Oncobox Bioinformatical Platform for Selecting Potentially Effective Combinations of Target Cancer Drugs Using High-Throughput Gene Expression Data

Kantelhardt

et al. 2020

Cancers

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Background: Inevitable recurrence after radiochemotherapy is the major problem in the treatment of glioblastoma, the most prevalent type of adult brain malignancy. Glioblastomas are notorious for a high degree of intratumor heterogeneity manifest through a diversity of cell types and molecular patterns. The current paradigm of understanding glioblastoma recurrence is that cytotoxic therapy fails to target effectively glioma stem cells. Recent advances indicate that therapy-driven molecular evolution is a fundamental trait associated with glioblastoma recurrence. There is a growing body of evidence indicating that intratumor heterogeneity, longitudinal changes in molecular biomarkers and specific impacts of glioma stem cells need to be taken into consideration in order to increase the accuracy of molecular diagnostics still relying on readouts obtained from a single tumor specimen. Methods: This study integrates a multisampling strategy, longitudinal approach and complementary transcriptomic investigations in order to identify transcriptomic traits of recurrent glioblastoma in whole-tissue specimens of glioblastoma or glioblastoma stem cells. In this study, 128 tissue samples of 44 tumors including 23 first diagnosed, 19 recurrent and 2 secondary recurrent glioblastomas were analyzed along with 27 primary cultures of glioblastoma stem cells by RNA sequencing. A novel algorithm was used to quantify longitudinal changes in pathway activities and model efficacy of anti-cancer drugs based on gene expression data. Results: Our study reveals that intratumor heterogeneity of gene expression patterns is a fundamental characteristic of not only newly diagnosed but also recurrent glioblastomas. Evidence is provided that glioblastoma stem cells recapitulate intratumor heterogeneity, longitudinal transcriptomic changes and drug sensitivity patterns associated with the state of recurrence. Conclusions: Our results provide a transcriptional rationale for the lack of significant therapeutic benefit from temozolomide in patients with recurrent glioblastoma. Our findings imply that the spectrum of potentially effective drugs is likely to differ between newly diagnosed and recurrent glioblastomas and underscore the merits of glioblastoma stem cells as prognostic models for identifying alternative drugs and predicting drug response in recurrent glioblastoma. With the majority of recurrent glioblastomas being inoperable, glioblastoma stem cell models provide the means of compensating for the limited availability of recurrent glioblastoma specimens.

Section: Introductionmentioning

confidence: 99%

Intratumoral Heterogeneity and Longitudinal Changes in Gene Expression Predict Differential Drug Sensitivity in Newly Diagnosed and Recurrent Glioblastoma

Kim

Kantelhardt

et al. 2020

Cancers

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“…We then calculated pathway activation levels of 3125 molecular pathways using Oncobox software (Sorokin et al 2018) and tested them for differential activation between the responder and non-responder tumors (Table S2). None of the pathways passed FDR threshold of 0.05, but the most significantly differential pathway according to Wilcoxon rank sum test was the Nectin adhesion Pathway (positive regulation of JNK cascade).…”

Section: Differentially Regulated Genes and Molecular Pathwaysmentioning

confidence: 99%

“…Among the other, the molecular data are linked with the information on clinical response to ramucirumab or its combinations. We used bioinformatic platform Oncobox (Sorokin et al 2018;Poddubskaya et al 2019a;Buzdin et al 2019a) to model ramucirumab efficiency based on RNA sequencing data and compared the output results with the known tumor response information. Oncobox algorithm builds personalized rating of target drugs for individual cancer patients.…”

Section: Introductionmentioning

confidence: 99%

RNA sequencing profiles and diagnostic signatures linked with response to ramucirumab in gastric cancer

Cold Spring Harb Mol Case Stud

Poddubskaya

Baranova

et al. 2020

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Gastric cancer (GC) is the fifth cancer type by associated mortality. Proportion of early diagnosis is low, and most patients are diagnosed at the advanced stages. First line therapy standardly includes fluoropyrimidines and platinum compounds with trastuzumab for HER2positive cases. For the recurrent disease there are several alternative options including ramucirumab, a monoclonal therapeutic antibody that inhibits VEGF-mediated tumor angiogenesis by binding with VEGFR2, alone or in combination with other cancer drugs. However, overall response rate rate following ramucirumab or its combinations is 30-80% of the patients, suggesting that personalization of drug prescription is needed to increase efficacy of treatment. We report here original tumor RNA sequencing profiles for 15 advanced GC patients linked with data on clinical response to ramucirumab or its combinations. Three genes showed differential expression in the tumors-responders vs non-responders: CHRM3, LRFN1 and TEX15. Of them, CHRM3 was upregulated in the responders. Using bioinformatic platform Oncobox we simulated ramucirumab efficiency and compared output model results with actual tumor response data. An agreement was observed between predicted and real clinical outcomes (AUC ≥ 0.7). These results suggest that RNA sequencing may be used to personalize prescription of ramucirumab for GC and indicate on potential molecular mechanisms underlying ramucirumab resistance. The RNA sequencing profiles obtained here are fully compatible with the previously published Oncobox Atlas of Normal Tissue Expression (ANTE) data.

“…Cross-comparison of genes expressed differentially in different GSC lines after radiation and preparation of textual and graphical outputs were performed by using the Whitehead BaRC (http://jura.wi.edu) and the Venn Diagramm (http://bioinformatics.psb.ugent.be) software. Pathway analyses were performed by using the Oncobox software described in [45]. For generation of the Oncobox database, which in total consists of 3125 molecular pathways open access pathway catalogues BioCarta [doi:10.1089/152791601750294344], KEGG OC [doi:10.1093/nar/gks1239], [46], Reactome [doi:10.1093/nar/gkn653], [47] and PID [doi:10.1093/nar/gkv1351], [48] were used.…”

Section: Microarrays and Bioinformatics Analysesmentioning

confidence: 99%

Diversity of Clinically Relevant Outcomes Resulting from Hypofractionated Radiation in Human Glioma Stem Cells Mirrors Distinct Patterns of Transcriptomic Changes

Kalasauskas

Sprang

et al. 2020

Cancers

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Hypofractionated radiotherapy is the mainstay of the current treatment for glioblastoma. However, the efficacy of radiotherapy is hindered by the high degree of radioresistance associated with glioma stem cells comprising a heterogeneous compartment of cell lineages differing in their phenotypic characteristics, molecular signatures, and biological responses to external signals. Reconstruction of radiation responses in glioma stem cells is necessary for understanding the biological and molecular determinants of glioblastoma radioresistance. To date, there is a paucity of information on the longitudinal outcomes of hypofractionated radiation in glioma stem cells. This study addresses long-term outcomes of hypofractionated radiation in human glioma stem cells by using a combinatorial approach integrating parallel assessments of the tumor-propagating capacity, stemness-associated properties, and array-based profiling of gene expression. The study reveals a broad spectrum of changes in the tumor-propagating capacity of glioma stem cells after radiation and finds association with proliferative changes at the onset of differentiation. Evidence is provided that parallel transcriptomic patterns and a cumulative impact of pathways involved in the regulation of apoptosis, neural differentiation, and cell proliferation underly similarities in tumorigenicity changes after radiation.