Rare de novo germline copy-number variation in testicular cancer.

Although heritable factors are an important determinant of risk of early-onset cancer, the majority of these malignancies appear to occur sporadically without identifiable risk factors. Germline de novo copy-number variations (CNVs) have been observed in sporadic neurocognitive and cardiovascular disorders. We explored this mechanism in 382 genomes of 116 early-onset cancer case-parent trios and unaffected siblings. Unique de novo germline CNVs were not observed in 107 breast or colon cancer trios or controls but were indeed found in 7% of 43 testicular germ cell tumor trios; this percentage exceeds background CNV rates and suggests a rare de novo genetic paradigm for susceptibility to some human malignancies.

Genome-wide copy number analysis of single cells.

Copy number variation (CNV) is increasingly recognized as an important contributor to phenotypic variation in health and disease. Most methods for determining CNV rely on admixtures of cells in which information regarding genetic heterogeneity is lost. Here we present a protocol that allows for the genome-wide copy number analysis of single nuclei isolated from mixed populations of cells. Single-nucleus sequencing (SNS), combines flow sorting of single nuclei on the basis of DNA content and whole-genome amplification (WGA); this is followed by next-generation sequencing to quantize genomic intervals in a genome-wide manner. Multiplexing of single cells is discussed. In addition, we outline informatic approaches that correct for biases inherent in the WGA procedure and allow for accurate determination of copy number profiles. All together, the protocol takes ∼3 d from flow cytometry to sequence-ready DNA libraries.

Reducing system noise in copy number data using principal components of self-self hybridizations.

Genomic copy number variation underlies genetic disorders such as autism, schizophrenia, and congenital heart disease. Copy number variations are commonly detected by array based comparative genomic hybridization of sample to reference DNAs, but probe and operational variables combine to create correlated system noise that degrades detection of genetic events. To correct for this we have explored hybridizations in which no genetic signal is expected, namely "self-self" hybridizations (SSH) comparing DNAs from the same genome. We show that SSH trap a variety of correlated system noise present also in sample-reference (test) data. Through singular value decomposition of SSH, we are able to determine the principal components (PCs) of this noise. The PCs themselves offer deep insights into the sources of noise, and facilitate detection of artifacts. We present evidence that linear and piecewise linear correction of test data with the PCs does not introduce detectable spurious signal, yet improves signal-to-noise metrics, reduces false positives, and facilitates copy number determination.

Tumour evolution inferred by single-cell sequencing.

Genomic analysis provides insights into the role of copy number variation in disease, but most methods are not designed to resolve mixed populations of cells. In tumours, where genetic heterogeneity is common, very important information may be lost that would be useful for reconstructing evolutionary history. Here we show that with flow-sorted nuclei, whole genome amplification and next generation sequencing we can accurately quantify genomic copy number within an individual nucleus. We apply single-nucleus sequencing to investigate tumour population structure and evolution in two human breast cancer cases. Analysis of 100 single cells from a polygenomic tumour revealed three distinct clonal subpopulations that probably represent sequential clonal expansions. Additional analysis of 100 single cells from a monogenomic primary tumour and its liver metastasis indicated that a single clonal expansion formed the primary tumour and seeded the metastasis. In both primary tumours, we also identified an unexpectedly abundant subpopulation of genetically diverse 'pseudodiploid' cells that do not travel to the metastatic site. In contrast to gradual models of tumour progression, our data indicate that tumours grow by punctuated clonal expansions with few persistent intermediates.

Novel genomic alterations and clonal evolution in chronic lymphocytic leukemia revealed by representational oligonucleotide microarray analysis (ROMA).

We examined copy number changes in the genomes of B cells from 58 patients with chronic lymphocytic leukemia (CLL) by using representational oligonucleotide microarray analysis (ROMA), a form of comparative genomic hybridization (CGH), at a resolution exceeding previously published studies. We observed at least 1 genomic lesion in each CLL sample and considerable variation in the number of abnormalities from case to case. Virtually all abnormalities previously reported also were observed here, most of which were indeed highly recurrent. We observed the boundaries of known events with greater clarity and identified previously undescribed lesions, some of which were recurrent. We profiled the genomes of CLL cells separated by the surface marker CD38 and found evidence of distinct subclones of CLL within the same patient. We discuss the potential applications of high-resolution CGH analysis in a clinical setting.

Abnormalities of the large ribosomal subunit protein, Rpl35a, in Diamond-Blackfan anemia.

Diamond-Blackfan anemia (DBA) is an inherited bone marrow failure syndrome characterized by anemia, congenital abnormalities, and cancer predisposition. Small ribosomal subunit genes RPS19, RPS24, and RPS17 are mutated in approximately one-third of patients. We used a candidate gene strategy combining high-resolution genomic mapping and gene expression microarray in the analysis of 2 DBA patients with chromosome 3q deletions to identify RPL35A as a potential DBA gene. Sequence analysis of a cohort of DBA probands confirmed involvement RPL35A in DBA. shRNA inhibition shows that Rpl35a is essential for maturation of 28S and 5.8S rRNAs, 60S subunit biogenesis, normal proliferation, and cell survival. Analysis of pre-rRNA processing in primary DBA lymphoblastoid cell lines demonstrated similar alterations of large ribosomal subunit rRNA in both RPL35A-mutated and some RPL35A wild-type patients, suggesting additional large ribosomal subunit gene defects are likely present in some cases of DBA. These data demonstrate that alterations of large ribosomal subunit proteins cause DBA and support the hypothesis that DBA is primarily the result of altered ribosomal function. The results also establish that haploinsufficiency of large ribosomal subunit proteins contributes to bone marrow failure and potentially cancer predisposition.

Novel patterns of genome rearrangement and their association with survival in breast cancer.

Representational Oligonucleotide Microarray Analysis (ROMA) detects genomic amplifications and deletions with boundaries defined at a resolution of approximately 50 kb. We have used this technique to examine 243 breast tumors from two separate studies for which detailed clinical data were available. The very high resolution of this technology has enabled us to identify three characteristic patterns of genomic copy number variation in diploid tumors and to measure correlations with patient survival. One of these patterns is characterized by multiple closely spaced amplicons, or "firestorms," limited to single chromosome arms. These multiple amplifications are highly correlated with aggressive disease and poor survival even when the rest of the genome is relatively quiet. Analysis of a selected subset of clinical material suggests that a simple genomic calculation, based on the number and proximity of genomic alterations, correlates with life-table estimates of the probability of overall survival in patients with primary breast cancer. Based on this sample, we generate the working hypothesis that copy number profiling might provide information useful in making clinical decisions, especially regarding the use or not of systemic therapies (hormonal therapy, chemotherapy), in the management of operable primary breast cancer with ostensibly good prognosis, for example, small, node-negative, hormone-receptor-positive diploid cases.

Representational oligonucleotide microarray analysis: a high-resolution method to detect genome copy number variation.

We have developed a methodology we call ROMA (representational oligonucleotide microarray analysis), for the detection of the genomic aberrations in cancer and normal humans. By arraying oligonucleotide probes designed from the human genome sequence, and hybridizing with "representations" from cancer and normal cells, we detect regions of the genome with altered "copy number." We achieve an average resolution of 30 kb throughout the genome, and resolutions as high as a probe every 15 kb are practical. We illustrate the characteristics of probes on the array and accuracy of measurements obtained using ROMA. Using this methodology, we identify variation between cancer and normal genomes, as well as between normal human genomes. In cancer genomes, we readily detect amplifications and large and small homozygous and hemizygous deletions. Between normal human genomes, we frequently detect large (100 kb to 1 Mb) deletions or duplications. Many of these changes encompass known genes. ROMA will assist in the discovery of genes and markers important in cancer, and the discovery of loci that may be important in inherited predispositions to disease.

A 9.1-kb gap in the genome reference map is shown to be a stable deletion/insertion polymorphism of ancestral origin.

We show a mute 9.1-kb gap in the human genome reference map, unraveled by RDA studies, to be a worldwide deletion/insertion polymorphism of stable type. The molecular and population data presented suggest its origin from a unique ancestral transposition event in chromosomal region 22q11.2, overlapping the IglambdaV genes at about 450 kb from the cluster of the IglambdaJ-C genes. These findings are not meant to be just another report of a polymorphic marker suitable for population studies. Rather, we wish to stress that a large number of inborn mute gaps may be spread all over the genome and that the many RDA-detected microdeletions already available are efficient tools for the discovery of this otherwise hidden category of genetic variation. Apart from their possible impact on expression of structural genes, mute gaps must be filled for the reference map of our genome to be truly completed.

DBC2, a candidate for a tumor suppressor gene involved in breast cancer.

A previously uncharacterized gene, DBC2 (deleted in breast cancer), was cloned from a homozygously deleted region at human chromosome 8p21. DBC2 contains a highly conserved RAS domain and two putative protein interacting domains. Our analyses indicate that DBC2 is the best candidate tumor suppressor gene from this region. It lies within the epicenter of the deletions and is homozygously deleted in 3.5% (7/200) of breast tumors. Mutation analysis of DBC2 led to discovery of two instances of somatic missense mutations in breast tumor specimens, whereas no missense mutations were found in other candidates from the region. Unlike other genes in the region, expression of DBC2 is often extinguished in breast cancer cells or tissues. Moreover, our functional analysis revealed that DBC2 expression in breast cancer cells lacking DBC2 transcripts causes growth inhibition. By contrast, expression of a somatic mutant discovered in a breast cancer specimen does not suppress the growth of breast cancer cells.