We present the analysis of the evolution of tumors in a case of hepatocellular carcinoma. This case is particularly informative about cancer growth dynamics and the underlying driving mutations. We sampled nine different sections from three tumors and seven more sections from the adjacent nontumor tissues. Selected sections were subjected to exon as well as whole-genome sequencing. Putative somatic mutations were then individually validated across all 9 tumor and 7 nontumor sections. Among the mutations validated, 24 were amino acid changes; in addition, 22 large indels/copy number variants (>1 Mb) were detected. These somatic mutations define four evolutionary lineages among tumor cells. Separate evolution and expansion of these lineages were recent and rapid, each apparently having only one lineage-specific protein-coding mutation. Hence, by using a cell-population genetic definition, this approach identified three coding changes (CCNG1, P62, and an indel/fusion gene) as tumor driver mutations. These three mutations, affecting cell cycle control and apoptosis, are functionally distinct from mutations that accumulated earlier, many of which are involved in inflammation/immunity or cell anchoring. These distinct functions of mutations at different stages may reflect the genetic interactions underlying tumor growth.cell genealogy | cellular evolution | foreground mutation T umorigenesis is generally believed to be the consequence of mutation accumulation, including single nucleotide substitutions, structural variations, and epigenetic changes, in somatic cells (1). A typical cancer may have thousands of somatic mutations, of which 10-100 may be in coding regions (2-7). A central issue in cancer genomics is then the dynamics of tumor growth in relation to the accumulation of these mutations. Given any individual case of cancer, the questions are hence: (i) how many adaptive mutations drive the tumor growth; (ii) how strongly each mutation drives the growth; and (iii) what their molecular nature is vis-à-vis that of the background mutations. To answer these questions, we treat each tumor as a population of cells and apply population genetic principles to infer adaptive mutations (8).Cancer mutations are often divided into drivers and passengers (9). Driver mutations are those that contribute directly to tumorigenesis and their identification is crucial for understanding the molecular biology of cancers. An important issue is how driver mutations should be defined operationally. Candidate driver mutation in the literature often refers to coding changes in genes that are commonly mutated, for example, in multiple cases of hepatocellular carcinoma (HCC). Adaptive mutation proposed here is an alternative definition of candidate driver mutation, inferred from the dynamics of cell proliferation in its natural setting within a single patient.In this report, we analyze a case of HCC, the fifth most common cancer worldwide, by such an approach. We regard HCC as particularly favorable for identifying candidate driver mutatio...

The development of the mature insect trachea requires a complex series of cellular events, including tracheal cell specification, cell migration, tubule branching, and tubule fusion. Here we describe the identification of the Drosophila melanogaster dysfusion gene, which encodes a novel basic helix-loop-helix (bHLH)-PAS protein conserved between Caenorhabditis elegans, insects, and humans, and controls tracheal fusion events. The Dysfusion protein functions as a heterodimer with the Tango bHLH-PAS protein in vivo to form a putative DNA-binding complex. The dysfusion gene is expressed in a variety of embryonic cell types, including trachealfusion, leading-edge, foregut atrium cells, nervous system, hindgut, and anal pad cells. RNAi experiments indicate that dysfusion is required for dorsal branch, lateral trunk, and ganglionic branch fusion but not for fusion of the dorsal trunk. The escargot gene, which is also expressed in fusion cells and is required for tracheal fusion, precedes dysfusion expression. Analysis of escargot mutants indicates a complex pattern of dysfusion regulation, such that dysfusion expression is dependent on escargot in the dorsal and ganglionic branches but not the dorsal trunk. Early in tracheal development, the Trachealess bHLH-PAS protein is present at uniformly high levels in all tracheal cells, but since the levels of Dysfusion rise in wild-type fusion cells, the levels of Trachealess in fusion cells decline. The downregulation of Trachealess is dependent on dysfusion function. These results suggest the possibility that competitive interactions between basic helix-loop-helix-PAS proteins (Dysfusion, Trachealess, and possibly Similar) may be important for the proper development of the trachea.The insect tracheal system consists of an intricately branched system of tubules that provide oxygen throughout the animal. The formation of the trachea consists of a series of developmental events, and its analysis provides an excellent model system for studying the morphogenesis of other branched structures, such as the vertebrate lung airways, circulatory system, kidney ducts, and excretory epithelia (9, 27, 38). The trachea is derived from an array of segmentally repeated clusters of precursor cells. After the tracheal precursor cells divide and invaginate, they extend branches, and the branches from neighboring segments fuse to form the mature tracheal tree. The fusion process is mediated by a distinct fusion cell residing on each branch (41). Branching and fusion are complex cellular processes and pose a number of developmental questions. How are fusion cells specified during tracheal development? What are the short-range and long-range factors that guide tracheal branches to their fusion partners? What is the nature of the adhesive and contact-guidance interactions that mediate fusion and allow the formation of adherens junctions that seal intercellular junctions? How is the cytoskeleton rearranged to allow the tracheal lumen to extend throughout the branch?The tracheal primordia extend bra...

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Cone-beam computed tomography is more accurate than PA in diagnosing periapical lesions associated with mandibular teeth. The volumes of artificial mandibular periapical lesions were accurately measured with CBCT data.