Continuous tissue microarray based identification of cancers with homogeneous target expression for successful targeted therapy in clinical routine practice

Immunophenotypic profile of tumor buds in breast cancer

BACKGROUND

Tumor buds are associated with lympho-vascular invasion and lymph node metastases leading to the assumption that they are involved in the early metastatic process. Hence, it would be important to know if tumor buds can be targeted with the most widely used targeted therapies in breast cancer (BC) and if changes in hormone and Her2 status occur. The aim of this study was to answer these questions by determining whether hormone receptor (HR) and Her2 status are expressed in the tumor buds of a large cohort of BCs.

DESIGN

We constructed a tumor bud next-generation tissue microarray (ngTMA) consisting of n = 199 BCs of non-special type. Generally, two 1 mm punches were taken from the tumor bud areas in the periphery (PTB) and within the tumor center (ITB). HR and Her2 status was assessed using immunohistochemistry and fluorescence in situ hybridization, respectively. HR status was positive if ≥1% of tumor bud cells were positive. Her2 status was considered positive if bud cells showed strong complete membranous Her2 over-expression or Her2 amplification.

RESULTS

Most tumor buds were positive for estrogen (ER) (PTB: 86%; ITB: 88.3) and progesterone receptor (PgR) (PTB: 72%; ITB: 72.8%) and Her2 was positive in: PTB 11.5% and ITB 11%. A difference between the main tumor mass and tumor buds (PTB and ITB) was seen for PgR in 3.5% of cases (n = 7). No differences were seen for ER and Her2 between tumor buds and main tumor mass.

CONCLUSION

Most tumor buds (96.5%) share the same HR and Her2 expression profile of the main tumor mass, implying that tumor buds relay on the same pathways as the main tumor mass and might be equally responsive to targeted therapies.

Role of EGFR as prognostic factor in head and neck cancer patients treated with surgery and postoperative radiotherapy: proposal of a new approach behind the EGFR overexpression

In an era of personalized treatment, there is a great interest in identifying factors which might predict patient response to radiotherapy (RT). The role of epidermal growth factor receptor (EGFR) in head and neck squamous cell carcinoma (HNSCC) remains still controversial. We performed a retrospective analysis on the prognostic value of EGFR in HNSCC patients treated with surgery and postoperative RT through a semiquantitative immunohistochemical analysis of EGFR membrane expression. We retrospectively analyzed 65 HNSCC patients treated in our Institute from 1997 to 2003 who underwent adjuvant RT after surgery. Median follow-up was 43.5 months (range 0.2-173 months). None of these patients were treated with postoperative concomitant chemotherapy. Tumor samples were obtained from surgical specimens. Membrane features (intensity, extension) of EGFR expression were evaluated, and a statistical analysis (univariate and multivariate) was conducted to correlate these parameters with overall survival (OS) and disease-free survival (DFS). Patients with an intense and complete labeling of EGFR presented worse OS and DFS compared with groups obtained by all other possible combination, and the difference was borderline statistically significant (P = 0.08 for OS and P = 0.006 for DFS). Moreover, a stratification of patients was performed considering EGFR expression on the tumor tissue and classifying its distribution as "homogeneous" or "heterogeneous." We found that patients showing an "heterogeneous" EGFR expression distribution had worse OS and DFS compared to the "homogeneous" group of patients. Based on our results, EGFR expression, especially referring to membrane features (semiquantitative analysis), might have a prognostic value for OS and DFS in locally advanced HNSCC treated with surgery and adjuvant RT. Prospective trials could be useful to confirm the prognostic role of EGFR expression and also to assess a predictive role to select that might benefit from more aggressive treatments.

Construction and analysis of tissue microarrays in the era of digital pathology: a pilot study targeting CDX1 and CDX2 in a colon cancer cohort of 612 patients

CDX1 and CDX2 are possibly predictive biomarkers in colorectal cancer. We combined digitally‐guided (next generation) TMA construction (ngTMA) and the utility of digital image analysis (DIA) to assess accuracy, tumour heterogeneity and the selective impact of different combined intensity‐percentage levels on prognosis.CDX1 and CDX2 immunohistochemistry was performed on ngTMAs covering normal tissue, tumour centre and invasive front. The percentages of all epithelial cells per staining intensity per core were analysed digitally. Beyond classical prognosis analysis following REMARK guidelines, we investigated pre‐analytical conditions, three different types of heterogeneity (mosaic‐like, targeted and haphazard) and influences on cohort segregation and patient selection. The ngTMA‐DIA approach produced robust biomarker data with infrequent core loss and excellent on‐target punching. The detailed assessment of tumour heterogeneity could – except for a certain diffuse mosaic‐like heterogeneity – exclude differences between the invasive front and tumour centre, as well as detect haphazard clonal heterogeneous elements. Moreover, lower CDX1 and CDX2 counts correlated with mucinous histology, higher TNM stage, higher tumour grade and worse survival (p < 0.01, all). Different protein expression intensity levels shared comparable prognostic power and a great overlap in patient selection. The combination of ngTMA with DIA enhances accuracy and controls for biomarker analysis. Beyond the confirmation of CDX1 and CDX2 as prognostically relevant markers in CRC, this study highlights the greater robustness of CDX2 in comparison to CDX1. For the assessment of CDX2 protein loss, cut‐points as percentage data of complete protein loss can be deduced as a recommendation.

Clinical Significance of Substaging and HER2 Expression in Papillary Nonmuscle Invasive Urothelial Cancers of the Urinary Bladder

The study aimed to verify the prognostic utility, therapeutic application and clinical benefits of tumor substaging and HER2 status in papillary non-muscle invasive bladder cancer (NMIBC). Select NMIBC transurethral resection specimens from 141 patients were used to construct tissue microarrays for assessing the substaging, HER2 protein expression by immunohistochemistry (HER2-IHC) and gene amplification by dual-color silver in situ hybridization (HER2-SISH). Substages were identified by the differing depth of tumor invasion (pTa / pT1a / pT1b / pT1c). HER2 protein expression was semiquantitatively analyzed and grouped into negative (score 0, 1+) and positive (score 2+, 3+). Other clinicopathological variables were also investigated. For NMIBC, HER2-IHC and HER2-SISH showed positive results in 6/141 (4.3%) and 4/141 (2.8%) respectively, which correlated well with tumor substaging. In multivariate analysis, substaging, HER2-IHC, and HER2-SISH were found to be independent predictors of progression-free survival (P < 0.001, P < 0.001, P = 0.031). HER2-IHC was the sole independent predictor of recurrent free survival in NMIBC (P = 0.017). It is suggested that tumor substaging and HER2 status are independent predictive markers for tumor progression or recurrence, and thus could be included in diagnostic and therapeutic management for NMIBC.

Determination of Tumor Heterogeneity in Colorectal Cancers Using Heterogeneity Tissue Microarrays

Cancer is often heterogeneous both on a morphological and on a genetic level. Though resected tumors are often large, molecular tumor analysis is usually restricted to one tissue block. In this project we introduce a new tool for a high-throughput heterogeneity analysis of colorectal cancer. A heterogeneity tissue microarray (TMA) was manufactured from tissues of 340 patients with colorectal cancer. For this purpose 8 different tissue spots were taken from as many different cancer blocks per patient as possible (at least 4 different blocks). Additional tissue samples from 1 to 4 corresponding lymph node metastases were added from 134 patients. The system was then validated by analysing one parameter each known for minimal (p53) or substantial (HER2) heterogeneity in colorectal cancer. P53 alterations as detected by immunohistochemistry were seen in 174 (51.3 %) of 339 analyzable primary tumors of which 23 (13.2 % of positive cases) showed a heterogeneous distribution pattern. HER2 overexpression was seen in 18 (5.4 %) of 336 evaluable tumors. HER2 amplification occurred in 6 (33.3 %) of the 18 cases with HER2 overexpression. Genomic heterogeneity was more prevalent for HER2 alterations than for p53 alterations. For immunohistochemical expression analysis, 16 of 18 positive cases were heterogeneous (88.9 %) and for amplification 3 of 6 cases (50 %) were heterogeneous. Large section validation revealed, however a considerable fraction of heterogeneous cases were due to technical artifacts. In summary, our data suggest, that heterogeneity TMAs are a powerful tool to rapidly screen for molecular heterogeneity in colorectal cancer.

Application of Tissue Microarray Technology to Stem Cell Research

There is virtually an unlimited number of possible Tissue Microarray (TMA) applications in basic and clinical research and ultimately in diagnostics. However, to assess the functional importance of novel markers, researchers very often turn to cell line model systems. The appropriate choice of a cell line is often a difficult task, but the use of cell microarray (CMA) technology enables a quick screening of several markers in cells of different origins, mimicking a genomic-scale analysis. In order to improve the morphological evaluations of the CMA slides we harvested the cells by conventional trypsinization, mechanical scraping and cells grown on coverslips. We show that mechanical scraping is a good evaluation method since keeps the real morphology very similar to those grown on coverslips. Immunofluorescence images are of higher quality, facilitating the reading of the biomarker cellular and subcellular localization. Here, we describe CMA technology in stem cell research.