A personalized probabilistic approach to ovarian cancer diagnostics.

OBJECTIVE: The identification/development of a machine learning-based classifier that utilizes metabolic profiles of serum samples to accurately identify individuals with ovarian cancer. METHODS: Serum samples collected from 431 ovarian cancer patients and 133 normal women at four geographic locations were analyzed by mass spectrometry. Reliable metabolites were identified using recursive feature elimination coupled with repeated cross-validation and used to develop a consensus classifier able to distinguish cancer from non-cancer. The probabilities assigned to individuals by the model were used to create a clinical tool that assigns a likelihood that an individual patient sample is cancer or normal. RESULTS: Our consensus classification model is able to distinguish cancer from control samples with 93% accuracy. The frequency distribution of individual patient scores was used to develop a clinical tool that assigns a likelihood that an individual patient does or does not have cancer. CONCLUSIONS: An integrative approach using metabolomic profiles and machine learning-based classifiers has been employed to develop a clinical tool that assigns a probability that an individual patient does or does not have ovarian cancer. This personalized/probabilistic approach to cancer diagnostics is more clinically informative and accurate than traditional binary (yes/no) tests and represents a promising new direction in the early detection of ovarian cancer.

Cancer Exacerbates Chemotherapy-Induced Sensory Neuropathy.

For the constellation of neurologic disorders known as chemotherapy-induced peripheral neuropathy, mechanistic understanding and treatment remain deficient. Here, we present the first evidence that chronic sensory neuropathy depends on nonlinear interactions between cancer and chemotherapy. Global transcriptional profiling of dorsal root ganglia revealed differential expression, notably in regulators of neuronal excitability, metabolism, and inflammatory responses, all of which were unpredictable from effects observed with either chemotherapy or cancer alone. Systemic interactions between cancer and chemotherapy also determined the extent of deficits in sensory encoding and ion channel protein expression by single mechanosensory neurons, with the potassium ion channel Kv3.3 emerging as one potential contributor to sensory neuron dysfunction. Validated measures of sensorimotor behavior in awake, behaving animals revealed dysfunction after chronic chemotherapy treatment was exacerbated by cancer. Notably, errors in precise forelimb placement emerged as a novel behavioral deficit unpredicted by our previous study of chemotherapy alone. These original findings identify novel contributors to peripheral neuropathy and emphasize the fundamental dependence of neuropathy on the systemic interaction between chemotherapy and cancer. SIGNIFICANCE: These findings highlight the need to account for pathobiological interactions between cancer and chemotherapy as a major contributor to neuropathy and will have significant and immediate impact on future investigations in this field.

MEDICASCY: A Machine Learning Approach for Predicting Small-Molecule Drug Side Effects, Indications, Efficacy, and Modes of Action.

To improve the drug discovery yield, a method which is implemented at the beginning of drug discovery that accurately predicts drug side effects, indications, efficacy, and mode of action based solely on the input of the drug's chemical structure is needed. In contrast, extant predictive methods do not comprehensively address these aspects of drug discovery and rely on features derived from extensive, often unavailable experimental information for novel molecules. To address these issues, we developed MEDICASCY, a multilabel-based boosted random forest machine learning method that only requires the small molecule's chemical structure for the drug side effect, indication, efficacy, and probable mode of action target predictions; however, it has comparable or even significantly better performance than existing approaches requiring far more information. In retrospective benchmarking on high confidence predictions, MEDICASCY shows about 78% precision and recall for predicting at least one severe side effect and 72% precision drug efficacy. Experimental validation of MEDICASCY's efficacy predictions on novel molecules shows close to 80% precision for the inhibition of growth in ovarian, breast, and prostate cancer cell lines. Thus, MEDICASCY should improve the success rate for new drug approval. A web service for academic users is available at http://pwp.gatech.edu/cssb/MEDICASCY.

The ability of miRNAs to induce mesenchymal-to-epithelial transition (MET) in cancer cells is highly dependent upon genetic background.

Understanding of the molecular basis of host cell-miRNA interactions is prerequisite to the successful application of miRNAs as potential therapeutic agents. We studied the morphological and molecular consequences of over expression of three sequence divergent miRNAs previously implicated in the mesenchymal-to-epithelial transition process (MET) in three distinct mesenchymal-like cancer cell lines. The ability of miRNAs to induce morphological changes characteristic of MET positively correlated with induced changes in the expression of genes previously implicated in the process. Variability in the responses of different mesenchymal-like cells to over expression of the same miRNAs was attributable to inherent differences in trans-regulatory profiles pre-disposing these cells to miRNA-induced MET. Collectively our results indicate that miRNA-mediated regulation of MET is a highly integrated process that is significantly modulated by the molecular background of individual cells.

Sequence diverse miRNAs converge to induce mesenchymal-to-epithelial transition in ovarian cancer cells through direct and indirect regulatory controls.

Epithelial-to-mesenchymal transition (EMT) has been shown to be similarly regulated by multiple miRNAs, some displaying little or no sequence identity. While alternate models have been proposed to explain the functional convergence of sequence divergent miRNAs, little experimental evidence exists to elucidate the underlying mechanisms involved. Representative members of the miR-200 family of miRNAs and the sequence divergent miR-205 miRNA were independently over expressed in mesenchymal-like ovarian cancer (OC) cells resulting in mesenchymal-to-epithelial transition (MET). The miR-205 and the miR-200 family of miRNAs were found to coordinately induce MET in mesenchymal-like OC cells by affecting both direct and indirect changes in the expression of genes previously associated with EMT/MET. Only two direct targets of these miRNAs (ZEB 1 and WNT5A) are commonly down regulated in response to over-expression of miR-205 and/or the miR-200 family of miRNAs. Down-regulation of these genes, alone or in combination, only partially recapitulates the changes induced by the miRNAs indicating an additional contribution of indirect changes regulated by the miRNAs. Combined gene expression analyses and phylogenetic comparisons suggest an evolutionarily more recent involvement of miR-205 in the EMT/MET process.

Essential role of JunD in cell proliferation is mediated via MYC signaling in prostate cancer cells.

JunD, a member of the AP-1 family, is essential for cell proliferation in prostate cancer (PCa) cells. We recently demonstrated that JunD knock-down (KD) in PCa cells results in cell cycle arrest in G1-phase concomitant with a decrease in cyclin D1, Ki67, and c-MYC, but an increase in p21 levels. Furthermore, the over-expression of JunD significantly increased proliferation suggesting JunD regulation of genes required for cell cycle progression. Here, employing gene expression profiling, quantitative proteomics, and validation approaches, we demonstrate that JunD KD is associated with distinct gene and protein expression patterns. Comparative integrative analysis by Ingenuity Pathway Analysis (IPA) identified 1) cell cycle control/regulation as the top canonical pathway whose members exhibited a significant decrease in their expression following JunD KD including PRDX3, PEA15, KIF2C, and CDK2, and 2) JunD dependent genes are associated with cell proliferation, with MYC as the critical downstream regulator. Conversely, JunD over-expression induced the expression of the above genes including c-MYC. We conclude that JunD is a crucial regulator of cell cycle progression and inhibiting its target genes may be an effective approach to block prostate carcinogenesis.

Machine learning predicts individual cancer patient responses to therapeutic drugs with high accuracy.

Precision or personalized cancer medicine is a clinical approach that strives to customize therapies based upon the genomic profiles of individual patient tumors. Machine learning (ML) is a computational method particularly suited to the establishment of predictive models of drug response based on genomic profiles of targeted cells. We report here on the application of our previously established open-source support vector machine (SVM)-based algorithm to predict the responses of 175 individual cancer patients to a variety of standard-of-care chemotherapeutic drugs from the gene-expression profiles (RNA-seq or microarray) of individual patient tumors. The models were found to predict patient responses with >80% accuracy. The high PPV of our algorithms across multiple drugs suggests a potential clinical utility of our approach, particularly with respect to the identification of promising second-line treatments for patients failing standard-of-care first-line therapies.

Time-course analysis of microRNA-induced mesenchymal-to-epithelial transition underscores the complexity of the underlying molecular processes.

Expression levels of the miR-200 family of miRNAs are significantly reduced during the epithelial-to-mesenchymal transition (EMT) and consequent metastasis of ovarian and other cancers. Consistently, ectopic over-expression of miR-200 family miRNAs in mesenchymal-like cells reverses the process by converting treated cells to an epithelial phenotype, thereby reducing invasiveness and increasing sensitivity to chemotherapeutic drugs. To better understand the dynamics and molecular processes underlying miRNA-induced mesenchymal-to mesenchymal transition (MET), a time-course study was conducted where miRNA-induced morphological and molecular changes associated with MET were monitored over a period of 144 h. Morphological transition from an elongated mesenchymal-like to a cuboidal epithelial-like phenotype is maximized at 48 h with cells returning to the elongated phenotype by 144 h. Changes in the expression of >3000 genes, including many previously associated with epithelial-to-mesenchymal transition (EMT), are most pronounced at 48 h, and approach starting levels of expression by 144 h. The majority of these genes are not direct targets of miR-429. Targeted (siRNA) inhibition of key miR-429 regulated genes previously implicated as drivers of EMT/MET, do not recapitulate miR-429 induced MET indicating that the underlying molecular processes are complex.

Evidence for the importance of post-transcriptional regulatory changes in ovarian cancer progression and the contribution of miRNAs.

High-throughput technologies have identified significant changes in patterns of mRNA expression over cancer development but the functional significance of these changes often rests upon the assumption that observed changes in levels of mRNA accurately reflect changes in levels of their encoded proteins. We systematically compared the expression of 4436 genes on the RNA and protein levels between discrete tumor samples collected from the ovary and from the omentum of the same OC patient. The overall correlation between global changes in levels of mRNA and their encoding proteins is low (r = 0.38). The majority of differences are on the protein level with no corresponding change on the mRNA level. Indirect and direct evidence indicates that a significant fraction of the differences may be mediated by microRNAs.

Snail-induced epithelial-to-mesenchymal transition of MCF-7 breast cancer cells: systems analysis of molecular changes and their effect on radiation and drug sensitivity.

BACKGROUND: Epithelial-to-mesenchymal transition (EMT) has been associated with the acquisition of metastatic potential and the resistance of cancer cells to therapeutic treatments. MCF-7 breast cancer cells engineered to constitutively express the zinc-finger transcriptional repressor gene Snail (MCF-7-Snail cells) have been previously shown to display morphological and molecular changes characteristic of EMT. We report here the results of a comprehensive systems level molecular analysis of changes in global patterns of gene expression and levels of glutathione and reactive oxygen species (ROS) in MCF-7-Snail cells and the consequence of these changes on the sensitivity of cells to radiation treatment and therapeutic drugs. METHODS: Snail-induced changes in global patterns of gene expression were identified by microarray profiling using the Affymetrix platform (U133 Plus 2.0). The resulting data were processed and analyzed by a variety of system level analytical methods. Levels of ROS and glutathione (GSH) were determined by fluorescent and luminescence assays, and nuclear levels of NF-κB protein were determined by an ELISA based method. The sensitivity of cells to ionizing radiation and anticancer drugs was determined using a resazurin-based cell cytotoxicity assay. RESULTS: Constitutive ectopic expression of Snail in epithelial-like, luminal A-type MCF-7 cells induced significant changes in the expression of >7600 genes including gene and miRNA regulators of EMT. Mesenchymal-like MCF-7-Snail cells acquired molecular profiles characteristic of triple-negative, claudin-low breast cancer cells, and displayed increased sensitivity to radiation treatment, and increased, decreased or no change in sensitivity to a variety of anticancer drugs. Elevated ROS levels in MCF-7-Snail cells were unexpectedly not positively correlated with NF-κB activity. CONCLUSIONS: Ectopic expression of Snail in MCF-7 cells resulted in morphological and molecular changes previously associated with EMT. The results underscore the complexity and cell-type dependent nature of the EMT process and indicate that EMT is not necessarily predictive of decreased resistance to radiation and drug-based therapies.

Functional and evolutionary significance of human microRNA seed region mutations.

MicroRNAs have emerged in recent years as important regulators of cell function in both normal and diseased cells. MiRNAs coordinately regulate large suites of target genes by mRNA degradation and/or translational inhibition. The mRNA target specificities of miRNAs in animals are primarily encoded within a 7 nt "seed region" mapping to positions 2-8 at the molecule's 5' end. We here combine computational analyses with experimental studies to explore the functional significance of sequence variation within the seed region of human miRNAs. The results indicate that a substitution of even a single nucleotide within the seed region changes the spectrum of mRNA targets by >50%. The high functional cost of even single nucleotide changes within seed regions is consistent with their high sequence conservation among miRNA families both within and between species and suggests processes that may underlie the evolution of miRNA regulatory control.

Transcriptional override: a regulatory network model of indirect responses to modulations in microRNA expression.

BACKGROUND: Documented changes in levels of microRNAs (miRNA) in a variety of diseases including cancer are leading to their development as early indicators of disease, and as a potential new class of therapeutic agents. A significant hurdle to the rational application of miRNAs as therapeutics is our current inability to reliably predict the range of molecular and cellular consequences of perturbations in the levels of specific miRNAs on targeted cells. While the direct gene (mRNA) targets of individual miRNAs can be computationally predicted with reasonable degrees of accuracy, reliable predictions of the indirect molecular effects of perturbations in miRNA levels remain a major challenge in molecular systems biology. RESULTS: Changes in gene (mRNA) and miRNA expression levels between normal precursor and ovarian cancer cells isolated from patient tissue samples were measured by microarray. Expression of 31 miRNAs was significantly elevated in the cancer samples. Consistent with previous reports, the expected decrease in expression of the mRNA targets of upregulated miRNAs was observed in only 20-30% of the cancer samples. We present and provide experimental support for a network model (The Transcriptional Override Model; TOM) to account for the unexpected regulatory consequences of modulations in the expression of miRNAs on expression levels of their target mRNAs in ovarian cancer. CONCLUSIONS: The direct and indirect regulatory effects of changes in miRNA expression levels in vivo are interactive and complex but amenable to systems level modeling. Although TOM has been developed and validated within the context of ovarian cancer, it may be applicable in other biological contexts as well, including of potential future use in the rational design of miRNA-based strategies for the treatment of cancers and other diseases.

Evidence for the importance of personalized molecular profiling in pancreatic cancer.

OBJECTIVES: There is a growing body of evidence that targeted gene therapy holds great promise for the future treatment of cancer. A crucial step in this therapy is the accurate identification of appropriate candidate genes/pathways for targeted treatment. One approach is to identify variant genes/pathways that are significantly enriched in groups of afflicted individuals relative to control subjects. However, if there are multiple molecular pathways to the same cancer, the molecular determinants of the disease may be heterogeneous among individuals and possibly go undetected by group analyses. METHODS: In an effort to explore this question in pancreatic cancer, we compared the most significantly differentially expressed genes/pathways between cancer and control patient samples as determined by group versus personalized analyses. RESULTS: We found little to no overlap between genes/pathways identified by gene expression profiling using group analyses relative to those identified by personalized analyses. CONCLUSIONS: Our results indicate that personalized and not group molecular profiling is the most appropriate approach for the identification of putative candidates for targeted gene therapy of pancreatic and perhaps other cancers with heterogeneous molecular etiology.

Integral role of platelet-derived growth factor in mediating transforming growth factor-ß1-dependent mesenchymal stem cell stiffening.

Mesenchymal stem cells (MSCs) play an important role in matrix remodeling, fibroblast activation, angiogenesis, and immunomodulation and are an integral part of fibrovascular networks that form in developing tissues and tumors. The engraftment and function of MSCs in tissue niches is regulated by a multitude of soluble proteins. Transforming growth factor-ß1 (TGF-ß1) and platelet-derived growth factor-BB (PDGF) have previously been recognized for their role in MSC biology; thus, we sought to investigate their function in mediating MSC mechanics and matrix interactions. Cytoskeletal organization, characterized by cell elongation, stress fiber formation, and condensation of actin and microtubules, was dramatically affected by TGF-ß1, individually and in combination with PDGF. The intracellular mechanical response to these stimuli was measured with particle tracking microrheology. MSCs stiffened in response to TGF-ß1 (their elastic moduli was ninefold higher than control cells), a result that was enhanced by the addition of PDGF (100-fold change). Blocking TGF-ß1 or PDGF signaling with inhibitors SB-505124 or JNJ-10198409, respectively, reversed soluble-factor-induced stiffening, indicating that crosstalk between these two pathways is essential for stiffening response. A genome-wide microarray analysis revealed TGF-ß1-dependent regulation of cytoskeletal actin-binding protein genes. Actin crosslinking and bundling protein genes, which regulate cytosolic rheology through changes in semiflexible actin polymer meshwork, were upregulated with TGF-ß1 treatment. TGF-ß1 alone and in combination with PDGF also amplified surface integrin expression and adhesivity of MSCs with extracellular matrix proteins. These findings will provide a more mechanistic insight for modeling tissue-level rigidity in fibrotic tissues and tumors.

Molecular profiling supports the role of epithelial-to-mesenchymal transition (EMT) in ovarian cancer metastasis.

BACKGROUND: While metastasis ranks among the most lethal of all cancer-associated processes, on the molecular level, it remains one of the least well understood. One model that has gained credibility in recent years is that metastasizing cells at least partially recapitulate the developmental process of epithelial-to-mesenchymal transition (EMT) in their transit from primary to metastatic sites. While experimentally supported by cell culture and animal model studies, the lack of unambiguous confirmatory evidence in cancer patients has led to persistent challenges to the model's relevance in humans. METHODS: Gene expression profiling (Affymetrix, U133) was carried out on 14 matched sets of primary (ovary) and metastatic (omentum) ovarian cancer (serous adenocarcinoma) patient samples. Hierarchical clustering and functional pathway algorithms were used in the data analysis. RESULTS: While histological examination reveled no morphological distinction between the matched sets of primary and metastatic samples, gene expression profiling clearly distinguished two classes of metastatic samples. One class displayed expression patterns statistically indistinguishable from primary samples isolated from the same patients while a second class displayed expression patterns significantly different from primary samples. Further analyses focusing on genes previously associated with EMT clearly distinguished the primary from metastatic samples in all but one patient. CONCLUSION: Our results are consistent with a role of EMT in most if not all ovarian cancer metastases and demonstrate that identical morphologies between primary and metastatic cancer samples is insufficient evidence to negate a role of EMT in the metastatic process.

Molecular profiling predicts the existence of two functionally distinct classes of ovarian cancer stroma.

Although stromal cell signaling has been shown to play a significant role in the progression of many cancers, relatively little is known about its importance in modulating ovarian cancer development. The purpose of this study was to investigate the process of stroma activation in human ovarian cancer by molecular analysis of matched sets of cancer and surrounding stroma tissues. RNA microarray profiling of 45 tissue samples was carried out using the Affymetrix (U133 Plus 2.0) gene expression platform. Laser capture microdissection (LCM) was employed to isolate cancer cells from the tumors of ovarian cancer patients (Cepi) and matched sets of surrounding cancer stroma (CS). For controls, ovarian surface epithelial cells (OSE) were isolated from the normal (noncancerous) ovaries and normal stroma (NS). Hierarchical clustering of the microarray data resulted in clear separations between the OSE, Cepi, NS, and CS samples. Expression patterns of genes encoding signaling molecules and compatible receptors in the CS and Cepi samples indicate the existence of two subgroups of cancer stroma (CS) with different propensities to support tumor growth. Our results indicate that functionally significant variability exists among ovarian cancer patients in the ability of the microenvironment to modulate cancer development.

The effects of MicroRNA transfections on global patterns of gene expression in ovarian cancer cells are functionally coordinated.

BACKGROUND: MicroRNAs (miRNAs) are a class of small RNAs that have been linked to a number of diseases including cancer. The potential application of miRNAs in the diagnostics and therapeutics of ovarian and other cancers is an area of intense interest. A current challenge is the inability to accurately predict the functional consequences of exogenous modulations in the levels of potentially therapeutic miRNAs. METHODS: In an initial effort to systematically address this issue, we conducted miRNA transfection experiments using two miRNAs (miR-7, miR-128). We monitored the consequent changes in global patterns of gene expression by microarray and quantitative (real-time) polymerase chain reaction. Network analysis of the expression data was used to predict the consequence of each transfection on cellular function and these predictions were experimentally tested. RESULTS: While ~20% of the changes in expression patterns of hundreds to thousands of genes could be attributed to direct miRNA-mRNA interactions, the majority of the changes are indirect, involving the downstream consequences of miRNA-mediated changes in regulatory gene expression. The changes in gene expression induced by individual miRNAs are functionally coordinated but distinct between the two miRNAs. MiR-7 transfection into ovarian cancer cells induces changes in cell adhesion and other developmental networks previously associated with epithelial-mesenchymal transitions (EMT) and other processes linked with metastasis. In contrast, miR-128 transfection induces changes in cell cycle control and other processes commonly linked with cellular replication. CONCLUSIONS: The functionally coordinated patterns of gene expression displayed by different families of miRNAs have the potential to provide clinicians with a strategy to treat cancers from a systems rather than a single gene perspective.

Gene transfection enhanced by ultrasound exposure combined with drug treatment guided by gene chip analysis.

PURPOSE: Heterogeneous bioeffects have been reported in previous studies of ultrasound-mediated gene delivery. The goal of this study is to identify the differences between cells that take up plasmid DNA (pDNA) after sonication but are not transfected and cells that similarly take up pDNA but are transfected. We used these findings to select drugs that regulate intracellular processes expected to enhance gene transfection in combination with US. MATERIALS AND METHODS: Gene expression among DU145 human prostate cancer cells after ultrasound-mediated transfection was analyzed using Affymetrix GeneChip Human Genome U133 Plus 2.0 Arrays. Drug treatments suggested by the microarray analysis were combined with US exposure to regulate the corresponding intracellular processes. Cell viability and transfection efficiency were determined by flow cytometry to analyze the effects of US combined with drug treatment. RESULTS: Genes such as GADD45α (growth arrest and DNA-damage inducible, alpha) and Topoisomerase IIα were found to be associated with successful transfection. Drugs that regulate GADD45α and Topoisomerase IIα (e.g., ethyl methanesulfomate, amsacrine and chloroquine) were shown to increase ultrasound-mediated transfection efficiency by up to 2 fold. CONCLUSIONS: Among cells with pDNA uptake after sonication, we found that genes are differentially expressed among transfected cells versus non-transfected cells. Regulation of the expression level of GADD45α and TOP2α and other intracellular processes can yield higher efficiency of ultrasound-mediated gene transfection. This suggests that a strategy to increase gene transfection efficiency involving the combination of sonication and regulation of intracellular processes using drugs could further enhance US-mediated gene transfection.

Isolation and characterization of stem-like cells from a human ovarian cancer cell line.

Increasing evidence supports the existence of a subpopulation of cancer cells capable of self-renewal and differentiation into diverse cell lineages. These cancer stem-like or cancer-initiating cells (CICs) also demonstrate resistance to chemo- and radiotherapy and may function as a primary source of cancer recurrence. We report here on the isolation and in vitro propagation of multicellular ovarian cancer spheroids from a well-established ovarian cancer cell line (OVCAR-3). The spheroid-derived cells (SDCs) display self-renewal potential, the ability to produce differentiated progeny, and increased expression of genes previously associated with CICs. SDCs also demonstrate higher invasiveness, migration potential, and enhanced resistance to standard anticancer agents relative to parental OVCAR-3 cells. Furthermore, SDCs display up-regulation of genes associated with epithelial-to-mesenchymal transition (EMT), anticancer drug resistance and/or decreased susceptibility to apoptosis, as well as, down-regulation of genes typically associated with the epithelial cell phenotype and pro-apoptotic genes. Pathway and biological process enrichment analyses indicate significant differences between the SDCs and precursor OVCAR-3 cells in TGF-beta-dependent induction of EMT, regulation of lipid metabolism, NOTCH and Hedgehog signaling. Collectively, our results indicate that these SDCs will be a useful model for the study of ovarian CICs and for the development of novel CIC-targeted therapies.