Identification of alpha-enolase as an autoantigen in lung cancer: Its overexpression is associated with clinical outcomes

Purpose: Although existence of humoral immunity has been previously shown in malignant pleural effusions, only a limited number of immunogenic tumor-associated antigens (TAA) have been identified and associated with lung cancer. In this study, we intended to identify more TAAs in pleural effusion-derived tumor cells. Experimental Design: Using morphologically normal lung tissues as a control lysate in Western blotting analyses, 54 tumor samples were screened with autologous effusion antibodies. Biochemical purification and mass spectrometric identification of TAAs were done using established effusion tumor cell lines as antigen sources. We identified a p48 antigen as of-enolase (ENO1). Semiquantitative immunohistochemistry was used to evaluate expression status of ENO1 in the tissue samples of 80 patients with non-small cell lung cancer (NSCLC) and then correlated with clinical variables. Results: Using ENO1-specifc antiserum, up-regulation of ENO1 expression in effusion tumor cells from 11 of 17 patients was clearly observed compared with human normal lung primary epithelial and non-cancer-associated effusion cells. Immunohistochemical studies consistently showed high level of ENO1 expression in all the tumors we have examined thus far. Log-rank and Cox's analyses of ENO1 expression status revealed that its expression level in primary tumors was a key factor contributing to overall- and progression-free survivals of patients (P < 0.05). The same result was also obtained in the early stage of NSCLC patients, showing that tumors expressing relatively higher ENO1 level were tightly correlated with poorer survival outcomes. Conclusions: Our data strongly support a prognostic role of ENO1 in determining tumor malignancy of patients with NSCLC

An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics

For a decade, The Cancer Genome Atlas (TCGA) program collected clinicopathologic annotation data along with multi-platform molecular profiles of more than 11,000 human tumors across 33 different cancer types. TCGA clinical data contain key features representing the democratized nature of the data collection process. To ensure proper use of this large clinical dataset associated with genomic features, we developed a standardized dataset named the TCGA Pan-Cancer Clinical Data Resource (TCGA-CDR), which includes four major clinical outcome endpoints. In addition to detailing major challenges and statistical limitations encountered during the effort of integrating the acquired clinical data, we present a summary that includes endpoint usage recommendations for each cancer type. These TCGA-CDR findings appear to be consistent with cancer genomics studies independent of the TCGA effort and provide opportunities for investigating cancer biology using clinical correlates at an unprecedented scale. Analysis of clinicopathologic annotations for over 11,000 cancer patients in the TCGA program leads to the generation of TCGA Clinical Data Resource, which provides recommendations of clinical outcome endpoint usage for 33 cancer types

Failure analysis of a cracked plate based on endochronic plastic theory coupled with damage

An anisotropic model of damage mechanics for ductile fracture incorporating the endochronic theory of plasticity is presented in order to take into account material deterioration during plastic deformation. An alternative form of endochronic (internal time) theory which is actually an elasto-plastic damage theory with isotropic-nonlinear kinematic hardening is developed for ease of numerical computation. Based on this new damage model, a finite element algorithm is formulated and then employed to characterize the fracture of thin aluminum plate containing a center crack. A new criterion termed as Y R -Criterion is proposed to define both the crack initiation angle and load. Experiments have been conducted to verify the validity of the proposed damage model and it is found that the theoretical crack initiation loads correspond closely with the measured values.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/42776/1/10704_2004_Article_BF00034511.pd

Driver Fusions and Their Implications in the Development and Treatment of Human Cancers.

Gene fusions represent an important class of somatic alterations in cancer. We systematically investigated fusions in 9,624 tumors across 33 cancer types using multiple fusion calling tools. We identified a total of 25,664 fusions, with a 63% validation rate. Integration of gene expression, copy number, and fusion annotation data revealed that fusions involving oncogenes tend to exhibit increased expression, whereas fusions involving tumor suppressors have the opposite effect. For fusions involving kinases, we found 1,275 with an intact kinase domain, the proportion of which varied significantly across cancer types. Our study suggests that fusions drive the development of 16.5% of cancer cases and function as the sole driver in more than 1% of them. Finally, we identified druggable fusions involving genes such as TMPRSS2, RET, FGFR3, ALK, and ESR1 in 6.0% of cases, and we predicted immunogenic peptides, suggesting that fusions may provide leads for targeted drug and immune therapy

Genomic and Functional Approaches to Understanding Cancer Aneuploidy

Aneuploidy, whole chromosome or chromosome arm imbalance, is a near-universal characteristic of human cancers. In 10,522 cancer genomes from The Cancer Genome Atlas, aneuploidy was correlated with TP53 mutation, somatic mutation rate, and expression of proliferation genes. Aneuploidy was anti-correlated with expression of immune signaling genes, due to decreased leukocyte infiltrates in high-aneuploidy samples. Chromosome arm-level alterations show cancer-specific patterns, including loss of chromosome arm 3p in squamous cancers. We applied genome engineering to delete 3p in lung cells, causing decreased proliferation rescued in part by chromosome 3 duplication. This study defines genomic and phenotypic correlates of cancer aneuploidy and provides an experimental approach to study chromosome arm aneuploidy. Analyzing >10,000 human cancers, Taylor et al. show that aneuploidy is correlated with somatic mutation rate, expression of proliferation genes, and decreased leukocyte infiltration. Loss of chromosome arm 3p is common in squamous cancers, but deletion of chromosome 3p reduces cell proliferation in vitro

Somatic Mutational Landscape of Splicing Factor Genes and Their Functional Consequences across 33 Cancer Types

Hotspot mutations in splicing factor genes have been recently reported at high frequency in hematological malignancies, suggesting the importance of RNA splicing in cancer. We analyzed whole-exome sequencing data across 33 tumor types in The Cancer Genome Atlas (TCGA), and we identified 119 splicing factor genes with significant non-silent mutation patterns, including mutation over-representation, recurrent loss of function (tumor suppressor-like), or hotspot mutation profile (oncogene-like). Furthermore, RNA sequencing analysis revealed altered splicing events associated with selected splicing factor mutations. In addition, we were able to identify common gene pathway profiles associated with the presence of these mutations. Our analysis suggests that somatic alteration of genes involved in the RNA-splicing process is common in cancer and may represent an underappreciated hallmark of tumorigenesis