Developer

This pipeline is released by the BMAP team.

Benchmark Data

This pipeline was validated using a standard sample (GW-OYC001), which consists of 19 target drug-related genes and 21 mutations, with mutation frequencies ranging from 5% to 60%. The pipeline successfully detected all variant sites, and all variants in the standard sample were cross-validated using both NGS and ddPCR.

Workflow

1. Cancer genomic data analysis

NGS based somatic variant calling and clinical annotation.
This application processes NGS sequencing data to identify somatic variants and generates an assistant report, which includes treatment recommendations and relevant clinical trial options.

Background

A 64-year-old female non-smoker was diagnosed as lung cancer.

Method

To discover potential therapeutic regimens, next-generation sequencing (NGS) analysis was performed.

Results

EGFR exon20 insertion mutation, was identified and may be associated with resistance to the 1 st/3rd generation EGFR TKIs. It should be noted that the sensitivity of patients harboring this mutation to second-generation EGFR TKI remains to be explored [1].

Fig. 1. Next-generation sequencing results showing the novel EGFR P772delinsVDNR mutation.

Reference

[1] Liang P, et al. A possible EGFR TKIs resistance mechanism of lung adenocarcinoma patients with a novel EGFR exon 20-ins mutation: A case report. Lung Cancer 152, 193-195 (2021).

v2.1: Upload the docker image to SRS repository，SRS repository ID: SRS1043140100231540736
v2.0: Upload the scripts to CRS repository，CRS repository ID: CRS1043138710197252096
v1.2: Add the clinical annotation using clinical knowledge graph iCMDB，including target therapy, prognosis, and clinical trials ongoing.
v1.1: Update the Mutect to Mutect2
v1.0: Quality control, Variant Calling, Gene annotation

Reproducibility

The pipeline utilizes code CRS1043138710197252096 and Docker image SRS573973980869046272, both of which are stored in the BMAP repositories.

Pipeline

Somatic variants are extracted following the GATK Best Practices guidelines for somatic short variant discovery, which can be found here . The variants are then annotated using a commercial knowledge database (iCMDB).

Usage

1. Select the application 'Cancer Genomic Analysis'
2. Click on the 'Analysis' button
3. Click on the 'Paired Tumor-Normal'
4. Fill in the request parameters

Note: the R1 and R2 file names should include the subfolder name and the extension name (eg. data/normal_R1.fq.gz).
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5. Upload the compressed data in gz or rar format.

6. View the results