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Cluster analysis has proved to be an invaluable tool for the exploratory and unsupervised analysis of highdimensional datasets. Among methods for clustering, hierarchical approaches have enjoyed substantial popularity in genomics and other fields for their ability to simultaneously uncover multiple layers of clustering structure. A critical and challenging question in cluster analysis is whether the identified clusters represent important underlying structure or are artifacts of natural sampling variation. Few approaches have been proposed for addressing this problem in the context of hierarchical clustering, for which the problem is further complicated by the natural tree structure of the partition, and the multiplicity of tests required to parse the layers of nested clusters. In this article, we propose a Monte Carlo based approach for testing statistical significance in hierarchical clustering which addresses these issues. The approach is implemented as a sequential testing procedure guaranteeing control of the family-wise error rate. Theoretical justification is provided for our approach, and its power to detect true clustering structure is illustrated through several simulation studies and applications to two cancer gene expression datasets.

Uterine carcinosarcoma is an aggressive variant of endometrial carcinoma characterized by unusual histologic features including discrete malignant epithelial and mesenchymal components (carcinoma and sarcoma). Recent studies have confirmed a monoclonal origin, and comprehensive genomic characterizations have identified mutations such as Tp53 and Pten. However, the biological origins and specific combination of driver events underpinning uterine carcinosarcoma have remained mysterious. Here, we explored the role of the tumor suppressor Fbxw7 in endometrial cancer through defined genetic model systems. Inactivation of Fbxw7 and Pten resulted in the formation of precancerous lesions (endometrioid intraepithelial neoplasia) and well-differentiated endometrioid adenocarcinomas. Surprisingly, all adenocarcinomas eventually developed into definitive uterine carcinosarcomas with carcinomatous and sarcomatous elements including heterologous differentiation, yielding a faithful genetically engineered model of this cancer type. Genomic analysis showed that most tumors spontaneously acquired Trp53 mutations, pointing to a triad of pathways (p53, PI3K, and Fbxw7) as the critical combination underpinning uterine carcinosarcoma, and to Fbxw7 as a key driver of this enigmatic endometrial cancer type. Lineage tracing provided formal genetic proof that the uterine carcinosarcoma cell of origin is an endometrial epithelial cell that subsequently undergoes a prominent epithelial–mesenchymal transition underlying the attainment of a highly invasive phenotype specifically driven by Fbxw7.

Recent sequencing studies have extensively explored the somatic alterations present in the nuclear genomes of cancers. Although mitochondria control energy metabolism and apoptosis, the origins and impact of cancer-associated mutations in mtDNA are unclear. In this study, we analyzed somatic alterations in mtDNA from 1675 tumors. We identified 1907 somatic substitutions, which exhibited dramatic replicative strand bias, predominantly C > T and A > G on the mitochondrial heavy strand. This strand-asymmetric signature differs from those found in nuclear cancer genomes but matches the inferred germline process shaping primate mtDNA sequence content. A number of mtDNA mutations showed considerable heterogeneity across tumor types. Missense mutations were selectively neutral and often gradually drifted towards homoplasmy over time. In contrast, mutations resulting in protein truncation undergo negative selection and were almost exclusively heteroplasmic. Our findings indicate that the endogenous mutational mechanism has far greater impact than any other external mutagens in mitochondria and is fundamentally linked to mtDNA replication. The DNA in a cell's nucleus must be copied faithfully, and divided equally, when a cell divides to produce two new cells. Mistakes—or mutations—are sometimes made during the copying process, and mutations can also be introduced by exposing DNA to damaging agents known as mutagens, such as UV light or cigarette smoke. These mutations are then maintained in all of the descendants of the cell. Most of these mutations have no impact on the cell's characteristics (‘passenger mutations’). However, ‘driver mutations’ that allow cells to divide uncontrollably and spread to other body sites can lead to cancer. Mitochondria are cellular compartments that are responsible for generating the energy a cell needs to survive and are also responsible for initiating programmed cell death. Mitochondria contain their own DNA—entirely separate from that in the nucleus of the cell—that encodes the proteins most essential for energy production. Mitochondrial DNA molecules are frequently exposed to damaging molecules called reactive oxygen species that are produced by the mitochondria. Therefore, these reactive oxygen species have been thought to be one of the most important causes of mitochondrial DNA mutations. In addition, because cancer cells produce energy differently to normal cells, mutations in the mitochondrial DNA that change the ability of the mitochondria to produce energy have been conventionally thought to help normal cells to become cancerous. However, conclusive evidence for a link between cancer and mitochondrial DNA mutations is lacking. Ju et al. examined the mitochondrial DNA sequences taken from 1675 cancer biopsies from over thirty different types of cancer and compared these to normal tissue from the same patients. This revealed 1907 mutations in the mitochondrial DNA taken from the cancer cells. The pattern of the mutations suggests that the majority of the mutations are not introduced from reactive oxygen species, but from the errors the mitochondria themselves make in the process of duplicating their DNA when a cell divides. Unexpectedly, known mutagens, such as cigarette smoke or UV light, had a negligible effect on mitochondrial DNA mutations. Contrary to conventional wisdom, Ju et al. found no evidence that the mitochondrial DNA mutations help cancer to develop or spread. Instead, like passenger mutations found in the DNA in the cell nucleus, most mitochondrial genome mutations have no discernible effect. However, Ju et al. revealed that DNA mutations that damage normal mitochondrial activity are less likely to be maintained in cancer cells. Presumably, mitochondria containing these proteins produce less energy, and so a cell containing too many of these mutations will find it harder to survive. This shows that having enough correctly functioning mitochondria is essential for even cancer cells to thrive.

High-throughput sequencing protocols such as RNA-seq have made it possible to interrogate the sequence, structure and abundance of RNA transcripts at higher resolution than previous microarray and other molecular techniques. While many computational tools have been proposed for identifying mRNA variation through differential splicing/alternative exon usage, challenges in its analysis remain. Here, we propose a framework for unbiased and robust discovery of aberrant RNA transcript structures using short read sequencing data based on shape changes in an RNA-seq coverage profile. Shape changes in selecting sample outliers in RNA-seq, SCISSOR, is a series of procedures for transforming and normalizing base-level RNA sequencing coverage data in a transcript independent manner, followed by a statistical framework for its analysis ( https://github.com/hyochoi/SCISSOR ). The resulting high dimensional object is amenable to unsupervised screening of structural alterations across RNA-seq cohorts with nearly no assumption on the mutational mechanisms underlying abnormalities. This enables SCISSOR to independently recapture known variants such as splice site mutations in tumor suppressor genes as well as novel variants that are previously unrecognized or difficult to identify by any existing methods including recurrent alternate transcription start sites and recurrent complex deletions in 3′ UTRs. Many computational tools identify mRNA variations by analyzing the transformed RNA-seq data such as collapsed reads. Here, the authors report a computational method which uses shape changes in the RNA-seq coverage profile to discover changes in mRNA expression and alternative splicing.

Trey Ideker and colleagues report a comprehensive genome-wide analysis of head and neck squamous cell carcinoma, reporting that TP53 mutations are frequently accompanied by loss of chromosome 3p. Their data indicate that the combination of these two events has a stronger negative effect on survival rate than either event alone. Head and neck squamous cell carcinoma (HNSCC) is characterized by aggressive behavior with a propensity for metastasis and recurrence. Here we report a comprehensive analysis of the molecular and clinical features of HNSCC that govern patient survival. We find that TP53 mutation is frequently accompanied by loss of chromosome 3p and that the combination of these events is associated with a surprising decrease in survival time (1.9 years versus >5 years for TP53 mutation alone). The TP53 -3p interaction is specific to chromosome 3p and validates in HNSCC and pan-cancer cohorts. In human papillomavirus (HPV)-positive tumors, in which HPV inactivates TP53 , 3p deletion is also common and is associated with poor outcomes. The TP53 -3p event is modified by mir-548k expression, which decreases survival further, and is mutually exclusive with mutations affecting RAS signaling. Together, the identified markers underscore the molecular heterogeneity of HNSCC and enable a new multi-tiered classification of this disease.

In parallel with an ongoing human clinical trial, genetically engineered mouse models of lung cancer with different genetic alterations are treated with chemotherapeutic agents; the results have implications for the clinical trial. Successful trial separation The idea of 'co-clinical' trials has been put forward as way of evaluating novel therapies. By testing a drug simultaneously in human clinical and mouse preclinical trials, the thinking is, the two sets of data can be combined to extract extra information. To demonstrate the potential of this approach, genetically engineered mouse models were used to mirror a randomized phase II clinical trial of the chemotherapeutic docetaxel in KRAS -driven lung cancer, comparing its action alone with that in combination with a MEK inhibitor. In the mouse model, tumours with Kras or Kras and p53 mutations were more responsive to the combination than to docetaxel alone, whereas mice carrying a deletion of Lkb1 in addition to activated Kras remained relatively unresponsive. This has important implications for the ongoing clinical trial, suggesting that patients should be tested for LKB1 mutations. Targeted therapies have demonstrated efficacy against specific subsets of molecularly defined cancers 1 , 2 , 3 , 4 . Although most patients with lung cancer are stratified according to a single oncogenic driver, cancers harbouring identical activating genetic mutations show large variations in their responses to the same targeted therapy 1 , 3 . The biology underlying this heterogeneity is not well understood, and the impact of co-existing genetic mutations, especially the loss of tumour suppressors 5 , 6 , 7 , 8 , 9 , has not been fully explored. Here we use genetically engineered mouse models to conduct a ‘co-clinical’ trial that mirrors an ongoing human clinical trial in patients with KRAS -mutant lung cancers. This trial aims to determine if the MEK inhibitor selumetinib (AZD6244) 10 increases the efficacy of docetaxel, a standard of care chemotherapy. Our studies demonstrate that concomitant loss of either p53 (also known as Tp53 ) or Lkb1 (also known as Stk11 ), two clinically relevant tumour suppressors 6 , 9 , 11 , 12 , markedly impaired the response of Kras -mutant cancers to docetaxel monotherapy. We observed that the addition of selumetinib provided substantial benefit for mice with lung cancer caused by Kras and Kras and p53 mutations, but mice with Kras and Lkb1 mutations had primary resistance to this combination therapy. Pharmacodynamic studies, including positron-emission tomography (PET) and computed tomography (CT), identified biological markers in mice and patients that provide a rationale for the differential efficacy of these therapies in the different genotypes. These co-clinical results identify predictive genetic biomarkers that should be validated by interrogating samples from patients enrolled on the concurrent clinical trial. These studies also highlight the rationale for synchronous co-clinical trials, not only to anticipate the results of ongoing human clinical trials, but also to generate clinically relevant hypotheses that can inform the analysis and design of human studies.

Lung cancer is the leading cause of cancer-related deaths worldwide, and lung squamous carcinomas (LUSC) represent about 30% of cases. Molecular aberrations in lung adenocarcinomas have allowed for effective targeted treatments, but corresponding therapeutic advances in LUSC have not materialized. However, immune checkpoint inhibitors in sub-populations of LUSC patients have led to exciting responses. Using computational analyses of The Cancer Genome Atlas, we identified a subset of LUSC tumors characterized by dense infiltration of inflammatory monocytes (IMs) and poor survival. With novel, immunocompetent metastasis models, we demonstrated that tumor cell derived CCL2-mediated recruitment of IMs is necessary and sufficient for LUSC metastasis. Pharmacologic inhibition of IM recruitment had substantial anti-metastatic effects. Notably, we show that IMs highly express Factor XIIIA, which promotes fibrin cross-linking to create a scaffold for LUSC cell invasion and metastases. Consistently, human LUSC samples containing extensive cross-linked fibrin in the microenvironment correlated with poor survival. Lung squamous carcinomas (LUSC) are poorly molecularly characterized, but sub-populations show promising response to immune checkpoint inhibitors. Here, the authors identify a subset of LUSC characterized by infiltration of inflammatory monocytes, where metastasis is linked to Factor XIIIA promoting fibrin cross-linking.

Head and neck squamous cell carcinoma (HNSCC) is a frequently fatal heterogeneous disease. Beyond the role of human papilloma virus (HPV), no validated molecular characterization of the disease has been established. Using an integrated genomic analysis and validation methodology we confirm four molecular classes of HNSCC (basal, mesenchymal, atypical, and classical) consistent with signatures established for squamous carcinoma of the lung, including deregulation of the KEAP1/NFE2L2 oxidative stress pathway, differential utilization of the lineage markers SOX2 and TP63, and preference for the oncogenes PIK3CA and EGFR. For potential clinical use the signatures are complimentary to classification by HPV infection status as well as the putative high risk marker CCND1 copy number gain. A molecular etiology for the subtypes is suggested by statistically significant chromosomal gains and losses and differential cell of origin expression patterns. Model systems representative of each of the four subtypes are also presented.

Lkb1 and cancer causation Mutations in the Lkb1 tumour suppressor gene are found in Peutz–Jeghers syndrome patients who have an increased incidence of cancers. Now Lkb1 mutations have been found in the squamous carcinoma subtype of non-small-cell lung cancers. In a mouse model for lung cancer in which Lkb1 loss is combined with K-Ras mutations, more aggressive tumours arise than with K-Ras mutations alone and often these are classified as squamous and large-cell carcinomas. Thus loss of Lkb1 modulates lung cancer differentiation, and Lkb1 loss may be a useful marker for predicting disease development and spread. The pathways regulated by LKB1 represent possible therapeutic targets. Mutations in the Lbk1 tumour suppressor gene are found in the squamous carcinoma subtype of non-small cell lung cancers for the first time. In a mouse model for lung cancer in which Lkb1 loss is combined with Kras mutations, more aggressive tumours arise than with Kras mutations alone and often these are classified as squamous carcinomas, thus Lkb1 loss modulates lung cancer differentiation. Germline mutation in serine/threonine kinase 11 ( STK11 , also called LKB1 ) results in Peutz–Jeghers syndrome, characterized by intestinal hamartomas and increased incidence of epithelial cancers 1 . Although uncommon in most sporadic cancers 2 , inactivating somatic mutations of LKB1 have been reported in primary human lung adenocarcinomas and derivative cell lines 3 , 4 , 5 . Here we used a somatically activatable mutant Kras-driven model of mouse lung cancer to compare the role of Lkb1 to other tumour suppressors in lung cancer. Although Kras mutation cooperated with loss of p53 or Ink4a/Arf (also known as Cdkn2a ) in this system, the strongest cooperation was seen with homozygous inactivation of Lkb1 . Lkb1 -deficient tumours demonstrated shorter latency, an expanded histological spectrum (adeno-, squamous and large-cell carcinoma) and more frequent metastasis compared to tumours lacking p53 or Ink4a/Arf . Pulmonary tumorigenesis was also accelerated by hemizygous inactivation of Lkb1 . Consistent with these findings, inactivation of LKB1 was found in 34% and 19% of 144 analysed human lung adenocarcinomas and squamous cell carcinomas, respectively. Expression profiling in human lung cancer cell lines and mouse lung tumours identified a variety of metastasis-promoting genes, such as NEDD9, VEGFC and CD24, as targets of LKB1 repression in lung cancer. These studies establish LKB1 as a critical barrier to pulmonary tumorigenesis, controlling initiation, differentiation and metastasis.

Lung adenocarcinoma (LAD) has extreme genetic variation among patients, which is currently not well understood, limiting progress in therapy development and research. LAD intrinsic molecular subtypes are a validated stratification of naturally-occurring gene expression patterns and encompass different functional pathways and patient outcomes. Patients may have incurred different mutations and alterations that led to the different subtypes. We hypothesized that the LAD molecular subtypes co-occur with distinct mutations and alterations in patient tumors. The LAD molecular subtypes (Bronchioid, Magnoid, and Squamoid) were tested for association with gene mutations and DNA copy number alterations using statistical methods and published cohorts (n = 504). A novel validation (n = 116) cohort was assayed and interrogated to confirm subtype-alteration associations. Gene mutation rates (EGFR, KRAS, STK11, TP53), chromosomal instability, regional copy number, and genomewide DNA methylation were significantly different among tumors of the molecular subtypes. Secondary analyses compared subtypes by integrated alterations and patient outcomes. Tumors having integrated alterations in the same gene associated with the subtypes, e.g. mutation, deletion and underexpression of STK11 with Magnoid, and mutation, amplification, and overexpression of EGFR with Bronchioid. The subtypes also associated with tumors having concurrent mutant genes, such as KRAS-STK11 with Magnoid. Patient overall survival, cisplatin plus vinorelbine therapy response and predicted gefitinib sensitivity were significantly different among the subtypes. The lung adenocarcinoma intrinsic molecular subtypes co-occur with grossly distinct genomic alterations and with patient therapy response. These results advance the understanding of lung adenocarcinoma etiology and nominate patient subgroups for future evaluation of treatment response.