Oncobox Method for Scoring Efficiencies of Anticancer Drugs Based on Gene Expression Data

Tkachev, Victor; Sorokin, Maxim; Garazha, Andrew; Borisov, Nicolas; Buzdin, Anton

doi:10.1007/978-1-0716-0138-9_17

Cited by 23 publications

(34 citation statements)

References 47 publications

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“…Considering that MGMT is the major molecular determinant of chemoresistance to TMZ in GB [3,43], the latter finding suggests that recGBs may be less responsive to TMZ than ndGBs. To validate this assumption, we modelled the responsiveness to TMZ by calculating a metric termed the balanced efficiency score (BES), which is a numeric measure of drug response that can be predicted using expression levels of genes, the function of which is essential in determining tumor sensitivity to a given drug [47]. Demonstrating the adequacy of the BES ranking approach, a subset of ndGBs for which the information on progression free survival (PFS) was available (n = 16) showed a statistically significantly association between BES-TMZ > 0 and increased PFS (HR = 0.29, 95% CI: 0.088-0.96, p = 0.043) ( Figure 7C).…”

Section: Recgb-derived Gscs Retain Transcriptomic Patterns Associatedmentioning

confidence: 99%

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

Kim

Sorokin

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.

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Section: Recgb-derived Gscs Retain Transcriptomic Patterns Associatedmentioning

confidence: 99%

“…Efficiencies of anticancer target drugs (ATDs) were simulated based on individual gene expression profiles according to Tkachev et al using as a metric the balanced efficiency score (BES) calculated for every ATD [47].…”

Section: In Silico Modeling Of Drug Efficienciesmentioning

confidence: 99%

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

Kim

Sorokin

Kantelhardt

et al. 2020

Cancers

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“…where PAL is Pathway activation level, n is number of genes in a pathway, average_gene_expression_cancer is geometrically averaged gene expression value in all samples of a given cohort (treatment responders or non-responders), and average_gene_expression_norm is geometrically averaged normalized gene expression value in control samples.Ranking of target cancer drugs using Balanced Efficiency Scores (BES) was performed as described previously (Poddubskaya et al 2019b;Buzdin et al 2018;Tkachev et al 2020). The Oncobox software returned personalized list of target drugs in descent order of predicted efficacy.…”

Section: Molecular Pathway Analysis and Ranking Of Target Drugsmentioning

confidence: 99%

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

Sorokin

Poddubskaya

Baranova

et al. 2020

Cold Spring Harb Mol Case Stud

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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.

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“…A number of PALs were found to be characteristic for cancer drug response ( Zhu et al, 2015 ) and sensitivity to X-ray irradiation ( Sorokin et al, 2018 ), asthma ( Alexandrova et al, 2016 ), Hutchinson-Gilford progeria ( Aliper et al, 2015 ), macular degeneration ( Makarev et al, 2014 ), fibrosis ( Makarev et al, 2016 ), viral infection ( Buzdin et al, 2016 ), and aging ( Aliper et al, 2016 ). Algorithms were developed to convert pathway activation data into the optimized selection of cancer drugs ( Artemov et al, 2015 ; Tkachev et al, 2020 ) that had several recent clinical applications ( Poddubskaya et al, 2018 , 2019a , b ; Sorokin et al, 2020b ). However, those studies used manually curated/annotated pathways and were, therefore, limited by the overall number (~10 or ~100) of pathways under analysis.…”

Section: Introductionmentioning

confidence: 99%

Algorithmic Annotation of Functional Roles for Components of 3,044 Human Molecular Pathways

et al. 2021

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Current methods of high-throughput molecular and genomic analyses enabled to reconstruct thousands of human molecular pathways. Knowledge of molecular pathways structure and architecture taken along with the gene expression data can help interrogating the pathway activation levels (PALs) using different bioinformatic algorithms. In turn, the pathway activation profiles can characterize molecular processes, which are differentially regulated and give numeric characteristics of the extent of their activation or inhibition. However, different pathway nodes may have different functions toward overall pathway regulation, and calculation of PAL requires knowledge of molecular function of every node in the pathway in terms of its activator or inhibitory role. Thus, high-throughput annotation of functional roles of pathway nodes is required for the comprehensive analysis of the pathway activation profiles. We proposed an algorithm that identifies functional roles of the pathway components and applied it to annotate 3,044 human molecular pathways extracted from the Biocarta, Reactome, KEGG, Qiagen Pathway Central, NCI, and HumanCYC databases and including 9,022 gene products. The resulting knowledgebase can be applied for the direct calculation of the PALs and establishing large scale profiles of the signaling, metabolic, and DNA repair pathway regulation using high throughput gene expression data. We also provide a bioinformatic tool for PAL data calculations using the current pathway knowledgebase.

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Oncobox Method for Scoring Efficiencies of Anticancer Drugs Based on Gene Expression Data

Cited by 23 publications

References 47 publications

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

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

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

Algorithmic Annotation of Functional Roles for Components of 3,044 Human Molecular Pathways

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