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Testicular germ cell tumours (TGCTs) appear as different histological subtypes or mixtures of these. They show similar, multiple DNA copy number changes, where gain of 12p is pathognomonic. However, few high-resolution analyses have been performed and focal DNA copy number changes with corresponding candidate target genes remain poorly described for individual subtypes. We present the first high-resolution DNA copy number aberration (CNA) analysis on the subtype embryonal carcinomas (ECs), including 13 primary ECs and 5 EC cell lines. We identified recurrent gains and losses and allele-specific CNAs. Within these regions, we nominate 30 genes that may be of interest to the EC subtype. By in silico analysis of data from 150 TGCTs from The Cancer Genome Atlas (TCGA), we further investigated CNAs, RNA expression, somatic mutations and fusion transcripts of these genes. Among primary ECs, ploidy ranged between 2.3 and 5.0, and the most common aberrations were DNA copy number gains at chromosome (arm) 7, 8, 12p, and 17, losses at 4, 10, 11, and 18, replicating known TGCT genome characteristics. Gain of whole or parts of 12p was found in all samples, including a highly amplified 100 kbp segment at 12p13.31, containing SLC2A3. Gain at 7p21, encompassing ETV1, was the second most frequent aberration. In conclusion, we present novel CNAs and the genes located within these regions, where the copy number gain of SLC2A3 and ETV1 are of interest, and which copy number levels also correlate with expression in TGCTs.

Tumor evolution is dependent on and constrained by the genotypes emerging from genome instability. We hypothesized that non-site-specific copy number motifs would correlate with underlying replication defects and also with tumor and patient fate. Six feature detectors were defined to characterize and score the local spatial behaviour of a copy number profile. By accumulating scores across genomic regions, a low-dimensional representation of the tumor genome was obtained. The proposed Copy Aberration Regional Mapping Analysis (CARMA) algorithm was applied to 2384 breast tumors from three breast cancer cohorts, revealing distinct copy number motifs in established molecular subtypes. A prognostic index combining the features predicted breast cancer specific survival better than both the genomic instability index (GII) and all commonly used clinical stratifications. CARMA offers effective comparison of tumor subgroups and extracts biologically and clinically relevant features from allele-specific copy number profiles.

Homozygous deletions are rare in cancers and often target tumour suppressor genes. Here, we build a compendium of 2218 primary tumours across 12 human cancer types and systematically screen for homozygous deletions, aiming to identify rare tumour suppressors. Our analysis defines 96 genomic regions recurrently targeted by homozygous deletions. These recurrent homozygous deletions occur either over tumour suppressors or over fragile sites, regions of increased genomic instability. We construct a statistical model that separates fragile sites from regions showing signatures of positive selection for homozygous deletions and identify candidate tumour suppressors within those regions. We find 16 established tumour suppressors and propose 27 candidate tumour suppressors. Several of these genes (including MGMT, RAD17, and USP44) show prior evidence of a tumour suppressive function. Other candidate tumour suppressors, such as MAFTRR, KIAA1551, and IGF2BP2, are novel. Our study demonstrates how rare tumour suppressors can be identified through copy number meta-analysis., Homozygous deletions are rare in cancers and often target tumour suppressor genes. Here, the authors conduct pan-cancer analyses and apply statistical modelling to identify 27 candidate tumour suppressors, including MAFTRR, KIAA1551, and IGF2BP2.

Homozygous deletions are rare in cancers and often target tumour suppressor genes. Here, we build a compendium of 2218 primary tumours across 12 human cancer types and systematically screen for homozygous deletions, aiming to identify rare tumour suppressors. Our analysis defines 96 genomic regions recurrently targeted by homozygous deletions. These recurrent homozygous deletions occur either over tumour suppressors or over fragile sites, regions of increased genomic instability. We construct a statistical model that separates fragile sites from regions showing signatures of positive selection for homozygous deletions and identify candidate tumour suppressors within those regions. We find 16 established tumour suppressors and propose 27 candidate tumour suppressors. Several of these genes (including MGMT, RAD17, and USP44) show prior evidence of a tumour suppressive function. Other candidate tumour suppressors, such as MAFTRR, KIAA1551, and IGF2BP2, are novel. Our study demonstrates how rare tumour suppressors can be identified through copy number meta-analysis.

Chromosomal instability is a well-defined hallmark of tumor aggressiveness and metastatic progression in colorectal cancer. The magnitude of genetic heterogeneity among distinct liver metastases from the same patient at the copy number level, as well as its relationship with chemotherapy exposure and patient outcome, remains unknown. We performed high-resolution DNA copy number analyses of 134 liver metastatic deposits from 45 colorectal cancer patients to assess: (i) intra-patient inter-metastatic genetic heterogeneity using a heterogeneity score based on pair-wise genetic distances among tumor deposits; and (ii) genomic complexity, defined as the proportion of the genome harboring aberrant DNA copy numbers. Results were analyzed in relation to the patients’ clinical course; previous chemotherapy exposure and outcome after surgical resection of liver metastases. We observed substantial variation in the level of intra-patient inter-metastatic heterogeneity. Heterogeneity was not associated with the number of metastatic lesions or their genomic complexity. In metachronous disease, heterogeneity was higher in patients previously exposed to chemotherapy. Importantly, intra-patient inter-metastatic heterogeneity was a strong prognostic determinant, stronger than known clinicopathological prognostic parameters. Patients with a low level of heterogeneity (below the median level) had a three-year progression-free and overall survival rate of 23% and 66% respectively, versus 5% and 18% for patients with a high level (hazard ratio0.4, 95% confidence interval 0.2–0.8, P = 0.01; and hazard ratio0.3,95% confidence interval 0.1–0.7, P = 0.007). A low patient-wise level of genomic complexity (below 25%) was also a favorable prognostic factor; however, the prognostic association of intra-patient heterogeneity was independent of genomic complexity in multivariable analyses. In conclusion, intra-patient inter-metastatic genetic heterogeneity is a pronounced feature of metastatic colorectal cancer, and the strong prognostic association reinforces its clinical relevance and places it as a key feature to be explored in future patient cohorts., Author Summary Liver metastasis from colorectal cancer confers a poor patient prognosis and is often manifested as multiple independent lesions. Clonal evolution is an important biological process in metastatic development, but the magnitude and clinical relevance of genetic heterogeneity among metastatic deposits in individual patients remains unknown. We describe for the first time a large variation among patients in the level of inter-metastatic heterogeneity at the DNA copy number level in liver metastases from colorectal cancer. We found this heterogeneity to be a biological feature independent both of the number of metastases per patient and of the extent of copy number aberrations (genomic complexity)of the metastases. Previous chemotherapy exposure was associated with a higher patient-wise level of heterogeneity in subsequent metastases. Importantly, we discovered inter-metastatic heterogeneity to be a key determinant of patient survival and a stronger prognostic factor than known clinicopathological parameters of metastatic colorectal cancer. This study reinforces the clinical relevance of tumor heterogeneity and we identify inter-metastatic heterogeneity as an important feature to explore in future cohorts of patients with metastatic colorectal cancer.

Background Cancer progression is associated with genomic instability and an accumulation of gains and losses of DNA. The growing variety of tools for measuring genomic copy numbers, including various types of array-CGH, SNP arrays and high-throughput sequencing, calls for a coherent framework offering unified and consistent handling of single- and multi-track segmentation problems. In addition, there is a demand for highly computationally efficient segmentation algorithms, due to the emergence of very high density scans of copy number. Results A comprehensive Bioconductor package for copy number analysis is presented. The package offers a unified framework for single sample, multi-sample and multi-track segmentation and is based on statistically sound penalized least squares principles. Conditional on the number of breakpoints, the estimates are optimal in the least squares sense. A novel and computationally highly efficient algorithm is proposed that utilizes vector-based operations in R. Three case studies are presented. Conclusions The R package is a software suite for segmentation of single- and multi-track copy number data using algorithms based on coherent least squares principles.