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Cited by 100Cancer-related molecular mechanisms researchRNA modifications and cancerLung Cancer Research Studies

Genome‐wide small nucleolar RNA expression analysis of lung cancer by next‐generation deep sequencing

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Gao, Lu, Ma, Jie, Mannoor, Kaiissar, Guarnera, Maria A., Shetty, Amol, Zhan, Min, Xing, Lingxiao, Stass, Sanford A. +1 more·2015·International Journal of Cancer
DOI 10.1002/ijc.29169
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Abstract

Emerging evidence indicates that small nucleolar RNAs (snoRNAs), a class of small noncoding RNAs, may play important function in tumorigenesis. Nonsmall‐cell lung cancer (NSCLC) is the number one cancer killer for men and women. Systematically characterizing snoRNAs in NSCLC will develop biomarkers for its early detection and prognostication. We used next‐generation deep sequencing to comprehensively characterize snoRNA profiles in 12 NSCLC tissues. We used quantitative reverse transcription polymerase chain reaction (qRT‐PCR) to verify the findings in 40 surgical Stage I NSCLC specimens and 126 frozen NSCLC tissues of different stages. The 126 NSCLC tissues were divided into a training set and a testing set. Deep sequencing identified 458 snoRNAs, of which, 29 had a ≥3.0‐fold expression level change in Stage I NSCLC tissues versus normal tissues. qRT‐PCR analysis showed that 16 of 29 snoRNAs exhibited consistent changes with deep sequencing data. The 16 snoRNAs exhibited 0.75–0.94 area under receiver–operator characteristic curve values in distinguishing lung tumor from normal lung tissues (all ≤0.0001) with 70.0–95.0% sensitivity and 70.0–95.0% specificity. Six genes (snoRA47, snoRA68, snoRA78, snoRA21, snoRD28 and snoRD66) were identified whose expressions were associated with overall survival of the NSCLC patients. A prediction model consisting of three genes (snoRA47, snoRA68 and snoRA78) was developed in the training set of 77 cases, which could significantly predict overall survival of the NSCLC patients ( p < 0.0001). The prognostic performance of the prediction model was confirmed in the testing set of 49 NSCLC patients. The identified snoRNA signatures may provide potential biomarkers for the early detection and prognostication of NSCLC.

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  • There is evidence that malignant cells of lung cancer tissue in primary cultures and lung cancer cell lines express members of the SNORD115 cluster, in addition to many other SNORDs and SNORAs.

    “Although it has been reiterated in recent publications, (Cavaillé, 2017; Chung et al., 2020; Deogharia and Majumder, 2018), there is evidence that malignant cells of lung cancer tissue in primary cultures and lung cancer cell lines express members of SNORD115 cluster, in addition to many other SNORDs and SNORAs (Gao et al., 2014; Liao et al., 2010; Mourksi et al., 2020).”

    From Small nucleolar RNAs in plasma extracellular vesicles and their discriminatory power as diagnostic biomarkers of Alzheimer's disease (2021) · cites this paper as Gao et al., 2014

    Table 3 (p. E628) identifies SNORD115-32 and SNORD115-41 alongside other SNORDs and SNORAs in lung tumor tissue. The Patients and clinical specimens section describes surgically removed and frozen tissues, not primary cultures or lung cancer cell lines; the paper also does not establish expression specifically in isolated malignant cells. (LLM, conf=0.88)

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  28. V C 2014 UICC 10970215, 2015, 6, Downloaded from https://onlinelibrary.wiley.com/doi/10.1002/ijc.29169, Wiley Online Library on [01/09/2023]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License

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Authors
Gao, L., Ma, J., Mannoor, K., Guarnera, M. A., Shetty, A., Zhan, M., Xing, L., Stass, S. A., & Jiang, F.
Affiliations
  • University of Maryland, Baltimore (US)
  • Hebei Medical University (CN)
Corresponding author
Jiang, Feng
ORCID
Venue
International Journal of Cancer
Publisher
Wiley
Published
2014-09-04
Volume
136
Issue
6
Pages
E623-9
ISSN
  • 0020-7136 (ISSN-L)
  • 1097-0215
DOI
10.1002/ijc.29169
OpenAlex
W1947520875
Cited by
100
References
1
Citations by year
2026: 2 · 2025: 5 · 2024: 20 · 2023: 5 · 2022: 13 · 2021: 16 · 2020: 10 · 2019: 7 · 2018: 9 · 2017: 6 · 2016: 4 · 2015: 3
FWCI
1.39
Type
journal article
Language
en
Open access
Licence
onlinelibrary.wiley.com/termsAndConditions#vor (vor)
Locations
  • International Journal of Cancer (publishedVersion)
  • PubMed (publishedVersion)
Funders
  • LUNGevity Foundation
  • National Cancer Institute (R01CA161837)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › Cancer-related molecular mechanisms research
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › RNA modifications and cancer
  • Health Sciences › Medicine › Oncology › Lung Cancer Research Studies
Keywords
small nucleolar RNA, non-small cell lung cancer, prognostic factors, early detection, overall survival prediction, tumor versus normal tissue discrimination, prediction model
MeSH terms
Aged, Carcinoma, Non-Small-Cell Lung, Female, Humans, Lung Neoplasms, Male, Middle Aged, Neoplasm Staging, Gene Expression Regulation, Neoplastic, Proportional Hazards Models, Reverse Transcriptase Polymerase Chain Reaction, RNA, Small Nucleolar, High-Throughput Nucleotide Sequencing

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