Pan-cancer driver copy number alterations identified by joint expression/CNA data analysis

Completing a genomic characterisation of microscopic tumour samples with copy number

BACKGROUND

Genomic insights in settings where tumour sample sizes are limited to just hundreds or even tens of cells hold great clinical potential, but also present significant technical challenges. We previously developed the DigiPico sequencing platform to accurately identify somatic mutations from such samples.

RESULTS

Here, we complete this genomic characterisation with copy number. We present a novel protocol, PicoCNV, to call allele-specific somatic copy number alterations from picogram quantities of tumour DNA. We find that PicoCNV provides exactly accurate copy number in 84% of the genome for even the smallest samples, and demonstrate its clinical potential in maintenance therapy.

CONCLUSIONS

PicoCNV complements our existing platform, allowing for accurate and comprehensive genomic characterisations of cancers in settings where only microscopic samples are available.

The Revelation of Continuously Organized, Co-Overexpressed Protein-Coding Genes with Roles in Cellular Communications in Breast Cancer

Many human cancers, including breast cancer, are polygenic and involve the co-dysregulation of multiple regulatory molecules and pathways. Though the overexpression of genes and amplified chromosomal regions have been closely linked in breast cancer, the notion of the co-upregulation of genes at a single locus remains poorly described. Here, we describe the co-overexpression of 34 continuously organized protein-coding genes with diverse functions at 8q.24.3(143437655-144326919) in breast and other cancer types, the CanCord34 genes. In total, 10 out of 34 genes have not been reported to be overexpressed in breast cancer. Interestingly, the overexpression of CanCord34 genes is not necessarily associated with genomic amplification and is independent of hormonal or HER2 status in breast cancer. CanCord34 genes exhibit diverse known and predicted functions, including enzymatic activities, cell viability, multipotency, cancer stem cells, and secretory activities, including extracellular vesicles. The co-overexpression of 33 of the CanCord34 genes in a multivariant analysis was correlated with poor survival among patients with breast cancer. The analysis of the genome-wide RNAi functional screening, cell dependency fitness, and breast cancer stem cell databases indicated that three diverse overexpressed CanCord34 genes, including a component of spliceosome PUF60, a component of exosome complex EXOSC4, and a ribosomal biogenesis factor BOP1, shared roles in cell viability, cell fitness, and stem cell phenotypes. In addition, 17 of the CanCord34 genes were found in the microvesicles (MVs) secreted from the mesenchymal stem cells that were primed with MDA-MB-231 breast cancer cells. Since these MVs were important in the chemoresistance and dedifferentiation of breast cancer cells into cancer stem cells, these findings highlight the significance of the CanCord34 genes in cellular communications. In brief, the persistent co-overexpression of CanCord34 genes with diverse functions can lead to the dysregulation of complementary functions in breast cancer. In brief, the present study provides new insights into the polygenic nature of breast cancer and opens new research avenues for basic, preclinical, and therapeutic studies in human cancer.

CiberAMP: An R Package to Identify Differential mRNA Expression Linked to Somatic Copy Number Variations in Cancer Datasets

Simple Summary

The ability to establish accurate correlations between the number of copies of genes and the expression levels of their encoded transcripts remains a challenge despite the extensive progress made in the understanding of the genome of cancer cells. Here, we describe a new algorithm that does so by integrating both genomics and transcriptomics data from the Cancer Genome Atlas. In addition to explaining the step-by-step basis of this new method, we provide examples of how this new algorithm can help identify functionally meaningful gene copy alterations that are recurrently detected in cancer patients.

Abstract

Somatic copy number variations (SCNVs) are genetic alterations frequently found in cancer cells. These genetic alterations can lead to concomitant perturbations in the expression of the genes included in them and, as a result, promote a selective advantage to cancer cells. However, this is not always the case. Due to this, it is important to develop in silico tools to facilitate the accurate identification and functional cataloging of gene expression changes associated with SCNVs from pan-cancer data. Here, we present a new R-coded tool, designated as CiberAMP, which utilizes genomic and transcriptomic data contained in the Cancer Genome Atlas (TCGA) to identify such events. It also includes information on the genomic context in which such SCNVs take place. By doing so, CiberAMP provides clues about the potential functional relevance of each of the SCNV-associated gene expression changes found in the interrogated tumor samples. The main features and advantages of this new algorithm are illustrated using glioblastoma data from the TCGA database.

Copy number alterations and epithelial‑mesenchymal transition genes in diffuse and intestinal gastric cancers in Mexican patients

Gastric cancer (GC) is a common malignancy with the highest mortality rate among diseases of the digestive system, worldwide. The present study of GC alterations is crucial to the understanding of tumor biology and the establishment of important aspects of cancer prognosis and treatment response. In the present study, DNA from Mexican patients with diffuse GC (DGC), intestinal GC (IGC) or non‑atrophic gastritis (NAG; control) was purified and whole‑genome analysis was performed with high‑density arrays. Shared and unique copy number alterations (CNA) were identified between the different tissues involving key genes and signaling pathways associated with cancer. This led to the molecular distinction and identification of the most relevant molecular functions to be identified. A more detailed bioinformatics analysis of epithelial‑mesenchymal transition (EMT) genes revealed that the altered network associated with chromosomal alterations included 11 genes that were shared between DGC, IGC and NAG, as well as 19 DGC‑ and 7 IGC‑exclusive genes. Furthermore, the main molecular functions included adhesion, angiogenesis, migration, metastasis, morphogenesis, proliferation and survival. The present study provided the first whole‑genome high‑density array analysis in Mexican patients with GC and revealed shared and exclusive CNA‑associated genes in DGC and IGC. In addition, a bioinformatics‑predicted network was generated, focusing on CNA‑altered genes associated with EMT and the hallmarks of cancer, as well as precancerous alterations that may lead to GC. Molecular signatures of diffuse and intestinal GC, predicted bioinformatically, involve common and distinct CNA‑EMT genes related to the hallmarks of cancer that are potential candidates for screening biomarkers of GC, including early stages.

27-Hydroxycholesterol, The Estrogen Receptor Modulator, Alters DNA Methylation in Breast Cancer

27-hydroxycholesterol (27-HC) is the first known endogenous selective estrogen receptor modulator (SERM), and its elevation from normal levels is closely associated with breast cancer. A plethora of evidence suggests that aberrant epigenetic signatures in breast cancer cells can result in differential responses to various chemotherapeutics and often leads to the development of resistant cancer cells. Such aberrant epigenetic changes are mostly dictated by the microenvironment. The local concentration of oxygen and metabolites in the microenvironment of breast cancer are known to influence the development of breast cancer. Hence, we hypothesized that 27-HC, an oxysterol, which has been shown to induce breast cancer progression via estrogen receptor alpha (ERα) and liver X receptor (LXR) and by modulating immune cells, may also induce epigenetic changes. For deciphering the same, we treated the estrogen receptor-positive cells with 27-HC and identified DNA hypermethylation on a subset of genes by performing DNA bisulfite sequencing. The genes that showed significant DNA hypermethylation were phosphatidylserine synthase 2 (PTDSS2), MIR613, indoleamine 2,3-dioxygenase 1 (IDO1), thyroid hormone receptor alpha (THRA), dystrotelin (DTYN), and mesoderm induction early response 1, family member 3 (MIER). Furthermore, we found that 27-HC weakens the DNMT3B association with the ERα in MCF-7 cells. This study reports that 27-HC induces aberrant DNA methylation changes on the promoters of a subset of genes through modulation of ERα and DNMT3B complexes to induce the local DNA methylation changes, which may dictate drug responses and breast cancer development.