miR-455-3p has superior diagnostic potential to PSA in peripheral blood for prostate cancer

doi:10.21203/rs.3.rs-4066028/v1

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Research Article

miR-455-3p has superior diagnostic potential to PSA in peripheral blood for prostate cancer

https://doi.org/10.21203/rs.3.rs-4066028/v1

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Background

Prostate-specific antigen (PSA) is commonly used as a biomarker to diagnose and predict the course of prostate cancer (PCa). However, PSA detection is susceptible to changes in the physiologic environment, which may lead to some misdiagnosis. Thus, it is crucial to find a novel diagnostic marker.

Methods

We accessed microRNA (miRNA) expression datasets (GSE206793 and GSE112264) from the GEO database, analyzing peripheral blood samples from PCa patients. Differentially expressed miRNAs (DEmiRNAs) were identified using GEO2R. A specific miRNA, miR-455-3p, was pinpointed through rigorous analysis of clinical correlations and ROC curves. Peripheral blood samples from healthy individuals and PCa patients were subjected to qRT-PCR validation, aligning results with the GSE206793 dataset. The miRWalk database was utilized to predict downstream genes, while STRING facilitated the construction of a protein-protein interaction (PPI) network. KEGG pathway analysis enriched our understanding of potential molecular pathways.

Results

We found that miR-455-3p was highly expressed in the peripheral blood of PCa patients with Gleason score (GS) ≥ 8, while independent of T stage, age and PSA. ROC analysis revealed a favorable diagnostic efficacy of miR-455-3p and AUC for the two datasets was respectively 0.943 and 0.847. The qRT-PCR assay also revealed consistent results. Interestingly, the PSA levels of P1 (GS = 5 + 4) and P6 (GS = 3 + 3) were respectively 3.38 and 4.45 ng/ml, while miR-455-3p was highly expressed in both, suggesting its low misdiagnosis. The speculation was validated in GSE206793 dataset. Finally, 9 potential targets of miR-455-3p were predicted. PPI network revealed PPP2R2A, ITGB1 and CDKN1A as key nodes. KEGG pathway analysis revealed that they were enriched in various cancers, biological processes and molecular signals.

Conclusion

Our study identifies miR-455-3p as a promising diagnostic marker for PCa, outperforming PSA in terms of specificity and sensitivity. The robustness of miR-455-3p, coupled with its potential downstream targets and associated pathways, highlights its clinical significance for improved PCa diagnosis and management.

prostate cancer

miR-455-3p

prostate-specific antigen

diagnostic marker

receptor operating characteristic

Prostate cancer (PCa) is one of the common malignant tumors in the male urinary system worldwide, whose incidence and mortality are increasing year by year (Lowrance et al. 2023). What’s worse is that the bone metastasis and recurrence commonly occur, which makes the prognosis poor (Wells et al. 2023). The basic diagnosis of PCa includes rectal digital examination detection, serum prostate-specific antigen (PSA) detection, biopsy analysis and histological analysis (Litwin and Tan 2017). However, the PCa progress and unnormal hyperplasia are difficult to be verified by these methods(Jansen et al. 2009; Jones and Koeneman 2008). In particular, PSA results are susceptible to drugs, inflammation and benign prostatic lesions, leading to a lack of specificity and sensitivity in PCa prognosis(Llop et al. 2018). Therefore, it is crucial to find a novel clinical diagnostic marker.

microRNAs (miRNAs) are the single-stranded non-coding RNAs with high conservative. They were constructed with a length of about 18 to 22 nucleotides(Correia et al. 2019). miRNAs interfere with protein translation by binding to the sequences in the 3’ untranslated region (UTR) of messenger RNAs (mRNAs), reducing the stability of mRNAs or inhibiting the expression of the transcription genes(Bartel 2009). Participating in various physiological processes such as cell proliferation and apoptosis, it plays an important regulatory role in diseases and is closely related to the occurrence of various tumors(Jaszczuk et al. 2022; Menon et al. 2022; Tong et al. 2022). Circulating miRNAs have received increasing attention in recent years as diagnostic markers for various diseases due to their convenience in monitoring(Li et al. 2013; Luo et al. 2013; Valihrach et al. 2020). Studies have shown that circulating miRNAs are complementary candidate biomarkers for PCa diagnosis.

With the development of sequencing technology, bioinformatics has been used to explore the pathological mechanisms of various diseases at the gene level. Gene Expression Omnibus (GEO) database is an online gene chip database of gene expression in species(Clough and Barrett 2016). Gene maps and microarrays are used to screen for differentially expressed miRNAs (DEmiRNAs) and genes. However, the research on biomarkers is still insufficient. The present study identified a common target, miR-455-3p, via interaction analysis of two GEO datasets. miR-455-3p was then analyzed for correlation with clinical features in PCa and validated with clinical samples. The downstream binding genes of miR-455-3p were further predicted. Finally, a protein-protein interaction (PPI) network was constructed for the target genes and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis was performed.

Data collection

The GSE206793 and GSE112264 datasets from the GEO database (ncbi.nlm.nih.gov/geo/) were selected for subsequent analysis. Samples for both datasets were obtained from peripheral blood of healthy individuals and cancer patients. GSE206793 dataset included 5 healthy individuals, 40 low-risk, 16 medium-risk and 91 high-risk PCa patients with clinical informations (including age, Gleason score (GS) and PSA). GSE112264 dataset included 41 healthy individuals, 809 PCa patients with different Tumor (T) stages (T1 to T4) and 50 each of 10 other cancer patients (including biliary tract cancer, bladder cancer, colorectal cancer, esophageal cancer, gastric cancer, glioma, hepatocellular carcinoma, lung cancer, pancreatic cancer and sarcoma). The two datasets were built on GPL19117 (Affymetix Multispecies miRNA-4 Array) and GPL21263 (3D-Gene Human miRNA V21_1.0.0) platforms, respectively.

DEmiRNAs screening

GEO2R is an interactive network tool, which can compare and analyze multiple samples under the same experimental conditions. Gene expression matrices were analyzed and downloaded online using GEO2R. For GSE206793 dataset, |log2 (fold change, FC)| > 1 and P < 0.05 were used as the screening conditions. For the GSE112264 dataset, which had a large screening range due to its large cases, |log2 (FC)| > 3 and P < 0.01 were used as screening conditions for dimensionality reduction. The DEmiRNAs screened from the two datasets were interacted to screen for a target miRNA (miR-455-3p).

Clinical feature analysis

In GSE206793 dataset, miR-455-3p expression was analyzed in PCa patients with different risk degrees. PCa patients were further divided into two groups based on age (< 60 vs ≥ 60), GS (< 8 vs ≥ 8) and PSA (< 4 vs ≥ 4) for comparison. In GSE112264 dataset, miR-455-3p expression was analyzed in PCa patients with different T stages and compared with other cancer patients. The receptor operating characteristic (ROC) of miR-455-3p in both datasets was further analyzed using the pROC R package to evaluate its diagnostic efficacy.

Clinical sample collection

We collected peripheral blood samples from 8 PCa patients diagnosed in the Department of Urology of the Fifth Hospital of Guangzhou Medical University and 4 healthy individuals. The magnetic resonance imaging (MRI) films and pathologic informations of the PCa patients were provided by the Department of Radiology of the Fifth Affiliated Hospital of Guangzhou Medical University. The study was approved by the Ethics Committee of the Fifth Hospital of Guangzhou Medical University. Ethical approval number: KY01-2021-11-06.

Quantitative reverse transcription PCR (qRT-PCR) assay

Total RNA was extracted from peripheral blood samples using Trizol reagent (BioTeke, China). After determining the concentration and purity of RNA samples, RNA reverse transcription was performed according to the steps of reverse transcription kit (Vazyme, China). The synthetic cDNAs were used as template for fluorescence detection using SYBR Green qPCR detection kit (Biosharp, China). The results were quantified using the relative quantitative 2^−∆∆CT method. The relative miR-455-3p expression was normalized to U6 expression. Primer sequences of miR-455-3p: 5ʹ-ACACTCCAGCTGCAGTCCATGGGCAT-3ʹ (F) and 5ʹ-ACTGGTG TCGTGGAGTCGGC-3ʹ (R). Primer sequences of U6: 5ʹ-GCTTCGGCACATATACT AAAAT-3ʹ (F) and 5ʹ-CGCTTCACGAATTTGCGTGTCAT-3ʹ (R).

Target gene prediction

The miRWalk website (http://mirwalk.umm.uni-heidelberg.de/) was used to predict the target genes of miR-455-3p. Candidate genes were identified by setting the screening conditions (binding score as 1, acting position as 3' UTR and both in miRDB and miRTarBase).

PPI network construction

Interaction analysis between miR-455-3p targets using the STRING website (https://cn.string-db.org/) and constructing a PPI network. Active interaction sources for PPI included textmining, experiments, databases, co-expression, neighbourhood, gene fusion and co-occurrence. The interaction score was set to 0.4 (medium confidence).

KEGG pathway analysis

KEGG pathways were enriched by calculating strength (enrichment index) and false discovery rate (FDR) based on PPI network counts. The top 20 enriched pathways with FDR < 0.05 were displayed.

Statistical analysis

SPSS 25.0 software was used for statistical analysis. The measurement data were expressed as t test and mean ± SD. The enumeration data were expressed as chi-square test. Adjust P values were obtained from multiple hypothesis test. P < 0.05 was considered statistically signiffcant.

miR-455-3p is highly expressed in peripheral blood of PCa patients

To obtain DEmiRNAs in peripheral blood of PCa patients, we performed a comparative analysis between GSE206793 and GSE112264 datasets. For GSE206793 dataset, 46 DEmiRNAs were obtained by screening with a thresholds of |log2 (FC)| > 1 and P < 0.05 (Fig. 1A). Due to the large samples in GSE112264 dataset, 604 DEmiRNAs were obtained by dimensionality reduction with a higher screening threshold of |log2 (FC)| > 3 and P < 0.01 (Fig. 1B). We found that miR-455-3p co-occurred in both datasets (Fig. 1C). Furthermore, miR-455-3p was highly expressed in the peripheral blood of PCa patients compared to healthy individuals (Fig. 2A and 2C). Figure 1D demonstrates the miR-455-3p expression in each sample of the GSE112264 dataset. These results suggest that miR-455-3p may be a risk factor for PCa development.

miR-455-3p has a unique clinical feature in PCa

Further insight into the correlation between miR-455-3p and clinical features of PCa. Patients in the GSE206793 dataset were divided into low-risk, medium-risk and high-rsk groups according to the EAU-ESTRO-SIOG Guidelines on Prostate Cancer. Patients in the GSE112264 dataset were divided into T1, T2, T3 and T4 groups according to T stage. We found that miR-455-3p expression was not associated with risk degree and T stage (Fig. 2B and 2D). Then, patients in the GSE206793 dataset were divided into two groups based on age (< 60 vs ≥ 60), GS (< 8 vs ≥ 8) and PSA (< 4 vs ≥ 4) for comparison. The results revealed that miR-455-3p was highly expressed in patients with GS ≥ 8, independent of age and PSA (Fig. 3A-3C). The miR-455-3p expression in peripheral blood of other cancer patients was further observed. Compared with PCa, miR-455-3p was highly expressed in lung cancer, glioma and bladder cancer, suggesting a risk feature in cancer (Fig. 2E). These results indicate that miR-455-3p is a risk factor for PCa.

miR-455-3p has high diagnostic efficacy for PCa

To validate the diagnostic efficacy of miR-455-3p, ROC analysis was performed on both datasets. ROC is a coordinate diagram for statistical analysis formed with the false-positive rate on the horizontal axis and the true-positive rate on the vertical axis. Area under the curve (AUC) is the most important measure of ROC analysis. Typically, the AUC value ranges from 0.5 to 1.0. The higher the AUC value, the better the diagnostic efficacy. The results indicated that miR-455-3p had favorable diagnostic efficacy in GSE206793 and GSE112264 datasets, with AUC values of 0.943 and 0.847, respectively (Fig. 3D and 3E). This indicates that miR-455-3p can be a novel diagnostic marker for PCa.

To clarify the diagnostic efficacy of miR-455-3p, we collected peripheral blood samples from 4 healthy individuals and 8 PCa patients for expression validation. qRT-PCR results demonstrated that miR-455-3p was highly expressed in patients with GS ≥ 8, which was consistent with the analyzed results of the GSE206793 dataset (Fig. 4A and 4B). The diagnostic efficacy between miR-455-3p and PSA was further compared. The serum PSA levels of 8 PCa patients were obtained based on their case reports, and the comparison revealed that PSA levels were not associated with GS (Fig. 4C). Interestingly, 2 patients (P1 and P6) had aberrant serum PSA levels of 3.38 and 4.45 ng/ml, while their GS was 9 (5 + 4) and 6 (3 + 3), respectively (Fig. 4D). PSA was misdiagnosed in P1 and had low diagnostic efficacy in P6, while the corresponding miR-455-3p was highly expressed (Fig. 4D). MRI films of P1 and P6 further demonstrated their lesions (Fig. 4E). Conclusively, we speculate that miR-455-3p may possess a superior diagnostic efficacy to PSA.

miR-455-3p has superior diagnostic efficacy to PSA

To further verify our speculation, we obtained 20 PCa patients with serum PSA < 4 ng/ml from GSE206793 dataset for expression validation. Comparison among all PCa patients revealed that PSA levels were not associated with GS, which was consistent with the clinical samples detection (Fig. 5A). Expression validation against 20 misdiagnosed patients showed that miR-455-3p was highly expressed in these patients compared to 5 healthy individuals (Fig. 5B). In addition, miR-455-3p was highly expressed in patients with GS ≥ 8 compared to those with GS < 8, further emphasizing its correlation with high risk of PCa (Fig. 5C). Figure 5D demonstrated the serum PSA level with miR-455-3p expression in each misdiagnosed patient, which better illustrated the superior diagnostic efficacy of miR-455-3p to PSA.

PPP2R2A, ITGB1 and CDKN1A are key targets of miR-455-3p for cancer regulation

Finally, we provide insight into the related molecular mechanisms of miR-455-3p involved in the regulation of biological functions. Based on the transcriptional repression effect of miRNAs, 9 potential target genes of miR-455-3p (PPP2R2A, ATL2, TOR1B, POFUT2, CDKN1A, GIGYF2, ITGB1, GGCX and OTULINL) were successfully predicted using miRWalk website. The PPI network was further constructed for 9 target proteins using STRING website, in which PPP2R2A, ITGB1 and CDKN1A could be grouped into 3 clusters, respectively (Fig. 6A). KEGG pathway analysis revealed that these proteins were enriched in various cancers including PCa (such as small cell lung cancer, bladder cancer, glioma, pancreatic cancer and melanoma), biological processes (such as cell cycle, cellular senescence and focal adhesion) and molecular signals (such as p53, PI3K/Akt and FoxO signaling pathways) (Fig. 6B). These studies provide a basis for the molecular biology of miR-455-3p mediating PCa development.

PCa is a common clinical disease with a complex pathogenesis. Decreased immunity or changes in intracellular genetic material will lead to uncontrolled or abnormal cell growth(El-Amm et al. 2013; Ito 2014; Siegel et al. 2019). Although there have been some studies on circulating miRNAs as diagnostic markers for PCa, their diagnostic roles are still controversial, such as inconsistent results from different data sources(Cannistraci et al. 2014). In addition, individual differences in patients and tumor heterogeneity can affect the diagnostic efficacy of circulating miRNAs, thus hardly forming a unified conclusion(Aiso et al. 2018; Gasch et al. 2015; Hara et al. 2022; Yu et al. 2019).

The present study was based on two datasets (GSE206793 and GSE112264) expressing miRNAs in peripheral blood of PCa patients for diagnostic analysis. By setting reasonable screening thresholds, it was found that miR-455-3p co-occurred in both datasets and was highly expressed in PCa patients. In addition, miR-455-3p was highly expressed in patients with high GS, independent of T stage, age and PSA. Serum miR-455-3p was also highly expressed in other cancer patients, especially lung cancer, glioma and bladder cancer. These findings revealed a unique clinical feature of miR-455-3p in PCa. In glioma, miR-455-3p is highly expressed in patient tissues and represents an independent prognostic indicator of overall survival in patients, promising to serve as a prognostic biomarker(Wang et al. 2019). In liver cancer (LC), there was a 1.022-fold increase in the odds ratio for each unit increase in miR-455-3p, and increased serum levels of miR-122-5p and miR-455-3p were independently associated with an increased risk of incident LC in type 2 diabetes (T2D), which may be the potential biomarkers for early diagnosis of LC in T2D(Lee et al. 2021). Moreover, miR-455-3p has a potential diagnostic role in other non-cancer diseases, such as acute graft-versus-host disease, Alzheimer's disease and acute myocardial infarction(Lee et al. 2021). Consistent with these studies, ROC analysis demonstrated a favorable diagnostic efficacy of miR-455-3p in PCa patients (AUC > 0.8).

To validate the diagnostic efficacy of miR-455-3p, clinical blood samples were collected for assay. Consistent with the analysis of both datasets, miR-455-3p was highly expressed in PCa patients with GS ≥ 8, while PSA levels were not associated with GS. Among the 8 PCa patients, P1 with high GS (5 + 4) had a misdiagnosis of serum PSA < 4 ng/ml, while P6 with medium GS (3 + 3) had a serum PSA of 4.45 ng/ml, which was inconsistent with the risk degree. Clinically, serum PSA ≥ 4 ng/ml suggests a risk of developing PCa(Ito et al. 2004). However, PSA has the disadvantages of high false-positive rate, low sensitivity and inability to distinguish the malignancy degree of the tumor, failing to accurately diagnose and predict PCa development (Gupta et al. 2022; Jin et al. 2020; Schatteman et al. 2000). However, miR-455-3p was highly expressed in both P1 and P6, suggesting that it may have a superior diagnostic efficacy to PSA. Further validation using the GSE206793 dataset also revealed similar results. miR-455-3p was highly expressed in 20 misdiagnosed PCa patients (PSA < 4 ng/ml). Our study identified that miR-455-3p could be used as a novel diagnostic marker for PCa. Although miR-455-3p may have an advantage in diagnostic efficacy compared with PSA, a larger sample amount is still needed for validation.

Finally, the downstream targets of miR-455-3p were predicted by miRWalk website and 9 potential genes (PPP2R2A, ATL2, TOR1B, POFUT2, CDKN1A, GIGYF2, ITGB1, GGCX and OTULINL) were successfully screened. PPI network revealed that PPP2R2A, ITGB1 and CDKN1A were the key nodes. KEGG results indicated that they were closely related to cancer and involved in the regulation of various biological processes and molecular signals. In PCa, upregulation of miR-556-5p promoted cell proliferation by suppressing PPP2R2A expression(Zhao et al. 2015). In bladder cancer, miR-222 attenuated cisplatin-induced cell death by targeting the PPP2R2A/Akt/mTOR axis(Zeng et al. 2016). In addition, ITGB1 and CDKN1A were found to play key regulatory roles in PCa(Jain et al. 2013; Kurozumi et al. 2016; Lai et al. 2021; Pellinen et al. 2018). These results further suggest an important mediating role of miR-455-3p in PCa development.

In conclusion, miR-455-3p is highly expressed in the peripheral blood of PCa patients and correlates with GS. miR-455-3p is a novel diagnostic marker for PCa with superior diagnostic potential to PSA.

PSA

Prostate-specific antigen

PCa

Prostate cancer

miRNAs

microRNAs

GEO

Gene Expression Omnibus

DEmiRNAs

Differentially expressed miRNAs

Gleason score

Tumor

ROC

Receiver operating characteristic

AUC

Area under the curve

qRT-PCR

quantitative reverse transcriptase PCR

PPI

Protein-protein interaction

KEGG

Kyoto Encyclopedia of Genes and Genomes

UTR

Untranslated region

mRNAs

messenger RNAs

Fold change

MRI

Magnetic resonance imaging

FDR

False discovery rate

Standard deviation

Liver cancer

T2D

Type 2 diabetes

PPP2R2A

Protein phosphatase 2 regulatory subunit Balpha

ITGB1

Integrin subunit beta 1

CDKN1A

Cyclin dependent kinase inhibitor 1A

Ethics approval and consent to participate

Not applicable.

Consent for publication

Not applicable.

Availability of data and materials

The data presented in this study are available on request from the corresponding authors.

Competing interests

The authors declare that they have no competing interests.

Funding

This work was supported by Plan on enhancing scientific research in GMU and National Natural Science Foundation of China (Grant Number: 82201522).

Authors' contributions

Guangbin Zhu and Haiyan Wang conceived and designed the study. Yi Cen and Shourui Feng designed the experiments and wrote the original manuscript.

Yuyu Xu and Churuo Zhang performed the experiments and data analysis. Xiangjin Lin and Xuan Ye made the acquisition of data. Zeyu Zha did the analysis and interpretation of data. All authors read and approved the manuscript.

Aiso, T., Ohtsuka, K., Ueda, M., Karita, S., Yokoyama, T., & Takata, S., et al. (2018) Serum levels of candidate microRNA diagnostic markers differ among the stages of non-small-cell lung cancer. Oncology Letters, 16(5):6643–6651. doi:10.3892/ol.2018.9464.
Bartel, D.P. (2009) MicroRNAs: target recognition and regulatory functions. Cell, 136(2):215–233. doi:10.1016/j.cell.2009.01.002.
Cannistraci, A., Di Pace, A.L., De Maria, R., & Bonci, D. (2014) MicroRNA as new tools for prostate cancer risk assessment and therapeutic intervention: results from clinical data set and patients' samples. Biomed Research International, 2014:146170. doi:10.1155/2014/146170.
Chen, L., Bai, J., Liu, J., Lu, H., & Zheng, K. (2021) A Four-MicroRNA Panel in Peripheral Blood Identified as an Early Biomarker to Diagnose Acute Myocardial Infarction. Frontiers in Physiology, 12:669590. doi:10.3389/fphys.2021.669590.
Clough, E., & Barrett, T. (2016) The Gene Expression Omnibus Database. Methods Mol Biol, 1418:93–110. doi:10.1007/978-1-4939-3578-9_5.
Correia, D.S.M., Gjorgjieva, M., Dolicka, D., Sobolewski, C., & Foti, M. (2019) Deciphering miRNAs' Action through miRNA Editing. International Journal of Molecular Sciences, 20(24). doi:10.3390/ijms20246249.
El-Amm, J., Freeman, A., Patel, N., & Aragon-Ching, J.B. (2013) Bone-targeted therapies in metastatic castration-resistant prostate cancer: evolving paradigms. Prostate Cancer, 2013:210686. doi:10.1155/2013/210686.
Gasch, C., Plummer, P.N., Jovanovic, L., McInnes, L.M., Wescott, D., & Saunders, C.M., et al. (2015) Heterogeneity of miR-10b expression in circulating tumor cells. Scientific Reports, 5:15980. doi:10.1038/srep15980.
Gupta, K., Perchik, J.D., Fang, A.M., Porter, K.K., & Rais-Bahrami, S. (2022) Augmenting prostate magnetic resonance imaging reporting to incorporate diagnostic recommendations based upon clinical risk calculators. World Journal of Radiology, 14(8):249–255. doi:10.4329/wjr.v14.i8.249.
Hara, K., Murakami, M., Niitsu, Y., Takeuchi, A., Horino, M., & Shiba, K., et al. (2022) Heterogeneous circulating miRNA profiles of PBMAH. Frontiers in Endocrinology, 13:1073328. doi:10.3389/fendo.2022.1073328.
Ito, K. (2014) Prostate cancer in Asian men. Nature Reviews Urology, 11(4):197–212. doi:10.1038/nrurol.2014.42.
Ito, K., Yamamoto, T., Ohi, M., Takechi, H., Kurokawa, K., & Suzuki, K., et al. (2004) Cumulative probability of PSA increase above 4.0 NG/ML in population-based screening for prostate cancer. International Journal of Cancer, 109(3):455–460. doi:10.1002/ijc.11711.
Jain, A.K., Raina, K., & Agarwal, R. (2013) Deletion of p21/Cdkn1a confers protective effect against prostate tumorigenesis in transgenic adenocarcinoma of the mouse prostate model. Cell Cycle, 12(10):1598–1604. doi:10.4161/cc.24741.
Jansen, F.H., Roobol, M., Jenster, G., Schroder, F.H., & Bangma, C.H. (2009) Screening for prostate cancer in 2008 II: the importance of molecular subforms of prostate-specific antigen and tissue kallikreins. European Urology, 55(3):563–574. doi:10.1016/j.eururo.2008.11.040.
Jaszczuk, I., Koczkodaj, D., Kondracka, A., Kwasniewska, A., Winkler, I., & Filip, A. (2022) The role of miRNA-210 in pre-eclampsia development. Annals of Medicine, 54(1):1350–1356. doi:10.1080/07853890.2022.2071459.
Jin, W., Fei, X., Wang, X., Song, Y., & Chen, F. (2020) Detection and Prognosis of Prostate Cancer Using Blood-Based Biomarkers. Mediators of Inflammation, 2020:8730608. doi:10.1155/2020/8730608.
Jones, M.J., & Koeneman, K.S. (2008) Local-regional prostate cancer. Urologic Oncology-Seminars and Original Investigations, 26(5):516–521. doi:10.1016/j.urolonc.2008.03.007.
Kurozumi, A., Goto, Y., Matsushita, R., Fukumoto, I., Kato, M., & Nishikawa, R., et al. (2016) Tumor-suppressive microRNA-223 inhibits cancer cell migration and invasion by targeting ITGA3/ITGB1 signaling in prostate cancer. Cancer Science, 107(1):84–94. doi:10.1111/cas.12842.
Lai, W., Zhu, W., Xiao, C., Li, X., Wang, Y., & Han, Y., et al. (2021) HJURP promotes proliferation in prostate cancer cells through increasing CDKN1A degradation via the GSK3beta/JNK signaling pathway. Cell Death & Disease, 12(6):583. doi:10.1038/s41419-021-03870-x.
Lee, H.M., Wong, W., Fan, B., Lau, E.S., Hou, Y., & O, C.K., et al. (2021) Detection of increased serum miR-122-5p and miR-455-3p levels before the clinical diagnosis of liver cancer in people with type 2 diabetes. Scientific Reports, 11(1):23756. doi:10.1038/s41598-021-03222-x.
Li, C., Li, J.F., Cai, Q., Qiu, Q.Q., Yan, M., & Liu, B.Y., et al. (2013) MiRNA-199a-3p: A potential circulating diagnostic biomarker for early gastric cancer. Journal of Surgical Oncology, 108(2):89–92. doi:10.1002/jso.23358.
Litwin, M.S., & Tan, H.J. (2017) The Diagnosis and Treatment of Prostate Cancer: A Review. Jama-Journal of the American Medical Association, 317(24):2532–2542. doi:10.1001/jama.2017.7248.
Llop, E., Ferrer-Batalle, M., Barrabes, S., Guerrero, P.E., Ramirez, M., & Saldova, R., et al. (2018) Erratum: Improvement of Prostate Cancer Diagnosis by Detecting PSA Glycosylation-Specific Changes: Erratum. Theranostics, 8(3):746–748. doi:10.7150/thno.23906.
Lowrance, W., Dreicer, R., Jarrard, D.F., Scarpato, K.R., Kim, S.K., & Kirkby, E., et al. (2023) Updates to Advanced Prostate Cancer: AUA/SUO Guideline (2023). Journal of Urology, 209(6):1082–1090. doi:10.1097/JU.0000000000003452.
Luo, J., Chen, M., Huang, H., Yuan, T., Zhang, M., & Zhang, K., et al. (2013) Circulating microRNA-122a as a diagnostic marker for hepatocellular carcinoma. Oncotargets and Therapy, 6:577–583. doi:10.2147/OTT.S44215.
Menon, A., Abd-Aziz, N., Khalid, K., Poh, C.L., & Naidu, R. (2022) miRNA: A Promising Therapeutic Target in Cancer. International Journal of Molecular Sciences, 23(19). doi:10.3390/ijms231911502.
Motaei, J., Kerachian, M.A., Mousavi, S.A., Alimoghadam, K., Ghavamzadeh, A., & Manoochehrabadi, S., et al. (2021) Circulating miR-455-3p, miR-5787, and miR-548a-3p as potential noninvasive biomarkers in the diagnosis of acute graft-versus-host disease: a validation study. Annals of Hematology, 100(10):2621–2631. doi:10.1007/s00277-021-04573-1.
Pellinen, T., Blom, S., Sanchez, S., Valimaki, K., Mpindi, J.P., & Azegrouz, H., et al. (2018) ITGB1-dependent upregulation of Caveolin-1 switches TGFbeta signalling from tumour-suppressive to oncogenic in prostate cancer. Scientific Reports, 8(1):2338. doi:10.1038/s41598-018-20161-2.
Schatteman, P.H., Hoekx, L., Wyndaele, J.J., Jeuris, W., & Van Marck, E. (2000) Inflammation in prostate biopsies of men without prostatic malignancy or clinical prostatitis: correlation with total serum PSA and PSA density. European Urology, 37(4):404–412. doi:10.1159/000020161.
Siegel, R.L., Miller, K.D., & Jemal, A. (2019) Cancer statistics, 2019. Ca-a Cancer Journal for Clinicians, 69(1):7–34. doi:10.3322/caac.21551.
Swingler, T.E., Niu, L., Pontifex, M.G., Vauzour, D., & Clark, I.M. (2022) The microRNA-455 Null Mouse Has Memory Deficit and Increased Anxiety, Targeting Key Genes Involved in Alzheimer's Disease. International Journal of Molecular Sciences, 23(1). doi:10.3390/ijms23010554.
Tong, H., Wang, L., Shi, J., Jin, H., Zhang, K., & Bao, Y., et al. (2022) Upregulated miR-322-5p regulates cell cycle and promotes cell proliferation and apoptosis by directly targeting Wee1 in mice liver injury. Cell Cycle, 21(24):2635–2650. doi:10.1080/15384101.2022.2108128.
Valihrach, L., Androvic, P., & Kubista, M. (2020) Circulating miRNA analysis for cancer diagnostics and therapy. Molecular Aspects of Medicine, 72:100825. doi:10.1016/j.mam.2019.10.002.
Wang, W., Mu, S., Zhao, Q., Xue, L., & Wang, S. (2019) Identification of differentially expressed microRNAs and the potential of microRNA-455-3p as a novel prognostic biomarker in glioma. Oncology Letters, 18(6):6150–6156. doi:10.3892/ol.2019.10927.
Wells, K.V., Krackeler, M.L., Jathal, M.K., Parikh, M., Ghosh, P.M., & Leach, J.K., et al. (2023) Prostate cancer and bone: clinical presentation and molecular mechanisms. Endocrine-Related Cancer, 30(9). doi:10.1530/ERC-22-0360.
Yu, H., Guan, Z., Cuk, K., Zhang, Y., & Brenner, H. (2019) Circulating MicroRNA Biomarkers for Lung Cancer Detection in East Asian Populations. Cancers, 11(3). doi:10.3390/cancers11030415.
Zeng, L.P., Hu, Z.M., Li, K., & Xia, K. (2016) miR-222 attenuates cisplatin-induced cell death by targeting the PPP2R2A/Akt/mTOR Axis in bladder cancer cells. Journal of Cellular and Molecular Medicine, 20(3):559–567. doi:10.1111/jcmm.12760.
Zhao, W., Cao, L., Zeng, S., Qin, H., & Men, T. (2015) Upregulation of miR-556-5p promoted prostate cancer cell proliferation by suppressing PPP2R2A expression. Biomedicine & Pharmacotherapy, 75:142–147. doi:10.1016/j.biopha.2015.07.015.

No competing interests reported.

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miR-455-3p has superior diagnostic potential to PSA in peripheral blood for prostate cancer

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Abstract

Background

Methods

Results

Conclusion

Figures

Introduction

Materials and methods

Data collection

DEmiRNAs screening

Clinical feature analysis

Clinical sample collection

Quantitative reverse transcription PCR (qRT-PCR) assay

Target gene prediction

PPI network construction

KEGG pathway analysis

Statistical analysis

Results

miR-455-3p is highly expressed in peripheral blood of PCa patients

miR-455-3p has a unique clinical feature in PCa

miR-455-3p has high diagnostic efficacy for PCa

miR-455-3p has superior diagnostic efficacy to PSA

PPP2R2A, ITGB1 and CDKN1A are key targets of miR-455-3p for cancer regulation

Discussion

Abbreviations

Declarations

References

Additional Declarations

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