CEDSS: “The Origins and Detection of Lethal Prostate Cancer”
Paul Boutros, Ph.D., M.B.A.
Director, Cancer Data Sciences
UCLA
Please see zoom details below:
Meeting URL: https://stanford.zoom.us/s/93515779500
Dial: +1 650 724 9799 or +1 833 302 1536
Meeting ID: 935 1577 9500
Meeting Passcode: 767148
ABOUT
Boutros earned his B.Sc. degree from the University of Waterloo in Chemistry in 2004, and his Ph.D. degree from the University of Toronto, Canada, in Medical Biophysics in 2008. At Toronto, he also earned an executive M.B.A. from the Rothman School of Management. In 2008, Boutros started his independent research career at the Ontario Institute for Cancer Research first as a fellow (2008–2010) and then as principal investigator (2010–2018). He moved to California to join the UCLA faculty in 2018.
Hosted by: Utkan Demirci, Ph.D.
Sponsored by the Canary Center & the Department of Radiology
Stanford University – School of Medicine
Ge Wang, PhD
Clark & Crossan Endowed Chair Professor
Director of the Biomedical Imaging Center
Rensselaer Polytechnic Institute
Troy, New York
Abstract:
AI-based tomography is an important application and a new frontier of machine learning. AI, especially deep learning, has been widely used in computer vision and image analysis, which deal with existing images, improve them, and produce features. Since 2016, deep learning techniques are actively researched for tomography in the context of medicine. Tomographic reconstruction produces images of multi-dimensional structures from externally measured “encoded” data in the form of various transforms (integrals, harmonics, and so on). In this presentation, we provide a general background, highlight representative results, and discuss key issues that need to be addressed in this emerging field.
About:
AI-based X-ray Imaging System (AXIS) lab is led by Dr. Ge Wang, affiliated with the Department of Biomedical Engineering at Rensselaer Polytechnic Institute and the Center for Biotechnology and Interdisciplinary Studies in the Biomedical Imaging Center. AXIS lab focuses on innovation and translation of x-ray computed tomography, optical molecular tomography, multi-scale and multi-modality imaging, and AI/machine learning for image reconstruction and analysis, and has been continuously well funded by federal agencies and leading companies. AXIS group collaborates with Stanford, Harvard, Cornell, MSK, UTSW, Yale, GE, Hologic, and others, to develop theories, methods, software, systems, applications, and workflows.
CEDSS: Systematic identification of fluid-based biomarkers for ovarian and prostate cancer
Thomas Kislinger, Ph.D.
Professor & Chair
Department of Medical Biophysics
University of Toronto
Senior Scientist
Princess Margaret Cancer Centre
Zoom Webinar Details
Meeting URL: https://stanford.zoom.us/s/94878578384
Dial: +1 650 724 9799 or +1 833 302 1536
Webinar ID: 948 7857 8384
Passcode: 692692
Register Here
ABOUT
Thomas Kislinger received his MSc in Analytical Chemistry from the University of Munich, Germany (1998). He completed his PhD in 2001, investigating the role of Advanced Glycation Endproducts in diabetic vascular complications at the University of Erlangen, Germany and Columbia University, New York. Between 2002 and 2006 he completed a post-doctoral fellowship at the University of Toronto. In 2006 he joined the Princess Margaret Cancer Centre as an independent investigator. Dr. Kislinger holds positions as Senior Scientist at the Princess Margaret Cancer Centre and as Professor and Chair at the University of Toronto in the Department of Medical Biophysics. The Kislinger lab applies proteomics technologies to translational and basic cancer biology. This includes the development of novel proteomics methodologies, identification of liquid biopsy signatures and the molecular identification of novel cell surface markers.
Hosted by: Utkan Demirci, Ph.D.
Sponsored by: The Canary Center & the Department of Radiology
Stanford University – School of Medicine
CEDSS: Disseminated cell hybrids as biomarkers for cancer detection, prognosis and treatment response
Melissa Wong, Ph.D.
Associate Professor and Vice Chair
Department of Cell, Development and Cancer Biology
Program Co-Lead, Knight Cancer Institute
Oregon Health & Science University
Zoom Details
Meeting URL: https://stanford.zoom.us/s/98184098662
Dial: US: +1 650 724 9799 or +1 833 302 1536 (Toll Free)
Meeting ID: 981 8409 8662
Passcode: 084321
ABSTRACT
Metastatic progression defines the final stages of tumor evolution and underlies the majority of cancer-related deaths. The heterogeneity in disseminated tumor cell populations capable of seeding and growing in distant organ sites contributes to the development of treatment resistant disease. We recently reported the identification of a novel tumor-derived cell population, circulating hybrid cells (CHCs), harboring attributes from both macrophages and neoplastic cells, including functional characteristics important to metastatic spread. These disseminated hybrids outnumber conventionally defined circulating tumor cells (CTCs) in cancer patients. It is unknown if CHCs represent a generalized cancer mechanism for cell dissemination, or if this population is relevant to the metastatic cascade. We detect CHCs in the peripheral blood of patients with cancer in myriad disease sites encompassing epithelial and non-epithelial malignancies. Further, we demonstrate that in vivo-derived hybrid cells harbor tumor-initiating capacity in murine cancer models and that CHCs from human breast cancer patients express stem cell antigens, features consistent with the ability to seed and grow at metastatic sites. We reveal heterogeneity of CHC phenotypes reflect key tumor features, including oncogenic mutations and functional protein expression. Importantly, this novel population of disseminated neoplastic cells opens a new area in cancer biology and renewed opportunity for battling metastatic disease.
ABOUT
The research focus of the Wong laboratory revolves around understanding the regulatory mechanisms that control epithelial stem cell homeostasis and their expansion in developmental, homeostasis and disease contexts, including cancer. I have substantial training and experience in intestinal stem cell investigation leveraging in vivo and ex vivo modeling, as well as in myriad cutting edge technologies (i.e. cyCIF, scRNA-seq). My publication record spans my post-doctoral fellowship in Dr. Jeffrey Gordon’s laboratory at Washington University School of Medicine, to studies in my own laboratory at Oregon Health & Science University. Our research impacts the understanding of regulatory mechanisms that govern cell state in the context of the evolving tissue microenvironment and changing cell signaling landscape, in development and disease.
Our studies in stem cell regulation led to the intriguing finding that stem cells can fuse with tissue macrophages in the context of injury repair and may impact tissue regeneration. We have extended these findings to the cancer setting, where cancer-macrophage fusions are detectible in primary and metastatic tumors, and my group recently identified and characterized these cells as a novel circulating tumor cell population. Importantly, our studies in cell culture, in mice and humans provide an indepth evaluation of hybrid cells to set the foundation for continued investigations into their biology, impact on disease progression or tissue regeneration, and use as a biomarker for disease burden. Importantly, we coined the term, circulating hybrid cell (CHC) for this novel population and reported they exist at higher levels than conventionally defined circulating tumor cells in the peripheral blood of cancer patients. This work was published in 2018 and highlighted by Science Magazine as one of the top ten publications in the cancer field in the science family journals. The science proposed in this U01 application leverage hybrid cell biology to assess treatment response and resistance in breast cancer patients undergoing targeted therapy. Our proposal leverages active collaborations with Dr. Young Hwan Young’s group to synergize biology with computation, as well as a number of other valuable collaborators to ensure success of the proposed, cutting-edge science.
Hosted by: Utkan Demirci, Ph.D.
Sponsored by: The Canary Center & the Department of Radiology
Stanford University – School of Medicine
Targeted violence continues against Black Americans, Asian Americans, and all people of color. The department of radiology diversity committee is running a racial equity challenge to raise awareness of systemic racism, implicit bias and related issues. Participants will be provided a list of resources on these topics such as articles, podcasts, videos, etc., from which they can choose, with the “challenge” of engaging with one to three media sources prior to our session (some videos are as short as a few minutes). Participants will meet in small-group breakout sessions to discuss what they’ve learned and share ideas.
Please reach out to Marta Flory, flory@stanford.edu with questions. For details about the session, including recommended resources and the Zoom link, please reach out to Meke Faaoso at mfaaoso@stanford.edu.
CEDSS: “Building a Scalable Clinical Genomics Program: How tumor, normal, and plasma DNA sequencing are informing cancer care, cancer risk, and cancer detection”
Elizabeth and Felix Rohatyn Chair & Associate Director of the Marie-Josée and Henry R. Kravis Center for Molecular Oncology
Memorial Sloan Kettering Cancer Center
Zoom Details
Meeting URL: https://stanford.zoom.us/s/92559505314
Dial: US: +1 650 724 9799 or +1 833 302 1536 (Toll Free)
Meeting ID: 925 5950 5314
Passcode: 418727
11:00am – 12:00pm Seminar & Discussion
RSVP Here
ABSTRACT
Tumor molecular profiling is a fundamental component of precision oncology, enabling the identification of oncogenomic mutations that can be targeted therapeutically. To accelerate enrollment to clinical trials of molecularly targeted agents and guide treatment selection, we have established a center-wide, prospective clinical sequencing program at Memorial Sloan Kettering Cancer Center using a custom, paired tumor-blood normal sequencing assay (MSK-IMPACT), which we have used to profile more than 50,000 patients with solid tumors. Yet beyond just the characterization of tumor-specific alterations, the inclusion of blood DNA has readily enabled the identification of germline risk alleles and somatic mutations associated with clonal hematopoiesis. To complement this approach, we have also implemented a ‘liquid biopsy’ cfDNA panel (MSK-ACCESS) for cancer detection, surveillance, and treatment selection and monitoring. In my talk, I will describe the prevalence of somatic and germline genomic alterations in a real-world population, the clinical benefits of cfDNA assessment, and how clonal hematopoiesis can inform cancer risk and confound liquid biopsy approaches to cancer detection.
ABOUT
Michael Berger, PhD, holds the Elizabeth and Felix Rohatyn Chair and is Associate Director of the Marie-Josée and Henry R. Kravis Center for Molecular Oncology at Memorial Sloan Kettering Cancer Center, a multidisciplinary initiative to promote precision oncology through genomic analysis to guide the diagnosis and treatment of cancer patients. He is also an Associate Attending Geneticist in the Department of Pathology with expertise in cancer genomics, computational biology, and high-throughput DNA sequencing technology. His laboratory is developing experimental and computational methods to characterize the genetic makeup of individual cancers and identify genomic biomarkers of drug response and resistance. As Scientific Director of Clinical NGS in the Molecular Diagnostics Service, he oversees the development and bioinformatics associated with clinical sequencing assays, and he helped lead the development and implementation of MSK-IMPACT, a comprehensive FDA-authorized tumor sequencing panel that been used to profile more than 60,000 tumors from advanced cancer patients at MSK. The resulting data have enabled the characterization of somatic and germline biomarkers across many cancer types and the identification of mutations associated with clonal hematopoiesis. Dr. Berger also led the development of a clinically validated plasma cell-free DNA assay, MSK-ACCESS, which his laboratory is using to explore tumor evolution, acquired drug resistance, and occult metastatic disease. He received his Bachelor’s Degree in Physics from Princeton University and his Ph.D. in Biophysics from Harvard University.
Hosted by: Utkan Demirci, Ph.D.
Sponsored by: The Canary Center & the Department of Radiology
Stanford University – School of Medicine
Radiology Department-Wide Research Meeting
• Research Announcements
• Mirabela Rusu, PhD – Learning MRI Signatures of Aggressive Prostate Cancer: Bridging the Gap between Digital Pathologists and Digital Radiologists
• Akshay Chaudhari, PhD – Data-Efficient Machine Learning for Medical Imaging
Location: Zoom – Details can be found here: https://radresearch.stanford.edu
Meetings will be the 3rd Friday of each month.
Hosted by: Kawin Setsompop, PhD
Sponsored by: the the Department of Radiology
CEDSS: The First Cell: A new model for cancer research and treatment
Azra Raza, M.D.
Chan Soon-Shiong Professor of Medicine
Director, Myelodysplastic Syndrome Center
Columbia University Medical Center
Location: Zoom
Meeting URL: https://stanford.zoom.us/s/99340345860
Dial: US: +1 650 724 9799 or +1 833 302 1536 (Toll Free)
Meeting ID: 993 4034 5860
Passcode: 711508
ABSTRACT
Cancer research continues to be predicated on a 1970’s model of research and treatment. Despite half a century of intense research, we are failing spectacularly to improve the outcome for patients with advanced disease. Those who are cured continue to be treated mostly with the older strategies (surgery-chemo-radiation). Our contention is that the real solution to the cancer problem is to diagnose cancer early, at the stage of The First Cell. The rapidly evolving technologies are doing much in this area but need to be expanded. We study a pre-leukemic condition called myelodysplastic syndrome (MDS) with the hope that we can detect the first leukemia cells as the disease transforms to acute myeloid leukemia (AML). Towards this end, we have collected blood and bone marrow samples on MDS and AML patients since 1984. Today, our Tissue Repository has more than 60,000 samples. We propose novel methods to identify surrogate markers that can identify the First Cell through studying the serial samples of patients who evolve from MDS to AML.
ABOUT
Dr. Raza is a Professor of Medicine and Director of the MDS Center at Columbia University in New York, NY.She started her research in Myelodisplastic Syndromes (MDS) in 1982 and moved to Rush University, Chicago, Illinois in 1992, where she was the Charles Arthur Weaver Professor in Oncology and Director, Division of Myeloid Diseases. The MDS Program, along with a Tissue Repository containing more than 50,000 samples from MDS and acute leukemia patients was successfully relocated to the University of Massachusetts in 2004 and to Columbia University in 2010.
Before moving to New York, Dr. Raza was the Chief of Hematology Oncology and the Gladys Smith Martin Professor of Oncology at the University of Massachussetts in Worcester. She has published the results of her laboratory research and clinical trials in prestigious, peer reviewed journals such as The New England Journal of Medicine, Nature, Blood, Cancer, Cancer Research, British Journal of Hematology, Leukemia, and Leukemia Research. Dr. Raza serves on numerous national and international panels as a reviewer, consultant and advisor and is the recipient of a number of awards.
Hosted by: Utkan Demirci, Ph.D.
Sponsored by: The Canary Center & the Department of Radiology
Stanford University – School of Medicine
Roxana Daneshjou, MD, PhD
Assistant Professor, Biomedical Data Science & Dermatology
Assistant Director, Center of Excellence for Precision Heath & Pharmacogenomics
Director of Informatics, Stanford Skin Innovation and Interventional Research Group
Stanford University
Title: Building Fair and Trustworthy AI for Healthcare
Abstract: AI for healthcare has the potential to revolutionize how we practice medicine. However, to do this in a fair and trustworthy manner requires special attention to how AI models work and their potential biases. In this talk, I will cover the considerations for building AI systems that improve healthcare.
Mildred Cho, PhD
Professor of Pediatrics, Center of Biomedical Ethics
Professor of Medicine, Primary Care and Population Health
Stanford University
Title: Facilitating Patient and Clinician Value Considerations into AI for Precision Medicine
Abstract:
For the development of ethical machine learning (ML) for precision medicine, it is essential to understand how values play into the decision-making process of developers. We conducted five group design exercises with four developer participants each (N=20) who were asked to discuss and record their design considerations in a series of three hypothetical scenarios involving the design of a tool to predict progression to diabetes. In each group, the scenario was first presented as a research project, then as development of a clinical tool for a health care system, and finally as development of a clinical tool for their own health care system. Throughout, developers documented their process considerations using a virtual collaborative whiteboard platform. Our results suggest that developers more often considered client or user perspectives after changing the context of the scenario from research to a tool for a large healthcare setting. Furthermore, developers were more likely to express concerns arising from the patient perspective and societal and ethical issues such as protection of privacy after imagining themselves as patients in the health care system. Qualitative and quantitative data analysis also revealed that developers made reflective/reflexive statements more often in the third round of the design activity (44 times) than in the first (2) or second (6) rounds. These statements included statements on how the activity connected to their real-life work, what they could take away from the exercises and integrate into actual practice, and commentary on being patients within a health care system using AI. These findings suggest that ML developers can be encouraged to link the consequences of their actions to design choices by encouraging “empathy work” that directs them to take perspectives of specific stakeholder groups. This research could inform the creation of educational resources and exercises for developers to better align daily practices with stakeholder values and ethical ML design.