bluuebunny/crossref_metadata_2025_split huggingface dataset:
Growth control of human ovarian cancer cells by the dynein light chain and TGFβ receptor interacting protein km23-1
Authors: Mulder Kathleen M. , Pulipati Nageswara Rao , Liu Xin , Sun Baodong , Zhao Yan , Jin Qunyan , Ding Wei , Pandey Manoj K. , Huber Jonathan P. 
Published: May 2015

Abstract
We have identified km23-1 as a TGFβ signaling intermediate that is also a light chain of the minus-end directed motor protein dynein (DLC). Our results suggest that km23-1 (also termed DYNLRB1/robl1/mLC7-1/Dnlc2a) can function as a “motor receptor” to recruit TGFβ signaling components to the dynein motor for endosomal trafficking prior to nuclear translocation. For example, we have shown that overexpression of the dynactin subunit dynamitin, which is known to disrupt dynein-mediated intracellular transport, blocks TGFβ-stimulated nuclear translocation of Smad2. Further, siRNA blockade of km23-1 resulted in a reduction both in nuclear levels of phosphorylated (ie, activated) Smad2 and of TGFβ/Smad2-dependent transcriptional activity (JBC 282: 19122, 2007). Similarly, we have shown that km23-2 is required for Smad3 TGFβ signaling (JCP 221: 707, 2009). However, many human ovarian cancer cells (HOCCs) have lost growth inhibitory responsiveness to TGFβ. In order to assess whether km23-1 could also regulate the growth of aggressive, TGFβ-resistant HOCCs, we developed a tet-off-inducible model system for induction of wild-type km23-1 expression in SKOV-3 HOCCs. Here we show that overexpression of km23-1 (by 10-20 fold) suppressed the growth of the cells in vitro and markedly impeded tumor formation in vivo. Fluorescence-activated cell sorting (FACS) analysis in the SKOV-3 model system demonstrated an increased fraction of cells in G2/M after induction of km23-1 expression (dox removal), compared with controls. Similar results were obtained for the TGFβ-resistant IGROV-1 HOCCs. Additional studies revealed that km23-1 overexpression in HOCCs increased the mitotic index, in association with activation of both MEK and ERK and an elevation of cyclin B1 protein expression levels. The elevated levels of phospho-MEK, phospho-ERK, and cyclin B1, as well as the distribution of the cells in mitosis, suggest that the cells are delayed in prometaphase/ metaphase. This mitotic delay, followed by cell death, appears to be the mechanism by which high levels of km23-1 can suppress ovary tumor growth in vivo. Since dynein is known to have critical functions at this point in mitosis by inactivating the spindle assembly checkpoint (SAC), studies are underway to investigate how km23-1 overexpression regulates the SAC to cause the reduced tumor formation in vivo. This work was supported by NIH grants CA100239, CA92889, and CA90765 to KMM. Our results indicate that km23-1 is a critical ovarian cancer target for the development of novel diagnostic and therapeutic agents. In this regard, US patents have been issued to KMM related to km23-1-based methods for diagnostic/prognostic screening, as well as for the identification of km23-1-based therapeutic agents for ovarian cancer (US 7,229,758 B2; 6-07 & US 7,741,043; 6-10).
Phosphoproteomics and mass-action modeling to predict optimal drug combination in signaling networks
Authors: Morales Fabiana C. , Iadevaia Sergio , Lu Yiling , Ram Prahlad , Mills Gordon B. 
Published: May 2015

Abstract
Targeted therapeutics hold tremendous promise in inhibiting cancer cell proliferation. However, targeting proteins individually can be compensated for by bypass mechanisms and activation of regulatory loops. Designing optimal therapeutic combination must therefore take into consideration the complex dynamic networks in the cell. In this study, we analyzed the insulinlike growth factor (IGF-1) signaling network in the MDA-MB231 breast cancer cell line using reverse phase protein arrays to quantify the dynamic crosstalk between the phosphoinositide 3-kinase (PI3K), the mitogen-activated protein kinase (MAPK) and the mammalian target of rapamycin (mTOR) pathways. We developed a computational procedure that integrated mass-action modeling with particle swarm optimization to train the model against the experimental data and infer the unknown model parameters. The trained model was used to predict how targeting individual signaling proteins altered the rest of the network and identify drug combination that minimally increased phosphorylation of other proteins elsewhere in the network. Experimental testing of the modeling predictions showed that optimal drug combination inhibited cell signaling and proliferation, while non-optimal combination of inhibitors increased phosphorylation of non-targeted proteins and rescued cells from cell death. The integrative approach described here is useful for generating experimental intervention strategies that could optimize drug combination and discover novel pharmacologic targets for cancer therapy.
Affinity and size capture of circulating tumor cells: A platform for increased sensitivity
Authors: Maimonis Peter J. , Merdek Keith , Dietenhofer Kurt , Yen Lucy , Palmer Gary 
Published: May 2015

Abstract
Background: The potential clinical value of evaluating circulating tumor cells (CTCs) from blood is clear. CTC analysis can aid in cancer diagnosis, prognosis, and treatment prediction. However, since CTCs are rare, current analysis is limited by low efficiencies. Variability of expression of cell surface antigens by CTCs make capture mechanisms based on antibody affinity less than ideal. We report here data from a CTC platform that combines affinity capture with size filtration capture.
Methods: A spiked cell model was used, involving whole EDTA blood spiked with SKBR-3 human breast cancer cells. Two microfluidic chips were analyzed, a standard chip (T7) with constant gap size between posts, and a gradient chip (MA3) with a gap-size gradient between posts starting at 40 μ and decreasing to 12 μ. Chips were coated with either an anti-EpCAM monoclonal antibody or with no Ab. An anti-cytokeratin (CK) Ab in combination with a nuclear specific fluorescent stain on an automated cell imaging platform was used to identify CTCs.
Results: 45% of cells were captured by size alone (MA3 with no Ab), 16% of cells were captured by affinity alone (T7 with MAb), and 65% of cells were captured by a combination of antibody affinity and size gradient (MA3 with MAb). This increased capture efficiency has been confirmed in clinical samples from patients with metastatic breast cancer, with a greater than 40% increase in capture efficiency utilizing both mechanisms. Whole blood from healthy donors run through either chip type yielded virtually no CTCs. FACS analysis showed that 75% of cultured SKBR-3 cells express high levels of EpCAM. This expression level will vary, as will, presumably, the relative contributions of the antibody capture mechanism and the size capture mechanism. A “heat map” analysis can demonstrate visually the relative contributions of each and these will be presented.
Conclusions: The MA3 microfluidic chip captures CTCs using a combination of affinity and size filtration. This allows for the capture of CTCs with varying expression levels of EpCAM by exploiting the size differential between these CTCs and other blood elements. This dual-capture mechanism may allow for more efficient capture than affinity alone. Further work evaluating this platform in late-stage breast cancer patients is ongoing.
Aberrant methylation in breast cancer and correlate with tumor phenotypes, prognostic factors, and patient outcome
Authors: Martinez-Galan Joaquina , Delgado-Perez Juan Ramón , Torres-Torres Blanca , Ballesteros Pedro , Gonzalez-Flores Encarnación , Valdivia Javier , Luque Raquel , Conde Veronica , Ortega Jose Antonio , de Almodovar Mariano Ruiz 
Published: May 2015

Abstract
Purpose: Posttranslational modifications are known to be altered in cancer cells, and loss of selected histone acetylation and methylation marks has recently been shown to predict patient outcome in human carcinoma.
Materials: Since January 2002 to June 2005, 107 women with breast cancer and 108 control subjects were recruited. A sensitive SYBR green methylation-specific PCR quantitative technique was used to analyze the utility of circulating DNA with CpG island hypermethylation of APC, RAR-β, E-cadherin, ESR1 and 14-3-3σ gene promoter regions as breast cancer biomarkers. Sera were collected in 107 operable breast cancer patients (pts) previously surgery and in 60 of those pts after treatment. Respect controls, 34 had benign breast disease and 74 with no evidence of breast disease
Results: Mean serum values of methylated ESR1 and 14-3-3σ gene promoters significantly differed between breast cancer patients and healthy controls (p = 0.0112 for ESR1 and p= 0.0047 for 14-3-3- σ). When their results were combined, it was found that hypermethylation of these two genes differentiated between breast cancer patients and healthy controls (p≤0.0001) with a sensitivity of 81% (95% confidence interval: 72—88%) and specificity of 88% (95% CI: 78—94%). Presence of methylated ESR1 in serum of breast cancer patients was associated with ER-negative phenotype (p = 0.0179); and presence of methylated 14-3-3-σ was associated with T3-4 stage (OMS) (p&lt; 0.05) and nodal positive status (p&lt; 0.05). We observed lower methylated ERS1 or 14-3-3-σ values after surgery, respect pretreatment levels, but without an overall statistically significant difference. With a median follow up of 6 years, we found that patients with a significant decrease of sera methylated levels of both genes after surgery had better time to progression an overall survival respect patients without this observation
Conclusions: These results also suggest that this panel of genes detected in ductal lavage and blood specimens could be useful to biomarkers for early detection breast cancer. These findings cast some doubts on the utility for early cancer diagnosis of highly sensitive techniques to identify hypermethylation of specific gene promoters in DNA extracted from serum. Although numerous issues remain to be resolved, the quantitative measurement of circulating methylated DNA is a promising tool for cancer risk assessment.
Nanotechnology and individualized oncology
Authors: Ferrari Mauro 
Published: May 2015

Abstract
The advent of novel engineering technologies affords unprecedented advances toward long-elusive objectives of medical research. Individualized medicine responds to the basic but generally unattainable question of identifying the right therapy, reaching the right therapeutic target in the body at the right time, and securing immediate feedback as for its efficacy and undesired collateral effect. Finally, individualized medicine appears to be a credible general objective in cancer, owing to the integration of classical disciplines of clinical medicine, methods of molecular biology, and novel technology platforms.
Nanotechnologies are of great interest in the context of the drive toward individualized oncology, and may prove to be the necessary catalyst for its large-scale implementation. In this talk I will present nanoporous-silicon-based approaches for the individualization of medical intervention: multistage vectors for the preferential localization of therapeutic agents; therapeutic monitoring nanotextured chips for the proteomic and peptidomic content profiling of biological samples; nanochannel delivery systems for intelligent time-release from implants, and bionanoscaffolds for post-traumatic osteoregeneration.
While novel nanoplatforms engender direct clinical applications, at the same time they afford the formulation of novel frameworks and hypotheses for the basic understanding of pathological processes. In particular, multistage particulates are the probes that afford the exploration of a new perspective of cancer, that is, that the unifying aspect of the canonical ‘hallmarks of cancers’ all relate to dysregulation of mass transport at scales including the molecular, cellular, microenvironmental, and systemic. These considerations are the starting point for “Transport OncoPhysics.”
Clinical trials using novel molecular imaging cancer biomarkers: Current status and future directions
Authors: Mankoff David A. 
Published: May 2015

Abstract
The ability to assay cancer biologic features is key to advances in the both the basic biomedical science and clinical patient care. Advances in our ability to assay molecular processes including gene expression, protein expression, and molecular and cellular biochemistry have fueled recent advances in our understanding of many diseases and our ability to treat them. Most assays require sampling of cells or tissue to perform the measurements. Thus the cell culture system, animal model, or patient must be perturbed in order to perform the assay. This requirement makes serial assays over time more difficult and leaves open the possibility that the assay itself may change the state of the system being measured. The ability to measure biologic processes without perturbing them would be highly desirable and would offer complementary information to that obtained by most traditional assay methods. The ability to image regional biochemistry and molecular biology, termed molecular imaging [1,2] offers great promise in using molecular imaging as a cancer biomarker. Quantitative capability is an important feature of molecular imaging, for example, the ability to measure regional tumor receptor expression. The quantitative and non-invasive nature of molecular imaging makes it a potentially very powerful tool for cancer drug development and testing and for translational science [3].
This talk will review the use of molecular imaging as a biomarker, particular positron emission tomography (PET). Examples will be shown using PET imaging to (1) provide prognostic information based upon in vivo measures of cancer differentiation and aggressiveness, (2) measure the regional expression of possible therapeutic targets, (3) provide early assessment of response to therapy. Current clinical trials involving PET as a cancer biomarker will be reviewed, including those using PET radiopharmaceuticals beyond 18F-fluoridexoyglucose (FDG) [3, 4]. The spectrum of current trials will be discussed, with an emphasis on current NCI and ACRIN clinical trials of novel imaging probes, and an eye towards matching future trials of targeted cancer therapy with companion molecular imaging trials.
Cancer genomics and the TCGA project
Authors: Haussler David 
Published: May 2015

Abstract
Large-scale cancer genomics projects such as The Cancer Genome Atlas (TCGA) and the International Cancer Genomics Consortium (ICGC) will sequence tens of thousands of tumors in the new few years, along with matched normal blood samples and other normal tissues. TCGA alone plans to analyze 500 clinically characterized samples from each of 20 different cancer types, detecting frequently mutated genes, common copy number variants, altered gene expression and methylation changes. These data will provide an exceptional resource for identifying new diagnostic targets and predictors of response.
Building on technology developed for the UCSC genome browser, we have developed a cancer genome analysis pipeline and a cancer genomics browser to interpret cancer genomics data that will aid in the identification of new targets. We use a new approach called PARADIGM, based on factor graphs, to map multiple data types into a single coherent pathway model for higher level interpretation. PARADIGM currently employs models for many hundreds of pathways from pathway libraries such as NCI pathways, Wikipathways, KEGG, etc. By transforming raw genomic data to pathway activity levels, PARADIGM provides a comprehensible window into the data that can be coupled to predictors of response to improve accuracy. We discuss the early results of this approach to the TCGA data.
Prediction of disease risk using common genetic variants
Authors: Hunter David J. 
Published: May 2015

Abstract
A frequently proposed application of knowledge on inherited predisposition to cancers is the possibility that susceptible individuals could be targeted for enhanced surveillance, lifestyle advice, or chemoprevention, and thus have reduced risk of diagnosis or mortality from cancer. Action based on knowledge of mutations in high penetrance genes such as BRCA1 in breast cancer, or hMSH2 and colorectal cancer has become established practice in high risk clinics. With the advent of genome-wide association studies (GWAS) dozens of common genetic variants (mostly SNPs) have been discovered to be associated with cancer at various sites, with approximately 30 discovered for prostate cancer alone. In general, the relative risks associated with these risk variants are an order of magnitude or more less than those associated with high penetrance gene mutations, and thus, the risk information contributed by a single common risk variant contributes minimally to risk prediction. However, when cumulated into multi-SNP risk scores, large relative risks are predicted for the small number of persons in the tail of the risk distribution (i.e. those who have inherited mostly risk variants as opposed to “protective” variants). For this small number of people, the estimated relative risks approach those for the high penetrance single gene mutations, but at this stage of our knowledge the risk scores are unstable and may change as more common variants are discovered. For the majority of people, with either modestly elevated or modestly reduced predicted risks, the clinical application of this knowledge is even less secure. However, combinations of risk variants have been shown at some cancer sites to be at least as predictive as available risk scores based on demographic and lifestyle factors. As more variants are discovered, the predictive value of these risk scores will increase, and thus the clinical utility of the information should be rigorously tested.
Potential clinical utilities of prostate cancer risk-associated SNPs
Authors: Xu Jianfeng 
Published: May 2015

Abstract
Prostate cancer (PCa) is the most common solid organ malignancy affecting American men and the second leading cause of cancer related death. Recently, more than 30 PCa risk-associated single nucleotide polymorphisms (SNPs) have been discovered from genome-wide association studies (GWAS). These risk-associated SNPs have been consistently replicated in multiple case-control study populations of European descent. Although each of these SNPs is only moderately associated with PCa risk, a genetic score based on a combination of risk-associated SNPs can be used to identify men at high risk for PCa.
However, these results were obtained from case-control studies which have several significant limitations. The validity of these genetic associations, the relative performance of genetic markers for PCa risk prediction compared to existing clinical variables such as PSA, and more importantly, whether genetic markers add value to existing clinical variables, are key questions that need to be addressed in well-controlled prospective studies prior to their consideration for clinical use.
In this presentation, I will present the findings of PCa risk prediction using multiple risk-associated SNPs. I will also discuss our effort to assess clinical validity and clinical utility of these genetic markers in the Reduction by DUtasteride of Prostate Cancer Events (REDUCE) study, a large randomized clinical trial. All men in the REDUCE trial had a negative biopsy at baseline and were followed-up for four years, with scheduled not-for-cause (i.e. regardless of PSA levels and other clinical indications) prostate biopsies at years 2 and 4. Therefore, this study design minimizes the potential impact of PSA detection bias on associations between PCa risk and SNPs. In addition, because it is a clinical trial, a number of clinical variables, such as free/total PSA ratio and prostate volume were measured at baseline using a standardized protocol. Therefore, it allows us to compare performance of genetic markers and existing clinical variables in predicting positive prostate biopsy in the same study. Finally, the study design allows us to assess whether genomic-targeted chemoprevention, based on estimated risk from genetic markers, can improve efficacy of chemoprevention. This study represents an important next and critical step towards an assessment of the potential clinical utility of genetic markers.
Deep collective cancer invasion: Breaking radioresistance by anti-integrin therapy
Authors: Friedl Peter 
Published: May 2015

Abstract
The tumor microenvironment contributes to cancer invasion, growth and survival and thereby impacts tumor responses to therapy. We here show for orthotopic fibrosarcoma and melanoma xenografts deep invasive growth driven by proliferation concurrent with collective invasion of multicellular strands along the normoxic perivascular stroma. Invasion was fast (up to 200 µm per day), non-destructive and independent of β1 and β3 integrins. Despite normoxia, perivascular invasion strands were resistant to high-dose hypofractionated irradiation which otherwise was sufficient to induce regression of the tumor main mass. This invasion-associated radioresistance was sensitive to the simultaneous inhibition of β1 and β3 integrins by RNA interference or combined anti-β1/aV integrin antibody treatment caused byproliferation arrest, anoikis induction ablating both tumor lesion and invasion strands. Thus, collective invasion is an important invasion mode in solid tumors into a microenvironmentally privileged perivascular survival niche which conveys radioresistance by integrin-dependent signals. Consequently, combining anti-integrin therapy with hypofractionated irradiation may be amenable to clinical cancer treatment of locally destructive and otherwise radioresistant tumor lesions.
Angiogenesis success and pitfalls in diagnosis, therapy and cancer prevention
Authors: Albini Adriana 
Published: May 2015

Abstract
In contrast to conventional chemotherapy, which targets the genetically mutated cancer cells, anti-vascular tumor therapy is primarily directed towards the newly formed blood vessel compartment, and is supposed to have the some advantages compared to conventional cytotoxic chemotherapy: (I) it is not restricted to a certain histologic tumor type, since all solid tumors depend on angiogenesis and the maintenance of functional microvasculature; (II) the tumor microvasculature is well accessible to systemic treatment; (III) it reaches the whole tumor mass, since every single tumor microvessel has to supply up to hundreds of critically dependent tumor cell layers; (IV) angiogenesis in adult organisms is only induced during the reproductive ovarian cycle or wound healing, thus an antagonism of angiogenesis should be a highly selective therapy; (V) the endothelial cell is genetically stable and therefore less prone to development of drug resistance. Recent evidences, however, show recurrence of tumor growth after an initial period of suppression during long-term therapy using antiangiogenic agents. Redundancy of alternative proangiogenetic factors in antiangiogenic monotherapies, upregulation of proangiogenic or anti-apoptotic factors, or heterogeneity of vascular dependency among tumor subpopulations are thought to be possible mechanisms for this phenomenon, as well as vascular remodeling. On the other hand, targeting angiogenic pathways can undermine elements and function of the cardiovascular system leading to potentially deadly side effects ranging from hypertension to heart failure. It is important to reconsider all the implications of antiangiogenic treatment to improve the therapeutic outcome and patients’ well being.