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. 2024 Nov 14:17:1017-1032.
doi: 10.2147/OTT.S475644. eCollection 2024.

Prognostic Value of miR-10a-3p in Non-Small Cell Lung Cancer Patients

Affiliations

Prognostic Value of miR-10a-3p in Non-Small Cell Lung Cancer Patients

Julija Simiene et al. Onco Targets Ther. .

Abstract

Purpose: Poor lung cancer patients' outcomes and survival rates demand the discovery of new biomarkers for the specific, significant, and less invasive detection of non-small cell lung cancer (NSCLC) progression. The present study aimed to investigate the potential of miRNA expression as biomarkers in NSCLC utilizing a preclinical cell culture setup based on screening of miRNAs in NSCLC cells grown in 3D cell culture.

Patients and methods: The study was performed using lung cancer cell lines, varying in different levels of aggressiveness: NCI-H1299, A549, Calu-1, and NCI-H23, as well as noncancerous bronchial epithelial cell line HBEC3, which were grown in 3D cell culture. Total RNA from all cell lines was extracted and small RNA libraries were prepared and sequenced using the Illumina NGS platform. The expression of 8 differentially expressed miRNAs was further validated in 89 paired tissue specimens and plasma samples obtained from NSCLC patients. Statistical analysis was performed to determine whether miRNA expression and clinicopathological characteristics of NSCLC patients could be considered as independent factors significantly influencing PFS or OS.

Results: Differentially expressed miRNAs, including let-7d-3p, miR-10a-3p, miR-28-3p, miR-28-5p, miR-100-3p, miR-182-5p, miR-190a-5p, and miR-340-5p, were identified through next-generation sequencing in NSCLC cell lines with varying levels of aggressiveness. Validation of patient samples, including tumor and plasma specimens, revealed that out of the 8 investigated miRNAs, only plasma miR-10a-3p showed a significant increase, which was associated with significantly extended progression-free survival (PFS) (p=0.009). Furthermore, miR-10a-3p in plasma emerged as a statistically significant prognostic variable for NSCLC patients' PFS (HR: 0.5, 95% CI: 0.3-0.9, p=0.029).

Conclusion: Our findings of screening miRNA expression patterns in NSCLC cells grown in 3D cell culture indicated that the expression level of circulating miR-10a-3p has the potential as a novel non-invasive biomarker to reflect the short-term prognosis of NSCLC patients.

Keywords: 3D cell culture; NSCLC; miRNAs; non-invasive clinical biomarkers; survival.

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Conflict of interest statement

The authors confirm that there are no known conflicts of interest associated with this publication and the financial support received has no influence to its outcome.

Figures

Figure 1
Figure 1
miRNA expression pattern in lung cancer cell lines in contrast to normal lung cell line. (A) Venn diagram demonstrating counts of statistically significant differentially expressed miRNAs in H23, H1299, Calu-1, and A549 (>2 fold-change, FDR<0.05, at least 10 mapped reads per million transcripts in miRNA library) compared to normal lung cell line HBEC. The bold text represents 8 commonly deregulated miRNAs in the more aggressive Calu-1, H1299, and A549 cells. (B) Expression pattern of miRNAs differentially expressed in lung cancer H23, H1299, Calu-1, and A549.
Figure 2
Figure 2
Relative expression of selected miRNAs in NSCLC tissue (n=89) and plasma (n=89) compared to paracancerous and normal samples. The expression levels of let-7d-3p (A), miR-10a-3p (B), miR-28-3p (C), miR-28-5p (D), miR-100-3p (E), miR-182-5p (F), miR-190a-5p (G), and miR-340-5p (H) were normalized to the housekeeping gene RNU6B and determined by the 2−ΔCt method. Wilcoxon and Mann–Whitney tests were used to evaluate statistically significant differences. Whiskers of the boxplot denote the nonoutlier range.
Figure 3
Figure 3
Kaplan-Meier curves illustrating PFS based on the expression of selected miRNAs in NSCLC plasma samples (n=89). Patients were categorized into high and low expression cohorts based on the median value of let-7d-3p (A), miR-10a-3p (B), miR-28-3p (C), miR-28-5p (D), miR-100-3p (E), miR-182-5p (F), miR-190a-5p (G), and miR-340-5p (H). The comparison between groups was conducted using the Log rank test, with corresponding p-values displayed. The bold text represents the statistically significant results (p<0.05).
Figure 4
Figure 4
A forest plot of prognostic factors for NSCLC patients’ PFS in plasma (n=89). A forest plot showing the hazard ratio and 95% confidence intervals associated with Univariate (A) and Multivariate (B) Cox Regression analysis of prognostic factors for NSCLC patients’ PFS in plasma samples. Circles represent the hazard ratio, and the horizontal bars extend from the lower limit to the upper limit of the 95% confidence interval of the hazard ratio estimate. Horizontal bars colored in orange represent the statistically significant results (p<0.05), horizontal bars colored in black represent the statistically non-significant results (p>0.05).

References

    1. Phillips I, Stares M, Allan L, Sayers J, Skipworth R, Laird B. Optimising outcomes in non small cell lung cancer: targeting cancer cachexia. Front Biosci. 2022;27(4):129. - PubMed
    1. Long L, Zhang X, Bai J, Li Y, Wang X, Zhou Y. Tissue-specific and exosomal miRNAs in lung cancer radiotherapy: from regulatory mechanisms to clinical implications. Cancer Manag Res. 2019;11:4413–4424. doi:10.2147/CMAR.S198966 - DOI - PMC - PubMed
    1. Pei Q, Luo Y, Chen Y, Li J, Xie D, Ye T. Artificial intelligence in clinical applications for lung cancer: diagnosis, treatment and prognosis. Clin Chem Lab Med. 2022;60(12):1974–1983. doi:10.1515/cclm-2022-0291 - DOI - PubMed
    1. Li J, Zhang Q, Jiang D, Shao J, Li W, Wang C. CircRNAs in lung cancer- role and clinical application. Cancer Lett. 2022;544:215810. doi:10.1016/j.canlet.2022.215810 - DOI - PubMed
    1. Markou A, Lianidou E, Georgoulias V. Metastasis-related miRNAs: a new way to differentiate patients with higher risk? Future Oncol. 2015;11(3):365–367. doi:10.2217/fon.14.294 - DOI - PubMed