README.md

metadata

dataset_info:
  features:
    - name: ARID1A KD
      dtype: string
    - name: BAP1 KO
      dtype: string
    - name: CDH1 KO
      dtype: string
    - name: KEAP1 KO
      dtype: string
    - name: STK11 KO
      dtype: string
    - name: NF1 KO
      dtype: string
    - name: NF2 KO
      dtype: string
    - name: PBRM1 KO
      dtype: string
    - name: PTEN KO
      dtype: string
    - name: RB1 KO
      dtype: string
    - name: TP53 KO
      dtype: string
    - name: VHL KO
      dtype: string
    - name: TP53BP1 KO
      dtype: string
  splits:
    - name: train
      num_bytes: 3468
      num_examples: 38
  download_size: 8229
  dataset_size: 3468
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*
license: cc-by-4.0
tags:
  - biology
  - chemistry
  - medical

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Dataset Details

Dataset Description

• Curated by: [More Information Needed]
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Source Data

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Recommendations

Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.

Citation [optional]

BibTeX:

@article{
  doi:10.1126/sciadv.abm6638,
  author = {Xu Feng  and Mengfan Tang  and Merve Dede  and Dan Su  and Guangsheng Pei  and Dadi Jiang  and Chao Wang  and Zhen Chen  and Mi Li  and Litong Nie  and Yun Xiong  and Siting Li  and Jeong-Min Park  and Huimin Zhang  and Min Huang  and Klaudia Szymonowicz  and Zhongming Zhao  and Traver Hart  and Junjie Chen },
  title = {Genome-wide CRISPR screens using isogenic cells reveal vulnerabilities conferred by loss of tumor suppressors},
  journal = {Science Advances},
  volume = {8},
  number = {19},
  pages = {eabm6638},
  year = {2022},
  doi = {10.1126/sciadv.abm6638},
  URL = {https://www.science.org/doi/abs/10.1126/sciadv.abm6638},
  eprint = {https://www.science.org/doi/pdf/10.1126/sciadv.abm6638},
  abstract = {Exploiting cancer vulnerabilities is critical for the discovery of anticancer drugs. However, tumor suppressors cannot be directly targeted because of their loss of function. To uncover specific vulnerabilities for cells with deficiency in any given tumor suppressor(s), we performed genome-scale CRISPR loss-of-function screens using a panel of isogenic knockout cells we generated for 12 common tumor suppressors. Here, we provide a comprehensive and comparative dataset for genetic interactions between the whole-genome protein-coding genes and a panel of tumor suppressor genes, which allows us to uncover known and new high-confidence synthetic lethal interactions. Mining this dataset, we uncover essential paralog gene pairs, which could be a common mechanism for interpreting synthetic lethality. Moreover, we propose that some tumor suppressors could be targeted to suppress proliferation of cells with deficiency in other tumor suppressors. This dataset provides valuable information that can be further exploited for targeted cancer therapy. Whole-genome CRISPR screens uncover synthetic lethal interactions for tumor suppressors.}
}

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