Summary #

Introduction #

driver and passenger mutations을 구분하는 것은 도전이다.

The aim of these studies was to survey the numbers and patterns of somatic point mutations in a diverse set of human cancer genomes and hence to obtain insights into the relative contributions of driver and passenger mutations.

Somatic protein kinase mutations #

kinase 유전자 패밀리는 암 유전자인 경우가 많으며, 이들 유전자의 저해제가 암 치료제인 경우가 많다.

각종 암 210에서 kinase 유전자들(518) 코딩영역과 splice junction을 시퀀싱 - 274 Mb - 1007 somatic mutation을 찾다.

Prevalence of somatic mutations #

많은 것부터 없는 것까지 다양

Signatures of somatic mutations #

암종에 따라 다른 특징

• Lung cancer by tobacco carcinogens
• Melanoma by UV light
• Glioblastoma by mutagenic alkylating chemotherapy

Prevalence of driver and passenger mutations #

Germline polymorphism에 C:G>G:C는 별로 없는데, 몇몇 암종에는 많이 발견됨

Characteristics of driver mutations #

driver냐 아니냐 확인 - observed ratio of non-synonymous: synonymous mutations compared with that expected by chance --> positive or negative selection

158 drivers, 921 passengers 확인

MMR deficent cancer는 selective pressure가 낮음 (1.08) - 변이율이 올라가면 전체적으로 선택압은 낮아진다.

kinase 관련 변이와 아닌 것과의 pressure 차이는 1.4:1.23

Potential protein kinase cancer genes #

selection pressure로 driver 정도를 정렬하여 보면, 잘 알려진 암 유전자들도 있고, 그렇지 않은 것들도 있음.

Reactome, Panther, INOH 데이터셋을 이용한 pathway 분석시, FGF signalling pathway가 가장 유의하게 높게 나옴.

재미있게도 Apoptosis나, Cell cycle 관련 pathway는 나오지 않음.

Discussion #

518중 120개 유전자가 driver mutation으로 보임.

Methods #

DNA from primary tumors, cancer cell lines, normal tissue samples. More than 80% of tumour cells were used.

To assess the significance of this ratio, an exact Monte Carlo test was developed which was applied to the entire set and to subsets of mutations.

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