sCNAphase: using haplotype resolved read depth to genotype somatic copy number alterations from low cellularity aneuploid tumors

Tracing cancer evolution and heterogeneity using Hi-C

Chromosomal rearrangements can initiate and drive cancer progression, yet it has been challenging to evaluate their impact, especially in genetically heterogeneous solid cancers. To address this problem we developed HiDENSEC, a new computational framework for analyzing chromatin conformation capture in heterogeneous samples that can infer somatic copy number alterations, characterize large-scale chromosomal rearrangements, and estimate cancer cell fractions. After validating HiDENSEC with in silico and in vitro controls, we used it to characterize chromosome-scale evolution during melanoma progression in formalin-fixed tumor samples from three patients. The resulting comprehensive annotation of the genomic events includes copy number neutral translocations that disrupt tumor suppressor genes such as NF1, whole chromosome arm exchanges that result in loss of CDKN2A, and whole-arm copy-number neutral loss of homozygosity involving PTEN. These findings show that large-scale chromosomal rearrangements occur throughout cancer evolution and that characterizing these events yields insights into drivers of melanoma progression.

Accucopy: accurate and fast inference of allele-specific copy number alterations from low-coverage low-purity tumor sequencing data

BACKGROUND

Copy number alterations (CNAs), due to their large impact on the genome, have been an important contributing factor to oncogenesis and metastasis. Detecting genomic alterations from the shallow-sequencing data of a low-purity tumor sample remains a challenging task.

RESULTS

We introduce Accucopy, a method to infer total copy numbers (TCNs) and allele-specific copy numbers (ASCNs) from challenging low-purity and low-coverage tumor samples. Accucopy adopts many robust statistical techniques such as kernel smoothing of coverage differentiation information to discern signals from noise and combines ideas from time-series analysis and the signal-processing field to derive a range of estimates for the period in a histogram of coverage differentiation information. Statistical learning models such as the tiered Gaussian mixture model, the expectation-maximization algorithm, and sparse Bayesian learning were customized and built into the model. Accucopy is implemented in C++ /Rust, packaged in a docker image, and supports non-human samples, more at http://www.yfish.org/software/ .

CONCLUSIONS

We describe Accucopy, a method that can predict both TCNs and ASCNs from low-coverage low-purity tumor sequencing data. Through comparative analyses in both simulated and real-sequencing samples, we demonstrate that Accucopy is more accurate than Sclust, ABSOLUTE, and Sequenza.

Cyclin E2 Promotes Whole Genome Doubling in Breast Cancer

Genome doubling is an underlying cause of cancer cell aneuploidy and genomic instability, but few drivers have been identified for this process. Due to their physiological roles in the genome reduplication of normal cells, we hypothesised that the oncogenes cyclins E1 and E2 may be drivers of genome doubling in cancer. We show that both cyclin E1 (CCNE1) and cyclin E2 (CCNE2) mRNA are significantly associated with high genome ploidy in breast cancers. By live cell imaging and flow cytometry, we show that cyclin E2 overexpression promotes aberrant mitosis without causing mitotic slippage, and it increases ploidy with negative feedback on the replication licensing protein, Cdt1. We demonstrate that cyclin E2 localises with core preRC (pre-replication complex) proteins (MCM2, MCM7) on the chromatin of cancer cells. Low CCNE2 is associated with improved overall survival in breast cancers, and we demonstrate that low cyclin E2 protects from excess genome rereplication. This occurs regardless of p53 status, consistent with the association of high cyclin E2 with genome doubling in both p53 null/mutant and p53 wildtype cancers. In contrast, while cyclin E1 can localise to the preRC, its downregulation does not prevent rereplication, and overexpression promotes polyploidy via mitotic slippage. Thus, in breast cancer, cyclin E2 has a strong association with genome doubling, and likely contributes to highly proliferative and genomically unstable breast cancers.

Deep whole-genome sequencing of 3 cancer cell lines on 2 sequencing platforms

To test the performance of a new sequencing platform, develop an updated somatic calling pipeline and establish a reference for future benchmarking experiments, we performed whole-genome sequencing of 3 common cancer cell lines (COLO-829, HCC-1143 and HCC-1187) along with their matched normal cell lines to great sequencing depths (up to 278x coverage) on both Illumina HiSeqX and NovaSeq sequencing instruments. Somatic calling was generally consistent between the two platforms despite minor differences at the read level. We designed and implemented a novel pipeline for the analysis of tumor-normal samples, using multiple variant callers. We show that coupled with a high-confidence filtering strategy, the use of combination of tools improves the accuracy of somatic variant calling. We also demonstrate the utility of the dataset by creating an artificial purity ladder to evaluate the somatic pipeline and benchmark methods for estimating purity and ploidy from tumor-normal pairs. The data and results of the pipeline are made accessible to the cancer genomics community.