Advertisement
Browse Subject Areas
?

Click through the PLOS taxonomy to find articles in your field.

For more information about PLOS Subject Areas, click here.

  • Loading metrics

Open Access

Peer-reviewed

Research Article

The potential of piR-823 as a diagnostic biomarker in oncology: A systematic review

  • Eun Jung Sohn,

    Roles Formal analysis, Investigation, Writing – original draft

    Current address: Department of Biotechnology, Inje University, Gimhae, Republic of Korea

    Affiliations Research Center for Molecular Control of Cancer Cell Diversity, Pusan National University, Yangsan, Republic of Korea, Department of Anatomy, School of Medicine, Pusan National University, Yangsan, Republic of Korea

    ⨯
  • Myoung-Eun Han,

    Roles Formal analysis, Investigation

    Affiliations Research Center for Molecular Control of Cancer Cell Diversity, Pusan National University, Yangsan, Republic of Korea, Department of Anatomy, School of Medicine, Pusan National University, Yangsan, Republic of Korea

    ⨯
  • Young Mok Park,

    Roles Formal analysis, Funding acquisition, Validation

    Affiliation Department of Surgery, School of Medicine, Pusan National University, Yangsan, Republic of Korea

    ⨯
  • Yun Hak Kim,

    Roles Conceptualization

    Affiliations Department of Anatomy, School of Medicine, Pusan National University, Yangsan, Republic of Korea, Department of Biomedical Informatics, School of Medicine, Pusan National University, Yangsan, Republic of Korea

    ⨯
  • Sae-Ock Oh

    Roles Conceptualization, Supervision, Writing – original draft, Writing – review & editing

    hedgehog@pusan.ac.kr

    Affiliations Research Center for Molecular Control of Cancer Cell Diversity, Pusan National University, Yangsan, Republic of Korea, Department of Anatomy, School of Medicine, Pusan National University, Yangsan, Republic of Korea

    ⨯

Abstract

Background

Emerging evidence has demonstrated that PIWI-interacting RNAs (piRNAs) play important roles in various physiological processes and contribute to cancer progression. Moreover, piRNAs and PIWI protein levels are associated with the prognosis and chemoresistance of various cancers. The limitations of biomarkers challenge early detection and monitoring of chemoresistance and cancer relapse.

Methods

To evaluate the potential of piRNA as a diagnostic biomarker in oncology, we systematically reviewed previous studies on the subject. PubMed, Embase, and Cochrane databases were searched to evaluate the diagnostic relevance of piRNAs in cancer. Eighteen studies (2,352 patients) were included. The quality of each study was evaluated with AMSTAR and QUADAS-2 tool.

Results & conclusions

The area under the curve (AUC) values of 26 piRNAs in patients with cancer ranged from 0.624 to 0.978, with piR-9491 showing the highest value (0.978). The sensitivity of the total of 21 piRNAs in cancer patients was between 42.86 and 100, with piR-9491 showing the highest sensitivity (100). The specificity of these 21 piRNAs ranged from 60.10 to 96.67 (with piR-018569 showing the highest specificity (96.67)). Their odds ratios were between 1.61 and 44.67, and piR-12488 showed the highest odds ratio (44.67). Generally, the piRNAs in this review showed better sensitivity and AUC values than current clinical diagnostic biomarkers, although current biomarkers appear to be more specific. Reviewed piRNAs showed better diagnostic performance than currently used clinical biomarkers. Notably, piR-823 showed a significant diagnostic performance in four types of cancer (colorectal, esophageal, gastric, and renal cell cancer). However, all 18 studies included in this review were a case-control study. So, further prospective studies are required for their validation.

Citation: Sohn EJ, Han M-E, Park YM, Kim YH, Oh S-O (2023) The potential of piR-823 as a diagnostic biomarker in oncology: A systematic review. PLoS ONE 18(12): e0294685. https://doi.org/10.1371/journal.pone.0294685

Editor: Julie Decock, Qatar Biomedical Research Institute, QATAR

Received: May 23, 2023; Accepted: November 6, 2023; Published: December 7, 2023

Copyright: © 2023 Sohn et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: All relevant data are within the paper and its Supporting information files.

Funding: This work was supported by grants from the Medical Research Center (MRC) Program (NRF- 2022R1A5A2027161) and from the Bio&Medical Technology Development Program (No. RS-2023-00223764) of the National Research Foundation (NRF) funded by the Korean government (MSIT). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Competing interests: The authors have declared that no competing interests exist.

Introduction

PIWI-interacting RNAs (piRNAs) have been shown to play critical roles in many physiological and pathological processes since their discovery in germ cells in 2006 [1]. piRNAs are small non-coding RNA molecules consisting of 23–31 nucleotides and are mainly involved in the regulation of gene expression and maintenance of genomic integrity. Many studies have shown that piRNAs differ from miRNAs or siRNAs in terms of their chemical structure, size, processing, precursors, associated proteins, and functional mechanisms [2]. piRNAs have 2’-O-methylation at their 3’-end and bind to a PIWI protein, an Argonaute/PIWI family protein, to form the piRNA-induced silencing complex (piRISC). The main functional mechanisms by which piRNAs regulate gene expression involve regulation of RNA degradation and modification of chromatin structure and histone proteins. They can suppress transposable elements (TEs), which are DNA sequences that move around the genome and disrupt gene function [3] through cleavage following base pairing with their target genes. Notably, they can also target non-transposon (protein-coding) genes. For example, mouse pachytene piRNAs can cleave target mRNA together with the mouse PIWI homolog (MIWI) protein through an siRNA-like mechanism [4]. Interestingly, they regulate mRNA stability by promoting deadenylation and decay. Mouse pachytene piRNAs can recruit deadenylase CAF1 to late spermatids [5]. In addition, they can modify the chromatin structure and histone proteins by interacting with DNA [6] and histone methylation machinery [7, 8].

Critical roles of piRNAs have been suggested in a variety of physiological processes, including germline cell biology, development, neuronal function, and immune responses [9–15]. They have also been associated with pathological conditions, including cancer [16], reproductive diseases, retinal diseases, cardiovascular diseases, and neurodegenerative diseases [17, 18]. Abnormal piRNA expression has been observed in many cancer types, including breast cancer, colorectal cancer, glioma, lymphoma, and multiple myeloma. Some oncogenic piRNAs, including piR-36026, piR-54265, piR-33221, and piR823, promote tumor progression by increasing cell proliferation, migration, and invasion, while inhibiting apoptosis. However, some tumor-suppressor piRNAs, including piR-36712, inhibit tumor development. piR-36712 overexpression in breast cancer cells has been shown to decrease cell proliferation and tame malignant phenotypes, while its knockdown increases cancer cell proliferation.

The potential use of piRNAs as biomarkers for various diseases, including cancer and cardiovascular, neurodegenerative, and infectious diseases, has been suggested. Notably, owing to their high stability, the potential of piRNAs as non-invasive biomarkers in body fluids has been evaluated. It is possible that the 2’-O-methyl modification in piRNAs may be stabilizing by protecting against 3’ uridylation and truncation [19, 20]. Notably, piRNAs have been observed in human body fluids, including serum and plasma samples, and remain stable after long-term incubation at room temperature [21–26]. Early detection and monitoring of chemoresistance and cancer relapse are complicated by the limitations of current biomarkers. Therefore, in this review, we evaluated the potential of piRNAs as diagnostic biomarkers for cancer.

Methods

This systematic review was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (S1 Table, PRISMA) statement [27].

Search strategy

Relevant literature was identified through searches in the PubMed, Embase, and Cochrane libraries. All literature we have identified from three libraries is presented in the supporting information. The keywords used for retrieval included: (1) PIWI-interacting RNA or piRNA; and (2) neoplasm, cancer, carcinoma, malignancy, or tumor; and (3) sensitivity, specificity, or biomarker. The retrieved literature was published from 2006 to 2023 (Apr).

Eligibility criteria

We included both cohort (prospective and retrospective) studies as well as case-control studies. Specifically, we focused on studies that investigated the diagnostic value of piRNAs to extract and calculate key indicators directly or indirectly, including sensitivity, specificity, true positive (TP), false positive (FP), false negative (FN), and true negative (TN). The diagnosis of cancer was based on general guidelines for each cancer, such as histopathology or other appropriate diagnostic criteria. However, we excluded studies that provided incomplete diagnostic information or analyzed previously published papers, such as meta-analyses, systematic reviews, case reviews, case reports and letters. Articles published in languages other than English were excluded from the analysis. Additionally, the lists of authors, centers of study, and recruitment intervals of the included studies were compared to identify duplicate reports of the same research or studies with a substantial overlap in their study populations. In such cases, less informative studies were excluded from the analysis.

Study selection

To eliminate personal bias, two reviewers independently conducted the search process. Any disagreements were resolved through discussions with a third author. At the first stage we screened the titles and/or abstracts of the search results and selected possibly relevant studies for the second stage of the study selection process. In the second stage, after excluding conference abstracts, we retrieved and evaluated the full texts in detail. Subsequently, the studies that met the eligibility criteria were included in the analysis.

Data extraction and quality assessment

Two authors independently screened each retrieved record and performed data extraction. Any differences were resolved through discussions with a third author until a consensus was reached. The following information was extracted from the literature: author; year of publication; patient country; comprehensive sensitivity and specificity of the biomarkers; TP, FP, FN, and TN; type; and number of cases. Finally, the area under the curve (AUC), sensitivity, specificity, and diagnostic odds ratios were evaluated. All included literature was summarized in Table 1. AMSTAR checklist(S2 Table, [28]) was used to assess the quality of this systemic review. In addition, QUADAS-2 checklist (S3 Table, [29]) was used to assess the quality of included studies.

thumbnail
Download:
Table 1. Main characteristics of the articles included in this study.

https://doi.org/10.1371/journal.pone.0294685.t001

Results

We searched three databases (PubMed, Embase, and Cochrane) for relevant literature and identified 641 papers. After removing duplicates (n = 122), we screened titles and abstracts and removed conference abstracts, reviews, meta-analyses, and non-human studies (n = 277). Full texts and abstracts were examined, and manuscripts unrelated to the subject and with incomplete data or fewer than 20 samples were removed (n = 233). Finally, 18 studies with 2,352 patients were included in this systematic review (Fig 1, Table 1, S4 Table). The most frequently studied type of cancer was colorectal cancer (n = 7, number of patients = 1,488).

thumbnail
Download:
Fig 1. Flow chart of the research process.

https://doi.org/10.1371/journal.pone.0294685.g001

Comparison of diagnostic performance of piRNAs in colorectal cancer

The AUC values of 9 piRNAs were compared in patients with colorectal cancer (n = 1,488, Fig 2A). Their AUC values ranged from 0.707 to 0.942; however, the current clinical diagnostic biomarkers (carcinoembryonic antigen (CEA) and cancer antigen 19–9 (CA 19–9)) for colorectal cancer ranged from 0.672 to 0.707 and 0.574 to 0.617, respectively. piR-31143 had the highest value (0.942), whereas piR-28876 had the lowest value (0.707). Most piRNAs in these studies showed better AUC values than current biomarkers.

thumbnail
Download:
Fig 2. Comparison of the diagnostic performance of piRNAs in colorectal cancer.

Representative values of diagnostic performance including AUC value (A), sensitivity (B), specificity (C) and odds ratio (D) for colorectal cancer were compared.

https://doi.org/10.1371/journal.pone.0294685.g002

The sensitivities of the 9 piRNAs in colorectal cancer patients had values from 54.60 to 93.10%; however, current clinical diagnostic biomarkers (CEA and CA19-9) for colorectal cancer had respective values from 41.11 to 41.80 and from 19.10 to 27.78 (Fig 2B). piR-24000 showed the highest sensitivity (93.10) and piR-017724 showed the lowest sensitivity (54.6). Most piRNAs in these studies showed better sensitivity than the current biomarkers.

Specificities of the 9 piRNA in colorectal cancer were from 65.10 to 100, while current clinical diagnostic biomarkers (CEA and CA19-9) for this cancer range from 93.33 to 94.6 and from 95.56 to 96.4, respectively (Fig 2C). piR-31143 showed the highest specificity (100) and piR-54265 showed the lowest sensitivity (65.10). Overall, most piRNAs in these studies showed poorer specificity than the current biomarkers.

Odds ratios of 8 piRNAs in patients with colorectal cancer were from 3.59 to 41.88, and current clinical diagnostic biomarkers (CEA and CA19-9) are characterized by values from 9.77 to 12.46 and from 6.25 to 8.27, respectively (Fig 2D). piR-823 showed the highest odds ratio (41.88) and piR-28876 showed the lowest odds ratio (3.59).

Generally, the piRNAs in this review showed better sensitivity and AUC values than the current clinical diagnostic biomarkers for CRC, although the current biomarkers showed better specificity.

Comparison of diagnostic performance of piRNAs in other cancers

The AUC values of 20 piRNAs were compared in a variety of cancer patients (n = 864, Fig 3A), except for those with colorectal cancer. The AUC ranged from 0.624 to 0.978. piR-9491 had the highest value (0.978), whereas piR-164568 had the lowest value (0.624).

thumbnail
Download:
Fig 3. Comparison of the diagnostic performance of piRNAs in a variety of cancer types, excluding colorectal cancer.

Representative values of diagnostic performance including AUC value (A), sensitivity (B), specificity (C) and odds ratio (D) for colorectal cancer were compared.

https://doi.org/10.1371/journal.pone.0294685.g003

The sensitivities of 14 piRNAs were compared in a variety of cancer patients (n = 583, Fig 3B), except for those with colorectal cancer. The sensitivities were between 42.86 to 100. piR-9491 showed the highest sensitivity (100), whereas piR-004918 showed the lowest sensitivity (42.86).

The specificities of 14 piRNAs were compared in a variety of cancer patients (n = 583, Fig 3C), except for those with colorectal cancer. Their specificities ranged from 60.10 to 96.67. piR-018569 showed the highest specificity (96.67), whereas piR-164568 showed the lowest specificity (60.10).

Odds ratios (ORs) of 13 piRNAs were compared in a variety of cancer patients (n = 583, Fig 3D), except for those with colorectal cancer. Their odds ratios were between 1.61 and 44.67. piR-12488 showed the highest odds ratio (44.67), and piR-164568 showed the lowest value (1.61).

Discussion

In this review, we examined the diagnostic value of piRNAs in a variety of cancers. Interestingly, their usefulness as serum biomarkers has been examined most frequently in patients with CRC. We found that piRNAs performed better than current serum biomarkers, including CEA, CA19-9 and guanylyl cyclase C (GCC). Moreover, piR-823 showed a good diagnostic performance in several cancer types.

piR-823 showed better performance among reviewed piRNAs in colorectal cancer (Fig 2). The average odds ratio of reviewed biomarkers in colorectal cancer was 15.16. The best piRNA in odds ratio was piR-823(41.88, 95% confidence interval (CI): 16.51~106.24), followed by piR-24000 (30, 95% CI: 11.66~77.22) and piR-020619 (29.8, 95% CI:16.81~52.84). The average AUC value was 0.78. The best piRNA was piR-31143 (0.94, 95% CI: 0.75~1.00), followed by piR-823 (0.93, 95% CI: 0.89~0.97) and piR-020619 (0.91, 95% CI: 0.88~0.94). The average sensitivity value was 63.31. The best piRNA was piR-24000 (93.10, 95% CI: 85.76~96.80), followed by piR-54265 (85.70, 95% CI: 82.92~88.02) and piR-823 (83.30, 95% CI: 73.95~89.80). The average specificity value was 83.68. The best piRNA was piR-31143 (100), followed by piR-823 (89.3, 95% CI 80.34~94.50) and piR-020619 (86.11, 95% CI: 80.30~90.41). In other types of cancer including gastric cancer, piR-823 showed better diagnostic performance (Fig 3).

Several serum biomarkers are available for the detection and monitoring of colorectal cancer. CEA is a glycoprotein associated with cellular adhesion [30]. Although it is normally expressed during fetal development, it is overexpressed in many cancers, including colorectal cancer. Elevated levels of CEA in serum have been found to be associated with advanced colorectal cancer and poor prognosis [31]. However, due to its poor sensitivity and prevalence in non-malignant conditions, the use of this marker is not recommended in colorectal cancer. CA 19–9 is a carbohydrate antigen normally synthesized in the gastrointestinal tract [30]. However, its expression is elevated in several gastrointestinal cancers including colorectal cancer. Nonetheless, its use as a biomarker for colorectal cancer is limited because of its low sensitivity and specificity. GCC is a transmembrane receptor expressed in normal colorectal tissues and overexpressed in colorectal cancer [32]. Serum GCC levels are elevated in patients with colorectal cancer and may be useful as a biomarker for early detection. miRNAs are small non-coding RNA molecules involved in the regulation of gene expression [33]. Several studies have identified specific miRNAs that are dysregulated in colorectal cancer and may serve as potential serum biomarkers. As current serum biomarkers show better specificity and poorer sensitivity (Fig 2), their combination with piRNAs could improve the overall diagnostic performance.

piR-823 which consists of 28 nucleotides was first reported in gastric cancer by Cui et al. [21]. Its expression was noted in white blood cells [21], cancer cell lines and blood plasma [26, 34]. Its association with malignancy has been reported in many cancer types including breast [35], colorectal, gastric [21], prostate cancer [36], esophageal cancer [37], liver cancer [38] and multiple myeloma [39]. Although the expressional regulation of its target genes such as DNMT1, DNMT3A and DNMT3B has been reported in breast cancer cells [35], one of its notable underlying mechanisms for the progression of malignancy is its binding with its target proteins and regulation of their activity. In colorectal cancer cells, several interaction partners had been studied. It interacts with HSF1 and regulates the phosphorylation at Ser326 and then the transcriptional activity in colorectal cancer cells [40]. Its interaction with HSF1 finally led to the increased expression of HSP27, HSP60 and HSP70. Another interaction partner is PINK1 and its interaction with PINK1 promoted the proteasome-mediated degradation of PINK1, which leads to the inhibition of mitophagy and apoptosis of colorectal cancer cells [41]. In multiple myeloma, it interacts with DNMT3B and leads to the aberrant DNA methylation [39]. In liver fibrogenesis, it interacts with EIF3B and increased the translation of TGF-β1 mRNA [42].

In addition to its oncogenic roles, some studies have suggested that piR-823 may act as a tumor suppressor. The expression level of piR-823 was decreased in the tumor tissue of renal cell carcinoma but positively correlated with worse outcomes [25]. In addition, its expression level is significantly lower in gastric cancer tissues than in non-cancerous tissues [43]. Moreover, piR-823 blood levels are lower in patients with gastric cancer than in controls, even though its presence is positively associated with tumor-node-metastasis and distant metastasis [21].

The role of piR-823 as a prognostic factor has been reported in multiple myeloma, where it re-educates endothelial cells in the tumor microenvironment [44]. PIWI proteins have been associated with a poor prognosis in glioblastoma [45], colorectal cancer [46] and liver cancer [47].

The study design of all 18 articles included in this review were a case-control study (S4 Table). To establish those piRNA as a clinical biomarker, further prospective studies are required [48]. Samples need to be collected before cancer development or diagnosis and patients who develop cancer during subsequent follow-up need to be compared with control patients matched for confounding variables.

Conclusion & limitation

This study showed that the piRNAs can be novel clinical biomarkers for the cancer diagnosis because they showed better sensitivity and AUC values than current clinical diagnostic biomarkers, although current biomarkers appear to be more specific. In addition, piR-823 showed a significant diagnostic performance in four types of cancer (colorectal, esophageal, gastric, and renal cell cancer). Further prospective studies are required for their validation because all 18 studies in this review were a case-control study. Cautious interpretation is required because there is heterogeneity in aspects of cancer type, population, materials and experimental methods (Table 1 and S4 Table) in this review. In addition, pre-prints or grey literature were not included in this review.

References

  1. 1. Wang X, Ramat A, Simonelig M, Liu MF. Emerging roles and functional mechanisms of PIWI-interacting RNAs. Nat Rev Mol Cell Biol. 2023;24(2):123–41. Epub 20220914. pmid:36104626.
  2. 2. Mokarram P, Niknam M, Sadeghdoust M, Aligolighasemabadi F, Siri M, Dastghaib S, et al. PIWI interacting RNAs perspectives: a new avenues in future cancer investigations. Bioengineered. 2021;12(2):10401–19. pmid:34723746.
  3. 3. Ozata DM, Gainetdinov I, Zoch A, O’Carroll D, Zamore PD. PIWI-interacting RNAs: small RNAs with big functions. Nat Rev Genet. 2019;20(2):89–108. pmid:30446728.
  4. 4. Zhang P, Kang JY, Gou LT, Wang J, Xue Y, Skogerboe G, et al. MIWI and piRNA-mediated cleavage of messenger RNAs in mouse testes. Cell Res. 2015;25(2):193–207. Epub 20150113. pmid:25582079.
  5. 5. Gou LT, Dai P, Yang JH, Xue Y, Hu YP, Zhou Y, et al. Pachytene piRNAs instruct massive mRNA elimination during late spermiogenesis. Cell Res. 2014;24(6):680–700. Epub 20140502. pmid:24787618.
  6. 6. Molaro A, Falciatori I, Hodges E, Aravin AA, Marran K, Rafii S, et al. Two waves of de novo methylation during mouse germ cell development. Genes Dev. 2014;28(14):1544–9. pmid:25030694.
  7. 7. Sugimoto K, Kage H, Aki N, Sano A, Kitagawa H, Nagase T, et al. The induction of H3K9 methylation by PIWIL4 at the p16Ink4a locus. Biochem Biophys Res Commun. 2007;359(3):497–502. Epub 20070529. pmid:17544373.
  8. 8. Lu Y, Zhang K, Li C, Yao Y, Tao D, Liu Y, et al. Piwil2 suppresses p53 by inducing phosphorylation of signal transducer and activator of transcription 3 in tumor cells. PLoS One. 2012;7(1):e30999. Epub 20120127. pmid:22303479.
  9. 9. Ashe A, Sapetschnig A, Weick EM, Mitchell J, Bagijn MP, Cording AC, et al. piRNAs can trigger a multigenerational epigenetic memory in the germline of C. elegans. Cell. 2012;150(1):88–99. Epub 20120625. pmid:22738725.
  10. 10. Szakmary A, Cox DN, Wang Z, Lin H. Regulatory relationship among piwi, pumilio, and bag-of-marbles in Drosophila germline stem cell self-renewal and differentiation. Curr Biol. 2005;15(2):171–8. pmid:15668175.
  11. 11. Zhang X, He X, Liu C, Liu J, Hu Q, Pan T, et al. IL-4 Inhibits the Biogenesis of an Epigenetically Suppressive PIWI-Interacting RNA To Upregulate CD1a Molecules on Monocytes/Dendritic Cells. J Immunol. 2016;196(4):1591–603. Epub 20160111. pmid:26755820.
  12. 12. Shirayama M, Seth M, Lee HC, Gu W, Ishidate T, Conte D Jr., et al. piRNAs initiate an epigenetic memory of nonself RNA in the C. elegans germline. Cell. 2012;150(1):65–77. Epub 20120625. pmid:22738726.
  13. 13. Lee EJ, Banerjee S, Zhou H, Jammalamadaka A, Arcila M, Manjunath BS, et al. Identification of piRNAs in the central nervous system. RNA. 2011;17(6):1090–9. Epub 20110422. pmid:21515829.
  14. 14. Rajasethupathy P, Antonov I, Sheridan R, Frey S, Sander C, Tuschl T, et al. A role for neuronal piRNAs in the epigenetic control of memory-related synaptic plasticity. Cell. 2012;149(3):693–707. pmid:22541438.
  15. 15. Roque CG, Hengst U. Wimpy Nerves: piRNA Pathway Curbs Axon Regrowth after Injury. Neuron. 2018;97(3):477–8. pmid:29420927.
  16. 16. Wu X, Pan Y, Fang Y, Zhang J, Xie M, Yang F, et al. The Biogenesis and Functions of piRNAs in Human Diseases. Mol Ther Nucleic Acids. 2020;21:108–20. Epub 20200523. pmid:32516734.
  17. 17. Qiu W, Guo X, Lin X, Yang Q, Zhang W, Zhang Y, et al. Transcriptome-wide piRNA profiling in human brains of Alzheimer’s disease. Neurobiol Aging. 2017;57:170–7. Epub 20170603. pmid:28654860.
  18. 18. Sun W, Samimi H, Gamez M, Zare H, Frost B. Pathogenic tau-induced piRNA depletion promotes neuronal death through transposable element dysregulation in neurodegenerative tauopathies. Nat Neurosci. 2018;21(8):1038–48. Epub pmid:30038280.
  19. 19. Ji L, Chen X. Regulation of small RNA stability: methylation and beyond. Cell Res. 2012;22(4):624–36. Epub 20120313. pmid:22410795.
  20. 20. Kurth HM, Mochizuki K. 2’-O-methylation stabilizes Piwi-associated small RNAs and ensures DNA elimination in Tetrahymena. RNA. 2009;15(4):675–85. Epub 20090224. pmid:19240163.
  21. 21. Cui L, Lou Y, Zhang X, Zhou H, Deng H, Song H, et al. Detection of circulating tumor cells in peripheral blood from patients with gastric cancer using piRNAs as markers. Clin Biochem. 2011;44(13):1050–7. Epub 20110617. pmid:21704610.
  22. 22. Gu X, Wang C, Deng H, Qing C, Liu R, Liu S, et al. Exosomal piRNA profiling revealed unique circulating piRNA signatures of cholangiocarcinoma and gallbladder carcinoma. Acta Biochim Biophys Sin (Shanghai). 2020;52(5):475–84. pmid:32369104.
  23. 23. Vychytilova-Faltejskova P, Stitkovcova K, Radova L, Sachlova M, Kosarova Z, Slaba K, et al. Circulating PIWI-Interacting RNAs piR-5937 and piR-28876 Are Promising Diagnostic Biomarkers of Colon Cancer. Cancer Epidemiol Biomarkers Prev. 2018;27(9):1019–28. Epub 20180705. pmid:29976566.
  24. 24. Wang Z, Yang H, Ma D, Mu Y, Tan X, Hao Q, et al. Serum PIWI-Interacting RNAs piR-020619 and piR-020450 Are Promising Novel Biomarkers for Early Detection of Colorectal Cancer. Cancer Epidemiol Biomarkers Prev. 2020;29(5):990–8. Epub 20200217. pmid:32066615.
  25. 25. Iliev R, Fedorko M, Machackova T, Mlcochova H, Svoboda M, Pacik D, et al. Expression Levels of PIWI-interacting RNA, piR-823, Are Deregulated in Tumor Tissue, Blood Serum and Urine of Patients with Renal Cell Carcinoma. Anticancer Res. 2016;36(12):6419–23. pmid:27919963.
  26. 26. Yang X, Cheng Y, Lu Q, Wei J, Yang H, Gu M. Detection of stably expressed piRNAs in human blood. Int J Clin Exp Med. 2015;8(8):13353–8. Epub 20150815. pmid:26550265.
  27. 27. Liberati A, Altman DG, Tetzlaff J, Mulrow C, Gotzsche PC, Ioannidis JP, et al. The PRISMA statement for reporting systematic reviews and meta-analyses of studies that evaluate health care interventions: explanation and elaboration. J Clin Epidemiol. 2009;62(10):e1–34. Epub 20090723. pmid:19631507.
  28. 28. Shea BJ, Grimshaw JM, Wells GA, Boers M, Andersson N, Hamel C, et al. Development of AMSTAR: a measurement tool to assess the methodological quality of systematic reviews. BMC Med Res Methodol. 2007;7:10. Epub 20070215. pmid:17302989.
  29. 29. Whiting PF, Rutjes AW, Westwood ME, Mallett S, Deeks JJ, Reitsma JB, et al. QUADAS-2: a revised tool for the quality assessment of diagnostic accuracy studies. Ann Intern Med. 2011;155(8):529–36. pmid:22007046.
  30. 30. Desai S, Guddati AK. Carcinoembryonic Antigen, Carbohydrate Antigen 19–9, Cancer Antigen 125, Prostate-Specific Antigen and Other Cancer Markers: A Primer on Commonly Used Cancer Markers. World J Oncol. 2023;14(1):4–14. Epub 20230226. pmid:36895994.
  31. 31. Becerra AZ, Probst CP, Tejani MA, Aquina CT, Gonzalez MG, Hensley BJ, et al. Evaluating the Prognostic Role of Elevated Preoperative Carcinoembryonic Antigen Levels in Colon Cancer Patients: Results from the National Cancer Database. Ann Surg Oncol. 2016;23(5):1554–61. Epub 20160112. pmid:26759308.
  32. 32. Caspi A, Entezari AA, Crutcher M, Snook AE, Waldman SA. Guanylyl cyclase C as a diagnostic and therapeutic target in colorectal cancer. Per Med. 2022;19(5):457–72. Epub 20220803. pmid:35920071.
  33. 33. Suarez B, Sole C, Marquez M, Nanetti F, Lawrie CH. Circulating MicroRNAs as Cancer Biomarkers in Liquid Biopsies. Adv Exp Med Biol. 2022;1385:23–73. pmid:36352210.
  34. 34. Freedman JE, Gerstein M, Mick E, Rozowsky J, Levy D, Kitchen R, et al. Diverse human extracellular RNAs are widely detected in human plasma. Nat Commun. 2016;7:11106. Epub 20160426. pmid:27112789.
  35. 35. Ding X, Li Y, Lu J, Zhao Q, Guo Y, Lu Z, et al. piRNA-823 Is Involved in Cancer Stem Cell Regulation Through Altering DNA Methylation in Association With Luminal Breast Cancer. Front Cell Dev Biol. 2021;9:641052. Epub 20210315. pmid:33791297.
  36. 36. Oner C, Turgut Cosan D, Colak E. Estrogen and Androgen Hormone Levels Modulate the Expression of PIWI Interacting RNA in Prostate and Breast Cancer. PLoS One. 2016;11(7):e0159044. Epub 20160714. pmid:27414029.
  37. 37. Su JF, Zhao F, Gao ZW, Hou YJ, Li YY, Duan LJ, et al. piR-823 demonstrates tumor oncogenic activity in esophageal squamous cell carcinoma through DNA methylation induction via DNA methyltransferase 3B. Pathol Res Pract. 2020;216(4):152848. Epub 20200205. pmid:32051106.
  38. 38. Rizzo F, Rinaldi A, Marchese G, Coviello E, Sellitto A, Cordella A, et al. Specific patterns of PIWI-interacting small noncoding RNA expression in dysplastic liver nodules and hepatocellular carcinoma. Oncotarget. 2016;7(34):54650–61. pmid:27429044.
  39. 39. Ai L, Mu S, Sun C, Fan F, Yan H, Qin Y, et al. Myeloid-derived suppressor cells endow stem-like qualities to multiple myeloma cells by inducing piRNA-823 expression and DNMT3B activation. Mol Cancer. 2019;18(1):88. Epub 20190413. pmid:30979371.
  40. 40. Yin J, Jiang XY, Qi W, Ji CG, Xie XL, Zhang DX, et al. piR-823 contributes to colorectal tumorigenesis by enhancing the transcriptional activity of HSF1. Cancer Sci. 2017;108(9):1746–56. Epub 20170703. pmid:28618124.
  41. 41. Wang S, Jiang X, Xie X, Yin J, Zhang J, Liu T, et al. piR-823 inhibits cell apoptosis via modulating mitophagy by binding to PINK1 in colorectal cancer. Cell Death Dis. 2022;13(5):465. Epub 20220517. pmid:35581181.
  42. 42. Tang X, Xie X, Wang X, Wang Y, Jiang X, Jiang H. The Combination of piR-823 and Eukaryotic Initiation Factor 3 B (EIF3B) Activates Hepatic Stellate Cells via Upregulating TGF-beta1 in Liver Fibrogenesis. Med Sci Monit. 2018;24:9151–65. Epub 20181217. pmid:30556540.
  43. 43. Cheng J, Deng H, Xiao B, Zhou H, Zhou F, Shen Z, et al. piR-823, a novel non-coding small RNA, demonstrates in vitro and in vivo tumor suppressive activity in human gastric cancer cells. Cancer Lett. 2012;315(1):12–7. Epub 20111010. pmid:22047710.
  44. 44. Li B, Hong J, Hong M, Wang Y, Yu T, Zang S, et al. piRNA-823 delivered by multiple myeloma-derived extracellular vesicles promoted tumorigenesis through re-educating endothelial cells in the tumor environment. Oncogene. 2019;38(26):5227–38. Epub 20190319. pmid:30890754.
  45. 45. Tamtaji OR, Behnam M, Pourattar MA, Hamblin MR, Mahjoubin-Tehran M, Mirzaei H, et al. PIWI-interacting RNAs and PIWI proteins in glioma: molecular pathogenesis and role as biomarkers. Cell Commun Signal. 2020;18(1):168. Epub 20201027. pmid:33109195.
  46. 46. Sun R, Gao CL, Li DH, Li BJ, Ding YH. Expression Status of PIWIL1 as a Prognostic Marker of Colorectal Cancer. Dis Markers. 2017;2017:1204937. Epub 20170529. pmid:28634417.
  47. 47. Zeng G, Zhang D, Liu X, Kang Q, Fu Y, Tang B, et al. Co-expression of Piwil2/Piwil4 in nucleus indicates poor prognosis of hepatocellular carcinoma. Oncotarget. 2017;8(3):4607–17. pmid:27894076.
  48. 48. Lee YT, Fujiwara N, Yang JD, Hoshida Y. Risk stratification and early detection biomarkers for precision HCC screening. Hepatology. 2023;78(1):319–62. Epub 20221011. pmid:36082510.
  49. 49. Iyer DN, Wan TM, Man JH, Sin RW, Li X, Lo OS, et al. Small RNA Profiling of piRNAs in Colorectal Cancer Identifies Consistent Overexpression of piR-24000 That Correlates Clinically with an Aggressive Disease Phenotype. Cancers (Basel). 2020;12(1). Epub 20200112. pmid:31940941.
  50. 50. Sabbah NA, Abdalla WM, Mawla WA, AbdAlMonem N, Gharib AF, Abdul-Saboor A, et al. piRNA-823 Is a Unique Potential Diagnostic Non-Invasive Biomarker in Colorectal Cancer Patients. Genes (Basel). 2021;12(4). Epub 20210419. pmid:33921704.
  51. 51. Mai D, Zheng Y, Guo H, Ding P, Bai R, Li M, et al. Serum piRNA-54265 is a New Biomarker for early detection and clinical surveillance of Human Colorectal Cancer. Theranostics. 2020;10(19):8468–78. Epub 20200709. pmid:32754257.
  52. 52. Qu A, Wang W, Yang Y, Zhang X, Dong Y, Zheng G, et al. A serum piRNA signature as promising non-invasive diagnostic and prognostic biomarkers for colorectal cancer. Cancer Management and Research. 2019;11:3703–20. pmid:31118791
  53. 53. Li J, Tong Y, Sun Z, Chen Y, Wang Y, Zhou L, et al. A duplex-specific nuclease assisted photoelectrochemical biosensor based on MoS(2)@ReS(2)/Ti(3)C(2) hybrid for ultrasensitive detection of colorectal cancer-related piRNA-31,143. Acta Biomater. 2022;149:287–96. Epub 20220625. pmid:35764241.
  54. 54. Ge L, Zhang N, Li D, Wu Y, Wang H, Wang J. Circulating exosomal small RNAs are promising non-invasive diagnostic biomarkers for gastric cancer. J Cell Mol Med. 2020;24(24):14502–13. Epub 20201109. pmid:33169519.
  55. 55. Zhou X, Liu J, Meng A, Zhang L, Wang M, Fan H, et al. Gastric juice piR-1245: A promising prognostic biomarker for gastric cancer. J Clin Lab Anal. 2020;34(4):e23131. Epub 20191128. pmid:31777102.
  56. 56. Bartos M, Siegl F, Kopkova A, Radova L, Oppelt J, Vecera M, et al. Small RNA Sequencing Identifies PIWI-Interacting RNAs Deregulated in Glioblastoma-piR-9491 and piR-12488 Reduce Tumor Cell Colonies In Vitro. Front Oncol. 2021;11:707017. Epub 20210813. pmid:34485142.
  57. 57. Wang H, Shi B, Zhang X, Shen P, He Q, Yin M, et al. Exosomal hsa-piR1089 promotes proliferation and migration in neuroblastoma via targeting KEAP1. Pathol Res Pract. 2023;241:154240. Epub 20221123. pmid:36436316.
  58. 58. Li J, Wang N, Zhang F, Jin S, Dong Y, Dong X, et al. PIWI-interacting RNAs are aberrantly expressed and may serve as novel biomarkers for diagnosis of lung adenocarcinoma. Thoracic Cancer. 2021;12(18):2468–77. pmid:34346164
  59. 59. Li Y, Dong Y, Zhao S, Gao J, Hao X, Wang Z, et al. Serum-derived piR-hsa-164586 of extracellular vesicles as a novel biomarker for early diagnosis of non-small cell lung cancer. Frontiers in Oncology. 2022;12. pmid:36249068
  60. 60. Markert L, Holdmann J, Klinger C, Kaufmann M, Schork K, Turewicz M, et al. Small RNAs as biomarkers to differentiate benign and malign prostate diseases: An alternative for transrectal punch biopsy of the prostate? PLoS One. 2021;16(3):e0247930. Epub 20210324. pmid:33760831.
  61. 61. Chang Z, Ji G, Huang R, Chen H, Gao Y, Wang W, et al. PIWI-interacting RNAs piR-13643 and piR-21238 are promising diagnostic biomarkers of papillary thyroid carcinoma. Aging (Albany NY). 2020;12(10):9292–310. Epub 20200519. pmid:32428871.