Small Noncoding RNA Expression in Cancer

Abstract Objective: Glioblastoma (GBM) and Primary Central Nervous System Lymphoma (PCNSL) are common intracranial malignant tumors. They sometimes present similar radiological findings and diagnoses could be difficult without surgical biopsy. For improving the current management, development of non-invasive biomarkers are desired. In this study, we explored the differently expressed circulating small noncoding RNA (sncRNA) in serum for specific diagnostic tool of GBM and PCNSL. Material & Methods: Serum samples were obtained from three groups: 1) GBM patients (N=26), 2) PCNSL patients (N=14) 3) healthy control (N=114). The total small RNAs were extracted from serum. The whole expression profiles of serum sncRNAs were measured using Next-Generation Sequencing System. We analyzed serum levels of sncRNAs (15–55 nt) in each serum samples. The difference of sncRNAs expression profile among three groups were compared. Data analysis was performed by logistic regression analysis followed by leave-one-out cross-validation (LOOCV). The accuracy of diagnostic models of sncRNAs combination were evaluated by receiver operating characteristic (ROC) analysis. Results: We created the combination models using three sncRNA in each models based on the logistic regression analysis. The model 1 (based on sncRNA-X1, X2 and X3) enabled to differentiate GBM patients form healthy control with a sensitivity of 92.3% and a specificity of 99.2% (AUC: 0.993). The model 2 (based on sncRNA-Y1, Y2 and Y3) enabled to differentiate PCNSL patients form healthy control with a sensitivity of 100% and a specificity of 93.9% (AUC: 0.984). The model 3 (based on sncRNA-Z1, Z2 and Z3) enabled to differentiate GBM patients form PCNSL patients with a sensitivity of 92.3% and a specificity of 78.6% (AUC: 0.920). Conclusion: We found three diagnostic models of serum sncRNAs as non-invasive biomarkers potentially useful for detection of GBM and PCNSL from healthy control, and for differentiation GBM from PCNSL.

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P46.01 Intronic Noncoding RNA Expression of DCN is Related to Cancer-Associated Fibroblasts and NSCLC Patients’ Prognosis

Journal of Thoracic Oncology ◽

10.1016/j.jtho.2021.01.850 ◽

2021 ◽

Vol 16 (3) ◽

pp. S489

Author(s):

J. Zhou ◽

T. Cheng ◽

X. Li ◽

J. Pineda ◽

X. Wang ◽

...

Keyword(s):

Noncoding Rna ◽

Rna Expression ◽

Cancer Associated Fibroblasts ◽

Nsclc Patients

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Sequence Variations of Epstein-Barr Virus-Encoded Small Noncoding RNA and Latent Membrane Protein 1 in Hematologic Tumors in Northern China

Intervirology ◽

10.1159/000510398 ◽

2021 ◽

Vol 64 (2) ◽

pp. 69-80

Author(s):

Hai-Yu Wang ◽

Lingling Sun ◽

Ping Li ◽

Wen Liu ◽

Zhong-Guang Zhang ◽

...

Keyword(s):

Membrane Protein ◽

Nested Pcr ◽

Noncoding Rna ◽

Epstein Barr Virus ◽

Northern China ◽

Latent Membrane Protein ◽

Latent Membrane Protein 1 ◽

Small Noncoding Rna ◽

Barr Virus ◽

Epstein Barr

Objective: To investigate the relationship between hematologic tumors and Epstein-Barr virus (EBV)-encoded small noncoding RNA (EBER) variations as well as latent membrane protein 1 (LMP1) variations. Methods: Patients with leukemia and myelodysplastic syndrome (MDS) were selected as subjects. Genotypes 1/2 and genotypes F/f were analyzed using the nested PCR technology, while EBER and LMP1 subtypes were analyzed by the nested PCR and DNA sequencing. Results: Type 1 was more dominant than type 2, found in 59 out of 82 (72%) leukemia and in 31 out of 35 (88.6%) MDS, while type F was more prevalent than type f in leukemia (83/85, 97.6%) and MDS (29/31, 93.5%) samples. The distribution of EBV genotypes 1/2 was not significantly different among leukemia, MDS, and healthy donor groups, neither was that of EBV genotypes F/f. EB-6m prototype was the dominant subtype of EBER in leukemia and MDS (73.2% [30/41] and 83.3% [10/12], respectively). The frequency of EB-6m was lower than that of healthy people (96.7%, 89/92), and the difference was significant (p < 0.05). China 1 subtype was the dominant subtype of LMP1 in leukemia and MDS (70% [28/40] and 90% [9/10], respectively), and there was no significant difference in the distribution of LMP1 subtypes among the 3 groups (p > 0.05). Conclusion: The distribution of EBV 1/2, F/f, EBER, and LMP1 subtypes in leukemia and MDS was similar to that in the background population in Northern China, which means that these subtypes may be rather region-restricted but not associated with leukemia and MDS pathogenesis.

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