Virtually all risk prediction for breast cancer assumes that breast cancer is a homogeneous disease

October 14, 2010 By Robert Graham Reporting -- From New York City at NYU /Businesswire/


Hybrid Medical research shows that Virtually all risk prediction
for breast cancer assumes that breast cancer is a homogeneous disease, i.e. all types of breast cancer have the same risk profiles.

Genomic Science indicates that we have to change the breast cancer culture to find a cure. Stem cells and progenitor cells has shown promise. Like stem cells, progenitor cells have a tendency to differentiate into a specific type of cell. In contrast to stem cells, however, they are already far more specific: they are pushed to differentiate into their "target" cell. The most important difference between stem cells and progenitor cells is that stem cells can replicate indefinitely, whereas progenitor cells can only divide a limited number of times. Controversy about the exact definition remains and the concept is still evolving.

Hybrid Medical first direction of research aims to determine what cell becomes transformed; in other words, the cell of origin of a breast tumor. In the mammary gland, mammary stem cells, which can self-renew and differentiate, generate rapidly dividing progenitors that in turn generate differentiated cells of the mammary gland epithelial lineages: the luminal and myoepithelial lineages. Cancer is thought to originate in these stem cells or in progenitor cells that have acquired self-renewal. Thus, a first degree of heterogeneity comes from whether a tumor comes from a stem cell or a progenitor cell.

Hybrid second direction aims to determine what genetic alterations
transform a normal breast cell and make it cancerous. The repertoire of genetic alterations can be found by using high-throughput, large-scale methods, such as mass sequencing and array comparative genomic hybridization (aCGH) . These have
revealed a number of alterations – mutations, deletions,
amplifications and fusions – that target hundreds of genes,
suggesting a high level of heterogeneity. Some tumors can
have a high level of genetic instability whereas others can
have an apparently normal genome.

For an example when monitoring the activities of a protein
created by a gene associated with breast cancer,
called "ABCC11." By studying this gene and its
complex cellular and molecular interactions in
the body, researchers have discovered a distinct
link between the gene and excessively smelly
armpits and wet, sticky earwax.

Panoincell qX also uses a Visualize Real-Time Breast Cancer
Data using Signal Stochastic Resonance Units Neurons
Detection and Analysis for Breast Cancer model after McCulloch-Pitts Panoincell qX computer-assisted diagnosing of breast cancer from mammograms.

How Panoincell qX works is a genetic network simulation trained
with tumor incidence data from knockout experiments.
The genetic network is implemented using a neural
network; knockout genotypes are simulated by removing
nodes in the neural network. Two analyses are used to
interpret the resulting network weights. We use a novel
approach of fixing the network topology that allows knockout
TSG (tumor suppressor gene) data from multiple studies to
overlap and indirectly inform one another. The trained
simulation is validated by reproducing qualitative mammary
cancer susceptibilities of ATM, BRCA1, and p53 TSGs. The work
Panoincell qx is valuable because it allows TSG mammary cancer
susceptibility to be quantified using genetic network
topology and in vivo knockout data.