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Microsatellite instability as prognostic marker in bladder tumors: a clinical significance.

ABSTRACT: BACKGROUND: Carcinoma of urinary bladder is one of the leading causes of death in India. Successful treatment of bladder cancer depends on the early detection & specific diagnostic approaches. In the present study, microsatellite instability (MSI) has been evaluated as a prognostic marker in patients with superficial urinary bladder cancer in lower urinary tract for determining risk of recurrence. METHODS: A total of 44 patients with bladder tumors diagnosed with Transitional Cell Carcinomas [TCC] from lower urinary tract were selected for the study. Tumors were staged and graded according to AJCC-UICC (1997) classification and patients were followed with cystoscopy as per the protocol. Polymerase chain reaction (PCR) was done to amplify microsatellite sequences at mononucleotide BAT - 26, BAT - 40, TGFbeta RII, IGFIIR, hMSH3, BAX and dinucleotide D2S123, D9S283, D9S1851 and D18S58 loci in blood (control) and tumor DNA. PCR products were separated on 8% denaturing polyacrylamide gel and visualized by autoradiography. RESULTS: MSI was observed in 72.7% of tumors at BAT - 26, BAT - 40, D2S123, D9S283, D9S1851 and D18S58 loci. Good association of MSI was seen with tumor stage and grade. MSI - High (instability at > 30% of loci) was frequently observed in high stage (40.6%) and high grade (59.4%) tumors. Of 24 tumors of Ta-T1 stage with different grades, 11 (9/18 high grade and 2/6 low grade tumors) recurred in the mean duration of 36 months. MSI positivity was significantly high in patients who had one or more recurrences (p = 0.02 for high grade and 0.04 for low grade tumors). CONCLUSIONS: MSI may be an independent prognostic marker for assessing risk of recurrence in superficial tumors irrespective of the grade. Further studies on progression would help in stratifying the patients of T1G3 for early cystectomy vs bladder preservation protocol.

SUBMITTER: Vaish M

PROVIDER: S-EPMC545959 | biostudies-literature | 2005

REPOSITORIES: biostudies-literature

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Microsatellite instability as prognostic marker in bladder tumors: a clinical significance.

Vaish Minal M Mandhani Anil A Mittal R D RD Mittal Balraj B

BMC urology 20050112

<h4>Background</h4>Carcinoma of urinary bladder is one of the leading causes of death in India. Successful treatment of bladder cancer depends on the early detection & specific diagnostic approaches. In the present study, microsatellite instability (MSI) has been evaluated as a prognostic marker in patients with superficial urinary bladder cancer in lower urinary tract for determining risk of recurrence.<h4>Methods</h4>A total of 44 patients with bladder tumors diagnosed with Transitional Cell C ...[more]

PMID: 15647110

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Project description:Background & aimsMicrosatellite instability (MSI) and mismatch-repair deficiency (dMMR) in colorectal tumors are used to select treatment for patients. Deep learning can detect MSI and dMMR in tumor samples on routine histology slides faster and less expensively than molecular assays. However, clinical application of this technology requires high performance and multisite validation, which have not yet been performed.MethodsWe collected H&E-stained slides and findings from molecular analyses for MSI and dMMR from 8836 colorectal tumors (of all stages) included in the MSIDETECT consortium study, from Germany, the Netherlands, the United Kingdom, and the United States. Specimens with dMMR were identified by immunohistochemistry analyses of tissue microarrays for loss of MLH1, MSH2, MSH6, and/or PMS2. Specimens with MSI were identified by genetic analyses. We trained a deep-learning detector to identify samples with MSI from these slides; performance was assessed by cross-validation (N = 6406 specimens) and validated in an external cohort (n = 771 specimens). Prespecified endpoints were area under the receiver operating characteristic (AUROC) curve and area under the precision-recall curve (AUPRC).ResultsThe deep-learning detector identified specimens with dMMR or MSI with a mean AUROC curve of 0.92 (lower bound, 0.91; upper bound, 0.93) and an AUPRC of 0.63 (range, 0.59-0.65), or 67% specificity and 95% sensitivity, in the cross-validation development cohort. In the validation cohort, the classifier identified samples with dMMR with an AUROC of 0.95 (range, 0.92-0.96) without image preprocessing and an AUROC of 0.96 (range, 0.93-0.98) after color normalization.ConclusionsWe developed a deep-learning system that detects colorectal cancer specimens with dMMR or MSI using H&E-stained slides; it detected tissues with dMMR with an AUROC of 0.96 in a large, international validation cohort. This system might be used for high-throughput, low-cost evaluation of colorectal tissue specimens.

Dataset Information

Microsatellite instability as prognostic marker in bladder tumors: a clinical significance.

Publications

Microsatellite instability as prognostic marker in bladder tumors: a clinical significance.

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