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Gene for predicting the prognosis for early-stage breast cancer, and a method for predicting the prognosis for early-stage breast cancer by using the same

a prognostic gene and breast cancer technology, applied in the field of early-stage breast cancer prognosis gene and early-stage breast cancer prognosis prediction method, can solve the problems of difficult to perform, explosive increase in related information, key drawbacks and drawbacks of analysis results, etc., and achieve the effect of reducing unnecessary anti-cancer therapy

Inactive Publication Date: 2013-12-26
GENCURIX
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  • Summary
  • Abstract
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AI Technical Summary

Benefits of technology

The patent text describes a method for predicting the prognosis of early-stage breast cancer patients using a prognostic gene and a method for analyzing gene expression patterns. The invention is based on the use of microarray technology to analyze the genome of breast cancer cells and identify patterns that predict progression of the disease. The method aims to provide a more accurate and reliable way to predict which patients will benefit from anticancer treatments and which patients may not require them. By using microarrays to analyze the gene expression patterns of breast cancer cells, researchers hope to better understand the mechanisms of cancer development and identify new targets for therapy. The invention also addresses the limitations of current clinical methods for predicting prognosis, such as the difficulty in standardizing and quantifying the results and the need for high-performance computing equipment. The use of microarrays and other genomic analysis techniques to predict prognosis has been actively researched and several gene expression patterns have been identified as potential prognosis predictors. The invention provides a valuable tool for predicting the outcome of early-stage breast cancer patients and reducing unnecessary anticancer treatments.

Problems solved by technology

In spite of the disadvantages of high cost, researches using microarray are actively developed such that amounts of related information are explosively increasing.
However, analyzing results are key point as well as drawback.
However, since it is difficult to perform to the researchers who familiar with traditional biological research range and experimental methods, it is not utilized usefully.
It is difficult to decide whether this early-stage breast cancer patients after surgery receive treatments for anticancer.
Although it is possible to predict for an approximate prognosis by pathological observation, the observation result is difficult to standardize and quantify, and its reliability is low.
Due to the nature of anticancer treatments, patients suffer from a huge pain and financial expenditure.

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  • Gene for predicting the prognosis for early-stage breast cancer, and a method for predicting the prognosis for early-stage breast cancer by using the same
  • Gene for predicting the prognosis for early-stage breast cancer, and a method for predicting the prognosis for early-stage breast cancer by using the same
  • Gene for predicting the prognosis for early-stage breast cancer, and a method for predicting the prognosis for early-stage breast cancer by using the same

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Experimental Methods

Collection of Expression Profile in the Early Stage Breast Cancer Tissue

[0081]Expression profiles and clinical information obtained with frozen tissue of the early stage breast cancer were collected from the Gene Expression Omnibus (GEO, at the World Wide Web: ncbi.nlm.nih.gov / geo). Each of total nine independent expression profile sets was consisting of more than 100 samples. It was made to perform prognosis related-researches for the early stage breast cancer patients (2, 4, 9, 10, 13, 25, 32, 33). Eight dataset of them were generated with same platform, Affymetrix® U133A, and last dataset was generated by Agilent Hu25K. Most of them, the patient's clinical information (age, sex, tumor size, state of tumor metastasis and degree of tumor differentiation) and survival information were collected together. Six datasets of eight data sets generated by Affymetrix® U133A information was about distant-metastasis free survival, and last two datasets were about overall s...

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Abstract

The present invention relates to a method for selecting a gene intended to predict the prognosis for a cancer, to the selected gene for predicting the prognosis of cancer and to a kit for predicting and a method for predicting metastasis in breast-cancer patients by using the same. In the present invention, a straight forward method is used to achieve high-reliability prediction of the patient's prognosis by analysing for the genetic characteristics of early stage breast cancer, and thus the present invention can be used to advantage in prognosis diagnosis which can reduce unnecessary anticancer therapy.

Description

CROSS-REFERENCE TO RELATED APPLICATIONS[0001]This application is a continuation of International Application No. PCT / KR2012 / 000021 filed on Jan. 2, 2012, which claims priority to Korean Application No. 10-2011-0000521 filed on Jan. 4, 2011. The entire contents of the aforementioned patent applications are incorporated herein by reference.SEQUENCE LISTING[0002]The instant application contains a Sequence Listing which has been submitted in ASCII format via EFS-Web and is hereby incorporated by reference in its entirety. Said ASCII copy, created on Jul. 4, 2013, is named 93515-307161_ST25.txt and is 15,319 bytes in size.FIELD OF THE INVENTION[0003]The present invention relates to a development of a prognostic gene and a method for predicting prognosis of the early stage breast cancer.DESCRIPTION OF THE RELATED ART[0004]As human genome information has been utilizing actively, cancer researches tens to identify mechanism at genome level. In particular, microarray is able to identify canc...

Claims

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Application Information

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Patent Type & Authority Applications(United States)
IPC IPC(8): C12Q1/68G16B25/10
CPCC12Q1/6886C12Q2600/118C12Q2600/158G16B25/00G16B25/10G01N33/57415G01N33/57484G01N2333/723
Inventor SHINCHOI, YOON LAKIM, YOUNG-DEUGOH, EU SELKIM, SI EUN
Owner GENCURIX
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