Daniel Hübschmann

The whole-genome landscape of medulloblastoma subtypes

Current therapies for medulloblastoma, a highly malignant childhood brain tumour, impose debilitating effects on the developing child, and highlight the need for molecularly targeted treatments with reduced toxicity. Previous studies have been unable to identify the full spectrum of driver genes and molecular processes that operate in medulloblastoma subgroups. Here we analyse the somatic landscape across 491 sequenced medulloblastoma samples and the molecular heterogeneity among 1,256 epigenetically analysed cases, and identify subgroup-specific driver alterations that include previously undiscovered actionable targets. Driver mutations were confidently assigned to most patients belonging to Group 3 and Group 4 medulloblastoma subgroups, greatly enhancing previous knowledge. New molecular subtypes were differentially enriched for specific driver events, including hotspot in-frame insertions that target KBTBD4 and ‘enhancer hijacking’ events that activate PRDM6. Thus, the application of integrative genomics to an extensive cohort of clinical samples derived from a single childhood cancer entity revealed a series of cancer genes and biologically relevant subtype diversity that represent attractive therapeutic targets for the treatment of patients with medulloblastoma.

Integration of genomics and histology revises diagnosis and enables effective therapy of refractory cancer of unknown primary with PDL1 amplification

Identification of the tissue of origin in cancer of unknown primary (CUP) poses a diagnostic challenge and is critical for directing site-specific therapy. Currently, clinical decision-making in patients with CUP primarily relies on histopathology and clinical features. Comprehensive molecular profiling has the potential to contribute to diagnostic categorization and, most importantly, guide CUP therapy through identification of actionable lesions. We here report the case of an advanced-stage malignancy initially mimicking poorly differentiated soft-tissue sarcoma that did not respond to multiagent chemotherapy. Molecular profiling within a clinical whole-exome and transcriptome sequencing program revealed a heterozygous, highly amplified KRAS G12S mutation, compound-heterozygous TP53 mutation/deletion, high mutational load, and focal high-level amplification of Chromosomes 9p (including PDL1 [CD274] and JAK2) and 10p (including GATA3). Integrated analysis of molecular data and histopathology provided a rationale for immune checkpoint inhibitor (ICI) therapy with pembrolizumab, which resulted in rapid clinical improvement and a lasting partial remission. Histopathological analyses ruled out sarcoma and established the diagnosis of a poorly differentiated adenocarcinoma. Although neither histopathology nor molecular data were able to pinpoint the tissue of origin, our analyses established several differential diagnoses including triple-negative breast cancer (TNBC). We analyzed 157 TNBC samples from The Cancer Genome Atlas, revealing PDL1 copy number gains coinciding with excessive PDL1 mRNA expression in 24% of cases. Collectively, these results illustrate the impact of multidimensional tumor profiling in cases with nondescript histology and immunophenotype, show the predictive potential of PDL1 amplification for immune checkpoint inhibitors (ICIs), and suggest a targeted therapeutic strategy in Chromosome 9p24.1/PDL1-amplified cancers.

Precision Oncology Based on Omics Data: The NCT Heidelberg Experience

Precision oncology implies the ability to predict which patients will likely respond to specific cancer therapies based on increasingly accurate, high‐resolution molecular diagnostics as well as the functional and mechanistic understanding of individual tumors. While molecular stratification of patients can be achieved through different means, a promising approach is next‐generation sequencing of tumor DNA and RNA, which can reveal genomic alterations that have immediate clinical implications. Furthermore, certain genetic alterations are shared across multiple histologic entities, raising the fundamental question of whether tumors should be treated by molecular profile and not tissue of origin. We here describe MASTER (Molecularly Aided Stratification for Tumor Eradication Research), a clinically applicable platform for prospective, biology‐driven stratification of younger adults with advanced‐stage cancer across all histologies and patients with rare tumors. We illustrate how a standardized workflow for selection and consenting of patients, sample processing, whole‐exome/genome and RNA sequencing, bioinformatic analysis, rigorous validation of potentially actionable findings, and data evaluation by a dedicated molecular tumor board enables categorization of patients into different intervention baskets and formulation of evidence‐based recommendations for clinical management. Critical next steps will be to increase the number of patients that can be offered comprehensive molecular analysis through collaborations and partnering, to explore ways in which additional technologies can aid in patient stratification and individualization of treatment, to stimulate clinically guided exploratory research projects, and to gradually move away from assessing the therapeutic activity of targeted interventions on a case‐by‐case basis toward controlled clinical trials of genomics‐guided treatments.

Spatial niche formation but not malignant progression is a driving force for intratumoural heterogeneity

Intratumoural heterogeneity (ITH) is a major cause of cancer-associated lethality. Extensive genomic ITH has previously been reported in clear cell renal cell carcinoma (ccRCC). Here we address the question whether ITH increases with malignant progression and can hence be exploited as a prognostic marker. Unexpectedly, precision quantitative image analysis reveals that the degree of functional ITH is virtually identical between primary ccRCCs of the lowest stage and advanced, metastatic tumours. Functional ITH was found to show a stage-independent topological pattern with peak proliferative and signalling activities almost exclusively in the tumour periphery. Exome sequencing of matching peripheral and central primary tumour specimens reveals various region-specific mutations. However, these mutations cannot directly explain the zonal pattern suggesting a role of microenvironmental factors in shaping functional ITH. In conclusion, our results indicate that ITH is an early and general characteristic of malignant growth rather than a consequence of malignant progression.

Integrative genomic and transcriptomic analysis of leiomyosarcoma

Leiomyosarcoma (LMS) is an aggressive mesenchymal malignancy with few therapeutic options. The mechanisms underlying LMS development, including clinically actionable genetic vulnerabilities, are largely unknown. Here we show, using whole-exome and transcriptome sequencing, that LMS tumors are characterized by substantial mutational heterogeneity, near-universal inactivation of TP53 and RB1, widespread DNA copy number alterations including chromothripsis, and frequent whole-genome duplication. Furthermore, we detect alternative telomere lengthening in 78% of cases and identify recurrent alterations in telomere maintenance genes such as ATRX, RBL2, and SP100, providing insight into the genetic basis of this mechanism. Finally, most tumors display hallmarks of “BRCAness”, including alterations in homologous recombination DNA repair genes, multiple structural rearrangements, and enrichment of specific mutational signatures, and cultured LMS cells are sensitive towards olaparib and cisplatin. This comprehensive study of LMS genomics has uncovered key biological features that may inform future experimental research and enable the design of novel therapies.The molecular genetic landscape of leiomyosarcoma (LMS) is largely unknown. Here, the authors identify frequent DNA copy number alterations, whole-genome duplication, TP53 and RB1 inactivation, alternative telomere lengthening, and genomic imprints of defective DNA repair via homologous recombination as a potential therapeutic target in LMS patients.

Genomic features of renal cell carcinoma with venous tumor thrombus

A venous tumor thrombus (VTT) is a potentially lethal complication of renal cell carcinoma (RCC) but virtually nothing is known about the underlying natural history. Based on our observation that venous thrombi contain significant numbers of viable tumor cells, we applied multiregion whole exome sequencing to a total of 37 primary tumor and VTT samples including normal tissue specimens from five consecutive patients. Our findings demonstrate mutational heterogeneity between primary tumor and VTT with 106 of 483 genes (22%) harboring functional SNVs and/or indels altered in either primary tumor or thrombus. Reconstruction of the clonal phylogeny showed clustering of tumor samples and VTT samples, respectively, in the majority of tumors. However, no new subclones were detected suggesting that pre-existing subclones of the primary tumor drive VTT formation. Importantly, we found several lines of evidence for “BRCAness” in a subset of tumors. These included mutations in genes that confer “BRCAness”, a mutational signature and an increase of small indels. Re-analysis of SNV calls from the TCGA KIRC-US cohort confirmed a high frequency of the “BRCAness” mutational signature AC3 in clear cell RCC. Our findings warrant further pre-clinical experiments and may lead to novel personalized therapies for RCC patients.

Quantitative Approaches to Nuclear Architecture Analysis and Modelling

The spatial organisation of the genome in the cell nucleus has emerged as a key element to understand gene function. A wealth of molecular and microscopic information has been accumulated, resulting in a variety of – sometimes contradictory – models of nuclear architecture. So far, however, a large part of this structural information and in consequence also the models derived from them are ‘qualitative’. In this overview, a brief introduction will be given into quantitative experimental and modelling approaches to large scale nuclear genome architecture in human cells. As a biomedical application example, the use of a quantitative computer model of the 3D architecture allowed to explore different implications of nuclear structure on chromosomal aberrations. In addition, we shall present two novel examples for quantitative computer modelling: (1) The impact of SC 35 splicing domains on nuclear genome structure; (2) The dynamics of large scale nuclear genome structure in a Brownian motion model. Finally, we shall discuss some perspectives to extend quantitative nuclear structure analysis to the nanoscale.