Distance in cancer gene expression from stem cells predicts patient survival.
The degree of histologic cellular differentiation of a cancer has been associated with prognosis but is subjectively assessed. We hypothesized that information about tumor differentiation of individual cancers could be derived objectively from cancer gene expression data, and would allow creation of...
Saved in:
| Main Authors: | , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Public Library of Science (PLoS)
2017-01-01
|
| Series: | PLoS ONE |
| Online Access: | https://doi.org/10.1371/journal.pone.0173589 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1849419053434667008 |
|---|---|
| author | Markus Riester Hua-Jun Wu Ahmet Zehir Mithat Gönen Andre L Moreira Robert J Downey Franziska Michor |
| author_facet | Markus Riester Hua-Jun Wu Ahmet Zehir Mithat Gönen Andre L Moreira Robert J Downey Franziska Michor |
| author_sort | Markus Riester |
| collection | DOAJ |
| description | The degree of histologic cellular differentiation of a cancer has been associated with prognosis but is subjectively assessed. We hypothesized that information about tumor differentiation of individual cancers could be derived objectively from cancer gene expression data, and would allow creation of a cancer phylogenetic framework that would correlate with clinical, histologic and molecular characteristics of the cancers, as well as predict prognosis. Here we utilized mRNA expression data from 4,413 patient samples with 7 diverse cancer histologies to explore the utility of ordering samples by their distance in gene expression from that of stem cells. A differentiation baseline was obtained by including expression data of human embryonic stem cells (hESC) and human mesenchymal stem cells (hMSC) for solid tumors, and of hESC and CD34+ cells for liquid tumors. We found that the correlation distance (the degree of similarity) between the gene expression profile of a tumor sample and that of stem cells orients cancers in a clinically coherent fashion. For all histologies analyzed (including carcinomas, sarcomas, and hematologic malignancies), patients with cancers with gene expression patterns most similar to that of stem cells had poorer overall survival. We also found that the genes in all undifferentiated cancers of diverse histologies that were most differentially expressed were associated with up-regulation of specific oncogenes and down-regulation of specific tumor suppressor genes. Thus, a stem cell-oriented phylogeny of cancers allows for the derivation of a novel cancer gene expression signature found in all undifferentiated forms of diverse cancer histologies, that is competitive in predicting overall survival in cancer patients compared to previously published prediction models, and is coherent in that gene expression was associated with up-regulation of specific oncogenes and down-regulation of specific tumor suppressor genes associated with regulation of the multicellular state. |
| format | Article |
| id | doaj-art-91ed221401b54d5fb9766fa47c71ff87 |
| institution | Kabale University |
| issn | 1932-6203 |
| language | English |
| publishDate | 2017-01-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS ONE |
| spelling | doaj-art-91ed221401b54d5fb9766fa47c71ff872025-08-20T03:32:15ZengPublic Library of Science (PLoS)PLoS ONE1932-62032017-01-01123e017358910.1371/journal.pone.0173589Distance in cancer gene expression from stem cells predicts patient survival.Markus RiesterHua-Jun WuAhmet ZehirMithat GönenAndre L MoreiraRobert J DowneyFranziska MichorThe degree of histologic cellular differentiation of a cancer has been associated with prognosis but is subjectively assessed. We hypothesized that information about tumor differentiation of individual cancers could be derived objectively from cancer gene expression data, and would allow creation of a cancer phylogenetic framework that would correlate with clinical, histologic and molecular characteristics of the cancers, as well as predict prognosis. Here we utilized mRNA expression data from 4,413 patient samples with 7 diverse cancer histologies to explore the utility of ordering samples by their distance in gene expression from that of stem cells. A differentiation baseline was obtained by including expression data of human embryonic stem cells (hESC) and human mesenchymal stem cells (hMSC) for solid tumors, and of hESC and CD34+ cells for liquid tumors. We found that the correlation distance (the degree of similarity) between the gene expression profile of a tumor sample and that of stem cells orients cancers in a clinically coherent fashion. For all histologies analyzed (including carcinomas, sarcomas, and hematologic malignancies), patients with cancers with gene expression patterns most similar to that of stem cells had poorer overall survival. We also found that the genes in all undifferentiated cancers of diverse histologies that were most differentially expressed were associated with up-regulation of specific oncogenes and down-regulation of specific tumor suppressor genes. Thus, a stem cell-oriented phylogeny of cancers allows for the derivation of a novel cancer gene expression signature found in all undifferentiated forms of diverse cancer histologies, that is competitive in predicting overall survival in cancer patients compared to previously published prediction models, and is coherent in that gene expression was associated with up-regulation of specific oncogenes and down-regulation of specific tumor suppressor genes associated with regulation of the multicellular state.https://doi.org/10.1371/journal.pone.0173589 |
| spellingShingle | Markus Riester Hua-Jun Wu Ahmet Zehir Mithat Gönen Andre L Moreira Robert J Downey Franziska Michor Distance in cancer gene expression from stem cells predicts patient survival. PLoS ONE |
| title | Distance in cancer gene expression from stem cells predicts patient survival. |
| title_full | Distance in cancer gene expression from stem cells predicts patient survival. |
| title_fullStr | Distance in cancer gene expression from stem cells predicts patient survival. |
| title_full_unstemmed | Distance in cancer gene expression from stem cells predicts patient survival. |
| title_short | Distance in cancer gene expression from stem cells predicts patient survival. |
| title_sort | distance in cancer gene expression from stem cells predicts patient survival |
| url | https://doi.org/10.1371/journal.pone.0173589 |
| work_keys_str_mv | AT markusriester distanceincancergeneexpressionfromstemcellspredictspatientsurvival AT huajunwu distanceincancergeneexpressionfromstemcellspredictspatientsurvival AT ahmetzehir distanceincancergeneexpressionfromstemcellspredictspatientsurvival AT mithatgonen distanceincancergeneexpressionfromstemcellspredictspatientsurvival AT andrelmoreira distanceincancergeneexpressionfromstemcellspredictspatientsurvival AT robertjdowney distanceincancergeneexpressionfromstemcellspredictspatientsurvival AT franziskamichor distanceincancergeneexpressionfromstemcellspredictspatientsurvival |