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TP53 mutations are associated with improved survival in ovarian carcinoma patients receiving first-line chemotherapy plus bevacizumab: results from the MITO16A/MaNGO OV-2 study

<p><strong>PURPOSE</strong> Bevacizumab (BEV) is considered an effective treatment option for advanced ovarian carcinoma. However, to date, there are no biomarkers that define a BEV-responsive patient subpopulation.</p> <p><strong>METHODS</strong> In the context of the MITO16A/MaNGO OV-2 trial, a phase IV study of chemotherapy combined with BEV in first-line treatment of advanced ovarian carcinoma, we evaluated <em>TP53</em> mutations by next generation sequencing (NGS) and p53 protein expression by immunohistochemistry (IHC) on 202 and 311 cases, respectively. We further correlated NGS and IHC data with clinicopathological characteristics and survival of patients.</p> <p><strong>RESULTS</strong> <em>TP53</em> mutations of unknown function (named unclassified), mostly of the missense type, represented the majority of variants in our population (44.4%) and were associated with a significantly improved overall survival both in univariate (p=0.03, HR=0.43) and multivariate analysis (p=0.012, HR=0.39). Concordance between <em>TP53 </em>mutational analysis and protein expression was 91%. A trend toward improved OS was observed in patients with p53 IHC overexpression (HR=0.70, p=0.15) compared to p53 wild-type patients.</p> <p><strong>CONCLUSION </strong>Our results indicate that the presence of unclassified <em>TP53</em> mutations has favorable prognostic significance in patients with ovarian carcinoma receiving upfront BEV plus chemotherapy. In particular, unclassified missense <em>TP53</em> mutations characterize a subpopulation of patients with a significant survival advantage, independently of clinicopathological characteristics. Our findings warrant future investigations to confirm the prognostic impact of <em>TP53 </em>mutations in BEV-treated ovarian carcinoma patients and deserve to be assessed for their potential predictive role in future randomized clinical studies.</p>

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12/100

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8
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4
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0
Reuse readiness
0
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0

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Dataset details

Repository
zenodo
Published
October 29, 2023
License
Not reported
DOI
10.5281/zenodo.8138608

Scored with release 0.9.0

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