Cell signalling, which is often derailed in cancer, is a network of multiple interconnected pathways with numerous feedback mechanisms. Dynamics of cell signalling is intimately regulated by addition and removal of phosphate groups by kinases and phosphatases. We examined expression of members of the PTP4A family of phosphatases across acute leukemias. While expression of PTP4A1 and PTP4A2 remained relatively unchanged across diseases, PTP4A3 showed marked overexpression in ETV6-RUNX1 and BCR-ABL1 subtypes of precursor B cell acute lymphoblastic leukemia. We show that PTP4A3 is regulated by the ETV6-RUNX1 fusion, but noticed no marked impact on cell viability either after PTP4A3 silencing or treatment with a PTP4A3 inhibitor. Regulation of PTP4A3 expression is altered in specific subgroups of acute leukemias and this is likely brought about by expression of the aberrant fusion genes.

Improvements in survival for Ewing sarcoma pediatric and adolescent patients have been modest over the past 20 years. Combinations of anticancer agents endure as an option to overcome resistance to single treatments caused by compensatory pathways. Moreover, combinations are thought to lessen any associated adverse side effects through reduced dosing, which is particularly important in childhood tumors. Using a parallel phenotypic combinatorial screening approach of cells derived from three pediatric tumor types, we identified Ewing sarcoma-specific interactions of a diverse set of targeted agents including approved drugs. We were able to retrieve highly synergistic drug combinations specific for Ewing sarcoma and identified signaling processes important for Ewing sarcoma cell proliferation determined by EWS-FLI1 We generated a molecular target profile of PKC412, a multikinase inhibitor with strong synergistic propensity in Ewing sarcoma, revealing its targets in critical Ewing sarcoma signaling routes. Using a multilevel experimental approach including quantitative phosphoproteomics, we analyzed the molecular rationale behind the disease-specific synergistic effect of simultaneous application of PKC412 and IGF1R inhibitors. The mechanism of the drug synergy between these inhibitors is different from the sum of the mechanisms of the single agents. The combination effectively inhibited pathway crosstalk and averted feedback loop repression, in EWS-FLI1-dependent manner. Mol Cancer Ther; 16(1); 88-101. ©2016 AACR.

A phase I/II clinical trial suggests that dabrafenib shrinks or stabilizes low-grade gliomas in children with the BRAF V600E mutation. Objective, durable responses occurred in 38% of patients, and the side effects were less severe than with chemotherapy. The researchers have started a second trial for patients with glioma and other BRAF-mutant tumor types, this time evaluating dabrafenib combined with trametinib.

We report cytogenetic and molecular genetic analysis of a pediatric tumor positive for the CIC-DUX4 fusion. The tumor belongs to a rare, diagnostically challenging subgroup of undifferentiated small round cell sarcomas. A balanced t(4;19)(q35;q13.1-2) was identified by G-banding, as a sole cytogenetic finding. The translocation was also identified by the M-FISH technique. After RT-PCR, the tumor sample was positive for the CIC-DUX4 fusion. The PCR product contains a novel, so far unreported variant of the CIC-DUX4 fusion transcript, with a fusion of the exon 20 from the CIC gene and the exon 1 from the DUX4 gene.

Prostate cancer (CP) cells differ from their normal counterpart in gene expression. Genes encoding secreted or extracellular proteins with increased expression in CP may serve as potential biomarkers. For their detection and quantification, assays based on monoclonal antibodies are best suited for development in the clinical setting. One approach to obtain antibodies is to use recombinant proteins as immunogen. However, the synthesis of recombinant protein for each identified candidate is time-consuming and expensive. It is also not practical to generate high quality antibodies to all identified candidates individually. Furthermore, non-native forms (e.g., recombinant) of proteins may not always lead to useful antibodies. Our approach was to purify a subset of proteins from CP tissue specimens for use as immunogen.

Maintenance therapy with full-dose erlotinib for patients with advanced non-small cell lung cancer (NSCLC) has demonstrated a significant overall survival (OS) benefit. However, 150 mg/day of erlotinib seems too toxic as maintenance therapy. This study aimed to evaluate the efficacy and safety of low-dose erlotinib (25 mg/day) as maintenance treatment after platinum doublet chemotherapy in NSCLC harboring epidermal growth factor receptor (EGFR) mutation.

The rapid increase in the incidence rate of colorectal cancer has led to the search and identification of biomarkers that can predict risk for and future behavior of this malignancy and management. To study the biological role of the phosphorylated Fas associated death domain (pFADD) gene in colorectal cancer, we performed a GAL4-based yeast two-hybrid screening of a human heart cDNA library.

Microarray technology is a powerful genomic tool for simultaneously studying and analyzing the behavior of thousands of genes. The analysis of images obtained from this technology plays a critical role in the detection and treatment of diseases. The aim of the current study is to develop an automated system for analyzing data from microarray images in order to detect cancerous cases. The proposed system consists of three main phases, namely image processing, data mining, and the detection of the disease. The image processing phase performs operations such as refining image rotation, gridding (locating genes) and extracting raw data from images the data mining includes normalizing the extracted data and selecting the more effective genes. Finally, via the extracted data, cancerous cell is recognized. To evaluate the performance of the proposed system, microarray database is employed which includes Breast cancer, Myeloid Leukemia and Lymphomas from the Stanford Microarray Database. The results indicate that the proposed system is able to identify the type of cancer from the data set with an accuracy of 95.45%, 94.11%, and 100%, respectively.

Drug resistance remains a major problem in the treatment of cancer for both hematological malignancies and solid tumors. Intrinsic or acquired resistance can be caused by a range of mechanisms, including increased drug elimination, decreased drug uptake, drug inactivation and alterations of drug targets. Recent data showed that other than by well-known genetic (mutation, amplification) and epigenetic (DNA hypermethylation, histone post-translational modification) modifications, drug resistance mechanisms might also be regulated by splicing aberrations. This is a rapidly growing field of investigation that deserves future attention in order to plan more effective therapeutic approaches. The protocol described in this paper is aimed at investigating the impact of aberrant splicing on drug resistance in solid tumors and hematological malignancies. To this goal, we analyzed the transcriptomic profiles of several in vitro models through RNA-seq and established a qRT-PCR based method to validate candidate genes. In particular, we evaluated the differential splicing of DDX5 and PKM transcripts. The aberrant splicing detected by the computational tool MATS was validated in leukemic cells, showing that different DDX5 splice variants are expressed in the parental vs. resistant cells. In these cells, we also observed a higher PKM2/PKM1 ratio, which was not detected in the Panc-1 gemcitabine-resistant counterpart compared to parental Panc-1 cells, suggesting a different mechanism of drug-resistance induced by gemcitabine exposure.

The identification of functional driver events in cancer is central to furthering our understanding of cancer biology and indispensable for the discovery of the next generation of novel drug targets. It is becoming apparent that more complex models of cancer are required to fully appreciate the contributing factors that drive tumorigenesis in vivo and increase the efficacy of novel therapies that make the transition from pre-clinical models to clinical trials. Here we present a methodology for generating uniform and reproducible tumor spheroids that can be subjected to siRNA functional screening. These spheroids display many characteristics that are found in solid tumors that are not present in traditional two-dimension culture. We show that several commonly used breast cancer cell lines are amenable to this protocol. Furthermore, we provide proof-of-principle data utilizing the breast cancer cell line BT474, confirming their dependency on amplification of the epidermal growth factor receptor HER2 and mutation of phosphatidylinositol-4,5-biphosphate 3-kinase (PIK3CA) when grown as tumor spheroids. Finally, we are able to further investigate and confirm the spatial impact of these dependencies using immunohistochemistry.

Primary central nervous system lymphoma (PCNSL) is a type of non-Hodgkin lymphoma (NHL), and it has been postulated that metabolic disorder may contribute to NHL etiology. We retrospectively investigated the prognostic significance of hyperglycemia in patients with PCNSL. We evaluated glucose transporter type 1 (GLUT1) expression by immunohistochemistry and analyzed its association with hyperglycemia and survival.

To explore expression of angiopoietin-like protein 2 (ANGPTL2) and its effect on biological behavior such as proliferation and invasiveness in gastric cancer.

To analyze colorectal carcinogenesis and age-related DNA methylation alterations of gene sequences associated with epigenetic clock CpG sites.

It has become clear that tumorigenesis results from much more than just the activation of an oncogene and/or the inactivation of a tumor-suppressor gene, and that the cancer cell genome contains many more alterations than can be specifically targeted at once. This observation has led our group to a search for alternative ways to kill cancer cells (while sparing normal cells) by focusing on properties unique to the former. We have identified four approaches with the potential to generate new anticancer therapies: combatting the tactics by which cancers evade antitumor immune responses, targeting metabolic adaptations that tumor cells use to survive conditions that would kill normal cells, manipulating a cancer cell's response to excessive oxidative stress, and exploiting aneuploidy. This review describes our progress to date on these fronts.

Fluid-phase endocytosis is a homeostatic process with an unknown role in tumor initiation. The driver mutation in pancreatic ductal adenocarcinoma (PDAC) is constitutively active KRasG12D, which induces neoplastic transformation of acinar cells through acinar-to-ductal metaplasia (ADM). We have previously shown that KRasG12D-induced ADM is dependent on RAC1 and EGF receptor (EGFR) by a not fully clarified mechanism. Using three-dimensional mouse and human acinar tissue cultures and genetically engineered mouse models, we provide evidence that (i) KRasG12D leads to EGFR-dependent sustained fluid-phase endocytosis (FPE) during acinar metaplasia; (ii) variations in plasma membrane tension increase FPE and lead to ADM in vitro independently of EGFR; and (iii) that RAC1 regulates ADM formation partially through actin-dependent regulation of FPE. In addition, mice with a pancreas-specific deletion of the Neural-Wiskott-Aldrich syndrome protein (N-WASP), a regulator of F-actin, have reduced FPE and impaired ADM emphasizing the in vivo relevance of our findings. This work defines a new role of FPE as a tumor initiating mechanism.

Amplicon-based massively parallel sequencing (MPS) is an effective platform for identifying clinically actionable mutations across many genes in limited amounts of tissue. Most lung cancers are diagnosed and staged using small tissue samples obtained by transbronchial biopsy (TBB). To determine whether the mutations in TBB specimens detected by amplicon-based MPS reflect those present in the tumors, we compared the mutational profiles of preoperative TBB specimens and corresponding surgically resected specimens.

The perfect method to discover and validate actionable somatic variants in cancer has not yet been developed, yet significant progress has been made toward this goal. There have been huge increases in the throughput and cost of deoxyribonucleic acid (DNA) and ribonucleic acid (RNA) sequencing technologies that have led to the burgeoning possibility of using sequencing data in clinical settings. Discovery of somatic mutations is relatively simple and has been improved recently due to laboratory methods optimization, bioinformatics algorithms development, and the expansion of various databases of population genomic information. Tiered systems of evidence evaluation are currently being used to classify genomic variants for clinicians to more rapidly and accurately determine actionability of these aberrations. These efforts are complicated by the intricacies of communicating sequencing results to physicians and supporting its biological relevance, emphasizing the need for increasing education of clinicians and administrators, and the ongoing development of ethical standards for dealing with incidental results. This chapter will focus on general aspects of DNA and RNA tumor sequencing technologies, data analysis and interpretation, assessment of biological and clinical relevance of genomic aberrations, ethical aspects of germline sequencing, and how these factors impact cancer personalized care.

Novel, "outside of the box" approaches are needed for evaluating candidate molecules, especially in oncology. Throughout the years of 2000-2010, the efficiency of drug development fell to barely acceptable levels, and in the second decade of this century, levels have improved only marginally. This dismal condition continues despite unprecedented progress in the development of a variety of high-throughput tools, computational methods, aggregated databases, drug repurposing programs and innovative chemistries. Here we tested a hypothesis that the economic impact of targeting a particular gene product is predictable a priori by employing a combination of transcriptome profiles and quantitative metrics reflecting existing literature.