Interrogating gene expression in tumor can identify up- and downregulated molecular targets of cancer drugs. Here we report the results of prospective clinical investigation of using RNA sequencing analysis for personalized cancer therapy. Transcriptomic profiles were analyzed using Oncobox platform that identifies altered expression of drug target genes and molecular pathways and builds a personalized rating of targeted therapeutics. Totally, 239 adult solid cancer patients were enrolled: 135 received cancer drug therapy, others received palliative treatment or radiotherapy, or died before therapy started. Oncobox recommended drugs were prescribed in 59 % of the cases receiving therapy. Otherwise, patients received non-targeted therapy or targeted therapy predicted as inefficient by Oncobox (controls). Patients in the Oncobox group were significantly pre-treated compared to controls, but we observed a longer progression-free survival (PFS) trend in the Oncobox group. Furthermore, post-hoc analysis revealed that time between biopsy collection and tumor profiling significantly impacts Oncobox predictive capacity. Excluding patient cases with biopsy obtained more than 7 months before sequencing lead to a significant difference in PFS between Oncobox and control groups with hazard ratio of 0.45 (p-value = 0.023). These results suggest that transcriptomic profiling provides clinically relevant therapeutic match and can improve disease control rate in solid cancers.
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http://dx.doi.org/10.1016/j.compbiomed.2025.109716 | DOI Listing |
Comput Biol Med
January 2025
Oncobox Ltd., Moscow, Russia; World-Class Research Center "Digital Biodesign and Personalized Healthcare", Sechenov First Moscow State Medical University, Moscow, Russia; Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Moscow, 117997, Russia; PathoBiology Group, European Organization for Research and Treatment of Cancer (EORTC), Brussels, Belgium. Electronic address:
Interrogating gene expression in tumor can identify up- and downregulated molecular targets of cancer drugs. Here we report the results of prospective clinical investigation of using RNA sequencing analysis for personalized cancer therapy. Transcriptomic profiles were analyzed using Oncobox platform that identifies altered expression of drug target genes and molecular pathways and builds a personalized rating of targeted therapeutics.
View Article and Find Full Text PDFFront Immunol
December 2024
Institute of Personalized Oncology, I.M. Sechenov First Moscow State Medical University, Moscow, Russia.
Background: Immune checkpoint inhibitors (ICIs) treatment have shown high efficacy for about 15 cancer types. However, this therapy is only effective in 20-30% of cancer patients. Thus, the precise biomarkers of ICI response are an urgent need.
View Article and Find Full Text PDFCancers (Basel)
November 2024
Institute for Personalized Oncology, World-Class Research Center "Digital Biodesign and Personalized Healthcare", I.M. Sechenov First Moscow State Medical University, 119991 Moscow, Russia.
Background: In clinical practice, various methods are used to identify gene rearrangements in tumor samples, ranging from "classic" techniques, such as IHC, FISH, and RT-qPCR, to more advanced highly multiplexed approaches, such as NanoString technology and NGS panels. Each of these methods has its own advantages and disadvantages, but they share the drawback of detecting only a restricted (although sometimes quite extensive) set of preselected biomarkers. At the same time, whole transcriptome sequencing (WTS, RNAseq) can, in principle, be used to detect gene fusions while simultaneously analyzing an incomparably wide range of tumor characteristics.
View Article and Find Full Text PDFTher Adv Med Oncol
November 2024
I.M. Sechenov First Moscow State Medical University, Moscow 119991, Russia.
Background: Glioblastoma (GBM) is the most aggressive and lethal central nervous system (CNS) tumor. The treatment strategy is mainly surgery and/or radiation therapy, both combined with adjuvant temozolomide (TMZ) chemotherapy. Historically, methylation of gene promoter is used as the major biomarker predicting individual tumor response to TMZ.
View Article and Find Full Text PDFFront Genet
October 2024
Laboratory for Translational Genomic Bioinformatics, Moscow Institute of Physics and Technology, Dolgoprudny, Russia.
Introduction: The differential ratio of nonsynonymous to synonymous nucleotide substitutions (dN/dS) is a common measure of the rate of structural evolution in proteincoding genes. In addition, we recently suggested that the proportion of transposable elements in gene promoters that host functional genomic sites serves as a marker of the rate of regulatory evolution of genes. Such functional genomic regions may include transcription factor binding sites and modified histone binding loci.
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