Expression profile of small nucleolar RNAs (snoRNAs) in penile cancer

Abstract

Background

The role of small nucleolar RNAs (snoRNAs) has been investigated in the carcinogenesis of several malignancies; however, their function in penile cancer (PeCa) has not been reported. In this context, the study aimed to identify the expression profile of snoRNAs in the clinicopathological features of PeCa.

Methods

This cross-sectional observational study examined the expression profile of snoRNAs in eight patients diagnosed with PeCa and four patients with phimosis (used as controls) using the GeneChip Array, correlating it with clinicopathological characteristics. Human papillomavirus (HPV) identification was performed using nested polymerase chain reaction (PCR). In silico analysis was conducted to characterize snoRNAs and assess their influence on the therapeutic approach for tumor types in other regions.

Results

Two hundred and seventy snoRNAs showed differential expression between the studied groups, with the majority being overexpressed. In the Venn diagram, SNORD78 and SNORD46 had their expression identified exclusively in samples with perineural invasion and lymph node metastasis, respectively. SNORD13F was the least expressed (fold change =−10.41), while SNORD43 was the most overexpressed (fold change =9.79). In silico analysis revealed that SNORA70 and SNORA38 were associated with a reduced therapeutic response to commonly used antineoplastic drugs in PeCa.

Conclusions

Despite the need to confirm the expression of these molecules in a larger number of samples and using another methodology, we suggest that these snoRNAs may serve as diagnostic, prognostic, and treatment biomarkers in PeCa.

Highlight box.

Key findings

• This study identified 270 small nucleolar RNAs (snoRNAs) that may be involved in penile carcinogenesis, with SNORD78 and SNORD46 potentially serving as biomarkers for lymph node metastasis and perineural invasion.

What is known and what is new?

• SnoRNAs have been studied in various types of cancer due to their potential as biomarkers in diagnosis and prognosis.

• To our knowledge, this is the first study to explore the expression profile of snoRNAs in penile cancer.

What is the implication, and what should change now?

• We propose that these snoRNAs could serve as biomarkers for diagnosis, prognosis, and treatment in penile cancer.

Introduction

Although some improvements have been made in understanding the pathogenesis and treatment of patients with penile cancer (PeCa) (1), there is still a lack of information on genetic and/or epigenetic factors associated with tumorigenesis in this type of tumor. Additionally, this tumor is highly prevalent in developing countries, such as Brazil (2). It is urgent to disseminate knowledge about PeCa and provide assistance for early diagnosis, as the majority of cases in the country result in total or partial organ amputation due to the presence of high-grade tumors with regional lymph node metastases at the time of diagnosis, thereby reducing life expectancy (3,4).

Despite 98% of human DNA consisting of non-coding regions, at least 80% of the human genome is biologically active, including regulatory RNAs such as small nucleolar RNAs (snoRNAs) (5,6). Recently, evidence has shown that snoRNAs are important regulatory molecules involved in various processes, including inflammation and cancer (7,8).

SnoRNAs are medium-sized non-coding RNAs, ranging in length from 60 to 300 nucleotides (nt) (9). They are located in the introns of coding and non-coding transcripts (sometimes in the introns of pseudogenes of protein partner complexes in snoRNP) (10). SnoRNAs are involved in the chemical modification of ribosomal RNA (rRNA), as they recognize and bind to complementary sequences in target rRNAs and signal to direct a chemical modification, indicating the exact base to be modified (8,10,11). They can be divided into two main categories based on their unique structural elements, which are conserved: box C/D snoRNAs (SNORDs) and box H/ACA snoRNAs (SNORAs) (12). Additionally, it is important to mention some small RNAs associated with the Cajal body (scaRNAs), which are usually involved in guiding small nuclear RNA modifications (13). Alteration in a single snoRNA can have deleterious effects. The relevance of snoRNA dysregulation in human cancer has been extensively investigated and challenges the view that snoRNAs function solely as maintenance genes for post-transcriptional modification of rRNAs (7).

It is important to emphasize that snoRNAs share biological characteristics with extensively studied miRNAs, including being accessible markers useful in the clinic (11). Their role as biomarkers in diagnosis, prognosis, and chemotherapy resistance has been studied in breast cancer (14), lung cancer (15), bladder cancer (16), and others. Although the involvement of snoRNAs has been explored in various types of cancer, there are still no reports of snoRNA involvement in PeCa. To the best of our knowledge, this is the first study addressing the expression profile of snoRNAs in PeCa. We present this article in accordance with the STROBE reporting checklist (available at https://tau.amegroups.com/article/view/10.21037/tau-24-305/rc).

Methods

In this cross-sectional observational study, 8 patients with anatomopathological diagnosis of PeCa were selected, and they underwent surgical procedures at referral hospitals in São Luis-Maranhão [University Hospital of the Federal University of Maranhão (HU-UFMA) and Aldenora Bello Cancer Hospital (HCAB)] from August 2016 to August 2017. For control samples, 4 specimens were collected from patients diagnosed with phimosis who did not show viral cytopathic effects, and neoplastic or preneoplastic lesions, including lichen sclerosus.

The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. All patients or their legal guardians were informed about the research and only participated after signing the Free and Informed Consent Form (FICF). This project was approved by the Research Ethics Committee of the University Hospital of the Federal University of Maranhão (No. 1.093.435).

Molecular analysis

For our molecular analysis, initially, tumor samples were selected from the archive of formalin-fixed paraffin-embedded (FFPE) surgical specimens. The slides from the selected cases based on inclusion criteria were reviewed by a uropathologist, who chose cases with at least 70% neoplastic cells. The blocks related to the slides were forwarded for 10-micrometer cuts using a microtome. The sections were stored in sterile tubes and sent for RNA extraction.

The DNA extraction was performed, right after surgery, from fresh tumor tissue with phenol-chloroform, as previously described by Sambrook et al. [1989] (17), with modifications. The RNA was obtained using the High Pure miRNA Isolation Kit (Roche Applied Science, UK), according to manufacturer specifications, from paraffined tumor right before the microarray.

HPV identification

To qualify PeCa samples as to the presence or absence of human papillomavirus (HPV) DNA, a two-step nested polymerase chain reaction (PCR) was conducted. In the first PCR, a set of generic primers called PGMY09/11 was used, as described by Coutlée et al. [2002] (18), which produces a 450 bp fragment of the L1 region of HPV. In the second PCR, the GP5+/6+ primer was used, according to Jacobs et al. [1997] (19). Genotyping of HPV positive samples was performed through sequencing. The obtained nucleotide sequences were viewed in the MEGA 6.0 software, then compared with those from the GenBank/NCBI database, using the BLAST (Basic Local Alignment Search Tool) as a genotyping tool (http://blast.ncbi.nlm.nih.gov/Blast.cgi).

SnoRNAs expression analysis

After RNA extraction, the samples were submitted for analysis using the GeneChip^® Array 4.0 (Affymetrix, Inc., Santa Clara, CA, USA). The array comprised 1,996 probe sets designed to capture small ncRNAs. Total RNA was labeled with the FlashTag^TM Biotin HSR RNA Labeling Kit (Affymetrix) and then purified. The labeled snoRNA was hybridized onto the arrays through GeneChip^® hybridization, followed by washing and staining in the Hybridization Oven 645 (Affymetrix Santa Clara CA, USA) and Fluidics Station 450 (Affymetrix Santa Clara CA, USA). Subsequently, the array was scanned using the GeneChip^® Scanner 7G (Affymetrix, Santa Clara, CA, USA) and Command Console Software 3.2 (Affymetrix, Santa Clara, CA, USA) under standard settings. The raw data were normalized using the robust multi-array average (RMA) method and the detection above background (DABG) algorithm with the Expression Console (Affymetrix, Santa Clara, CA, USA).

In silico analysis

From the raw expression data obtained through microarray analysis, assisted by Transcriptome Analysis Console (TAC) 4.0 software, altered expression was identified by comparing tumor samples with phimosis. The expression pattern was also correlated with clinicopathological features, including lymph node metastasis, angiolymphatic invasion, perineural invasion, staging [tumor, node, metastasis (TNM), 2018], pathological classification of the primary tumor (pT), and HPV status.

Using TAC 4.0 software, after log₂ conversion of normalized signal intensities from the arrays, the data were compared (limma), selecting snoRNAs with a fold change ≥2.0 and ≤−2.0, and P<0.05. False discovery rates (FDRs) were minimized by applying adjusted P values (FDR P value).

Subsequently, we sought additional information about the most relevant altered snoRNAs, such as chromosomal location (RNA central, https://rnacentral.org/) and host gene (SnoDB, http://scottgroup.med.usherbrooke.ca/snoDB/; HGNC, https://www.genenames.org/; snoRNA Atlas, http://snoatlas.bioinf.uni-leipzig.de/). All sequences generated by the TAC program underwent BLAST analysis to confirm the information present in the platforms mentioned earlier.

In the quest to uncover a potential relationship between snoRNAs and therapeutic resistance, we investigated how they behave when exposed to commonly used drugs in PeCa therapy. To achieve this, we conducted research using GPSno (http://hanlab.uth.edu/GPSno). Since this database lacks information on PeCa, not to mention vulvar cancer, we sought data on evolutionarily close cancers, such as cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC). Additional details, including copy number variation, DNA methylation, correlation with proteins, and their clinical significance in other types of cancer, were explored using SNORic (http://bioinfo.life.hust.edu.cn/SNORic/). Both of these tools are associated with The Cancer Genome Atlas (TCGA) program.

Results

All patients who participated in this study had a diagnosis of squamous cell carcinoma, usual histological subtype (Table 1). The expression of 8 samples from patients with PeCa and 4 control samples from patients with phimosis was analyzed. The age between these groups was not significantly different (P>0.05). The ages for controls 1, 2, 3 and 4 were 13, 15, 17 and 17 years, respectively.

Table 1. Clinical-epidemiological characterization and HPV status of patients with penile cancer.

Variables	Cases
	C1	C2	C3	C4	C5	C6	C7	C8
Age (years)	46	45	62	103	80	76	54	78
Profession	Farmer	Farmer	Retiree	Retiree	Retiree	Farmer	Mechanic	Retiree
Marital status	Married	Married	Married	Married	Married	Married	Married	Single
Tumor topography	Glans	Glans	Glans	Glans and body	Glans	Glans and body	Balanopreputial sulcus	Glans
Histological type	Usual	Usual	Usual	Usual	Usual	Usual	Usual	Usual
Histological grade	III	III	III	III	II	II	II	II
Primary tumor (pT)	pT2	pT3	pT3	pT3	pT1a	pT3	pT2	pT1a
Staging	IIa	IIb	IIb	IIb	IIb	IV	IV	I
Type of surgery	Partial penectomy	Total penectomy	Total penectomy	Partial penectomy	Partial penectomy	Total penectomy	Partial penectomy	Partial penectomy
Lymphadenectomy	Positive	Negative	Positive	Negative	Negative	Positive	Positive	Negative
Lymph node metastasis	Positive	Negative	Positive	Negative	Negative	Positive	Positive	Negative
Angiolymphatic invasion	Positive	Negative	Positive	Positive	Negative	Positive	Positive	Negative
Perineural invasion	Negative	Positive	Positive	Positive	Negative	Positive	Negative	Negative
Lichen sclerosus	Negative	Negative	Negative	Negative	Positive	Positive	Positive	Positive
HPV	Positive	Negative	Positive	Positive	Positive	Negative	Negative	Negative
HPV subtype	11	X	16	16	30	X	X	X

HPV, human papillomavirus.

Expression of snoRNAs

A total of 270 snoRNAs with differential expression were identified (fold change ≥2.0 and ≤−2.0, and P value <0.05). Among these, 11 snoRNAs exhibited differential expression between tumor and non-tumor tissues, with 7 being upregulated and 4 downregulated. SNORD13 (RNAU13) fold change =2.36) was one of the most expressed in this group (table available at https://cdn.amegroups.cn/static/public/tau-24-305-1.pdf).

Two hundred and sixty-nine snoRNAs demonstrated differential expression in clinicopathological features (lymph node metastasis, angiolymphatic invasion, perineural invasion, staging, pT, and HPV status). The snoRNAs with the greatest variations in expression for each studied clinicopathological characteristic are summarized in Table 2. SNORD43 showed the highest difference (fold change =9.79), while SNORD13F was the least expressed (fold change =–10.41), among the aforementioned characteristics.

Table 2. Differentially expressed snoRNAs according to clinicopathological characteristics.

Ensembl	Variable	Fold change	P value
HPV (negative × positive)
ENSG00000201700	SNORD113-3, 14qI-3	−2.41	<0.001
ENSG00000238316	RNA U13	2.09	0.03
Lymph node metastasis (negative × positive)
ENSG00000251992	SCARNA17, mgU12-22-U4-8, U91	2.32	<0.001
ENSG00000238387	SNORD13F	−4.80	0.007
Angiolymphatic invasion (negative × positive)
ENSG00000199411	U43, SNORD43	5.47	0.030
ENSG00000238387	SNORD62	−3.9	0.01
Perineural invasion (negative × positive)
ENSG00000263764	U43, SNORD43	5.96	0.01
ENSG00000238387	SNORD13F	−10.13	<0.001
Phimosis (absence × presence)
ENSG00000221139	SNORD23	−3.28	0.009
ENSG00000238387	SNORD13F	−10.41	0.02
T1 × T2
ENSG00000212378	SNORD78	3.22	<0.001
ENSG00000206688	HBII-85-18, SNORD116-18	−2.5	0.004
T1 × T3
ENSG00000212378	SNORD78	3.4	<0.001
ENSG00000251940	SNORA15	3.46	<0.001
T2 × T3
ENSG00000278249	SCARNA2, HBII-382, mgU2-25/61	2.14	0.02
ENSG00000252526	SNORA70	2.04	0.03
I × IV
ENSG00000251992	SCARNA17, mgU12-22-U4-8, U91	3.87	0.002
ENSG00000255717	SNORD26, U26	5.56	0.01
I × IIA
ENSG00000207098	SNORA70	−3.51	0.046
ENSG00000200026	U8	2.26	0.03
I × IIB
ENSG00000212378	SNORD78	3.59	0.008
ENSG00000251992	SCARNA17, mgU12-22-U4-8, U91	5.11	<0.001
IIA × IIB
ENSG00000263764	U43/SNORD43	9.79	0.02
ENSG00000272344	14qII-21, SNORD114-21	−2.32	0.004
IIA × IV
ENSG00000263764	U43/SNORD43	9.79	0.009
ENSG00000252128	SNORD27	−3.38	<0.001

HPV, human papillomavirus; snoRNAs, small nucleolar RNAs; T, size and extent of the primary tumor.

Regarding the types of identified snoRNAs, 158 were of the C/D box type, 102 were H/ACA box type, and 10 were small Cajal Body. Concerning the location of these biomolecules, the host genes were classified into genes encoding protein products [129], long non-coding RNAs (lncRNAs) [75], pseudogenes [1], and obtaining this information was not possible for 65 cases (see table available at https://cdn.amegroups.cn/static/public/tau-24-305-2.pdf).

Through the interpretation of the Venn diagram, some snoRNAs were identified as exclusively expressed in specific clinicopathological characteristics. These findings are summarized in the online table (available at https://cdn.amegroups.cn/static/public/tau-24-305-3.pdf). SNORD78 and SNORD46 had their expression exclusively identified in samples with perineural invasion and lymph node metastasis, respectively.

In an effort to validate our data, a search was conducted in SNORIC, utilizing TCGA data to provide information on the behavior of these snoRNAs in other tumor types. Additionally, a literature search was performed. Table 3 describes the current knowledge about these snoRNAs in other cancers. It was observed that some snoRNAs are associated with factors indicating a worse prognosis, such as metastasis, with a particular emphasis on SNORD78.

Table 3. Information on the participation of snoRNAs in cancer based on the TCGA and NCBI.

SnoRNA (Ensembl)	TCGA	NCBI
SNORD78 (ENSG00000208317)	High expression (P<0.05) was observed when comparing tumor samples with normal samples in tumors in 10 types of malignant neoplasms	In NSCLC, high expression of SNORD78 was associated with worse prognosis. Inhibition of this snoRNA suppressed tumor cell proliferation. While overexpression of SNORD78 promoted cell proliferation. SNORD78 promoted cancer cell invasion by inducing the epithelial-mesenchymal transition. SNORD78 was also obviously up-regulated in cancer stem cells and is required for NSCLC self-renewal. The oncogenic activity of SNORD78 has also been confirmed with in vivo data (20)
	Upregulation was associated (P<0.05) with lower survival in head and neck cancer, Renal papillary cell carcinoma, stomach adenocarcinoma, high grade histologic in bladder cancer, clear cell renal cancer, stage IV hepatocellular carcinoma in breast cancer, breast and renal papillary cell carcinoma, stage III in endometrial cancer	High expression of SNORD78 has been observed in patients with hepatocellular carcinoma, so it has been associated with distant metastasis, and more aggressive staging. Knockdown of SNORD78 inhibited cell proliferation (21)
	Correlation was observed with copy number variation and methylation. In addition to correlation with expression of EIF4EBP1, YAP, ARAF proteins, FASN, fibronectin, NF2, MRe11, SLC1A5, MYH11	Showed a sensitivity of 83.61% in identifying lung cancer (22)
		In prostate cancer, SNORD78 expression was higher in a subgroup of patients who developed metastatic disease (23)
SNORD46 (ENSG00000200913)	High expression (P<0.05) was observed when comparing tumor samples with normal samples in tumors in 11 types of malignant neoplasms	SNORD46 acts as an oncogene in lung cancer. In vitro silencing leads to decreased cell viability, inhibition of invasion and migration (7)
	Upregulation was associated (P<0.05) with shorter survival in adrenocortical carcinoma, cervical squamous cell carcinoma and endocervical adenocarcinoma and esophageal carcinoma, more advanced pathological staging in 7 types of tumors
	Correlation was observed with copy number variation and methylation. In addition to correlation with expression of proteins EIF4EBP1, MYH11, SLC1A5, fibronectin, NF2, 53BP1, Akt, C-Raf, Bak, 14-3-3, 4EBP1
SNORA38 (ENSG00000201042)	High expression (P<0.05) was observed when comparing tumor samples with normal samples in 3 types of tumors	Overexpression in metastatic breast cancer (24)
	Association of high expression with pathological stage II in breast cancer, and grade III in endometrial cancer
SNORD50B (ENSG00000203875)	Lower expression (P<0.05) was observed when comparing tumor samples with normal samples in tumors in 2 types of malignant neoplasms	The SNORD50A-SNORD50B locus is directly linked and inhibits K-Ras and is recurrently deleted in human cancer (25)
	Correlation was observed with variation in copy number. In addition to correlation with expression of proteins Bcl-2, fibronectin, CDK1, Akt, c-Raf, SRC, LKB1
SNORD27 (ENSG00000252128)	High expression (P<0.05) was observed when comparing tumor samples with normal samples in 6 types of tumors	Overexpression was associated with lower survival in patients with myeloma (26)
	Upregulation was associated (P<0.05) with shorter survival in esophageal cancer and lung cancer, more advanced pathological staging in endometrial cancer, bladder cancer and cholangiocarcinoma
	Correlation was observed with variation in copy number and methylation. In addition to correlation with protein expression Fox, PARP1, AR

NCBI, National Center for Biotechnology Information; NSCLC, non-small cell lung cancer; snoRNAs, small nucleolar RNAs; TCGA, The Cancer Genome Atlas.

Cisplatin and methotrexate are commonly used drugs in the chemotherapy treatment of PeCa (27). Since the database used (GPSno) lacks information for PeCa and vulvar cancer, searches for information on embryologically close cancers, such as CESC, were conducted. It was noted that the expression of these snoRNAs can impact treatment efficacy. The search data is summarized in Table 4.

Table 4. Prediction of correlation between expression and treatment successfulness.

SnoRNA symbol	Drug	Rs	Correlation with treatment	P value
SNORA70	Methotrexate	−0.46	Negative	<0.001
SNORA38	Methotrexate	−0.41	Negative	<0.001
HBII-240; SNORD72	Cisplatin	0.32	Positive	<0.001
HBII-115; SNORD23	Methotrexate	0.34	Positive	<0.001
SNORA9	Cisplatin	0.49	Positive	<0.001

SnoRNA, small nucleolar RNA.

Discussion

snoRNAs play a role in carcinogenesis, acting as either oncogenes or tumor suppressors, and may serve as biomarkers in cancers. These biomolecules can participate in mechanisms such as rRNA acetylation, splicing, and post-transcriptional control of mRNA. Additionally, snoRNAs can be further processed to generate snoRNA-derived RNAs (sdRNAs), with characteristics and functions similar to microRNAs and Piwi-interacting RNAs (piRNAs) (28). Given the importance of these snoRNAs, this study identified 270 snoRNAs that may be involved in penile carcinogenesis, suggesting that some, through in silico analysis and literature review, have the potential to act as biomarkers.

It is important to note that our study is based on the identification of a selected set of transcripts presented in the GeneChip^® Array 4.0 (Affymetrix, Inc., Santa Clara, CA, USA), limiting the analysis of snoRNAs not included. Nevertheless, the chip array used was designed to detect 1,996 correctly annotated snoRNAs, covering almost the entirety [2,123] of predicted snoRNAs (snoDB 2.0., accessed on 20/07/23).

Most snoRNAs are transcribed from introns, usually located within genes responsible for encoding proteins associated with both ribosome biogenesis and function. This arrangement ensures the proper balance between ribosomes and associated snoRNAs (29). However, a significant portion of these biomolecules also originates from non-coding genes, such as lncRNAs (30), with notable examples being GAS5 (9 snoRNAs), SNHG14 (24 snoRNAs), and MEG8 (14 snoRNAs), which harbor these snoRNAs as identified in this research. A positive correlation of expression between these lncRNAs and their corresponding snoRNAs was also demonstrated. Furthermore, proteins targeting SNHGs may also target their corresponding snoRNAs (31). It is worth noting that some maintenance lncRNAs, which play important roles in snoRNA biogenesis, also have significant functions in cancer, such as MEG8, which contributes significantly to the induction of epithelial-mesenchymal transition (32); and GAS5, which can induce apoptosis and inhibit the proliferative and metastatic properties of tumors (33); besides being promising therapeutic targets (31,34). Therefore, we suggest additional studies on these lncRNAs to understand the underlying regulatory mechanisms they may also have in PeCa.

Among the snoRNAs with the greatest difference between tumor and control samples, SNORD13 (RNA U13) stands out. In a comparative analysis, lung adenocarcinoma also showed an overexpression of this snoRNA (29). An interactome developed by Romano et al. [2022] (35) revealed that SNORD13 interacts more with molecules located in the nucleus and is involved in transcriptional regulation and RNA metabolism. This snoRNA appears to be related to a more aggressive cellular activity, as its expression was higher in more severe cases, such as angiolymphatic invasion, perineural invasion, and advanced stages.

SNORD43 is commonly used as a reference gene (36,37), although in this study, altered behavior was observed in PeCa, with higher expression in cases with unfavorable prognostic factors, such as angiolymphatic invasion, perineural invasion, and advanced stages. According to observations by Kaur et al. [2020] (38), SNORD43 behaves differently in normal and tumor tissue samples, indicating that other molecules should be used as references.

Altered expression was observed in more than one clinicopathological feature in various snoRNAs (e.g., SNORA73, SNORA15, SNORD75, SNORD78, SNORD46). Notably, SNORA38 was altered in angiolymphatic invasion, lymph node metastasis, perineural invasion, phimosis, and advanced stages (table available at https://cdn.amegroups.cn/static/public/tau-24-305-1.pdf). This snoRNA showed distinct expression in tumor cases with and without angiolymphatic invasion and lymph node metastasis, suggesting its potential as a biomarker. Overexpression of SNORA38 was found in more aggressive cases of breast cancer with lower overall survival (24), and its involvement in the regulation of chromatin structure and cancer pluripotency has been proposed (24,39).

The dysregulation of SNORD78 has been reported in various types of cancer. In a series of 106 prostate cancer patients, SNORD78 showed increased expression in individuals who developed distant metastases (23). It was observed to promote invasion of non-small cell lung cancer (NSCLC) cells by inducing epithelial-mesenchymal transition (39). Conversely, the inhibition of SNORD78 was capable of inhibiting cell proliferation in vitro and in vivo (20,21).

Filippova et al. [2019] (40) demonstrated that snoRNAs can be edited using CRISPR/Cas9 tools. Subsequently, Hebras et al. [2020] (41) inactivated SNORD78 in human cancer cell lines using this technology. These data, in addition to elucidating the role of snoRNAs in the regulation of host gene processing, present the possibility of using this molecular tool as a marker in PeCa.

We identified the expression of SCARNA17 exclusively in samples with lymph node metastasis, SNORD115-34 in perineural invasion, and SNORD46 was expressed only in cases with lymph node metastasis and perineural invasion. Metastasis is the main adverse prognostic factor in PeCa (42). The association between high expression of this snoRNA and unfavorable prognostic factors has been observed in leukemia (43). Furthermore, the functional annotation of its coexpressed genes suggests that this snoRNA is related to biological processes linked to the cell cycle and tumor signaling pathways, such as the Wnt, mitogen-activated protein kinase (MAPK), mammalian target of rapamycin (mTOR), and nuclear factor kappa B (NF-κB) signaling pathways (44).

It has been demonstrated that some non-coding RNAs can act to promote drug resistance. The lncRNA small nucleolar RNA host gene 12 (SNHG12) is overexpressed in temozolomide-resistant glioblastoma (45). Godel et al. [2020] (46) observed that snoRNAs (SNORD3A, SNORA13, and SNORA28) induce doxorubicin resistance in osteosarcomas by modulating the expression of genes involved in DNA repair, ribosome biogenesis, and proliferation. In a literature review (47), it was highlighted that snoRNAs are important regulators of lymphocyte activity and immune response against cancer. We suggest conducting a study on PeCa with the snoRNAs described here and therapeutic resistance, as SNORA70 and SNORA38 snoRNAs have been associated with a reduced response to drugs, while the expression of SNORD72, SNORD23, and SNORA9 was related to an increasing response in similar cancers (GPSno). We also recommend assessing the behavior of these snoRNAs in non-invasive samples, such as plasma, serum, blood, and urine, as they would be more accessible, facilitating collection for diagnosis or monitoring.

These data are unprecedented and provide an overview of snoRNA expression in PeCa. In silico analysis demonstrated that some snoRNAs may have potential as biomarkers in PeCa. Additionally, there are few publications on these biomolecules, making it challenging to compare our data. It should be noted that many of the snoRNAs observed in this study have not yet been reported in the literature. In this case, further research on these markers is necessary, especially to validate their expression patterns using other techniques.

Despite the interesting findings we have described, it is important to make clear the limitations of this work. The sample size is small and no confirmations/ validations were made with other bench methodologies. Despite this, there are good and recognized studies already published in the literature that have investigated a small number of PeCa samples (48), especially since their incidence is not so high, as well as studies that have used in silico tools as a form of confirmation and validation (49,50).

Conclusions

Furthermore, our work provides a comprehensive view of the involvement of snoRNAs with altered expression in association with relevant clinicopathological characteristics in PeCa. These data offer new perspectives for future research in search of effective targeted therapy.

Supplementary

The article’s supplementary files as

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. This project was approved by the Research Ethics Committee of the University Hospital of the Federal University of Maranhão (No. 1.093.435). All subjects or their legal guardians were educated about the study and gave written informed consent.

Data Sharing Statement

Available at https://tau.amegroups.com/article/view/10.21037/tau-24-305/dss

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DOI: 10.21037/tau-24-305