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Adult cystic nephroma (CN) and mixed epithelial and stromal tumor of the kidney (MEST) are considered as separate entities in the 2004 World Health Organization classification of renal neoplasms. Recent studies suggested that the two share clinicopathologic features and may represent the same disease process of varying morphology. However, definitive genetic evidence is lacking. We examined their relationship using gene expression profiling and histologic analysis. Gene expression profiles of 3 CN and 3 MEST were analyzed using HGU133 Plus 2.0 microarrays (Affymetrix) and were compared with each other and also with 48 other renal tumors and 13 normal kidneys. Histologic examination of 26 CN and 13 MEST focused on the cystic septal thickness, cyst-to-stroma ratio, stromal cellularity and composition, types of epithelial cells lining cysts and glands, and estrogen and progesterone receptors expression. Patients' age, sex distribution, and tumor size were similar between the two. They also shared many histologic features, including lining epithelium of cysts and glands, stromal cellularity and composition. Unsupervised clustering of mRNA expression profiles demonstrated that they had very similar expression profiles that were distinct from other renal tumors. By microarray analysis, progesterone receptor expression was significantly higher in CN and MEST relative to both normal and other renal tumors, while estrogen receptor expression was not. By immunohistochemistry, expression of both receptors was similar between CN and MEST. This study provides the most convincing molecular evidence that CN and MEST represent different parts of the morphologic spectrum of the same disease.

We describe an affordable, harmless, and administrative (AHA) metabolic biomarker (MBM) for homecare cancer screening. It may save hundreds of thousands of women’s and thousands of men’s lives every year from breast cancer and melanoma. The goal is to increase the specificity of infrared (IR) imagery to reduce the false alarm rate (FAR). The patient’s hands are immersed in icy cold water, about 11oC, for 30 seconds. We then compare two IR images, taken before and after the cold stimulus, and the difference reveals an enhanced signal and noise ratio (SNR) at tumorigenesis sites since the contraction of capillaries under cold challenge is natural to healthy capillaries, except those newly built capillaries during angiogenesis (Folkman, Nature 1995). Concomitant with the genome and the phenome (molecular signaling by phosphor-mediate protein causing inflammation by platelet activating factor (PAF) that transform cells from benign to malignant is the amplification of nitric oxide (NO) syntheses, a short-lived reactive oxygen species (ROS) that dilates regional blood vessels; superseding normal autonomic nervous system regulation. A rapidly growing tumor site might implicate accumulation of ROS , for which NO can rapidly stretch the capillary bed system usually having thinning muscular lining known as Neo-Angiogenesis (NA) that could behave like Leaky In-situ Faucet Effect (LIFE) in response to cold challenge. To emphasize the state of art knowledge of NA , we mentioned in passing the first generation of an anticapillary growth drug, Avastin by Genetech; it is an antibody protein that is injected for metastasis, while the second generation drug; Sorafenib by Bayers (2001) and Sutent by Pfizer (2000) both target molecular signaling loci to block receptor associated tyrosine kinase induced protein phosphorylation in order to reverse the angiogenesis. Differentiating benign from malignant in a straightforward manner is required to achieve the wellness protocol, yet would become prohibitively expensive and impossible to follow through. For example, given the probability of detection (PD) about 0.1% over unspecified number of years (e.g. menopause years for breast cancer), one might need hundred thousand volunteers. We suggested a Time Reversal Invariant Paradigm (TRIP) (a private communication with Vatican) for gathering equivalent cancer symptom imagery from recovery histories of dozens of patients. We further mixed it with few % of recovered/non-sick cases for negative controls. Creating Virtual images and running videos of these, frame by frame, in two directions (forward and backward in time) resulted in identical Receiver Operation Characteristics (ROC) for both the computer Aided Target Recognition (AiTR) algorithm and the human radiological experts; namely PD versus FAR within the standard deviation; even though the physiology could be entirely different. Such a TRIP would be true taken by any memory-less instantaneous imagery devices (IR, ultrasound, X-rays, MRI excluding magnetic hysteresis memory). In summary, such an affordable, harmless, and administrative, neo-angiogenesis metabolic biomarker can help monitor the transitioning from benign to malignant states of high-risk home alone seniors and also monitor the progress of home alone seniors treatment at home. Therefore, Smartphone equipped with a day camera having IR spectral filtering for a contact self imaging called joystick, when augmented with AHA NA MBM , may be suited for HAS homecare.

Renal cell carcinoma (RCC) is a heterogeneous disease that includes several histologically distinct subtypes. The most common RCC subtypes are clear cell, papillary, and chromophobe, and recent gene expression profiling studies suggest that classification of RCC based on transcriptional signatures could be beneficial. Traditionally, however, patterns of chromosomal alterations have been used to assist in the molecular classification of RCC. The purpose of this study was to determine whether it was possible to develop a classification model for the three major RCC subtypes that utilizes gene expression profiles as the bases for both molecular genetic and cytogenetic classification. Gene expression profiles were first used to build an expression-based RCC classifier. The RCC gene expression profiles were then examined for the presence of regional gene expression biases. Regional expression biases are genetic intervals that contain a disproportionate number of genes that are coordinately up- or down-regulated. The presence of a regional gene expression bias often indicates the presence of a chromosomal abnormality. In this study, we demonstrate an expression-based classifier can distinguish between the three most common RCC subtypes in 99% of cases (n = 73). We also demonstrate that detection of regional expression biases accurately identifies cytogenetic features common to RCC. Additionally, the in silico-derived cytogenetic profiles could be used to classify 81% of cases. Taken together, these data demonstrate that it is possible to construct a robust classification model for RCC using both transcriptional and cytogenetic features derived from a gene expression profile.

The purpose of this study was to determine whether three investigators would produce similar results when reading/scoring the same breast infrared images. They used their standard methods of analysis (subjective to semi-objective analysis). Two of the investigators submitted breast infrared images from 71 screened patients. The images were stored in a database and displayed for scoring by three investigators (two who submitted the data and one additional reader). The left and right breasts were analyzed separately. The investigators submitted their scores to the database without knowledge of the scores of the other two investigators. Overall, concordance of results among all three investgators was 76% (all three investigators' readings agreed on 107 of 141 breasts). Comparison of paired results of the three investigators resulted in 79 to 94% agreement for the six comparisons (three investigators and two breasts) with an overall agreement of 88% (371 of 424 paired comparisons). This preliminary comparison of three investigators' blinded results of breast infrared image readings from a screening population, demonstrates that breast infrared images taken at different Centers with different techniques can be interpreted by different investigators with very similar results. As the database grows there will be an increase in the number and percentage of patients with abnormal infrared images (high risk and breast cancer patients). This will allow a better and more thorough analysis of the results to refine and standardize the reading technique, and further to allow the assessment of previously untested algorithms with this unique database.