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Targeted sequencing of histologically defined serous endometrial cancer reflects prognosis and correlates with preoperative biopsy.

ABSTRACT: The aim of this study was to evaluate the impact of discordant endometrial sampling on the prognosis of patients finally diagnosed with uterine papillary serous carcinoma (UPSC) and to analyze UPSC mutational profile. Retrospective cohort study comparing outcomes of patients post-operatively diagnosed with UPSC and preoperatively diagnosed with endometrioid endometrial cancer (EEC) or UPSC. Genes commonly implicated in carcinogenesis were analyzed in a subgroup of 40 patients post-operatively diagnosed with UPSC, using next generation sequencing. 61 patients with UPSC on post-surgical, final pathology were included in the study. Prior to surgery, 15 were diagnosed with EEC (discordant) and 46 were correctly diagnosed with UPSC (concordant). After a median follow-up of 41.6 months [5.4-106.7], a preoperative diagnosis of EEC was associated with better 3-year progression-free survival (100% vs. 60.9%, P = 0.003) and longer disease free interval (63.5 versus 15 months, P = 0.026) compared to patients with an initial diagnosis of UPSC. Patients with a concordant diagnosis of UPSC were 5 times more likely to progress or die compared to those with a discordant EEC diagnosis (P = 0.02, P = 0.03, respectively), and their tumors were associated with higher rates of TP53 (88.9% vs. 61.5%, P = 0.04), and a lower rate of PTEN (14.8% vs. 38.5%, P = 0.09) and ARID1A (3.7% vs. 23.1%, P = 0.05) mutations. A pre-surgical diagnosis of EEC is associated with improved prognosis in patients with UPSC. Some histologically defined UPSC tumors contain endometrioid-like molecular characteristics that may confer a survival advantage, suggesting a possible need for molecular approaches to better stratify patients into risk groups.

SUBMITTER: Octeau D

PROVIDER: S-EPMC6906727 | biostudies-literature | 2019 Nov

REPOSITORIES: biostudies-literature

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Targeted sequencing of histologically defined serous endometrial cancer reflects prognosis and correlates with preoperative biopsy.

Octeau David D Abitbol Jeremie J Amajoud Zainab Z Laskov Ido I Ferenczy Alex A Pelmus Manuela M Eisenberg Neta N Kessous Roy R Matanes Emad E Lau Susie S Yasmeen Amber A Lopez-Ozuna Vanessa V Salvador Shannon S Gotlieb Walter H WH Kogan Liron L

Gynecologic oncology reports 20191127

The aim of this study was to evaluate the impact of discordant endometrial sampling on the prognosis of patients finally diagnosed with uterine papillary serous carcinoma (UPSC) and to analyze UPSC mutational profile. Retrospective cohort study comparing outcomes of patients post-operatively diagnosed with UPSC and preoperatively diagnosed with endometrioid endometrial cancer (EEC) or UPSC. Genes commonly implicated in carcinogenesis were analyzed in a subgroup of 40 patients post-operatively di ...[more]

PMID: 31867434

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Project description:ObjectiveThe aim of this study is to explore the consistency of P53 immunohistochemical expression between preoperative biopsy and final pathology in endometrial cancer (EC), and to predict the prognosis of patients based on the 4-tier P53 expression and classic clinicopathological parameters.MethodsThe medical data of patients with stage I-III EC who received preoperative biopsy and initial surgical treatment in two medical centers was retrospectively collected. The consistency of P53 immunohistochemistry expression between preoperative biopsy and final pathology was compared using Cohen's kappa coefficient and Sankey diagram, then 4-tier P53 expression was defined (P53wt/P53wt, P53abn/P53wt, P53wt/P53abn, and P53abn/P53abn). Univariate and multivariate Cox regression analysis was used to determine the correlation between 4-tier P53 expression and the prognosis of patients. On this basis, the nomogram models were established to predict the prognosis of patients by combining 4-layer P53 expression and classic clinicopathological parameters, then risk stratification was performed on patients.ResultsA total of 1186 patients were ultimately included in this study through inclusion and exclusion criteria. Overall, the consistency of P53 expression between preoperative biopsy and final pathology was 83.8%, with a kappa coefficient of 0.624. ROC curve suggested that the AUC of 4-tier P53 expression to predict the prognosis of patients was better than AUC of P53 expression in preoperative biopsy or final pathology alone. Univariate and multivariate Cox regression analysis suggested that 4-tier P53 expression was an independent influencing factor for recurrence and death. On this basis, the nomogram models based on 4-tier P53 expression and classical clinicopathological factors were successfully established. ROC curve suggested that the AUC (AUC for recurrence and death was 0.856 and 0.838, respectively) of the models was superior to the single 4-tier P53 expression or the single classical clinicopathological parameters, which could provide a better risk stratification for patients.ConclusionThe expression of P53 immunohistochemistry had relatively good consistency between preoperative biopsy and final pathology of EC. Due to the discrepancy of P53 immunohistochemistry between preoperative biopsy and final pathology, the prognosis of patients can be better evaluated based on the 4-layer P53 expression and classic clinical pathological parameters.

Project description:BackgroundThe risk of prostate cancer metastatic is correlated with its volume and grade. These parameters are now best estimated preoperatively with magnetic resonance imaging (MRI) and MRI-guided biopsy.ObjectiveTo estimate the risk of metastatic recurrence after radical prostatectomy (RP) in our model versus conventional clinical European Association of Urology (EAU) classification. The secondary objective is biochemical recurrence (BCR).Design setting and participantsA retrospective study was conducted of a cohort of 713 patients having undergone MRI-guided biopsies and RP between 2009 and 2018. The preoperative variables included prostate-specific antigen, cT stage, tumor volume (TV) based on the lesion's largest diameter at MRI, percentage of Gleason pattern 4/5 (%GP4/5) at MRI-guided biopsy, and volume of GP4/5 (VolGP4/5) calculated as TV × %GP4/5.Outcome measurements and statistical analysisThe variables' ability to predict recurrence was determined in univariable and multivariable Fine-and-Gray models, according to the Akaike information criterion (AIC) and Harrell's C-index.Results and limitationsOverall, 176 (25%), 430 (60%), and 107 (15%) patients had low, intermediate, and high-risk disease, respectively, according to the EAU classification. During a median follow-up period of 57 mo, metastatic recurrence was observed in 48 patients with a 5-yr probability of 5.6% (95% confidence interval [CI] 3.9-7.7). VolGP4/5 (categories: <0.5, 0.5-1.0, 1.01-3.2, and >3.2 ml) was the parameter with the lowest AIC and the highest C-index for metastatic recurrence of 0.82 (95% CI 0.76-0.88), and for BCR it was 0.73 (95% CI 0.68-0.78). In a multivariable model that included %GP4/5 and TV, C-index values were 0.86 (95% CI 0.79-0.91) for metastatic recurrence and 0.77 (0.72-0.82) for BCR. The same results for EAU classification were 0.74 (0.67-0.80) and 0.67 (0.63-0.72), respectively. Limitations are related to short follow-up and expertise of radiologists and urologists.ConclusionsWe developed a preoperative risk tool integrating the VolGP4/5 based on MRI and MRI-guided biopsies to predict metastatic recurrence after RP. Our model showed higher accuracy than conventional clinical risk models. These findings might enable physicians to provide more personalized patient care.Patient summaryAggressiveness of prostate cancer evaluated before treatment by incorporating magnetic resonance imaging (MRI) and MRI-guided biopsy results gives a better estimate of the risk of metastatic recurrence than previous parameters not based on MRI.

Project description:Background:Glioblastoma represents an archetypal example of a heterogeneous malignancy. To understand the diverse molecular consequences of this complex tumor ecology, we analyzed RNA-seq data generated from commonly identified intratumoral structures in glioblastoma enriched using laser capture microdissection. Methods:Raw gene-level values of fragments per kilobase of transcript per million reads mapped and the associated clinical data were acquired from the publicly available Ivy Glioblastoma Atlas Project database and analyzed using MetaboAnalyst (v3.0). The database includes gene expression data generated from multiple structural features commonly identified in glioblastoma enriched by laser capture microdissection. Results:We uncovered a relationship between subtype heterogeneity in glioblastoma and its unique tumor microenvironment, with infiltrating cells harboring a proneural signature while the mesenchymal subtype was enriched in perinecrotic regions. When evaluating the tumors' transcriptional profiles in the context of their derived structural regions, there was a relatively small amount of intertumoral heterogeneity in glioblastoma, with individual regions from different tumors clustering tightly together. Analyzing the transcriptional profiles in the context of evolutionary progression identified unique cellular programs associated with specific phases of gliomagenesis. Mediators of cell signaling and cell cycle progression appear to be critical events driving proliferation in the tumor core, while in addition to a multiplex strategy for promoting angiogenesis and/or an immune-tolerant environment, transformation to perinecrotic zones involved global metabolic alterations. Conclusion:These findings suggest that intratumoral heterogeneity in glioblastoma is a conserved, predictable consequence to its complex microenvironment, and combinatorial approaches designed to target these unequivocally present tumor biomes may lead to therapeutic gains.

Dataset Information

Targeted sequencing of histologically defined serous endometrial cancer reflects prognosis and correlates with preoperative biopsy.

Publications

Targeted sequencing of histologically defined serous endometrial cancer reflects prognosis and correlates with preoperative biopsy.

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