Search

Background: The impact of tumour mutational burden (TMB) on outcome with molecularly matched therapy is unknown. Higher TMB could predict resistance to molecularly matched therapy through co-occurring driver mutations., Methods: One hundred and four patients with advanced cancers underwent molecular profiling in the DKTK-MASTER program. Fifty-five patients received systemic therapy excluding immunotherapy. Patients with molecularly matched (n = 35) or non-molecularly informed therapy (n = 20) were analysed for TMB and survival. Results were validated in an independent cohort of patients receiving molecularly matched (n = 68) or non-molecularly informed therapy (n = 40). Co-occurring driver mutations and TMB were analysed in the exploratory cohort and The Cancer Genome Atlas (TCGA) datasets., Results: Patients were stratified by the median TMB of 1.67 mutations per Megabase (mut/Mb) of 35 patients receiving molecularly matched therapy into TMB-high or TMB-low groups. Median overall survival (4 months [95% CI, 3.3-7.6] versus 12.8 months [95% CI, 10-not reached], p < 0.001) and progression-free survival (1.8 months [95% CI, 1.1-3.7] versus 7.9 months [95% CI, 2.8-17.0], p = 0.003) were significantly shorter in the TMB-high group compared to the TMB-low group. In the validation cohort, shorter OS and PFS were identified in the TMB-high group (TMB cut-off of 4 mut/Mb) treated with molecularly matched therapy. No differences were observed in patients receiving non-molecularly informed systemic therapy. A significant correlation between co-occurring driver mutations and TMB (n = 104, r = 0.78 [95% CI, 0.68-0.85], p < 0.001) was found in the exploratory cohort as well as the majority (24/33) of TCGA studies., Conclusion: A high TMB was associated with unfavourable outcome in patients receiving molecularly matched therapy, indicating untargeted resistance pathways. Therefore, TMB should be further investigated as a predictive biomarker in precision oncology programs., Competing Interests: Declaration of Competing Interest Till de Bortoli, Manuela Benary, Mario Lamping, Reinhold Schäfer and Frederick Klauschen report no potential conflicts of interest. Peter Horak reported consulting or advisory board membership for Platomics and honoraria from Platomics, Roche. Sebastian Stintzing has received honoraria/consulting or advisory role from Amgen, Bayer, Lilly, Merck KGaA, MSD, Pierre Fabre, Roche, Sanofi, Servier, Taiho Pharmaceuticals, Takeda, Boehringer Ingelheim, research funding from Merck Serono, Pierre Fabre, Roche Molecular Diagnostics, travel, accommodation and expenses support from Amgen, Bayer, Lilly, Merck KgaA, Pierre Fabre, Roche, Sanofi, Sirtex Medical and Takeda. Inge Tinhofer reports honoraria/consulting or advisory role for Merck KgaA and MerckSerono. Serge Leyvraz reports consulting or advisory role and travel expenses support from Bayer. Ulrich Keller reports a consulting role for Roche, Janssen-Cilag, Takeda, BMS, Gilead, Hexal, Pfizer, Astra-Zeneca, Pentixapharm and honoraria from Gilead, Amgen, Novartis, BMS, Roche, Takeda, MSD, as well as research funding from Celgene, Takeda, BMS, Roche, Astra-Zeneka, Novartis, MSD, Janssen-Cilag, Pfizer. Other support was declared from Roche, BMS, Gilead, Takeda, Janssen-Cilag and Celgene. Albrecht Stenzinger reported Advisory Board/Speaker’s Bureau from Aignostics, Astra Zeneca, AGCT, Bayer, BMS, Eli Lilly, Illumina, Incyte, Janssen, MSD, Novartis, Pfizer, Roche, Seattle Genetics, Takeda, Thermo Fisher and research grants from Bayer, BMS, Chugai, Incyte. Stefan Fröhling reported consulting or advisory board membership from Bayer, Illumina, Roche; honoraria: Amgen, Eli Lilly, PharmaMar, Roche and research funding from AstraZeneca, Pfizer, PharmaMar, Roche, as well as travel or accommodation expenses support from Amgen, Eli Lilly, Illumina, PharmaMar, Roche. Razelle Kurzrock has received research funding from Biological Dynamics, Boehringer Ingelheim, Debiopharm, Foundation Medicine, Genentech, Grifols, Guardant, Incyte, Konica Minolta, Medimmune, Merck Serono, Omniseq, Pfizer, Sequenom, Takeda, and TopAlliance; as well as consultant and/or speaker fees and/or advisory board for Actuate Therapeutics, AstraZeneca, Bicara Therapeutics, Biological Dynamics, EISAI, EOM Pharmaceuticals, Iylon, Merck, NeoGenomics, Neomed, Pfizer, Prosperdtx, Roche, TD2/Volastra, Turning Point Therapeutics, X-Biotech and has an equity interest in CureMatch Inc., CureMetrix, and IDbyDNA; She also serves on the Board of CureMatch and CureMetrix,and is a co-founder of CureMatch. Ulrich Keilholz has received advisory board/speaker bureau, trial support, research collaboration or research support from Amgen, AstraZeneca, BMS, Boehringer Ingelheim, Glycotope, Innate, Lilly, Medimmune, MerckSerono, MSD/Merck, Novartis, Pfizer, Roche/Genentech and Sirtex. Damian Rieke has received consultant and/or advisory board and/or speaker fees from Bayer, Bristol-Myers Squibb and Lilly. Ivan Jelas has received consultant and/or advisory board and/or speaker fees from Bristol-Myers Squibb, Merck and Roche., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

The architectural chromatin factor high-mobility group AT-hook 2 (HMGA2) is causally involved in several human malignancies and pathologies. HMGA2 is not expressed in most normal adult somatic cells, which renders the protein an attractive drug target. An established cell-based compound library screen identified the fibroblast growth factor receptor (FGFR) inhibitor PD173074 as an antagonist of HMGA2-mediated transcriptional reporter gene activation. We determined that PD173074 binds the C-terminus of HMGA2 and interferes with functional coordination of the three AT-hook DNA-binding domains mediated by the C-terminus. The HMGA2-antagonistic effect of PD173074 on transcriptional activation may therefore result from an induced altered DNA-binding mode of HMGA2. PD173074 as a novel HMGA2-specific antagonist could trigger the development of derivates with enhanced attributes and clinical potential., (© 2023 Federation of European Biochemical Societies.)

The COSMIC database (version 94) lists 576 genes in the Cancer Gene Census which have a defined function as drivers of malignancy (oncogenes) or as tumour suppressors (Tier 1). In addition, there are 147 genes with similar functions, but which are less well characterised (Tier 2). Furthermore, next-generation sequencing projects in the context of precision oncology activities are constantly discovering new ones. Since cancer genes differ from their wild-type precursors in numerous molecular and biochemical properties and exert significant differential effects on downstream processes, simple assays that can uncover oncogenic or anti-oncogenic functionality are desirable and may precede more sophisticated analyses. We describe simple functional assays for PTPN11 (protein-tyrosine phosphatase, non-receptor-type 11)/SHP2 mutants, which are typically found in RASopathies and exhibit potential oncogenic activity. We have also designed a functional test for lysyl oxidase (LOX), a prototypical class II tumour suppressor gene whose loss of function may contribute to neoplastic transformation by RAS oncogenes. Moreover, we applied this test to analyse three co-regulated, RAS-responsive genes for transformation-suppressive activity. The integration of these tests into systems biology studies will contribute to a better understanding of cellular networks in cancer., (Copyright © 2021 Elsevier Ltd. All rights reserved.)

Background: Reliable and reproducible interpretation of molecular aberrations constitutes a bottleneck of precision medicine. Evidence-based decision management systems may improve rational therapy recommendations. To cope with an increasing amount of complex molecular data in the clinical care of patients with cancer, we established a workflow for the interpretation of molecular analyses., Methods: A specialized physician screened results from molecular analyses for potential biomarkers, irrespective of the diagnostic modality. Best available evidence was retrieved and categorized through establishment of an in-house database and interrogation of publicly available databases. Annotated biomarkers were ranked using predefined evidence levels and subsequently discussed at a molecular tumour board (MTB), which generated treatment recommendations. Subsequent translation into patient treatment and clinical outcomes were followed up., Results: One hundred patients were discussed in the MTB between January 2016 and May 2017. Molecular data were obtained for 70 of 100 patients (50 whole exome/RNA sequencing, 18 panel sequencing, 2 immunohistochemistry (IHC)/microsatellite instability analysis). The MTB generated a median of two treatment recommendations each for 63 patients. Thirty-nine patients were treated: 6 partial responses and 12 stable diseases were achieved as best responses. Genetic counselling for germline events was recommended for seven patients., Conclusion: The development of an evidence-based workflow allowed for the clinical interpretation of complex molecular data and facilitated the translation of personalized treatment strategies into routine clinical care. The high number of treatment recommendations in patients with comprehensive genomic data and promising responses in patients treated with combination therapy warrant larger clinical studies., Competing Interests: Conflict of interest statement M.L., M.B., C.M., E.B., K.J., S.B., K.K., S.O., R.S., and F.K. reported no conflicts of interest. S.L. received support and consulting compensation from Bayer. M.L.Y., T.K. and M.S. are employees of Alacris Theranostics. D.L. is currently an employee of AstraZeneca and reported employment, stock ownership and patents/royalties/intellectual property for her spouse at Bayer. C.S. received honoraria from Merck Serono, I.T. took part in an advisory board by Merck Serono. D.B. is a shareholder of MicroDiscovery GmbH. U.K. reported research funding from Merck Sharp & Dohme, Novartis, Bristol-Myers Squibb, Roche, GlaxoSmithKline, AstraZeneca and Merck Serono and served as a consultant or as a member of the advisory board with Merck Sharp & Dohme, Bristol-Myers Squibb, AstraZeneca, Merck Serono and GlaxoSmithKline. D.T.R. received payments as a consultant for Alacris Theranostics and honoraria from Bristol-Myers Squibb., (Copyright © 2019 Elsevier Ltd. All rights reserved.)

Background: Diagnosis and treatment decisions in cancer increasingly depend on a detailed analysis of the mutational status of a patient's genome. This analysis relies on previously published information regarding the association of variations to disease progression and possible interventions. Clinicians to a large degree use biomedical search engines to obtain such information; however, the vast majority of scientific publications focus on basic science and have no direct clinical impact. We develop the Variant-Information Search Tool (VIST), a search engine designed for the targeted search of clinically relevant publications given an oncological mutation profile., Results: VIST indexes all PubMed abstracts and content from ClinicalTrials.gov. It applies advanced text mining to identify mentions of genes, variants and drugs and uses machine learning based scoring to judge the clinical relevance of indexed abstracts. Its functionality is available through a fast and intuitive web interface. We perform several evaluations, showing that VIST's ranking is superior to that of PubMed or a pure vector space model with regard to the clinical relevance of a document's content., Conclusion: Different user groups search repositories of scientific publications with different intentions. This diversity is not adequately reflected in the standard search engines, often leading to poor performance in specialized settings. We develop a search engine for the specific case of finding documents that are clinically relevant in the course of cancer treatment. We believe that the architecture of our engine, heavily relying on machine learning algorithms, can also act as a blueprint for search engines in other, equally specific domains. VIST is freely available at https://vist.informatik.hu-berlin.de/.

The hallmarks of cancer capture the most essential phenotypic characteristics of malignant transformation and progression. Although numerous factors involved in this multi-step process are still unknown to date, an ever-increasing number of mutated/altered candidate genes are being identified within large-scale cancer genomic projects. Therefore, investigators need to be aware of available and appropriate techniques capable of determining characteristic features of each hallmark. We review the methods tailored to experimental cancer researchers to evaluate cell proliferation, programmed cell death, replicative immortality, induction of angiogenesis, invasion and metastasis, genome instability, and reprogramming of energy metabolism. Selecting the ideal method is based on the investigator's goals, available equipment and also on financial constraints. Multiplexing strategies enable a more in-depth data collection from a single experiment - obtaining several results from a single procedure reduces variability and saves time and relative cost, leading to more robust conclusions compared to a single end point measurement. Each hallmark possesses characteristics that can be analyzed by immunoblot, RT-PCR, immunocytochemistry, immunoprecipitation, RNA microarray or RNA-seq. In general, flow cytometry, fluorescence microscopy, and multiwell readers are extremely versatile tools and, with proper sample preparation, allow the detection of a vast number of hallmark features. Finally, we also provide a list of hallmark-specific genes to be measured in transcriptome-level studies. Although our list is not exhaustive, we provide a snapshot of the most widely used methods, with an emphasis on methods enabling the simultaneous evaluation of multiple hallmark features., (Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.)

The small GTP-binding proteins HRAS, KRAS and NRAS belong to a family of oncoproteins associated with many types of human cancer. Signal transduction processes initiated at receptor tyrosine kinases converge on RAS proteins which serve as molecular switches linking upstream signals with the transcriptional machinery. RAS proteins interact with a number of effector proteins that in turn activate the Raf/MEK/ERK pathway, the PI3K/PKB/Akt pathway, the RalGDS/Ral pathway and other downstream pathways. Mutations in RAS lock the protein in its active form. Chronic activation of the KRAS isoform is the basis for resistance toward antibody therapies targeting receptor tyrosine kinases, as an upstream stimulus through growth factor receptor-mediated activation is no longer required. However, the complexity of the RAS signaling system necessitates the search for additional activating mechanisms as well as biomarkers associated with pathway activation. During recent years, several RAS pathway-related gene signatures were identified, mostly by microarray-based gene expression profiling of normal versus RAS-transformed cells. The signatures can serve as a source of common biomarkers indicating functionally relevant downstream effects of the RAS signaling system. In searching for new markers, we compared the gene expression signatures compiled in 24 independent studies. We analyzed differentially regulated genes recovered in microarray studies on human specimens to discriminate paired normal and tumor tissues. Although the overlap between individual studies was low, this meta-analysis revealed Kruppel-like factor 5 (KLF5), the CD44 antigen and members of the epidermal growth factor (EGR)-family as common downstream effectors of RAS.

A limited number of somatic mutations are known to trigger malignancy via chronic activation of cellular signaling pathways. High-throughput analysis of gene expression in cancer cells has revealed a plethora of deregulated genes by far exceeding the number of known genetic alterations. Targeted tumor therapy takes advantage of deregulated signaling in cancer. However, cancer cells may evade successful therapy, e.g., targeting oncogenic kinases, due to mutation of the target protein or to resistance mechanisms acting downstream of or parallel to the therapeutic block. To improve therapy and molecular diagnostics, we need detailed information on the wiring of pathway components and targets that ultimately execute the malignant properties of advanced tumors. Here we review work on Ras-mediated signal transduction and Ras pathway-responsive targets. We introduce the concept of signal-regulated transcriptional modules comprising groups of target genes responding to individual branches of the pathway network. Furthermore, we discuss functional approaches based on RNA interference for elucidating critical nodes in oncogenic signaling and the targets essential for malignancy.