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Long non-coding RNAs may serve as biomarkers in breast cancer combined with primary lung cancer.

ABSTRACT: Long non-coding RNAs (lncRNAs) have been shown to play important regulatory role in certain type of cancers biology, including breast and lung cancers. However, the lncRNA expression in breast cancer combined with primary lung cancer remains unknown. In this study, databases of the Cancer Genome Atlas (TCGA) and the lncRNA profiler of contained candidate 192 lncRNAs were utilized. 11 lncRNAs were differentially expressed in breast cancer, 9 candidate lncRNAs were differentially expressed in lung cancer. In order to find the aberrant expression of lncRNAs in breast cancer combined with primary lung cancer, seven samples of primary breast cancer and lung cancer were studied for the expression of selected lncRNAs. The results showed that SNHG6 and NEAT1 were reversely expressed in breast cancer combined with primary lung cancer compared with primary breast or lung cancer. In addition, a significant correlation of lncRNAs was found in the patients whose age was above 56 in breast cancer. What's more, PVT1 expression was negatively correlated with the pathological stage, and the level of ER, PR, HER2, p53 in breast cancer. Furthermore, lncRNA expression did not have significant relationship with the 5-year survival of patients with breast cancer combined with primary lung cancer. The findings revealed that PVT1, SNHG6, NEAT1 may serve as a prognostic marker for breast cancer combined with primary lung cancer. Therefore, these lncRNAs are potential molecular indicators in the diagnosis and prognosis of cancer in the future.

SUBMITTER: Ding X

PROVIDER: S-EPMC5601645 | biostudies-literature | 2017 Aug

REPOSITORIES: biostudies-literature

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Long non-coding RNAs may serve as biomarkers in breast cancer combined with primary lung cancer.

Ding Xianfeng X Zhang Yuhan Y Yang Hongjian H Mao Weimin W Chen Bo B Yang Shifeng S Ding Xiaowen X Zou Dehong D Mo Wenju W He Xiangming X Zhang Xiping X

Oncotarget 20170421 35

Long non-coding RNAs (lncRNAs) have been shown to play important regulatory role in certain type of cancers biology, including breast and lung cancers. However, the lncRNA expression in breast cancer combined with primary lung cancer remains unknown. In this study, databases of the Cancer Genome Atlas (TCGA) and the lncRNA profiler of contained candidate 192 lncRNAs were utilized. 11 lncRNAs were differentially expressed in breast cancer, 9 candidate lncRNAs were differentially expressed in lung ...[more]

PMID: 28938549

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Project description:BackgroundThe immune microenvironment is a critical regulator of clear cell renal cell carcinoma (ccRCC) progression. However, the underlying mechanisms the regulatory role of immune-related long non-coding RNAs (irlncRNAs) in the ccRCC tumor microenvironment (TME) are still obscure. Herein, we investigated prognostics role of irlncRNAs for ccRCC.MethodsThe raw data of patients with ccRCC were downloaded from The Cancer Genome Atlas (TCGA) database, and immune-related genes were obtained from the ImmPort database. First, we investigated the correlation between the immune-related genes and irlncRNAs. Then, we identified the differentially expressed irlncRNA pairs (ILRPs) between normal and cancer tissue samples, and prognostic model was constructed with the differentially expressed ILRPs. We further explored whether the signature risk scores of ILRPs had a considerable impact on immune cell infiltration. Finally, we performed a drug sensitivity analysis based on risk score.ResultsThere were 13 upregulated and 40 downregulated irlncRNAs between the ccRCC and normal tissue samples. We further selected the irlncRNAs that significantly affect the prognosis of patients with ccRCC via univariate Cox, lasso regression, and multivariate regression analyses. Twelve ILRPs were used to construct a prognostic signature. The model showed the ILRPs model could be used to assess the prognosis of ccRCC patients. Study of the influence of risk score and clinical characteristics on the prognosis of patients with ccRCC showed risk score to be an independent factor affecting the outcome of ccRCC. We further performed the difference analysis of immune cell abundance between ccRCC and normal tissue samples. The results showed that patients with higher abundance of M0 macrophages, plasma cells, follicular helper T cells, and regulatory T cells (Tregs) had a poor outcome. Finally, we performed a drug sensitivity analysis based on risk score. The results showed that high-risk score patients are sensitive to orafenib, sunitinib, temsirolimus, cisplatin, and gemcitabine.ConclusionsOur study has developed a novel and reasonable ILPRs model for prognostic prediction, which does not require transcriptional levels to be detected.

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Long non-coding RNAs may serve as biomarkers in breast cancer combined with primary lung cancer.

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Long non-coding RNAs may serve as biomarkers in breast cancer combined with primary lung cancer.

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