Carolin M. Sauer

Characterization of somatic mutations at single-cell resolution is essential to study cancer evolution, clonal mosaicism and cell plasticity. Here, we describe SComatic, an algorithm designed for the detection of somatic mutations in single-cell transcriptomic and ATAC-seq (assay for transposase-accessible chromatin sequence) data sets directly without requiring matched bulk or single-cell DNA sequencing data. SComatic distinguishes somatic mutations from polymorphisms, RNA-editing events and artefacts using filters and statistical tests parameterized on non-neoplastic samples. Using >2.6 million single cells from 688 single-cell RNA-seq (scRNA-seq) and single-cell ATAC-seq (scATAC-seq) data sets spanning cancer and non-neoplastic samples, we show that SComatic detects mutations in single cells accurately, even in differentiated cells from polyclonal tissues that are not amenable to mutation detection using existing methods. Validated against matched genome sequencing and scRNA-seq data, SComatic achieves F1 scores between 0.6 and 0.7 across diverse data sets, in comparison to 0.2-0.4 for the second-best performing method. In summary, SComatic permits de novo mutational signature analysis, and the study of clonal heterogeneity and mutational burdens at single-cell resolution.

Osteosarcoma is the most common primary cancer of the bone, with a peak incidence in children and young adults. Using multi-region whole-genome sequencing, we find that chromothripsis is an ongoing mutational process, occurring subclonally in 74% of osteosarcomas. Chromothripsis generates highly unstable derivative chromosomes, the ongoing evolution of which drives the acquisition of oncogenic mutations, clonal diversification, and intra-tumor heterogeneity across diverse sarcomas and carcinomas. In addition, we characterize a new mechanism, termed loss-translocation-amplification (LTA) chromothripsis, which mediates punctuated evolution in about half of pediatric and adult high-grade osteosarcomas. LTA chromothripsis occurs when a single double-strand break triggers concomitant TP53 inactivation and oncogene amplification through breakage-fusion-bridge cycles. It is particularly prevalent in osteosarcoma and is not detected in other cancers driven by TP53 mutation. Finally, we identify the level of genome-wide loss of heterozygosity as a strong prognostic indicator for high-grade osteosarcoma.

Each year, blood transfusions save millions of lives. However, under current blood-matching practices, sensitization to non-self-antigens is an unavoidable adverse side effect of transfusion. We describe a universal donor typing platform that could be adopted by blood services worldwide to facilitate a universal extended blood-matching policy and reduce sensitization rates. This DNA-based test is capable of simultaneously typing most clinically relevant red blood cell (RBC), human platelet (HPA), and human leukocyte (HLA) antigens. Validation was performed, using samples from 7927 European, 27 South Asian, 21 East Asian, and 9 African blood donors enrolled in 2 national biobanks. We illustrated the usefulness of the platform by analyzing antibody data from patients sensitized with multiple RBC alloantibodies. Genotyping results demonstrated concordance of 99.91%, 99.97%, and 99.03% with RBC, HPA, and HLA clinically validated typing results in 89 371, 3016, and 9289 comparisons, respectively. Genotyping increased the total number of antigen typing results available from 110 980 to >1 200 000. Dense donor typing allowed identification of 2 to 6 times more compatible donors to serve 3146 patients with multiple RBC alloantibodies, providing at least 1 match for 176 individuals for whom previously no blood could be found among the same donors. This genotyping technology is already being used to type thousands of donors taking part in national genotyping studies. Extraction of dense antigen-typing data from these cohorts provides blood supply organizations with the opportunity to implement a policy of genomics-based precision matching of blood.

The drivers of recurrence and resistance in ovarian high grade serous carcinoma remain unclear. We investigate the acquisition of resistance by collecting tumour biopsies from a cohort of 276 women with relapsed ovarian high grade serous carcinoma in the BriTROC-1 study. Panel sequencing shows close concordance between diagnosis and relapse, with only four discordant cases. There is also very strong concordance in copy number between diagnosis and relapse, with no significant difference in purity, ploidy or focal somatic copy number alterations, even when stratified by platinum sensitivity or prior chemotherapy lines. Copy number signatures are strongly correlated with immune cell infiltration, whilst diagnosis samples from patients with primary platinum resistance have increased rates of CCNE1 and KRAS amplification and copy number signature 1 exposure. Our data show that the ovarian high grade serous carcinoma genome is remarkably stable between diagnosis and relapse and acquired chemotherapy resistance does not select for common copy number drivers.

Chromosomal instability is a major challenge to patient stratification and targeted drug development for high-grade serous ovarian carcinoma (HGSOC). Here we show that somatic copy number alterations (SCNAs) in frequently amplified HGSOC cancer genes significantly correlate with gene expression and methylation status. We identify five prevalent clonal driver SCNAs (chromosomal amplifications encompassing MYC, PIK3CA, CCNE1, KRAS and TERT) from multi-regional HGSOC data and reason that their strong selection should prioritise them as key biomarkers for targeted therapies. We use primary HGSOC spheroid models to test interactions between in vitro targeted therapy and SCNAs. MYC chromosomal copy number is associated with in-vitro and clinical response to paclitaxel and in-vitro response to mTORC1/2 inhibition. Activation of the mTOR survival pathway in the context of MYC-amplified HGSOC is statistically associated with increased prevalence of SCNAs in genes from the PI3K pathway. Co-occurrence of amplifications in MYC and genes from the PI3K pathway is independently observed in squamous lung cancer and triple negative breast cancer. In this work, we show that identifying co-occurrence of clonal driver SCNA genes could be used to tailor therapeutics for precision medicine.