Molecular and functional profiling identifies therapeutically targetable vulnerabilities in plasmablastic lymphoma

Plasmablastic lymphoma (PBL) represents a rare and aggressive lymphoma subtype frequently associated with immunosuppression. Clinically, patients with PBL are characterized by poor outcome. The current understanding of the molecular pathogenesis is limited. A hallmark of PBL represents its plasmacytic differentiation with loss of B-cell markers and, in 60% of cases, its association with Epstein-Barr virus (EBV). Roughly 50% of PBLs harbor a MYC translocation. Here, we provide a comprehensive integrated genomic analysis using whole exome sequencing (WES) and genome-wide copy number determination in a large cohort of 96 primary PBL samples. We identify alterations activating the RAS-RAF, JAK-STAT, and NOTCH pathways as well as frequent high-level amplifications in MCL1 and IRF4. The functional impact of these alterations is assessed using an unbiased shRNA screen in a PBL model. These analyses identify the IRF4 and JAK-STAT pathways as promising molecular targets to improve outcome of PBL patients

CIViCdb 2022: evolution of an open-access cancer variant interpretation knowledgebase

CIViC (Clinical Interpretation of Variants in Cancer; civicdb.org) is a crowd-sourced, public domain knowledgebase composed of literature-derived evidence characterizing the clinical utility of cancer variants. As clinical sequencing becomes more prevalent in cancer management, the need for cancer variant interpretation has grown beyond the capability of any single institution. CIViC contains peer-reviewed, published literature curated and expertly-moderated into structured data units (Evidence Items) that can be accessed globally and in real time, reducing barriers to clinical variant knowledge sharing. We have extended CIViC’s functionality to support emergent variant interpretation guidelines, increase interoperability with other variant resources, and promote widespread dissemination of structured curated data. To support the full breadth of variant interpretation from basic to translational, including integration of somatic and germline variant knowledge and inference of drug response, we have enabled curation of three new Evidence Types (Predisposing, Oncogenic and Functional). The growing CIViC knowledgebase has over 300 contributors and distributes clinically-relevant cancer variant data currently representing >3200 variants in >470 genes from >3100 publications

Implementation of an evidence-based decision-making algorithm in the interdisciplinary Molecular Tumor Board of the Charité Comprehensive Cancer Center

Background: Precision cancer medicine (PCM) holds promise to inform tumor therapy decision making by matching systemic therapy options (TOs) to a patient’s molecular tumor properties, most commonly attempted by interdisciplinary Molecular Tumor Boards (MTBs). Yet, replicable interpretation of obtained molecular data as well as coherent TO prioritization across MTBs are still hampered by a lack of inter-MTB standardization of diagnostic pipelines and the process of TO allocation and prioritization. This is further complicated by the increasing availability of extensive and complex profiling techniques such as whole-exome- and RNA-sequencing as well as the rapidly growing body of biomedical evidence. To meet these requirements, a TO decision- making workflow was established and tested in the first 100 patients (pts) of the MTB of the Charité Comprehensive Cancer Center. Methods: An evidence-based algorithm for the analysis and interpretation of tumor profiling data as well as TO decision-making was developed. Pts were either allocated to the diagnostic pipeline by the MTB or included with available outside profiling data, irrespective of the diagnostic modality. A dedicated physician analyzed the profiling data for potential biomarkers by applying the algorithm and best available evidence was researched by manual interrogation of an in-house database as well as public databases. TOs were prioritized by defined evidence levels and subsequently discussed in the MTB for the generation of recorded TOs. Translation into treatment and patient outcomes were followed-up by structured descriptive analysis, permitted by the transfer of both patient and MTB data into a PCM database specifically designed for this purpose. Results: Between January 2016 and May 2017, 100 pts were discussed in the MTB. Profiling data was available for 70/100 pts (90%) and a median of 2 TOs (range: 1- 6) each were made for 63/70 (90%) pts. Of those, 39 pts (62%) were treated according to the TO (“matched”), 24 pts were treated with unmatched agents. Best responses were 6 partial responses (PRs) and 12 stable diseases (SDs) in the matched cohort versus 1 complete response (CR), 1 PR and 9 SDs for the unmatched group. Median progression-free survival (PFS) was 66 and 94 days, respectively. Combination therapy was initiated in 7 matched pts, resulting in superior outcomes of 4 PRs, 2 SDs and a median PFS of 182 days. Detected germline events led to recommendation of genetic counseling in 7 pts. Conclusion: The tested decision-making workflow allowed for a structured, reproducible annotation and interpretation of complex molecular data and generation of TOs, irrespective of the profiling modality. It resulted in high rates of TO recommendation and translation into treatment, showing its feasibility to implement PCM strategies into clinical routine.Hintergrund: Der Ansatz der Präzisionsonkologie (PO) beruht auf dem Prinzip, spezifischen molekularen Alterationen von Tumorzellen systemische Therapieoptionen (TO) zuzuordnen und diese somit gezielt zu behandeln. Dennoch sind sowohl die reproduzierbare Interpretation molekularer Daten als auch ihre klinische Translation in die Behandlung durch eine fehlende Standardisierung der diagnostischen Modalitäten und der Priorisierung von TOs zwischen MTBs limitiert. Die wachsende Verfügbarkeit breiter Profiling-Methoden wie Ganz-Exom- und RNA- Sequenzierung sowie der rasant wachsende Umfang biomedizinischer Literatur erschweren den Ansatz weiterhin. In der vorliegenden Arbeit wurde ein evidenzbasierter Entscheidungsalgorithmus entwickelt und für die ersten 100 Patient*innen der Molekularen Tumorkonferenz (MTK) des Charité Comprehensive Cancer Centers getestet. Methodik: Zur Analyse von patientenspezifischen Profilingdaten und TO-Priorisierung wurde ein evidenzbasierter Algorithmus entwickelt. Die Patient*innen (PT) wurden der Art des molekularen Profilings durch die MTK zugeführt oder mit extern generierten Resultaten eingeschlossen. Die Ergebnisse wurden durch Anwendung des Algorithmus hinsichtlich möglicher Biomarker analysiert, mittels Abfrage einer erstellten internen Datenbank sowie öffentlich zugänglicher Datenbanken einer oder mehreren TOs zugeordnet und nach prädefinierten Evidenzleveln priorisiert. Falls möglich, wurde nachfolgend für jede/n Patient*in durch die interdisziplinäre Diskussion in der MTK evidenzbasierte TOs generiert. Deren klinische Umsetzung sowie das Behandlungsergebnis wurden strukturiert nachverfolgt und nach Eingabe in eine für die MTK konzipierte PO-Datenbank analysiert und deskriptiv dargestellt. Ergebnisse: Zwischen Januar 2016 und Mai 2017 wurden 100 PT in der MTK diskutiert. Resultate waren für 70/100 PT verfügbar. Für insgesamt 63/70 PT (90%) wurden im Median je 2 TO (Spannbreite: 1-6) generiert. 39 PT (62%) wurden gemäß der protokollierten TO behandelt („Präzisionskohorte“), 24 PT erhielten eine andere Therapie („konventionelle Kohorte“). In der Präzisionskohorte wurden 6 partielle Remissionen (PRs) und 12 stabile Erkrankungen (SDs) verzeichnet, in der konventionellen Kohorte wurden eine komplette Remission (CR), 1 PR und 9 SDs erzielt. Das mediane progressionsfreie Überleben (PFS) betrug 66 bzw. 94 Tage. Sieben PT erhielten eine präzisionsonkologische Kombinationstherapie, resultierend in 4 PRs, 2 SDs und einem prolongierten medianen PFS von 182 Tagen. Sieben PT erhielten die Empfehlung einer genetischen Beratung aufgrund von detektierten Keimbahnalterationen. Schlussfolgerung: Der entwickelte Arbeitsalgorithmus ermöglichte eine von der Diagnostik unabhängige, reproduzierbare Annotation komplexer molekularer Daten. Die Anwendung resultierte in einer hohen Rate von TO Empfehlungen sowie einer hohen Behandlungsrate und zeigte daher eine Anwendbarkeit für die PO Implementation in die klinische Versorgung

Information, communication, and cancer patients’ trust in the physician: what challenges do we have to face in an era of precision cancer medicine?

Purpose!#!Despite promising achievements in precision cancer medicine (PCM), participating patients are still faced with manifold uncertainties, especially regarding a potential treatment benefit of molecular diagnostics (MD). Hence, MD poses considerable challenges for patient information and communication. To meet these challenges, healthcare professionals need to gain deeper insight into patients' subjective experiences. Therefore, this qualitative study examined information aspects of MD programs in cancer patients.!##!Methods!#!In two German Comprehensive Cancer Centers, 30 cancer patients undergoing MD participated in semi-structured interviews on information transfer and information needs regarding MD. Additionally, patients provided sociodemographic and medical data and indicated their subjective level of information (visual analogue scale, VAS, 0-10).!##!Results!#!On average patients had high levels of information (mean = 7, median = 8); nevertheless 20% (n = 6) showed an information level below 5 points. Qualitative analysis revealed that patients show limited understanding of the complex background of MD and have uncertainties regarding their personal benefit. Further, patients described unmet information needs. Existential threat in awaiting the results was experienced as burdensome. To withstand the strains of their situation, patients emphasized the importance of trusting their physician.!##!Conclusion!#!The challenges in PCM consist in providing unambiguous information, especially concerning treatment benefit, and providing guidance and support. Therefore, psycho-oncology needs to develop guidelines for adequate patient communication in order to help healthcare providers and cancer patients to handle these challenges in the developing field of PCM