June 25, 2024

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MSKCC: Tumor-related genome detection public database

MSKCC: Tumor-related genome detection public database

MSKCC: Tumor-related genome detection public database. Previously in an NC document (How to use public data to send NC), a public sequencing data (MSK-IMPACT) was mentioned. So now let’s briefly introduce this data set. In this way, when conducting public data mining, except for TCGA. At the same time, you can also consider using this data set to increase the content of analysis.


Through the high-throughput detection method of next-generation sequencing, we can detect the changes in the genome of many genes of a person at one time. MSK-IMPACTTM is a hybrid capture technology based on NGS panel that can quickly detect all protein coding mutations, copy number mutations, promoter mutations, and structural rearrangements in 468 genes related to cancer. Unlike conventional testing, MSK-IMPACTTM is suitable for any tumor type.

MSKCC: Tumor-related genome detection public database 

If you just say that this sequencing technology can be used to detect the genome information of patients, it is actually useless for our scientific research. Crucially, the Memorial Sloan Kettering Cancer Center (MSK) shared the more than 10,000 samples they previously tested on patients for data mining. This is convenient for us to use.

This data is saved on the cBioPortal website (https://www.cbioportal.org/study/summary?id=msk_impact_2017)
MSKCC: Tumor-related genome detection public database

In addition, regarding the use of cBioPotral, we have introduced this before. Those who are interested can take a look at our second post.

A brief introduction to the use of MSKCC data set

Regarding this data set, we need to pay attention to it, although this is a pan-tumor data set. We can have most tumors in it. In addition, the clinical information about the patient also includes follow-up and medication. This record of medication usage is better than TCGA.

But it should be noted that, because MSKCC is still doing genome sequencing. So what we can get through this data set is the change in the DNA level of each patient. Based on changes in DNA levels, mutations, copy numbers, and fusion genes are basically commonly used. Therefore, if you want to observe the changes in mRNA gene expression of this patient, you cannot use it.

In addition, because this project is directed to monitor the detection of several tumor-related genes. So this rare gene that you might want to study is not included in this data set. This also needs attention.

So in summary, this data set is more likely to be used for genome data mining (mutation, copy number, etc.), after the whole genome observation, if you want to further observe the changes in clinical drug patients for certain gene mutations .

(source:internet, reference only)

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