Uwe M. Martens

Personalized treatment for colorectal cancer: novel developments and putative therapeutic strategies

BackgroundColorectal cancer (CRC) is the third most common cancer diagnosed worldwide and continues to be a major healthcare concern. Molecular heterogeneity of CRC is believed to be one of the main factors responsible for the considerable variability in treatment response. With the recent development of powerful genomic technologies, novel insights in tumor biology of CRC have now been provided, facilitating the recognition of new molecular subtypes with prognostic and predictive implications.PurposeThe purpose of this review article is to summarize current knowledge about genomic, epigenomic, and proteomic characteristics of CRC, as well as their implications for biomarker identification and individualized targeted therapy.ConclusionSupplementing the findings from several previous studies, the Cancer Genome Atlas (TCGA) project recently finalized the systematic characterization of CRC resulting in the first tumor dataset with complete molecular measurements at DNA, RNA, and protein levels. The challenge now is to translate these findings into a robust and reproducible CRC classification system linking molecular features of the tumor to precision medicine.

A method for using real world data in breast cancer modeling

OBJECTIVESnToday, hospitals and other health care-related institutions are accumulating a growing bulk of real world clinical data. Such data offer new possibilities for the generation of disease models for the health economic evaluation. In this article, we propose a new approach to leverage cancer registry data for the development of Markov models. Records of breast cancer patients from a clinical cancer registry were used to construct a real world data driven disease model.nnnMETHODSnWe describe a model generation process which maps database structures to disease state definitions based on medical expert knowledge. Software was programmed in Java to automatically derive a model structure and transition probabilities. We illustrate our method with the reconstruction of a published breast cancer reference model derived primarily from clinical study data. In doing so, we exported longitudinal patient data from a clinical cancer registry covering eight years. The patient cohort (n=892) comprised HER2-positive and HER2-negative women treated with or without Trastuzumab.nnnRESULTSnThe models generated with this method for the respective patient cohorts were comparable to the reference model in their structure and treatment effects. However, our computed disease models reflect a more detailed picture of the transition probabilities, especially for disease free survival and recurrence.nnnCONCLUSIONSnOur work presents an approach to extract Markov models semi-automatically using real world data from a clinical cancer registry. Health care decision makers may benefit from more realistic disease models to improve health care-related planning and actions based on their own data.

Transition probabilities of HER2-positive and HER2-negative breast cancer patients treated with Trastuzumab obtained from a clinical cancer registry dataset.

Records of female breast cancer patients were selected from a clinical cancer registry and separated into three cohorts according to HER2-status (human epidermal growth factor receptor 2) and treatment with or without Trastuzumab (a humanized monoclonal antibody). Propensity score matching was used to balance the cohorts. Afterwards, documented information about disease events (recurrence of cancer, metastases, remission of local/regional recurrences, remission of metastases and death) found in the dataset was leveraged to calculate the annual transition probabilities for every cohort.

Implementierung eines IT-gestützten molekularen Tumorboards in der Regelversorgung

ZusammenfassungNGS-basierte Sequenzierungsverfahren, die die Bestimmung des individuellen Mutationsprofils eines Tumors ermöglichen, haben im vergangenen Jahrzehnt zu einem Paradigmenwechsel in der Onkologie geführt. Allerdings stellen die versorgungsgerechte Interpretation der molekularen Befunde und die darauf basierende Therapieentscheidung in der Regelversorgung aktuell noch eine beträchtliche zeitliche und personelle Herausforderung dar. Der Implementierung eines molekularen Tumorboards kommt deshalb eine zentrale Bedeutung zu. Die prozessorientierte Informations- und Kommunikationsplattform VITU (Virtuelles Tumorboard) unterstützt dessen Planung und Durchführung, indem es die ortsunabhängige, standardisierte Vernetzung von Experten ermöglicht und Tools für die Datenanalyse bereithält. Durch die strukturierte Speicherung im FHIR-Format werden die Behandlungsdaten auch für die wissensgenerierende Patientenversorgung und Forschung zugänglich gemacht.AbstractIn the last decade, next generation sequencing (NGS)-based technologies have led to axa0paradigm shift in oncology by enabling the identification of individual tumor mutation profiles; however, in the routine setting the patient-centered interpretation of the molecular genetic findings leading to stratified treatment decisions represents axa0considerable temporal and personnel challenge. The implementation of axa0molecular tumor board is therefore of central importance. The process-oriented information and communication platform virtual tumor board (VITU) supports its organization and realization by enabling axa0location-independent, standardized networking of experts and by providing data analysis tools. Due to structured storage of the treatment data in the fast healthcare interoperability resources (FHIR) format, they are also made available for knowledge-generating patient care and research.

Larotrectinib (LOXO-101)

One of the most challenging issues in oncology research and treatment is identifying oncogenic drivers within an individual patients tumor which can be directly targeted by a clinically available therapeutic drug. In this context, gene fusions as one important example of genetic aberrations leading to carcinogenesis follow the widely accepted concept that cell growth and proliferation are driven by the accomplished fusion (usually involving former proto-oncogenes) and may therefore be successfully inhibited by substances directed against the fusion. This concept has already been established with oncogenic gene fusions like BCR-ABL in chronic myelogenous leukemia (CML) or anaplastic lymphoma kinase (ALK) in lung cancer, including special tyrosine kinase inhibitors (TKIs) which are able to block the activation of the depending downstream proliferation pathways and, consequently, tumor growth. During the last decade, the NTRK1, 2, and 3 genes, encoding the TRKA, B, and C proteins, have attracted increasing attention as another significant and targetable gene fusion in a variety of cancers. Several TRK inhibitors have been developed, and one of them, Larotrectinib (formerly known as LOXO-101), represents an orally available, selective inhibitor of the TRK receptor family that has already shown substantial clinical benefit in both pediatric and adult patients harboring an NTRK gene fusion over the last few years.