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Abstracts Life Science Technologies Day (LST) 2018

Abstracts from invited speakers for Life Science Technology Day 2018. Key note speakers are Chris Sander, Harvard University, Boston and Ilya Shmulevich, Institute for Systems Biology, Seattle. Speakers from KTH Royal Institute of Technology are Amelie Eriksson Karlström, Jerker Widengren,
Mats Danielsson,Wouter van Der Wijngaart and Adil Mardinoglu.

Abstracts

Pathway Landscape of the Cancer Genome Atlas and the Design of Combination Therapy

Chris Sander , Dana-Farber Cancer Institute and Harvard Medical School, Boston

(1) Pathway Landscape of the Cancer Genome Atlas. Genetic alterations in signaling pathways that control cell-cycle progression, apoptosis, and cell growth are common hallmarks of cancer, but the extent, mechanisms, and co-occurrence of alterations in these pathways differ between individual tumors and tumor types. Using mutations, copy-number changes, mRNA expression, gene fusions and DNA methylation in 9,125 tumors profiled by The Cancer Genome Atlas (TCGA), we analyzed the mechanisms and patterns of somatic alterations in ten canonical pathways: cell cycle, Hippo, Myc, Notch, Nrf2, PI-3- Kinase/Akt, RTK-RAS, TGFb signaling, p53 and b-catenin/Wnt. We charted the detailed landscape of pathway alterations in 33 cancer types, stratified into 64 subtypes, and identified patterns of co-occurrence and mutual exclusivity. Eighty-nine percent of tumors had at least one driver alteration in these pathways, and 57% percent of tumors had at least one alteration potentially targetable by currently available drugs. Thirty percent of tumors had multiple targetable alterations, indicating numerous opportunities for combination therapy to be explored in pre-clinical and clinical work.

(2) Perturbation Biology for Combination Therapy. Cells and organisms have evolved as robust to external perturbations and adaptive to changing conditions. This capacity poses severe problems for cancer patients. Some targeted anti-cancer drugs work remarkably well, yet resistance is almost certain to emerge. We use data-driven perturbation biology that combines experiment (systematic perturbation coupled with rich observation of molecular and cellular response) and computation (machine learning derived executable network models for cancer cells) to design anti-cancer combination therapy.
 

Radionuclide therapy using peptide nucleic acid (PNA)-mediated pretargeting of HER2-expressing tumors

Amelie Eriksson Karlström , KTH

In vivo pretargeting is a promising approach to reduce side effects during treatment with radiolabeled tumor-targeting antibodies or alternative scaffold proteins, such as affibody molecules. We have developed a concept where the tumor-targeting agent is conjugated to a peptide nucleic acid (PNA) strand, which binds with high affinity to a radiolabeled, complementary PNA strand. Pretargeting is a two-step procedure, where the primary agent is administered first, and the secondary agent is administered after the primary agent has accumulated in the tumor and cleared from non-tumor tissue. A proof-of-concept pretargeting study in mice carrying xenografted human HER2-expressing tumors demonstrated improved median survival for mice treated with an affibody-PNA conjugate and a 177Lu-labeled PNA probe. We have also applied the same PNA-based pretargeting system to tumor targeting with the monoclonal antibody trastuzumab and could demonstrate clear visualization of HER2-expressing tumors.
 

Fluorescence fluctuation and super-resolution techniques and their possible role in cellular and molecular cancer diagnostics

Jerker Widengren , KTH

Highly sensitive fluorescence readouts, such as microscopy and flow cytometry, are widely used in cancer diagnostics. Yet, there is more, currently un-exploited, diagnostic information to be retrieved from fluorescence readouts. Along this line, we have developed two new strategies applicable for cancer diagnostics; Fluorescence blinking can reflect local metabolic and environmental conditions, and by imaging this blinking, cells with cancer-specific metabolism can be distinguished. Further, we have shown that protein distribution patterns within cells, resolved by super-resolution imaging, can provide new diagnostic parameters and insights into underlying disease mechanisms. http://www.biomolphysics.kth.se

MedTEchLabs

Mats Danielsson , KTH

MedTechLabs is a new, long term, initiative by the Stockholm City Council, KTH and the Karolinska Institute. The goal is to enable a world class research environment in biomedical engineering in Stockholm by providing lab areas and by funding recruitment of young faculty with high potential. At the same time MedTechLabs will provide courses for implementation of research results that will have an immediate impact on patient outcomes. The first focus area is medical imaging and minimal invasive techniques and we will present some examples of ongoing research in this field.

Micro- and nano devices for cancer diagnostics and therapeutics

Wouter Metsola van Der Wijngaart , KTH

The field of micro- and nanosystem technology is increasingly focusing on the integration of small scale synthetic systems with biological entities. The presentation will provide examples of recent research in this area at the KTH micro- and nanosystems department. Examples include therapeutic nanoparticle synthesis, therapeutic cell microencapsulation, and lab-on-a-chip biomarker detection.
 

A pathology atlas of the human cancer transcriptome and its use in patient stratification

Adil Mardinoglu , KTH

There is great interest in understanding the underlying molecular mechanisms involved in the pathogenesis and progression of individual tumors. We used systems-level approaches to analyze the genome-wide transcriptome of 17 major cancer types with respect to clinical outcome. A general pattern emerged, with shorter patient survival associated with up-regulation of genes involved in cell growth and down-regulation of genes involved in cellular differentiation. All data are presented in an interactive open-access database (www.proteinatlas.org). Using genome-scale metabolic models, we show that cancer patients have widespread metabolic heterogeneity, highlighting the need for precise and personalized medicine for cancer treatment. Next, we used harvested information in stratification of liver cancer patients. Our integrative analysis highlighted mechanistic differences among tumors and identified a novel survival signature and potential subgroup-specific therapeutic targets for liver cancer treatment.
https://sysmedicine.com/
 

The Immune Landscape of Cancer

Ilya Shmulevich , Institute for Systems Biology , Seattle

I will present the results of an extensive immunogenomic analysis of more than 10,000 tumors, comprising 33 diverse cancer types by utilizing data compiled by The Cancer Genome Atlas. The analysis identified six immune subtypes that encompass multiple cancer types and are hypothesized to define immune response patterns impacting prognosis. Across these immune subtypes, we identified and characterized multiple control modalities of the intracellular and extracellular networks (transcription, microRNAs, copy number, and epigenetic processes) that are involved in tumor-immune cell interactions. I will describe the companion web portal, CRI iAtlas, which allows for interactive exploration of the analyses and data and serves as a resource for future targeted studies to further advance the immuno-oncology field. I will also briefly describe the ISB Cancer Genomics Cloud (ISB-CGC) resource and how it was used to perform very large scale immunogenomic analyses.