RESUMEN
Biomarker-stratified cancer pharmacotherapy was pioneered in the care of breast cancer patients. The utility of agents modulating hormone receptors, synthesis of steroid hormones, or HER2-targeting agents has been greatly enhanced by the detection of predictive biomarkers in diagnostic tumor samples. Based on deeper understanding of breast cancer biology multiple drug candidates have been developed to modulate additional molecular targets which may associate with specific biomarker profiles. Accordingly, exploratory biomarkers are increasingly incorporated in early clinical trials, thus demanding a new process of patient selection. Here, we describe the implementation of preemptive, multiplexed biomarker profiling linked to standard diagnostic algorithms for metastatic breast cancer patients treated at the West German Cancer Center. Profiling for experimental biomarkers was prospectively offered to patients with metastatic breast cancer who met generic clinical trial inclusion criteria. Formalin-fixed, paraffin-embedded tumor samples were retrieved and studied for potentially "actionable" biomarkers related to active clinical trials by immunohistochemistry, amplicon sequencing, and in situ hybridization. The clinical course of those "profiled" patients was closely monitored to offer trial participation whenever applicable. Here, we report results from the first 131 patients enrolled in this program. PIK3CA mutations (23 %) and amplifications (2 %), loss of PTEN expression (13 %), and FGFR1 amplifications (8 %) were detected next to established biomarkers such as estrogen (67 %) and progesterone receptor expression (52 %), and HER2 overexpression or amplification (23 %). So far 16 "profiled" patients (12 %) have been enrolled in biomarker-stratified early clinical trials. Preemptive profiling of investigational biomarkers can be integrated into the diagnostic algorithm of a large Comprehensive Cancer Center. Extensive administrative efforts are required to successfully enroll "profiled" patients with metastatic breast cancer in early clinical trials stratified by exploratory biomarkers.
Asunto(s)
Biomarcadores de Tumor/genética , Neoplasias de la Mama/genética , Perfilación de la Expresión Génica , Adulto , Anciano , Protocolos de Quimioterapia Combinada Antineoplásica/uso terapéutico , Biomarcadores de Tumor/metabolismo , Neoplasias de la Mama/tratamiento farmacológico , Neoplasias de la Mama/metabolismo , Neoplasias de la Mama/mortalidad , Femenino , Humanos , Persona de Mediana Edad , Metástasis de la Neoplasia , Pronóstico , Resultado del TratamientoRESUMEN
BACKGROUND: The challenges in pathology and in structuring of data are increasing. Although considerable amounts of data are generated during the pathological diagnostic process, these data are often not available in a structured form and have to be extracted from the reports through a time-consuming and error-prone manual approach. However, the data are required for various internal and external purposes, such as for audits, tumor organ centers, reporting to cancer registries, different consortia, billing, various aspects within the organization, and for research. OBJECTIVES: The aim of the work was the development of a digital system for the direct and high-quality acquisition of structured pathology data using the example of biopsy-based diagnostics of prostate carcinoma. MATERIALS AND METHODS: A solution was created in cooperation with the pathology laboratory information system (LIS) provider imassense GmbH (Berlin, Germany), whose LIS 'Informationssystem der digitalen Pathologie' (IS-P) is used at the Institute of Pathology at the University Hospital Essen. RESULTS AND CONCLUSION: Over a period of about 1.5 years, a system that is capable of structured reporting according to local, national (S3 guidelines, German Cancer Society) and international (International Collaboration on Cancer Reporting [ICCR]) specifications was developed and subsequently used. The data are stored in readable databases and can easily be generated via ISP. Apart from the disadvantage of a highly specialized solution adapted to the LIS, the project also shows the feasibility in the local academic environment with the above-mentioned advantages.
Asunto(s)
Próstata , Neoplasias de la Próstata , Masculino , Humanos , Próstata/patología , Neoplasias de la Próstata/diagnóstico , Biopsia , Informe de Investigación , Bases de Datos FactualesRESUMEN
PURPOSE: Multiple investigational drugs are currently explored in cancer patient populations defined by specific biomarkers. This demands a new process of patient selection for clinical trials. PATIENTS AND METHODS: Starting January 1, 2012, preemptive biomarker profiling was offered at the West German Cancer Center to all patients with advanced non-small-cell lung (NSCLC) or colorectal cancer (CRC), who met generic study inclusion criteria. Tumour specimens were subjected to prespecified profiling algorithms to detect 'actionable biomarkers' by amplicon sequencing, in situ hybridisation and immunohistochemistry. The clinical course was closely monitored to offer trial participation whenever applicable. RESULTS: Within 12 months, 267 patients (188 NSCLC, 79 CRC) were profiled. Estimated additional cost for biomarker profiling was 219615.51 EUR excluding histopathology workup and administration. The most prevalent biomarkers in pulmonary adenocarcinoma were KRAS mutations (29%), loss of PTEN expression (18%), EGFR mutations (9%), HER2 amplification (5%) and BRAF mutations (3%), while the prevalence of ALK translocations and PIK3CA mutations was extremely low. In pulmonary squamous cell carcinoma FGFR1 amplifications were found in 15%, PTEN expression was lost in 20% and DDR2 was mutated in a single case. KRAS mutations (41%) predominated in CRC, followed by loss of PTEN expression (16%), PIK3CA (5%) and BRAF (5%) mutations. So far 13 patients (5%) have entered biomarker-stratified clinical trials. Therapeutic decisions for approved drugs were guided in another 45 patients (17%). CONCLUSION: Preemptive biomarker profiling can be implemented into the diagnostic algorithm of a large Comprehensive Cancer Center. Substantial investments in diagnostics and administration are required.