As the most common female malignancy, breast cancer is the most likely reason that a woman will die of cancer around the world. Breast cancer mortality has dropped in the U.S. by 35% since 1990 due to improved early detection and timely treatment.  By contrast, most breast cancer deaths occur in low and middle income countries (LMICs).  The Breast Health Global Initiative (BHGI) developed resource-stratified guidelines as a framework for breast cancer management in limited resource environments.  Pilot studies from Latin America, Asia and sub-Saharan Africa use implementation research methods to demonstrate best practices that improve outcome despite resource constraints. “Phased implementation” is a novel approach to guide strategic program development to save breast cancer lives.

Learning Objectives: 

1. Understand why breast cancer mortality has dropped in the U.S. by 35% since 1990
2. Understand why breast cancer is the most likely reason that a woman will die of cancer around the world

Recent work has identified epigenomic features of distal regulatory elements to be dynamic and defining indicators of cellular specification and transformation. Of particular relevance is our nascent discovery of differentially methylated cytosines in regulatory DNA elements implicated in the control of myeloid differentiation in a murine model of mutant IDH1 leukemia. Strikingly, we have also found that vitamin C, a cofactor for TET, can reverse the methylation gains characteristic of the IDH1-mutant leukemic blasts in this engineered mouse model and initiate their expression of myeloid markers. These data suggest a new/additional role of TET/IDH mutations in driving an epigenetic-mediated silencing of regulatory elements required to activate myeloid differentiation. They also show that this mechanism can be readily reversed by exposing the affected cells to a known, nontoxic molecule (vitamin C). These findings raise the exciting possibility that this type of epigenetic change may constitute a more generalized mechanism contributing to the blocked differentiation phenotype of human AML blasts and one that may be targeted by strategies that have significantly reduced side effects.

Learning Objectives: 

1. An introduction to epigenetic dysfunction in cancer.
2. An understanding of the epigenetic features associated with gain of function IDH mutations in leukemia
3. An understanding of the role of vitamin C in the maintenance of DNA methylation homeostasis

Although targeted therapies often elicit profound initial patient responses, these effects are transient due to residual disease leading to acquired resistance. How tumors transition between drug responsiveness, tolerance and resistance, especially in the absence of pre-existing subclones, remains unclear. In EGFR-mutant lung adenocarcinoma cells, we demonstrate that residual disease and acquired resistance in response to EGFR inhibitors requires AURKA activity. Non-genetic resistance through the activation of AURKA by its co-activator TPX2 emerges in response to chronic EGFR inhibition where it mitigates drug-induced apoptosis. Aurora kinase inhibitors suppress this adaptive survival program, increasing the magnitude and duration of EGFR inhibitor response in pre-clinical models. Treatment induced activation of AURKA was associated with resistance to EGFR inhibitors in-vitro, in-vivo and in individuals with EGFR-mutant lung adenocarcinoma. These findings delineate a path whereby drug resistance emerges from drug-tolerant cells and unveils a synthetic lethal strategy for enhancing responses to EGFR inhibitors by suppressing AURKA driven residual disease and acquired resistance.
 

Learning Objectives:

1. Describe pathways of EGFR-TKI resistance mechanisms.
2. Approaches to identify novel targets in EGFR-TKI resistance patients.

Lung cancer is the leading cause of cancer-related mortality worldwide. Large-scale sequencing studies have revealed the complex genomic landscape of NSCLC and genomic differences between lung adenocarcinomas (LUAD) and lung squamous cell carcinomas (LUSC). However, in-depth exploration of NSCLC intratumor heterogeneity and cancer genome evolution has been limited to small retrospective cohorts. As such, the clinical significance of ITH and the potential for clonality of driver events to guide therapeutic strategies is not yet defined.

In this talk I will outline how intra-tumor heterogeneity can be deciphered using multi-region sequencing. I will examine how heterogeneity can be utilized to gain a deeper understanding of tumor evolution, focusing on results from the TRACERx  (TRAcking non-small cell lung Cancer Evolution through therapy (Rx)) study.

I will explore the clinical implications of intra-tumor heterogeneity and consider clinical approaches to tackle this devastating disease. 

Learning Objectives: 

1. Tumour heterogeneity is widespread in early stage NSCLC and occurs at both mutational and copy number level
2. APOBEC-mediate mutagenesis occurs later in lung cancer evolution and is associated with subclonal expansions
3. HLA LOH is a pervasive mechanisms of immune evasion. 

Two projects looking at novel approaches to targeting inflammatory breast cancer will be presented. Inflammatory breast cancer (IBC) is a unique, understudied, and most lethal subtype accounting for ~15% of all breast cancer deaths. IBC is characterized by Stage III or IV at diagnosis, no solid tumor, typically not detected by mammogram and rapid progression from onset of disease. The incidence of IBC is higher in younger patients and in women of African descent. There are limited treatment options for IBC. Targeted therapy with drugs that target HER1/2 (if the cancer is HER2-positive) e.g. the HER1/2 tyrosine kinase inhibitor lapatinib are one of the few treatment options but drug resistance is observed in the clinic. In the first project, we characterized a novel isogenic-derived progression model of lapatinib drug resistance and re-sensitization using the IBC cell line SUM149. In this study, lapatinib-resistant rSUM149 cells showed cross-resistance to a number of the drugs previously shown to act on the parental cells. The rSUM149 cells had increased levels of anti-apoptotic proteins, increased antioxidant expression, and decreased ability to accumulate reactive oxygen species (ROS), all of which lead to inhibition of drug-induced apoptosis. These results strengthen the need for novel strategies to modulate cellular redox to overcome drug resistance in IBC. In the second project, a major effort of our lab is to identify novel modulators of the hedgehog pathway in breast cancer. Dysregulation of the developmental Hedgehog (Hh) pathway is observed in many cancers with activation of the downstream Hh pathway effector GLI1 being linked to tumorigenesis and invasiveness in breast cancer including IBC. We have profiled a collection of GLI-directed small molecule antagonists possessing distinct mechanisms of action for efficacy in phenotypic models of IBC, with a subset including the direct GLI1 binder GANT61 demonstrating activity in vivo. Further, we have also shown that GLI1 is directly phosphorylated by the kinase DYRK1A at a site within its putative nuclear localization sequence suggesting a possible mechanistic role in modulating its function. Utilizing the BRITE Institute’s capabilities in high-throughput screening we have identified novel and potent DYRK1A inhibitors that are being assessed for cellular and in vivo efficacy.

Learning Objectives:

1. Understand some of the new and novel approaches to targeting inflammatory breast cancer
2. Understand why there are limited treatment options for IBC

Antibodies are extremely valuable and ubiquitous tools in life science research, but in spite of their widespread use in immunoassays over the past several decades, there is still a lack of understanding on the design, validation, and appropriate use of antibodies and controls to publish convincing science. It is generally accepted that a good antibody must be specific, selective, and should provide reproducible results in the context for which it is used. The large diversity of antibody users, their background and experience, their large range of applications, coupled with hundreds of commercial sources for antibodies and immunotechnologies, makes understanding antibody theory and use very relevant today. This presentation will discuss several key aspects of antibody design, validation, and best practices for publishing on various applications from basic immunopurifications and Western blots, to conformation specific binding and high speed imaging flow cytometry. Typical reviewer comments will be addressed and discussed in the context of antibody binding theory and practice. Further, best practices in selecting antibodies, the need for multiple validations, documentation, and commercial source partnerships will be discussed. 

Learning Objectives:

1. What are the key elements of antibody design and validation 
2. How to select the right antibody 
3. What information is helpful for reviewers 

The oncogenic transcription factor c-MYC (MYC) is deregulated, and often overexpressed, in more than 50% of cancers. MYC deregulation is associated with poor prognosis and aggressive disease, suggesting that the development of therapeutic inhibitors targeting MYC would dramatically impact patient care and outcome. MYC is a highly regulated transcription factor, with a protein and mRNA half-life of approximately 30 min. The most extensively studied pathway regulating MYC protein stability involves ubiquitylation and proteasomal degradation mediated by the E3-ligase, SCFFbxw7. We provide evidence for a SCFFBXW7-independent regulatory mechanism centered on Lysine 52 (K52) within MYC Box I (MBI) of the MYC protein. This residue has been shown to be post-translationally modified by both ubiquitylation and SUMOylation, hinting at the interplay of post-translational modifications at this site, and the importance of this residue. We demonstrate that mutation of K52 to arginine (R) renders the MYC protein more labile. Mechanistically, we show that the degradation pathway regulated by K52 is independent of the Cullin-Ring-Ligase (CRL) family of E3-ligases, which includes not only the canonical SCFFBXW7, but also a number of other known MYC-targeting E3-ligases, such as SCFSKP2, SCFβTCRP, SCFFBXO28 and DCXTRUSS. To characterize this degradation pathway further we will utilize unbiased and targeted experiments to elucidate the proteins involved. Taken together, our data identifies a novel regulatory pathway centred on K52 that may be exploited for the development of anti-MYC therapeutics. 

Learning Objectives: 

1. Learn about the critical role of MYC in tumorigenesis
2. Understand the relationship between the amount of MYC protein in the cell and its tumorigenicity
3. Understand how the stability of the MYC protein is regulated in the cell

In the last two decades, large amount of next-generation sequencing (NGS) and -omics data has been generated in the field of immuno-oncology. Generating hypotheses by analyzing hundreds if not thousands of differentially expressed genes from expression studies and mining information from large amount of publicly available NGS and -omics data can be a very daunting task. QIAGEN’s Oncoland/Arraystudio (from Omicsoft) and Ingenuity Pathway Analysis (IPA) software provide with a set of tools and functionalities to do analysis and interpretation of NGS data to generate meaningful hypotheses and the ability to mine and compare information across a very large number of datasets curated from publicly available from sources such as GEO, SRA, TCGA, GTEX and others. In this webinar, we use gene expression data from a clinical study (GSE67501) focused on understanding the mechanism underlying anti-PD-1 therapy failure in advanced renal cell carcinoma patients. Using this data and the data curated from TCGA and other sources, it will be demonstrated how Arraystudio and Ingenuity Pathway Analysis can be used to generate hypotheses for mechanism of action and to discover potential targets and biomarkers.

Learning Objectives: 

1. Introduction to databases backing Ingenuity Pathway Analysis and Oncoland
2. Studying potential biomarkers and targets through Oncoland’s data mining and comparison tools
3. Generation of peer-reviewed literature backed hypotheses through Ingenuity Pathway Analysis

In the past two decades a small number of infrequently dividing cells have been proposed as the source of multi-drug resistance during cancer treatment. These cells identified by their expression of stem cell markers have been shown to proliferate when grafted in animals and have been called cancer stem cells in analogy to adult stem cells maintaining organ homeostasis. In this talk different kinetic models of tumor proliferation are presented and compared to tumor kinetics in large number of patients with metastatic disease obtained from cancer clinical trials. The conclusion from this analysis is that almost all analyzed tumors after initial volume decrease begin to grow exponentially, inconsistent with the hypothesis that small number of self-renewing, drug resistance cells drive this growth. Cell proliferation resembles the proliferation of embryonic stem cells early in embryogenesis and not of adult stem cells. Our data is consistent with exponential cell proliferation with fixed growth rate, implying that the number of proliferating cells in these cancers is very large and divide symmetrically. The main implication of this work is that cancer therapies must target all cells and not just a small subset of cells in a tumor. 

Learning Objectives: 

1. To present current models of tumor growth and evidence that in advanced cancers, although rare stem-like cancer cells might exist, the majority of cells drive tumor growth.
2. For a therapy to be curative it has to target all cancer cells, because most cells are the source of drug resistance. 

PacBio Sequencing simultaneously provides long sequence reads, high consensus accuracy, minimal sequence bias, and methylation detection. I will highlight new advances and updates on applying PacBio sequencing in cancer research, including targeted sequencing, genome-wide structural variant detection and de novo assembly of cancer genomes. Other topics presented will include full-length RNA sequencing (Iso-Seq) for the detection of gene fusions and cancer-related transcript splice isoforms, and how high-accuracy single-molecule consensus reads (through a process called circular consensus sequencing (CCS)), a capability unique to PacBio sequencing technology, can be leveraged for high-resolution, phased minor variant analysis. 

Learning Objectives: 

1. Learn about new methods to detect larger-scale genetic variants in cancer genomes
2. Understand the utility of long-read PacBio sequencing for long-distance phasing of variants
3. Get familiar with full-length RNA-seq (Iso-Seq) for the detection of gene fusions and cancer-related transcript splice isoforms

One of the main challenges in precision medicine consists of developing predictors of drug response to select the most beneficial therapy for each individual patient. In this context, preclinical models are crucial to study the association between molecular features of tumor cells and response to chemical perturbations. However, only few predictors have been successfully translated to clinical settings. Such a low success rate is due not only to the complexity of the mechanisms underlying anticancer drug response, but also to the lack of robustness of the predictors developed in preclinical settings. To address this issue we developed PharmacoGx, a computational platform enabling meta-analysis of large-scale drug screenings of in vitro and in vivo model systems, and PharmacoDB (pharmacodb.pmgenomics.ca), a web-application enabling quick access to a large compendium of pharmacogenomics datasets. In this presentation I will show how we used our new platforms to (i) identify pathways whose genomic and transcriptomic patterns are preserved between model systems and patient tumors, and (ii) develop univariate and multivariate predictors of drug response that can be validated in clinical trial data. 

Learning Objectives: 

1. Learn about the potential and limitations of biomarker discovery using preclinical pharmacogenomic data
2. Learn about the computational tools available for biomarker discovery in preclinical settings

Mammalian cells including cancer cells respond to stress with mechanisms that promote the preservation of cellular functions. These mechanisms have been intensively investigated as potential targets to boost the cytotoxicity of cancer therapy. However, the same pathways underlie the emission of signals that coordinate adaptive responses across tissues, organs and the whole organism, implying that their inhibition may compromise immunological tumour control. Thus, the quantity of cancer cells that succumb treatment (which never is 100%) may be less important than the actual mechanisms activated in the course of cancer cell death for disease outcome.

To date the anatomic extent of tumor (TNM-classification) has been by far the most important factors to predict the prognosis of cancer patients. However, this classification provides limited prognostic information and does not predict response to therapy. 

We redefined cancer by integrating the immune system, to transfer cutting-edge medicine to the patients. We showed that tumors from human colorectal cancer with a high-density of infiltrating memory and effector-memory T-cells (Tem) are less likely to disseminate to lymphovascular and perineural structures and to regional lymph-nodes. We demonstrated the critical tumor-microenvironment parameters determining the dissemination to distant metastasis. We showed that the combination of immune parameters associating the nature, the density, the functional immune orientation and the location of immune cells within the tumor was essential to accurately define the impact of the local host-immune reaction on patients prognosis. We defined these parameters as the “immune contexture”. We characterized the immune landscape within human tumors, and showed the importance of adaptive immune cells including, cytotoxic T-cells, Th1-cells, B-cells and T-follicular-helper (Tfh) cells. We described the immunopenotype and antigenome associated with immune escape mechanisms and demonstrated mechanisms associated with pre-existing and proliferating intratumoral T-cells. 

Based on the immune contexture, a standardized, simple and powerful digital-pathology-based immune stratification-system, termed “Immunoscore”, was delineated having a prognostic power superior to that of the currently used cancer staging-system. Tumor invasion parameters were statistically dependent on the host-immune reaction. A worldwide consortium is validating the prognostic value of Immunoscore, using a standardized-assay. Recent data are supporting the significant role of Immunoscore within lung, liver, and brain metastases and cancer evolution. Thus, tumor progression, invasion and recurrence are dependent on pre-existing immunity and on Immunoscore.

Learning Objectives: 

1. To decipher and understand the complexity of the tumor microenvironment.
2. To demonstrate the need for genomics, immunomics and systems biology to achieve precision medicine.

RNA sequencing unlocks the mysteries hidden in the transcriptome. Whether your goal is gene expression analysis, gene fusion analysis, SNP analysis or miRNA expression analysis, achieving high-performance library preparation can prove essential to maximizing your discoveries. In this webinar, you will learn about best practices, considerations and tips for library prep such as the use of unique molecular indices, as well as useful insights and advice for sample prep, sample QC, sequencing, data analysis and interpretation so you can achieve your greatest RNA-seq outcomes. 
 
Whether you’re just beginning RNA sequencing or are an experienced transcriptomics researcher, this webinar has something new for you! Join us for an encyclopedic discussion of RNA sequencing with Dr. Jonathan Shaffer, Associate Director of NGS Assay Technologies, and learn everything you need to know about RNA sequencing (but were afraid to ask).

Learning Objectives: 

1. Understand the different types of RNA NGS  (Stranded transcriptome, targeted panels, 3' transcriptome and targeted panels,  and  miRNA) and  the differences in their library construction methods
2. Learn the benefits of incorporating Unique Molecular Indices (UMIs) into RNA libraries
3. Understand primary, secondary and tertiary RNAseq data analysis  and best practices

Pancreatic tumors are dynamic pseudo-organs that contain numerous cell types interacting to create unique physiology. A typical pancreatic tumor is made up largely of stromal fibroblasts and immune cell populations, rather than cancer cells. These non-malignant cells act collaboratively to create a dense fibrotic matrix that blocks cancer cells from accessing nutrients and oxygen by inhibiting vascularization. The cancer cells are thus in a state of near-starvation and must employ unorthodox methods to obtain nutrients to support their bioenergetic and biosynthetic needs. Our group has provided foundational work describing the cell autonomous reprogramming of metabolic processes in the cancer cells to facilitate survival and growth under these challenging circumstances. Beyond cell intrinsic metabolic alterations, pancreatic cancer cells also work cooperatively with the non-cancer cells in the tumor microenvironment through the exchange of growth factors, signaling molecules and metabolites. In this seminar, I will describe new work illuminating pathways of metabolic crosstalk among pancreatic cancer-associated fibroblasts, tumor associated macrophages, and malignant pancreatic cancer cells in maintenance of tumor growth, survival and therapeutic resistance. 

For Research Use Only. Not for use in diagnostic procedures.

Learning Objectives: 

1. Pancreatic cancer is the most deadly major cancer, and this owes in large part to the lack of effective therapies
2. Pancreatic tumors are nutrient and oxygen limited and are composed of numerous cell types that interact to promote growth and survival
3. Metabolic networks exist among the cells in pancreatic tumors that facilitate growth, survival, and promote therapeutic resistance

The microbiome signatures in the context of gynecologic cancers (endometrial and ovarian) and the potential for their clinical use will be discussed. The use of microfluidic technologies to interrogate the role of these microbes in the disease processes and interference with treatment will also be addressed.

Learning Objectives:

1. Learn how the vaginal microbiome can be used to detect endometrial cancer
2. Study ovarian cancer microbiome use as a prognostic tool
3. Explore the use of microfluidic technologies for a single cell level of mechanistic interrogation for the role of the microbiome in gynecologic cancers 

High-throughput screening is widely useful in identifying genes and pathways that drive changes in cell behavior such as cell cycle regulation, metastasis, and drug resistance.  MilliporeSigma develops and distributes a comprehensive portfolio of functional genomics tools for efficient, high quality, genome-scale analysis of cellular processes.  In this webinar, we will demonstrate the utility of three genome-wide approaches to unbiased identification of relevant gene pathways for cancer discovery: shRNA knock-down, CRISPR knock-out, and CRISPR activator libraries.

Learning Objectives: 

1. Learn how to select reagents for whole-genome screens
2. Learn about complementarity between screening technologies 
3. Learn example methods for candidate validation

In prior work, we have pursued how tumor reactive monoclonal antibody (mAb), together with activators of innate immune cells, like NK cells, can augment antibody dependent cell-mediated cytotoxicity (ADCC) of cancer cells in vitro. Following preclinical development in mice, this work has been translated into clinical efficacy in the setting of maintenance therapy for high risk neuroblastoma, and the FDA approval of the anti-GD2 mAb, dinutuximab. We have shown how the genotype of patients for NK inhibitory KIR genes can influence the activity of this therapy. More recently, we have identified a novel combination therapy (“In Situ Vaccination”) given directly to a large existing tumor that enables it to function as a potent vaccine, providing long-lasting cure of mice from large tumors that were previously non-curable with other immunotherapy approaches. Following local radiotherapy (RT), we directly inject a tumor-reactive immunocytokine [a tumor-reactive anti-GD2 mAb linked to IL2, a potent immune cell activator]. Most mice bearing a single large melanoma show tumor elimination with long lasting protective immunity with this approach (Morris et al, Cancer Research, 76:3929, 2016). In mice with 2 tumors, delivering RT to both the 1st + 2nd tumors, or adding checkpoint-blockade therapy using an anti-CTLA-4 mAb, enables injection of immunocytokine to the 1st tumor to eradicate it as well as the 2nd tumor in most mice. (Morris et al, Cancer Immunology Research,6: 825-834, 2018). Clinical testing in melanoma is being initiated. Preliminary results are similar in mice bearing pancreatic cancer or neuroblastoma, and clinical translation in neuroblastoma has been started. We hypothesize that In Situ Vaccination will also be effective in other tumors that appear resistant to checkpoint-blockade.

Learning Objectives: 

1. Immune responses can be induced against “cold” tumors
2. Combined approaches, activating presentation and recognition,  blocking an immunosuppressive micro-environment, and “taking off the brakes” can be synergistic.

Molecular analyses of cancer biology have tended to segregate between a focus on nucleic acids – DNA, RNA and their modifications – and a focus on proteins and protein function. Proteogenomics represents a fusion of those two approaches, leveraging the strengths of each to provide a more integrated vision of the flow of information from DNA to RNA to protein and eventually function at the molecular level. Proteogenomic studies have been incorporated into multiple activities associated with precision oncology, demonstrating substantial added value. Innovative study designs integrating genomic, transcriptomic and proteomic data, particularly those using clinically relevant samples and involving clinical trials, are poised to provide new insights regarding cancer risk, progression, and response to therapy.

Learning Objectives: 

1. Understand the value-added of including protein measurements with genomics and transcriptomics
2. Understand the importance of pathway-level analysis

Understanding the immune repertoire is an important aspect of immuno-oncology research, which can be used to gather insights into the function and overall status of the immune system. We have developed a simple and straightforward workflow with an RNA-seq panel, which uses Unique Molecular Indices (UMIs), and a data analysis package to characterize the alpha, beta, gamma and delta chains of the human or mouse T-cell receptors, including the CDR1, CDR2 and CDR3 regions. In this webinar, we will discuss both performance and application data for T-cell receptor sequencing and how a complete workflow including UMIs and UMI-enabled software helps increase the overall confidence in the final data analysis.

Learning Objectives: 

1. Understand the biology of T-cells & T-cell receptors
2. Identify different methods of T-cell clonotyping
3. Learn how unique molecular indexing is being used in NGS applications

With over 265,000 new cases per year and over 50,000 deaths, breast and ovarian cancers represent a significant health burden in the USA.  Prior work has demonstrated that CD4 helper T cell immunity is protective against recurrence of both breast and ovarian cancer.  Based on pre-existent immunity, several degenerate epitope-based vaccines have been developed targeting tumor-associated antigens such as HER2/neu and the Folate Receptor Alpha.  These vaccines demonstrate the ability to generate robust long-lived immunity and may have a role, when combined with other agents, in protecting against disease relapse.

Learning Objectives: 

1. Learn fundamentals of vaccination
2. Learn types of antigens that are targeted with cancer vaccines.
3. Learn clinical settings in which vaccines are being used.