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CTNNB1 mutations or APC abnormalities have been observed in ∼85% of desmoids examined by Sanger sequencing and are associated with Wnt/β-catenin activation. We sought to identify molecular aberrations in "wild-type" tumors (those without CTNNB1 or APC alteration) and to determine their prognostic relevance. CTNNB1 was examined by Sanger sequencing in 117 desmoids; a mutation was observed in 101 (86%) and 16 were wild type. Wild-type status did not associate with tumor recurrence. Moreover, in unsupervised clustering based on U133A-derived gene expression profiles, wild-type and mutated tumors clustered together. Whole-exome sequencing of eight of the wild-type desmoids revealed that three had a CTNNB1 mutation that had been undetected by Sanger sequencing. The mutation was found in a mean 16% of reads (vs. 37% for mutations identified by Sanger). Of the other five wild-type tumors sequenced, two had APC loss, two had chromosome 6 loss, and one had mutation of BMI1. The finding of low-frequency CTNNB1 mutation or APC loss in wild-type desmoids was validated in the remaining eight wild-type desmoids; directed miSeq identified low-frequency CTNNB1 mutation in four and comparative genomic hybridization identified APC loss in one. These results demonstrate that mutations affecting CTNNB1 or APC occur more frequently in desmoids than previously recognized (111 of 117; 95%), and designation of wild-type genotype is largely determined by sensitivity of detection methods. Even true CTNNB1 wild-type tumors (determined by next-generation sequencing) may have genomic alterations associated with Wnt activation (chromosome 6 loss/BMI1 mutation), supporting Wnt/β-catenin activation as the common pathway governing desmoid initiation.

Gene fusions involving the catalytic domain of tyrosine kinases (TKs) are found in a variety of hematological and solid tumor malignancies. Clinically, TK fusions have emerged as prime targets for therapy with small molecule kinase inhibitors. Unfortunately, identification of TK fusions has been hampered by experimental limitations. Here, we developed version 2.0 of a genomically based systematic kinase fusion screen and used it to detect a novel imatinib-sensitive C6orf204-PDGFRB fusion in a patient with precursor T lymphoblastic lymphoma (T-ALL) and an associated myeloproliferative neoplasm with eosinophilia. These data validate the ability of this targeted capture-sequencing approach to detect TK fusion events in small amounts of DNA extracted directly from patient samples.

An important idea that emerges from the energy landscape theory of protein folding is that subtle global features of the protein landscape can profoundly affect the apparent mechanism of folding. The relationship between various characteristic temperatures in the phase diagrams and landmarks in the folding funnel at fixed temperatures can be used to classify different folding behaviors. The one-dimensional picture of a folding funnel classifies folding kinetics into four basic scenarios, depending on the relative location of the thermodynamic barrier and the glass transition as a function of a single-order parameter. However, the folding mechanism may not always be quantitatively described by a single-order parameter. Several other order parameters, such as degree of secondary structure formation, collapse and topological order, are needed to establish the connection between minimalist models and proteins in the laboratory. In this article we describe a simple multidimensional funnel based on two-order parameters that measure the degree of collapse and topological order. The appearance of several different "mechanisms" is illustrated by analyzing lattice models with different potentials and sequences with different degrees of design. In most cases, the two-dimensional analysis leads to a classification of mechanisms totally in keeping with the one-dimensional scheme, but a topologically distinct scenario of fast folding with traps also emerges. The nature of traps depends on the relative location of the glass transition surface and the thermodynamic barrier in the multidimensional funnel.

The understanding, and even the description of protein folding is impeded by the complexity of the process. Much of this complexity can be described and understood by taking a statistical approach to the energetics of protein conformation, that is, to the energy landscape. The statistical energy landscape approach explains when and why unique behaviors, such as specific folding pathways, occur in some proteins and more generally explains the distinction between folding processes common to all sequences and those peculiar to individual sequences. This approach also gives new, quantitative insights into the interpretation of experiments and simulations of protein folding thermodynamics and kinetics. Specifically, the picture provides simple explanations for folding as a two-state first-order phase transition, for the origin of metastable collapsed unfolded states and for the curved Arrhenius plots observed in both laboratory experiments and discrete lattice simulations. The relation of these quantitative ideas to folding pathways, to uniexponential vs. multiexponential behavior in protein folding experiments and to the effect of mutations on folding is also discussed. The success of energy landscape ideas in protein structure prediction is also described. The use of the energy landscape approach for analyzing data is illustrated with a quantitative analysis of some recent simulations, and a qualitative analysis of experiments on the folding of three proteins. The work unifies several previously proposed ideas concerning the mechanism protein folding and delimits the regions of validity of these ideas under different thermodynamic conditions. © 1995 Wiley-Liss, Inc.

Objectives: The study of adenoid cystic carcinoma (ACC) of the salivary gland requires long-term follow up due to the slow growth rate of the tumor and its propensity to recur many years after therapy. Current management strategy for ACC has varied little in the last 60 years, but techniques in surgical and radiotherapy have improved. We have retrospectively studied patients with adenoid cystic carcinoma of the salivary gland during the last 25 years to determine current survival data at our institution. Methods: Forty-two patients treated for ACC of the salivary gland between 1975 and 2003 were registered at Northwestern Memorial Hospital. Kaplan-Meier analysis was used to characterize survival for this patient population. Tumor site, staging, and size of tumor were analyzed to determine their relationship to patient survival. Prognostic factors were compared to determine if each played a significant role in predicting mortality. Results: Of the 42 patients studied, 19 patients died during follow-up after receiving treatment for ACC. Twenty-three patients were alive at the date of last contact. Kaplan-Meier analysis of the 42 patients yielded a 5-year survival rate of 82.5% and a 10-year survival rate of 61%. Tumor site, stage, and size appeared to influence survival. Conclusion: Our review represents the most current assessment of survival for patients with adenoid cystic carcinoma at our institution. The data presented in our study concur with more recent literature, suggesting survival probability in patients with adenoid cystic carcinoma may be higher due to improved surgical technique and management with radiation therapy.

Objectives: To identify angiogenesis/metastasis related genes that are predictive of locoregional failure in patients undergoing chemoradiotherapy (CRT) treatment. Methods: Tumor tissue was collected and snap-frozen from 35 sequential patients with histologically confirmed laryngopharyngeal cancer being treated with CRT. Gene expression analysis was performed on all cases using a novel cDNA array consisting of 277 genes functionally associated with angiogenesis (n = 152) and/or metastasis (n = 125). A total of 1152 randomly selected genes were used for intersample normalization. RNA was extracted from freshly frozen pretreatment biopsies, reverse transcribed, labelled using cy3 and cy5, and then hybridized onto the micro array slide. Image capture and analysis was performed using GenePix Pro 3.0. Locoregional failure was correlated to the gene expression profiles to identify genes predictive for locoregional failure. Genes were validated and quantified using real time RT-PCR. Results: Of 35 patients, locoregional failure occurred in 9. Seventeen genes correlated with locoregional failure (2 sample t test P Conclusions: Genomic screening and real-time RT-PCR analyses identified and validated 4 genes predictive for locoregional failure in LPC patients treated by CRT. The role of these genes in treatment selection and the functional basis for their activity in CRT response merits further consideration.