Vincent Detours

Clustering Patterns of Cytotoxic T-Lymphocyte Epitopes in Human Immunodeficiency Virus Type 1 (HIV-1) Proteins Reveal Imprints of Immune Evasion on HIV-1 Global Variation

ABSTRACT The human cytotoxic T-lymphocyte (CTL) response to human immunodeficiency virus type 1 (HIV-1) has been intensely studied, and hundreds of CTL epitopes have been experimentally defined, published, and compiled in the HIV Molecular Immunology Database. Maps of CTL epitopes on HIV-1 protein sequences reveal that defined epitopes tend to cluster. Here we integrate the global sequence and immunology databases to systematically explore the relationship between HIV-1 amino acid sequences and CTL epitope distributions. CTL responses to five HIV-1 proteins, Gag p17, Gag p24, reverse transcriptase (RT), Env, and Nef, have been particularly well characterized in the literature to date. Through comparing CTL epitope distributions in these five proteins to global protein sequence alignments, we identified distinct characteristics of HIV amino acid sequences that correlate with CTL epitope localization. First, experimentally defined HIV CTL epitopes are concentrated in relatively conserved regions. Second, the highly variable regions that lack epitopes bear cumulative evidence of past immune escape that may make them relatively refractive to CTLs: a paucity of predicted proteasome processing sites and an enrichment for amino acids that do not serve as C-terminal anchor residues. Finally, CTL epitopes are more highly concentrated in alpha-helical regions of proteins. Based on amino acid sequence characteristics, in a blinded fashion, we predicted regions in HIV regulatory and accessory proteins that would be likely to contain CTL epitopes; these predictions were then validated by comparison to new sets of experimentally defined epitopes in HIV-1 Rev, Tat, Vif, and Vpr.

Human cancer cell lines: Experimental models for cancer cells in situ? For cancer stem cells?

Established human cancer cell lines are routinely used as experimental models for human cancers. Their validity for such use is analyzed and discussed, with particular focus on thyroid tumors. Although cell lines retain some properties of the cells of origin, from the points of view of their genetics, epigenetics and gene expression, they show clear differences in these properties compared to in vivo tumors. This can be explained by a prior selection of initiating cells and a Darwinian evolution in vitro. The properties of the cell lines are compared to those of the postulated cancer stem cells and their use as models in this regard are discussed. Furthermore, other proper and possible uses of the cell lines are discussed.

Human Thyroid Tumor Cell Lines Derived from Different Tumor Types Present a Common Dedifferentiated Phenotype

Cell lines are crucial to elucidate mechanisms of tumorigenesis and serve as tools for cancer treatment screenings. Therefore, careful validation of whether these models have conserved properties of in vivo tumors is highly important. Thyrocyte-derived tumors are very interesting for cancer biology studies because from one cell type, at least five histologically characterized different benign and malignant tumor types can arise. To investigate whether thyroid tumor-derived cell lines are representative in vitro models, characteristics of eight of those cell lines were investigated with microarrays, differentiation markers, and karyotyping. Our results indicate that these cell lines derived from differentiated and undifferentiated tumor types have evolved in vitro into similar phenotypes with gene expression profiles the closest to in vivo undifferentiated tumors. Accordingly, the absence of expression of most thyrocyte-specific genes, the nonresponsiveness to thyrotropin, as well as their large number of chromosomal abnormalities, suggest that these cell lines have acquired characteristics of fully dedifferentiated cells. They represent the outcome of an adaptation and evolution in vitro, which questions the reliability of these cell lines as models for differentiated tumors. However, they may represent useful models for undifferentiated cancers, and by their comparison with differentiated cells, can help to define the genes involved in the differentiation/dedifferentiation process. The use of any cell line as a model for a cancer therefore requires prior careful and thorough validation for the investigated property.

Principles Governing A-to-I RNA Editing in the Breast Cancer Transcriptome.

Summary Little is known about how RNA editing operates in cancer. Transcriptome analysis of 68 normal and cancerous breast tissues revealed that the editing enzyme ADAR acts uniformly, on the same loci, across tissues. In controlled ADAR expression experiments, the editing frequency increased at all loci with ADAR expression levels according to the logistic model. Loci-specific “editabilities,” i.e., propensities to be edited by ADAR, were quantifiable by fitting the logistic function to dose-response data. The editing frequency was increased in tumor cells in comparison to normal controls. Type I interferon response and ADAR DNA copy number together explained 53% of ADAR expression variance in breast cancers. ADAR silencing using small hairpin RNA lentivirus transduction in breast cancer cell lines led to less cell proliferation and more apoptosis. A-to-I editing is a pervasive, yet reproducible, source of variation that is globally controlled by 1q amplification and inflammation, both of which are highly prevalent among human cancers.

Genome-wide gene expression profiling suggests distinct radiation susceptibilities in sporadic and post-Chernobyl papillary thyroid cancers

Papillary thyroid cancers (PTCs) incidence dramatically increased in the vicinity of Chernobyl. The cancer-initiating role of radiation elsewhere is debated. Therefore, we searched for a signature distinguishing radio-induced from sporadic cancers. Using microarrays, we compared the expression profiles of PTCs from the Chernobyl Tissue Bank (CTB, n=12) and from French patients with no history of exposure to ionising radiations (n=14). We also compared the transcriptional responses of human lymphocytes to the presumed aetiological agents initiating these tumours, γ-radiation and H2O2. On a global scale, the transcriptomes of CTB and French tumours are indistinguishable, and the transcriptional responses to γ-radiation and H2O2 are similar. On a finer scale, a 118 genes signature discriminated the γ-radiation and H2O2 responses. This signature could be used to classify the tumours as CTB or French with an error of 15–27%. Similar results were obtained with an independent signature of 13 genes involved in homologous recombination. Although sporadic and radio-induced PTCs represent the same disease, they are distinguishable with molecular signatures reflecting specific responses to γ-radiation and H2O2. These signatures in PTCs could reflect the susceptibility profiles of the patients, suggesting the feasibility of a radiation susceptibility test.

Gene expression and the biological phenotype of papillary thyroid carcinomas.

The purpose of this paper is to correlate the molecular phenotype of papillary thyroid carcinoma (PTC) to their biological pathology. We hybridized 26 PTC on microarrays and showed that nearly 44% of the transcriptome was regulated in these tumors. We then combined our data set with two published PTC microarray studies to produce a platform- and study-independent list of PTC-associated genes. We further confirmed the mRNA regulation of 15 genes from this list by quantitative reverse transcription–PCR. Analysis of this list with statistical tools led to several conclusions: (1) there is a change in cell population with an increased expression of genes involved in the immune response, reflecting lymphocyte infiltration in the tumor compared to the normal tissue. (2) The c-jun N-terminal kinase pathway is activated by overexpression of its components. (3) The activation of ERKK1/2 by genetic alterations is supplemented by activation of the epidermal growth factor but not of the insulin-like growth factor signaling pathway. (4) There is a downregulation of immediate early genes. (5) We observed an overexpression of many proteases in accordance with tumor remodeling, and suggested a probable role of S100 proteins and annexin A2 in this process. (6) Numerous overexpressed genes favor the hypothesis of a collective migration mode of tumor cells.

Absence of a specific radiation signature in post-Chernobyl thyroid cancers

Thyroid cancers have been the main medical consequence of the Chernobyl accident. On the basis of their pathological features and of the fact that a large proportion of them demonstrate RET-PTC translocations, these cancers are considered as similar to classical sporadic papillary carcinomas, although molecular alterations differ between both tumours. We analysed gene expression in post-Chernobyl cancers, sporadic papillary carcinomas and compared to autonomous adenomas used as controls. Unsupervised clustering of these data did not distinguish between the cancers, but separates both cancers from adenomas. No gene signature separating sporadic from post-Chernobyl PTC (chPTC) could be found using supervised and unsupervised classification methods although such a signature is demonstrated for cancers and adenomas. Furthermore, we demonstrate that pooled RNA from sporadic and chPTC are as strongly correlated as two independent sporadic PTC pools, one from Europe, one from the US involving patients not exposed to Chernobyl radiations. This result relies on cDNA and Affymetrix microarrays. Thus, platform-specific artifacts are controlled for. Our findings suggest the absence of a radiation fingerprint in the chPTC and support the concept that post-Chernobyl cancer data, for which the cancer-causing event and its date are known, are a unique source of information to study naturally occurring papillary carcinomas.

Genes expressed in specific areas of the human fetal cerebral cortex display distinct patterns of evolution

The developmental mechanisms through which the cerebral cortex increased in size and complexity during primate evolution are essentially unknown. To uncover genetic networks active in the developing cerebral cortex, we combined three-dimensional reconstruction of human fetal brains at midgestation and whole genome expression profiling. This novel approach enabled transcriptional characterization of neurons from accurately defined cortical regions containing presumptive Broca and Wernicke language areas, as well as surrounding associative areas. We identified hundreds of genes displaying differential expression between the two regions, but no significant difference in gene expression between left and right hemispheres. Validation by qRTPCR and in situ hybridization confirmed the robustness of our approach and revealed novel patterns of area- and layer-specific expression throughout the developing cortex. Genes differentially expressed between cortical areas were significantly associated with fast-evolving non-coding sequences harboring human-specific substitutions that could lead to divergence in their repertoires of transcription factor binding sites. Strikingly, while some of these sequences were accelerated in the human lineage only, many others were accelerated in chimpanzee and/or mouse lineages, indicating that genes important for cortical development may be particularly prone to changes in transcriptional regulation across mammals. Genes differentially expressed between cortical regions were also enriched for transcriptional targets of FoxP2, a key gene for the acquisition of language abilities in humans. Our findings point to a subset of genes with a unique combination of cortical areal expression and evolutionary patterns, suggesting that they play important roles in the transcriptional network underlying human-specific neural traits.

InSilico DB genomic datasets hub: an efficient starting point for analyzing genome-wide studies in GenePattern, Integrative Genomics Viewer, and R/Bioconductor

Genomics datasets are increasingly useful for gaining biomedical insights, with adoption in the clinic underway. However, multiple hurdles related to data management stand in the way of their efficient large-scale utilization. The solution proposed is a web-based data storage hub. Having clear focus, flexibility and adaptability, InSilico DB seamlessly connects genomics dataset repositories to state-of-the-art and free GUI and command-line data analysis tools. The InSilico DB platform is a powerful collaborative environment, with advanced capabilities for biocuration, dataset sharing, and dataset subsetting and combination. InSilico DB is available from https://insilicodb.org.

Integration and cross-validation of high-throughput gene expression data: comparing heterogeneous data sets.

Data analysis – not data production – is becoming the bottleneck in gene expression research. Data integration is necessary to cope with an ever increasing amount of data, to cross‐validate noisy data sets, and to gain broad interdisciplinary views of large biological data sets. New Internet resources may help researchers to combine data sets across different gene expression platforms. However, noise and disparities in experimental protocols strongly limit data integration. A detailed review of four selected studies reveals how some of these limitations may be circumvented and illustrates what can be achieved through data integration.