* Your assessment is very important for improving the workof artificial intelligence, which forms the content of this project
Download The Cancer Genome Atlas
Survey
Document related concepts
Epigenetics of neurodegenerative diseases wikipedia , lookup
Long non-coding RNA wikipedia , lookup
Gene expression programming wikipedia , lookup
Epitranscriptome wikipedia , lookup
Genomic imprinting wikipedia , lookup
Public health genomics wikipedia , lookup
Site-specific recombinase technology wikipedia , lookup
Genome (book) wikipedia , lookup
Nutriepigenomics wikipedia , lookup
Polycomb Group Proteins and Cancer wikipedia , lookup
Gene expression profiling wikipedia , lookup
BRCA mutation wikipedia , lookup
Cancer epigenetics wikipedia , lookup
Secreted frizzled-related protein 1 wikipedia , lookup
Transcript
I focused my project specifically on The Cancer Genome Atlas’s (TCGA) research on breast and high-grade serous ovarian (HGS-OvCa) cancers. It was seen through mRNA expression analysis, which helps identify variations in gene expression by measuring mRNA levels, that there are 4 distinct subtypes of breast cancer based on variations in mRNA expression. These included luminal A, luminal B, HER2-enriched (HER2E), and basal-like. Each of the 4 subtypes of breast cancer can have up to three different protein receptors present on them, including estrogen receptor (ER), progesterone receptor (PR), or human epidermal growth factor receptor 2 (HER2). As part of their study, TCGA researchers compared the breast cancer subtypes to other common cancers and their results showed that the basal-like breast cancer subtype is most similar to HGS-OvCa on a genomic level than to any of the other breast cancer subtypes. It was seen that both had similar types and frequencies of genomic mutations which suggests that the two cancers may have come from a similar molecular origin. These similarities include a high frequency of TP53 genes mutations, high expression of the AKT3 genes, inactivation of BRCA1, amplification and high expression of cMYC, loss of the tumor suppressor gene RB1, and amplification of Cyclin E1. It is believed that through these findings that both cancers may potentially be susceptible to similar treatments. With TCGA’s large-scale genomic data on breast and high-grade serous ovarian cancers, it is possible for future treatment options to become available. By gaining a better understanding of the genetics of tumor samples of a variety of cancers, better therapeutic options can be created. It is hoped that the research performed by TCGA will help other researchers expand on their studies so that more effective drugs can be made for treating cancers.