{"title":"Different Tumor Types Share a Common Nuclear Map of Chromosome Territories.","authors":"Fritz F Parl","doi":"10.1177/11769351221148592","DOIUrl":null,"url":null,"abstract":"<p><p>Different tumor types are characterized by unique histopathological patterns including distinctive nuclear architectures. I hypothesized that the difference in nuclear appearance is reflected in different nuclear maps of chromosome territories, the discrete regions occupied by individual chromosomes in the interphase nucleus. To test this hypothesis, I used interchromosomal translocations (ITLs) as an analytical tool to map chromosome territories in 11 different tumor types from the TCGA PanCancer database encompassing 6003 tumors with 5295 ITLs. For each chromosome I determined the number and percentage of all ITLs for any given tumor type. Chromosomes were ranked according to the frequency and percentage of ITLs per chromosome. The ranking showed similar patterns for all tumor types. Chromosomes 1, 8, 11, 17, and 19 were ranked in the top quarter, accounting for 35.2% of 5295 ITLs, whereas chromosomes 13, 15, 18, 21, and X were in the bottom quarter, accounting for only 10.5% ITLs. The correlation between the chromosome ranking in the total group of 6003 tumors and the ranking in individual tumor types was significant, ranging from <i>P</i> < .0001 to .0033. Thus, contrary to my hypothesis, different tumor types share a common nuclear map of chromosome territories. Based on the large number of ITLs in 11 different types of malignancy one can discern a shared pattern of chromosome territories in cancer and propose a probabilistic model of chromosomes 1, 8, 11, 17, 19 in the center of the nucleus and chromosomes 13, 15, 18, 21, X at the periphery.</p>","PeriodicalId":35418,"journal":{"name":"Cancer Informatics","volume":null,"pages":null},"PeriodicalIF":2.4000,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/cd/06/10.1177_11769351221148592.PMC9903037.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Cancer Informatics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1177/11769351221148592","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MATHEMATICAL & COMPUTATIONAL BIOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Different tumor types are characterized by unique histopathological patterns including distinctive nuclear architectures. I hypothesized that the difference in nuclear appearance is reflected in different nuclear maps of chromosome territories, the discrete regions occupied by individual chromosomes in the interphase nucleus. To test this hypothesis, I used interchromosomal translocations (ITLs) as an analytical tool to map chromosome territories in 11 different tumor types from the TCGA PanCancer database encompassing 6003 tumors with 5295 ITLs. For each chromosome I determined the number and percentage of all ITLs for any given tumor type. Chromosomes were ranked according to the frequency and percentage of ITLs per chromosome. The ranking showed similar patterns for all tumor types. Chromosomes 1, 8, 11, 17, and 19 were ranked in the top quarter, accounting for 35.2% of 5295 ITLs, whereas chromosomes 13, 15, 18, 21, and X were in the bottom quarter, accounting for only 10.5% ITLs. The correlation between the chromosome ranking in the total group of 6003 tumors and the ranking in individual tumor types was significant, ranging from P < .0001 to .0033. Thus, contrary to my hypothesis, different tumor types share a common nuclear map of chromosome territories. Based on the large number of ITLs in 11 different types of malignancy one can discern a shared pattern of chromosome territories in cancer and propose a probabilistic model of chromosomes 1, 8, 11, 17, 19 in the center of the nucleus and chromosomes 13, 15, 18, 21, X at the periphery.
期刊介绍:
The field of cancer research relies on advances in many other disciplines, including omics technology, mass spectrometry, radio imaging, computer science, and biostatistics. Cancer Informatics provides open access to peer-reviewed high-quality manuscripts reporting bioinformatics analysis of molecular genetics and/or clinical data pertaining to cancer, emphasizing the use of machine learning, artificial intelligence, statistical algorithms, advanced imaging techniques, data visualization, and high-throughput technologies. As the leading journal dedicated exclusively to the report of the use of computational methods in cancer research and practice, Cancer Informatics leverages methodological improvements in systems biology, genomics, proteomics, metabolomics, and molecular biochemistry into the fields of cancer detection, treatment, classification, risk-prediction, prevention, outcome, and modeling.