The cytologic criteria of malignancy

Cytology and cell biology are two separate fields that share a focus on cancer. Cancer is still diagnosed based on morphology, and surprisingly little is known about the molecular basis of the defining structural features. Cytology uses the smallest possible biopsy for diagnosis by reducing morphologic “criteria of malignancy” to the smallest scale. To begin to develop common ground, members of the American Society of Cytopathology Cell Biology Liaison Working Group classify some of the “criteria of malignancy” and review their relation to current cell biology concepts. The criteria of malignancy are extremely varied, apparently reflecting many different pathophysiologies in specific microenvironments. Criteria in Group 1 comprise tissue‐level alterations that appear to relate to resistance to anoikis, alterations in cell adhesion molecules, and loss of apical–basal polarity. Criteria in Group 2 reflect genetic instability, including chromosomal and possibly epigenetic instability. Criteria in Groups 3 are subcellular structural changes involving cytoplasmic components, nuclear lamina, chromatin and nucleoli that cannot be accounted for by genetic instability. Some distinct criteria in Group 3 are known to be induced by cancer genes, but their precise structural basis remains obscure. The criteria of malignancy are not closely related to the histogenetic classification of cancers, and they appear to provide an alternative, biologically relevant framework for establishing common ground between cytologists and cell biologists. To understand the criteria of malignancy at a molecular level would improve diagnosis, and likely point to novel cell physiologies that are not encompassed by current cell biology concepts. J. Cell. Biochem. 110: 795–811, 2010. © 2010 Wiley‐Liss, Inc.     

The yin-yang of PR-domain family genes in tumorigenesis

Cancer is essentially caused by alterations in normal cellular genes. Multiple gene changes involving at least two types of cancer genes, protooncogenes and tumor suppressor genes, are required for the clonal expansion of a malignant cell. This discussion focuses on the recently recognized role of a small but expanding family of PR-domain genes in tumorigenesis. The protein products of these genes are involved in human cancers in an unusual yin-yang fashion. Two products are normally produced from a PR-domain family member which differ by the presence or absence of the PR domain; the PR-plus product is disrupted or underexpressed whereas the PR-minus product is present or overexpressed in cancer cells. This imbalance in the amount of the two products, a result of either genetic or epigenetic events, appears to be an important cause of malignancy.     

Comprehensive genetic analysis of cancer cells

Human cancer is viewed as a disorder of genes originating from the progeny of a single cell that has accumulated multiple genetic alterations. The genetic alterations include point mutation, chromosomal rearrangements and imbalances. Amplifications primarily involve oncogenes whose overexpression leads to growth deregulation, while deletions commonly target tumor suppressor genes that control cell cycle checkpoints and DNA repair mechanisms. With the advent of molecular cytogenetics procedures for global detection of genomic imbalances and for multicolor visualization of structural chromosome changes, as well as the completion of human genome mapping and the development of microarray technology for serial gene expression analysis of the entire genomes, a significant progress has been made in uncovering the molecular basis of cancer. The major challenge in cancer biology is to decipher the molecular anatomy of various cancers and to identify cancer-related genes that now comprise only a fraction of human genes. The complete genetic anatomy of specific cancers would allow a better understanding of the role of genetic alterations in carcinogenesis, provide diagnostic and prognostic markers and discriminate between cells at different stages of progression toward malignancy. This review highlights current technologies that are available to explore cancer cells and outlines their application to investigations in human hepatocellular carcinoma.     

An Integrated Approach to Uncover Driver Genes in Breast Cancer Methylation Genomes

Background

Cancer cells typically exhibit large-scale aberrant methylation of gene promoters. Some of the genes with promoter methylation alterations play “driver” roles in tumorigenesis, whereas others are only “passengers”.

Results

Based on the assumption that promoter methylation alteration of a driver gene may lead to expression alternation of a set of genes associated with cancer pathways, we developed a computational framework for integrating promoter methylation and gene expression data to identify driver methylation aberrations of cancer. Applying this approach to breast cancer data, we identified many novel cancer driver genes and found that some of the identified driver genes were subtype-specific for basal-like, luminal-A and HER2+ subtypes of breast cancer.

Conclusion

The proposed framework proved effective in identifying cancer driver genes from genome-wide gene methylation and expression data of cancer. These results may provide new molecular targets for potential targeted and selective epigenetic therapy.     

Modeling cancer progression via pathway dependencies

Cancer is a heterogeneous disease often requiring a complexity of alterations to drive a normal cell to a malignancy and ultimately to a metastatic state. Certain genetic perturbations have been implicated for initiation and progression. However, to a great extent, underlying mechanisms often remain elusive. These genetic perturbations are most likely reflected by the altered expression of sets of genes or pathways, rather than individual genes, thus creating a need for models of deregulation of pathways to help provide an understanding of the mechanisms of tumorigenesis. We introduce an integrative hierarchical analysis of tumor progression that discovers which a priori defined pathways are relevant either throughout or in particular steps of progression. Pathway interaction networks are inferred for these relevant pathways over the steps in progression. This is followed by the refinement of the relevant pathways to those genes most differentially expressed in particular disease stages. The final analysis infers a gene interaction network for these refined pathways. We apply this approach to model progression in prostate cancer and melanoma, resulting in a deeper understanding of the mechanisms of tumorigenesis. Our analysis supports previous findings for the deregulation of several pathways involved in cell cycle control and proliferation in both cancer types. A novel finding of our analysis is a connection between ErbB4 and primary prostate cancer.     

Evolutionary dynamics of BRCA1 alterations in breast tumorigenesis

Cancer results from the accumulation of alterations in oncogenes and tumor suppressor genes. Tumor suppressors are classically defined as genes which contribute to tumorigenesis if their function is lost. Genetic or epigenetic alterations inactivating such genes may arise during somatic cell divisions or alternatively may be inherited from a parent. One notable exception to this rule is the BRCA1 tumor suppressor that predisposes to hereditary breast cancer when lost. Genetic alterations of this gene are hardly ever observed in sporadic breast cancer, while individuals harboring a germline mutation readily accumulate a second alteration inactivating the remaining allele—a finding which represents a conundrum in cancer genetics. In this paper, we present a novel mathematical framework of sporadic and hereditary breast tumorigenesis. We study the dynamics of genetic alterations driving breast tumorigenesis and explore those scenarios which can explain the absence of somatic BRCA1 alterations while replicating all other disease statistics. Our results support the existence of a heterozygous phenotype of BRCA1 and suggest that the loss of one BRCA1 allele may suppress the fitness advantage caused by the inactivation of other tumor suppressor genes. This paper contributes to the mathematical investigation of breast tumorigenesis.     

Cancer Evolution Is Associated with Pervasive Positive Selection on Globally Expressed Genes

Cancer is an evolutionary process in which cells acquire new transformative, proliferative and metastatic capabilities. A full understanding of cancer requires learning the dynamics of the cancer evolutionary process. We present here a large-scale analysis of the dynamics of this evolutionary process within tumors, with a focus on breast cancer. We show that the cancer evolutionary process differs greatly from organismal (germline) evolution. Organismal evolution is dominated by purifying selection (that removes mutations that are harmful to fitness). In contrast, in the cancer evolutionary process the dominance of purifying selection is much reduced, allowing for a much easier detection of the signals of positive selection (adaptation). We further show that, as a group, genes that are globally expressed across human tissues show a very strong signal of positive selection within tumors. Indeed, known cancer genes are enriched for global expression patterns. Yet, positive selection is prevalent even on globally expressed genes that have not yet been associated with cancer, suggesting that globally expressed genes are enriched for yet undiscovered cancer related functions. We find that the increased positive selection on globally expressed genes within tumors is not due to their expression in the tissue relevant to the cancer. Rather, such increased adaptation is likely due to globally expressed genes being enriched in important housekeeping and essential functions. Thus, our results suggest that tumor adaptation is most often mediated through somatic changes to those genes that are important for the most basic cellular functions. Together, our analysis reveals the uniqueness of the cancer evolutionary process and the particular importance of globally expressed genes in driving cancer initiation and progression.     

Zonal changes in the three-dimensional morphology of the chondron under compression: the relationship among cellular, pericellular, and extracellular deformation in articular cartilage

The pericellular matrix (PCM) is a narrow region of tissue that completely surrounds chondrocytes in articular cartilage. Previous theoretical models of the "chondron" (the PCM with enclosed cells) suggest that the structure and properties of the PCM may significantly influence the mechanical environment of the chondrocyte. The objective of this study was to quantify changes in the three-dimensional (3D) morphology of the chondron in situ at different magnitudes of compression applied to the cartilage extracellular matrix. Fluorescence immunolabeling for type-VI collagen was used to identify the boundaries of the cell and PCM, and confocal microscopy was used to form 3D images of chondrons from superficial, middle, and deep zone cartilage in explants compressed to 0%, 10%, 30%, and 50% surface-to-surface strain. Lagrangian tissue strain, determined locally using texture correlation, was highly inhomogeneous and revealed depth-dependent compressive stiffness and Poisson's ratio of the extracellular matrix. Compression significantly decreased cell and chondron height and volume, depending on the zone and magnitude of compression. In the superficial zone, cellular-level strains were always lower than tissue-level strains. In the middle and deep zones, however, tissue strains below 25% were amplified at the cellular level, while tissue strains above 25% were decreased at the cellular level. These findings are consistent with previous theoretical models of the chondron, suggesting that the PCM can serve as either a protective layer for the chondrocyte or a transducer that amplifies strain, such that cellular-level strains are more homogenous throughout the tissue depth despite large inhomogeneities in local ECM strains.     

A mathematical methodology for determining the temporal order of pathway alterations arising during gliomagenesis

Human cancer is caused by the accumulation of genetic alterations in cells. Of special importance are changes that occur early during malignant transformation because they may result in oncogene addiction and thus represent promising targets for therapeutic intervention. We have previously described a computational approach, called Retracing the Evolutionary Steps in Cancer (RESIC), to determine the temporal sequence of genetic alterations during tumorigenesis from cross-sectional genomic data of tumors at their fully transformed stage. Since alterations within a set of genes belonging to a particular signaling pathway may have similar or equivalent effects, we applied a pathway-based systems biology approach to the RESIC methodology. This method was used to determine whether alterations of specific pathways develop early or late during malignant transformation. When applied to primary glioblastoma (GBM) copy number data from The Cancer Genome Atlas (TCGA) project, RESIC identified a temporal order of pathway alterations consistent with the order of events in secondary GBMs. We then further subdivided the samples into the four main GBM subtypes and determined the relative contributions of each subtype to the overall results: we found that the overall ordering applied for the proneural subtype but differed for mesenchymal samples. The temporal sequence of events could not be identified for neural and classical subtypes, possibly due to a limited number of samples. Moreover, for samples of the proneural subtype, we detected two distinct temporal sequences of events: (i) RAS pathway activation was followed by TP53 inactivation and finally PI3K2 activation, and (ii) RAS activation preceded only AKT activation. This extension of the RESIC methodology provides an evolutionary mathematical approach to identify the temporal sequence of pathway changes driving tumorigenesis and may be useful in guiding the understanding of signaling rearrangements in cancer development.     

Cancer metabolism within tumor microenvironments

Background: Tumor microenvironments could determine cancer heterogeneity and malignancy. Hypoxia, nutrition starvation, and acidic pH could contribute to cancer malignancy associated with genetic, epigenetic, and metabolic alterations, promoting invasion and metastasis. Cancer cells adapting to extreme tumor microenvironments could enable evasion of cell death and immune responses. It could stimulate drug resistance and recurrence, resulting in poor patient prognosis. Therefore, investigating druggable targets of the malignant cancer cells within tumor microenvironments is necessary, but such treatments are limited. Cell-cell metabolic interaction may also contribute to cancer malignancy within the tumor microenvironments. Organelle-organelle interactions have recently gained attention as new cancer therapy targets as they play essential roles in the metabolic adaptation to the tumor microenvironment.In this review, we overview (1) metabolic alterations within tumor microenvironments, (2) cell-to-cell, and (3) organelle-to-organelle metabolic interactions, and we add novel insights into cancer therapy.     

Stochastic Tunneling of Two Mutations in a Population of Cancer Cells

Cancer initiation, progression, and the emergence of drug resistance are driven by specific genetic and/or epigenetic alterations such as point mutations, structural alterations, DNA methylation and histone modification changes. These alterations may confer advantageous, deleterious or neutral effects to mutated cells. Previous studies showed that cells harboring two particular alterations may arise in a fixed-size population even in the absence of an intermediate state in which cells harboring only the first alteration take over the population; this phenomenon is called stochastic tunneling. Here, we investigated a stochastic Moran model in which two alterations emerge in a cell population of fixed size. We developed a novel approach to comprehensively describe the evolutionary dynamics of stochastic tunneling of two mutations. We considered the scenarios of large mutation rates and various fitness values and validated the accuracy of the mathematical predictions with exact stochastic computer simulations. Our theory is applicable to situations in which two alterations are accumulated in a fixed-size population of binary dividing cells.     

Protein-tyrosine kinase and protein-serine/threonine kinase expression in human gastric cancer cell lines

Protein kinases play key roles in cellular functions. They are involved in many cellular functions including; signal transduction, cell cycle regulation, cell division, and cell differentiation. Alterations of protein kinase by gene amplification, mutation or viral factors often induce tumor formation and tumor progression toward malignancy. The identification and cloning of kinase genes can provide a better understanding of the mechanisms of tumorigenesis as well as diagnostic tools for tumor staging. In this study, we have used degenerated polymerase-chain-reaction primers according to the consensus catalytic domain motifs to amplify protein kinase genes (protein-tyrosine kinase, PTK, and protein-serine/threonine kinase, PSK) from human stomach cancer cells. Following amplification, the protein kinase molecules expressed in the gastric cancer cells were cloned into plasmid vectors for cloning and sequencing. Sequence analysis of polymerase-chain-reaction products resulted in the identification of 25 protein kinases, including two novel ones. Expression of several relevant PTK/PSK genes in gastric cancer cells and tissues was further substantiated by RT-PCR using gene-specific primers. The identification of protein kinases expressed or activated in the gastric cancer cells provide the framework to understand the oncogenic process of stomach cancer.     

Loss of annexin A1 expression in human breast cancer detected by multiple high-throughput analyses

To test the efficacy of combined high-throughput analyses (HTA) in target gene identification, screening criteria were set using >fivefold difference by microarray and statistically significant changes (p<0.01) in SAGE and EST. Microarray analysis of two normal and seven breast cancer samples found 129 genes with >fivefold changes. Further SAGE and EST analyses of these genes identified four qualified genes, ERBB2, GATA3, AGR2, and ANXA1. Their expression pattern was validated by RT-PCR in both breast cell lines and tissue samples. Loss of ANXA1 in breast cancer was further confirmed at mRNA level by Human Breast Cancer Tissue Profiling Array and at protein level by immunohistochemical staining. This study demonstrated that combined HTA effectively narrowed the number of genes for further study, while retaining the sensitivity in identifying biologically important genes such as ERBB2 and ANXA1. A distinctive loss of ANXA1 in breast cancer suggests its involvement in maintaining normal breast biology.     

Glycogene expression alterations associated with pancreatic cancer epithelial-mesenchymal transition in complementary model systems

Background

The ability to selectively detect and target cancer cells that have undergone an epithelial-mesenchymal transition (EMT) may lead to improved methods to treat cancers such as pancreatic cancer. The remodeling of cellular glycosylation previously has been associated with cell differentiation and may represent a valuable class of molecular targets for EMT.

Methodology/Principal Findings

As a first step toward investigating the nature of glycosylation alterations in EMT, we characterized the expression of glycan-related genes in three in-vitro model systems that each represented a complementary aspect of pancreatic cancer EMT. These models included: 1) TGFβ-induced EMT, which provided a look at the active transition between states; 2) a panel of 22 pancreatic cancer cell lines, which represented terminal differentiation states of either epithelial-like or mesenchymal-like; and 3) actively-migrating and stationary cells, which provided a look at the mechanism of migration. We analyzed expression data from a list of 587 genes involved in glycosylation (biosynthesis, sugar transport, glycan-binding, etc.) or EMT. Glycogenes were altered at a higher prevalence than all other genes in the first two models (p<0.05 and <0.005, respectively) but not in the migration model. Several functional themes were shared between the induced-EMT model and the cell line panel, including alterations to matrix components and proteoglycans, the sulfation of glycosaminoglycans; mannose receptor family members; initiation of O-glycosylation; and certain forms of sialylation. Protein-level changes were confirmed by Western blot for the mannose receptor MRC2 and the O-glycosylation enzyme GALNT3, and cell-surface sulfation changes were confirmed using Alcian Blue staining.

Conclusions/Significance

Alterations to glycogenes are a major component of cancer EMT and are characterized by changes to matrix components, the sulfation of GAGs, mannose receptors, O-glycosylation, and specific sialylated structures. These results provide leads for targeting aggressive and drug resistant forms of pancreatic cancer cells.