Iveta Selingerová

Anterior gradient 2 and mucin 4 expression mirrors tumor cell differentiation in pancreatic adenocarcinomas, but aberrant anterior gradient 2 expression predicts worse patient outcome in poorly differentiated tumors.

Objectives This study aimed to determine anterior gradient 2 (AGR2) expression in biopsies from pancreatic ductal adenocarcinomas (PDACs) and to evaluate AGR2 as a potential independent prognostic factor. Methods Tissue sample sections from a cohort of 135 consecutive surgically resectable PDACs were subjected to semiquantitative immunohistochemical analysis of AGR2 and mucin 4 (MUC4) expression. Results Anterior gradient 2 was over-expressed in PDAC compared with normal ductal cells. Since tumor lesions of PDAC are heterogeneous and constitute structures with various differentiation states, expression of both AGR2 and MUC4 was evaluated in each separate component. Expression levels of both proteins reflected the degree of tumor differentiation. Generally, well differentiated regions of tumor lesions expressed high levels of both proteins, moderately differentiated regions showed less AGR2 and MUC4, and poorly differentiated structures showed only weak positivity or were entirely negative. Of particular interest were occasional cases of strong AGR2 expression in high-grade tumors, where elevated protein levels were associated with shorter patient survival. Conclusions Anterior gradient 2 and MUC4 reflect the level of differentiation of PDACs. However, in less differentiated tumors, aberrantly elevated AGR2 expression predicts poor patient outcome.

A Simple Model to Assess the Probability of Invasion in Ductal Carcinoma In Situ of the Breast Diagnosed by Needle Biopsy

Objectives. The aim of the study was to develop a clinical prediction model for assessing the probability of having invasive cancer in the definitive surgical resection specimen in patients with biopsy diagnosis of ductal carcinoma in situ (DCIS) of the breast, to facilitate decision making regarding axillary surgery. Methods. In 349 women with DCIS, predictors of invasion in the definitive resection specimen were identified. A model to predict the probability of invasion was developed and subsequently simplified to divide patients into two risk categories. The models performance was validated on another patient population. Results. Multivariate logistic regression revealed four independent predictors of invasion: (i) suspicious (micro)invasion in the biopsy specimen; (ii) visibility of the lesion on ultrasonography; (iii) size of the lesion on mammography >30 mm; (iv) clinical palpability of the lesion. The actual frequency of invasion in the high-risk patient group in the test and validation population was 52.6% and 48.3%, respectively; in the low-risk group it was 16.8% and 7.1%, respectively. Conclusion. The model proved to have good performance. In patients with a low probability of invasion, an axillary procedure can be omitted without a substantial risk of additional surgery.

Survival of Patients with Primary Brain Tumors: Comparison of Two Statistical Approaches

Purpose We reviewed the survival time for patients with primary brain tumors undergoing treatment with stereotactic radiation methods at the Masaryk Memorial Cancer Institute Brno. We also identified risk factors and characteristics, and described their influence on survival time. Methods In summarizing survival data, there are two functions of principal interest, namely, the survival function and the hazard function. In practice, both of them can depend on some characteristics. We focused on nonparametric methods, propose a method based on kernel smoothing, and compared our estimates with the results of the Cox regression model. The hazard function is conditional to age and gross tumor volume and visualized as a color-coded surface. A multivariate Cox model was also designed. Results There were 88 patients with primary brain cancer, treated with stereotactic radiation. The median survival of our patient cohort was 47.8 months. The estimate of the hazard function has two peaks (about 10 months and about 40 months). The survival time of patients was significantly different for various diagnoses (p≪0.001), KI (p = 0.047) and stereotactic methods (p = 0.033). Patients with a greater GTV had higher risk of death. The suitable threshold for GTV is 20 cm3. Younger patients with a survival time of about 50 months had a higher risk of death. In the multivariate Cox regression model, the selected variables were age, GTV, sex, diagnosis, KI, location, and some of their interactions. Conclusion Kernel methods give us the possibility to evaluate continuous risk variables and based on the results offer risk-prone patients a different treatment, and can be useful for verifying assumptions of the Cox model or for finding thresholds of continuous variables.

Adjustment of serum HE4 to reduced glomerular filtration and its use in biomarker-based prediction of deep myometrial invasion in endometrial cancer

Background We investigated the efficacy of circulating biomarkers together with histological grade and age to predict deep myometrial invasion (dMI) in endometrial cancer patients. Methods HE4ren was developed adjusting HE4 serum levels towards decreased glomerular filtration rate as quantified by the eGFR-EPI formula. Preoperative HE4, HE4ren, CA125, age, and grade were evaluated in the context of perioperative depth of myometrial invasion in endometrial cancer (EC) patients. Continuous and categorized models were developed by binary logistic regression for any-grade and for G1-or-G2 patients based on single-institution data from 120 EC patients and validated against multicentric data from 379 EC patients. Results In non-cancer individuals, serum HE4 levels increase log-linearly with reduced glomerular filtration of eGFR ≤ 90 ml/min/1.73 m2. HE4ren, adjusting HE4 serum levels to decreased eGFR, was calculated as follows: HE4ren = exp[ln(HE4) + 2.182 × (eGFR-90) × 10-2]. Serum HE4 but not HE4ren is correlated with age. Model with continuous HE4ren, age, and grade predicted dMI in G1-or-G2 EC patients with AUC = 0.833 and AUC = 0.715, respectively, in two validation sets. In a simplified categorical model for G1-or-G2 patients, risk factors were determined as grade 2, HE4ren ≥ 45 pmol/l, CA125 ≥ 35 U/ml, and age ≥ 60. Cumulation of weighted risk factors enabled classification of EC patients to low-risk or high-risk for dMI. Conclusions We have introduced the HE4ren formula, adjusting serum HE4 levels to reduced eGFR that enables quantification of time-dependent changes in HE4 production and elimination irrespective of age and renal function in women. Utilizing HE4ren improves performance of biomarker-based models for prediction of dMI in endometrial cancer patients.

Prognostic impact of combined immunoprofiles in oropharyngeal squamous cell carcinoma patients with respect to AJCC 8th edition

OBJECTIVES To examine combined immunoprofiles of epidermal growth factor receptor (EGFR), CD44, and p16 in oropharyngeal squamous cell carcinoma (OPSCC) and to correlate them with radiotherapy treatment outcomes and clinicopathological parameters. Prognostic impact of the American Joint Committee on Cancer (AJCC) 8th edition staging system in comparison with 7th edition was analyzed. METHODS The study included 77 OPSCC patients treated by definitive intensity-modulated radiotherapy (IMRT). Clinical staging was assessed according to the AJCC, both 7th and 8th edition. Immunohistochemical (IHC) analysis of CD44 and EGFR was performed on primary biopsy tumor tissues. To evaluate the HPV status, IHC detection of p16 was employed. RESULTS The AJCC 8th edition staging system revealed correlations between overall survival (OS), progression-free survival (PFS), locoregional control (LRC), and clinical stage. EGFR and CD44 positivity (+) and p16 negativity (-) were associated with clinical stage IV of the disease. CD44+ and EGFR+ OPSCC displayed worse OS and LRC, and these cases also showed the worst 3-year OS and LRC. Combined analysis of protein expressions identified an association between p16- and EGFR+, p16- and CD44+, EGFR+, and CD44+. Combined immunoprofiles CD44+/p16-, EGFR+/p16-, and EGFR+/CD44+ were associated with worst OS and LRC. CONCLUSIONS Combined immunoprofiles of p16, EGFR, and CD44 might provide valuable prognostic and predictive information for the individual OPSCC patients, especially in terms of response to IMRT and prediction of treatment outcomes. Application of the AJCC 8th edition staging for HPV+ OPSCC proved to improve hazard discrimination and prognostication of OPSCC.