Alexander Boag

Immunohistochemical Evidence of Loss of PTEN Expression in Primary Ductal Adenocarcinomas of the Breast

Germline mutations in PTEN, encoding a dual-specificity phosphatase on 10q23.3, cause Cowden syndrome (CS), which is characterized by a high risk of breast and thyroid cancers. Loss of heterozygosity of 10q22-24 markers and somatic PTEN mutations have been found to a greater or lesser extent in a variety of sporadic component and noncomponent cancers of CS. Among several series of sporadic breast carcinomas, the frequency of loss of flanking markers around PTEN is approximately 30 to 40%, and the somatic intragenic PTEN mutation frequency is <5%. In this study, we analyzed PTEN expression in 33 sporadic primary breast carcinoma samples using immunohistochemistry and correlated this to structural studies at the molecular level. Normal mammary tissue had a distinctive pattern of expression: myoepithelial cells uniformly showed strong PTEN expression. The PTEN protein level in mammary epithelial cells was variable. Ductal hyperplasia with and without atypia exhibited higher PTEN protein levels than normal mammary epithelial cells. Among the 33 carcinoma samples, 5 (15%) were immunohistochemically PTEN-negative; 6 (18%) had reduced staining, and the rest were PTEN-positive. In the PTEN-positive tumors as well as in normal epithelium, the protein was localized in the cytoplasm and in the nucleus (or nuclear membrane). Among the immunostain negative group, all had hemizygous PTEN deletion but no structural alteration of the remaining allele. Thus, in these cases, an epigenetic phenomenon such as hypermethylation, -ecreased protein synthesis or increased protein degradation may be involved. In the cases with reduced staining, 5 of 6 had hemizygous PTEN deletion and 1 did not have any structural abnormality. Finally, clinicopathological features were analyzed against PTEN protein expression. Three of the 5 PTEN immunostain-negative carcinomas were also both estrogen and progesterone receptor-negative, whereas only 5 of 22 of the PTEN-positive group were double receptor-negative. The significance of this last observation requires further study.

Analysis of PTEN and the 10q23 region in primary prostate carcinomas

Deletions involving chromosome 10q23 occur frequently in prostatic carcinomas. Recently, a novel tumour suppressor gene, PTEN, mapping to this interval, has been identified. Mutation or deletion of PTEN has been observed in a proportion of prostate cancer cell lines; however, primary prostate carcinomas have not been studied. We have investigated the involvement of PTEN in primary prostatic adenocarcinomas using a panel of 51 matched normal and prostate tumour DNAs. We first determined the proportion of tumours with allele loss at loci in 10q23 which span the region containing the PTEN gene. Our results show that LOH involving 10q23 is common in primary prostate carcinomas. Twenty-five of 51 (49%) tumours showed loss of heterozygosity (LOH) over the region spanning the PTEN locus. We next directly analysed the PTEN gene for mutations of the coding region using single strand conformation polymorphism (SSCP) and sequence analyses. Of those tumours with LOH, only a single tumour was found to carry a missense mutation in PTEN. No mutations in PTEN were identified in tumours without LOH. Our results suggest either that mutation of PTEN is a late event in prostate tumorigenesis, or that another tumour suppressor gene important in prostate cancer may lie close to PTEN in 10q23.

Analysis of the 10q23 chromosomal region and the PTEN gene in human sporadic breast carcinoma

We examined a panel of sporadic breast carcinomas for loss of heterozygosity (LOH) in a 10-cM interval on chromosome 10 known to encompass the PTEN gene. We detected allele loss in 27 of 70 breast tumour DNAs. Fifteen of these showed loss limited to a subregion of the area studied. The most commonly deleted region was flanked by D10S215 and D10S541 and encompasses the PTEN locus. We used a combination of denaturing gradient gel electrophoresis and single-strand conformation polymorphism analyses to investigate the presence of PTEN mutations in tumours with LOH in this region. We did not detect mutations of PTEN in any of these tumours. Our data show that, in sporadic breast carcinoma, loss of heterozygosity of the PTEN locus is frequent, but mutation of PTEN is not. These results are consistent with loss of another unidentified tumour suppressor in this region in sporadic breast carcinoma.

High-throughput detection of prostate cancer in histological sections using probabilistic pairwise Markov models.

In this paper we present a high-throughput system for detecting regions of carcinoma of the prostate (CaP) in HSs from radical prostatectomies (RPs) using probabilistic pairwise Markov models (PPMMs), a novel type of Markov random field (MRF). At diagnostic resolution a digitized HS can contain 80Kx70K pixels - far too many for current automated Gleason grading algorithms to process. However, grading can be separated into two distinct steps: (1) detecting cancerous regions and (2) then grading these regions. The detection step does not require diagnostic resolution and can be performed much more quickly. Thus, we introduce a CaP detection system capable of analyzing an entire digitized whole-mount HS (2x1.75cm(2)) in under three minutes (on a desktop computer) while achieving a CaP detection sensitivity and specificity of 0.87 and 0.90, respectively. We obtain this high-throughput by tailoring the system to analyze the HSs at low resolution (8microm per pixel). This motivates the following algorithm: (Step 1) glands are segmented, (Step 2) the segmented glands are classified as malignant or benign, and (Step 3) the malignant glands are consolidated into continuous regions. The classification of individual glands leverages two features: gland size and the tendency for proximate glands to share the same class. The latter feature describes a spatial dependency which we model using a Markov prior. Typically, Markov priors are expressed as the product of potential functions. Unfortunately, potential functions are mathematical abstractions, and constructing priors through their selection becomes an ad hoc procedure, resulting in simplistic models such as the Potts. Addressing this problem, we introduce PPMMs which formulate priors in terms of probability density functions, allowing the creation of more sophisticated models. To demonstrate the efficacy of our CaP detection system and assess the advantages of using a PPMM prior instead of the Potts, we alternately incorporate both priors into our algorithm and rigorously evaluate system performance, extracting statistics from over 6000 simulations run across 40 RP specimens. Perhaps the most indicative result is as follows: at a CaP sensitivity of 0.87 the accompanying false positive rates of the system when alternately employing the PPMM and Potts priors are 0.10 and 0.20, respectively.

Augmenting Detection of Prostate Cancer in Transrectal Ultrasound Images Using SVM and RF Time Series

We propose a novel and accurate method based on ultrasound RF time series analysis and an extended version of support vector machine classification for generating probabilistic cancer maps that can augment ultrasound images of prostate and enhance the biopsy process. To form the RF time series, we record sequential ultrasound RF echoes backscattered from tissue while the imaging probe and the tissue are stationary in position. We show that RF time series acquired from agar-gelatin-based tissue mimicking phantoms, with difference only in the size of cell-mimicking microscopic glass beads, are distinguishable with statistically reliable accuracies up to 80.5%. This fact indicates that the differences in tissue microstructures affect the ultrasound RF time series features. Based on this phenomenon, in an ex vivo study involving 35 prostate specimens, we show that the features extracted from RF time series are significantly more accurate and sensitive compared to two other established categories of ultrasound-based tissue typing methods. We report an area under receiver operating characteristic curve of 0.95 in tenfold cross validation and 0.82 in leave-one-patient-out cross validation for detection of prostate cancer.

BENIGN MIXED EPITHELIAL STROMAL TUMOR OF THE KIDNEY OF POSSIBLE MULLERIAN ORIGIN

Benign mixed epithelial and stromal tumor of the kidney has only recently been recognized as a distinct clinical and pathological entity.1 Approximately 38 cases have been iden- tified in the literature. We report an unusual case of mixed epithelial and stromal tumor that may be of mullerian deri- vation. A 51-year-old woman with an incidental renal mass de- tected on ultrasound underwent computerized tomography which revealed an enhancing, inhomogeneous 16 12 10 cm. mass in the left kidney (fig. 1). The mass contained irregular small cystic pockets and peripheral punctate calci- fications. There was an ill-defined mobile mass in the left upper quadrant on physical examination, and the patient underwent left radical nephrectomy for presumed cystic re- nal cell carcinoma. Gross pathological examination revealed a 13 8 7 cm. white multilocular cystic tumor filled with mucoid fluid. The cysts were small, less than 1 cm., with thin walls and no significant solid component. The tumor replaced the upper pole and projected into the renal pelvis but was confined within the renal capsule. Microscopically the tumor was com- posed of a mixture of epithelial and stromal elements. Cystic dilated spaces were lined by an admixture of mucus produc- ing columnar and ciliated serous epithelium (fig. 2). Papillary projections containing fibrovascular cores were seen extend- ing into these cystic spaces. There was no cytologic atypia or mitotic activity observed in the epithelial lining. The epithe- lial elements were strongly decorated by antikeratin stain CAM 5.2 and carcinoembryonic antigen stain was negative. The immunophenotype of the subepithelial stromal elements was vimentin positive, desmin negative, muscle specific actin (HHF35) negative, smooth muscle actin negative, CD34 neg- ative, S100 negative, estrogen receptor protein focal positive and progesterone receptor protein focal positive. The glandu- lar epithelium also displayed strong positivity for estrogen

Fer Protein-Tyrosine Kinase Promotes Lung Adenocarcinoma Cell Invasion and Tumor Metastasis

Epidermal growth factor receptor (EGFR) is frequently amplified or mutated in non–small cell lung cancer (NSCLC). Although Fer protein-tyrosine kinase signals downstream of EGFR, its role in NSCLC tumor progression has not been reported. Here, Fer kinase was elevated in NSCLC tumors compared to normal lung epithelium. EGFR signaling in NSCLC cells fosters rapid Fer activation and increased localization to lamellipodia. Stable silencing of Fer in H1299 lung adenocarcinoma cells (Fer KD) caused impaired EGFR-induced lamellipodia formation compared to control cells. Fer KD NSCLC cells showed reduced Vav2 tyrosine phosphorylation that was correlated with direct Fer-mediated phosphorylation of Vav2 on tyrosine-172, which was previously reported to increase the guanine nucleotide exchange factor activity of Vav2. Indeed, Fer KD cells displayed defects in Rac-GTP localization to lamellipodia, cell migration, and cell invasion in vitro. To test the role of Fer in NSCLC progression and metastasis, control and Fer KD cells were grown as subcutaneous tumors in mice. Although Fer was not required for tumor growth, Fer KD tumor-bearing mice had significantly fewer numbers of spontaneous metastases. Combined, these data demonstrate that Fer kinase is elevated in NSCLC tumors and is important for cellular invasion and metastasis. Implications: Fer protein-tyrosine kinase is a potential therapeutic target in metastatic lung cancer. Mol Cancer Res; 11(8); 952–63. ©2013 AACR.

Discrete Fourier Analysis of Ultrasound RF Time Series for Detection of Prostate Cancer

In this paper, we demonstrate that a set of six features extracted from the discrete Fourier transform of ultrasound radio-frequency (RF) time series can be used to detect prostate cancer with high sensitivity and specificity. Ultrasound RF time series refer to a series of echoes received from one spatial location of tissue while the imaging probe and the tissue are fixed in position. Our previous investigations have shown that at least one feature, fractal dimension, of these signals demonstrates strong correlation with the tissue microstructure. In the current paper, six new features that represent the frequency spectrum of the RF time series have been used, in conjunction with a neural network classification approach, to detect prostate cancer in regions of tissue as small as 0.03 cm2. Based on pathology results used as gold standard, we have acquired mean accuracy of 91%, mean sensitivity of 92% and mean specificity of 90% on seven human prostates.

Probabilistic pairwise Markov models: application to prostate cancer detection

Markov Random Fields (MRFs) provide a tractable means for incorporating contextual information into a Bayesian framework. This contextual information is modeled using multiple local conditional probability density functions (LCPDFs) which the MRF framework implicitly combines into a single joint probability density function (JPDF) that describes the entire system. However, only LCPDFs of certain functional forms are consistent, meaning they reconstitute a valid JPDF. These forms are specified by the Gibbs-Markov equivalence theorem which indicates that the JPDF, and hence the LCPDFs, should be representable as a product of potential functions (i.e. Gibbs distributions). Unfortunately, potential functions are mathematical abstractions that lack intuition; and consequently, constructing LCPDFs through their selection becomes an ad hoc procedure, usually resulting in generic and/or heuristic models. In this paper we demonstrate that under certain conditions the LCDPFs can be formulated in terms of quantities that are both meaningful and descriptive: probability distributions. Using probability distributions instead of potential functions enables us to construct consistent LCPDFs whose modeling capabilities are both more intuitive and expansive than typical MRF models. As an example, we compare the efficacy of our so-called probabilistic pairwise Markov models (PPMMs) to the prevalent Potts model by incorporating both into a novel computer aided diagnosis (CAD) system for detecting prostate cancer in whole-mount histological sections. Using the Potts model the CAD system is able to detection cancerous glands with a specificity of 0.82 and sensitivity of 0.71; its area under the receiver operator characteristic (AUC) curve is 0.83. If instead the PPMM model is employed the sensitivity (specificity is held fixed) and AUC increase to 0.77 and 0.87.

Flock Worker's Lung Disease: Natural History of Cases and Exposed Workers in Kingston, Ontario

BACKGROUND The natural history of flock workers lung (FWL) and longitudinal lung function changes in nylon flock-exposed workers have not been well characterized. METHODS Symptoms, pulmonary function testing, and chest radiographs from five index cases, subsequent case referrals, and screened employees of a flocking plant in Kingston, Ontario, Canada, were compared and analyzed for changes over time (variable follow-up intervals between 1991 and 2011). RESULTS Nine cases and 30 flock-exposed workers without FWL were identified. Four cases had persistent interstitial lung disease despite three having left the workplace. Two developed hypoxemic respiratory failure and secondary pulmonary hypertension and died of complications 18 and 20 years after diagnosis, respectively. Five cases resolved after leaving the workplace. Compared with resolved cases, persistent cases had lower diffusing capacity of the lung for carbon monoxide at presentation (P < .05) and follow-up (P < .05). Among exposed workers employed for 14.5 ± 4.7 years, five had abnormal chest radiographs vs none at baseline (P = .001) over 14.8 ± 4.6 years of follow-up. The prevalence of wheeze increased (P = .001), and FEV₁/FVC decreased (P < .001). FEV₁% predicted was significantly lower at follow-up (P = .05). Average FEV₁ decline was 46 mL/year (range, -27 to 151 mL/y). Seventy-seven percent of exposed workers were current or former smokers. CONCLUSIONS The natural history of FWL includes the following patterns: complete resolution of symptoms; radiographic and pulmonary function abnormalities; permanent, but stable symptoms and restrictive pulmonary function deficits; and progressive decline in pulmonary function, causing death from respiratory failure and secondary pulmonary hypertension. A low baseline diffusing capacity of the lung for carbon monoxide is associated with the persistence and progression of FWL.