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Estimating developmental states of tumors and normal tissues using a linear time-ordered model.

ABSTRACT: BACKGROUND: Tumor cells are considered to have an aberrant cell state, and some evidence indicates different development states appearing in the tumorigenesis. Embryonic development and stem cell differentiation are ordered processes in which the sequence of events over time is highly conserved. The "cancer attractor" concept integrates normal developmental processes and tumorigenesis into a high-dimensional "cell state space", and provides a reasonable explanation of the relationship between these two biological processes from theoretical viewpoint. However, it is hard to describe such relationship by using existed experimental data; moreover, the measurement of different development states is also difficult. RESULTS: Here, by applying a novel time-ordered linear model based on a co-bisector which represents the joint direction of a series of vectors, we described the trajectories of development process by a line and showed different developmental states of tumor cells from developmental timescale perspective in a cell state space. This model was used to transform time-course developmental expression profiles of human ESCs, normal mouse liver, ovary and lung tissue into "cell developmental state lines". Then these cell state lines were applied to observe the developmental states of different tumors and their corresponding normal samples. Mouse liver and ovarian tumors showed different similarity to early development stage. Similarly, human glioma cells and ovarian tumors became developmentally "younger". CONCLUSIONS: The time-ordered linear model captured linear projected development trajectories in a cell state space. Meanwhile it also reflected the change tendency of gene expression over time from the developmental timescale perspective, and our finding indicated different development states during tumorigenesis processes in different tissues.

SUBMITTER: Zhang B

PROVIDER: S-EPMC3223864 | biostudies-other | 2011

REPOSITORIES: biostudies-other

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Estimating developmental states of tumors and normal tissues using a linear time-ordered model.

Zhang Bo B Chen Beibei B Wu Tao T Xuan Zhenyu Z Zhu Xiaopeng X Chen Runsheng R

BMC bioinformatics 20110211

<h4>Background</h4>Tumor cells are considered to have an aberrant cell state, and some evidence indicates different development states appearing in the tumorigenesis. Embryonic development and stem cell differentiation are ordered processes in which the sequence of events over time is highly conserved. The "cancer attractor" concept integrates normal developmental processes and tumorigenesis into a high-dimensional "cell state space", and provides a reasonable explanation of the relationship bet ...[more]

PMID: 21310084

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Project description:BackgroundTumor protein 63 (p63) is a transcription factor of the p53 gene family involved in differentiation of several tissues including squamous epithelium. p63 immunohistochemistry is broadly used for tumor classification but published data on its expression in cancer is conflicting.MethodsTo comprehensively catalogue p63 expression, tissue microarrays (TMAs) containing 12,620 tissue samples from 115 tumor entities and 76 normal tissue types were analyzed.Resultsp63 expression was seen in various normal tissues including squamous epithelium and urothelium. At least occasional weak p63 positivity could be detected in 61 (53%) of 115 different tumor types. The frequencies of p63 positivity was highest in squamous cell carcinomas irrespective of their origin (96-100%), thymic tumors (100%), urothelial carcinomas (81-100%), basal type tumors such as basal cell carcinomas (100%), and various salivary gland neoplasias (81-100%). As a rule, p63 was mostly expressed in cancers derived from p63 positive normal tissues and mostly not detectable in tumors derived from p63 negative cancers. However, exceptions from this rule occurred. A positive p63 immunostaining in cancers derived from p63 negative tissues was unrelated to aggressive phenotype in 422 pancreatic cancers, 160 endometrium cancers and 374 ovarian cancers and might be caused by aberrant squamous differentiation or represent stem cell properties. In 355 gastric cancers, aberrant p63 expression occurred in 4% and was linked to lymph node metastasis (p = 0.0208). Loss of p63 in urothelial carcinomas - derived from p63 positive urothelium - was significantly linked to advanced stage, high grade (p < 0.0001 each) and poor survival (p < 0.0001) and might reflect clinically relevant tumor dedifferentiation.ConclusionThe high prevalence of p63 expression in specific tumor types makes p63 immunohistochemistry a suitable diagnostic tool. Loss of p63 expression might constitute a feature of aggressive cancers.

Dataset Information

Estimating developmental states of tumors and normal tissues using a linear time-ordered model.

Publications

Estimating developmental states of tumors and normal tissues using a linear time-ordered model.

Similar Datasets

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