We describe a man who, after a presumed encephalitic illness, was "locked-in" for 27 years. His CT and autopsy findings showed atrophy of the brainstem and a cystic lesion at the base of the pons. He survived longer than most other patients in a similar state.
8520 Background: Metastatic melanoma is a chemoresistant disease with poor prognosis. Angiogenesis plays a role in progression and metastasis of melanoma. Identifying angiogenic molecules that are differentially expressed between benign and malignant tissues may enable us to create an assay to predict sensitivity to antiangiogenic agents, thus guiding selection of patients for treatment. VEGF signals through its receptor VEGFR1/flt-1 (R1) but is thought to mediate most of its angiogenic and proliferative effects through VEGFR2/flk-1/kdr (R2). In smaller melanoma studies, VEGF, R2 and less commonly R1 expression was associated with disease aggression. We characterized VEGF, R1, and R2 expression on a cohort of 540 nevi and 548 melanomas. Methods: We stained tissue microarrays to assess VEGF, R1, and R2 expression by automated quantitative analysis (AQUA), an objective method for analysis of protein levels. We used S100 to define pixels as melanoma (tumor mask) within the array spot, and measured intensity of VEGF, R1, and R2 expression using Cy5 conjugated antibodies within the mask. Results: VEGF, R1, and R2 expression was significantly higher in melanomas than in nevi by unpaired t-tests (p<0.0001). VEGF and R2 expression was higher in metastatic than primary specimens (p<0.0001). Differential expression of R1 between metastatic and primary specimens was less pronounced (p=0.0158). R2 expression correlated with Breslow depth > 2 mm (p=0.0129). Cox univariate analysis revealed an association between decreased survival and expression of VEGF (p= 0.0488) and R2 (p=0.0035); however, this was not independent of disease stage. Conclusions: VEGF, R1, and R2 expression is higher in malignant melanocytes than in their benign counterparts and higher in metastatic than primary specimens. This association with disease aggression underscores the importance of these proteins as therapeutic targets. Differential expression of R2 was found to be more significant than R1, supporting the belief that VEGF mediates its effects through R2 in malignancy. To our knowledge, this is the largest study to examine the VEGF pathway in melanoma. Future clinical trials of antiangiogenic agents in melanoma should include correlative serum and tissue assays of VEGF, R1, and R2 as biomarkers of response to therapy. [Table: see text]
Background: Prediction of benefit from trastuzumab in patients (pts) with HER2+ breast cancer remains an important goal. We sought to investigate the predictive value of quantitative measurement of HER2, HER3, HER4, EGFR, ER and PTEN protein expression on the benefit of trastuzumab in the phase III HER2+ adjuvant N9831 study for pts randomized to chemotherapy alone (Arm A) or chemotherapy with sequential (Arm B) or concurrent trastuzumab (Arm C). Methods: For each marker, we evaluated quantitative expression, relationship with demographic data, and association with disease-free survival (DFS) of pts. Freshly cut tissue microarray slides with up to three-fold redundancy per specimen from the N9831 cohort were treated identically using the AQUA (Camp, et al; Nat Med 2002, JCO 2008) method of quantitative immunofluorescence for each marker. HER2 was tested with CB11 (mouse monoclonal, Biocare, Inc.) and preliminary results were available for 698 of nearly 1400 pt specimens to be tested. The minimum value per pt was used in statistical analysis. Specimens were classified with high versus low expression based on a median value cutpoint for each marker. Median follow-up was 7.0 yrs. Results: Quantitative HER2 was compared with centrally performed HER2 testing by IHC and FISH. Median quantitative HER2 via AQUA was 10,017 units for the HER2 IHC 3+ group (n=607) versus 1058, 831, and 970 for the HER2 IHC 2+ (n=68), 1+ (n=11), and 0 (n=11) groups, respectively. The Spearman correlation between quantitative HER2 and FISH HER2/CEP17 ratio was 0.32 (p<0.001). High quantitative HER2 was associated with lower percentage of hormone receptor positivity (48% vs 59%, chi-sq p=0.003) but not associated with age, race, nodal positivity, tumor histology, grade, or size. High HER2 did not impact DFS in any arm of the study (See Table). Data for additional HER2 testing, HER3, HER4, EGFR, ER and PTEN are in process and will be ready by September, 2011. Conclusions: Similar to results based on standard HER2 testing by IHC and FISH in N9831, quantitative HER2 did not impact benefit from adjuvant trastuzumab. Results for additional markers will be presented. Our complete quantitative results for a second epitope on HER2, HER3, HER4, ER and EGFR will be the first report of these markers in a large patient cohort in the adjuvant setting. Disease Free Survival Citation Information: Cancer Res 2011;71(24 Suppl):Abstract nr PD05-03.
Introduction: There have been disparate results reported in breast cancer testing for HER2 assessment as measured by protein expression or DNA amplification, yet both tests are routinely used to prescribe the drug Herceptin (trastuzumab, Genentech, So San Francisco, CA). Typically, immunohistochemistry (IHC) staining intensity of 3+ or FISH copy ratio of ≥2.0 are used to establish the cutoff between a negative and a positive result. However, it is unclear whether positivity is correlated with differential response to therapy. We used Automated Quantitative Analysis (AQUA) and a fluorescent immunohistochemical assay to measure HER2 expression in cases scored by central laboratory FISH and also receiving Herceptin therapy. The intentions of the study were two-fold: first, to provide further validation of the AQUA technology as applied to the clinical measurement of HER2 expression in breast cancer and second, to examine the potential of drug response stratification within those patients that are considered positive. Methods: AQUA fluorescence IHC staining was performed on a multi-cohort tissue microarray (TMA) set. The assay was constructed in the Genoptix CLIA laboratory per ASCO/CAP guidelines and with a cutpoint that was validated against IHC (with FISH reflex). The trial specimens tested were from the BCIRG-005/006 studies. BCIRG-005 had n=1544 cases all assessed as FISH- while the 006 cohort had n=1477 cases all assessed as FISH+. Disease free survival (DFS) was used as the variable in subsequent modeling and analysis. Results: The BCIRG 005 and 006 cohorts, examined in aggregate, allowed for an initial examination of agreement relationships between HER2 levels as assessed by AQUA scoring and HER2 levels as assessed by central lab FISH. Results indicated a 77% negative agreement, a 97% positive agreement and an 87% overall concordance agreement for a total of n=3021 cases. Additional Cox modeling of the patients that were enrolled as FISH+ and stratified for those who did or did not receive Herceptin treatment demonstrated a significant overall hazard ratio (HR = 0.75, CI=0.60,0.93) and when stratified for response to Herceptin, cases determined to be positive by AQUA showed significant benefit from treatment (HR = 0.66, CI = 0.52,0.85) in contrast to those who were scored as negative by AQUA that did demonstrate benefit from therapy (HR = 1.19, CI=0.71,1.97). Conclusions: Analysis of the cases in this study originally determined to be HER2+ by FISH indicates that AQUA may improve predictions of which patients will benefit from Herceptin therapy. Citation Information: Cancer Res 2012;72(24 Suppl):Abstract nr PD02-01.
Background: Random periareolar fine needle aspiration (RPFNA) cytology coupled with the Gail risk model has been used to predict the short-term risk of breast cancer in high risk women. The cytomorphologic features of atypical epithelial cells obtained by RPFNA can be subtle and result in inter-observer diagnostic variability and decreased sensitivity. Spectral-spatial analysis (SSA) is a method for objective image analysis that uses both color and spatial information to classify features into user-defined groups. We use SSA to classify cell clusters from RPFNA specimens into objective categories and compare that result to the cytopathology interpretation, which is the current standard.Design:Cell clusters on Papanicolau stained cytology Thin Prep slides from 7 benign and 7 malignant (14 total) breast RPFNA specimen were used to generate image stacks with the CRI Nuance platform. The specimens were processed and stained in three separate cytopathology laboratories. To build the algorithmic model, image stacks were analyzed using a neural network-based artificial intelligence system now distributed commercially as the Inform system. We manually painted green and red indicating feature (malignant) versus non-feature/background (benign) cells, respectively. A diagnostic algorithmic solution was created to stratify the new images as percent pixels correctly assigned as “malignant”. The solution was tested against cell clusters from 53 high-risk RPFNA specimen stratified by an expert pathologist (CZ) into the 5 categories of benign, epithelial hyperplasia, borderline, atypical and malignant. The specimens were collected from the contra lateral breast of patients with mastectomies for invasive carcinoma. Although 14 of the 67 cases were reused, no cellular clusters used in the training set were included in the validation set. The cytopathologist diagnosis was used as the gold standard and binarized to designate malignant cases as 1 and benign 0. These were compared to the green pixel (malignant) percentage in each case processed by INform.Results: The SSA algorithm classified all 7 malignant cases concordantly with the pathologist. The remaining 60 cases were classified as benign. The ROC curve generated from the cases had an AUC of 0.974 and an accuracy of 79.1%. The sensitivity was 100% and the specificity 76.7%.Conclusions: Spectral-spatial analysis can objectively classify benign and malignant cell clusters in excellent concordance to an expert pathologist. The epithelial hyperplasia, borderline, and atypical categories were all classified as benign by this solution representing a weakness in the solution. However, since these classes are not definitive with respect to biological behavior, the algorithm was binarized as above. In the future, algorithms will be based on biologically proven classes toward the goal of more definitive classification. A mature version of this technology could allow much broader usage of RPFNA since it would no longer be solely dependent on expert cytopathology interpretation. Citation Information: Cancer Res 2009;69(24 Suppl):Abstract nr 6001.
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