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Identification and functional analysis of lncRNAs and mRNAs between tumorigenesis and metastasis in CRC.

ABSTRACT: The role of long non-coding RNAs (lncRNAs) in colorectal cancer (CRC) tumorigenesis and metastasis remains poorly characterized. The aim of this study was to identify novel lncRNAs and their functions in CRC progression. Through microarray analysis of paired normal colorectal mucosa (NM), primary tumor (PT), and metastatic lymph node (MLN) tissues, lncRNA and mRNA expression patterns were identified. Further bioinformatic analyses were performed to compare the biological functions of lncRNAs between tumorigenesis and metastasis of CRC, which was further verified by TCGA-COAD and GSE82236. The expression of lncRNA MIR29B2CHG93 in paired CRC tissues was detected in a cohort of CRC patients. The effects of lncRNA MIR29B2CHG93 on proliferation, migration, and invasion were determined by in vitro experiments. We found that tumorigenesis-associated lncRNAs predominantly participated in the regulation of the EMT/P53/PI3K-Akt/KRAS signaling pathway as well as the processes related to cell cycle and cell mitosis, while metastasis-associated lncRNAs mainly regulated blood vessel morphogenesis and immune-related biological processes. Compared to the TCGA and GSE datasets, seven tumorigenesis-associated lncRNAs and eight metastasis-associated lncRNAs were identified. LncRNA MIR29B2CHG93 knockdown remarkably suppressed tumor growth and metastasis in vitro, which acted as a tumor promoter in CRC. The lncRNA MIR29B2CHG93 was significantly upregulated in CRC tissues and was indicator of unfavorable clinical outcome in CRC. These results revealed novel lncRNAs that provide new insights for an in-depth understanding of CRC progression. In particular, this study identified a novel lncRNA MIR29B2CHG93 in CRC progression, which might be a potential biomarker for diagnosis, prognosis and metastasis-prediction in CRC.

SUBMITTER: Liu H

PROVIDER: S-EPMC8751602 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Osteosarcoma (OS) is the most common pediatric malignant bone tumor, and occurrence of pulmonary metastasis generally causes a rapid and fatal outcome. Here we aimed to provide clues for exploring the mechanism of tumorigenesis and pulmonary metastasis for OS by comprehensive analysis of microRNA (miRNA), long non-coding RNA (lncRNA), and mRNA expression in primary OS and OS pulmonary metastasis. In this study, deep sequencing with samples from primary OS (n?=?3), pulmonary metastatic OS (n?=?3), and normal controls (n?=?3) was conducted and differentially expressed miRNAs (DEmiRNAs), lncRNAs (DElncRNAs), and mRNAs (DEmRNAs) between primary OS and normal controls as well as pulmonary metastatic and primary OS were identified. A total of 65 DEmiRNAs, 233 DElncRNAs, and 1405 DEmRNAs were obtained between primary OS and normal controls; 48 DEmiRNAs, 50 DElncRNAs, and 307 DEmRNAs were obtained between pulmonary metastatic and primary OS. Then, the target DEmRNAs and DElncRNAs regulated by the same DEmiRNAs were searched and the OS tumorigenesis-related and OS pulmonary metastasis-related competing endogenous RNA (ceRNA) networks were constructed, respectively. Based on these ceRNA networks and Venn diagram analysis, we obtained 3 DEmiRNAs, 15 DElncRNAs, and 100 DEmRNAs, and eight target pairs including miR-223-5p/(CLSTN2, AC009951.1, LINC01705, AC090673.1), miR-378b/(ALX4, IGSF3, SULF1), and miR-323b-3p/TGFBR3 were involved in both tumorigenesis and pulmonary metastasis of OS. The TGF-? superfamily co-receptor TGFBR3, which is regulated by miR-323b-3p, acts as a tumor suppressor in OS tumorigenesis and acts as a tumor promoter in pulmonary metastatic OS via activation of the epithelial-mesenchymal transition (EMT) program.In conclusion, the OS transcriptome (miRNA, lncRNA, and mRNA) is dynamically regulated. These analyses might provide new clues to uncover the molecular mechanisms and signaling networks that contribute to OS progression, toward patient-tailored and novel-targeted treatments.

Project description:Messenger RNA (mRNA) and long noncoding RNA (lncRNA) are two main subgroups of RNAs participating in transcription regulation. With the development of next generation sequencing, increasing lncRNAs are identified. Many hidden functions of lncRNAs are also revealed. However, the differences in lncRNAs and mRNAs are still unclear. For example, we need to determine whether lncRNAs have stronger tissue specificity than mRNAs and which tissues have more lncRNAs expressed. To investigate such tissue expression difference between mRNAs and lncRNAs, we encoded 9339 lncRNAs and 14,294 mRNAs with 71 expression features, including 69 maximum expression features for 69 types of cells, one feature for the maximum expression in all cells, and one expression specificity feature that was measured as Chao-Shen-corrected Shannon's entropy. With advanced feature selection methods, such as maximum relevance minimum redundancy, incremental feature selection methods, and random forest algorithm, 13 features presented the dissimilarity of lncRNAs and mRNAs. The 11 cell subtype features indicated which cell types of the lncRNAs and mRNAs had the largest expression difference. Such cell subtypes may be the potential cell models for lncRNA identification and function investigation. The expression specificity feature suggested that the cell types to express mRNAs and lncRNAs were different. The maximum expression feature suggested that the maximum expression levels of mRNAs and lncRNAs were different. In addition, the rule learning algorithm, repeated incremental pruning to produce error reduction algorithm, was also employed to produce effective classification rules for classifying lncRNAs and mRNAs, which gave competitive results compared with random forest and could give a clearer picture of different expression patterns between lncRNAs and mRNAs. Results not only revealed the heterogeneous expression pattern of lncRNA and mRNA, but also gave rise to the development of a new tool to identify the potential biological functions of such RNA subgroups.

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Identification and functional analysis of lncRNAs and mRNAs between tumorigenesis and metastasis in CRC.

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