BackgroundFirst-generation molecular profiles for human breast cancers have enabled the identification of features that can predict therapeutic response; however, little is known about how the various data types can best be combined to yield optimal predictors. Collections of breast cancer cell lines mirror many aspects of breast cancer molecular pathobiology, and measurements of their omic and biological therapeutic responses are well-suited for development of strategies to identify the most predictive molecular feature sets.ResultsWe used least squares-support vector machines and random forest algorithms to identify molecular features associated with responses of a collection of 70 breast cancer cell lines to 90 experimental or approved therapeutic agents. The datasets analyzed included measurements of copy number aberrations, mutations, gene and isoform expression, promoter methylation and protein expression. Transcriptional subtype contributed strongly to response predictors for 25% of compounds, and adding other molecular data types improved prediction for 65%. No single molecular dataset consistently out-performed the others, suggesting that therapeutic response is mediated at multiple levels in the genome. Response predictors were developed and applied to TCGA data, and were found to be present in subsets of those patient samples.ConclusionsThese results suggest that matching patients to treatments based on transcriptional subtype will improve response rates, and inclusion of additional features from other profiling data types may provide additional benefit. Further, we suggest a systems biology strategy for guiding clinical trials so that patient cohorts most likely to respond to new therapies may be more efficiently identified.

Squamous cell carcinomas (SCCs) are one of the most frequent forms of human malignancy, but, other than TP53 mutations, few causative somatic aberrations have been identified. We identified NOTCH1 or NOTCH2 mutations in ∼75% of cutaneous SCCs and in a lesser fraction of lung SCCs, defining a spectrum for the most prevalent tumor suppressor specific to these epithelial malignancies. Notch receptors normally transduce signals in response to ligands on neighboring cells, regulating metazoan lineage selection and developmental patterning. Our findings therefore illustrate a central role for disruption of microenvironmental communication in cancer progression. NOTCH aberrations include frameshift and nonsense mutations leading to receptor truncations as well as point substitutions in key functional domains that abrogate signaling in cell-based assays. Oncogenic gain-of-function mutations in NOTCH1 commonly occur in human T-cell lymphoblastic leukemia/lymphoma and B-cell chronic lymphocytic leukemia. The bifunctional role of Notch in human cancer thus emphasizes the context dependency of signaling outcomes and suggests that targeted inhibition of the Notch pathway may induce squamous epithelial malignancies.cancer genetics | genomic | cellular signaling

Alteration in genes which takes place during malignant conversion and progression could be potential targets for gene therapy. We previously identified REIC/Dkk-3 as a gene whose expression is reduced in many human cancers. Here, we showed that expression of REIC/Dkk-3 was consistently reduced in human prostate cancer tissues in a stagedependent manner. Forced expression of REIC/Dkk-3 induced apoptosis in human prostate cancer cell lines lacking endogenous REIC/Dkk-3 expression but not in REIC/Dkk-3-proficient normal prostate epithelial and stromal cells. The apoptosis involved c-Jun-NH 2 -kinase activation, mitochondrial translocation of Bax, and reduction of Bcl-2. A single injection of an adenovirus vector carrying REIC/Dkk-3 showed a dramatic antitumor effect on a xenotransplanted human prostate cancer. Thus, REIC/Dkk-3 could be a novel target for gene-based therapy of prostate cancer. (Cancer Res 2005; 65(21): 9617-22)

Timely intervention for cancer requires knowledge of its earliest genetic aberrations. Sequencing of tumors and their metastases reveals numerous abnormalities occurring late in progression. A means to temporally order aberrations in a single cancer, rather than inferring them from serially acquired samples, would define changes preceding even clinically evident disease. We integrate DNA sequence and copy number information to reconstruct the order of abnormalities as individual tumors evolve for two separate cancer types. We detect vast, unreported expansion of simple mutation sharply demarcated by recombinative loss of the second copy of TP53 in cutaneous squamous cell carcinomas (cSCCs) and serous ovarian adenocarcinomas, in the former surpassing 50 mutations per megabase. In cSCCs, we also report diverse secondary mutations in known and novel oncogenic pathways, illustrating how such expanded mutagenesis directly promotes malignant progression. These results reframe paradigms in which TP53 mutation is required later, to bypass senescence induced by driver oncogenes.

Purpose: One of the main challenges of lung cancer research is identifying patients at high risk for recurrence after surgical resection. Simple, accurate, and reproducible methods of evaluating individual risks of recurrence are needed. Experimental Design: Based on a combined analysis of time-to-recurrence data, censoring information, and microarray data from a set of 138 patients, we selected statistically significant genes thought to be predictive of disease recurrence. The number of genes was further reduced by eliminating those whose expression levels were not reproducible by real-time quantitative PCR. Within these variables, a recurrence prediction model was constructed using Cox proportional hazard regression and validated via two independent cohorts (n = 56 and n = 59). Results: After performing a log-rank test of the microarray data and successively selecting genes based on real-time quantitative PCR analysis, the most significant 18 genes had P values of <0.05.After subsequent stepwise variable selection based on gene expression information and clinical variables, the recurrence prediction model consisted of six genes (CALB1, MMP7, SLC1A7, GSTA1, CCL19, and IFI44). Two pathologic variables, pStage and cellular differentiation, were developed. Validation by two independent cohorts confirmed that the proposed model is significantly accurate (P = 0.0314 and 0.0305, respectively). The predicted median recurrence-free survival times for each patient correlated well with the actual data. Conclusions: We have developed an accurate, technically simple, and reproducible method for predicting individual recurrence risks. This model would potentially be useful in developing customized strategies for managing lung cancer.

No abstract

The receptor for advanced glycation end products (RAGE) is thought to be involved in the pathogenesis of a broad range of inflammatory, degenerative and hyperproliferative diseases. It binds to diverse ligands and activates multiple intracellular signaling pathways. Despite these pivotal functions, molecular events just downstream of ligand-activated RAGE have been surprisingly unknown. Here we show that the cytoplasmic domain of RAGE is phosphorylated at Ser391 by PKCζ upon binding of ligands. TIRAP and MyD88, which are known to be adaptor proteins for Toll-like receptor-2 and -4 (TLR2/4), bound to the phosphorylated RAGE and transduced a signal to downstream molecules. Blocking of the function of TIRAP and MyD88 largely abrogated intracellular signaling from ligand-activated RAGE. Our findings indicate that functional interaction between RAGE and TLRs coordinately regulates inflammation, immune response and other cellular functions.

Summary Somatic mutations in cancer are more frequent in heterochromatic and late-replicating regions of the genome. We report that regional disparities in mutation density are virtually abolished within transcriptionally silent genomic regions of cutaneous squamous cell carcinomas (cSCCs) arising in an XPC−/− background. XPC−/− cells lack global genome nucleotide excision repair (GG-NER), thus establishing differential access of DNA repair machinery within chromatin-rich regions of the genome as the primary cause for the regional disparity. Strikingly, we find that increasing levels of transcription reduce mutation prevalence on both strands of gene bodies embedded within H3K9me3-dense regions, and only to those levels observed in H3K9me3-sparse regions, also in an XPC-dependent manner. Therefore, transcription appears to reduce mutation prevalence specifically by relieving the constraints imposed by chromatin structure on DNA repair. We model this novel relationship between transcription, chromatin state and DNA repair, revealing a new, personalized determinant of cancer risk.