Advancing NSCLC Diagnosis: The Role of Tumor-Derived Serum Exosomal SNORD60 as a Novel Biomarker

Abstract

Due to the lack of efficient diagnosis techniques, non-small cell lung cancer (NSCLC) continues to be the main contributor to global death from cancer. Consequently, our research aims to identify reliable biomarkers for diagnosing non-small cell lung cancer (NSCLC) by using serum exosomal short nucleolar RNAs (snoRNAs). Based on the databases, we selected SNORD60 and further verified it in 48 paired FFPE tissues. To define exosomes isolated from the serum, we conducted transmission electron microscopy (TEM) and qNano besides western blots. qRT-PCR helped further verify SNORD60 in exosomal serum from 132 NSCLC patients and 143 participants in good health. The receiver operating characteristic (ROC) was employed to estimate the diagnostic efficacy of SNORD60, both alone and in combination with carcinoembryonic antigen (CEA) and cytokeratin 19 fragment (CYFRA21-1). SNORD60 was significantly overexpressed in tissues and serum exosomes of NSCLC patients compared to those of good-health individuals. To evaluate the effectiveness of diagnostic biomarkers for NSCLC and its early stage, serum exosomal SNORD60 was found to have the ability to be a diagnostic biomarker, as well as CEA or CYFRA21-1 with an exosomal combination of SNORD60. The exosomal level of SNORD60 is significantly overexpressed in patients with NSCLC, which offers a promising diagnostic biomarker of NSCLC.

Supplementary Information

The online version contains supplementary material available at 10.1007/s12291-024-01230-y.

Introduction

Based on the cancer data for the year 2022, it is noteworthy that while lung cancer no longer exhibits the greatest incidence rate among various types of cancer, it remains the primary contributor to mortality associated with cancer. Non-small cell lung cancer (NSCLC) is widely recognized as the predominant histological subtype of lung cancer, with about 85% [1, 2]. Although current diagnosis and treatment methods have made great progress, the overall 5-year survival rate of NSCLC patients is still extremely low [3, 4]. The primary factor contributing to the unfavorable prognosis is the late diagnosis of NSCLS, so missed the best time for treatment. Therefore, early NSCLC diagnosis has become a challenge in the current diagnosis and treatment.

Extracellular Vesicles (EVs) originate from cells and are in the microenvironment. They include exosomes and microvesicles. EVs may be categorized depending on their physical properties, such as size. “Small EVs” (sEVs) are those with a diameter of < 200 nm, while “medium/large EVs” (m/l EVs) are vesicles that have a diameter of more than 200 nm.

Exosomes are small lipid bilayer vesicles with a 30–100 nm diameter produced by several cells with their release into the extracellular environment [5], with a wide range of biological and genetic materials transferred horizontally to govern the function of receptor cells. They are considered good intercellular communication messengers. In the past ten years, miRNAs [6], lncRNAs [7], and circRNAs [8] have been extensively studied, while small nucleolar RNAs (snoRNAs) have gradually attracted the attention of researchers.

SnoRNAs are small noncoding RNAs, typically ranging from 60 to 300 nucleotides in length, and frequently localized in the nucleolus of eukaryotic cells [9]. snoRNAs primarily consist of the C/D and H/ACA boxes. They are essential in modifying, maturing, and stabilizing pre-rRNA (ribosomal RNA) [10]. Recent studies have found that free or exosomal snoRNAs were not only dysregulated in tumors but were also vital in their occurrence and progression. SNORA71A is a new prognostic biomarker in hepatocellular carcinoma (HCC) [11]. SNORA24 plays an oncogenic role by governing the p53 stability in colorectal cancer [12].

Initially, we selected SNORD60 based on SNORic databases, and then we verified its effectiveness in FFPE tissues and serum exosomes even further. SNORD60 had a significant overexpression in NSCLC and early-stage patients compared to good-health volunteers. It has a fairly good diagnostic efficiency, which could be improved by combining it with carcinoembryonic antigen (CEA) and the cytokeratin 19 fragment (CYFRA21-1). The results suggest tumor-derived serum exosomal snoRNA60 diagnostic markers for both NSCLC and its early stage.

Materials and Methods

Patients and Sample Preparation

The recruitment of 132 patients with NSCLC and 143 healthy volunteers from the Affiliated Tai’an City Central Hospital of Qingdao University occurred between March 2021 and July 2021.

Before the specimen was taken, all subjects had no treatment. The healthy volunteers were selected from those who participated in health checks. Query the clinical pathological characteristics of the patient medical record system, such as personal information and histopathological type. Participants with a history of cancer or elevated serum tumor marker levels were excluded.

Each patient and healthy volunteer collected about 4 mL of peripheral blood stored in evacuated and promoting coagulating tubes. Within 1 h, the blood underwent centrifugation at 4 °C at 1000 × g for 10 min and then preserved at − 80 °C.

In addition, we gathered formalin-fixed, paraffin-embedded (FFPE) specimens of NSCLC and corresponding adjacent normal tissue from a total of 48 NSCLC patients.

Isolation of Exosomes and LEVs

Following the procedures described above, the exosomes were extracted by ultracentrifugation. The serum was melted on ice. After reverse mixing, 30 min of 10,000 g centrifugation at 4 °C occurred. Subsequently, the exosomes were extracted by 2 h of 100,000 × g ultracentrifugation at 4 °C, and the large EVs (LEVs) were separated via two centrifugations at 14,000 × g for 35 min at 4 °C.

Identification of Exosomes

A total of 15 μL exosome suspension was dropped on the copper screen and left for 1 min in standing. After removing the residual exosome sample with clean filter paper, a 15 μL solution containing 2% uranyl acetate dye was slowly introduced for a period of 1 min before undergoing the dying process at ambient temperature. After 10 min of baking under the lamp concerning the dyed sample, an FEI Tecnai T20 transmission electron microscope (FEI Company, USA) was employed to recognize the morphology of the exosomes.

Subsequently, qNano (New Zealand) helped to measure the particle size and the width of the exosome distribution according to the protocols and then assessed by the Izon Control Suite (Izon Control Suite version 3.3.2.2001; Izon Science).

Typically, 20 µg exosomal protein extract was segregated through 10% SDS-PAGE and diverted to the PVDF membrane (Millipore, MA, USA)). Following 2 h of 5% skimmed milk blockage, the PVDF membrane was hatched for the entire night with primary antibodies (anti-TSG101, anti-CD9, and anti-CD81) (all 1:1000, Cell Signaling Technology, MA, USA) at 4 °C. Subsequently, it underwent 1-h incubation in the conjugation of the secondary antibody and HRP at ambient temperature. We utilized an ECL blotting test reagent (Bio-Rad, CA, USA) to observe the protein bands.

Databases

The download of snoRNA expression data from tumor and corresponding normal tissue specimens for lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC) was from the SNORic database, established based on the literature [13] where 46 patients with LUAD and 45 patients with LUSC provided both tissue samples. Using TCGA (http://cancergenome.nih.gov), We obtained the relevant clinical data of 989 instances of NSCLC, which includes 784 cases in the early stage (Table S1).

RNA Extraction and Quantitative Real-Time PCR (qRT-PCR)

The RNAprep Pure FFPE kit (Tiangen Biotech in Beijing, China) was employed to obtain total RNA from FFPE tissues following the procedure. The extraction of RNA from exosomes was carried out employing TRIzol reagent (Thermo Fisher Scientific, Carlsbad, USA) and subsequently transformed into cDNA by the process of reverse transcription deploying the miRNA first strand cDNA synthesis kit (AG11716). Totally, 10 µl are comprised of the reverse transcription system: 1.25 µl reverse transcription, 3.75 µl RNA, and 5 µl buffer. The program consisted of three steps: first, incubation at a temperature of 37 °C for a duration of 60 min; second, a temperature increase to 85 °C for a period of 5 min; and third, maintenance at a temperature of 4 °C until the completion of the process. The ultimate cDNA result should be kept at a temperature of –80 °C until it is employed for experimentation.

qPCR with SYBR Green Premix Pro Taq HS qPCR Kit (AG11701) was conducted on the LC480 (Roche Diagnostics, Germany). Calculating the relative expression amount of genes is done using the △Ct method (Ct^snoRNA-Ct^U6) according to the scheme described previously [14, 15]. Each sample was retested.

The sequences of the primers used were as follows:

For snoRNA 60: Forward 5’-GCTTTGACTTCTGACACCTCG-3’ and Reverse 5’-TGCTAAATAATCAGACTGCACGTG-3’.

For U6: Forward 5’-TGGAACGCTTCACGAATTTGCG-3’ and Reverse 5’-GGAACGATACAGAGAAGATTAGC-3’.

Statistical Analyses

GraphPad Prism 6.0 (CA, USA) and SPSS 22.0 (EIBM Corp., Armonk, NY, USA) conducted the statistical analysis. Different snoRNAs were confirmed among groups by ANOVA or Kruskal–Wallis tests. The relationship between clinical characteristics and snoRNAs was assessed with the paired-sample t-test and X² test. The receiver operating characteristic (ROC) and the area under the curve (AUC) helped calculate the diagnostic power of candidate predictors. The statistically significant cut-off value is defined as P < 0.05. Various parameters were integrated into models to conduct ROC curve analysis.

In summary, a multinomial logistic regression analysis model was constructed using SPSS software. This model was developed with the intention of classifying patient diagnoses, and SNORD60, CEA, and CYFRA21-1 were taken into consideration as factors that may have an impact on the classification. Afterward, the logistic regression equation’s constant terms and coefficients were acquired. Subsequently, the compute variable function in SPSS was employed to construct the integrated predictors. Ultimately, the ROC curve for the combination diagnosis was constructed using the combined predictors and the categorization of patient diagnosis.

Results

Determination of snoRNAs in NSCLC from the Database

Figure 1A–D show that heatmaps and volcano plots, drawn using paired data through log2 (FC = fold change) and p-value, showed the snoRNAs expression patterns.

Fig. 1.

Determination of SNORD60 from datasets. A–C The heatmaps highlighted the snoRNA differential expression in LUAD A and LUSC C. The red labeled the chosen SNORD60. B–D Volcano plots compared snoRNA differential expression employing log2 (FC) and the p-value in LUAD B and LUSC D. The yellow and green dots represent the up- and down-regulated snoRNAs, respectively. LUSC, lung squamous cell carcinoma; LUAD, lung adenocarcinoma

We selected 15 snoRNAs based on log2 (FC) and p-value. The snoRNA expression was verified in both FFPE tissues and serum exosomes by qPCR. Among these 15 selected snoRNAs, only SNORD60 showed significant overexpression in tumor and early-stage tissues compared to normal. Fig. S1 presents part of the data.

Furthermore, according to the database, SNORD60 had log2 (FC) = 1.6 and 2.2 with p value = 0.0001 and 6.5E–14, respectively.

SNORD60 was Significantly Overexpressed in NSCLC and Early NSCLC Tissues

Depending on TCGA, we verified an extensive sample of SNORD60 differential expression. Figure 2A–B illustrate that SNORD60 showed significant overexpression in tumor (n = 989) (P < 0.0001) and early-stage tissues (n = 784) than in normal (n = 91) (P < 0.0001). Because of this, they were chosen for a subsequent investigation. Furthermore, we analyzed the association between SNORD60 levels and clinicopathological features. Figure 2C and Table S1 reveal that SNORD60 correlates with T’s stage and histology.

Fig. 2.

SNORD60 was significantly overexpressed in NSCLC tissue. A–C Analysis of SNORD60 differential expression employing databases encompassing normal vs. NSCLC, normal vs. early-stage NSCLC, and stage T1 vs. T2 vs. T3 vs. T4. D–E Analysis of SNORD60 differential expression in 48 paired FFPE samples, encompassing normal vs. NSCLC (P < 0.0001) and normal vs. early-stage NSCLC (P = 0.0028). (*P < 0.05, **P < 0.01, ****P < 0.0001)

For additional identification of the different levels of SNORD60 expression in NSCLC, we verified SNORD60 expression by qPCR among 48 cases of NSCLC and paired paracancerous FFPE tissue samples. Consistently, Fig.. 2D–E reveal that SNORD60 showed a significant upregulation in NSCLC (P < 0.0001) and in 34 early-phase NSCLC (P = 0.0028) than in the good-health volunteers. Meanwhile, the connection assessment between SNORD60 expression levels and clinicopathological parameters showed no significant relationship (Table 1).

Table 1.

Characteristics of NSCLC patients for SNORD60 in FFPE specimens

Parameters	Samples, n	Δ Ct Median ( interquartile range)	P-value
Age (years)
> 62.5	24	3.000(2.268–3.765)	0.3104
≤ 62.5	24	3.060(2.670–4.170)
Gender
Male	32	2.915(2.333–3.780)	0.1805
Female	16	3.405(2.865–3.930)
Smoking
No	18	3.165(2.185–3.770)	0.7395
Yes	27	2.940(2.460–4.040)
Not available	3
Drinking
No	23	3.070(1.870–4.010)	0.7446
Yes	21	2.900(2.375–4.070)
Not Available	4
Histology
AC	24	2.950(1.975–3.538)	0.3104
SCC	24	3.090(2.635–4.323)
Tumor size
V > 6cm3	22	3.080(2.410–4.308)	0.6127
V ≤ 6cm3	23	3.000(2.290–3.540)
Not Available	3
T stage
T1	26	2.970(2.433–3.578)	0.9014
T2	14	3.080(1.770–4.308)
T3	3	3.530(2.460–3.840)
T4	2	3.920(2.760–5.080)
TX	3
LN meta
N0	32	3.020(2.333–3.968)	0.5660
N1	4	3.065(2.963–4.075)
N2	4	2.405(− 0.5750–3.353)
N3	4	3.260(1.453–4.753)
NX	4
Distant Nmeta
M0	44	3.050(2.465–3.968)
M1	1	1.110
MX	3
TNM stage
I	25	3.000(2.275–3.850)
II	9	3.070(2.695–4.085)
III	9	2.820(2.235–4.515)
IV	1	1.110
Not Available	4

Determination of Extracted Serum Exosomes

TEM, qNano, and Western blots defined isolated serum exosomes from NSCLC patients and the good-health volunteers. Figure 3A-B manifest the characteristic oval shape of exosomes, which have a diameter ranging from 50–150 nm and a consistent size distribution. There was an enrichment in TSG101, CD9, and CD81 as characteristic markers of exosomes (Fig. 3C).

Fig. 3.

Determination of derived serum exosomes. A Illustrative TEM images of isolated exosomes from sera from NSCLC patients B The 50–150 nm size distribution of exosomes as assessed by the qNano system. C Immunoblots manifesting the exosomal proteins TSG101, CD9, and CD81 expression levels

SNORD60 was Stably Expressed in Serum Exosomes

First, we studied the SNORD60 position in the serum by detecting SNORD60 levels in exosomes, LEVs, and vesicle-depleted serum. Figure 4A shows that SNORD60 is predominately expressed in serum exosomes other than in vesicle-depleted serum and LEVs.

Fig. 4.

Characteristics of serum exosomal SNORD60. A SNORD60 expression levels from vesicle-depleted serum, LEVs, and exosomes; B in exosomes treated with RNase A; and C in exosomes incubated at ambient temperature for various periods (LEVs, micro-vesicles; **P < 0.01, ***P < 0.001, ns, nonsignificant)

Subsequently, we validated the stability of SNORD60 in exosomes. Figure 4B presents that serum exosomes were treated with RNase A, which did not affect SNORD60 expression in exosomes. No significant alterations in SNORD60 expression were manifested throughout the four time intervals tested (0, 8, 16, and 24 h) when the exosomes were incubated at room temperature (Fig. 4C).

Serum exosomal SNORD60 as a marker for NSCLC and its early-stage diagnosis.

Initially, SNORD60 was detected in serum exosomes with extensive validation, including 132 NSCLC patients and 143 healthy individuals. Figure 5A-B illustrate a significant overexpression in serum exosomal SNORD60 among patients with NSCLC patients (P < 0.0001) and 56 patients (P < 0.0001) than among donors of good health. Furthermore, compared to healthy individuals, the snoRNA expression was significantly increased at every TNM stage (Fig. 4C). Table 2 provides a summary of the correlation between exosomal SNORD60 and the clinicopathological parameters of NSCLC cases, but no significant correlation was found.

Table 2.

Characteristics of NSCLC patients for SNORD60 in serum exosomes

Parameters	Samples, n	Δ Ct Median ( interquartile range)	P-value
Age (years)
≤ 62	68	7.628(6.700–9.705)	0.0567
> 62	64	7.163(6.135–8.611)
Gender
Male	78	7.485(6.531–9.225)	0.3959
Female	54	7.213(6.113–8.740)
Smoking
No	60	7.458(6.159–8.635)	0.4419
Yes	72	7.370(6.494–9.274)
Drinking
No	78	7.378(6.048–8.693)	0.1746
Yes	54	7.418(6.709–9.395)
Histology
AC	92	7.528(6.349–9.086)	0.8947
SCC	33	7.080(6.393–9.308)
others	7
T stage
T1	43	7.920(6.310–9.590)	0.2298
T2	44	7.563(6.040–9.274)
T3	10	6.648(6.356–7.370)
T4	28	7.210(6.454–7.908)
TX	7
LN meta
N0	51	7.530(6.310–9.095)	0.3824
N1	12	8.068(7.206–9.293)
N2	37	7.985(6.193–9.320)
N3	25	6.900(6.275–7.568)
NX	7
Distant meta
M0	84	7.460(6.326–9.216)	0.5378
M1	43	7.195(6.315–8.675)
MX	5
TNM stage
I	41	7.730(6.230–9.300)	0.9143
II	15	7.230(6.550–9.255)
III	29	6.925(6.340–8.840)
IV	43	7.445(6.315–8.675)
Not Available	4

We utilized the ROC curve to validate the SNROD60 value in serum exosomes as a valid marker for diagnosing NSCLC. Figure 5D illustrates that AUC was 0.8082, with a sensitivity of 82.5% and a specificity of 71.2%. The ROC curve showed favorable diagnostic efficiency of SNORD60 with AUC of 0.7969 with 85.3% sensitivity and 66.1% specificity (Fig. 5E) when comparing early-stage NSCLC patients with controls, indicating that SNORD60 is a promising noninvasive biomarker to diagnose NSCLC.

Fig. 5.

Serum exosomal SNORD60 acted as a biomarker for NSCLC diagnosis. A SNORD60 differential expression in serum exosomes of 143 healthy donors and 132 NSCLC patients and B in serum exosomes of 143 healthy donors and 56 early-stage NSCLC patients. C Serum exosomal SNORD60 expression levels in different TNM stages contrasted with healthy donors. D The ROC curve analysis of serum exosomal SNORD60 for NSCLC and (E) for early-stage NSCLC. ROC, receiving operating characteristics. (****P < 0.0001)

The serum exosomal SNORD60 and Tumor Markers Combination Raised the NSCLC Diagnostic Accuracy

The utilization of CEA as a pan-tumor prognostic biomarker is advised for diagnosing NSCLC. CEA levels were evaluated in 131 NSCLC patients, of which 55 were early-stage patients, and 143 were controls. The diagnostic efficiency was also calculated in combination with serum exosomal snoRNA expression. Figure 6A-B present that SNORD60 significantly increased the AUC of CEA from 0.7758 to 0.8941. In addition, we detected the cytokeratin 19 fragments CYFRA21-1 levels, another recognized circulatory tumor marker, in 130 NSCLC patients, of which were 55 early-stage patients and 143 controls and showed an AUC of 0.7838 for NSCLC diagnosis (Fig. 6C). Interestingly, the combination of SNORD60 and CYFRA21-1 showed a greater AUC of 0.8994 (Fig. 6D). The highest AUC of 0.9198 was from the combination of three markers, with a corresponding increase in sensitivity and specificity to 80.8% and 95.1%, respectively (Fig. 6E). CEA with serum exosomal SNORD60 combination (AUC = 0.8203) led to a significant improvement in the diagnostic effectiveness in the early stage than CEA alone (AUC = 0.6076) (Fig.. 6F-G). Similarly, the combination of SNORD60 with CYFRA21-1 led to a higher AUC (0.8348) than CYFRA21-1 alone (AUC = 0.6144) (Fig.. 6H-I). Furthermore, integrating the three biomarkers possessed the greatest AUC of 0.8475 with 80.0% sensitivity and 81.8% specificity for the early diagnosis of NSCLC (Fig. 6J). Together, serum exosomal SNORD60 can potentially improve the diagnostic precision of well-established markers for NSCLC in addition to its early stages, such as CEA and CYFRA21-1.

Fig. 6.

Enhanced diagnostic ability of serum exosomal SNORD60 integrated with established tumor markers in NSCLC and early-stage NSCLC patients. A–B The AUC of CEA or CEA integrated with SNORD60 for NSCLC diagnosis. C–D The AUC of CYFRA21-1 or CYFRA21-1 combined with SNORD60 for NSCLC diagnosis. E The AUC of SNORD60 combined with CEA and CYFRA21-1 for NSCLC diagnosis. F–G: The AUC of CEA or CEA combined with SNORD60 for early-stage NSCLC diagnosis. H–I: The AUC of CYFRA21-1 or CYFRA21-1 combined with SNORD60 for early-stage NSCLC diagnosis. J: The AUC of SNORD60 integrated with CEA and CYFRA21-1 for early-stage NSCLC diagnosis

Discussion

Prompt identification and timely intervention are essential for enhancing the overall survival rate of NSCLC [16, 17]. With the further study of tumor molecular biology, it is essential to find novel and effective biomarkers to support early diagnosis [18].

snoRNAs were considered to exist mainly in the nucleolus and to have a single function; therefore, the research on snoRNAs fell into a low tide for a long time. However, recently, since the advancement of sequencing technologies, there has been an increase in evidence suggesting that cancers have aberrantly regulated snoRNAs that are involved in genetic disorders[19, 20], hematopoiesis [21, 22], metabolism [23], and malignancies [24–26].

Herein, we first demonstrated that SNORD60 has a significantly up-regulated expression in FFPE tissues and serum exosomes extracted from NSCLC patients compared to controls. Moreover, it has the same performance in early-stage NSCLC.

The findings assume that tumor-derived serum exosomal snoRNA60 is an excellent biomarker for diagnosing NSCLC and its early stage. SNORD60 expression levels had no significant relationship with clinicopathological parameters, possibly due to the limited size of the sample.

SNORD60 is a type of snoRNA that belongs to the C/D box family. Its position is on chromosome 16, and its encoding is carried out by introns of the AA974883 gene [27]. To our knowledge, only quite a few articles have been reported on SNORD60. Zhou et al. discovered that SNORD60 has an oncogenic role in LUAD; therefore, it could be a biomarker for its diagnosis [28]. Zhang et al. found that A new biomarker for diagnosing renal cell cancer is a three-snoRNA profile consisting of SNORD15A, SNORD35B, and SNORD60 [29]. Wu et al. discovered through research that SNORD60 could function as a new biomarker for treating endometrial cancer, offering new approaches for diagnosis and therapy [30]. However, these articles were only verified in FFPE tissues or urinary sediment. No further validation was performed in serum or exosomes. Our research involves the above two types of specimens, which is more reliable.

Extensive research has highlighted the significant role of snoRNA in cancer research, emphasizing its importance. Kitagawa T. et al. [31] identified that SNORA74A and SNORA25 could function as noninvasive diagnostic biomarkers for the early detection of pancreatic ductal adenocarcinoma. Song et al. revealed that SNORA38 is an oncogene in breast cancer. Besides, it could serve as a prognostic marker [32]. Liu et al. demonstrated that 15 snoRNAs might serve as prognostic markers for sarcoma [33]. Previous studies assumed that snoRNAs were absent from exosomes, leading to limited research in this area. Consequently, very few articles have explored exosomal snoRNAs [31], while most researchers have concentrated on snoRNAs in tissue [11, 34], serum, or plasma samples [35, 36]. Our research mainly focused on the exosome by detecting the expression of snoRNAs in serum exosomes and analyzing their differences in different populations. We found that serum exosomal SNORNA60 is an ideal diagnostic biomarker for NSCLC and its early stage. Furthermore, similar to previous studies [15], snoRNA60 can stably exist in exosomes and resist interference by RNA enzymes. This will become a biomarker worthy of exploration in clinical practice.

There are certain constraints in our investigation. The association between snoRNA60 and the treatment efficacy or prognosis of NSCLC cannot be evaluated due to the limited size of our cohort, the lack of long-term clinical data, and the general inadequacy of the study. Additionally, the types of disease included in the study were relatively single, and benign conditions such as pneumonia were not involved. Furthermore, there were no functional or mechanistic experiments. Therefore, future research will be carried out in a larger cohort and more types of disease to confirm our findings. Furthermore, more research will be carried out in cells and animals to clarify the possible pathogenesis of snoRNA60. More importantly, we will explore the mechanism of exosomal SNORD60 upregulation to employ this understanding in a therapeutic setting in the future.

Conclusions

In conclusion, the exosomal SNORD60 level is significantly overexpressed in patients with NSCLC, especially in the early stage. Exosomal SNORD60-relatively novel diagnostic biomarkers could function as a possible diagnostic marker and potential therapeutic target for NSCLC. This biomarker is expected to evolve into new predictive elements that may be employed in clinical practice.

Supplementary Information

Below is the link to the electronic supplementary material.

Author contributions

All authors participated in the project design, interpretation of results, data analysis, and manuscript review; ZJZ and XML designed the experiments; LL and QZ conducted the experiments; NY performed the statistical analysis; KYW and NY wrote the article. All authors have accepted the final manuscript.

Funding

This work was funded via the Natural Science Foundation of Shandong Province (no. ZR2023QH096), the Tai’an City Science and Technology Development Plan Project (2022NS332, 2022NS212) and the Nursery Project of the Affiliated Tai’an City Central Hospital of Qingdao University (no.2022MPM01).

Data availability

The author can provide original data supporting the conclusion of this investigation without reservation.

Declarations

Conflict of interest

The author(s) declared no potential conflicts of interest.

Ethical approval

The research conducted with human subjects underwent a thorough evaluation and received clearance from the Affiliated Taian City Central Hospital Committee of Qingdao University (approval number: 2023–05-10). Each participant provided their informed permission in compliance with the principles outlined in the Declaration of Helsinki.