Type 1 plasminogen activator inhibitor (PAI-1) in clear cell renal cell carcinoma (CCRCC) and its impact on angiogenesis, progression and patient survival after radical nephrectomy

<p>Abstract</p> <p>Background</p> <p>To examine the expression of type 1 plasminogen inhibitor (PAI-1) in clear cell renal cell carcinoma (CCRCC), and its possible association with microvessel density (MVD), the expression of thrombospondin-1 (TSP-1), nuclear grade, tumour stage, continuously coded tumour size (CCTS) and to assess the value of PAI as a prognostic marker in 162 patients with CCRCC treated with radical nephrectomy.</p> <p>Methods</p> <p>A total of 172 consecutive patients with CCRCC treated with radical nephrectomy were enrolled in the study. The expression of PAI-1, TSP-1 and factor VIII were analysed on formalin-fixed, paraffin-embedded tissues without knowledge of the clinical outcome. Ten cases, where PAI-1 immunohistochemistry was not possible due to technical problems and lack of material, were excluded. Sixty-nine patients (43%) died of RCC, while 47 patients (29%) died of other diseases. Median follow-up was 13.8 years for the surviving 46 patients (28%).</p> <p>Results</p> <p>Nine percent of the tumours showed PAI-1 positivity. High expression of PAI-1 was significantly inversely correlated with TSP-1 (p = 0.046) and directly with advanced stage (p = 0.008), high NG (3+4) (p = 0.002), tumour size (p = 0.011), microvessel density (p = 0.049) and disease progression (p = 0.002). In univariate analysis PAI-1 was a significant prognosticator of cancer-specific survival (CSS) (p < 0.001). Multivariate analysis revealed that TNM stage (p < 0.001), PAI-1 (p = 0.020), TSP-1 (p < 0.001) and MVD (p = 0.007) were independent predictors of CSS.</p> <p>Conclusions</p> <p>PAI-1 was found to be an independently significant prognosticator of CSS and a promoter of tumour angiogenesis, aggressiveness and progression in CCRCC.</p

Robust Automated Tumour Segmentation on Histological and Immunohistochemical Tissue Images

Tissue microarray (TMA) is a high throughput analysis tool to identify new diagnostic and prognostic markers in human cancers. However, standard automated method in tumour detection on both routine histochemical and immunohistochemistry (IHC) images is under developed. This paper presents a robust automated tumour cell segmentation model which can be applied to both routine histochemical tissue slides and IHC slides and deal with finer pixel-based segmentation in comparison with blob or area based segmentation by existing approaches. The presented technique greatly improves the process of TMA construction and plays an important role in automated IHC quantification in biomarker analysis where excluding stroma areas is critical. With the finest pixel-based evaluation (instead of area-based or object-based), the experimental results show that the proposed method is able to achieve 80% accuracy and 78% accuracy in two different types of pathological virtual slides, i.e., routine histochemical H&E and IHC images, respectively. The presented technique greatly reduces labor-intensive workloads for pathologists and highly speeds up the process of TMA construction and provides a possibility for fully automated IHC quantification

Computer-assisted assessment of the Human Epidermal Growth Factor Receptor 2 immunohistochemical assay in imaged histologic sections using a membrane isolation algorithm and quantitative analysis of positive controls

<p>Abstract</p> <p>Background</p> <p>Breast cancers that overexpress the human epidermal growth factor receptor 2 (HER2) are eligible for effective biologically targeted therapies, such as trastuzumab. However, accurately determining HER2 overexpression, especially in immunohistochemically equivocal cases, remains a challenge. Manual analysis of HER2 expression is dependent on the assessment of membrane staining as well as comparisons with positive controls. In spite of the strides that have been made to standardize the assessment process, intra- and inter-observer discrepancies in scoring is not uncommon. In this manuscript we describe a pathologist assisted, computer-based continuous scoring approach for increasing the precision and reproducibility of assessing imaged breast tissue specimens.</p> <p>Methods</p> <p>Computer-assisted analysis on HER2 IHC is compared with manual scoring and fluorescence in situ hybridization results on a test set of 99 digitally imaged breast cancer cases enriched with equivocally scored (2+) cases. Image features are generated based on the staining profile of the positive control tissue and pixels delineated by a newly developed Membrane Isolation Algorithm. Evaluation of results was performed using Receiver Operator Characteristic (ROC) analysis.</p> <p>Results</p> <p>A computer-aided diagnostic approach has been developed using a membrane isolation algorithm and quantitative use of positive immunostaining controls. By incorporating internal positive controls into feature analysis a greater Area Under the Curve (AUC) in ROC analysis was achieved than feature analysis without positive controls. Evaluation of HER2 immunostaining that utilized membrane pixels, controls, and percent area stained showed significantly greater AUC than manual scoring, and significantly less false positive rate when used to evaluate immunohistochemically equivocal cases.</p> <p>Conclusion</p> <p>It has been shown that by incorporating both a membrane isolation algorithm and analysis of known positive controls a computer-assisted diagnostic algorithm was developed that can reproducibly score HER2 status in IHC stained clinical breast cancer specimens. For equivocal scoring cases, this approach performed better than standard manual evaluation as assessed by ROC analysis in our test samples. Finally, there exists potential for utilizing image-analysis techniques for improving HER2 scoring at the immunohistochemically equivocal range.</p

The prognostic relevance of interactions between venous invasion, lymph node involvement and distant metastases in renal cell carcinoma after radical nephrectomy

<p>Abstract</p> <p>Background</p> <p>To investigate a possible prognostic significance of interactions between lymph node invasion (LNI), synchronous distant metastases (SDM), and venous invasion (VI) adjusted for mode of detection, Eastern Cooperative Oncology Group performance status (ECOG PS), erythrocyte sedimentation rate (ESR) and tumour size (TS) in 196 patients with renal cell carcinoma treated with radical nephrectomy.</p> <p>Methods</p> <p>Median follow-up was 5.5 years (mean 6.9 years; range 0.01–19.4). The mode of detection, ECOG PS, ESR and TS were obtained from the patients' records. Vena cava invasion and distant metastases were detected by preoperative imaging. The surgical specimens were examined for pathological stage, LNI and VI.</p> <p>Results</p> <p>The univariate analyses showed significant impact of VI, LNI, SDM, ESR and TS (p < 0.001), as well as mode of detection (p = 0.003) and ECOG PS (p = 0.002) on cancer specific survival. In multivariate analyses LNI was significantly associated with survival only in patients without SDM or VI (p < 0.001) with a hazard ratio of 9.0. LNI lost its prognostic significance when SDM or VI was present.</p> <p>Conclusion</p> <p>Our findings underline the prognostic importance of the status of the lymph nodes. LNI, SDM, ESR, and VI were independently associated with cancer specific survival after radical nephrectomy. LNI provided the strongest prognostic information for patients without SDM or VI whereas SDM and VI had strongest impact on survival when there was no nodal involvement.</p

Surgical treatment and prognostic analysis for gastrointestinal stromal tumors (GISTs) of the small intestine: before the era of imatinib mesylate

BACKGROUND: Gastrointestinal stromal tumors (GISTs), the most common type of mesenchymal tumors of the gastrointestinal (GI) tract, demonstrate positive kit staining. We report our surgical experience with 100 small intestine GIST patients and identify predictors for long-term disease-free survival (DFS) and overall survival (OS) to clarify the difference between high- and low-risk patients. METHODS: The clinicopathologic and follow-up records of 100 small intestine GIST patients who were treated at Chung Gung Memorial Hospital between 1983 and 2002 were retrospectively reviewed. Clinical and pathological factors were assessed for long-term DFS and OS by using a univariate log-rank test and a multivariate Cox proportional hazard model. RESULTS: The patients included 52 men and 48 women. Their ages ranged from 27 to 82 years. Among the 85 patients who underwent curative resection, 44 (51.8%) developed disease recurrence (liver metastasis was the most common form of recurrence). The follow-up period ranged from 5 to 202 months (median: 33.2 months). The 1-, 3-, and 5-year DFS and OS rates were 85.2%, 53.8%, and 43.7%, and 91.5%, 66.6%, and 50.5%, respectively. Using multivariate analysis, it was found that high tumor cellularity, mitotic count >5/50 high-power field, and a Ki-67 index ≧10% were three independent factors that were inversely associated with DFS. However, absence of tumor perforation, mitotic count < 5/50 high power field, and tumor with low cellularity were predictors of long-term favorable OS. CONCLUSION: Tumors with low cellularity, low mitotic count, and low Ki-67 index, which indicate low risk, predict a more favorable DFS for small intestine GIST patients undergoing curative resection. Absence of tumor perforation with low mitotic count and low cellularity, which indicates low risk, can predict long-term OS for small intestine GIST patients who have undergone curative resection