Membrane connectivity estimated by digital image analysis of HER2 immunohistochemistry is concordant with visual scoring and fluorescence in situ hybridization results: algorithm evaluation on breast cancer tissue microarrays

<p>Abstract</p> <p>Introduction</p> <p>The human epidermal growth factor receptor 2 (HER2) is an established biomarker for management of patients with breast cancer. While conventional testing of HER2 protein expression is based on semi-quantitative visual scoring of the immunohistochemistry (IHC) result, efforts to reduce inter-observer variation and to produce continuous estimates of the IHC data are potentiated by digital image analysis technologies.</p> <p>Methods</p> <p>HER2 IHC was performed on the tissue microarrays (TMAs) of 195 patients with an early ductal carcinoma of the breast. Digital images of the IHC slides were obtained by Aperio ScanScope GL Slide Scanner. Membrane connectivity algorithm (HER2-CONNECT™, Visiopharm) was used for digital image analysis (DA). A pathologist evaluated the images on the screen twice (visual evaluations: VE1 and VE2). HER2 fluorescence <it>in situ </it>hybridization (FISH) was performed on the corresponding sections of the TMAs. The agreement between the IHC HER2 scores, obtained by VE1, VE2, and DA was tested for individual TMA spots and patient's maximum TMA spot values (VE1max, VE2max, DAmax). The latter were compared with the FISH data. Correlation of the continuous variable of the membrane connectivity estimate with the FISH data was tested.</p> <p>Results</p> <p>The pathologist intra-observer agreement (VE1 and VE2) on HER2 IHC score was almost perfect: kappa 0.91 (by spot) and 0.88 (by patient). The agreement between visual evaluation and digital image analysis was almost perfect at the spot level (kappa 0.86 and 0.87, with VE1 and VE2 respectively) and at the patient level (kappa 0.80 and 0.86, with VE1max and VE2max, respectively). The DA was more accurate than VE in detection of FISH-positive patients by recruiting 3 or 2 additional FISH-positive patients to the IHC score 2+ category from the IHC 0/1+ category by VE1max or VE2max, respectively. The DA continuous variable of the membrane connectivity correlated with the FISH data (HER2 and CEP17 copy numbers, and HER2/CEP17 ratio).</p> <p>Conclusion</p> <p>HER2 IHC digital image analysis based on membrane connectivity estimate was in almost perfect agreement with the visual evaluation of the pathologist and more accurate in detection of HER2 FISH-positive patients. Most immediate benefit of integrating the DA algorithm into the routine pathology HER2 testing may be obtained by alerting/reassuring pathologists of potentially misinterpreted IHC 0/1+ versus 2+ cases.</p

Induction of Bcl-2 Expression by Hepatitis B Virus Pre-S2 Mutant Large Surface Protein Resistance to 5-Fluorouracil Treatment in Huh-7 Cells

BACKGROUND: Hepatocellular carcinoma (HCC) is one of the most common malignancies worldwide with poor prognosis due to resistance to conventional chemotherapy and limited efficacy of radiotherapy. Our previous studies have indicated that expression of Hepatitis B virus pre-S2 large mutant surface antigen (HBV pre-S2Δ) is associated with a significant risk of developing HCC. However, the relationship between HBV pre-S2Δ protein and the resistance of chemotherapeutic drug treatment is still unclear. METHODOLOGY/PRINCIPAL FINDINGS: Here, we show that the expression of HBV pre-S2Δ mutant surface protein in Huh-7 cell significantly promoted cell growth and colony formation. Furthermore, HBV pre-S2Δ protein increased both mRNA (2.7±0.5-fold vs. vehicle, p=0.05) and protein (3.2±0.3-fold vs. vehicle, p=0.01) levels of Bcl-2 in Huh-7 cells. HBV pre-S2Δ protein also enhances Bcl-2 family, Bcl-xL and Mcl-1, expression in Huh-7 cells. Meanwhile, induction of NF-κB p65, ERK, and Akt phosphorylation, and GRP78 expression, an unfolded protein response chaperone, were observed in HBV pre-S2Δ and HBV pre-S-expressing cells. Induction of Bcl-2 expression by HBV pre-S2Δ protein resulted in resistance to 5-fluorouracil treatment in colony formation, caspase-3 assay, and cell apoptosis, and can enhance cell death by co-incubation with Bcl-2 inhibitor. Similarly, transgenic mice showed higher expression of Bcl-2 in liver tissue expressing HBV pre-S2Δ large surface protein in vivo. CONCLUSION/SIGNIFICANCE: Our result demonstrates that HBV pre-S2Δ increased Bcl-2 expression which plays an important role in resistance to 5-fluorouracil-caused cell death. Therefore, these data provide an important chemotherapeutic strategy in HBV pre-S2Δ-associated tumor

Inter-Method Performance Study of Tumor Volumetry Assessment on Computed Tomography Test-Retest Data

RATIONALE AND OBJECTIVES: Tumor volume change has potential as a biomarker for diagnosis, therapy planning, and treatment response. Precision was evaluated and compared among semi-automated lung tumor volume measurement algorithms from clinical thoracic CT datasets. The results inform approaches and testing requirements for establishing conformance with the Quantitative Imaging Biomarker Alliance (QIBA) CT Volumetry Profile. MATERIALS AND METHODS: Industry and academic groups participated in a challenge study. Intra-algorithm repeatability and inter-algorithm reproducibility were estimated. Relative magnitudes of various sources of variability were estimated using a linear mixed effects model. Segmentation boundaries were compared to provide a basis on which to optimize algorithm performance for developers. RESULTS: Intra-algorithm repeatability ranged from 13% (best performing) to 100% (least performing), with most algorithms demonstrating improved repeatability as the tumor size increased. Inter-algorithm reproducibility determined in three partitions and found to be 58% for the four best performing groups, 70% for the set of groups meeting repeatability requirements, and 84% when all groups but the least performer were included. The best performing partition performed markedly better on tumors with equivalent diameters above 40 mm. Larger tumors benefitted by human editing but smaller tumors did not. One-fifth to one-half of the total variability came from sources independent of the algorithms. Segmentation boundaries differed substantially, not just in overall volume but in detail. CONCLUSIONS: Nine of the twelve participating algorithms pass precision requirements similar to what is indicated in the QIBA Profile, with the caveat that the current study was not designed to explicitly evaluate algorithm Profile conformance. Change in tumor volume can be measured with confidence to within ±14% using any of these nine algorithms on tumor sizes above 10 mm. No partition of the algorithms were able to meet the QIBA requirements for interchangeability down to 10 mm, though the partition comprised of the best performing algorithms did meet this requirement above a tumor size of approximately 40 mm

A Robust Algorithm for Automated HER2 Scoring in Breast Cancer Histology Slides Using Characteristic Curves

This paper presents a novel feature descriptor and classification algorithms for automated scoring of HER2 in Whole Slide Images (WSI). Since a large amount of processing is involved in analyzing WSI images, the primary design goal has been to keep the computational complexity to the minimum possible level. We propose an efficient method based on characteristic curves which encode all relevant information in a smooth polynomial curve with the percentage of stained membranes plotted against variations in intensity/saturation of the colour thresholds used for segmentation. Our algorithm performed exceedingly well at a recent online contest held by the University of Warwick [1], obtaining the second best points score of 390 out of 420 and the overall seventh position in the combined leaderboard [2]. The paper describes three classification algorithms with features extracted from characteristic curves and provides experimental results and comparative analysi