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Steeghs, N.

Publications and source records attributed to Steeghs, N..

4 recordsLinked to original sources

The mutational footprints of cancer therapies

Some cancer therapies damage DNA and cause mutations both in cancer and healthy cells of the patient1. These therapy-induced mutations may underlie some of the long-term and late side effects of the treatment, such as mental disabilities, organ toxicities and secondary neoplasms. Currently we ignore the mutation pattern and burden caused by different cancer treatments. Here we identify mutational signatures, or footprints of six widely-used anti-cancer therapies with the study of whole-genomes from more than 3500 metastatic tumors originated in different organs. These include previously known and new mutational signatures generated by platinum-based drugs, and a novel signature of treatment with nucleoside metabolic inhibitors. Exploiting these mutational footprints, we estimate the contribution of different treatments to the mutation burden of tumors and their risk of causing coding and likely driver mutations in the genome. In summary, the mutational footprints identified here open a window to precisely appraise the mutational risk of different cancer therapies to understand their late side effects.

genomics↗

The genomic landscape of metastatic castration-resistant prostate cancers using whole genome sequencing reveals multiple distinct genotypes with potential clinical impact

Here we present whole-genome sequencing (WGS) analysis of fresh-frozen metastatic biopsies from 197 castration-resistant prostate cancer patients. Using hierarchical unsupervised clustering based on genomic aberrations only, we defined eight different clusters. We detected four distinct and potentially clinically relevant genotypes harboring unique genomic features, including: 1) Microsatellite Instability; 2) Homologous Recombination Deficiency (HRD) with enriched genomic deletions and BRCA2 aberrations; 3) tandem duplication phenotype associated with biallelic CDK12 mutations; and 4) a subgroup enriched for chromothripsis events. Our data suggest that classifying patients using WGS characteristics may improve classification of HRD patients. Moreover, we confirmed that important regulators of AR-mediated signaling are located in non-coding regions. Using ChIP sequencing data, we showed that the amplified AR and MYC promoter regions contain open chromatin and bind AR, suggesting a role in AR mediated biology. Thus, high-resolution WGS may be used to improve patient stratification.

cancer biology↗

Tumor mutational landscape is a record of the pre-malignant state

Chromatin structure has a major influence on the cell-specific density of somatic mutations along the cancer genome. Here, we present a pan-cancer study in which we searched for the putative cancer cell-of-origin of 2,550 whole genomes, representing 32 cancer types by matching their mutational landscape to the regional patterns of chromatin modifications ascertained in 104 normal tissue types. We found that, in almost all cancer types, the cell-of-origin can be predicted solely from their DNA sequences. Our analysis validated the hypothesis that high-grade serous ovarian cancer originates in the fallopian tube and identified distinct origins of breast cancer subtypes. We also demonstrated that the technique is equally capable of identifying the cell-of-origin for a series of 2,044 metastatic samples from 22 of the tumor types available as primaries. Moreover, cancer drivers, whether inherited or acquired, reside in active chromatin regions in the respective cell-of-origin. Taken together, our findings highlight that many somatic mutations accumulate while the chromatin structure of the cell-of-origin is maintained and that this historical record, captured in the DNA, can be used to identify the often elusive cancer cell-of-origin.

genomics↗

Pan-cancer whole genome analyses of metastatic solid tumors

Metastatic cancer is one of the major causes of death and is associated with poor treatment efficiency. A better understanding of the characteristics of late stage cancer is required to help tailor personalised treatment, reduce overtreatment and improve outcomes. Here we describe the largest pan-cancer study of metastatic solid tumor genomes, including 2,520 whole genome-sequenced tumor-normal pairs, analyzed at a median depth of 106x and 38x respectively, and surveying over 70 million somatic variants. Metastatic lesions were found to be very diverse, with mutation characteristics reflecting those of the primary tumor types, although with high rates of whole genome duplication events (56%). Metastatic lesions are relatively homogeneous with the vast majority (96%) of driver mutations being clonal and up to 80% of tumor suppressor genes bi-allelically inactivated through different mutational mechanisms. For 62% of all patients, genetic variants that may be associated with outcome of approved or experimental therapies were detected. These actionable events were distributed across various mutation types underlining the importance of comprehensive genomic tumor profiling for cancer precision medicine.

cancer biology↗