Background: Long non-coding RNA (lncRNA) zinc finger protein 667-antisense RNA 1 () is closely related to the advancement of a variety of cancers, but its functional role in colorectal cancer remains unclear. This study was designed to explore the function and molecular mechanisms of lncRNA in colorectal cancer.
Methods: Reverse transcriptase real-time quantitative polymerase chain reaction (RT-qPCR) was used for the detection of and proline-rich nuclear receptor co-activator protein 2 () expression level. Cell counting kit-8 (CCK-8), 5-Ethynyl-2'- deoxyuridine (EdU), and colony formation assays were conducted to assess cell proliferation; flow cytometry and transwell invasion assay were performed separately to measure cell apoptosis and invasion. RNA immunoprecipitation (RIP) assay was utilized to analyze the relationship between and . Western blot was to test the PNRC2 protein expression. The role of in the advancement of colorectal cancer was evaluated by tumor xenograft assay.
Results: LncRNA and were both decreased in colorectal cancer tissue samples and cells ( < 0.05). overexpression remarkably restrained proliferation and invasion in HCT-116 and LOVO cells, but enhanced cell apoptosis ( < 0.0001). Moreover, directly targeted , and positively regulated its expression. The influence of overexpression on invasion, apoptosis, and proliferation was suppressed by knockdown in HCT-116 and LOVO cells. Additionally, overexpression markedly inhibited tumor growth via upregulation of in mice ( < 0.05).
Conclusion: LncRNA expressed low in colorectal cancer. LncRNA repressed proliferation and invasion, and enhanced apoptosis of colorectal cancer cells by targeting .
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http://dx.doi.org/10.24976/Discov.Med.202537192.8 | DOI Listing |
BMC Cancer
January 2025
Department of Gastrointestinal Surgery I Section, Renmin Hospital of Wuhan University, Wuhan, 430060, China.
Background: Gastric cancer peritoneal metastasis lacks effective predictive indices. This article retrospectively explored predictive values of DNA ploidy, stroma, and nucleotyping in gastric cancer peritoneal metastasis.
Methods: A comprehensive analysis was conducted on specimens obtained from 80 gastric cancer patients who underwent gastric resection at the Department of Gastrointestinal Surgery of Wuhan University Renmin Hospital.
Nat Med
January 2025
Vall d'Hebron Hospital Campus and Vall d'Hebron Institute of Oncology (VHIO), University of Vic - Central University of Catalonia, Barcelona, Spain.
Encorafenib + cetuximab (EC) is approved for previously treated BRAF V600E-mutant metastatic colorectal cancer (mCRC) based on the BEACON phase 3 study. Historically, first-line treatment of BRAF V600E-mutant mCRC with chemotherapy regimens has had limited efficacy. The phase 3 BREAKWATER study investigated EC+mFOLFOX6 versus standard of care (SOC) in patients with previously untreated BRAF V600E mCRC.
View Article and Find Full Text PDFInt J Colorectal Dis
January 2025
Hereditary Digestive Tract Tumors Unit, Fondazione IRCCS Istituto Nazionale Dei Tumori, Via Giacomo Venezian 1, 20133, Milan, Italy.
Purpose: In this study, we investigated the progression of high-grade dysplasia (HGD)/CRC in patients with hereditary colorectal cancer syndromes (HCSS) and concomitant inflammatory bowel diseases (IBDs).
Methods: We described the natural history of a series of patients with confirmed diagnosis of hereditary colorectal cancer syndromes (HCCSs) and concomitant IBDs who were referred to the Hereditary Digestive Tumors Registry at the Fondazione IRCCS Istituto Nazionale dei Tumori of Milan.
Results: Between January 1989 and April 2024, among 450 patients with APC-associated polyposis and 1050 patients with Lynch syndrome (LS), we identified six patients with IBDs (five with UC, one with ileal penetrating CD) and concomitant HCCSs (five with LS, one with APC-associated polyposis).
Sci Rep
January 2025
Ministry of Higher Education, Mataria Technical College, Cairo, 11718, Egypt.
The current work introduces the hybrid ensemble framework for the detection and segmentation of colorectal cancer. This framework will incorporate both supervised classification and unsupervised clustering methods to present more understandable and accurate diagnostic results. The method entails several steps with CNN models: ADa-22 and AD-22, transformer networks, and an SVM classifier, all inbuilt.
View Article and Find Full Text PDFZhonghua Bing Li Xue Za Zhi
February 2025
Department of Pathology and Immunology, Washington University, St. Louis, MO 63110, U S A.
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