Mandatory chromosomal segment balance in aneuploid tumor cells

Copyright: Copyright 2013 Elsevier B.V., All rights reserved.Background: Euploid chromosome balance is vitally important for normal development, but is profoundly changed in many tumors. Is each tumor dependent on its own structurally and numerically changed chromosome complement that has evolved during its development and progression? We have previously shown that normal chromosome 3 transfer into the KH39 renal cell carcinoma line and into the Hone1 nasopharyngeal carcinoma line inhibited their tumorigenicity. The aim of the present study was to distinguish between a qualitative and a quantitative model of this suppression. According to the former, a damaged or deleted tumor suppressor gene would be restored by the transfer of a normal chromosome. If so, suppression would be released only when the corresponding sequences of the exogenous normal chromosome are lost or inactivated. According to the alternative quantitative model, the tumor cell would not tolerate an increased dosage of the relevant gene or segment. If so, either a normal cell derived, or, a tumor derived endogenous segment could be lost. Methods: Fluorescence in Situ Hybridization based methods, as well as analysis of polymorphic microsatellite markers were used to follow chromosome 3 constitution changes in monochromosomal hybrids. Results: In both tumor lines with introduced supernumerary chromosomes 3, the copy number of 3p21 or the entire 3p tended to fall back to the original level during both in vitro and in vivo growth. An exogenous, normal cell derived, or an endogenous, tumor derived, chromosome segment was lost with similar probability. Identification of the lost versus retained segments showed that the intolerance for increased copy number was particularly strong for 3p14-p21, and weaker for other 3p regions. Gains in copy number were, on the other hand, well tolerated in the long arm and particularly the 3q26-q27 region. Conclusion: The inability of the cell to tolerate an experimentally imposed gain in 3p14-p21 in contrast to the well tolerated gain in 3q26-q27 is consistent with the fact that the former is often deleted in human tumors, whereas the latter is frequently amplified. The findings emphasize the importance of even minor changes in copy number in seemingly unbalanced aneuploid tumors.publishersversionPeer reviewe

Accurate molecular classification of cancer using simple rules

<p>Abstract</p> <p>Background</p> <p>One intractable problem with using microarray data analysis for cancer classification is how to reduce the extremely high-dimensionality gene feature data to remove the effects of noise. Feature selection is often used to address this problem by selecting informative genes from among thousands or tens of thousands of genes. However, most of the existing methods of microarray-based cancer classification utilize too many genes to achieve accurate classification, which often hampers the interpretability of the models. For a better understanding of the classification results, it is desirable to develop simpler rule-based models with as few marker genes as possible.</p> <p>Methods</p> <p>We screened a small number of informative single genes and gene pairs on the basis of their depended degrees proposed in rough sets. Applying the decision rules induced by the selected genes or gene pairs, we constructed cancer classifiers. We tested the efficacy of the classifiers by leave-one-out cross-validation (LOOCV) of training sets and classification of independent test sets.</p> <p>Results</p> <p>We applied our methods to five cancerous gene expression datasets: leukemia (acute lymphoblastic leukemia [ALL] vs. acute myeloid leukemia [AML]), lung cancer, prostate cancer, breast cancer, and leukemia (ALL vs. mixed-lineage leukemia [MLL] vs. AML). Accurate classification outcomes were obtained by utilizing just one or two genes. Some genes that correlated closely with the pathogenesis of relevant cancers were identified. In terms of both classification performance and algorithm simplicity, our approach outperformed or at least matched existing methods.</p> <p>Conclusion</p> <p>In cancerous gene expression datasets, a small number of genes, even one or two if selected correctly, is capable of achieving an ideal cancer classification effect. This finding also means that very simple rules may perform well for cancerous class prediction.</p

Non-coding RNAs profiling in head and neck cancers

The majority of studies on human cancers published to date focus on coding genes. More recently, however, non-coding RNAs (ncRNAs) are gaining growing recognition as important regulatory components. Here we characterise the ncRNA landscape in 442 head and neck squamous cell carcinomas (HNSCs) from the cancer genome atlas (TCGA). HNSCs represent an intriguing case to study the potential role of ncRNA as a function of viral presence, especially as HPV is potentially oncogenic. Thus, we identify HPV16-positive (HPV16 ) and HPV-negative (HPV ) tumours and study the expression of ncRNAs on both groups. Overall, the ncRNAs comprise 36% of all differentially expressed genes, with antisense RNAs being the most represented ncRNA type (12.6%). Protein-coding genes appear to be more frequently downregulated in tumours compared with controls, whereas ncRNAs show significant upregulation in tumours, especially in HPV16 tumours. Overall, expression of pseudogenes, antisense and short RNAs is elevated in HPV16 tumours, while the remaining long non-coding RNA types are more active in all HNSC tumours independent of HPV status. In addition, we identify putative regulatory targets of differentially expressed ncRNAs. Among these 'targets' we find several well-established oncogenes, tumour suppressors, cytokines, growth factors and cell differentiation genes, which indicates the potential involvement of ncRNA in the control of these key regulators as a direct consequence of HPV oncogenic activity. In conclusion, our findings establish the ncRNAs as crucial transcriptional components in HNSCs. Our results display the great potential for the study of ncRNAs and the role they have in human cancers