Using the "Hallmarks of Cancer" as a framework for medical students and clinicians to understand oncogenesis.

Two landmark reviews in 2000 and 2011, describing the "Hallmarks of Cancer", provided a new and valuable framework for understanding the process of oncogenesis as a progressive accumulation of characteristics, each characteristic essential for a tumor to become a clinically relevant, metastatic neoplasia. The process of oncogenesis is conceptually important for physicians, both for clinical reasons, and for their engagement in oncological research. However, these reviews are written for specialists in the field, which presents barriers for novice learners. Therefore, to allow students, and also clinicians external to the oncological field, to access this valuable framework for understanding oncogenesis, we have created a condensed summary of the original reviews. Our institutions use a "flipped" approach to the large-group components of our preclinical education. We have successfully used our Hallmarks of Cancer summary as the prework for sessions on oncogenesis for five years at one institution, and nine years at the other, typically at the end of cancer blocks within integrated, multidisciplinary courses. We report here survey results indicating learners strongly appreciate the summary as both preparation material for participation in relevant flipped classroom sessions, and as a general review of oncogenesis. This condensed summary of the original Hallmarks of Cancer reviews makes many of the key concepts of oncogenesis available to medical students in their preclinical years, as well as to physicians outside the field of oncology.

Missing-in-Metastasis regulates cell motility and invasion via PTPδ-mediated changes in SRC activity.

MIM (Missing-in-Metastasis), also known as MTSS1 (metastasis suppressor 1), is a scaffold protein that is down-regulated in multiple metastatic cancer cell lines compared with non-metastatic counterparts. MIM regulates cytoskeletal dynamics and actin polymerization, and has been implicated in the control of cell motility and invasion. MIM has also been shown to bind to a receptor PTP (protein tyrosine phosphatase), PTPδ, an interaction that may provide a link between tyrosine-phosphorylation-dependent signalling and metastasis. We used shRNA-mediated gene silencing to investigate the consequences of loss of MIM on the migration and invasion of the MCF10A mammary epithelial cell model of breast cancer. We observed that suppression of MIM by RNAi enhanced migration and invasion of MCF10A cells, effects that were associated with increased levels of PTPδ. Furthermore, analysis of human clinical data indicated that PTPδ was elevated in breast cancer samples when compared with normal tissue. We demonstrated that the SRC protein tyrosine kinase is a direct substrate of PTPδ and, upon suppression of MIM, we observed changes in the phosphorylation status of SRC; in particular, the inhibitory site (Tyr527) was hypophosphorylated, whereas the activating autophosphorylation site (Tyr416) was hyperphosphorylated. Thus the absence of MIM led to PTPδ-mediated activation of SRC. Finally, the SRC inhibitor SU6656 counteracted the effects of MIM suppression on cell motility and invasion. The present study illustrates that both SRC and PTPδ have the potential to be therapeutic targets for metastatic tumours associated with loss of MIM.

A quantitative proteomics-based signature of platinum sensitivity in ovarian cancer cell lines.

Although DNA encodes the molecular instructions that underlie the control of cell function, it is the proteins that are primarily responsible for implementing those instructions. Therefore quantitative analyses of the proteome would be expected to yield insights into important candidates for the detection and treatment of disease. We present an iTRAQ (isobaric tag for relative and absolute quantification)-based proteomic analysis of ten ovarian cancer cell lines and two normal ovarian surface epithelial cell lines. We profiled the abundance of 2659 cellular proteins of which 1273 were common to all 12 cell lines. Of the 1273, 75 proteins exhibited elevated expression and 164 proteins had diminished expression in the cancerous cells compared with the normal cell lines. The iTRAQ expression profiles allowed us to segregate cell lines based upon sensitivity and resistance to carboplatin. Importantly, we observed no substantial correlation between protein abundance and RNA expression or epigenetic DNA methylation data. Furthermore, we could not discriminate between sensitivity and resistance to carboplatin on the basis of RNA expression and DNA methylation data alone. The present study illustrates the importance of proteomics-based discovery for defining the basis for the carboplatin response in ovarian cancer and highlights candidate proteins, particularly involved in cellular redox regulation, homologous recombination and DNA damage repair, which otherwise could not have been predicted from whole genome and expression data sources alone.

Protein-tyrosine phosphatase 1B antagonized signaling by insulin-like growth factor-1 receptor and kinase BRK/PTK6 in ovarian cancer cells.

Ovarian cancer, which is the leading cause of death from gynecological malignancies, is a heterogeneous disease known to be associated with disruption of multiple signaling pathways. Nevertheless, little is known regarding the role of protein phosphatases in the signaling events that underlie the disease; such knowledge will be essential to gain a complete understanding of the etiology of the disease and how to treat it. We have demonstrated that protein-tyrosine phosphatase 1B (PTP1B) was underexpressed in a panel of ovarian carcinoma-derived cell lines, compared with immortalized human ovarian surface epithelial cell lines. Stable restoration of PTP1B in those cancer cell lines substantially decreased cell migration and invasion, as well as proliferation and anchorage-independent survival. Mechanistically, the pro-survival IGF-1R signaling pathway was attenuated upon ectopic expression of PTP1B. This was due to dephosphorylation by PTP1B of IGF-1R ß-subunit and BRK/PTK6, an SRC-like protein-tyrosine kinase that physically and functionally interacts with the IGF-1R ß-subunit. Restoration of PTP1B expression led to enhanced activation of BAD, one of the major pro-death members of the BCL-2 family, which triggered cell death through apoptosis. Conversely, inhibition of PTP1B with a small molecular inhibitor, MSI-1436, increased proliferation and migration of immortalized HOSE cell lines. These data reveal an important role for PTP1B as a negative regulator of BRK and IGF-1Rß signaling in ovarian cancer cells.

Loss of DOK2 induces carboplatin resistance in ovarian cancer via suppression of apoptosis.

OBJECTIVE: Ovarian cancers are highly heterogeneous and while chemotherapy is the preferred treatment many patients are intrinsically resistant or quickly develop resistance. Furthermore, all tumors that recur ultimately become resistant. Recent evidence suggests that epigenetic deregulation may be a key factor in the onset and maintenance of chemoresistance. We set out to identify epigenetically silenced genes that affect chemoresistance. METHODS: The epigenomes of a total of 45 ovarian samples were analyzed to identify epigenetically altered genes that segregate with platinum response, and further filtered with expression data to identify genes that were suppressed. A tissue culture carboplatin resistance screen was utilized to functionally validate this set of candidate platinum resistance genes. RESULTS: Our screen correctly identified 19 genes that when suppressed altered the chemoresistance of the cells in culture. Of the genes identified in the screen we further characterized one gene, docking protein 2 (DOK2), an adapter protein downstream of tyrosine kinase, to determine if we could elucidate the mechanism by which it increased resistance. The loss of DOK2 decreased the level of apoptosis in response to carboplatin. Furthermore, in cells with reduced DOK2, the level of anoikis was decreased. CONCLUSIONS: We have developed a screening methodology that analyzes the epigenome and informatically identifies candidate genes followed by in vitro culture screening of the candidate genes. To validate our screening methodology we further characterized one candidate gene, DOK2, and showed that loss of DOK2 induces chemotherapy resistance by decreasing the level of apoptosis in response to treatment.

High-content analysis of cancer genome DNA alterations.

New technologies as well as concerted brute-force approaches have increased the content (number of genes) that can be characterized for genomic DNA alterations. Recent advances include the detection of activating point mutations in key kinase genes (BRAF, EGFR, and PIK3CA) in multiple cancer types: preliminary insight into the entire repertoire of genes that can be mutated in cancer; the discovery of new oncogenes by high-resolution profiling of DNA copy number alterations; and the bioinformatic-driven discovery of oncogenic gene fusions. High-content promoter methylation detection systems have been used to discover additional methylated genes and have provided evidence for a stem cell origin for certain tumors. Some of these advances have had significant impact on the development and clinical testing of new therapeutics.

Methylation detection oligonucleotide microarray analysis: a high-resolution method for detection of CpG island methylation.

Methylation of CpG islands associated with genes can affect the expression of the proximal gene, and methylation of non-associated CpG islands correlates to genomic instability. This epigenetic modification has been shown to be important in many pathologies, from development and disease to cancer. We report the development of a novel high-resolution microarray that detects the methylation status of over 25,000 CpG islands in the human genome. Experiments were performed to demonstrate low system noise in the methodology and that the array probes have a high signal to noise ratio. Methylation measurements between different cell lines were validated demonstrating the accuracy of measurement. We then identified alterations in CpG islands, both those associated with gene promoters, as well as non-promoter-associated islands in a set of breast and ovarian tumors. We demonstrate that this methodology accurately identifies methylation profiles in cancer and in principle it can differentiate any CpG methylation alterations and can be adapted to analyze other species.

Combining Algorithms to Find Signatures That Predict Risk in Early-Stage Stomach Cancer.

This study applied two mathematical algorithms, lattice up-stream targeting (LUST) and D -basis, to the identification of prognostic signatures from cancer gene expression data. The LUST algorithm looks for metagenes, which are sets of genes that are either overexpressed or underexpressed in the same patients. Whereas LUST runs unsupervised by clinical data, the D -basis algorithm uses implications and association rules to relate gene expression to clinical outcomes. The D -basis selects a small subset of the metagene (a signature) to predict survival. The two algorithms, LUST and D-basis, were combined and applied to mRNA expression and clinical data from The Cancer Genome Atlas (TCGA) for 203 stage 1 and 2 stomach cancer patients. Two small (four-gene) signatures effectively predict survival in early-stage stomach cancer patients. These signatures could be used as a guide for treatment. The first signature (DU4) consists of genes that are underexpressed on the long-survival/low-risk group: FLRT2, KCNB1, MYOC, and TNXB. The second signature consists of genes that are overexpressed on the short-survival/high-risk group: ASB5, SFRP1, SMYD1, and TACR2. Another nine-gene signature (REC9) predicts recurrence: BNC2, CCDC8, DPYSL3, MOXD1, MXRA8, PRELP, SCARF2, TAGLN, and ZNF423. Each patient is assigned a score that is a linear combination of the expression levels for the genes in the signature. Scores below a selected threshold predict low-risk/long survival, whereas high scores indicate a high risk of short survival. The metagenes associate with TCGA cluster C1. Both our signatures and cluster C1 identify tumors that are genomically silent, and have a low mutation load or mutation count. Furthermore, our signatures identify tumors that are predominantly in the WHO classification of poorly cohesive and the Lauren class of diffuse samples, which have a poor prognosis.

Genomic events associated with progression of pleural malignant mesothelioma.

Pleural malignant mesothelioma (MM) is an aggressive cancer with a very long latency and a very short median survival. Little is known about the genetic events that trigger MM and their relation to poor outcome. The goal of our study was to characterize major genomic gains and losses associated with MM origin and progression and assess their clinical significance. We performed Representative Oligonucleotide Microarray Analysis (ROMA) on DNA isolated from tumors of 22 patients who recurred at variable interval with the disease after surgery. The total number of copy number alterations (CNA) and frequent imbalances for patients with short time (<12 months from surgery) and long time to recurrence were recorded and mapped using the Analysis of Copy Errors algorithm. We report a profound increase in CNA in the short-time recurrence group with most chromosomes affected, which can be explained by chromosomal instability associated with MM. Deletions in chromosomes 22q12.2, 19q13.32 and 17p13.1 appeared to be the most frequent events (55-74%) shared between MM patients followed by deletions in 1p, 9p, 9q, 4p, 3p and gains in 5p, 18q, 8q and 17q (23-55%). Deletions in 9p21.3 encompassing CDKN2A/ARF and CDKN2B were characterized as specific for the short-term recurrence group. Analysis of the minimal common areas of frequent gains and losses identified candidate genes that may be involved in different stages of MM: OSM (22q12.2), FUS1 and PL6 (3p21.3), DNAJA1 (9p21.1) and CDH2 (18q11.2-q12.3). Imbalances seen by ROMA were confirmed by Affymetrix genome analysis in a subset of samples.

Comparative genomic hybridization by representational oligonucleotide microarray analysis.

The central cause to any cancer ultimately lies in the genome and the initial alterations that result in changes in gene expression that are reflected in the phenotype of the cancer cell. The gene expression data are rich in information but the primary lesions responsible for carcinogenesis are obscured due to the complex cascade of expression changes that can occur. The primary lesions can be characterized by the smallest of point mutations to small insertions and deletions (in/dels) to much larger deletions and amplifications (for simplicity all copy number gains will be referred to as amplifications) as well as balanced or unbalanced translocations. In addition to these mutations there are a myriad of epigenetic alterations that affect the cells phenotype. Any gene if important to tumor growth will be altered by mutation or by deletion/amplification eventually, and if a large number of tumor samples is analyzed the majority of these genes will be detected. This chapter describes a variation of comparative genomic hybridization, called Representational oligonucleotide microarray analysis (ROMA), that surveys reduced-complexity representations of tumor genomic DNA to discover deletions and amplifications (and the underlying cancer genes).