Snail Driving Alternative Splicing of CD44 by ESRP1 Enhances Invasion and Migration in Epithelial Ovarian Cancer

et al. 2020

Cancer Medicine

Previous studies have demonstrated the role of abnormal alternative splicing (AS) in tumor progression. This study examines the prognostic index (PI) of alternative splices (ASs) in patients with hepatocellular carcinoma (HCC). The clinical features and splicing events of patients with HCC were downloaded from The Cancer Genome Atlas (TCGA). Differentially expressed AS (DEAS) were compared between HCC and adjacent normal samples. Univariate Cox regression analysis was used to determine changes in DEAS associated with overall survival (OS). A PI was generated from OS‐associated DEASs using Kaplan‐Meier curves, receiver operating characteristic (ROC) curves, multivariate Cox regression, and cluster analysis. Then, the correlation between DEASs and splicing factors was assessed, followed by functional and pathway enrichment analysis. We identified 34 163 ASs of 8985 genes in HCC, and 153 OS‐ASs were identified using univariate Cox regression analysis. Low‐ and high‐PI groups were determined based on the median “PI‐ALL” value according to significantly different survival (P = 2.2e − 16). The ROC curve of all PI (PI‐ALL) had an area under the curve (AUC) of 0.993 for survival status in patients with HCC. A potential regulatory network associated with prognosis of patients with HCC was established. Enrichment analysis also resulted in the identification of several pathways potentially associated with carcinogenesis and progression of HCC. Four clusters were identified that were associated with clinical features and prognosis. Our study generated comprehensive profiles of ASs in HCC. The interaction network and functional connections were used to elucidate the underlying mechanisms of AS in HCC.

Section: Discussionmentioning

confidence: 79%

“…28 Splicing factors have the potential to become oncogenes or pseudo-oncogenes, which can promote carcinogenesis. 29,30 In our study, we identified 12 splicing factors that were abnormally expressed in HCC. Previous studies identified splicing factors associated with HCC, such as PFS, 31 FMRP, 32 YB-1, 33,34 hnRNPH1, 35 and SRp20.…”

Section: Discussionmentioning

confidence: 98%

Profiles of prognostic alternative splicing signature in hepatocellular carcinoma

Chen

et al. 2020

Cancer Medicine

“…47 Chen et al found that CD44 splicing was associated with invasion and migration in ovarian cancer. 48 The splicing variants of TP53, FAS, CASP9, and BCL2L1 have been associated with cancer cell apoptosis and survival. 18, 49 Calabretta's study showed that modulating the pyruvate kinase gene (PKM) splicing could promote gemcitabine resistance in pancreatic cancer cells.…”

Section: Discussionmentioning

confidence: 99%

Role of alternative splicing signatures in the prognosis of glioblastoma

Xie

Dang

et al. 2019

Cancer Medicine

Background Increasing evidence has validated the crucial role of alternative splicing (AS) in tumors. However, comprehensive investigations on the entirety of AS and their clinical value in glioblastoma (GBM) are lacking. Methods The AS profiles and clinical survival data related to GBM were obtained from The Cancer Genome Atlas database. Univariate and multivariate Cox regression analyses were performed to identify survival‐associated AS events. A risk score was calculated, and prognostic signatures were constructed using seven different types of independent prognostic AS events, respectively. The Kaplan‐Meier estimator was used to display the survival of GBM patients. The receiver operating characteristic curve was applied to compare the predictive efficacy of each prognostic signature. Enrichment analysis and protein interactive networks were conducted using the gene symbols of the AS events to investigate important processes in GBM. A splicing network between splicing factors and AS events was constructed to display the potential regulatory mechanism in GBM. Results A total of 2355 survival‐associated AS events were identified. The splicing prognostic model revealed that patients in the high‐risk group have worse survival rates than those in the low‐risk group. The predictive efficacy of each prognostic model showed satisfactory performance; among these, the Alternate Terminator (AT) model showed the best performance at an area under the curve (AUC) of 0.906. Enrichment analysis uncovered that autophagy was the most enriched process of prognostic AS gene symbols in GBM. The protein network revealed that UBC, VHL, KCTD7, FBXL19, RNF7, and UBE2N were the core genes in GBM. The splicing network showed complex regulatory correlations, among which ELAVL2 and SYNE1_AT_78181 were the most correlated (r = −.506). Conclusions Applying the prognostic signatures constructed by independent AS events shows promise for predicting the survival of GBM patients. A splicing regulatory network might be the potential splicing mechanism in GBM.

“…It has been demonstrated that CD44 is a multi-structural cell surface receptor that binds HA with a particularly high affinity [7, 47, 48]. A study focused on ovarian cancer showed that peritoneal metastasis may be triggered when CD44 on the ovarian cancer cells surface binds to HA on mesothelial cells [49].…”

Section: Discussionmentioning

confidence: 99%

CRISPR-Cas9-Mediated Silencing of CD44 in Human Highly Metastatic Osteosarcoma Cells

Yan²,

et al. 2018

Cell Physiol Biochem

Background/Aims: Metastasis is the major cause of death in patients with osteosarcoma. There is an urgent need to identify molecular markers that promote metastasis. Cluster of differentiation 44 is a receptor for hyaluronic acid (HA) and HA-binding has been proven to participate in various biological tumor activities, including tumor progression and metastasis. Methods: We performed a meta-analysis to investigate the relationship between CD44 expression, survival, and metastasis in patients with osteosarcoma. We then utilized the CRISPR-Cas9 system to specifically silence CD44 in highly metastatic human osteosarcoma cells (MNNG/HOS and 143B) and further determined the functional effects of CD44 knockout in these cells. Results: The meta-analysis demonstrated that a high level of CD44 may predict poor survival and higher potential of metastasis in patients with osteosarcoma. The expression of CD44 in highly metastatic human osteosarcoma cell lines was efficiently blocked by CRISPR-Cas9. When CD44 was silenced, the proliferation and spheroid formation of these osteosarcoma cells was inhibited under 3-D culture conditions. Furthermore, the migratory and invasive functions were also impaired in these highly metastatic osteosarcoma cells. Conclusion: These results suggest that developing new strategies to target CD44 in osteosarcoma may prevent metastasis and improve the clinical outcome of osteosarcoma patients.