How to use public data to send NC

How to use public data to send NC. With the gradual increase in the amount of sequencing in tumors, many current high-resolution analyses are based on pan-cancer data. The advantage of this is that the changes in most cancers can be observed. Today, I will introduce to you a pan-cancer analysis article published recently on Nature Communication (NC).

Background introduction

Immune checkpoint blockade (ICB) therapy has revolutionized the treatment of many malignancies, leading to extensive research on predictive and prognostic biomarkers. The latest research from several groups pointed out that the ICB response is associated with mutations in the SWI/SNF chromatin remodeling complex (the polybromo and BRG-1 associated factors, PBAF), which includes ARID2, PBRM1 and BRD7 genes These three genes. Recent studies have found that the relationship between PBAF and immunotherapy is unclear. In order to illustrate the relationship between PBAF complex and immunotherapy, the author did this pan-cancer analysis.

In the analysis in the article, the author used two large pan-cancer data to analyze the PBAF complex in different tumors. One pan-cancer data was used to analyze the relationship between PBAF complex mutations and prognosis. Multiple transcriptions were used. Set of data to analyze the function of PBAF complex mutations.

Main results:

1. PBAF complex mutations in various tumors

The author used TCGA’s pan-cancer data and MSK-IMPACT two public data sets to observe the mutation of PBAF complex in each tumor. Regarding the evaluation of mutations, the most classic one is to observe the mutation rate. Here, tumor mutation burden (tumor mutation burden, TMB) and fragment genome altered (FGA) are used for evaluation. Through the observation of TMB, the author found that the TMB of the PBAF complex is the most significant among kidney cancers.

2. The relationship between PBAF complex mutation and prognosis

In the above, the author found that the mutation is the most significant in kidney cancer. So I want to observe whether the mutation of the PBAF complex is related to the prognosis. Here for the prognostic analysis of mutations. The author divided the mutations into three groups: loss-of-function (LOF), non-loss-of-function (non-LOF) and no mutation to observe whether the prognosis is meaningful. After reading the prognosis of kidney cancer, I also looked at the prognosis of other cancers.

3. The relationship between PBAF complex mutation and tumor immunity

After understanding the relationship between PBAF mutations in various tumors and the prognosis. It is still necessary to evaluate the impact of mutations on function. Especially this complex is related to immunity. Therefore, the relationship with immunity was further evaluated. Here, the author does not use expression data like TCGA. Here the author uses three other “public data sets”. These public data sets are based on sequencing data generated during clinical trials.

Thoughts about the article

The above is the basic content of the article. The tip of the article to us is that the article uses multiple public data sets. Among them, TCGA is commonly used by us. In addition, the public data set MSK-IMPACT is also used. This data set contains information related to immunotherapy. So those who want to understand immunotherapy-related things can use this data. How to use it should be introduced later.

In addition to MSK-IMPACT, sequencing data from three public clinical trials were also used. These three data are mainly from the European Genome-Phenome Archive (EGA) organization. This organization stores a lot of sequencing data related to clinical trials. Those who want the relevant sequencing data of clinical trials can check here. But the data in this need to apply. In fact, if you have a good experimental design, you can send them an email to apply. You can get the download permission if you are not sure.

Also on the evaluation of gene mutations. The simplest one used before is the mutation rate. Through this article, we know that group evaluation can also be done through TMB and function changes.

(source:internet, reference only)

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