Cancer Systems Biology

Ravi Salgia, MD, PhD, is the Arthur and Rosalie Kaplan Chair in Medical Oncology at City of Hope National Medical Centre. Previously, he was Professor of Medicine at the University of Chicago. Prior to his tenure at the University of Chicago, Dr. Salgia was faculty at the Dana-Farber Cancer Institute and Harvard Medical School. He earned his undergraduate summa cum laude in mathematics, biology, and chemistry, and then his MD and PhD degrees from Loyola University in Chicago. His research interests focus on novel therapeutics against lung cancer, and he also maintains a strong interest in chaos theory and fractals and their application to cancer, especially lung cancer. Dr. Salgia has been honoured with numerous awards, including the ASCO Excellence in Teaching Award.Prof. Mohit Kumar Jolly earned his Bachelors and Masters degree from IIT Kanpur and PhD from Rice University, all in Bioengineering. Before moving to Indian Institute of Science (IISc), Bangalore to start his independent group in 2018, he was a Gulf Coast Consortia Postdoctoral Fellow in Computational Cancer Biology. His research interests are in phenotypic plasticity and heterogeneity driving cancer metastasis and drug resistance. He is the current Editor-in-Chief of NPJ Systems Biology & Applications. He received 2022 Young Alumnus Award of IIT Kanpur, 2023 ICTP Prize, and 2024 Young Outstanding Engineering Alumnus Award, Rice University.Prof. Prakash Kulkarni received his PhD in biochemistry from India and did postdoctoral training at the Indian Institute of Science, and New York University. He was an Assistant Professor at Johns Hopkins. Subsequently, he was Associate Professor at the Keck Laboratory for Structural Biology, University of Maryland. Previously, Prof. Kulkarni held Staff Scientist positions in Chemistry & Chemical Engineering, and Biology & Biological Engineering at Caltech, and in Genetics at Yale. His research interests are focused on understanding how protein conformational dynamics contributes to phenotypic switching, especially in evolution of multicellularity, cancer, and in non-genetic heterogeneity. He is a Fellow of the Royal Society of Biology, UK.Prof. Govindan Rangarajan obtained an Integrated MSc (Hons) degree from the Birla Institute of Technology and Science, Pilani, and a PhD from the University of Maryland, College Park, USA. He then worked at the Lawrence Berkeley Lab, University of California, Berkeley, before returning to India in 1992. He has been a faculty member of the Department of Mathematics, Indian Institute of Science (IISc), since 1992. He is currently the Director of IISc.Prof. Rangarajan's research interests include nonlinear dynamics and chaos and time series analysis. He is a JC Bose National Fellow. He is also a Fellow of the Indian Academy of Sciences and the National Academy of Sciences, India. He was awarded the Chevalier dans l'Ordre des Palmes Academiques (Knight of the Order of Academic Palms) by the Government of France. He was also a Homi Bhabha Fellow.

• Section 1 - Cancer systems biology: An overview1: Sui Huang: The necessary existence of cancer and its progression from first principles of cell state dynamics2: Vera Pancaldi and Jean- Pascal Capp: Non- genetic intratumoral heterogeneity and phenotypic plasticity as consequences of microenvironment- driven epigenomic dysregulation3: Caterina A.M. La Porta and Stefano Zapperi: Dimensions of cellular plasticity: EpithelialDS mesenchymal transition, cancer stem cells, and collective cell migration4: Divyjoy Singh, Abhay Gupta, Mohit Kumar Jolly, and Prakash Kulkarni: Phenotypic switching in cancer: A systems- level perspective5: Biplab Bose: Morphological state transition during epithelialDS mesenchymal transitionSection 2 - Cancer systems biology: New paradigms6: Laurie Graves, Ayalur Raghu Subbalakshmi, William C. Eward, Mohit Kumar Jolly, and Jason A. Somarelli: Evolution- informed multilayer networks: Overlaying comparative evolutionary genomics with systems- level analyses for cancer drug discovery7: Jintong Lang, Chunhe Li, and Jinzhi Lei: Landscape of cell- fate decisions in cancer cell plasticity8: Arnab Barua and Haralampos Hatzikirou: The road to cancer and back: A thermodynamic point of view9: Paromita Mitra, Uday Saha, Subhashis Ghosh, and Sandeep Singh: Cellular plasticity as emerging target against dynamic complexity in cancer10: Vishaka Gopalan, Sidhartha Goyal, and Sumaiyah Rehman: Modeling phenotypic heterogeneity and cell- state transitions during cancer progressionSection 3 - Single cell 'omics' analysis11: Benedict Anchang and Loukia G. Karacosta: Decoding drug resistance at a single- cell level using systems- level approaches12: Manu Setty: Computational methods to infer lineage decision- making in cancer using single-cell data13: Jianhua Xing and Weikang Wang: Analyzing cancer cell- state transition dynamics through live- cell imaging and high- dimensional single-cell trajectory analyses14: Syeda Subia Ahmed, Danielle Pi, Nicholas Bodkin, Vito W. Rebecca, and Yogesh Goyal: Emerging single- cell technologies and concepts to trace cancer progression and drug resistanceSection 4 - Computational approaches to drug development15: Supriyo Bhattacharya: Navigating protein dynamics: Bridging the gap with deep learning and machine intelligence16: Vitor B.P. Leite, Murilo N. Sanches, and Rafael G. Viegas: Cancer- related intrinsically disordered proteins: Functional insights from energy landscape analysis17: Priyanka Prakash: Targeting RASSection 5 - Statistical methods and data mining, machine learning, artificial intelligence, and cloud computing18: Brandi N. Davis- Dusenbery, Cera R. Fisher, Rowan Beck, and Zelia F. Worman: The power of connectionDLenabling collaborative, multimodal data analysis at petabyte scale to advance understanding of oncology19: Colton Ladbury and Arya Amini: Interpretation of machine learning models in cancer: The role of model- agnostic explainable artificial intelligence20: Jay G. Ronquillo: Applying cloud computing and informatics in cancer21: Luciane T. Kagohara and Joseph Tandurella: Single-cell sequencing analysis focused on cancer immunotherapy22: Arnulf Stenzl, Jenny Ghith, and Bob J.A. Schijvenaars: Application of artificial intelligence to overcome clinical information overload in cancer23: Xiwei Wu and Supriyo Bhattacharya: Application of artificial intelligence in cancer genomicsSection 6 - Biomechanics24: Madhurima Sarkar, Asadullah, and Shamik Sen: A role for mechanical heterogeneity in the tumor microenvironment in driving cancer cell invasion25: Christina R. Dollahon, Ting- Ching Wang, Srinikhil S. Vemuri, Suchitaa Sawhney, and Tanmay P. Lele: Adaptation of cancer cells to altered stiffness of the extra-cellular matrix26: Ajay Tijore, Alka Kumari, and Abhishek Goswami: Decoding mechano- oncology principles through microfluidic devices and biomaterial platforms27: Yasir Suhail, Wenqiang Du, Günter Wagner, and Kshitiz: Understanding contribution of fibroblasts in inception of cancer metastasis from an evolutionary perspective28: Medhavi Vishwakarma and Amrapali Datta: Cell competition in tumorigenesis and epithelial defense against cancerSection 7 - Translational mathematical oncology29: Philipp M. Altrock, Guranda Chitadze, Arne Traulsen, and Frederick L. Locke: Modelling cell population dynamics during chimeric antigen receptor T- cell therapy30: Srisairam Achuthan, Rishov Chatterjee, and Atish Mohanty: Modeling small cell lung cancer biology through deterministic and stochastic mathematical models31: Jasmine Foo and Einar Bjarki Gunnarsson: Mathematical models of resistance evolution under continuous and pulsed anti- cancer therapies32: Mohammad Kohandel, Cameron Meaney, and Dorsa Mohammadrezaei: Integrating in silico models with ex vivo data for designing better combinatorial therapies in cancer33: Annice Najafi and Jason George: Tumour- immune co- evolution dynamics and it's impact on immuno- therapy optimization34: Maria Jose Peláez, Shreya Goel, Vittorio Cristini, Zhihui Wang, and Prashant Dogra: Mechanistic modelling and machine learning to establish structureDS activity relationship of nanomaterials for improved tumour deliverySection 8 - Ecology, evolution, and cancer35: Rowan Barker- Clarke, Eshan S. King, Jeff Maltas, J. Arvid Ågren, Dagim Tadele, and Jacob G. Scott: Decoding cancer evolution through adaptive fitness landscapes36: Andriy Marusyk: A case against causal reductionism in acquired therapy resistance37: Ravi Salgia, Supriyo Bhattacharya, Atish Mohanty, and Govindan Rangarajan: Group behaviour and drug resistance in cancer38: Jeffrey West, Jill Gallaher, Maximilian A.R. Strobl, Mark Robertson- Tessi, and Alexander R.A. Anderson: The Fundamentals of evolutionary therapy in cancerSection 9 - Critical transitions and chaos in cancer39: Smita Deb, Subhendu Bhandary, Mohit Kumar Jolly, and Partha Sharathi Dutta: Methods for identifying critical transitions during cancer progression40: Abicumaran Uthamacumaran: Chaos and complexity: Hallmarks of cancer progression41: Andrzej Kasperski and Henry H. Heng: Cancer formation as creation and penetration of unknown life spaces