Frequent copy number gains of SLC2A3 and ETV1 in testicular embryonal carcinomas.

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.

The MCL35 gene expression proliferation assay predicts high-risk MCL patients in a Norwegian cohort of younger patients given intensive first line therapy.

Patients with mantle cell lymphoma (MCL) generally have a dismal prognosis. Intensified induction treatment with rituximab and high dose cytarabine (R_HDAC), and consolidation with high-dose therapy with autologous stem cell support has resulted in 10-year overall survival (OS) higher than 60%. However, the clinical course varies. Diagnostic tools capable of stratifying patients include the MCL International Prognostic Index (MIPI), gene expression-based proliferation signature, Ki-67 proliferation index or tumour cell morphology. Here, we tested the performance of a newly developed Nanostring-based RNA expression-based proliferation assay (MCL35) on formalin-fixed paraffin-embedded tumour tissue from younger patients recruited in or treated according to Nordic MCL protocols compared to the prognosticators listed above. Seventy-four patients were included and the assay performed well in all cases except four, which had inadequate RNA quality. The patients were evenly distributed in the MCL35 low-, intermediate- and high-risk categories. MCL35 low- and intermediate- risk groups had overlapping progression-free survival (PFS), while patients in the high-risk category had significantly inferior PFS. Combining MCL35 with MIPI or the MIPI-C (MIPI with the addition of binary Ki67 score +/-30%) showed a better discrimination than either assessment alone. In conclusion, the MCL35 assay alone or combined with MIPI or MIPI-C scores can identify patients who still have a dismal outcome despite intensified treatment.

Metabolic clusters of breast cancer in relation to gene- and protein expression subtypes.

BACKGROUND: The heterogeneous biology of breast cancer leads to high diversity in prognosis and response to treatment, even for patients with similar clinical diagnosis, histology, and stage of disease. Identifying mechanisms contributing to this heterogeneity may reveal new cancer targets or clinically relevant subgroups for treatment stratification. In this study, we have merged metabolite, protein, and gene expression data from breast cancer patients to examine the heterogeneity at a molecular level. METHODS: The study included primary tumor samples from 228 non-treated breast cancer patients. High-resolution magic-angle spinning magnetic resonance spectroscopy (HR MAS MRS) was performed to extract the tumors metabolic profiles further used for hierarchical cluster analysis resulting in three significantly different metabolic clusters (Mc1, Mc2, and Mc3). The clusters were further combined with gene and protein expression data. RESULTS: Our result revealed distinct differences in the metabolic profile of the three metabolic clusters. Among the most interesting differences, Mc1 had the highest levels of glycerophosphocholine (GPC) and phosphocholine (PCho), Mc2 had the highest levels of glucose, and Mc3 had the highest levels of lactate and alanine. Integrated pathway analysis of metabolite and gene expression data uncovered differences in glycolysis/gluconeogenesis and glycerophospholipid metabolism between the clusters. All three clusters had significant differences in the distribution of protein subtypes classified by the expression of breast cancer-related proteins. Genes related to collagens and extracellular matrix were downregulated in Mc1 and consequently upregulated in Mc2 and Mc3, underpinning the differences in protein subtypes within the metabolic clusters. Genetic subtypes were evenly distributed among the three metabolic clusters and could therefore contribute to additional explanation of breast cancer heterogeneity. CONCLUSIONS: Three naturally occurring metabolic clusters of breast cancer were detected among primary tumors from non-treated breast cancer patients. The clusters expressed differences in breast cancer-related protein as well as genes related to extracellular matrix and metabolic pathways known to be aberrant in cancer. Analyses of metabolic activity combined with gene and protein expression provide new information about the heterogeneity of breast tumors and, importantly, the metabolic differences infer that the clusters may be susceptible to different metabolically targeted drugs.

Canine Mammary Tumours Are Affected by Frequent Copy Number Aberrations, including Amplification of MYC and Loss of PTEN.

BACKGROUND: Copy number aberrations frequently occur during the development of many cancers. Such events affect dosage of involved genes and may cause further genomic instability and progression of cancer. In this survey, canine SNP microarrays were used to study 117 canine mammary tumours from 69 dogs. RESULTS: We found a high occurrence of copy number aberrations in canine mammary tumours, losses being more frequent than gains. Increased frequency of aberrations and loss of heterozygosity were positively correlated with increased malignancy in terms of histopathological diagnosis. One of the most highly recurrently amplified regions harbored the MYC gene. PTEN was located to a frequently lost region and also homozygously deleted in five tumours. Thus, deregulation of these genes due to copy number aberrations appears to be an important event in canine mammary tumour development. Other potential contributors to canine mammary tumour pathogenesis are COL9A3, INPP5A, CYP2E1 and RB1. The present study also shows that a more detailed analysis of chromosomal aberrations associated with histopathological parameters may aid in identifying specific genes associated with canine mammary tumour progression. CONCLUSIONS: The high frequency of copy number aberrations is a prominent feature of canine mammary tumours as seen in other canine and human cancers. Our findings share several features with corresponding studies in human breast tumours and strengthen the dog as a suitable model organism for this disease.

Glycan-related gene expression signatures in breast cancer subtypes; relation to survival.

Alterations in glycan structures are early signs of malignancy and have recently been proposed to be in part a driving force behind malignant transformation. Here, we explore whether differences in expression of genes related to the process of glycosylation exist between breast carcinoma subtypes - and look for their association to clinical parameters. Five expression datasets of 454 invasive breast carcinomas, 31 ductal carcinomas in situ (DCIS), and 79 non-malignant breast tissue samples were analysed. Results were validated in 1960 breast carcinomas. 419 genes encoding glycosylation-related proteins were selected. The DCIS samples appeared expression-wise similar to carcinomas, showing altered gene expression related to glycosaminoglycans (GAGs) and N-glycans when compared to non-malignant samples. In-situ lesions with different aggressiveness potentials demonstrated changes in glycosaminoglycan sulfation and adhesion proteins. Subtype-specific expression patterns revealed down-regulation of genes encoding glycan-binding proteins in the luminal A and B subtypes. Clustering basal-like samples using a consensus list of genes differentially expressed across discovery datasets produced two clusters with significantly differing prognosis in the validation dataset. Finally, our analyses suggest that glycolipids may play an important role in carcinogenesis of breast tumors - as demonstrated by association of B3GNT5 and UGCG genes to patient survival. In conclusion, most glycan-specific changes occur early in the carcinogenic process. We have identified glycan-related alterations specific to breast cancer subtypes including a prognostic signature for two basal-like subgroups. Future research in this area may potentially lead to markers for better prognostication and treatment stratification of breast cancer patients.

The multitude of molecular analyses in cancer: the opening of Pandora's box.

The availability of large amounts of molecular data of unprecedented depth and width has instigated new paths of interdisciplinary activity in cancer research. Translation of such information to allow its optimal use in cancer therapy will require molecular biologists to embrace statistical and computational concepts and models. Progress in science has been and should be driven by our innate curiosity. This is the human quality that led Pandora to open the forbidden box, and like her, we do not know the nature or consequences of the output resulting from our actions. Throughout history, ground-breaking scientific achievements have been closely linked to advances in technology. The microscope and the telescope are examples of inventions that profoundly increased the amount of observable features that further led to paradigmatic shifts in our understanding of life and the Universe. In cell biology, the microscope revealed details of different types of tissue and their cellular composition; it revealed cells, their structures and their ability to divide, develop and die. Further, the molecular compositions of individual cell types were revealed gradually by generations of scientists. For each level of insight gained, new mathematical and statistical descriptive and analytical tools were needed (Figure 1a). The integration of knowledge of ever-increasing depth and width in order to develop useful therapies that can prevent and cure diseases such as cancer will continue to require the joint effort of scientists in biology, medicine, statistics, mathematics and computation. Here, we discuss some major challenges that lie ahead of us and why we believe that a deeper integration of biology and medicine with mathematics and statistics is required to gain the most from the diverse and extensive body of data now being generated. We also argue that to take full advantage of current technological opportunities, we must explore biomarkers using clinical studies that are optimally designed for this purpose. The need for a tight interdisciplinary collaboration has never been stronger.

Glycan gene expression signatures in normal and malignant breast tissue; possible role in diagnosis and progression.

Glycosylation is the stepwise procedure of covalent attachment of oligosaccharide chains to proteins or lipids, and alterations in this process have been associated with malignant transformation. Simultaneous analysis of the expression of all glycan-related genes clearly gives the advantage of enabling a comprehensive view of the genetic background of the glycobiological changes in cancer cells. Studies focusing on the expression of the whole glycome have now become possible, which prompted us to review the present knowledge on glycosylation in relation to breast cancer diagnosis and progression, in the light of available expression data from tumors and breast tissue of healthy individuals. We used various data resources to select a set of 419 functionally relevant genes involved in synthesis, degradation and binding of N-linked and O-linked glycans, Lewis antigens, glycosaminoglycans (chondroitin, heparin and keratan sulfate in addition to hyaluronan) and glycosphingolipids. Such glycans are involved in a number of processes relevant to carcinogenesis, including regulation of growth factors/growth factor receptors, cell-cell adhesion and motility as well as immune system modulation. Expression analysis of these glycan-related genes revealed that mRNA levels for many of them differ significantly between normal and malignant breast tissue. An associative analysis of these genes in the context of current knowledge of their function in protein glycosylation and connection(s) to cancer indicated that synthesis, degradation and adhesion mediated by glycans may be altered drastically in mammary carcinomas. Although further analysis is needed to assess how changes in mRNA levels of glycan genes influence a cell's glycome and the precise role that such altered glycan structures play in the pathogenesis of the disease, lessons drawn from this study may help in determining directions for future research in the rapidly-developing field of glycobiology.