Fig. 10).

M⁷G methylation is the commonest tRNA modification as well as the 5-hydroxymethylcytosine (hm5C), 5-methylcytosine (m5C), N1-methyladenosine (m1A), N6-methyladenosine (m6A), and it is pivotal for the onset and progression of tumor[18, 19]. METTL1 and WDR4 have been proved to have an effect on the promotion and inhibition of tumor through m⁷G methylation in different tumor types[20, 21].MiRNA is a negative modulator of genes and is associated with many diseases, such as cancer and inflammatory diseases.In addition,the dysregulation of miNRA can make the gene regulation more complex[22]. Hence, revealing the fundamental casual links of miRNA modulation might offer valuable enlightenment for cancer treatment.

In our study,we initially predicted the m⁷G methylation-related miRNAs through METTL1 and WDR4.Then,the expression of m⁷G methylation-related miRNAs in THCA and normal specimens was comprehensively studied.The results showed that 47 of them were differently expressed miRNAs(28 upregulated and 19 downregulated),and 7 of them were tightly related to OS,which indicated that m⁷G methylation-related miRNA was associated with THCA and hence demonstrated the prediction significance.To further assess the predictive value of these miRNAs, a novel miRNA-derived prognosis hallmark was developed in this research, and the prognosis significance was excellent. The hallmark developed in the present paper provides potential biomarkers for THCA.

A total of 7 miRNAs(hsa-miR-146b-3p, hsa-miR-181a-2-3p, hsa-miR-6860, hsa-miR-221-5p, hsa-miR-96-5p, hsa-miR-214-3p, hsa-miR-612) were discovered to be independent factors of OS in THCA sufferers and were selected to establish a prognosis model. The overexpression of miR-146b-3p considerably facilitated the proliferative, metastatic, and invasive abilities of colorectal cancer and related to poor prognosis,which revealed that miR-146b-3p was an oncogenic gene in colorectal cancer [23].Another study on papillary thyroid cancer indicated that the increased expression of miR-146b-3p could enhance the invasive ability and metastasis of papillary thyroid cancer[24]. Similarly, miR-146b-3p was regulated upward in cancer samples in our research, which implied that miR-146b-3p might be a carcinogenic element in THCA. MiR-181a-2-3p can stimulate the development of gastric carcinoma via targeting MYLK[25].The same conclusion was confirmed in another research[26].In our analysis, miR-181a-2-3p was significantly upregulated in tumor samples and might act as a carcinogenic factor in THCA.There were few researches focusing on the founction of miR-6860 in cancer.According to the results of our study, we assume that miR-6860 can promote the progression of THCA,which needs further researches.The expression of miR-221-5p in serum is tightly correlated with the prognosis of gastric cancer[27].Another in vitro and vivo study showed that miR-221-5p modulated the cellular proliferaton and metastasis of human prostate carcinoma via the MAPK pathway[28].The roles of miR-96-5p have been researched in different types of cancers,including gastric cancer[29], oral cancer[30],breast cancer[31], and it acts as a tumor promoter in theses cancers, which is conssitent with our result regarding THCA. On the contrary,miR-214-3p was regulated downward in hepatocellular carcinoma and was linked to poor OS and recurrence[32]. Downregulated miR-214-3p facilitates the proliferation of breast cancer cells[33].The expressing level of miR-214-3p in our study was considerably regulated downward in tumor samples and related to poor prognosis,which revealed that miR-214-3p was a cancer inhibitor in THCA. The overexpression of miR-612 can repress the development, invasion, and tumorigenesis of melanoma cells[34] and cervical cancer [35] through different pathways.A study on papillary thyroid cancer indicated that the expression of miR-612 could inhibit the migration and invasion of PTC[36]. Our team discovered that miR-612 was downregulated in THCA samples and its low expressing level could forecast satisfactory OS, which revealed that it was a tumor-inhibiting factor herein. In summary,two of the miRNAs in the signature were downregulated in THCA samples, whereas five of them were upregulated and were related to OS in this study.Whether this miRNA palys a role in THCA patients’ prognosis by affecting m⁷G methylation remains to be studied.

The tumor immunity and m⁷G methylation are both hotspots of cancer research. However,the relationship between them remains elusive, GO and KEGG analyses were performed in this paper.Unfortunately, no immune-related biological processes and pathways were enriched.We futher screened out the DEGs as per the risk scoring and immunity scoring and unexpectedly discovered a significant difference between immunocytes and immunity-associated pathways.A previous study[37] has identified that Treg cells are tightly correlated with oncocyte metastasis and unsatisfactory prognostic results in PTC sufferers, which was coherent with our research. Thus, we assumed that the unfavorable clinical outcomes might be induced by the damaged anti-cancer immunity.In the present study,the prognosis DEGs displayed a strong relationship with immunocytes and immunity-associated pathways, which revealed that targeting immune-related pathways might be a new direction for the treatment of THCA.

The potential mechanisms of the m⁷G methylation-related miRNAs in THCA were still unclear.In the current study,the 7 m⁷G methylation-related miRNAs demonstrated a srong predictive power in THCA,and they might be biomarkers for THCA therapies.However, our signature was limited by public databases and lacked in vivo and vitro verifications, hence it ought to be confirmed by further researches and function assays.

Our team successfully established a novel predictive model based on 7 m⁷G methylation-related miRNAs, which exhibited an excellent forecast power and offered new enlightenment regarding the forecast of THCA prognoses. The latent mechanisms beneath the m⁷G methylation-associated miRNAs and cancer immune activity in THCA are still elusive and require more explorations.

THCA

Thyroid cancer

TCGA

The Cancer Genome Atlas

LASSO

Least absolute shrinkage and selection operator

miRNAs

MicroRNAs

overall survival

ROC

Receiver operating characteristic

Fold change

FDR

False discovery rate

Gene Oncology

KEGG

Kyoto Encyclopedia of Genes and Genomes

PCA

Principal component analysis

DEGs

Differentially expressed genes.BP:Biological process

Cellular Component

Molecular Function.

Ethics approval and consent to participate

Not applicable.

Consent for publication

All authors agree to publish the paper.

Availability of data and materials

The data analyzed in the study can be found on the TCGA database (https://portal.gdc.cancer.gov/).

Competing interests

The authors have no conflict of interest to declare.

Funding

This study was funded by the Science and Technology Project of Jiaxing（2022AD30076）.

Authors’ Contributions

LL designed this study; XYQ took charge of data analysis, prepared the figures, and wrote the manuscript; JT, YQC, ZQC,LC,CS took charge of data collection as well as the critical reading regarding the manuscript. The final manuscript has been read and approved by all authors.

Acknowledgments

All authors acknowledge the contributions from TCGA project.

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No competing interests reported.

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Version 1

posted 26 May, 2022

You are reading this latest preprint version

A novel m7G methylation-related miRNA signature for overall survival prediction in thyroid cancer

Status:

Version 1

Abstract

Background

Methods

Results

Conclusion

Figures

Introduction

Materials And Methods

Data Collection

Development of a Prognostic m⁷G Methylation-Related miRNA Signature

Functional Enrichment Analysis

Immune Activity Analysis

Relationship among Prognostic DEGs and Immunocytes and Immunity-associated pathways

Statistics

Results

Development of a Prognostic m⁷G Methylation-Related miRNA Signature

Independent Prognostic Value of the Risk Signature

Functional Analyses based on Risk Score and Immune Score

Comparison of Immune Activity

Relationship among Prognostic DEGs and Immunocytes and Immunity-associated pathways

Discussion

Conclusion

Abbreviations

Declarations

References

Competing Interests

Status:

Version 1

A novel m7G methylation-related miRNA signature for overall survival prediction in thyroid cancer

Status:

Version 1

Abstract

Background

Methods

Results

Conclusion

Figures

Introduction

Materials And Methods

Data Collection

Development of a Prognostic m7G Methylation-Related miRNA Signature

Functional Enrichment Analysis

Immune Activity Analysis

Relationship among Prognostic DEGs and Immunocytes and Immunity-associated pathways

Statistics

Results

Development of a Prognostic m7G Methylation-Related miRNA Signature

Independent Prognostic Value of the Risk Signature

Functional Analyses based on Risk Score and Immune Score

Comparison of Immune Activity

Relationship among Prognostic DEGs and Immunocytes and Immunity-associated pathways

Discussion

Conclusion

Abbreviations

Declarations

References

Competing Interests

Status:

Version 1

Development of a Prognostic m⁷G Methylation-Related miRNA Signature

Development of a Prognostic m⁷G Methylation-Related miRNA Signature