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German Cancer Research Center

The German Cancer Research Center (DKFZ) is, with more than 3,000 employees, the largest biomedical research facility in Germany. More than 1,000 scientists at DKFZ conduct research on how cancer emerges, ascertain cancer-risk factors, and look for new strategies that prevent individuals from getting cancer. They are currently developing new methods with which tumors can be diagnosed more precisely, and cancer patients can be treated more successfully. Employees at the Krebsinformationsdienst (KID) explain the widespread disease cancer to patients, family members and interested citizens. Jointly with the University Clinic Heidelberg, the DKFZ has installed the National Center for Tumour Diseases (NCT) Heidelberg, in which promising approaches from cancer research are transferred into the clinic.  In the German Consortium for Translational Cancer Research (DKTK) , one of the six German centers for health research, the DKFZ maintains translation centers at seven university partner sites.

The bonding of excellent university medicine with top-level research at a Helmholtz Center represents a significant contribution towards improving opportunities for cancer patients. The DKFZ is financed 90 percent by the Federal Ministry of Education and Research and 10 percent by the Federal State Baden-Württemberg, and is a member of the Helmholtz Association of German Research Centers.

The German Cancer Research Center (DKFZ)

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Prevention - our most powerful weapon against cancer

Michael Baumann, Director of the German Cancer Research Center, explains why we are lagging so far behind in terms of prevention and what we need to do to drive research and application forward.

Cancer researchers to market crayfish

By studying marbled crayfish, Sina Tönges and Frank Lyko, from the German Cancer Research Center (DKFZ), were able to gain new insights into the development of cancer. Now the researchers want to…

Pioneer in the fight against cancer

Stefan Pfister of the German Cancer Research Center (DKFZ) is developing new methods to diagnose tumors in children and adolescents more precisely and treat them more effectively.

How food protects our health

Cancer, dementia, diabetes: Eating a healthy diet can prevent numerous diseases. Yet many people still underestimate the importance of food for prevention. Helmholtz researchers provide arguments for…

Vaccine against cancer

The Corona pandemic has helped the development of mRNA vaccines make a breakthrough. But this technology was originally developed to treat cancer. In an interview, Dirk Jäger explains when we can…

How AI is revolutionizing medicine

Medicine is on the verge of another revolution: Artificial intelligence supports doctors in analyzing X-ray and ultrasound images and in improving diagnostics and treatment. Researchers in Germany are…

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National Center for Tumor Diseases (NCT)

The NCT is a long-term cooperation between the German Cancer Research Center (DKFZ), excellent partners in university medicine and other outstanding research partners at various locations in Germany.

Strengthening cancer research:

Expansion of the nct by four sites.

The expansion of the National Center for Tumor Diseases (NCT) is an important part of the National Decade against Cancer initiated by the Federal Ministry of Education and Research (BMBF). The goal of the NCT is to bring promising results from cancer research quickly and safely into clinical application. The aim is to give patients nationwide access to innovative treatment approaches. In order to expand patient participation in Germany, the partnership between patients and researchers has been firmly implemented in the NCT. The aim is to take the patient's perspective into account in all phases of cancer research. Heidelberg has been the first NCT site since 2004, Dresden the second site since 2015. On February 2, 2023, the BMBF announced the new sites: Berlin, SüdWest (Tübingen/Stuttgart-Ulm), WERA (Würzburg with partners Erlangen, Regensburg and Augsburg) and West (Cologne/Essen). This means that a total of six NCT sites are now cooperating with the German Cancer Research Center (DKFZ) to advance clinical cancer research in Germany and to improve treatment outcomes and the quality of life of cancer patients.  »Overview of NCT sites and their supporting institutions

Short film "One NCT"

Federal ministry of education and research announces new funding approaches and expansion of nct.

In the run-up to this year's World Cancer Day, Federal Research Minister Bettina Stark-Watzinger today presented new funding approaches for cancer research at the Future X Change forum of the National Decade against Cancer.

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• Published: 26 October 2023

NCT/DKFZ MASTER handbook of interpreting whole-genome, transcriptome, and methylome data for precision oncology

• Andreas Mock   ORCID: orcid.org/0000-0002-3332-9166 1   na1   nAff15 ,
• Maria-Veronica Teleanu 1 , 2   na1 ,
• Simon Kreutzfeldt 1 ,
• Christoph E. Heilig   ORCID: orcid.org/0000-0001-8869-1421 1 ,
• Jennifer Hüllein 3 ,
• Lino Möhrmann   ORCID: orcid.org/0000-0003-4650-6827 4 , 5 , 6 , 7 ,
• Arne Jahn 5 , 8 ,
• Dorothea Hanf 4 , 5 , 6 , 7 ,
• Irina A. Kerle 4 , 5 , 6 , 7 ,
• Hans Martin Singh   ORCID: orcid.org/0000-0001-7214-9339 1 , 9 ,
• Barbara Hutter 3 ,
• Sebastian Uhrig 3 ,
• Martina Fröhlich 3 ,
• Olaf Neumann   ORCID: orcid.org/0000-0003-2684-9187 10 ,
• Andreas Hartig 11 ,
• Sascha Brückmann 11 ,
• Steffen Hirsch   ORCID: orcid.org/0000-0002-4920-0930 12 ,
• Kerstin Grund 12 ,
• Nicola Dikow 12 ,
• Daniel B. Lipka   ORCID: orcid.org/0000-0001-5081-7869 1 , 13 ,
• Marcus Renner 1 ,
• Irfan Ahmed Bhatti 1 , 9 ,
• Leonidas Apostolidis 9 ,
• Richard F. Schlenk 2 , 9 , 14 ,
• Christian P. Schaaf 12 ,
• Albrecht Stenzinger   ORCID: orcid.org/0000-0003-1001-103X 10 ,
• Evelin Schröck   ORCID: orcid.org/0000-0002-3377-1704 5 , 8 ,
• Daniel Hübschmann   ORCID: orcid.org/0000-0002-6041-7049 3 ,
• Christoph Heining 4 , 5 , 6 , 7 ,
• Peter Horak   ORCID: orcid.org/0000-0003-4536-9306 1   na2 ,
• Hanno Glimm 4 , 5 , 6 , 7   na2 &
• Stefan Fröhling   ORCID: orcid.org/0000-0001-7907-4595 1   na2  

npj Precision Oncology volume  7 , Article number:  109 ( 2023 ) Cite this article

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• Cancer genomics
• Translational research

Analysis of selected cancer genes has become an important tool in precision oncology but cannot fully capture the molecular features and, most importantly, vulnerabilities of individual tumors. Observational and interventional studies have shown that decision-making based on comprehensive molecular characterization adds significant clinical value. However, the complexity and heterogeneity of the resulting data are major challenges for disciplines involved in interpretation and recommendations for individualized care, and limited information exists on how to approach multilayered tumor profiles in clinical routine. We report our experience with the practical use of data from whole-genome or exome and RNA sequencing and DNA methylation profiling within the MASTER (Molecularly Aided Stratification for Tumor Eradication Research) program of the National Center for Tumor Diseases (NCT) Heidelberg and Dresden and the German Cancer Research Center (DKFZ). We cover all relevant steps of an end-to-end precision oncology workflow, from sample collection, molecular analysis, and variant prioritization to assigning treatment recommendations and discussion in the molecular tumor board. To provide insight into our approach to multidimensional tumor profiles and guidance on interpreting their biological impact and diagnostic and therapeutic implications, we present case studies from the NCT/DKFZ molecular tumor board that illustrate our daily practice. This manual is intended to be useful for physicians, biologists, and bioinformaticians involved in the clinical interpretation of genome-wide molecular information.

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Introduction

Precision oncology (PO) is an emerging, highly interdisciplinary field of cancer medicine that aims to develop and apply clinical management strategies tailored to individual patients’ biological characteristics 1 , 2 . It has grown rapidly with the widespread availability of next-generation sequencing-based methods for detecting acquired molecular alterations that drive tumor growth 3 . In parallel, the need to identify hereditary factors that predispose to cancer development has also increased 4 . Structurally, the importance of PO is reflected in the growing number of cancer centers maintaining dedicated molecular tumor boards (MTBs) for biologically guided clinical decision-making 5 , 6 , 7 , 8 , 9 , 10 . Most PO workflows have been built around the analysis and interpretation of subgenomic cancer gene panels 11 , and a number of position papers offer guidance in interpreting the biological effects and clinical implications of cancer variants 12 , 13 , 14 , 15 . This handbook aims to support the advancement of PO by (i) describing the experience gained in the clinical interpretation of data from multidimensional tumor characterization by whole-genome or exome (WGS/WES) and RNA sequencing (RNA-seq) and DNA methylation profiling in the MASTER (Molecularly Aided Stratification for Tumor Eradication Research) trial of the National Center for Tumor Diseases (NCT) and the German Cancer Research Center (DKFZ) 6 , 16 and (ii) presenting key concepts using clinical cases from the MTB at NCT Heidelberg/Dresden.

Patient characteristics and tissue context

The clinical interpretation of molecular alterations starts with evaluating relevant patient characteristics and the tissue context in which a genetic profile occurs. The former relates, in particular, to previous therapies, in addition to disease stage and clinical performance status. For example, prior targeted therapies warrant a search for possible resistance mutations, and progression on single-agent immune checkpoint inhibition requires consideration of combination therapies if the tumor exhibits predictive biomarkers for immunotherapy. Concomitant cancers and non-oncologic diagnoses are other important host factors to account for. Tissue context refers to the histologic entity, biopsy site, type of tissue preservation, i.e., formalin fixation and paraffin embedding vs. snap freezing, and preanalytical parameters such as DNA and RNA quality and tumor cell content estimated by an experienced pathologist. Each case also requires consideration of the tumor entity’s molecular landscape, e.g., recurrent mutations, copy number alterations, and gene fusions (Fig. 1 ).

Cases were selected to exemplify how to approach, following current guidelines for oncogenicity classification, somatic variants that have not been curated and to emphasize the therapeutic impact of the histologic context. In addition, we included a structural variant, i.e., an insertion, to illustrate curation challenges in daily routine. a Gastrointestinal stromal tumor (GIST) studied by WES and RNA-seq of formalin-fixed and paraffin-embedded tumor tissue (histopathologic tumor cell content, 50%). A KIT exon 11 insertion (p.P585_R586insSPYDHKWEFP), whose expression was verified by RNA-seq, was nominated as a candidate driver because in-frame indels in KIT exon 11, encoding the KIT juxtamembrane domain, are known oncogenic events in GIST and rarely occur in other cancers ( www.cancerhotspots.org 55 ). A literature search revealed that a similar variant (p.P585_586insLPYDHKWEFP) was detected in a previous study but has not been functionally characterized to date 63 . Application of the VICC guideline for interpreting somatic variants in tumors ( www.cancervariants.org 28 ) resulted in a score of seven points, classifying the variant as likely oncogenic, which was composed of evidence from the following categories: “Oncogenicity Moderate 1” (OM1; two points): variant located in a critical and well-established part of a functional domain; OM2 (two points): variant associated with protein length changes because of in-frame indels in a known oncogene or tumor suppressor gene or stop-loss variants in a known tumor suppressor gene; “Oncogenicity Supporting 3” (OP3; one point): variant absent from controls or occurring at an extremely low frequency in the Genome Aggregation Database (gnomAD; https://gnomad.broadinstitute.org ); OP4 (one point): variant located in a mutation hotspot listed in Cancer Hotspots ( www.cancerhotspots.org ) and associated with an amino acid change count in Cancer Hotspots below 10 (resources such as cBioPortal [ www.cbioportal.org ], COSMIC [ https://cancer.sanger.ac.uk/cosmic ], or an entity’s published genetic landscape to be used for variants occurring in tumor types not covered well by Cancer Hotspots). Furthermore, we added OP2 evidence (one point; variant in a gene in a malignancy with a single genetic etiology) because KIT mutations drive the vast majority of GIST, and exon 11 indels are among the recurrent alterations. Based on this evaluation, the MTB recommended therapy with imatinib with an NCT evidence level of m1a, because KIT exon 11-mutant GIST is particularly sensitive to this agent 64 . CI, confidence interval; SBS, single-base substitution. b RAF- and NRAS-wildtype acral melanoma studied by WGS and RNA-seq of fresh-frozen tissue (histopathologic tumor cell content, 65%) after progressing on immuncheckpoint inhibition. The KIT gene was affected by a p.K642E missense mutation with loss of heterozygosity and an allele frequency (AF) of 80%, whose expression was verified by RNA-seq (AF, 100%), and a DNA copy number of 8 (average ploidy, 3). Activating KIT mutations occur in approximately 3% of melanomas, with enrichment in the acral subtype, and include mainly missense mutations affecting exons 9, 11, 13, 17, and 18, with up to 60% occurring in exons 11 or 13. The p.K642E and p.L576 variants account for approximately one-quarter of KIT mutations in melanoma and provide a rationale for therapy with imatinib. However, the objective response and disease control rates of these patients (24.4% and 66.7%, respectively; 65 ) are lower than those of patients with KIT -mutant GIST (80% and >90%, respectively), context-specific differences whose basis remains to be elucidated. APOBEC, apolipoprotein B mRNA editing enzyme, catalytic polypeptide; UV, ultraviolet. Take-home messages: (i) Current VICC guidelines should be applied when evaluating somatic variants of unclear biological significance. Certain alteration types remain difficult to annotate and may require case-by-case assessment, which should take place in multidisciplinary MTBs whenever possible. (ii) The clinical actionability of a driver alteration, determined by, e.g., the probability and duration of response to molecularly guided therapy, can vary widely depending on the histologic context, which must always be considered when selecting and prioritizing treatment options.

Quality measures, summary statistics, and complex molecular profiles

After examining general quality measures of sequencing runs, such as library size and RNA mapping and duplication rates, we first evaluate summary statistics and complex biomarkers, whose detection is enabled by comprehensive and multilayered profiling. These biomarkers include computational estimates of tumor purity and ploidy, tumor mutational burden, mutational signatures (Fig. 2a 17 ), and the quantification of genomic instability by assessing the loss-of-heterozygosity-homologous-recombination-deficiency (HRD-LOH) score and the number of the large-scale state transitions (LSTs; Fig. 2b ). The HRD-LOH score corresponds to the number of subchromosomal segments with loss of heterozygosity larger than 15 megabase pairs (Mbp), and LSTs are defined as switches between segments with different copy number states larger than 10 Mbp but smaller than entire chromosome arms 18 , 19 , 20 . Moreover, we quantify microsatellite instability according to the MSIsensor algorithm 21 . For central nervous system tumors 22 and sarcomas 23 , genome-wide DNA methylation profiles allow entity predictions using published classifiers (Fig. 3 ). For all other entities, similarity analyses of transcriptional profiles within the MASTER cohort allow comparison of an individual case with known diagnoses 24 . When methylome- or transcriptome-based entity predictions suggest a likely differential diagnosis, pathologic reevaluation is recommended.

a Fractions of mutational signatures identified in the tumor. DSB, double-strand break. hom. recomb., homologous recombination. b Somatic DNA copy number profiles of the tumor and a matched normal control. The tumor exhibits segmental gains and losses of all chromosomes as well as a high HRD-LOH score and numerous LSTs (19 and 23, respectively), corresponding to a highly rearranged genome. Consistent with the genomic “scars” of HRD, the SBS3 mutational signature explained 50% of all SNVs. Of note, no germline or somatic mutations in BRCA1/2 were detected. Chromosomes 1 to X are indicated.

Patient with undifferentiated pleomorphic sarcoma of the lung according to histopathology. Immunohistochemistry: Melan A, HMB45, CD34, MyoD, CD30, SOX10, CD68, CD117, cytokeratin 7/8, CD123, CD1a, and CD21 negative; CD56, S100, and PD-L1 (90%, Cologne Score 5) positive; proliferation rate (MIB-1), 80%. Treatment course: surgery followed by adjuvant chemotherapy with doxorubicin and ifosfamide; switch to pazopanib due to liver metastases, stable disease; switch to trabectedin and pembrolizumab due to lung metastases after six months, complete metabolic response; brain metastases with continuing remission at peripheral sites after six months. WGS and RNA-seq revealed gene expression similarity to melanoma, a high tumor mutational burden (891 SNVs and 8 indels), and a highly prevalent SBS7 mutational signature associated with UV light exposure 66 . DNA methylation profiling showed a match score of 0.95 with cutaneous melanoma 23 , 67 . The figure shows a projection of the index case and several melanomas (MEL) on a DNA methylation-based sarcoma reference cohort ( n  = 1077; 23 ), in which undifferentiated sarcomas (USARC) are highlighted (t-distributed stochastic neighbor embedding [t-SNE] using the 10,000 most variable probes according to standard deviation via the R package Rtsne (version 0.16) using 3000 iterations and a perplexity value of 30). This finding prompted recommendations to reevaluate the diagnosis and modify further treatment if applicable. Take-home messages: (i) New multiomics layers, such as genome-wide DNA methylation profiles, can help refine diagnosis, especially for cancer types without distinct morphologic features or pathognomonic molecular alterations. (ii) Multiomics-guided diagnostic reclassification can inform therapeutic decision-making.

Highly actionable and entity-defining alterations

The first individual molecular changes we evaluate from a clinical perspective are the “known knowns” of PO, i.e., highly actionable and entity-defining alterations. This is facilitated by a whitelist in our variant annotation pipeline consisting of (i) genes that are part of the OnkoKB knowledge base 25 , (ii) biomarker-drug associations that were the basis of previous MTB recommendations at NCT Heidelberg/Dresden, and a manually curated set of entity-defining alterations, e.g., SS18::SSX fusions in synovial sarcoma 26 . This whitelist is continuously adapted as new evidence becomes available, and clinical interpretation is not limited to this gene set. Even if convincing evidence for treatment recommendations can be provided based on the highly actionable genes alone, we seek to explore all biological layers to identify new parameters that can inform clinical management. For example, SNVs or copy number alterations are always presented alongside the respective gene’s expression level to allow for integrative interpretation. All clinically actionable alterations are assigned to seven biomarker baskets based on the cellular pathways or processes involved: tyrosine kinases, PI3K-AKT-mTOR signaling, RAF-MEK-ERK signaling, cell cycle, developmental regulation, DNA damage repair, and immune evasion.

Oncogenicity of small genetic variants

We regularly encounter genetic variants in known cancer genes that have not been described in PO knowledge bases 27 . In such cases, we apply the VICC standard operating procedure for interpreting the pathogenicity of somatic variants in cancer 28 . It focuses on the oncogenicity of acquired small genetic alterations, i.e., SNVs and indels, but is not intended for interpreting other alteration types, such as copy number changes or gene fusions, leaving room for further development. Additional insight into the functional consequences of unknown alterations can be derived from the RNA-seq data, which provide the normalized expression level of both the affected gene and a variant of interest.

Copy number alterations as diagnostic markers and actionable targets

Since information on genomic gains and losses can guide clinical decision-making, we provide a copy number plot for each patient. For example, the degree and pattern of copy number changes may support the diagnosis of a particular entity. Figure 4 shows that synovial sarcoma, a fusion-driven, genomically “silent” sarcoma, and leiomyosarcoma, characterized by genomic “chaos”, display very different copy number patterns. Furthermore, copy number information can be used to infer the average ploidy of a tumor genome, whose knowledge is essential for the functional and, ultimately, clinical interpretation of genomic imbalances. For example, a focal amplification with a copy number of 6 is less likely to be a tumor-driving alteration if the average ploidy is 4 instead of 2. While global copy number changes, whose patterns were recently categorized into multiple signatures reflecting distinct mutational processes 29 , 30 , have thus far been primarily of diagnostic value, focal genomic losses, and amplifications can be therapeutic targets. A particular challenge associated with WGS/WES data is the detection of copy number alterations that are focal but still contain tens to hundreds of genes. The delineation of driver and, thus, potentially actionable genes within an amplicon is greatly aided by the whitelisting mentioned above and by integration with RNA-seq data to pinpoint loci whose copy number change leads to altered expression (Fig. 5 ). In contrast to focal amplifications affecting established oncogenes, the actionability of copy number losses affecting tumor suppressor genes is more difficult to determine, especially when only one gene copy is deleted, and the other allele remains intact (Fig. 6 ). In the future, such uncertainties may be resolved by integrating pathway analyses inferred from RNA-seq and proteomic data.

a Few DNA copy number changes in a patient with SS18::SSX2 -positive synovial sarcoma. Consistent with the “silent” genomes of many fusion-driven cancers, a low tumor mutational burden was found with 23 SNVs and indels, corresponding to 0.6 non-synonymous mutations per coding megabase. b Multiple DNA copy number alterations in a patient with genomically unstable leiomyosarcoma. c Pathognomonic amplification of MDM2 and CDK4 on chromosome 12q14-q15 (red arrow), which are targeted by small-molecule inhibitors 68 , 69 , and few other genomic imbalances in a patient with well-differentiated liposarcoma. d Higher genomic complexity with multiple DNA copy number alterations in a patient with dedifferentiated liposarcoma (DDLS). Take-home messages: (i) The extent of DNA copy number alterations varies considerably among tumor types. (ii)The patterns of genomic imbalances can aid in the diagnostic categorization of various cancer entities. (iii) Recurrent amplicons may harbor genes that can be targeted therapeutically, such as CDK4 and MDM2 in DDLS.

a Squamous cell carcinoma of an unknown primary site in the neck region studied by WGS and RNA-seq. MMR, mismatch repair. TCN, total copy number. b Evidence of numerous DNA copy number alterations, including amplification (total copy number, 8; average tumor ploidy, 2) of a region on chromosome 11q13.3 containing the oncogenes CCND1 , FGF3 , and FGF4 (red arrow). A query of the OnkoKB precision oncology knowledgebase ( www.onkokb.org ) showed that data on the oncogenicity of FGF3 and FGF4 amplification are inconclusive. RNA-seq analysis showed decreased transcription of FGF3 and FGF4 , indicating that their amplification is a passenger alteration. In contrast, CCND1 was expressed, suggesting that it functions as a driver. The finding of homozygous deletion of CDKN2A/B on chromosome 9p21.3 further supported the role of the CCND1–CDK4/6 axis in the pathogenesis of this tumor. However, the clinical efficacy of CDK4/6 inhibition in this scenario varies and appears to be dependent on histology 70 , 71 . Based on two clinical trials of the CDK4/6 inhibitor palbociclib in combination with cetuximab in CDKN2A -negative squamous cell carcinoma of the head and neck region 72 , 73 , the MTB recommended this treatment with an NCT evidence level of m2a. Chromosomes 1 to Y are indicated. Take-home messages: (i) An amplicon can harbor dozens to thousands of genes that can act as drivers or passengers in a given histologic context. (ii) Integrating WGS/WES and RNA-seq data can guide the selection of driver genes and inform treatment.

a Advanced esophageal cancer studied by WGS and RNA-seq. b DNA copy number plot showing a heterozygous deletion of chromosome 10q associated with loss of one PTEN allele, which, together with a focal deletion of exons 6 to 8 of the other allele, is predicted to result in loss of PTEN function, providing a rationale for therapeutic inhibition of constitutively active PI3K–AKT–mTOR signaling. Chromosomes 1 to Y are indicated. c Intrahepatic cholagiocarcinoma studied by WGS and RNA-seq. In addition to a FGFR2::DBP fusion, potentially actionable DNA copy number alterations affecting tumor suppressor genes within the PI3K–AKT–mTOR pathway (average tumor ploidy, 4; PTEN copy number, 3; TSC1 copy number, 2; FBXW7 copy number, 2) were detected; however, none of these loci was affected by alterations of the remaining allele that would result in complete inactivation, leaving the functional consequences of the copy number losses unclear. RNA-seq showed that all genes were expressed, which, without information on protein expression, argued against treatment recommendations based, at best, on partial inactivation of negative regulators of PI3K–AKT–mTOR signaling. Future integration of proteomic profiling and RNA-based pathway activity estimation into our workflow will provide a more accurate assessment of the impact of DNA copy number alterations on gene function, i.e., their influence on protein synthesis in a given tumor environment. Take-home messages: (i) Heterozygous deletions of tumor suppressor genes without a second “hit” affecting the remaining allele should be interpreted with caution and require further validation, e.g., by immunohistochemistry. (ii) In the case of a deletion affecting one copy of a tumor suppressor gene, examination of the remaining allele, RNA expression, and the integrity of other genes relevant to the respective pathway support the evaluation of functional impact and, thus, clinical actionability.

Gene fusions as actionable targets

A major advantage of combined WGS/WES and RNA-seq analysis is the identification of targetable gene fusions that may evade detection by targeted sequencing due to their complexity or breakpoint location, e.g., NRG1 fusions in KRAS-wildtype pancreatic cancer 31 . For the detection of gene fusions from RNA-seq data, we have developed the Arriba pipeline, which has become a gold standard in terms of accuracy and speed 32 , 33 , 34 . Combined WGS/WES and RNA-seq also allow us to accurately determine the molecular anatomy of gene fusions. This is relevant from a therapeutic perspective since most actionable fusions involve genes encoding kinases, and constitutive kinase activation and “druggability” can be assumed if an open reading frame is created that includes the intact catalytic domain (Fig. 7 ). Another advantage of including RNA-seq is that one can verify the expression of a fusion gene in the tumor. This information is particularly relevant when evaluating previously undescribed fusions in which an established drug target is joined to a novel partner gene.

a FGFR1::ADAM9 fusion generated by an interstitial deletion on chromosome 8p linking FGFR1 exons 1–12 to ADAM9 exons 12−1 in a patient with chondroblastic osteosarcoma of the femur. As this fusion was out of frame, retained only part of the FGFR1 kinase domain, and was supported by only a few reads, the MTB classified it as non-functional and without therapeutic implications. b FGFR2::WDR65 fusion linking FGFR2 exons 1−17 to WDR65 exons 12−23 in a patient with intrahepatic cholangiocarcinoma (iCCC). The chimeric transcript, which is supported by multiple reads for both partners, is characterized by a recurrent breakpoint in FGFR2 exon 17 and retains the FGFR2 kinase domain. FGFR2 fusions are identified in approximately 15% of iCCC 74 and targeted by the recently approved FGFR inhibitor pemigatinib. c Oncogenic FGFR1::PLAG1 fusion in a patient with myoepithelial carcinoma. The genomic breakpoints are located between the promoter and the transcription start site of both FGFR1 and PLAG1 , resulting in the expression of full-length PLAG1 regulated by the FGFR1 promoter. Accordingly, PLAG1 but not FGFR1 was highly expressed, as indicated by the different number of reads. PLAG1 fusions are characteristic of myoepithelial carcinoma, an aggressive form of salivary gland cancer 75 , and are not yet amenable to targeted therapies. d Detection of 184 gene fusions in a patient with DDLS, originating primarily from the alteration of chromosome 12q characteristic of this entity. Gene fusions may be a source of immunogenic neoantigens that can mediate a response to immunotherapy even in tumors with low mutational burden 76 . Take-home messages: (i) RNA-seq is the most accurate method to detect functional gene fusions. (ii) The oncogenicity of a gene fusion does not automatically render the fusion a druggable target. (iii) To date, druggable fusions are mainly restricted to chimeric proteins containing a kinase domain that is constitutively active and triggers downstream signaling.

Clinical interpretation of transcriptomic data

As described above, analysis of RNA-seq data improves the biological annotation of genetic alterations. In addition, transcriptomic information alone can also yield therapeutic recommendations. First, aberrant expression of kinase genes can guide the use of corresponding inhibitors 35 , 36 , 37 , as exemplified by the identification of candidates for rogaratinib treatment based on FGFR1-3 expression 38 . Second, gene expression data enable personalized immunotherapy approaches. For example, we frequently identify overexpression of CLDN6 or MAGEA4/8 , which prompts eligibility evaluation for appropriate biomarker-stratified clinical trials (ClinicalTrials.gov Identifiers: NCT04503278, NCT03247309). A remaining challenge is the definition of tumor-specific gene expression. We usually report the rank of a gene’s transcript per million value within the MASTER cohort, which, however, can be strongly influenced by a tumor’s location (e.g., primary tumor vs. lung or liver metastasis) and the composition of its microenvironment. Overall, we find that the availability of a transcriptomic data layer significantly increases the number of biologically guided therapy recommendations (Fig. 8 ).

Rationale: These two cases from the same entity highlight the therapeutic value derived from integrating transcriptomic analysis for the emerging list of antibody-drug conjugates and cellular immunotherapy strategies. a Adenoid cystic carcinoma (ACC) studied by WGS. The only treatment recommendation was PARP inhibition based on a dominant SBS3 mutational signature. b ACC studied by WGS and RNA-seq. In contrast to the previous case, transcriptomic information yielded several treatment recommendations, i.e., sacituzumab govitecan based on overexpression of TACSTD2 ; multi-tyrosine kinase inhibition based on overexpression of DDR1 , FGFR2 , IGF1R , PDGFA , PDGFB , and NTRK3 ; T-cell based immunotherapy within a phase 1 clinical trial (ClinicalTrials.gov Identifier: NCT03441100) based on MAGEA1 overexpression and a HLA-A*02 genotype; and enfortumab vedotin based on PVRL4 (also called NECTIN4 ) overexpression. Take-home messages: (i) RNA-seq enables the detection of targets for antibody-drug conjugates or cellular immunotherapies. (ii) The selection of kinase inhibitors can be guided through the assessment of their target landscape by RNA-seq.

Assessment and reporting of germline variants

A major advantage of parallel WGS/WES of tumor and control samples is the ability to directly detect pathogenic germline variants 39 , which are found in approximately 10–15% of cases in the MASTER program and not known before study enrollment in the majority of cases 6 , 40 . The control sample is usually derived from blood. However, other tissues, e.g., skin, must be used in patients with hematologic neoplasms or after allogeneic stem cell transplantation. The calling of germline variants in cancer predisposition genes, including SNVs, indels, and structural variants, is performed using an open source bioinformatics pipeline at DKFZ 6 , 24 , and interpretation of filtered rare variants is performed according to the American College of Medical Genetics and Genomics (ACMG) and Association for Molecular Pathology guidelines 41 and further specifications 42 by a team of clinical geneticists. For clinical interpretation of germline variants, molecular and clinical characteristics, such as histopathologic diagnosis, age of onset, previous cancers, other phenotypic abnormalities, and especially family history, are considered (Box 1 ). As this extensive information is not always available during the primary clinical workup, a framework for additional genetic data collection is established. In addition, open questions can be discussed with the treating physician as part of the MTB. The MTB also decides whether a germline finding triggers a recommendation for genetic counseling and must consider the patient’s consent options. If a pathogenic germline variant was detected, a board-certified clinical geneticist or other certified physician with appropriate training should inform the patient about the results and offer formal genetic counseling 43 . Apart from recommendations for genetic testing, pathogenic germline variants can support treatment decisions, e.g., the administration of a PARP inhibitor in germline BRCA1/2 -mutated pancreatic cancer 44 . An important goal is to harmonize germline variant evaluation across PO programs and improve the data collection and follow-up for patients with genetic tumor risk syndromes.

Box 1: Detection of clinically relevant mosaicism

A male patient diagnosed with leiomyosarcoma of the mesenterial fat at age 59 years was enrolled in the MASTER program due to progressive disease on doxorubicin and olaratumab and on gemcitabine and docetaxel. WGS revealed 30 SNVs and one indel, including variants in TP53 (p.H193R; AF, 0.79) and RB1 (p.F839fs*10; AF, 0.81), which were both associated with loss of heterozygosity of the wildtype allele, a typical finding in leiomyosarcomas that show near-universal inactivation of TP53 and RB1 77 . Illustrating the value of paired tumor and matched normal tissue analysis, the RB1 indel was detected in the control sample with an allele frequency of 5.7%. The medical history revealed that enucleation was performed at the age of three years due to an eye tumor, and genetic counseling was recommended due to the very likely presence of a pathogenic RB1 variant as mosaicism. RB1 mosaicism occurs in approximately 5% of parents of children with unilateral retinoblastoma 78 . The degree of mosaicism in different tissues is difficult to assess, but the variant may be inherited up to 50%. This should be considered during treatment, especially irradiation, due to an increased risk of secondary malignancies (38% vs. 21% by age 50 in irradiated vs. non-irradiated patients 79 ).

Assignment of evidence to actionable biomarkers and treatment recommendations

We recently described our approach to assigning evidence to biomarker-drug response associations 14 and the variant classification system developed at NCT, which is used by the major precision oncology networks in Germany 15 . There are four NCT evidence levels: m1, evidence in the same entity; m2: evidence in a different entity; m3, preclinical evidence; m4, biological rationale. Levels m1 and m2 have three suffixes denoting the study type from which the evidence was derived: A, prospective study or meta-analysis; B, retrospective cohort or case-control study; C, case study or single unusual responder. Treatment recommendations are drafted before the MTB and are primarily based on evidence for associations between molecular biomarkers and drug response, taking into account tumor entity (Fig. 9 ). We do not limit our recommendations to approved drugs, as compounds in clinical development may become available in the short to medium term. Alternatively, a patient’s molecular findings would need to be regularly reevaluated in an MTB, which is currently not feasible due to the increasing number of cases and limited automation of clinical decision-making to date. All recommendations are based on both knowledgebase entries and an extensive manual literature search and always include suitable biomarker-stratified trials if available.

The number of molecular alterations identified by multiomics is steadily increasing, which entails two main challenges, i.e., determining the biological significance and clinical relevance of a candidate biomarker. a The evidence supporting a molecularly informed therapy ranges from preclinical studies to phase 3 clinical trials or meta-analyses. The underlying histologic entity must always be considered when assigning evidence to a molecular biomarker. In the case presented, therapy A is supported by clinical data from other entities (m2a), whereas for therapy B, there are retrospective data from the same entity supporting the recommendation (m1b). b The final evidence attributed to treatment can be listed as a range between the lowest and highest level, (e.g., m2a–m3). The number of references listed varies among curators, but we advise careful judgment and restriction to the most contextually relevant ones. c , d Prioritization of therapies is a complex process and depends on several variables that must be considered in a patient’s specific clinical and socioeconomic situation at a given time. For example, a therapy may be available in a clinical trial, but exclusion criteria beyond molecular features preclude enrollment, and another treatment option must be pursued.

Molecular tumor board discussion

Given the increasing number of patients enrolled in the MASTER trial and the related CATCH (Comprehensive Assessment of Clinical Features and Biomarkers to Identify Patients with Advanced or Metastatic Breast Cancer for Marker-Driven Trials in Humans) program for metastatic breast cancer 45 , two MTBs are held at NCT Heidelberg each week that focus on clinical decision-making based on WGS/WES, RNA-seq, and methylome data and last, on average, two hours. Participants include treating physicians, molecular oncologists, pathologists, clinical geneticists, and clinical bioinformaticians. The MTBs are multicentric, including, e.g., participants from all partner sites of the German Cancer Cancer Consortium. Each case discussion begins with a presentation of the clinical history by the treating physician, followed by a summary of the molecular alterations by a clinical bioinformatician. Next, the molecular oncologist responsible for the clinical interpretation of the multiomics profile presents and assigns a level of evidence to the resulting recommendations and concludes with a proposed ranking of treatment options. Finally, clinical geneticists evaluate and classify the germline variants detected, supported by the personal and family histories provided by the treating clinician, followed by a recommendation for genetic counseling if indicated. Similar to conventional, entity-specific tumor boards, MTBs regularly discuss matters pertaining to a patient’s performance status and previously administered therapies. In this context, the ranking of molecularly informed therapy options is particularly important and consequently accounts for a relevant part of the discussion. When available, molecular biomarker-stratified clinical trials are generally prioritized over off-label therapies. However, there are examples where the latter are ranked higher, either when the evidence level is higher or when other criteria, e.g., clinical performance status, prevent the patient from being enrolled in a trial. Due to its multicenter structure, the MTB also provides an ideal forum for the regular dissemination of information about new trials across Germany. Every case presentation, which typically lasts eight to ten minutes, ends with a consensus on the recommended treatment options.

Molecular tumor board report

The MTB report, which summarizes treatment recommendations based on the multiomics data, begins with a summary of the disease course and previous therapy. Over the years, we have developed a structure for reporting treatment recommendations that has proven to be a comprehensive basis for clinical decision-making (Fig. 10 ). Recommendations are organized into blocks, each reflecting a specific therapy approach. They begin with a list of detected biomarkers of response or resistance to the respective treatment, followed by evidence supporting the particular entity-biomarker-drug association. Where available, biomarker-stratified clinical trials are provided. Each block concludes with a summary and synthesis of the evidence for and against a therapeutic strategy. At the end of the report, a table summarizes all recommendations and the prioritization decided on in the MTB. Of the germline variants, only those assigned to ACMG classes 4 and 5 are included. Finally, the consented MTB report is sent to the treating oncologist, who takes further steps regarding patient counseling and therapy implementation.

a Main components of a therapy recommendation block as used in the MASTER MTB report. b Summary and ranking of therapy recommendations with their respective evidence levels. Several factors influence the final choice of therapy, such as its availability, patient preference, side effects, and approval status.

The MASTER trial continues to evolve regarding both the dimensions in which individual tumors are studied and the bioinformatics workflow linked to multidimensional profiling. Emerging diagnostic layers include (phospho)proteomics 46 , drug sensitivity profiling in primary cell lines and organoids, tumor microenvironment analyses, digital pathology, radiomics, and liquid biopsies. The bioinformatics pipeline has recently been extended to include, e.g., elements that allow the prediction of pharmacogenomic risk and immunogenic neoepitopes, as well as tumor telomere status 47 . To develop additional predictive biomarkers based on integrative data analyses, we are increasingly pursuing systems biology approaches, focusing on the functional taxonomy of tumors and signaling pathway activities 48 , 49 that might be exploited therapeutically. Furthermore, we aim to leverage the potential of WGS by exploring alterations in intergenic regions that may have clinical implications.

Due to the inclusion criteria of the MASTER program, i.e., advanced cancers in young adults and rare malignancies, we currently use multiomics profiling in only a fraction of all cancer patients. A critical issue on the way to comprehensive profiling in all cancer patients is the scalability of the diagnostic workflow through automation, especially of high-level operations that follow the primary acquisition and bioinformatic processing of raw data. To this end, we are developing the Knowledge Connector, a customized software suite that supports the four major components of the MTB workflow, i.e., (i) preparation, including the linkage of a patient’s clinical and molecular data with information from external databases and the growing collection of in-house cases and the documentation and evidence grading of treatment recommendations; (ii) presentation of relevant clinical and molecular data, their association, and the resulting recommendations, including supporting evidence; (iii) semi-automated issuing of an MTB report; and (iv) MTB organization, including patient enrollment, participant documentation, and direct links to individual case presentations.

Another issue is that access to molecularly guided off-label therapies may be more likely in rare cancers than in common entities for which more evidence-based standard treatments exist. Notwithstanding this consideration, the potential of multiomics-guided PO to improve patient outcomes is best realized by systematically testing the clinical value of new biomarkers. Hence, a major effort is underway at NCT to develop a portfolio of molecularly stratified clinical trials as part of the NCT Precision Medicine in Oncology (PMO) Program, which currently includes the NCT PMO-1601 (ClinicalTrials.gov Identifier: NCT03110744) 50 , NCT PMO-1602/CRAFT (NCT04551521) 51 , NCT PMO-1603/TOP-ART (NCT03127215) 52 , and NCT PMO-1604 (NCT04410653) protocols.

Multilayered tumor profiling in the MASTER trial

MASTER is a prospective, continuously recruiting, multicenter observational study for biology-guided stratification of adults with rare cancers, including rare subtypes of common entities, using comprehensive molecular profiling, and clinical decision-making in a multidisciplinary MTB 53 . The study is conducted in accordance with the Declaration of Helsinki and the protocol (S-206/2011) was approved by the Ethics Committee of the Medical Faculty of Heidelberg University. The diagnostic workflow (Fig. 11 ) starts with patient registration and obtaining informed consent for sample acquisition and molecular analysis, including tiered consent for germline analysis. Tumor tissue is obtained through resection or biopsy, and a minimum tumor cell content of 20%, evaluated by a pathologist, is required for further analysis. In parallel, a blood sample is collected to enable comparative analysis of the germline genome. Processing of tissue and blood specimens, as well as WGS/WES, RNA-seq, and array-based DNA methylation profiling, are performed under accredited conditions in a dedicated NCT/DKFZ Sample Processing Laboratory and the DKFZ Genomics and Proteomics Core Facility, respectively. Here, minimum coverage in the tumor (WGS, 80x; WES, 120x; RNA-seq, 30 million reads) and control (WGS, 40x; WES, 80x) samples is ensured. Further technical details were reported recently 6 . Methylome data are generated using Infinium MethylationEPIC BeadChip technology (Illumina, #WG-317) following the manufacturer’s instructions. The raw data obtained for a sample can exceed one terabyte and are first processed through an automated bioinformatics workflow established at DKFZ 54 , followed by annotation of molecular alterations by clinical bioinformaticians at NCT and DKFZ using in-house pipelines and various knowledge bases and tools (Table 1 ).

Tumor DNA and RNA obtained from tumor tissue are analyzed by DNA methylation profiling and WGS/WES or RNA-seq, respectively. DNA derived from blood serves as a matched normal control for WGS/WES. Created with Biorender.com.

Reporting summary

Further information on research design is available in the Nature Research Reporting Summary linked to this article.

Data availability

The data presented in Fig. 4 were generated from processed beta values deposited in the Gene Expression Omnibus public repository under accession number GSE140686.

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Acknowledgements

We thank Prof. Christian Kölsche (Institute of Pathology, University of Munich [LMU], Germany) for assistance in creating Fig. 4 .

Open Access funding enabled and organized by Projekt DEAL.

Author information

Andreas Mock

Present address: Institute of Pathology, Ludwig-Maximilians-Universität (LMU) München, Munich, Germany

These authors contributed equally: Andreas Mock, Maria-Veronica Teleanu.

These authors jointly supervised this work: Peter Horak, Hanno Glimm, Stefan Fröhling.

Authors and Affiliations

Division of Translational Medical Oncology, National Center for Tumor Diseases (NCT) Heidelberg and German Cancer Research Center (DKFZ), Heidelberg, Germany

Andreas Mock, Maria-Veronica Teleanu, Simon Kreutzfeldt, Christoph E. Heilig, Hans Martin Singh, Daniel B. Lipka, Marcus Renner, Irfan Ahmed Bhatti, Peter Horak & Stefan Fröhling

Department of Hematology, Oncology and Rheumatology, Heidelberg Unversity Hospital, Heidelberg, Germany

Maria-Veronica Teleanu & Richard F. Schlenk

Computational Oncology Group, Molecular Precision Oncology Program, NCT Heidelberg and DKFZ, Heidelberg, Germany

Jennifer Hüllein, Barbara Hutter, Sebastian Uhrig, Martina Fröhlich & Daniel Hübschmann

Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany; Helmholtz-Zentrum Dresden-Rossendorf (HZDR), Dresden, Germany

Lino Möhrmann, Dorothea Hanf, Irina A. Kerle, Christoph Heining & Hanno Glimm

Translational Medical Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany

Lino Möhrmann, Arne Jahn, Dorothea Hanf, Irina A. Kerle, Evelin Schröck, Christoph Heining & Hanno Glimm

Department of Translational Medical Oncology, National Center for Tumor Diseases/University Cancer Center (NCT/UCC) Dresden, Dresden, Germany

DKFZ, Heidelberg, Germany

Institute for Clinical Genetics, University Hospital Carl Gustav Carus, Technische Universität Dresden and Hereditary Cancer Syndrome Center Dresden, Dresden, Germany

Arne Jahn & Evelin Schröck

Department of Medical Oncology, NCT Heidelberg and Heidelberg University Hospital, Heidelberg, Germany

Hans Martin Singh, Irfan Ahmed Bhatti, Leonidas Apostolidis & Richard F. Schlenk

Institute of Pathology, Heidelberg University Hospital, Heidelberg, Germany

Olaf Neumann & Albrecht Stenzinger

Institute of Pathology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany

Andreas Hartig & Sascha Brückmann

Institute of Human Genetics, Heidelberg University Hospital, Heidelberg, Germany

Steffen Hirsch, Kerstin Grund, Nicola Dikow & Christian P. Schaaf

Translational Cancer Epigenomics, Division of Translational Medical Oncology, NCT Heidelberg and DKFZ, Heidelberg, Germany

Daniel B. Lipka

NCT Trial Center, NCT Heidelberg and DKFZ, Heidelberg, Germany

Richard F. Schlenk

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Contributions

Concept and design: A.M., M-V.T., S.F. Drafting of the manuscript: A.M., M.-V.T., S.F. Bioinformatics: J.H., B.H., M.F., S.U., D.H. Administrative, technical, or material support: S.F., H.G., D.H., E.S., C.P.S., A.S. Supervision: C.P.S, E.S., D.H., P.H., H.G., S.F. All the authors contributed for Critical revision of the manuscript for important intellectual content, acquisition, analysis, or interpretation of data, accountability for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved and final approval of completed version of manuscript.

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Correspondence to Stefan Fröhling .

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C.E.H.: Consulting or advisory board membership: Boehringer Ingelheim; honoraria: Novartis, Roche; research funding: Boehringer Ingelheim. S.F.: Consulting or advisory board membership: Bayer, Illumina, Roche; honoraria: Amgen, Eli Lilly, PharmaMar, Roche; research funding: AstraZeneca, Pfizer, PharmaMar, Roche; travel or accommodation expenses: Amgen, Eli Lilly, Illumina, PharmaMar, Roche.

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Mock, A., Teleanu, MV., Kreutzfeldt, S. et al. NCT/DKFZ MASTER handbook of interpreting whole-genome, transcriptome, and methylome data for precision oncology. npj Precis. Onc. 7 , 109 (2023). https://doi.org/10.1038/s41698-023-00458-w

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German Cancer Consortium ( DKTK ) – A national consortium for translational cancer research

Stefan joos.

1 German Cancer Consortium (DKTK), German Cancer Research Center (DKFZ), Heidelberg, Germany

2 German Cancer Research Center (DKFZ), Heidelberg, Germany

Dirk M. Nettelbeck

Anette reil‐held, katja engelmann, alexandra moosmann, angelika eggert.

3 Charité, Berlin, Germany

Wolfgang Hiddemann

4 Ludwig‐Maximilians‐Universität München, München, Germany

Mechthild Krause

5 University Cancer Center, Dresden, Germany

Christoph Peters

6 Comprehensive Cancer Center Freiburg (CCCF), Germany

Martin Schuler

7 West German Cancer Center, University Hospital Essen, Germany

Klaus Schulze‐Osthoff

8 Medical Faculty, Comprehensive Cancer Center, Tübingen, Germany

Hubert Serve

9 University Cancer Center, University Hospital Frankfurt (UCT), Germany

Wolfgang Wick

10 National Center of Tumor Diseases (NCT), Heidelberg, Germany

11 Heidelberg University Hospital, Heidelberg, Germany

Josef Puchta

Michael baumann.

The German Cancer Consortium (‘Deutsches Konsortium für Translationale Krebsforschung’, DKTK ) is a long‐term cancer consortium, bringing together the German Cancer Research Center ( DKFZ ), Germany's largest life science research center, and the leading University Medical Center‐based Comprehensive Cancer Centers ( CCC s) at seven sites across Germany. DKTK was founded in 2012 following international peer review and has positioned itself since then as the leading network for translational cancer research in Germany. DKTK is long term funded by the German Ministry of Research and Education and the federal states of each DKTK partner site. DKTK acts at the interface between basic and clinical cancer research, one major focus being to generate suitable multisite cooperation structures and provide the basis for including higher numbers of patients and facilitate effective collaborative forward and reverse translational cancer research. The consortium addresses areas of high scientific and medical relevance and develops critical infrastructures, for example, for omics technologies, clinical and research big data exchange and analysis, imaging, and clinical grade drug manufacturing. Moreover, DKTK provides a very attractive environment for interdisciplinary and interinstitutional training and career development for clinician and medical scientists.

Abbreviations

1. background.

Strategies to improve the impact of cancer research for patients have been widely discussed in Germany and Europe over the past two decades. One factor contributing to limited progress is the complexity of the disease cancer, with enormous biological heterogeneities between different tumor classes, tumors within each class in different patients, in each individual tumor (or its metastases) and during time of tumor progression and therapy. Another reason is that translating findings from basic research into the clinic is limited by structural deficits in facilitating interactions between basic and clinical research. Combatting these problems requires a critical mass of patients, resources, and infrastructures that can only be achieved through large‐scale cooperation which overcome the problem of fragmentation of cancer care and cancer research.

1.1. The German Centers for Health Research

In order to improve innovative translational research for the most widespread diseases and to bundle nationwide research activities in the federal system of Germany, six German Centers for Health Research (DZGs) were founded between 2009 and 2012. These are the German Centers for Neurodegenerative Disease (DZNE, 2009), Diabetes Research (DZD, 2009), Infection Research (DZIF, 2012), Lung Research (DZL, 2011), Heart and Vascular Research (DZHK, 2011), and Translational Cancer Research (DKTK, 2012). Each DZG constitutes a network of one of the National Health Research Centers organized within the Helmholtz Association, large university and nonuniversity biomedical research centers and leading university medical centers. Together, the DZGs form an integrated interdisciplinary and interinstitutional network in Germany, involving two thirds of the German university medical centers and all national as well as some other academic research institutions. Strong cooperation and state‐of‐the‐art infrastructures provide an excellent environment for translational and clinical research. The successful development of the DZGs was underscored by recent international reviews and the evaluation by the German Science Council, an advisory body to the government, concluding that the DZG network created the prerequisites for an improved and accelerated translational research of highly relevant disease entities in Germany .

1.2. DKTK: Structure and governance

The members of the DKTK consortium were selected in a multistep procedure by an international expert panel following a competitive call by the German Federal Ministry of Education and Research. In addition to the DKFZ as DKTK's core center and the National Center for Tumor Diseases (NCT) in Heidelberg, the Comprehensive Cancer Centers (CCCs) at the University Medical Centers in Berlin, Dresden, Essen (together with partners from Düsseldorf), Frankfurt (together with partners from Mainz), Freiburg, Tübingen, and Munich with its two university medical centers were selected (Fig.  1 ). All partner sites are engaged in broad portfolios of translational and clinical cancer research, with partner site‐specific research and clinical profiles providing a solid basis for complementarity.

The DKTK core center and partner sites.

The DKTK's annual budget amounts to 28 Mio. Euro, 90% of which is financed by the German Federal Government through the Ministry of Education and Research, and 10% by the federal states of the participating DKTK partner sites. To guarantee its legal and financial structure as well as its long‐term sustainability, DKTK has been constituted as a foundation under public law represented by DKFZ. An important consequence of this structure is that DKTK is funded on a long‐term, institutional basis. The governance structure includes a Steering Committee that represents all member sites by their respective spokesperson, an international Scientific Advisory Board (SAB), and the Foundation Council, comprised of a representative of the German Federal Ministry of Education and Research and a representative of each of the seven German states. A DKTK coordinating bureau, which was established at the core center DKFZ in Heidelberg, supports and manages all scientific, administrative, and financial activities and processes, cooperating closely with the DKFZ administration department and local DKTK coordinators at all partner sites.

2. DKTK: an integrated network for multicenter translational research

The aim of DKTK is to provide an internationally recognized multicenter framework for innovative and highly competitive research in translational oncology. Special emphasis is placed on exploiting synergies by applying intelligent networking, bundling interdisciplinary expertise and critical mass from all partner sites, and strengthening the research profiles at the individual University Medical Centers. The establishment of new professorships, young investigator groups, and cutting‐edge infrastructure strongly support this endeavor.

2.1. Site‐overarching research programs

The DKTK acts at the interface of basic and clinical cancer research. Specific themes are addressed within currently five research programs, overall covering a number of innovative discovery research themes, forward and reverse preclinical programs, and early clinical studies (Table  1 ). DKTK thus contributes to several highly relevant areas of modern cancer research, including identification of molecular biomarkers for tumor classification, risk‐adapted stratification and new treatment paradigms, elucidation of individualized combination therapies and novel diagnostic and therapeutic approaches, such as immunotherapy strategies beyond checkpoint inhibition, and the development of personalized stratification strategies in radiation oncology and imaging.

The DKTK's translational research programs

2.2. Competitive joint funding program

The competitive Joint Funding Program with annual calls represents a key element of DKTK to trigger and expand interactions between the partner sites, create added value, and strengthen DKTK's overall research impact. The program supports innovative, collaborative activities in basic and preclinical research, infrastructure development, and multicenter investigator‐initiated trials (IITs), which are identified in a highly competitive evaluation and selection process involving the SAB. So far, a total of 20 projects and IITs have been supported within DKTK's Joint Funding Program, each involving at least three and often all eight partner sites. Ongoing studies are listed in Table  2 with two recently initiated DKTK‐wide strategic initiatives in the fields of imaging and surgery. DKTK's Joint Funding Program has been crucial for increasing DKTK's productivity and is expected to leverage further funding as well as further innovative and larger scale clinical trials.

DKTK's ongoing joint funding projects and consortium‐wide strategic initiatives

2.3. Research platforms and infrastructures

The DKTK has made strong efforts to set up cutting‐edge joint infrastructures, providing access to highly sophisticated technologies and services.

The Clinical Communication Platform (CCP) has been established as the central hub of DKTK for collecting and exchanging clinical data and biomaterials and thereby provides a bridge across disciplines and institutions. Located at partner‐site Frankfurt, the CCP office organizes task forces for clinical data management, a task force for biobanking, and a team of IT specialists to develop and implement information technology solutions. The CCP has begun to establish long‐term, systematic, smart, and flexible solutions for documenting clinical data, storing and handling biomaterial, and exchanging information among DKTK partner sites. Most importantly, a virtual, joint clinical and biomaterial database has been developed as an advanced IT backbone and interface at all partner sites (‘bridgeheads’). Its major purpose is to provide consortium‐wide access to high‐quality patient data, clinical trial information, and information about stored biomaterials. Currently, to further pursue translational clinical cancer research on a national scale, the unique DKTK‐CCP bridgehead structure is rolled out to non‐DKTK CCCs sponsored by the Deutsche Krebshilfe (German Cancer Aid) within their Comprehensive Cancer Center of Excellence program (which also includes all DKTK partner sites).

Within DKFZ's Cancer Genome Sequencing and Proteome Analysis Platform , a DKTK sequencing facility has been built into a national cancer sequencing core center, which is available to all DKTK scientists and beyond. The platform has facilitated the exchange of expertise among the different sites and created harmonized procedures and common standards, and also offers advanced bioinformatics services by one of the largest and most experienced clusters of biological data scientists. The facility has been instrumental in the stimulation and successful completion of multiple high‐impact research projects. Complementary to the genome sequencing core, a decentralized, harmonized Proteome Platform is currently being established within DKTK to bundle a wide range of proteomics expertise in the network and to make the respective technologies, equipments, and specialized expertises available to researchers of the consortium.

Twice weekly, consortium‐wide molecular tumor boards were established within DKTK based on the CCP and Genome Sequencing Platform. While immunohistochemistry, FISH, or NGS panel‐based molecular diagnostics for discussions in multidisciplinary tumor boards has become clinical routine during the past decade at all DKTK partner sites, DKTK paved the way in Germany for site‐overarching utilization of advanced molecular diagnostics including whole‐genome sequencing for cutting‐edge multicenter trials.

Further unique platforms have strengthened interinstitutional translational and clinical research in the field of radiation oncology and imaging, including all current German particle therapy units and a wide range of preclinical and clinical high‐field magnetic resonance imaging (MRI) und positron emission tomography (PET) units. The powerful RadPlanBio platform, hosted in Dresden and Heidelberg, has been specifically developed by DKTK data scientists for dose‐space‐time resolved data storage, analysis, and exchange over all partner sites. It has been instrumental in various clinical trials and reverse translation projects of DKTK. It is currently being integrated as a module into the CCP and has also been expanded to a number of non‐DKTK sites to allow for further enlarging the patient base for translational studies in radiation oncology and imaging. Additional core services include a GMP facility located in Tübingen for central academic production of clinical‐grade antibodies and (personalized) peptide vaccines which are already being used in several clinical trials across the consortium. A genetic screening and gene editing technology platform helps identify novel targets and develop therapeutic interventions.

2.4. Cooperation management of research programs and platforms

Altogether, more than 1000 researchers are contributing to DKTK's translational research. Effective tools facilitating cooperation between the scientists at the different centers have been developed, for example, scientific workshops, seminars, and an annual retreat of the entire DKTK where achievements and further goals of the translation center are presented and discussed. All programs and platforms within DKTK are represented by coordinators who in addition to the Steering Committee facilitate development and implementation of the overarching DKTK research strategy, both DKTK‐wide and at the individual partner sites.

2.5. Examples of major scientific highlights

A fundamental task of future cancer research will be to address the great complexity that molecular profiling will add to the taxonomy of cancer. DKTK aims to make major contributions in this research area, as can be illustrated best by two highly successful programs: INFORM and MASTER.

The INFORM registry study (INdividualized Therapy FOr Relapsed Malignancies in Childhood) offers comprehensive genomic analyses nationwide to all children with relapsing cancers and provides information about biomarker‐stratified treatment options (Worst et al ., 2016 ). Patients are discussed in INFORM interdisciplinary tumor boards. This program is now interlinked with other European programs on personalized oncology in pediatric cancer and initiating a series of exploratory biomarker‐driven early clinical trials (INFORM‐2).

The aim of the DKTK MASTER program (Molecularly Aided Stratification for Tumor ERadication Research) is multifold (Horak et al ., 2017 ): (a) offering optimal molecular diagnostics by performing exome and transcriptome sequencing in all DKTK adult patients under 50 years of age who have advanced‐stage cancers or in patients with rare cancers; (b) providing all relevant information on the molecular status of every tumor as a stratification tool for treatment selection in individual patients; (c) developing a bioinformatics and systems medicine extension that incorporates bioinformatics predictions and experimental validation in addition to supporting clinical decision making through a physician interface for the interpretation of molecular data; and (d) implementing a program for anticancer targets to fund, support, and coordinate access to novel anticancer agents in IITs. MASTER patients from all partner sites are discussed in a consortium‐wide molecular tumor board, also providing excellent training for young clinician scientists. Furthermore, DKTK MASTER has triggered several, mostly multi‐institutional translational research activities and IITs in the consortium.

A similar approach was successfully applied in several Joint Funding projects in which novel personalized treatment strategies for patients with high‐risk glioma, acute leukemia, and lung cancer have been defined. DKTK is currently extending this paradigmatic approach to more advanced formats of clinical studies. One example is a study of relapsing EGFR‐mutated lung cancer, which involves DKTK centers, centers of the German Center for Lung Research (DZL), the national AIO study group, and four centers from France. This also demonstrates the successful interaction with another German Center of Health Research. Another example is the molecularly stratified umbrella trial NCT Neuro Master Match (N 2 M 2 ), which has started recruiting adult patients with glioma at all DKTK sites (Pfaff et al ., 2018 ; Wick et al ., 2019 ). The clinical impact of this research approach is demonstrated by major contributions, which DKTK research could make to novel tumor classification schemes, as for example, the WHO Classification of Brain Tumors (Louis et al ., 2016 ) or EANO guidelines for the diagnosis and treatment of adult astrocytic and oligodendroglial gliomas (Weller et al ., 2017 ) and ependymal tumors (Ruda et al ., 2018 ).

The DKTK Radiation Oncology Group, with participants from all partner sites, has identified clinically relevant biomarkers for individualizing radiotherapy of HNSCC in various multicenter studies. Biomarkers are being validated in prospective clinical studies, and prospective intervention studies are in preparation. These activities have been facilitated by DKTK's unique RadPlanBio platform, study center, and medicolegal unit.

Further innovative early clinical trials (see https://dktk.dkfz.de/en/research/clinical-trials for an overview), performed within the Joint Funding Program and beyond, include peptide vaccination in patients with leukemia, breast cancer, and brain cancer (including academic GMP production of personalized peptide vaccines), the use and validation of demethylating substances as therapeutic agents across cancer entities, and diagnostic PSMA (prostate‐specific membrane antigen) radiopharmaceuticals for prostate carcinoma imaging.

Research progress within DKTK has been reported in more than 2800 ISI‐cited articles, of which more than 540 were published in journals with impact factors above 10 (as of October 1st, 2018). Thus, DKTK has been highly successful in positioning itself as an important force for translational cancer research in Germany.

3. Novel career and training opportunities in translational oncology

As many other countries worldwide, Germany is facing the general challenge to attract young physicians and scientists into academic careers. Several scientific societies and committees, including the high‐level national Forum Health Research under the auspices of the Federal Ministry of Education and Research, have thoroughly analyzed the situation during the past years. Key recommendations include major investments into training and career perspectives of clinician and medical scientists. The German Centers for Health Research, including DKTK, are among the major addressees for this call for action.

3.1. DKTK professorships and young investigator groups

The strong network research environment as well as the increasing national and international visibility of DKTK attracts an increasing number of high potential trainees and leading advanced clinician and medical scientists to apply for open positions at DKTK partner sites. As a unique asset, DKTK can offer attractive long‐term career perspectives in the field of translational oncology. So far, 11 new joint DKTK full professors have been appointed who are working with a DKTK budget at the joint DKTK translation centers at all partner sites. These top‐class researchers are significantly shaping DKTK's progress in translational oncology research. DKTK has further invested great effort in attracting young talents to establish Young Investigator Groups. The DKTK's funding structure makes it possible to offer a tenure option, which is highly attractive for young scientists interested in translational research, and provide long‐term career perspectives for them. So far, eight new research units for young scientists have been established in the consortium.

3.2. Training and education of clinician and medical scientists

DKTK is making major efforts in developing structures to support translational clinical research for physicians and scientists at all career levels. To promote training and education, the DKTK School of Oncology has been established, offering training programs for clinician and medical scientists. The school significantly promotes interactions between laboratory‐based researchers, medical scientists, and clinician scientists, thereby creating a new translational culture among the next generation of cancer researchers in Germany. The curriculum covers key aspects of translational and interdisciplinary clinical research, including programs on unmet medical need assessment, trial design, medicolegal, and patient‐centered approaches. Clinician scientists and medical scientists undergoing clinical training in multidisciplinary cancer diagnosis and treatment are granted the time to establish a research project and to apply for further funding for their research. Overall, the DKTK School of Oncology (SoO) brings together more than 150 junior researchers at all partner sites, providing them with access to local programs and the DKTK SoO education events. New formats for interaction based on e‐learning and e‐doing tools bring further benefit to the existing network. The International Summer School in Translational Cancer Research, jointly performed with Cancer Core Europe (previously with the Eurocan Platform), attracts up to 60 international clinician scientists and medical scientists annually by offering a 1‐week teaching course on cutting‐edge topics such as innovative aspects of cancer biology, translational research, preventive and clinical research, and the bridging of these research fields.

4. Future directions and european perspective

DKTK has emerged, within only few years, as the leading network for translational cancer research in Germany. Researchers within but also beyond DKTK consider this consortium as a role model for research networking on a national level. Synergies and added value have been achieved in several ways, for example, by offering access to unique technologies, establishing clinical databases, and developing standardized procedures. In this way, quality‐controlled workflows for multicenter preclinical and clinical trials and large cancer registries are available at all partner sites. This is particularly relevant in light of the increased cancer stratification into molecularly distinct subentities.

Of particular importance for the success of DKTK, however, has been the generation of strong team spirit and a stimulating site‐overarching translational ecosystem through effective and inclusive governance, combined with the unique setting offered by the long‐term institutional funding needed for strategic and sustainable translational programs and structures. DKTK will further build on these foundations primarily in three ways:

First, and most straightforward, it will use its research network to contribute to tackling the major challenges in translational cancer research (i.e., personalized molecular diagnosis and therapy, tumor heterogeneity and resistance, immunotherapy, early detection of cancer and minimal residual disease, and turning big data into smart data) by conducting new and innovative research projects.

Second, together with the other DZGs, overarching structures and horizontal research programs will be generated. Thus, strong and very innovative cross‐linking activities can be implemented, for example, related to aging, comorbidity, artificial intelligence, drug development, or prevention. Furthermore, the DZGs including DKTK can build effective interaction platforms with industry or with regulatory authorities to streamline and improve trial regulation.

Third, DKTK will cooperate intensely with other translational cancer research centers and networks on a national and international scale. Within Germany, a number of CCCs with a strong translational research focus have emerged over the past years, which are not member of DKTK. Most of them are funded by an excellence program of the German Cancer Aid. It will be important for DKTK as well as for these centers to interact closely for leveraging the national research potential in this field. One good example in this direction is the access to the CCP also for non‐DKTK centers, but further such open activities need to follow. Whether it will be possible to extent DKTK by new partner sites needs to be further explored with the federal and state governments.

With about 55 000 new cancer patients per year, a joint IT and biobank structure over the consortium, and an increasing number of biologically and clinically well‐characterized patient cohorts as well as a growing number of innovative IITs, DKTK offers important assets for translational cancer research in international partnerships, for example, on rare tumors or highly stratified trials requiring large patient cohorts which are beyond the capacity of national networks. Cancer Core Europe is a potential umbrella for bringing together such national networks (see Eggermont et al ., 2019 ), an option that should be explored within the upcoming European research programs, particularly a potential mission in cancer (Celis and Pavalkis, 2017 ).

Conflict of interest

In the past 5 years, Dr Baumann attended an advisory board meeting of MERCK KGaA (Darmstadt), for which the University of Dresden received a travel grant. He further received funding for his research projects and for educational grants to the University of Dresden by Teutopharma GmbH (2011‐2015), IBA (2016), Bayer AG (2016‐2018), Merck KGaA (2016‐2030), Medipan GmbH (2014‐2018). Dr Baumann, as former chair of OncoRay (Dresden) and present CEO and Scientific Chair of the German Cancer Research Center (DKFZ, Heidelberg), signed/s contracts for his institute(s) and for the staff for research funding and collaborations with a multitude of companies worldwide. For the German Cancer Research Center (DKFZ, Heidelberg) Dr Baumann is on the supervisory boards of HI‐STEM gGmbH (Heidelberg).

For the present study, Dr Baumann confirms that none of the above mentioned funding sources were involved in the study design or materials used, nor in the collection, analysis and interpretation of data nor in the writing of the paper.

Author contributions

All authors contributed to the writing of this article.

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Disclosing progress in cancer survival with less delay

Affiliations.

• 1 Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany.
• 2 Cancer Registry of Rhineland-Palatinate, Institute for Medical Biostatistics, Epidemiology and Informatics, University Medical Center, Johannes Gutenberg University Mainz, Mainz, Germany.
• 3 Saarland Cancer Registry, Saarbrücken, Germany.
• 4 Cancer Registry of Schleswig-Holstein, Lübeck, Germany.
• 5 Division of Preventive Oncology, German Cancer Research Center (DKFZ), and National Center for Tumor Diseases (NCT), Heidelberg, Germany.
• 6 German Cancer Consortium (DKTK), German Cancer Research Center, Heidelberg, Germany.
• PMID: 31785152
• DOI: 10.1002/ijc.32816

Cancer registration plays a key role in monitoring the burden of cancer. However, cancer registry (CR) data are usually made available with substantial delay to ensure best possible completeness of case ascertainment. Here, we investigate empirically with routinely available data whether such a delay is mandatory for survival analyses or whether data can be used earlier to provide more up-to-date survival estimates. We compared distributions of prognostic factors and period relative survival estimates for three population-based CRs in Germany (Schleswig-Holstein (SH), Rhineland-Palatinate (RP), Saarland (SA)) computed on datasets extracted one (DY+1) to 5 years after the year of diagnosis (DY+5; reference). Analyses were conducted for seven cancer sites and various survival analyses scenarios. The proportion of patients registered in the datasets at a given time varied strongly across registries with 57% (SH), 2% (RP) and 26% (SA) registered in DY+1 and >93% in all registries in DY+3. Five-year survival estimates for the most recent three-year period were comparable to estimates from the reference dataset already in DY+1 (mean absolute deviations = 0.2-0.6% units). Deviations >1% units were only observed for pancreatic and lung cancer in RP and leukemia in SA (all ≤1.5% units). For estimates of 1-year survival based on the most recent 1-year period only, slightly longer delays were required, but reasonable estimates were still obtained after 1-2 years, depending on the CR and cancer site. Thus, progress in cancer survival could be disclosed in a more timely manner than commonly practiced despite delays in completeness of registration.

Keywords: cancer; methodology; population-based; registry; survival.

© 2019 The Authors. International Journal of Cancer published by John Wiley & Sons Ltd on behalf of UICC.

Publication types

• Research Support, Non-U.S. Gov't
• Empirical Research
• Germany / epidemiology
• Neoplasms / mortality*
• Survival Analysis
• Time Factors

Opening a new front against pancreatic cancer

A new type of investigational therapeutic in development for pancreatic cancer has shown unprecedented tumor-fighting abilities in preclinical models of the disease, suggesting it has the potential to offer novel treatment options for nearly all pancreatic tumors, a comprehensive study has found.

The inhibitors in this new class of oral medications, being developed by Revolution Medicines Inc., target the oncogenic or active cancer-causing form of RAS proteins (such as KRAS, NRAS, and HRAS). These RAS "oncoproteins" drive up to a third of all human cancers. The research findings -- conducted by a consortium of academic researchers led by Columbia scientists and the scientific team at Revolution Medicines -- were published in a paper appearing today in Nature .

Currently the third leading cause of death from cancer, pancreatic cancer kills about 50,000 people annually in the United States alone. Despite decades of research, the disease continues to stymie drug developers and oncologists. What's especially frustrating is that scientists know exactly what causes most cases at the cellular level. "For over four decades, we have known that there's one particular RAS protein, called KRAS, that's mutated and drives about 95% of all pancreatic ductal adenocarcinoma cases, and we've had no direct tools to attack it for most of that time," says Kenneth Olive, PhD, associate professor of medicine at Columbia University's Vagelos College of Physicians and Surgeons and Herbert Irving Comprehensive Cancer Center, one of the study's senior authors.

When the study's co-senior author, Mallika Singh, PhD, vice president for translational research at Revolution Medicines, told Olive the company had invented a class of inhibitors that had the potential to target all RAS mutations, he was incredulous. "My immediate reaction was skepticism," says Olive. "But I was curious, and we quickly established a collaboration."

Preclinical studies soon launched in the Olive lab at Columbia, led by Urszula Wasko, a PhD student in the molecular pharmacology graduate program. Early pilot experiments with RMC-7977 were remarkably effective. "We immediately knew we were working with something entirely different," says Olive. At the same time, Olive and Revolution Medicines worked to bring together pancreatic cancer experts from other academic institutions, including the University of Pennsylvania, Dana-Farber Cancer Institute, University of North Carolina at Chapel Hill, and Memorial Sloan Kettering. "Rather than compete against one another, we established a consortium and agreed to share data in real time. That was transformative," says Olive.

Pancreatic cancer researchers have developed many different preclinical models of the disease over the years, each with its own strengths and weaknesses. Rather than pick one, the expanded team tested RMC-7977 in all of them. "By unleashing a consortium of scientists on this problem, we were able to examine active RAS inhibition in every major class of model for pancreatic cancer, and this inhibitor performed really well in all," says Olive.

The preclinical tumor model Olive's lab has long favored is widely recognized for its broad resistance to treatment. "RMC-7977 as a single agent outperformed the best combination regimen that has ever been reported in the literature in that model system," he says, adding that it's the first time he's ever seen tumors routinely get smaller in those systems. Other models the consortium tested yielded similar results.

Because RMC-7977 also inhibits wild-type RAS proteins essential to the health of many normal cells, the scientists also carefully examined normal tissues in the treated animals. This work showed that tumor cells are uniquely sensitive to the inhibitor, while the impact in normal cells was minimal.

Though the initial responses in preclinical tumor models to the inhibitor were impressive, Olive hastens to point out that the tumors were not eliminated.

"In almost every case, the tumor came back," he says. In tissue culture, the investigators identified another oncogene, called MYC, that was altered in most of the resistant tumors, then developed a combination treatment that was effective against tumor cells that had developed resistance to the active RAS inhibitor. Those results suggest a combinatorial approach that is worth exploring in patients in the future.

In a field with a long history of failed drug development efforts, the new results are cause for optimism, Olive says. "I've been working on pancreatic cancer for almost 20 years, and I've never seen preclinical results like these. I think there is a real chance this approach will help change the standard of care for pancreatic cancer patients, but only clinical trials can determine that. I'm excited that Columbia is one of many institutions participating in the clinical development of these new agents."

• Pancreatic Cancer
• Brain Tumor
• Lung Cancer
• Breast Cancer
• Ovarian Cancer
• Colon Cancer
• Prostate Cancer
• Renal cell carcinoma
• Monoclonal antibody therapy
• Breast cancer
• Prostate cancer
• Drug discovery
• Tumor suppressor gene

Story Source:

Materials provided by Columbia University Irving Medical Center . Note: Content may be edited for style and length.

Journal Reference :

• Urszula N. Wasko, Jingjing Jiang, Tanner C. Dalton, Alvaro Curiel-Garcia, A. Cole Edwards, Yingyun Wang, Bianca Lee, Margo Orlen, Sha Tian, Clint A. Stalnecker, Kristina Drizyte-Miller, Marie Menard, Julien Dilly, Stephen A. Sastra, Carmine F. Palermo, Marie C. Hasselluhn, Amanda R. Decker-Farrell, Stephanie Chang, Lingyan Jiang, Xing Wei, Yu C. Yang, Ciara Helland, Haley Courtney, Yevgeniy Gindin, Karl Muonio, Ruiping Zhao, Samantha B. Kemp, Cynthia Clendenin, Rina Sor, William P. Vostrejs, Priya S. Hibshman, Amber M. Amparo, Connor Hennessey, Matthew G. Rees, Melissa M. Ronan, Jennifer A. Roth, Jens Brodbeck, Lorenzo Tomassoni, Basil Bakir, Nicholas D. Socci, Laura E. Herring, Natalie K. Barker, Junning Wang, James M. Cleary, Brian M. Wolpin, John A. Chabot, Michael D. Kluger, Gulam A. Manji, Kenneth Y. Tsai, Miroslav Sekulic, Stephen M. Lagana, Andrea Califano, Elsa Quintana, Zhengping Wang, Jacqueline A. M. Smith, Matthew Holderfield, David Wildes, Scott W. Lowe, Michael A. Badgley, Andrew J. Aguirre, Robert H. Vonderheide, Ben Z. Stanger, Timour Baslan, Channing J. Der, Mallika Singh, Kenneth P. Olive. Tumor-selective activity of RAS-GTP inhibition in pancreatic cancer . Nature , 2024; DOI: 10.1038/s41586-024-07379-z

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