Beyond miRNAs: exploratory profiling of PIWI-interacting RNAs and small nucleolar RNAs in non-small cell lung cancer-related malignant pleural effusions

Introduction

Pleural effusion (PE) arises from a wide range of diseases, including heart failure, malignancy, pneumonia and tuberculosis (1). Distinguishing benign pleural effusion (BPE) from malignant pleural effusion (MPE) remains a common clinical challenge. Although pleural fluid (PF) cytology and pleural biopsy are considered diagnostic standards, cytology has limited sensitivity (approximately 55%), and biopsy is invasive and not always feasible (2).

Liquid biopsy approaches have created new opportunities for the minimally invasive analysis of cell-free and small extracellular vesicle (sEV)-associated nucleic acids in PF (3). Among these, small RNAs represent a diverse group of non-coding molecules with regulatory functions in cancer biology (4). The most extensively studied small RNAs include microRNAs (miRNAs), PIWI-interacting RNAs (piRNAs), small nucleolar RNAs (snoRNAs), and transfer RNAs (tRNAs) (4). While miRNAs regulate gene expression post-transcriptionally (5), piRNAs and snoRNAs, originally described in the context of transposon silencing and ribosomal RNA modification, are increasingly recognized for their broader regulatory roles (5,6). Beyond their canonical role in protein synthesis, tRNAs have been implicated in cancer-associated regulatory mechanisms (7).

Dysregulated expression of miRNAs, piRNAs, snoRNAs and tRNAs has been reported in cancer tissues, cell lines and circulating biofluids (5,6,8,9). However, only a limited number of miRNAs have been described in PF (10-12). The presence of other small RNA species—particularly piRNAs, snoRNAs and tRNAs—has not been systematically investigated. Their detection and characterization in PF could provide new insights into the molecular landscape of pleural effusions and identify additional candidates to discriminate between benign and malignant conditions. To date, this area remains largely unexplored.

In this exploratory pilot study, we aimed to determine whether piRNAs, snoRNAs, and tRNAs are detectable in PF and whether differential expression analysis between BPE and MPE yields potentially biologically relevant information. We further sought to characterize the predicted targets and associated signaling pathways of candidate small RNAs using comprehensive bioinformatic analyses. In doing so, we assessed the feasibility of this approach for generating preliminary hypotheses regarding the involvement of these small RNA classes in MPE and their potential as biomarkers for future validation.

Methods

PF samples

PF samples were obtained from a local biobank established at the Pleural Medicine Unit of Arnau de Vilanova University Hospital (Lleida, Spain). The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. The study was approved by the Ethics Committee of Clinical Research of the Arnau de Vilanova University Hospital (CEIC-1947). Written informed consent was obtained from all participants.

For this exploratory pilot study, we selected eight PF samples: four from patients with BPE due to heart failure and four from patients with MPE, including two with NSCLC and two with colorectal cancer (CRC), all metastasized. After centrifugation to remove cellular components, PF supernatants were heat-treated at 60 ℃ for 30 minutes.

Small RNA sequencing

All laboratory procedures were performed at QIAGEN (Germany). sEVs, operationally defined according to Welsh et al. (13), were isolated from 8 mL of PF using the exoRNeasy Maxi Kit (QIAGEN), followed by total RNA extraction according to the manufacturer’s instructions. Synthetic miRNA spike-ins were added to monitor extraction efficiency and sequencing performance.

Small RNA libraries were prepared using the QIAseq miRNA Library Kit (QIAGEN), assessed by capillary electrophoresis (TapeStation D1000), pooled equimolarly, quantified by quantitative polymerase chain reaction (qPCR), and sequenced on an Illumina NextSeq platform (1×75 bp, 2×10 cycles). Raw data were demultiplexed, and FASTQ files were generated using bcl2fastq2 (Illumina, San Diego, USA). Primary analyses were performed using the CLC Genomics Server version 21.0.4.

Reads were aligned to miRBase v22 for miRNAs (14), piRNAdb v1.7.6 for piRNAs, snoDB v2.0 for snoRNAs (15), and an hg38-based reference for tRNAs (16).

Statistical analysis

All analyses were conducted using R (17). Prior to differential expression analysis, two preprocessing steps were applied: (I) filtering to remove low-abundance RNAs, retaining only features whose geometric mean counts per million (CPM) within a condition exceeded a threshold equivalent to 10 raw counts in the sample with the smallest library size; (II) normalization of log-transformed CPM values using Trimmed Mean of M values (TMM) scaling factors computed with the edgeR calcNormFactors function.

Differential expression analyses were performed using the Limma-Voom pipeline for the following comparisons: BPE vs. all MPE, BPE vs. CRC-derived MPE, and BPE vs. NSCLC-derived MPE. P values were adjusted using the Benjamini-Hochberg method, with false discovery rate (FDR) correction applied separately for each RNA class (miRNA, piRNA, snoRNA and tRNA).

Functional enrichment analyses were conducted using gprofiler2 across multiple annotation resources, including Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), Reactome (REAC), transcription factor targets (TF), WikiPathways (WP), and Human Phenotype Ontology (HP). For miRNAs, experimentally supported interactions appearing at least six times in multiMiR were included; piRNA targets were retrieved from piRNAdb, and snoRNA targets were obtained from snoDB, including both predicted and experimentally validated interactions.

Results

Characteristics of the study population

PF samples from eight patients were analyzed. Clinical and diagnostic characteristics of the study population are summarized in Table 1. MPE were confirmed by the presence of malignant cells in PF, whereas BPE were classified according to established clinical criteria (18).

Relative abundance of miRNAs, piRNA, snoRNA and tRNAs

Small RNA sequencing detected multiple RNA species in all PF samples. In most specimens, miRNAs were the most abundant class, followed by tRNAs, piRNAs, and snoRNAs (Table 2). The overall proportions of these RNA classes did not differ significantly between benign and malignant samples.

Differential expression of small RNAs

Three comparisons were conducted to identify differentially expressed small RNAs: (I) BPE vs. all MPE, (II) BPE vs. CRC-derived MPE, and (III) BPE vs. NSCLC-derived MPE. Initial filtering based on fold change (FC < Q_0.05 or FC > Q_0.95) and nominal P value (P<0.05) yielded candidate lists for each RNA class (Figure 1 and Figure S1). As seen by the Venn diagrams in Figure S1C, there is almost no overlap between comparisons for piRNAs, snoRNA and tRNA candidates.

Figure 1 Differentially expressed small RNAs between BPE and NSCLC-derived MPE. (A) Volcano plot showing P value versus FC for all small RNAs; the horizontal line indicates the P=0.05 threshold, and the vertical lines indicate FC thresholds of 0.05 and 0.95. (B-E) Tables listing small RNAs that pass these thresholds, ordered by P value: (B) miRNAs; (C) piRNAs; (D) snoRNAs; (E) tRNAs. Entries in bold indicate an adjusted P value <0.05. The colors indicate the RNA type: miRNAs in green, piRNAs in blue, snoRNAs in red, and tRNAs in black. BPE, benign pleural effusion; FC, fold change; miRNAs, microRNAs; MPE, malignant pleural effusion; NSCLC, non-small cell lung cancer; piRNAs, PIWI-interacting RNAs; snoRNA, small nucleolar RNAs; tRNAs, transfer RNAs.

After FDR correction, statistically significant differences (adjusted P value <0.05) were observed only between BPE and NSCLC-derived MPE. In this contrast, nine small RNAs were significantly upregulated in NSCLC-related samples: five miRNAs (miR-200c-3p, miR-1269a, miR-1246, miR-4455, and miR-141-3p), three piRNAs (piR-33165, piR-32165, piR-33057), and one snoRNA (SNORA21). No tRNA species showed significantly differential expression after correction (Figure 2).

Figure 2 Differentially expressed small RNAs between BPE and NSCLC-derived MPE. (A-D) Volcano plots showing P value versus FC for each small RNA type; points in bold indicate an adjusted P value <0.05: (A) miRNAs; (B) piRNAs; (C) snoRNAs; (D) tRNAs. The tables below each plot list the corresponding differentially expressed small RNAs. The colors indicate the RNA type: miRNAs in green, piRNAs in blue, snoRNAs in red, and tRNAs in black. Adj. P value, adjusted P value; BPE, benign pleural effusion; FC, fold change; miRNAs, microRNAs; MPE, malignant pleural effusion; NSCLC, non-small cell lung cancer; piRNAs, PIWI-interacting RNAs; snoRNA, small nucleolar RNAs; tRNAs, transfer RNAs.

Subsequent target and functional enrichment analyses were focused on the BPE versus NSCLC-derived MPE comparison, as this was the only contrast yielding small RNAs with statistically significant differential expression after FDR correction.

Associations of selected small RNAs with NSCLC

Table 3 summarizes published evidence linking differentially expressed small RNAs or their predicted targets to NSCLC. Among the five differentially expressed miRNAs, four (miR-200c-3p, miR-1269a, miR-1246, and miR-141-3p) have been previously associated with NSCLC. Reported miRNA-target interactions in the NSCLC context include RRM2, TCF4, GLI3, and PTEN for miR-200c-3p, and FOXO1 for miR-1269a. Additional target relationships have been reported in other cancer types but involve genes with known relevance to NSCLC (19).

In contrast, none of the three differentially expressed piRNAs has been previously reported in NSCLC, and only one has a documented target. The differentially expressed snoRNA SNORA21 has been described in the serum sEVs of NSCLC patients, although no targets have been reported.

Because information on piRNAs and snoRNAs in cancer is limited, associations were reported for candidates identified in the preliminary stage of the analysis (Figure 1) were also summarized. Within this expanded set, several snoRNAs have been reported to be associated with NSCLC. Specifically, SNORD42B and SNORD83A were increased in NSCLC tissue and plasma from patients (20,21), SNORD15A was elevated in both normal and tumor tissue from non-smokers (22), and SNORD1C was overexpressed in tumor-initiating cells isolated from primary NSCLC tumors (23).

Regarding target relationships, while they are mainly reported in other cancer types, we identified one piRNA and several snoRNAs whose targets are implicated in NSCLC progression. piR-28700 targets MIR205HG, which promotes proliferation, migration and epithelial-to-mesenchymal transition (EMT) (24-26), and NFE2L2, which acts as an oncogenic driver via metabolic reprogramming (27). Predicted snoRNA targets include tumor suppressors GAS5 (28), NME2 (29) and MUC4 (30), oncogenes GLI2 (31), SNHG1 (32) and ANGPT2 (33), as well as context-dependent genes AKAP12, DDX3X, ZFR, and SLC26A6 (34-37).

Functional enrichment analysis

Enrichment analyses of predicted targets were performed using gprofiler2 (Figure 3). The targets of the differentially expressed miRNAs were enriched in functional categories related to transcriptional and chromatin regulation, cell growth and death, and cancer-associated signaling pathways.

Figure 3 Enrichment analysis of the targets of the small RNAs listed in Table 2; miRNA targets were pre-filtered to include only those with reported associations with NSCLC. Tables showing the correspondence between functionally enriched categories and small RNA targets: (A) miRNAs; (B) piRNAs; (C) snoRNAs. For miRNAs, only targets with reported interactions or established roles in NSCLC were considered, whereas for piRNAs and snoRNAs, all targets from the extended sets were included. The first two columns of each table denote the database and functional category, respectively, while the first two rows denote the small RNA and their targets. Cells are colored when the target is annotated with the corresponding functional category in the database. Each color represents a different database: Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), Reactome (REAC), Transcription Factor targets (TF), WikiPathways (WP), and Human Phenotype Ontology (HP). Hsa, Homo sapiens; IgA, immunoglobulin A; IgE, immunoglobulin E; miRNAs, microRNAs; NSCLC, non-small cell lung cancer; piRNAs, PIWI-interacting RNAs; snoRNA, small nucleolar RNAs.

For piRNAs and snoRNAs, enrichment analyses yielded fewer categories, reflecting the limited number of reported interactions. The enriched categories of piRNA targets included regulation of the ERBB signaling pathway. For snoRNA targets, the enriched categories included DNA helicase activity and single-stranded RNA binding, primarily driven by NME2 and ZFR, targets of SNORD15A and SNORD15B, respectively. Given the small sample size and reliance on predicted interactions, these findings should be interpreted as hypothesis-generating.

Discussion

In this exploratory pilot study, we characterized the small RNA landscape of PF sEVs and demonstrated that, in addition to well-studied miRNAs, other small RNA species, including piRNAs, snoRNAs, and tRNAs, are detectable in PF, specifically in its sEV compartment. Among the profiled small RNAs, a subset of miRNAs, piRNAs and snoRNAs was differentially expressed between BPE and NSCLC-associated MPE. Several of these molecules, or their predicted targets, have been previously linked to pathways relevant to lung cancer biology, suggesting that the small RNA repertoire of PF sEVs may provide novel candidates for biomarker exploration.

Several miRNAs identified as overexpressed in NSCLC-related MPE, particularly miR-200c-3p, miR-141-3p, and miR-1246, have been previously associated with NSCLC or reported as elevated in MPE (11,38,39). Therefore, their detection is consistent with earlier observations and supports the validity of our analytical methods. Although miR-1269a has not been previously described in PF, it has been reported to be upregulated in the serum sEVs of patients with NSCLC (40). miR-4455 has been implicated in tumor-related processes in other malignancies (41). Reported target relationships for these miRNAs include genes involved in treatment response, transcriptional regulation, and tumor suppression, both in NSCLC and other cancer contexts (42-47).

In contrast, little information is available regarding the roles of piRNAs and snoRNAs in NSCLC. Among the small RNAs identified in this study, only SNORA21 has previously been reported in NSCLC, albeit in serum rather than PF sEVs (48). Within the extended set of candidates selected based on fold change and nominal P value, several snoRNAs have been associated with NSCLC tissues or circulating samples (20,21,23), whereas no direct evidence exists for the majority of piRNAs. Nevertheless, the predicted targets of some piRNAs and snoRNAs identified in this study include genes known to influence NSCLC progression, metabolic reprogramming, and cell survival (24-37).

The detection of multiple classes of small RNAs in PF sEVs suggests that this biological fluid may reflect a complex regulatory environment influenced by tumor-derived signals, host responses, and sEV-mediated communication within the pleural space. The differential expression observed in NSCLC-related MPE raises the possibility that some of these RNAs mirror tumor-associated processes, including transcriptional regulation, chromatin dynamics, and survival pathways. The presence of piRNAs and snoRNAs, RNA species with emerging roles in cancer biology, further suggests that additional, previously unexplored regulatory layers may contribute to the pathophysiology of MPE.

Enrichment analyses of the predicted targets identified functional categories related to transcriptional and chromatin regulation, cell growth, and cancer-associated signaling pathways, particularly for miRNA targets. These findings are consistent with the established role of miRNAs, especially the miR-200 family, in EMT, metastasis, and tumor progression in NSCLC (49). For piRNAs and snoRNAs, pathway associations rely largely on predicted targets and should therefore be interpreted cautiously. Notably, enrichment in the regulation of ERBB signaling for piRNA targets and RNA-binding processes for snoRNA targets is biologically plausible in the context of NSCLC (50,51) but requires validation in larger cohorts and functional studies.

A major strength of this study is its novelty; to our knowledge, this is the first report to systematically profile piRNAs, snoRNAs, and tRNAs in PF. However, this study has important limitations, primarily the very small sample size, which restricts generalizability. Although statistically significant differences were identified after FDR correction, the results should be viewed as hypothesis-generating.

Overall, this pilot study broadens the repertoire of small RNAs detectable in PF and demonstrates the feasibility of profiling beyond miRNAs, particularly snoRNAs, as a source of biological insight and hypothesis generation in MPE. Future studies should focus on validation in larger, independent cohorts, targeted quantification using orthogonal techniques, functional characterization of selected piRNAs and snoRNAs, and integration with other liquid biopsy approaches.

Conclusions

This exploratory pilot study identified a broad spectrum of small RNAs in PF sEVs and demonstrated the differential expression of piRNAs and snoRNAs, in addition to miRNAs, in NSCLC-related MPE. Although preliminary, these findings support the feasibility of profiling diverse small RNA species in PF and highlight candidate small RNAs for future exploratory and validation studies. Larger studies are needed to validate these observations and define their diagnostic and biological relevance.

Acknowledgments

We would like to acknowledge the Bioinformatics and Computational Biology Service at the University of Lleida for their assistance.

Footnote

Data Sharing Statement: Available at https://tlcr.amegroups.com/article/view/10.21037/tlcr-2025-1-1448/dss

Peer Review File: Available at https://tlcr.amegroups.com/article/view/10.21037/tlcr-2025-1-1448/prf

Funding: This project has been funded by Instituto de Salud Carlos III (ISCIII) through the projects “PI21/00438” and “CP20/00039” and co-funded by the European Union.

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://tlcr.amegroups.com/article/view/10.21037/tlcr-2025-1-1448/coif). The authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. The study was approved by the Ethics Committee of Clinical Research of the Arnau de Vilanova University Hospital (CEIC-1947). Written informed consent was obtained from all participants.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

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