scholarly journals Gene essentiality in cancer cell lines is modified by the sex chromosomes

2021 ◽  
Author(s):  
Shahar Shohat ◽  
Ethel Vol ◽  
Sagiv Shifman

Human sex differences are thought to arise from gonadal hormones and genes on the sex chromosomes. Here we studied how sex and the sex chromosomes can modulate the outcome of mutations across the genome. We used the results of genome-wide CRISPR-based screens on 306 female and 396 male cancer cell lines to detect differences in gene essentiality between the sexes. By exploiting the tendency of cancer cells to lose or gain sex chromosomes, we were able to dissect the contribution of the Y and X chromosomes to variable gene essentiality. Using this approach, we identified 178 differentially essential genes that depend on the biological sex or the sex chromosomes. Integration with sex bias in gene expression and the rate of somatic mutations in human tumors highlighted genes that escape from X-inactivation, cancer-testis antigens, and Y-linked paralogs as central to the functional genetic differences between males and females.

PLoS ONE ◽  
2014 ◽  
Vol 9 (6) ◽  
pp. e98330 ◽  
Author(s):  
Yvonne G. van der Zwan ◽  
Martin A. Rijlaarsdam ◽  
Fernando J. Rossello ◽  
Amanda J. Notini ◽  
Suzan de Boer ◽  
...  

Author(s):  
Nicholas J. Rossiter ◽  
Kimberly S. Huggler ◽  
Charles H. Adelmann ◽  
Heather R. Keys ◽  
Ross W. Soens ◽  
...  

SUMMARYForward genetic screens across hundreds of diverse cancer cell lines have started to define the genetic dependencies of proliferating human cells and how these vary by genotype and lineage. Most screens, however, have been carried out in culture media that poorly resemble metabolite availability in human blood. To explore how medium composition influences gene essentiality, we performed CRISPR-based screens of human cancer cell lines cultured in traditional versus human plasma-like medium (HPLM). Sets of medium-dependent fitness genes span several cellular processes and can vary with both natural cell-intrinsic diversity and the specific combination of basal and serum components that comprise typical culture media. Notably, we traced the causes for each of three conditional growth phenotypes to the availability of metabolites uniquely defined in HPLM versus traditional media. Our findings reveal the profound impact of medium composition on gene essentiality in human cells, and also suggest general strategies for using genetic screens in HPLM to uncover new cancer vulnerabilities and gene-nutrient interactions.


PLoS ONE ◽  
2015 ◽  
Vol 10 (8) ◽  
pp. e0135958 ◽  
Author(s):  
Prasanna Vidyasekar ◽  
Pavithra Shyamsunder ◽  
Rajpranap Arun ◽  
Rajalakshmi Santhakumar ◽  
Nand Kishore Kapadia ◽  
...  

2019 ◽  
pp. 1-10
Author(s):  
Wei-Sheng Wu ◽  
Jer-Wei Chang ◽  
Hung-Jiun Liaw ◽  
Yu-Han Chu ◽  
Yu-Xuan Jiang

Background Recent advances in ChIP-seq technologies have led to the identification of thousands of TP53 binding loci in various cell types, providing unmatched opportunities for analysis and comparison of the TP53 genome-wide binding patterns under different experimental conditions. These ChIP-seq datasets provide valuable resources for studying the function of TP53. However, there are currently no databases available for easily comparing and analyzing TP53 genome-wide binding patterns derived from different cell lines. Moreover, the TP53 ChIP-seq datasets are scattered among different papers, so extensive work is required to collect and process them for further analysis. Description To solve these problems, we comprehensively collected 13 publicly available TP53 ChIP-seq datasets derived from various cell lines. We re-mapped these 13 ChIP-seq datasets to the most updated reference human genome hg38 and identified the binding peaks (regions with significant enrichment of TP53 binding) and the target genes of TP53 in the human genome using the same data processing pipeline. Note that processing these 13 ChIP-seq datasets using the same pipeline is very crucial because it makes comparing the identified peaks and target genes of TP53 from different datasets possible. Finally, we developed a web-based platform (called the p53BLD), which provides a browse mode to visualize the binding loci of TP53 in the genome and a search mode to retrieve genes whose promoters are bound by TP53. The search mode is very powerful. Users can apply union, intersect, and/or difference operations on the 13 ChIP-seq datasets to generate a list of TP53 binding target genes that satisfies the users’ specifications. The generated gene list can then be downloaded for further analysis. Therefore, the p53BLD can also be regarded as a discovery tool that helps users to generate interesting gene lists for studying TP53. Conclusions Here we presented the first p53 Binding Loci Database (p53BLD). In the case study, we showed that using p53BLD can identify novel TP53 binding targets (KAT6A and KMT2A) in specific cancer cell lines. We believe that p53BLD is a useful resource for studying the function of TP53 in different cancer cell lines. P53BLD is available online at link1/, link2/, or link3/


2008 ◽  
Vol 18 (5) ◽  
pp. 791-801 ◽  
Author(s):  
Y.-J. Shann ◽  
C. Cheng ◽  
C.-H. Chiao ◽  
D.-T. Chen ◽  
P.-H. Li ◽  
...  

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