Precision medicine in Cancer Care

By Lucia Cavelier, Uppsala University, SciLifeLab and Department of Immunology, Genetics and Pathology, Gunilla Enblad, Uppsala University, Department of Immunology, Genetics and Pathology, Deborah Mascalzoni, Uppsala University, Centre for Research Ethics & Bioethics, Aristidis Moustakas, Uppsala University, Department of Medical Biochemistry and Microbiology, Johan Rung, Uppsala University, SciLifeLab and Department of Immunology, Genetics and Pathology, Carolina Wählby, Uppsala University, SciLifeLab and Department of Information Technology

Precision Medicine
Photo Credits: Preaetorianphoto

Precision medicine aims at “matching the proper medical treatment to the right patient”. Cancer perfectly exemplifies the modern trend of precision medicine because, even within a single patient’s body, tumours may exhibit diverse properties that often complicate efficient treatment. A simple question presented to a cancer patient today: “What is your expectation of your oncology clinic?” is often met with this honest reply: “Take a sample from my tumour (or even better from my blood), test it for the best possible drug and get back to me with that drug as fast as possible”! Simultaneously, a second question is often asked: “May we take all the data we collect from you and share it world-wide, so that treatment of future patients may be improved?” This down-to-earth conversation captures the deeper challenge that precision medicine in cancer faces today. In short, personalized medicine can be summarized in concrete action points: match the right treatment with the right patient, minimize side-effects of compounds and enable the caring community to improve the design of new treatments and drugs.

The aims of the workshop

Genomic medicine (or tumour classification based on digital image analysis) generates large data-sets containing sensitive information. To provide standardized and optimized decision algorithms in real-time to the treating doctor, genetic profiles are ideally correlated to cancer phenotypes, such as digital tumour images, disease and treatment outcomes and other informative clinical parameters. Generating national/international knowledge networks requires the sharing of data between collaborating hospitals, treating clinicians, academic researchers and industrial partners. Implementation of existing regulations covering legal aspects, security and protection of patient data and ethical standards is a key aspect in the formation and function of such networks. Today, international consortia such as the Global Alliance for Genomics and Health work to address many of such challenges through standards, tools, and policies. However, their implementation into national healthcare is not straightforward.

The workshop aims at:

  1. Generating a checklist for a critical minimum of the types of data that should be stored and shared, in order to facilitate their use to tailor the decision toward best treatment in real-time and for future developments.
  2. Identifying major legal and ethical obstacles currently limiting data sharing, and then clarifying how these can be overcome in order to implement the necessary changes in national healthcare systems. Precision medicine can then become a part of routine cancer care and stimulate the development of new therapies and diagnostics.

Precision medicine: a paradigm shift in how we treat cancer

By analysing individual patient susceptibility to cancer development and sensitivity or resistance to therapy, modern genomic sciences rapidly screen the genome of tumours in an individual, identify genetic alterations, and classify this individual using national/international databases and algorithms of cancer type and subtype. The power of modern DNA sequencing is based on high accuracy and rapid delivery of results. The technology is robotized, costs have decreased and the speed of data analysis has picked up. The challenges associated with the need to process large sample numbers at once mean that traditional research laboratories, or oncology clinics, are lagging behind in both infrastructure and IT-capacity.

As new technologies evolve rapidly, their implementation presents challenges that must be dealt with. These include managerial aspects of handling the large amount of data generated, the means by which the information circulates between oncologists and patients and through national/international databases. The shift in clinical practice, needed to support the application of precision medicine, poses ethical and financial problems. Strong computational coupling of all players in the care provision chain is necessary and this requires the implementation of all the relevant technological developments. Effective use of such computational coupling needs to become part of the simple “daily practice” of the modern oncology department.

New competencies needed in healthcare

The interpreter of the precision technology data in the oncology department is ultimately the clinician; who is now asked to collaborate with specialists performing the sophisticated IT-based analyses and yet continue to deliver traditional, simple and concrete diagnostic or consulting services to their patients. In other words, the precision medicine revolution will succeed only when new tools of operation become widespread and routine, and this obviously will involve a new generation of medical professionals who are familiar with both medical and IT language. We may see new workflows where data processing and management require a lot more attention than today, and new structures for the clinical workforce, with bioinformaticians in more prominent roles, bridging the gap between medical professionals and IT experts.

Concrete examples of how today’s oncology departments are reorganizing to face the precision medicine evolution can be found in new national initiatives. For example, Genomics England Ltd and Genomic Medicine Sweden are building the infrastructure and communication lines discussed above. Multinational operations, supported by the European Union, coordinate several major oncology departments, with the aim to implement the new models of multicentre identity that facilitate communication, data sharing and effectiveness in patient treatment based on the most up-to-date technological advances. A top example is Cancer Core Europe, a consortium of six Comprehensive Cancer Centres.

Precision Medicine
Precision Medicine demands implementation at a global level via cooperation and
open communication between the patient-oncologist unit, the precision research units, the IT security
expert panels and the international legal unit. A current challenge in such implementation maximizing efficiency in the overlaps and communication between these principal actors.

Strategic aspects of infrastructure development

To understand how the biology of an individual affects their medical state, we need reference data with as much detail as possible about the biological variation between humans, and the associated manifestations of cancer. Ideally, we need longitudinal data, with the medical history and observed medical data before and after different treatments, for patients with different genetic setups. The more detail we have in our reference data, the better we will be able to interpret new medical data from an individual and predict optimal treatment. Therefore, to reach the impact promised by precision medicine, we need to enable the collection and integration of medical and biological data across borders, through the responsible sharing of data between researchers and clinicians. To drive innovation in diagnostics and therapy, it is also important to enable data sharing with industry. Major pharmaceutical actors are today pro-active in expanding their precision medicine initiatives. While industrial use of the advancements in precision oncology for developing more efficient diagnostics and treatments is a positive thing, uncertainties remain concerning the conditions for access to genomic data.

At the same time, the integrity and privacy rights of the patient have to be safeguarded, and informed consent for data use has to be given or revoked by the patient clearly and unambiguously. Such stringent information handling, and the secure storage, transfer and archiving of patient data all require new IT infrastructures and processes that may be far from what are available today in hospitals around the world. A legal framework of agreements and contracts between organizations, regulating data sharing and management, must be implemented.

Implementing precision medicine in cancer care, meeting the challenges of complex data and strategies for data sharing

The clinical interpretation necessary for cancer care must link the molecular characteristics of an individual patient with data from many other patients, ideally in real-time. Although current clinical practice takes into account only a few actionable genetic markers in reaching clinical decisions, the future challenge is to be able to integrate the correlations between molecular phenotypes and clinical outcomes into decision-making. As more complex analysis inevitably develops, incorporating whole genome/transcriptome information into cancer risk prediction, there will be a growing need for more unbiased processing of large data-sets.

The current practice and immediate future plan is the expansion of large data depositories in super-computer hubs nationally and internationally. Communication and sharing of data between these hubs is of utmost importance. This is easy to state but not so easy to achieve when one considers: a) the perspective of the oncologist needing to access multiple databases; b) the cancer patient wanting to access their own data and protect them legally from unnecessary use or even unanticipated cyber-threats; c) the organized health system wishing to generate informed statistical and policy-driving analyses to inform the general public; and d) the pharmaceutical industry wanting to generate new therapy protocols based on the data.

When it comes to genomic data, the patient is the legal owner according to established international regulations. The same regulations apply to academic and industrial research units. In Europe, the General Data Protection Regulation (GDPR) gives member countries a unified legal framework and regulates data sharing with non-EU countries. GDPR does not allow data sharing with such countries unless their data protection laws are considered strong enough. For example, the Privacy Shield program registers US organizations deemed to fulfil these data protection criteria set by the EU.

The ongoing centralization of legal authorities and organizations that govern the deposition and sharing of large data-sets needs to coincide with the training of new experts who can work at the interface of law, IT and research, in order for the desired goal of data sharing and internationalized communication to be applied effectively at every oncology department.

Precision medicine – a technology for all?


The challenge of oncology for children also transcends the technological world: far fewer tumour tissue samples are available which necessitates the use of international biobanks. National approaches, such as Genomics England Ltd and Genomic Medicine Sweden, offer concrete proposals on this front.

Some global dilemmas

•   As long as we collect data and tumour tissue from a mainly western/northern population, our knowledge data library will not cover the cancer diseases that are common in low- and middle-income countries (LMIC).

•   Identifying ways of sharing data and collaborating on data analysis is critical for also opening up the opportunities in precision medicine for cancer patients in LMIC, as the establishment of necessary infrastructures will take time to develop in a sustainable way.

•   We cannot expect all regions to be ready to take the step into precision medicine before there is a legislative and regulatory infrastructure in place that can provide surveillance and protect patient integrity.

This new world in precision oncology aspires to guarantee a much higher security level and a better service level for the patient: the cornerstones of data generation within this field. This workshop intends to map out the opportunities for and obstacles against achieving this on a global scale.

Digital Image Processing
Digital image processing makes it possible to combine markers for protein expression in stomach cancer, and the resulting image information can function as input to an AI system for recognizing pathologies.


Jaffee EM, Dang CV, Agus DB, Alexander BM, Anderson KC, Ashworth A, Barker AD, Bastani R, Bhatia S, Bluestone JA, Brawley O, Butte AJ, Coit DG, Davidson NE, Davis M, DePinho RA, Diasio RB, Draetta G, Frazier AL, Futreal A, Gambhir SS, Ganz PA, Garraway L, Gerson S, Gupta S, Heath J, Hoffman RI, Hudis C, Hughes-Halbert C, Ibrahim R, Jadvar H, Kavanagh B, Kittles R, Le QT, Lippman SM, Mankoff D, Mardis ER, Mayer DK, McMasters K, Meropol NJ, Mitchell B, Naredi P, Ornish D, Pawlik TM, Peppercorn J, Pomper MG, Raghavan D, Ritchie C, Schwarz SW,  Sullivan R, Wahl R, Wolchok JD, Wong SL, Yung A. Future cancer research priorities in the USA: A Lancet Oncology Commission. Lancet Oncol. 2017;18(11):e653-e706.

Moscow JA, Fojo T, Schilsky RL. The evidence framework for precision cancer medicine. Nat Rev Clin Oncol. 2018 Mar; 15(3):183-192.

Korngiebel DM, Thummel KE, Burke W. Implementing Precision Medicine: The Ethical Challenges. Trends Pharmacol Sci. 2017; 38(1):8-14.


[1] Cambridge Cancer Centre, the German Cancer Research Centre (DKFZ) and the National Centre for Tumour Diseases (NCT) in Heidelberg, the Val d’Hebron Institute of Oncology in Barcelona, the Karolinska Institute in Stockholm, Gustave Roussy Cancer Campus Grand Paris, and the National Cancer Institute (NKI) in Amsterdam.