Gene expression changes in an animal melanoma model correlate with aggressiveness of human melanoma metastases.

Metastasis is the deadliest phase of cancer progression. Experimental models using immunodeficient mice have been used to gain insights into the mechanisms of metastasis. We report here the identification of a "metastasis aggressiveness gene expression signature" derived using human melanoma cells selected based on their metastatic potentials in a xenotransplant metastasis model. Comparison with expression data from human melanoma patients shows that this metastasis gene signature correlates with the aggressiveness of melanoma metastases in human patients. Many genes encoding secreted and membrane proteins are included in the signature, suggesting the importance of tumor-microenvironment interactions during metastasis.

Novel pheochromocytoma susceptibility loci identified by integrative genomics.

Pheochromocytomas are catecholamine-secreting tumors that result from mutations of at least six different genes as components of distinct autosomal dominant disorders. However, there remain familial occurrences of pheochromocytoma without a known genetic defect. We describe here a familial pheochromocytoma syndrome consistent with digenic inheritance identified through a combination of global genomics strategies. Multipoint parametric linkage analysis revealed identical LOD scores of 2.97 for chromosome 2cen and 16p13 loci. A two-locus parametric linkage analysis produced maximum LOD score of 5.16 under a double recessive multiplicative model, suggesting that both loci are required to develop the disease. Allele-specific loss of heterozygosity (LOH) was detected only at the chromosome 2 locus in all tumors from this family, consistent with a tumor suppressor gene. Four additional pheochromocytomas with a similar genetic pattern were identified through transcription profiling and helped refine the chromosome 2 locus. High-density LOH mapping with single nucleotide polymorphism-based array identified a total of 18 of 62 pheochromocytomas with LOH within the chromosome 2 region, which further narrowed down the locus to <2 cM. This finding provides evidence for two novel susceptibility loci for pheochromocytoma and adds a recessive digenic trait to the increasingly broad genetic heterogeneity of these tumors. Similarly, complex traits may also be involved in other familial cancer syndromes.

A HIF1alpha regulatory loop links hypoxia and mitochondrial signals in pheochromocytomas.

Pheochromocytomas are neural crest-derived tumors that arise from inherited or sporadic mutations in at least six independent genes. The proteins encoded by these multiple genes regulate distinct functions. We show here a functional link between tumors with VHL mutations and those with disruption of the genes encoding for succinate dehydrogenase (SDH) subunits B (SDHB) and D (SDHD). A transcription profile of reduced oxidoreductase is detected in all three of these tumor types, together with an angiogenesis/hypoxia profile typical of VHL dysfunction. The oxidoreductase defect, not previously detected in VHL-null tumors, is explained by suppression of the SDHB protein, a component of mitochondrial complex II. The decrease in SDHB is also noted in tumors with SDHD mutations. Gain-of-function and loss-of-function analyses show that the link between hypoxia signals (via VHL) and mitochondrial signals (via SDH) is mediated by HIF1alpha. These findings explain the shared features of pheochromocytomas with VHL and SDH mutations and suggest an additional mechanism for increased HIF1alpha activity in tumors.

Critical role of CDK2 for melanoma growth linked to its melanocyte-specific transcriptional regulation by MITF.

The genomic organization of the CDK2 gene, which overlaps the melanocyte-specific gene SILV/PMEL17, poses an interesting regulatory challenge. We show that, despite its ubiquitous expression, CDK2 exhibits tissue-specific regulation by the essential melanocyte lineage transcription factor MITF. In addition, functional studies revealed this regulation to be critical for maintaining CDK2 kinase activity and growth of melanoma cells. Expression levels of MITF and CDK2 are tightly correlated in primary melanoma specimens and predict susceptibility to the CDK2 inhibitor roscovitine. CDK2 depletion suppressed growth and cell cycle progression in melanoma, but not other cancers, corroborating previous results. Collectively, these data indicate that CDK2 activity in melanoma is largely maintained at the transcriptional level by MITF, and unlike other malignancies, it may be a suitable drug target in melanoma.

A molecular signature of metastasis in primary solid tumors.

Metastasis is the principal event leading to death in individuals with cancer, yet its molecular basis is poorly understood. To explore the molecular differences between human primary tumors and metastases, we compared the gene-expression profiles of adenocarcinoma metastases of multiple tumor types to unmatched primary adenocarcinomas. We found a gene-expression signature that distinguished primary from metastatic adenocarcinomas. More notably, we found that a subset of primary tumors resembled metastatic tumors with respect to this gene-expression signature. We confirmed this finding by applying the expression signature to data on 279 primary solid tumors of diverse types. We found that solid tumors carrying the gene-expression signature were most likely to be associated with metastasis and poor clinical outcome (P < 0.03). These results suggest that the metastatic potential of human tumors is encoded in the bulk of a primary tumor, thus challenging the notion that metastases arise from rare cells within a primary tumor that have the ability to metastasize.

Diffuse large B-cell lymphoma outcome prediction by gene-expression profiling and supervised machine learning.

Diffuse large B-cell lymphoma (DLBCL), the most common lymphoid malignancy in adults, is curable in less than 50% of patients. Prognostic models based on pre-treatment characteristics, such as the International Prognostic Index (IPI), are currently used to predict outcome in DLBCL. However, clinical outcome models identify neither the molecular basis of clinical heterogeneity, nor specific therapeutic targets. We analyzed the expression of 6,817 genes in diagnostic tumor specimens from DLBCL patients who received cyclophosphamide, adriamycin, vincristine and prednisone (CHOP)-based chemotherapy, and applied a supervised learning prediction method to identify cured versus fatal or refractory disease. The algorithm classified two categories of patients with very different five-year overall survival rates (70% versus 12%). The model also effectively delineated patients within specific IPI risk categories who were likely to be cured or to die of their disease. Genes implicated in DLBCL outcome included some that regulate responses to B-cell-receptor signaling, critical serine/threonine phosphorylation pathways and apoptosis. Our data indicate that supervised learning classification techniques can predict outcome in DLBCL and identify rational targets for intervention.