Exploiting orthologue diversity for systematic detection of gain-of-function phenotypes

<p>Abstract</p> <p>Background</p> <p>Systematic search for genes whose gain-of-function by exogenous expression confers an advantage in cell-based selective screenings is a powerful method for unbiased functional exploration of the genome, and has the potential to disclose new targets for cancer therapy. A major limit of this approach resides in the labor-intensive cloning of resistant cells, identification of the integrated genes and validation of their ability to confer a selective advantage. Moreover, the selection has to be drastic and genes conferring a limited advantage are typically missed.</p> <p>Results</p> <p>We developed a new functional screening strategy based on transduction of mammalian cells of a given species with an expression library from another species, followed by one-shot quantitative tracing with DNA microarrays of all library-derived transcripts before and after selection. In this way, exogenous transcripts enriched after selection, and therefore likely to confer resistance, are readily detected. We transduced a retroviral cDNA expression library from mouse testis into human and canine cells, and optimized the use of commercial murine gene expression arrays for species-specific detection of library-derived transcripts. We then conducted a functional screening by growing library-transduced canine MDCK cells in suspension, to enrich for cDNAs conferring anchorage independence. Notably, these cells show partial resistance to loss of anchorage, and the selection can be of limited stringency, compromising approaches based on clonal selection or anyway requiring high stringency. Microarray analysis revealed reproducible enrichment after three weeks of growth on polyhema for seven genes, among which the Hras proto-oncogene and Sox5. When individually transduced into MDCK cells, Sox5 specifically promoted anchorage-independent growth, thereby confirming the validity and specificity of the approach.</p> <p>Conclusion</p> <p>The procedure described here brings substantial advantages to the field of expression cloning, being faster, more systematic and more sensitive. Indeed, this strategy allowed identification and validation of genes promoting anchorage-independent growth of epithelial cells under selection conditions not amenable to conventional expression cloning.</p

A Metabolic Imaging Study of Lexical and Phonological Naming Errors in Alzheimer Disease

Patients with Alzheimer disease (AD) produce a variety of errors on confrontation naming that indicate multiple loci of impairment along the naming process in this disease. We correlated brain hypometabolism, measured with 18fluoro-deoxy-glucose positron emission tomography, with semantic and formal errors, as well as nonwords deriving from phonological errors produced in a picture-naming test by 63 patients with AD. Findings suggest that neurodegeneration leads to: (1) phonemic errors, by interfering with phonological short-term memory, or with control over retrieval of phonological or prearticulatory representations, within the left supramarginal gyrus; (2) semantic errors, by disrupting general semantic or visual-semantic representations at the level of the left posterior middle and inferior occipitotemporal cortex, respectively; (3) formal errors, by damaging the lexical-phonological output interface in the left mid-anterior segment of middle and superior temporal gyri. This topography of semantic-lexical-phonological steps of naming is in substantial agreement with dual-stream neurocognitive models of word generation

Multi-label transcriptional classification of colorectal cancer reflects tumor cell population heterogeneity

Background: Transcriptional classification has been used to stratify colorectal cancer (CRC) into molecular subtypes with distinct biological and clinical features. However, it is not clear whether such subtypes represent discrete, mutually exclusive entities or molecular/phenotypic states with potential overlap. Therefore, we focused on the CRC Intrinsic Subtype (CRIS) classifier and evaluated whether assigning multiple CRIS subtypes to the same sample provides additional clinically and biologically relevant information. Methods: A multi-label version of the CRIS classifier (multiCRIS) was applied to newly generated RNA-seq profiles from 606 CRC patient-derived xenografts (PDXs), together with human CRC bulk and single-cell RNA-seq datasets. Biological and clinical associations of single- and multi-label CRIS were compared. Finally, a machine learning-based multi-label CRIS predictor (ML2CRIS) was developed for single-sample classification. Results: Surprisingly, about half of the CRC cases could be significantly assigned to more than one CRIS subtype. Single-cell RNA-seq analysis revealed that multiple CRIS membership can be a consequence of the concomitant presence of cells of different CRIS class or, less frequently, of cells with hybrid phenotype. Multi-label assignments were found to improve prediction of CRC prognosis and response to treatment. Finally, the ML2CRIS classifier was validated for retaining the same biological and clinical associations also in the context of single-sample classification. Conclusions: These results show that CRIS subtypes retain their biological and clinical features even when concomitantly assigned to the same CRC sample. This approach could be potentially extended to other cancer types and classification systems