Non-small cell lung cancer (NSCLC) has a 5-y survival rate of ∼16%, with most deaths associated with uncontrolled metastasis. We screened for stem cell identity-related genes preferentially expressed in a panel of cell lines with high versus low metastatic potential, derived from NSCLC tumors of Kras LA1/+ ;P53 R172HΔG/+ (KP) mice. The Musashi-2 (MSI2) protein, a regulator of mRNA translation, was consistently elevated in metastasis-competent cell lines. MSI2 was overexpressed in 123 human NSCLC tumor specimens versus normal lung, whereas higher expression was associated with disease progression in an independent set of matched normal/primary tumor/lymph node specimens. Depletion of MSI2 in multiple independent metastatic murine and human NSCLC cell lines reduced invasion and metastatic potential, independent of an effect on proliferation. MSI2 depletion significantly induced expression of proteins associated with epithelial identity, including tight junction proteins [claudin 3 (CLDN3), claudin 5 (CLDN5), and claudin 7 (CLDN7)] and down-regulated direct translational targets associated with epithelial-mesenchymal transition, including the TGF-β receptor 1 (TGFβR1), the small mothers against decapentaplegic homolog 3 (SMAD3), and the zinc finger proteins SNAI1 (SNAIL) and SNAI2 (SLUG). Overexpression of TGFβRI reversed the loss of invasion associated with MSI2 depletion, whereas overexpression of CLDN7 inhibited MSI2-dependent invasion. Unexpectedly, MSI2 depletion reduced E-cadherin expression, reflecting a mixed epithelialmesenchymal phenotype. Based on this work, we propose that MSI2 provides essential support for TGFβR1/SMAD3 signaling and contributes to invasive adenocarcinoma of the lung and may serve as a predictive biomarker of NSCLC aggressiveness.on-small cell lung cancer (NSCLC) is the leading cause of cancer-related deaths in the world (1). Approximately 7% of individuals born in the United States in 2013 will ultimately be diagnosed with lung cancer, and 160,000 die from this disease each year (1). The 5-y survival rate for lung cancer is around 16% of diagnosed cases (2). Much of the lethality of lung cancer is due to frequent diagnosis of the malignancy at the metastatic stage, when fundamental changes in tumor biology cause the disease to be refractory to many treatments. A better understanding of the biological processes that promote NSCLC metastasis promises to further improve clinical care of the patients. Kras LA1/+ ;P53 R172HΔG/+ (KP) mice provide a useful and wellvalidated model for the study of NSCLC metastasis. These mice combine a mutant p53 allele (p53 R175HΔG) with an activating KrasG12D allele (Kras LA1 ) (3), leading to development of adenocarcinomas resembling human NSCLC, which are often characterized by mutation of KRAS (∼30%) (4) and loss of TP53 (∼60%) (5). Many of the KP tumors metastasize to sites commonly seen in NSCLC patients (3). These features make the KP murine model a useful tool with which to evaluate factors that underlie NSCLC metastasis. Among the pathways activated...

Annually, there are 1.6 million new cases of cancer and nearly 600,000 cancer deaths in the United States alone. The public health burden associated with these numbers has motivated enormous research efforts into understanding the root causes of cancer. These efforts have led to the recognition that between 40% and 45% of cancers are associated with preventable risk factors and, importantly, have identified specific molecular mechanisms by which these exposures modify human physiology to induce or promote cancer. The increasingly refined knowledge of these mechanisms, which we summarize here, emphasizes the need for greater efforts toward primary cancer prevention through mitigation of modifiable risk factors. It also suggests exploitable avenues for improved secondary prevention (which includes the development of therapeutics designed for cancer interception and enhanced techniques for noninvasive screening and early detection) based on detailed knowledge of early neoplastic pathobiology. Such efforts would complement the current emphasis on the development of therapeutic approaches to treat established cancers and are likely to result in far greater gains in reducing morbidity and mortality.

Head and neck squamous cell carcinoma (HNSCC) is the sixth most common cancer worldwide and is frequently impervious to curative treatment efforts. Similar to other cancers associated with prolonged exposure to carcinogens, HNSCCs often have a high burden of mutations, contributing to substantial inter- and intra-tumor heterogeneity. The heterogeneity of this malignancy is further increased by the rising rate of human papillomavirus (HPV)-associated (HPV+) HNSCC, which defines an etiological subtype significantly different from the more common tobacco and alcohol associated HPV-negative (HPV−) HNSCC. Since 2011, application of large scale genome sequencing projects by The Cancer Genome Atlas (TCGA) network and other groups have established extensive datasets to characterize HPV− and HPV+ HNSCC, providing a foundation for advanced molecular diagnoses, identification of potential biomarkers, and therapeutic insights. Some genomic lesions are now appreciated as widely dispersed. For example, HPV− HNSCC characteristically inactivates the cell cycle suppressors TP53 (p53) and CDKN2A (p16), and often amplifies CCND1 (cyclin D), which phosphorylates RB1 to promote cell cycle progression from G1 to S. By contrast, HPV+ HNSCC expresses viral oncogenes E6 and E7, which inhibit TP53 and RB1, and activates the cell cycle regulator E2F1. Frequent activating mutations in PIK3CA and inactivating mutations in NOTCH1 are seen in both subtypes of HNSCC, emphasizing the importance of these pathways. Studies of large patient cohorts have also begun to identify less common genetic alterations, predominantly found in HPV− tumors, which suggest new mechanisms relevant to disease pathogenesis. Targets of these alterations including AJUBA and FAT1, both involved in the regulation of NOTCH/CTNNB1 signaling. Genes involved in oxidative stress, particularly CUL3, KEAP1 and NFE2L2, strongly associated with smoking, have also been identified, and are less well understood mechanistically. Application of sophisticated data-mining approaches, integrating genomic information with profiles of tumor methylation and gene expression, have helped to further yield insights, and in some cases suggest additional approaches to stratify patients for clinical treatment. We here discuss some recent insights built on TCGA and other genomic foundations.