STAG2 Is a Biomarker for Prediction of Recurrence and Progression in Papillary Non–Muscle-Invasive Bladder Cancer

Lelo, Alana; Prip, Frederik; Harris, Brent T.; Solomon, David A.; Berry, Deborah L.; Chaldekas, Krysta; Kumar, Anagha; Simko, Jeffry P.; Jensen, Jørgen Bjerggaard; Bhattacharyya, Pritish K.; Mannion, Ciaran; Kim, Jung-Sik; Philips, George; Dyrskjøt, Lars; Waldman, Todd

doi:10.1158/1078-0432.ccr-17-3244

Cited by 26 publications

(26 citation statements)

References 31 publications

(63 reference statements)

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“…The Exp(B) value STAG2 was 0.337, indicating that mutations in STAG2 may significantly decrease the probability of bladder cancer recurrence. This is consistent with previous reports that loss of STAG2 expression often indicates good prognosis in patients with bladder cancer, and STAG2 can also be used as a biomarker for prediction of recurrence and progression in papillary nonmuscle invasive bladder cancer . The revelation of significance of these two genes in the regression analysis indicates that our workflow was efficient in detecting genes associated with bladder cancer recurrence.…”

Section: Resultssupporting

confidence: 91%

“…We identified nine potential driver genes ( STAG2 , EME1 , AKAP9 , DST , ZNF91 , PARD3 , ZFP36L2 , METTL3 , and POLR3B ) whose mutations were negatively associated with bladder cancer recurrence ( P < 0.05, Table and Supporting Information Supplemental Table ). Among these nine genes, STAG2 was one of the most commonly mutated genes in bladder cancer and a potential predictor of recurrence for bladder cancer . STAG2 protein is a component of the cohesin complex, and predominantly functions in sister chromatid cohesion and segregation, DNA repair and gene expression .…”

Section: Discussionmentioning

confidence: 99%

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Identification of a nine‐gene panel as a prognostic indicator for recurrence with muscle‐invasive bladder cancer

Han

Zheng

Tian

et al. 2019

Journal of Surgical Oncology

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Background and Objectives Bladder cancer is one of the most common and highly recurrent cancers worldwide. Recurrence‐associated genes may potentially predict cancer recurrence. We aimed to construct a recurrence‐associated gene panel to improve the prognostic prediction of bladder cancer. Methods Based on DNA sequencing and clinical data from the TCGA‐BLCA project, we identified 10 potential driver genes significantly associated with recurrence of bladder cancer. We performed multivariable logistic regression analysis to construct an optimized recurrence prediction model with nine recurrence‐associated genes (EME1, AKAP9, ZNF91, PARD3, STAG2, ZFP36L2, METTL3, POLR3B, and MUC7) and clinical information as the independent variables. Results The area under the receiver operating characteristic (ROC) curve was 0.80 in this model, much higher than that of the baseline model (AUC = 0.73) and the same trend was also validated in its subset. Decision curve analysis also revealed that there is a significant net benefit gained by adding nine genes mutation to the baseline model. Furthermore, Kaplan‐Meier survival analysis showed that eight out of the nine genes (excluding MUC7) had good effects on the overall prognosis of patients. Conclusions This nine‐gene panel will most likely be a useful tool for prognostic evaluation and will facilitate the personalized management of patients with bladder cancer.

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Section: Resultssupporting

confidence: 91%

Section: Discussionmentioning

confidence: 99%

Identification of a nine‐gene panel as a prognostic indicator for recurrence with muscle‐invasive bladder cancer

Han

Zheng

Tian

et al. 2019

Journal of Surgical Oncology

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“…Recent studies indicate that STAG2 mutation is strongly associated with prognosis. [17][18][19] However, some studies have reached the opposite conclusion. In the current study, high expression of STAG2 was closely related to recurrence and poor prognosis in NMIBC patients.…”

Section: Discussionmentioning

confidence: 99%

STAG2 Coupled With p53 Alteration Has a Significant Impact on Bladder Cancer Recurrence and Progression

Chen

Xu²,

Meng

et al. 2019

Preprint

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Background:There is an unmet need for additional biomarkers for stratifying tumors based on their risk of recurrence and progression. Stromal antigen 2 (STAG2) and p53 are the most common mutations in bladder cancer and their association with the prognosis of bladder cancer remains unclear.Methods:Patients were divided into two cohorts according to stage and surgical procedure. The value of combined STAG2 expression (+/-) and P53 mutation (+/-) was evaluated for prediction of recurrence in 334 patients diagnosed by transurethral resection of bladder tumor (TURBT) and for prediction of survival in 144 patients who underwent radical cystectomy and pelvic lymphadenectomy( RCPLT).Results:We found that,in the 334 TURBT-treated patients, recurrence rate was significantly greater for STAG2(+) tumors than STAG2(-) tumors (73.5% vs. 55.0%, P=0.001). Of 144 RCPLT-treated patients, 127 (88.2%) were STAG2(+), of which 71 (55.9%) survived 5 years, compared to none of the 17 STAG2(-) patients. Patients with combined STAG2(+)/P53 mutation(+) tumors had the highest recurrence rate (83.5%) while patients with STAG2(-)/P53(-) tumors had the lowest recurrence rate (50%). Patients with STAG2(+)/P53(-) tumors achieved the highest 5-year survival rate (69.7%). Systemic chemotherapy did not improve prognosis of RCPLT-treated patients, but appeared to benefit STAG2(-) patients.Conclusions: Our results suggest that combined STAG2 expression and P53 status is a valuable biomarker for BCa prognosis, accurately predicting recurrence in TURBT-treated patients. STAG2(+)/P53(-) predicted a higher five-year survival and STAG2(-) predicted low five-year survival in RCPLT-treated patients. Chemotherapy may interfere with this predictive efficacy, especially in STAG2(-) patients.

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“…Several novel multi-gene-based signatures and single biomarkers for prediction of progression of NMIBC to MIBC have been reported in recent years and comparison of the 13-mRNA signature with them was conducted in our study (14)(15)(16)(17)(18). The ROC curves indicated that the performance of the 13-mRNA signature was similar to that of the 12-gene progression score model, and superior to that of the 5-gene model and three other single-gene biomarkers in two GEO datasets.…”

Section: Discussionmentioning

confidence: 99%

Identification of a 13‑mRNA signature for predicting disease progression and prognosis in patients with bladder cancer

et al. 2019

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There are no reliable criteria to assess risk of progression of non-muscle invasive bladder cancer to muscle invasive bladder cancer. The aim of the present study was to identify potential markers based on gene expression profiling to improve predictive power of disease progression and prognosis in patients with bladder cancer. In the present study, we screened seventy-three differentially expressed genes by analyzing bladder cancer samples with or without progression. Forty-seven prognosis-related genes were screened, 13 of which were identified to build a progression-associated gene signature using the LASSO regression method. Based on this 13-mRNA signature, patients were divided into high-and low-risk groups, with different prognostic outcomes. The gene signature was an independent prognostic factor for overall survival. Receiver operating characteristic analysis suggested that the signature performed well in the validation cohort and its predictive power outperformed other several published signatures. CTHRC1, MMP11, AEBP1, SNCAIP, COL1A1 and S100A8 were identified as hub genes and their expression levels were detected using reverse transcriptase-quantitative polymerase chain reaction. The expression of CTHRC1 was elevated in aggressive bladder cancer compared with non-invasive type, which suggests CTHRC1 may be a valuable biomarker for prediction of prognosis and progression of bladder cancer. Collectively, this 13-mRNA signature may be useful in predicting disease progression and prognosis, thereby contributing to individualized management of patients with bladder cancer.

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STAG2 Is a Biomarker for Prediction of Recurrence and Progression in Papillary Non–Muscle-Invasive Bladder Cancer

Cited by 26 publications

References 31 publications

Identification of a nine‐gene panel as a prognostic indicator for recurrence with muscle‐invasive bladder cancer

Identification of a nine‐gene panel as a prognostic indicator for recurrence with muscle‐invasive bladder cancer

STAG2 Coupled With p53 Alteration Has a Significant Impact on Bladder Cancer Recurrence and Progression

Identification of a 13‑mRNA signature for predicting disease progression and prognosis in patients with bladder cancer

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