Human cancer classification: a systems biology- based model integrating morphology, cancer stem cells, proteomics, and genomics

Abstract

Human cancer classification is currently based on the idea of cell of origin, light and electron microscopic attributes of the cancer. What is not yet integrated into cancer classification are the functional attributes of these cancer cells. Recent innovative techniques in biology have provided a wealth of information on the genomic, transcriptomic and proteomic changes in cancer cells. The emergence of the concept of cancer stem cells needs to be included in a classification model to capture the known attributes of cancer stem cells and their potential contribution to treatment response, and metastases. The integrated model of cancer classification presented here incorporates all morphology, cancer stem cell contributions, genetic, and functional attributes of cancer. Integrated cancer classification models could eliminate the unclassifiable cancers as used in current classifications. Future cancer treatment may be advanced by using an integrated model of cancer classification.

Keywords: Cancer Stem cells; Human Cancer; Integrated Classification; Multiple Omics.

Figure 1

Patterns and heterogeneity in Cancerous Prostate Tissue (Hematoxylin and eosin stain). A. Normal prostate showing luminal and basal cells. B. Prostate cancer with definable glandular pattern, usually part of Gleason pattern 3. C. Prostate cancer with aggregation, clustering or individual infiltrating cells as described for Gleason 4.

Figure 1

Patterns and heterogeneity in Cancerous Prostate Tissue (Hematoxylin and eosin stain). A. Normal prostate showing luminal and basal cells. B. Prostate cancer with definable glandular pattern, usually part of Gleason pattern 3. C. Prostate cancer with aggregation, clustering or individual infiltrating cells as described for Gleason 4.

Figure 1

Patterns and heterogeneity in Cancerous Prostate Tissue (Hematoxylin and eosin stain). A. Normal prostate showing luminal and basal cells. B. Prostate cancer with definable glandular pattern, usually part of Gleason pattern 3. C. Prostate cancer with aggregation, clustering or individual infiltrating cells as described for Gleason 4.

Figure 2

Comparison of Stem Cell and Lineage/Clonal Evolution Models of Cancer Cell Origin. (a)The lineage/clonal evolution model is used in morphological classification of cancer. One cell type gives rise to one cancer type. Squamous epithelium gives rise to squamous cell carcinoma. Pathologists do encounter squamous cell carcinoma in the urothelium of the urinary bladder. How we explain this is by “metaplasia of urothelium to squamous epithelium” and perhaps then to squamous cell carcinoma. An easier explanation will be cancer stem cell model as these have the capacity to become any cell type. (b) Cancer stem cells, with their inherent functional capacities including reduced cell death, are of interest when cancers are treated by irradiation or chemotherapy. Human cancers, examined in detail and extensively, do contain heterogeneous cell types; lung cancers are a good example. This leads to difficulties in some classification schemes depending on lineage.

Figure 2

Comparison of Stem Cell and Lineage/Clonal Evolution Models of Cancer Cell Origin. (a)The lineage/clonal evolution model is used in morphological classification of cancer. One cell type gives rise to one cancer type. Squamous epithelium gives rise to squamous cell carcinoma. Pathologists do encounter squamous cell carcinoma in the urothelium of the urinary bladder. How we explain this is by “metaplasia of urothelium to squamous epithelium” and perhaps then to squamous cell carcinoma. An easier explanation will be cancer stem cell model as these have the capacity to become any cell type. (b) Cancer stem cells, with their inherent functional capacities including reduced cell death, are of interest when cancers are treated by irradiation or chemotherapy. Human cancers, examined in detail and extensively, do contain heterogeneous cell types; lung cancers are a good example. This leads to difficulties in some classification schemes depending on lineage.

Figure 3

Figure Model of Cancer Classification. In this model, the Phenotype is represented by Morphological Characteristics/and subtypes; Proteomic profile can be derived from high-throughput tissue microarrays and immunohistochemistry plus automated computer-assisted quantitation with normalized intensities, protein microarrays and mass spectrometry; array comparative genomics for Copy Number Variation(CNV) and chromosomal aberrations, Genomic profiling using cDNA microarrays, and finally microRNA profiling. This provides protein profile and cDNA profiles for Gene Ontology and functional annotation. Signally pathways active or repressed can be derived. The CNV and microRNA data provide information to explain active oncogene induced pathways and miRNA targeted pathways that impact proliferation, cell survival, metastasis etc.