SERVICES
What We Provide
We provide personalized diagnosis and therapeutic target candidates for individual cancer patients. Our service currently covers breast cancer only. The coverage of our services will be expanded to several cancer types, such as lung cancer and hepatic cancer.
Degree of malignancy of the genome in individual patients
Sample probability (SP) of the genomic function in an individual breast cancer patient
SP indicates the degree of deviation from normal. The lower the SP, the higher the degree of malignancy.
The red dot represents the SP of a given patient.
SP is calculated with a density matrix generated with expression data of either 2,571 genes included in all genomic modules activated in normal breast tissue (n=28) or whole genes included in microarray data.
Cancerous transformation of biological functions in individual patients
Modular sample probabilities (MSPs) of an individual breast cancer patient based on genomic modules isolated from normal breast tissues
MSP indicates the degree of collapse of the biological function operated by a genomic module in the individual cancer genome.
BRNO and BRCA represent the MSPs of normal and cancerous breast tissues, respectively.
Blue dots represent the MSPs of a given patient.
Users can choose the reference sample groups that compare the MSPs of a given patient. By default, BRCA vs. BRNO is selected.
There are four other options: ER+ vs. ER-, PR+ vs. PR-, HER2+ vs. HER2-, and Cancer modules.
Users can choose the color scale of MSPs in the inter-modular network (IMN): absolute and relative scale.
Selecting a genomic module, users can see the MSP value and the list of genes that compose the module.
Absolute scale of MSP [0-1]
Relative scale of MSP [0-100]
Biological functions of the genomic modules
Eighty-five genomic modules were isolated from gene expression data of normal breast tissue (BRNO).
The biological functions of the modules were determined by gene ontology (GO) and compared between various tissues.
The intermodular network (IMN) was constructed with relative entropy between modules.
kernel: the domain composed of kernel modules, which is the core of the genomic system and operates the whole system in the base
ccdr: the domain composed of modules that operate the cell cycle regulation and DNA repair
meta.ccdr: the domain composed of modules that connect the ccdr to other domains
meta.1, meta.2, and meta.3: the domains composed of modules that connect between domains
adipo: the domain composed of modules that operate the fat tissue
epi and epi.1: the domains composed of modules that operate the epithelial cells
angio: the domain composed of modules related to the angiogenesis
stroma: the domain composed of modules that operate the stroma
Mapping genomic modules isolated from other types of cancer to individual patients
MSPs of an individual breast cancer patient based on genomic modules isolated from breast invasive carcinoma (BRCA), lung squamous cell carcinoma (LUSC), and lung adenocarcinoma (LUAD)
BRNO and BRCA represent the MSPs of normal and cancerous breast tissues, respectively.
Blue dots represent the MSPs of a given patient.
BRCA 25: the genomic module operating stem cells in breast cancer
LUSC 3: the genomic module operating stem cells in lung squamous cell carcinoma
LUSC 28: the genomic module related to the keratinization in lung squamous cell carcinoma
LUAD 20: the genomic module related to the immune response in lung adenocarcinoma
LUAD 27 and LUAD 51: the genomic modules operating NK cells in lung adenocarcinoma
Selecting a genomic module, users can see the MSP value and the list of genes that compose the module.
Degree of the contribution of each gene in cancerous transformation in individual patients
Log odds ratios (LORs) of genes that compose a genomic module in an individual breast cancer patient
(upper) Log expression ratios (LERs), the normalized gene expression data obtained from microarray
(lower) Log odds ratios (LORs), after processing the LERs
BRNO and BRCA represent the LORs of normal and cancerous breast tissues, respectively.
Black dots represent the LORs of a given patient.
The LORs of CD8B, CDCA7, FBXL5, and TRAIP are extraordinarily increased or decreased in the given breast cancer patient compared to the other breast cancer samples as well as the normal breast samples.
These genes are prognostic biomarkers having low cancer specificity.
However, the LERs cannot highlight these genes in the given patient compared to other breast cancer samples and even normal breast samples.
Users can choose a genomic module to see the LORs of genes that compose the given module.
By selecting a gene, users can see the LOR and LER values.
Precise classification of individual patients
Classification of an individual breast cancer patient with our reference breast cancer samples
The heat map depicts the absolute MSP values of our reference cancer samples and the given patient sample.
The red box indicates the MSPs and the location of the given patient among the reference cancer samples.
The hierarchical clustering of the reference cancer samples using MSP values provides a lot of information about the characteristics of the cancer sample groups.
The characteristics of a new patient sample can be inferred from the co-classified cancer samples.
Analysis of resection margin for individual patients
Classification of the resection margin sample of an individual cancer patient with our reference normal tissue and cancer samples
The heat map depicts the absolute MSP values of our reference normal and cancer samples and the given resection margin sample.
The red box indicates the MSPs and the location of the given resection margin sample among the reference normal and cancer samples.
After tumor resection surgery, the margins are usually sent to a pathologist to see if the cancer cells have been completely removed.
Morphological observations mainly judge the cancerous transformation of resection margins.
However, the observation through a microscope cannot detect cells that have undergone functional changes in the genome before transformation into cancer cells.
The reference normal and cancer samples are clearly divided into normal and cancer sample groups with the hierarchical clustering using MSP values.
The location of the resection margin sample within the reference samples tells the cancerous transformation at the genome level.
Summary