Study Cancer Progression Research Articles

Establishment of Primary Cell Cultures from Canine Oral Melanomas via Fine-Needle Aspiration: A Novel Tool for Tumorigenesis and Cancer Progression Studies.

Oral melanomas are the most common oral malignancies in dogs and are characterized by an aggressive nature, invasiveness, and poor prognosis. With biological and genetic similarities to human oral melanomas, they serve as a valuable spontaneous comparative model. Primary cell cultures are widely used in human medicine and, more recently, in veterinary medicine to study tumorigenesis, cancer progression, and innovative therapeutic approaches. This study aims to establish two- and three-dimensional primary cell lines from oral canine melanomas using fine-needle aspiration as a minimally invasive sampling method. For this study, samples were collected from six dogs, represented by four primary oral melanomas and five lymph nodal metastases. The cells were digested to obtain single-cell suspensions, seeded in flasks, or processed with Matrigel® to form organoids. The cell cultures were characterized through flow cytometry using antibodies against Melan-A, PNL2, and Sox-10. This technique offers a minimally invasive means to obtain cell samples, particularly beneficial for patients that are ineligible for surgical procedures, and enables the establishment of in vitro models crucial for comparative studies in mucosal melanoma oncology. To the best of our knowledge, this is the first work establishing neoplastic primary cell cultures via fine-needle aspiration in dogs.

Assessing the performance of methods for cell clustering from single-cell DNA sequencing data.

Many cancer genomes have been known to contain more than one subclone inside one tumor, the phenomenon of which is called intra-tumor heterogeneity (ITH). Characterizing ITH is essential in designing treatment plans, prognosis as well as the study of cancer progression. Single-cell DNA sequencing (scDNAseq) has been proven effective in deciphering ITH. Cells corresponding to each subclone are supposed to carry a unique set of mutations such as single nucleotide variations (SNV). While there have been many studies on the cancer evolutionary tree reconstruction, not many have been proposed that simply characterize the subclonality without tree reconstruction. While tree reconstruction is important in the study of cancer evolutionary history, typically they are computationally expensive in terms of running time and memory consumption due to the huge search space of the tree structure. On the other hand, subclonality characterization of single cells can be converted into a cell clustering problem, the dimension of which is much smaller, and the turnaround time is much shorter. Despite the existence of a few state-of-the-art cell clustering computational tools for scDNAseq, there lacks a comprehensive and objective comparison under different settings. In this paper, we evaluated six state-of-the-art cell clustering tools-SCG, BnpC, SCClone, RobustClone, SCITE and SBMClone-on simulated data sets given a variety of parameter settings and a real data set. We designed a simulator specifically for cell clustering, and compared these methods' performances in terms of their clustering accuracy, specificity and sensitivity and running time. For SBMClone, we specifically designed an ultra-low coverage large data set to evaluate its performance in the face of an extremely high missing rate. From the benchmark study, we conclude that BnpC and SCG's clustering accuracy are the highest and comparable to each other. However, BnpC is more advantageous in terms of running time when cell number is high (> 1500). It also has a higher clustering accuracy than SCG when cluster number is high (> 16). SCClone's accuracy in estimating the number of clusters is the highest. RobustClone and SCITE's clustering accuracy are the lowest for all experiments. SCITE tends to over-estimate the cluster number and has a low specificity, whereas RobustClone tends to under-estimate the cluster number and has a much lower sensitivity than other methods. SBMClone produced reasonably good clustering (V-measure > 0.9) when coverage is > = 0.03 and thus is highly recommended for ultra-low coverage large scDNAseq data sets.

Abstract 2734: Integrating hybrid spatiotemporal models and multiscale data for the study of cancer progression in 3D cultures

Abstract Tumour progression consists of various stages including migration to the surrounding tissues, leading to metastasis [1]. In this work, we investigate the multiscale quantitative characteristics of the spatial organization and migration of cancer in 3D cultures. For this study, we combined 3D cell culture experiments of Triple Negative Breast Cancer (TNBC) cells, hybrid spatiotemporal models, and longitudinal RNA-sequencing data analysis. The experiments included two experimental conditions; simple growth experiments, and experiments of growth in presence of the migrastatic drug Paclitaxel. The spatial distributions of the cells enabled us to calibrate and validate a hybrid Keller-Segel model, incorporated into a novel computational framework capable of interpreting the relation between morphological patterns and the underlying mechanisms of cancer growth [2]. The RNA-seq data included different time-points with and without treatment. The results suggested that cancer cells exhibited biased movement towards the bottom of the space, a movement that was inhibited in the presence of Paclitaxel. The calibrated model was able to describe the overall characteristics of the experimental observations, and suggested that cancer cells exhibited chemotactic migration and cell accumulation, as well as random motion throughout the period of development. The spatial pattern analysis revealed transient, non-random spatial distributions of cancer cells that consisted of clustered patterns across a wide range of neighbourhood distances, as well as dispersion for larger distances. The RNA-seq data exhibited coherence with the chemotactic migration hypothesis of the mathematical model, indicating significant under-representation of the Gene Ontology (GO) terms related to chemotactic migration in presence of the migrastatic drug. Overall, this study provided an insightful quantitative characterization of the spatiotemporal organization and progression of TNBC cells in 3D cultures. We anticipate that these developments will enable us to expand our studies to more realistic conditions, including the introduction of heterogeneic cell populations.

Polymeric Hydrogels for In Vitro 3D Ovarian Cancer Modeling.

Ovarian cancer (OC) grows and interacts constantly with a complex microenvironment, in which immune cells, fibroblasts, blood vessels, signal molecules and the extracellular matrix (ECM) coexist. This heterogeneous environment provides structural and biochemical support to the surrounding cells and undergoes constant and dynamic remodeling that actively promotes tumor initiation, progression, and metastasis. Despite the fact that traditional 2D cell culture systems have led to relevant medical advances in cancer research, 3D cell culture models could open new possibilities for the development of an in vitro tumor microenvironment more closely reproducing that observed in vivo. The implementation of materials science and technology into cancer research has enabled significant progress in the study of cancer progression and drug screening, through the development of polymeric scaffold-based 3D models closely recapitulating the physiopathological features of native tumor tissue. This article provides an overview of state-of-the-art in vitro tumor models with a particular focus on 3D OC cell culture in pre-clinical studies. The most representative OC models described in the literature are presented with a focus on hydrogel-based scaffolds, which guarantee soft tissue-like physical properties as well as a suitable 3D microenvironment for cell growth. Hydrogel-forming polymers of either natural or synthetic origin investigated in this context are described by highlighting their source of extraction, physical-chemical properties, and application for 3D ovarian cancer cell culture.

Causal Inference in Cancer Epidemiology: What Is the Role of Mendelian Randomization?

Observational epidemiologic studies are prone to confounding, measurement error, and reverse causation, undermining robust causal inference. Mendelian randomization (MR) uses genetic variants to proxy modifiable exposures to generate more reliable estimates of the causal effects of these exposures on diseases and their outcomes. MR has seen widespread adoption within cardio-metabolic epidemiology, but also holds much promise for identifying possible interventions for cancer prevention and treatment. However, some methodologic challenges in the implementation of MR are particularly pertinent when applying this method to cancer etiology and prognosis, including reverse causation arising from disease latency and selection bias in studies of cancer progression. These issues must be carefully considered to ensure appropriate design, analysis, and interpretation of such studies. In this review, we provide an overview of the key principles and assumptions of MR, focusing on applications of this method to the study of cancer etiology and prognosis. We summarize recent studies in the cancer literature that have adopted a MR framework to highlight strengths of this approach compared with conventional epidemiological studies. Finally, limitations of MR and recent methodologic developments to address them are discussed, along with the translational opportunities they present to inform public health and clinical interventions in cancer. Cancer Epidemiol Biomarkers Prev; 27(9); 995-1010. ©2018 AACR.

Statistical inference for partially observed branching processes with application to cell lineage tracking of in vivo hematopoiesis

Single-cell lineage tracking strategies enabled by recent experimental technologies have produced significant insights into cell fate decisions, but lack the quantitative framework necessary for rigorous statistical analysis of mechanistic models describing cell division and differentiation. In this paper, we develop such a framework with corresponding moment-based parameter estimation techniques for continuous-time, multi-type branching processes. Such processes provide a probabilistic model of how cells divide and differentiate, and we apply our method to study hematopoiesis, the mechanism of blood cell production. We derive closed-form expressions for higher moments in a general class of such models. These analytical results allow us to efficiently estimate parameters of much richer statistical models of hematopoiesis than those used in previous statistical studies. To our knowledge, the method provides the first rate inference procedure for fitting such models to time series data generated from cellular barcoding experiments. After validating the methodology in simulation studies, we apply our estimator to hematopoietic lineage tracking data from rhesus macaques. Our analysis provides a more complete understanding of cell fate decisions during hematopoiesis in nonhuman primates, which may be more relevant to human biology and clinical strategies than previous findings from murine studies. For example, in addition to previously estimated hematopoietic stem cell self-renewal rate, we are able to estimate fate decision probabilities and to compare structurally distinct models of hematopoiesis using cross validation. These estimates of fate decision probabilities and our model selection results should help biologists compare competing hypotheses about how progenitor cells differentiate. The methodology is transferrable to a large class of stochastic compartmental and multi-type branching models, commonly used in studies of cancer progression, epidemiology and many other fields.

Evaluation of a simple method for storage of blood samples that enables isolation of circulating tumor cells 96\xa0h after sample collection

BackgroundMinimizing the effects of transportation on the properties of biological material is a major challenge for the scientific community. The viability of cells is important in cases where their study is urgent for evaluation of treatment response or for the study of cancer progression. Circulating tumor cells (CTCs) constitute a cell subpopulation with great importance for oncologists, because of their prognostic value. Detection and isolation of CTCs from blood samples is a routine activity in many laboratories, but concerns exist with regard to the maintenance of the cells during transportation. In this study, experiments were conducted to determine the stability of gene and protein expression in CTCs over a period of 96 h.ResultsBlood samples collected from healthy individuals and patients with cancer were each divided into five aliquots, which were stored at 2–8 °C and analyzed after 0, 24, 48, 72 and 96 h of storage. CTCs from patients and CD45-negative cells from healthy individuals were isolated each day using enrichment protocols, and qPCR was performed to determine expression levels of genes encoding specific biological markers. In addition, cells from breast and colon cancer cell lines were spiked into blood samples from healthy individuals, and these samples were stored and analyzed over a period of 96 h by PCR and by flow cytometry. The markers that were studied included housekeeping genes and genes associated with the response to chemotherapy, as well as genes encoding transcription factors. The results demonstrated that the expression profiles of specific genes and proteins in CTCs were not significantly affected by 72 h of storage. After 96 h of storage, expression of some genes was altered.ConclusionThe transportation of blood at low temperature (2–8 °C) in the presence of the anticoagulant EDTA can protect CTCs from alteration of gene and protein expression for at least 72 h. Furthermore, under these conditions, CTCs can be detected and isolated 96 h after blood collection.

MicroRNAs regulate the epithelial to mesenchymal transition (EMT) in cancer progression.

MicroRNAs (miRNAs) are a class of small noncoding RNAs that regulate gene expression by targeting mRNAs and leading to either translation repression or RNA degradation. miRNAs have fundamental effects in the regulation of intracellular processes, and their importance during malignant transformation and metastasis is becoming increasingly well understood. The epithelial-mesenchymal transition (EMT), which reprograms tumor cells transcription, has been highlighted as a powerful process in tumor invasion, metastasis and tumorigenicity. In recent years, many studies have significantly enhanced our knowledge of EMT by the characterization of miRNAs that influence the signaling pathways and downstream events that define EMT on a molecular level. In this review, we detail the miRNAs and signal transduction pathways involved in the EMT process and demonstrate their importance in the study of cancer progression. We believe that this information will improve prognostication and reveal new opportunities for therapeutic intervention.

Abstract P5-11-10: Effect of claudin-3 protein expression on its sub-cellular localization and cellular motility in breast cancer cell lines

Abstract Tight Junctions (TJs), found at the apical side of vertebrate epithelial and endothelial junctions, serve as a selective barrier for the paracellular transport of solutes. Deregulation of these TJs has been shown to lead to loss of cell-to-cell adhesion. Subsequently, these cell barriers have become of interest in the study of cancer progression. Of the many proteins that make up a TJ, recent studies suggest a critical role for the claudin family in TJ formation and maintenance. Within this family of transmembrane proteins, we have previously shown claudin-3 to be overexpressed in two breast cancer cell lines, MCF-7 and MDA-MB-415, both of which are derived from metastatic deposits. In contrast, MDA-MB-157 cells (also of metastatic origin) expressed a lower level of claudin-3 relative to human mammary epithelial cells (HMEC). Indirect immunofluorescence (IF) analysis indicated that claudin-3 was primarily located in the membrane of MCF-7 and MDA-MB-415 but we also detected lower levels intracellularly. Notably, claudin-3 was not localized to the membrane in MDA-MB-157 cells. Instead, only an intracellular signal was detected. To more accurately determine the intracellular location of claudin-3 in the MDA-MB-157 cells, the current study, used differential detergent cell fractionation to isolate 4 sub-cellular fractions: cytosolic, membrane, nuclear and cytoskeletal. Consistent with the IF data, our preliminary analysis does not reveal membrane-specific claudin-3 signal but does show a low level of claudin-3 localized in the cytoskeletal fraction of MDA-MB-157 cells. This finding is striking as it indicates that claudin-3 does not necessarily play a role in the TJs of these cells (as indicated by the absence of claudin-3 localization to the membrane) but may function in the cytoskeleton, perhaps as part of a cell signaling pathway. Our earlier observations of MCF-7 and MDA-MB-415 cell lines (overexpress claudin-3) also revealed relatively high levels of claudin-3 in the cytoskeletal fraction but unlike MDA-MB-157, the majority of the protein was localized, as expected, in the membrane fraction. Deregulation and delocalization of claudin-3 in cell lines of metastatic origin suggests a possible role for this critical TJ protein in cellular invasiveness. Thus, we have begun to evaluate the impact of different levels of claudin-3 on cell motility using wound healing assays. Preliminary findings in MCF-7 show that siRNA-mediated suppression of claudin-3 protein slowed the migration of cells relative to their non-transfected counterparts. These findings suggest that overexpression of claudin-3 in MCF-7 cells may play a role in disrupting TJ integrity and thus contribute to enhanced cellular motility - a key component of tumor progression. Thus, it is possible that the siRNA-mediated suppression of claudin-3 may prove an effective therapeutic approach for breast cancers that overexpress claudin-3. We are currently in the process of analyzing both non-transfected and claudin-3- specific siRNA-transfected MDA-MB-415 and MDA-MB-157 to ascertain the effects of claudin-3 expression level on cellular motility in breast cancer cell lines that show either overexpressed or underexpressed levels of endogenous claudin-3 protein. Citation Information: Cancer Res 2013;73(24 Suppl): Abstract nr P5-11-10.

Comparison of Selected Methods for Modeling of Multi-State Disease Progression Processes: A Simulation Study

Prognostic studies are essential to understand the role of particular prognostic factors and, thus, improve prognosis. In most studies, disease progression trajectories of individual patients may end up with one of mutually exclusive endpoints or can involve a sequence of different events. One challenge in such studies concerns separating the effects of putative prognostic factors on these different endpoints and testing the differences between these effects. In this article, we systematically evaluate and compare, through simulations, the performance of three alternative multivariable regression approaches in analyzing competing risks and multiple-event longitudinal data. The three approaches are: (1) fitting separate event-specific Cox's proportional hazards models; (2) the extension of Cox's model to competing risks proposed by Lunn and McNeil; and (3) Markov multi-state model. The simulation design is based on a prognostic study of cancer progression, and several simulated scenarios help investigate different methodological issues relevant to the modeling of multiple-event processes of disease progression. The results highlight some practically important issues. Specifically, the decreased precision of the observed timing of intermediary (non fatal) events has a strong negative impact on the accuracy of regression coefficients estimated with either the Cox's or Lunn-McNeil models, while the Markov model appears to be quite robust, under the same circumstances. Furthermore, the tests based on both Markov and Lunn-McNeil models had similar power for detecting a difference between the effects of the same covariate on the hazards of two mutually exclusive events. The Markov approach yields also accurate Type I error rate and good empirical power for testing the hypothesis that the effect of a prognostic factor on changes after an intermediary event, which cannot be directly tested with the Lunn-McNeil method. Bootstrap-based standard errors improve the coverage rates for Markov model estimates. Overall, the results of our simulations validate Markov multi-state model for a wide range of data structures encountered in prognostic studies of disease progression, and may guide end users regarding the choice of model(s) most appropriate for their specific application.

Abstract 5172: Fluorescence labeling of cytokeratin-negative circulating tumor cells in peripheral blood: A new paradigm for the study of cancer progression

Abstract Introduction: The measurement of circulating tumor cells (CTCs) in blood generally requires either anti-EpCAM for capture, anti-cytokeratin (CK) for detection, or both. However, EpCAM and CK are absent in some tumor cells, and both may be down-regulated during neoplastic progression or during epithelial-to-mesenchymal transition (EMT). Here we show capture on a micro-fluidic system using single or multiple antibodies, and CTC detection with CEE-Enhanced (CE), a novel in situ staining method that fluorescently labels the capture antibodies bound to the CTCs. Methods: Buffy coat cells isolated from 8 mL of blood were pre-incubated with either anti-EpCAM alone or with a mixture of antibodies to epithelial and mesenchymal cell surface antigens. CTCs were captured on a micro-fluidic channel. Identification of CTCs was determined with anti-CK and with CE to detect cells with the capture antibodies bound to the cell surface antigens. All cells scored as positive for CK or CE were, by definition, CD45-negative and DAPI-positive. Results: Using anti-EpCAM alone for capture, significantly more CTCs were detected by CE staining than with anti-CK in breast and prostate cancers. This indicated that CK-negative CTCs were captured but not detected and that some EpCAM-positive CTCs were CK-negative. Results using capture antibody mixtures varied from sample to sample but gave up to 2-fold higher CK-positive cells than anti-EpCAM only, and as much as 4-fold higher CE-positive cells. Control blood from healthy donors was CK and CE-negative. All CK-positive cells co-stained with CE, as determined with different fluorescent labels. In a clinical study of stage IV breast cancer, CTCs were isolated with an antibody mixture and sequentially stained with CK and CE. Fifteen of 24 samples (63%) contained CK-positive cells (range 1-60 CTCs) while 24 of 24 samples (100%) contained additional CE-positive cells (range 1-41; median=11; Wilcoxon test, p=0.02). The modest correlation coefficient (r = 0.57, p=0.004) for the number of CE-positive and CK-positive cells in each sample suggests that one or more different phenotypes of CTCs were being detected. Amplified Her2 was detected by FISH in isolated CK-positive CTCs, and also in CK-negative, CE-positive CTCs from Her2-positive patients, indicating these were tumor cells. Conclusions: The CEE-Enhanced staining technology enables the detection of CK-negative CTCs. This novel detection method, based on the in situ labeling of antibodies used for capture, greatly expands single and multi-antibody approaches to the study of rare circulating cells. Specifically, this allows the exploration and study of circulating cells not expressing CK such as highly de-differentiated tumor cells, stem cells or those tumor cells undergoing EMT. The clinical significance of these CK-negative CTCs is under investigation. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 5172. doi:10.1158/1538-7445.AM2011-5172

Field defects in progression to gastrointestinal tract cancers

A field of defective tissue may represent a pre-malignant stage in progression to many cancers. However, field defects are often overlooked in studies of cancer progression through assuming tissue at some distance from the cancer is normal. We indicate, however, the generality of field defects in gastrointestinal cancers, including cancers of the oropharynx, esophagus, stomach, bile duct, pancreas, small intestine and colon/rectum. Common features of these field defects are reduced apoptosis competence, aberrant proliferation and genomic instability. These features are often associated with high bile acid exposure and may explain the association of dietary-related factors with cancer progression.

Quantitative Cancer Proteomics: Stable Isotope Labeling with Amino Acids in Cell Culture (SILAC) as a Tool for Prostate Cancer Research

Microarrays have been the primary means for large-scale analyses of genes implicated in cancer progression. However, more recently a need has been recognized for investigating cancer development directly at the protein level. In this report, we have applied a comparative proteomic technique to the study of metastatic prostate cancer. This technology, termed stable isotope labeling with amino acids in cell culture (SILAC), has recently gained popularity for its ability to compare the expression levels of hundreds of proteins in a single experiment. SILAC makes use of (12)C- and (13)C-labeled amino acids added to the growth media of separately cultured cell lines, giving rise to cells containing either "light" or "heavy" proteins, respectively. Upon mixing lysates collected from these cells, proteins can be identified by tandem mass spectrometry. The incorporation of stable isotopes also allows for a quantitative comparison between the two samples. Using this method, we compared the expression levels for more than 440 proteins in the microsomal fractions of prostate cancer cells with varying metastatic potential. Of these, 60 were found elevated greater than 3-fold in the highly metastatic cells, whereas 22 were reduced by equivalent amounts. Western blotting provided further confirmation of the mass spectrometry-based quantification. Our results demonstrate the applicability of this novel approach toward the study of cancer progression using defined cell lines.