Using proteomic and transcriptomic data to assess activation of intracellular molecular pathways

Buzdin, Anton; Tkachev, Victor; Zolotovskaia, Marianna; Garazha, Andrew; Moshkovskii, Sergei A.; Borisov, Nicolas; Гайфуллин, Нуршат; Suntsova, Maria

doi:10.1016/bs.apcsb.2021.02.005

Cited by 17 publications

(12 citation statements)

References 217 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…One of its major strengths is stability of final output data, which are not biased/distorted upon each new round of harmonization. Thus, it may become valuable for finding condition-specific features, e.g., for the assessment of tumor-specific gene expression or pathway activation patterns (Buzdin et al, 2020(Buzdin et al, , 2021. This type of analysis will be especially important when the experimental (case) and control samples come from the different datasets, which is a common situation in human physiology research.…”

Section: Discussionmentioning

confidence: 99%

Shambhala‐2: A Protocol for Uniformly Shaped Harmonization of Gene Expression Profiles of Various Formats

et al. 2022

Self Cite

View full text Add to dashboard Cite

Uniformly shaped harmonization of gene expression profiles is central for the simultaneous comparison of multiple gene expression datasets. It is expected to operate with the gene expression data obtained using various experimental methods and equipment, and to return harmonized profiles in a uniform shape. Such uniformly shaped expression profiles from different initial datasets can be further compared directly. However, current harmonization techniques have strong limitations that prevent their broad use for bioinformatic applications. They can either operate with only up to two datasets/platforms or return data in a dynamic format that will be different for every comparison under analysis. This also does not allow for adding new data to the previously harmonized dataset(s), which complicates the analysis and increases calculation costs. We propose here a new method termed Shambhala‐2 that can transform multi‐platform expression data into a universal format that is identical for all harmonizations made using this technique. Shambhala‐2 is based on sample‐by‐sample cubic conversion of the initial expression dataset into a preselected shape of the reference definitive dataset. Using 8390 samples of 12 healthy human tissue types and 4086 samples of colorectal, kidney, and lung cancer tissues, we verified Shambhala‐2's capacity in restoring tissue‐specific expression patterns for seven microarray and three RNA sequencing platforms. Shambhala‐2 performed well for all tested combinations of RNAseq and microarray profiles, and retained gene‐expression ranks, as evidenced by high correlations between different single‐ or aggregated gene expression metrics in pre‐ and post‐Shambhalized samples, including preserving cancer‐specific gene expression and pathway activation features. © 2022 Wiley Periodicals LLC. Basic Protocol: Shambhala‐2 harmonizer Alternate Protocol 1: Linear Shambhala/Shambhala‐1 Alternate Protocol 2: Alternative (flexible‐format and uniformly shaped) normalization methods Support Protocol 1: Watermelon multisection (WM) Support Protocol 2: Calculation of cancer‐to‐normal log‐fold‐change (LFC) and pathway activation level (PAL)

show abstract

Section: Discussionmentioning

confidence: 99%

Shambhala‐2: A Protocol for Uniformly Shaped Harmonization of Gene Expression Profiles of Various Formats

et al. 2022

Self Cite

View full text Add to dashboard Cite

show abstract

“…RNA sequencing is a method that has several advantages over DNA-based approaches. This approach has been proven informative for analyzing the expression level of various genes associated with the effectiveness of the response to anticancer drugs, 215 activation or inhibition of various molecular pathways. 202 , 216 , 217 Approaches for the analysis of the mutational load of tumors according to full transcriptome analysis are also described.…”

Section: Experimental Methods For Identification Of Fusion Oncogenesmentioning

confidence: 99%

Clinically relevant fusion oncogenes: detection and practical implications

et al. 2022

Self Cite

View full text Add to dashboard Cite

Mechanistically, chimeric genes result from DNA rearrangements and include parts of preexisting normal genes combined at the genomic junction site. Some rearranged genes encode pathological proteins with altered molecular functions. Those which can aberrantly promote carcinogenesis are called fusion oncogenes. Their formation is not a rare event in human cancers, and many of them were documented in numerous study reports and in specific databases. They may have various molecular peculiarities like increased stability of an oncogenic part, self-activation of tyrosine kinase receptor moiety, and altered transcriptional regulation activities. Currently, tens of low molecular mass inhibitors are approved in cancers as the drugs targeting receptor tyrosine kinase (RTK) oncogenic fusion proteins, that is, including ALK, ABL, EGFR, FGFR1-3, NTRK1-3, MET, RET, ROS1 moieties. Therein, the presence of the respective RTK fusion in the cancer genome is the diagnostic biomarker for drug prescription. However, identification of such fusion oncogenes is challenging as the breakpoint may arise in multiple sites within the gene, and the exact fusion partner is generally unknown. There is no gold standard method for RTK fusion detection, and many alternative experimental techniques are employed nowadays to solve this issue. Among them, RNA-seq-based methods offer an advantage of unbiased high-throughput analysis of only transcribed RTK fusion genes, and of simultaneous finding both fusion partners in a single RNA-seq read. Here we focus on current knowledge of biology and clinical aspects of RTK fusion genes, related databases, and laboratory detection methods.

show abstract

“…Oncobox test used included whole-exome sequencing (WES) and RNA sequencing (RNAseq) of tumor biosample. WES data are used to identify diagnostic mutations and to calculate tumor mutation burden, whereas RNAseq information helps identifying molecular drug targets that are differentially expressed in the tumor, and also differentially regulated molecular pathways compared to the healthy tissues (16,18). Annotated Oncobox pathway database was recently published (19).…”

Section: Case Presentationmentioning

confidence: 99%

RNA Sequencing for Personalized Treatment of Metastatic Leiomyosarcoma: Case Report

Seryakov¹,

Магомедова²,

Suntsova³

et al. 2021

Front. Oncol.

Self Cite

View full text Add to dashboard Cite

Uterine leiomyosarcoma (UL) is a rare malignant tumor that develops from the uterine smooth muscle tissue. Due to the low frequency and lack of sufficient data from clinical trials there is currently no effective treatment that is routinely accepted for UL. Here we report a case of a 65-years-old female patient with metastatic UL, who progressed on ifosfamide and doxorubicin therapy and developed severe hypertensive crisis after administration of second line pazopanib, which lead to treatment termination. Rapid progression of the tumor stressed the need for the alternative treatment options. We performed RNA sequencing and whole exome sequencing profiling of the patient’s biopsy and applied Oncobox bioinformatic algorithm to prioritize targeted therapeutics. No clinically relevant mutations associated with drug efficiencies were found, but the Oncobox transcriptome analysis predicted regorafenib as the most effective targeted treatment option. Regorafenib administration resulted in a complete metabolic response which lasted for 10 months. In addition, RNA sequencing analysis revealed a novel cancer fusion transcript of YWHAE gene with fusion partner JAZF1. Several chimeric transcripts for YWHAE and JAZF1 genes were previously found in uterine neoplasms and some of them were associated with tumor prognosis. However, their combination was detected in this study for the first time. Taken together, these findings evidence that RNA sequencing may complement analysis of clinically relevant mutations and enhance management of oncological patients by suggesting putative treatment options.

show abstract

Using proteomic and transcriptomic data to assess activation of intracellular molecular pathways

Cited by 17 publications

References 217 publications

Shambhala‐2: A Protocol for Uniformly Shaped Harmonization of Gene Expression Profiles of Various Formats

Shambhala‐2: A Protocol for Uniformly Shaped Harmonization of Gene Expression Profiles of Various Formats

Clinically relevant fusion oncogenes: detection and practical implications

RNA Sequencing for Personalized Treatment of Metastatic Leiomyosarcoma: Case Report

Contact Info

Product

Resources

About