CSAG1 Maintains the Integrity of the Mitotic Centrosome in Cells with Defective P53

Sapkota, Hem; Wren, Jonathan D.; Gorbsky, Gary J.

doi:10.1101/778522

Cited by 3 publications

(3 citation statements)

References 39 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Thus, genes in the MAGE-CSAG Xq28 gene cluster are functionally linked, similar to bacterial operons. Consistent with this idea, CSAG1 has been suggested to promote mitotic progression specifically in p53 defective tumor cells (Sapkota et al, 2020). Thus, CSAG1 may function to ensure proper cell division upon CSAG2 downregulation of p53.…”

Section: Of 16mentioning

confidence: 73%

See 1 more Smart Citation

CSAG2 is a cancer‐specific activator of SIRT1

Potts

2020

EMBO Reports

View full text Add to dashboard Cite

SIRT1 is a NAD+‐dependent deacetylase that controls key metabolic and signaling pathways, including inactivating the p53 tumor suppressor. However, the mechanisms controlling SIRT1 enzymatic activity in the context of cancer are unclear. Here, we show that the previously undescribed CSAG2 protein is a direct activator of SIRT1. CSAG2 is normally restricted to expression in the male germline but is frequently re‐activated in cancers. CSAG2 is necessary for cancer cell proliferation and promotes tumorigenesis in vivo. Biochemical studies revealed that CSAG2 directly binds to and stimulates SIRT1 activity toward multiple substrates. Importantly, CSAG2 enhances SIRT1‐mediated deacetylation of p53, inhibits p53 transcriptional activity, and improves cell survival in response to genotoxic stress. Mechanistically, CSAG2 binds SIRT1 catalytic domain and promotes activity independent of altering substrate affinity. Together, our results identify a previously undescribed mechanism for SIRT1 activation in cancer cells and highlight unanticipated approaches to therapeutically modulate SIRT1.

show abstract

Section: Of 16mentioning

confidence: 73%

“…CSAG2 is necessary and sufficient to drive cell and tumor growth CSAG1 has previously been suggested to play a role in mitotic progression (Sapkota et al, 2020). Therefore, we focused our study on CSAG2 that has not been previously characterized.…”

Section: Csag Genes Are Aberrantly Expressed In Cancer and Correlate mentioning

confidence: 99%

CSAG2 is a cancer‐specific activator of SIRT1

Potts

2020

EMBO Reports

View full text Add to dashboard Cite

show abstract

“…High expression of ADPGK has been found to be associated with a favorable prognosis in hepatocellular carcinoma 93 . CSAG1 (Putative chondrosarcoma-associated gene 1 protein) plays an important role in maintaining centrosome integrity during mitosis 94 . The downregulation of CSAG1 signi cantly increased multipolarity in cancer stem cells 95 .…”

Section: Discussionmentioning

confidence: 99%

Identification of novel protein biomarkers and drug targets for colorectal cancer by integrating human plasma proteome with genome

Sun

Zhao

Jiang

et al. 2022

Preprint

View full text Add to dashboard Cite

Background:Proteome is a major source of therapeutic targets. We conducted a proteome-wide Mendelian randomization (MR) study to identify candidate protein markers and therapeutic targets for colorectal cancer (CRC). Methods: Protein quantitative trait loci (pQTL) were derived from seven published genome-wide association studies (GWAS) on plasma proteosome, and summary-level data were extracted for 4,853 circulating protein markers. Genetic associations with CRC were obtained from a large-scaled GWAS meta-analysis (16,871 cases and 26,328 controls), the FinnGen cohort (4,957 cases and 304,197 controls) and the UK Biobank (9,276 cases and 477,069 controls). Colocalization and summary-data-based MR (SMR) analyses were performed sequentially to verify the causal role of candidate proteins. Single cell-type expression analysis, protein-protein interaction (PPI), and druggability evaluation were further conducted to detect the specific cell type with enrichment expression and prioritize potential therapeutic targets. Results: Collectively, genetically predicted levels of 13 proteins were associated with CRC risk. Elevated levels of two proteins (GREM1, CHRDL2) and decreased levels of 11 proteins were associated with an increased risk of CRC, among which six (CLSTN3, POLR2F, ADPGK, CSAG1, STXBP6, FUT3) were novel protein markers. These protein-coding genes mainly expressed in tissue stem cells, epithelial cells, and monocytes in colon tumor tissue. Two interactive pairs of proteins (GREM1 and CHRDL2; MMP2 and TIMP2) were identified to be involved in osteoclast differentiation and tumorigenesis pathways; four proteins (POLR2F, CSF2RA, CD86, MMP2) have been targeted for drug development on autoimmune diseases and other cancers, with the potentials of being repurposed as therapeutic targets for CRC. Conclusion: This study identified several protein biomarkers to be associated with CRC risk and provided new insights into the etiology and promising targets for the development of screening biomarkers and therapeutic drugs for CRC.

show abstract

A novel nine-microRNA-based model to improve prognosis prediction of renal cell carcinoma

Zeng²,

Fan

et al. 2022

BMC Cancer

View full text Add to dashboard Cite

Background With the improved knowledge of disease biology and the introduction of immune checkpoints, there has been significant progress in treating renal cell carcinoma (RCC) patients. Individual treatment will differ according to risk stratification. As the clinical course varies in RCC, it has developed different predictive models for assessing patient’s individual risk. However, among other prognostic scores, no transparent preference model was given. MicroRNA as a putative marker shown to have prognostic relevance in RCC, molecular analysis may provide an innovative benefit in the prophetic prediction and individual risk assessment. Therefore, this study aimed to establish a prognostic-related microRNA risk score model of RCC and further explore the relationship between the model and the immune microenvironment, immune infiltration, and immune checkpoints. This practical model has the potential to guide individualized surveillance protocols, patient counseling, and individualized treatment decision for RCC patients and facilitate to find more immunotherapy targets. Methods Downloaded data of RCC from the TCGA database for difference analysis and divided it into a training set and validation set. Then the prognostic genes were screened out by Cox and Lasso regression analysis. Multivariate Cox regression analysis was used to establish a predictive model that divided patients into high-risk and low-risk groups. The ENCORI online website and the results of the RCC difference analysis were used to search for hub genes of miRNA. Estimate package and TIMER database were used to evaluate the relationship between risk score and tumor immune microenvironment (TME) and immune infiltration. Based on Kaplan-Meier survival analysis, search for immune checkpoints related to the prognosis of RCC. Results There were nine miRNAs in the established model, with a concordance index of 0.702 and an area under the ROC curve of 0.701. Nine miRNAs were strongly correlated with the prognosis (P < 0.01), and those with high expression levels had a poor prognosis. We found a common target gene PDGFRA of hsa-miR-6718, hsa-miR-1269b and hsa-miR-374c, and five genes related to ICGs (KIR2DL3, TNFRSF4, LAG3, CD70 and TNFRSF9). The immune/stromal score, immune infiltration, and immune checkpoint genes of RCC were closely related to its prognosis and were positively associated with a risk score. Conclusions The established nine-miRNAs prognostic model has the potential to facilitate prognostic prediction. Moreover, this model was closely related to the immune microenvironment, immune infiltration, and immune checkpoint genes of RCC.

show abstract

CSAG1 Maintains the Integrity of the Mitotic Centrosome in Cells with Defective P53

Cited by 3 publications

References 39 publications

CSAG2 is a cancer‐specific activator of SIRT1

CSAG2 is a cancer‐specific activator of SIRT1

Identification of novel protein biomarkers and drug targets for colorectal cancer by integrating human plasma proteome with genome

A novel nine-microRNA-based model to improve prognosis prediction of renal cell carcinoma

Contact Info

Product

Resources

About