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Zolotovskaia M, Kovalenko M, Pugacheva P, Tkachev V, Simonov A, Sorokin M, Seryakov A, Garazha A, Gaifullin N, Sekacheva M, Zakharova G, Buzdin AA. Algorithmically Reconstructed Molecular Pathways as the New Generation of Prognostic Molecular Biomarkers in Human Solid Cancers. Proteomes 2023; 11:26. [PMID: 37755705 PMCID: PMC10535530 DOI: 10.3390/proteomes11030026] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2023] [Revised: 08/18/2023] [Accepted: 08/22/2023] [Indexed: 09/28/2023] Open
Abstract
Individual gene expression and molecular pathway activation profiles were shown to be effective biomarkers in many cancers. Here, we used the human interactome model to algorithmically build 7470 molecular pathways centered around individual gene products. We assessed their associations with tumor type and survival in comparison with the previous generation of molecular pathway biomarkers (3022 "classical" pathways) and with the RNA transcripts or proteomic profiles of individual genes, for 8141 and 1117 samples, respectively. For all analytes in RNA and proteomic data, respectively, we found a total of 7441 and 7343 potential biomarker associations for gene-centric pathways, 3020 and 2950 for classical pathways, and 24,349 and 6742 for individual genes. Overall, the percentage of RNA biomarkers was statistically significantly higher for both types of pathways than for individual genes (p < 0.05). In turn, both types of pathways showed comparable performance. The percentage of cancer-type-specific biomarkers was comparable between proteomic and transcriptomic levels, but the proportion of survival biomarkers was dramatically lower for proteomic data. Thus, we conclude that pathway activation level is the advanced type of biomarker for RNA and proteomic data, and momentary algorithmic computer building of pathways is a new credible alternative to time-consuming hypothesis-driven manual pathway curation and reconstruction.
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Affiliation(s)
- Marianna Zolotovskaia
- Laboratory for Translational Genomic Bioinformatics, Moscow Institute of Physics and Technology (State University), 141701 Dolgoprudny, Russia
- Omicsway Corp., Walnut, CA 91789, USA
- Laboratory of Clinical and Genomic Bioinformatics, I.M. Sechenov First Moscow State Medical University, 119048 Moscow, Russia
| | - Maks Kovalenko
- Laboratory for Translational Genomic Bioinformatics, Moscow Institute of Physics and Technology (State University), 141701 Dolgoprudny, Russia
| | - Polina Pugacheva
- Laboratory for Translational Genomic Bioinformatics, Moscow Institute of Physics and Technology (State University), 141701 Dolgoprudny, Russia
| | | | - Alexander Simonov
- Laboratory for Translational Genomic Bioinformatics, Moscow Institute of Physics and Technology (State University), 141701 Dolgoprudny, Russia
- Omicsway Corp., Walnut, CA 91789, USA
| | - Maxim Sorokin
- Laboratory for Translational Genomic Bioinformatics, Moscow Institute of Physics and Technology (State University), 141701 Dolgoprudny, Russia
- Laboratory of Clinical and Genomic Bioinformatics, I.M. Sechenov First Moscow State Medical University, 119048 Moscow, Russia
- PathoBiology Group, European Organization for Research and Treatment of Cancer (EORTC), 1200 Brussels, Belgium
| | | | | | - Nurshat Gaifullin
- Department of Pathology, Faculty of Medicine, Lomonosov Moscow State University, 119991 Moscow, Russia
| | - Marina Sekacheva
- Laboratory of Clinical and Genomic Bioinformatics, I.M. Sechenov First Moscow State Medical University, 119048 Moscow, Russia
| | - Galina Zakharova
- Laboratory of Clinical and Genomic Bioinformatics, I.M. Sechenov First Moscow State Medical University, 119048 Moscow, Russia
| | - Anton A. Buzdin
- Laboratory for Translational Genomic Bioinformatics, Moscow Institute of Physics and Technology (State University), 141701 Dolgoprudny, Russia
- PathoBiology Group, European Organization for Research and Treatment of Cancer (EORTC), 1200 Brussels, Belgium
- World-Class Research Center “Digital Biodesign and Personalized Healthcare”, Sechenov First Moscow State Medical University, 119048 Moscow, Russia
- Laboratory of Systems Biology, Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, 117997 Moscow, Russia
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2
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Sorokin M, Buzdin AA, Guryanova A, Efimov V, Suntsova MV, Zolotovskaia MA, Koroleva EV, Sekacheva MI, Tkachev VS, Garazha A, Kremenchutckaya K, Drobyshev A, Seryakov A, Gudkov A, Alekseenko IV, Rakitina O, Kostina MB, Vladimirova U, Moisseev A, Bulgin D, Radomskaya E, Shestakov V, Baklaushev VP, Prassolov V, Shegay PV, Li X, Poddubskaya EV, Gaifullin N. Large-scale assessment of pros and cons of autopsy-derived or tumor-matched tissues as the norms for gene expression analysis in cancers. Comput Struct Biotechnol J 2023; 21:3964-3986. [PMID: 37635765 PMCID: PMC10448432 DOI: 10.1016/j.csbj.2023.07.040] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2023] [Revised: 07/17/2023] [Accepted: 07/30/2023] [Indexed: 08/29/2023] Open
Abstract
Normal tissues are essential for studying disease-specific differential gene expression. However, healthy human controls are typically available only in postmortal/autopsy settings. In cancer research, fragments of pathologically normal tissue adjacent to tumor site are frequently used as the controls. However, it is largely underexplored how cancers can systematically influence gene expression of the neighboring tissues. Here we performed a comprehensive pan-cancer comparison of molecular profiles of solid tumor-adjacent and autopsy-derived "healthy" normal tissues. We found a number of systemic molecular differences related to activation of the immune cells, intracellular transport and autophagy, cellular respiration, telomerase activation, p38 signaling, cytoskeleton remodeling, and reorganization of the extracellular matrix. The tumor-adjacent tissues were deficient in apoptotic signaling and negative regulation of cell growth including G2/M cell cycle transition checkpoint. We also detected an extensive rearrangement of the chemical perception network. Molecular targets of 32 and 37 cancer drugs were over- or underexpressed, respectively, in the tumor-adjacent norms. These processes may be driven by molecular events that are correlated between the paired cancer and adjacent normal tissues, that mostly relate to inflammation and regulation of intracellular molecular pathways such as the p38, MAPK, Notch, and IGF1 signaling. However, using a model of macaque postmortal tissues we showed that for the 30 min - 24-hour time frame at 4ºC, an RNA degradation pattern in lung biosamples resulted in an artifact "differential" expression profile for 1140 genes, although no differences could be detected in liver. Thus, such concerns should be addressed in practice.
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Affiliation(s)
- Maksim Sorokin
- Moscow Institute of Physics and Technology, Dolgoprudny, Moscow Region 141701, Russia
- Omicsway Corp., Walnut, CA 91789, USA
- I.M. Sechenov First Moscow State Medical University, Moscow 119991, Russia
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Moscow 117997, Russia
| | - Anton A. Buzdin
- Moscow Institute of Physics and Technology, Dolgoprudny, Moscow Region 141701, Russia
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Moscow 117997, Russia
- World-Class Research Center "Digital biodesign and personalized healthcare", Sechenov First Moscow State Medical University, Moscow, Russia
- PathoBiology Group, European Organization for Research and Treatment of Cancer (EORTC), Brussels, Belgium
| | - Anastasia Guryanova
- Moscow Institute of Physics and Technology, Dolgoprudny, Moscow Region 141701, Russia
| | - Victor Efimov
- World-Class Research Center "Digital biodesign and personalized healthcare", Sechenov First Moscow State Medical University, Moscow, Russia
| | - Maria V. Suntsova
- Moscow Institute of Physics and Technology, Dolgoprudny, Moscow Region 141701, Russia
- I.M. Sechenov First Moscow State Medical University, Moscow 119991, Russia
| | - Marianna A. Zolotovskaia
- Moscow Institute of Physics and Technology, Dolgoprudny, Moscow Region 141701, Russia
- Omicsway Corp., Walnut, CA 91789, USA
| | - Elena V. Koroleva
- Moscow Institute of Physics and Technology, Dolgoprudny, Moscow Region 141701, Russia
| | - Marina I. Sekacheva
- Moscow Institute of Physics and Technology, Dolgoprudny, Moscow Region 141701, Russia
- I.M. Sechenov First Moscow State Medical University, Moscow 119991, Russia
| | - Victor S. Tkachev
- Omicsway Corp., Walnut, CA 91789, USA
- Oncobox Ltd., Moscow 121205, Russia
| | - Andrew Garazha
- Omicsway Corp., Walnut, CA 91789, USA
- Oncobox Ltd., Moscow 121205, Russia
| | | | - Aleksey Drobyshev
- I.M. Sechenov First Moscow State Medical University, Moscow 119991, Russia
| | | | - Alexander Gudkov
- I.M. Sechenov First Moscow State Medical University, Moscow 119991, Russia
| | - Irina V. Alekseenko
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Moscow 117997, Russia
- Institute of Molecular Genetics of National Research Centre "Kurchatov Institute", 2, Kurchatov Square, Moscow 123182, Russian
- FSBI "National Medical Research Center for Obstetrics, Gynecology and Perinatology named after Academician V.I. Kulakov" Ministry of Healthcare of the Russian Federation, Moscow 117198, Russia
| | - Olga Rakitina
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Moscow 117997, Russia
| | - Maria B. Kostina
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Moscow 117997, Russia
| | - Uliana Vladimirova
- I.M. Sechenov First Moscow State Medical University, Moscow 119991, Russia
- Oncobox Ltd., Moscow 121205, Russia
| | - Aleksey Moisseev
- I.M. Sechenov First Moscow State Medical University, Moscow 119991, Russia
| | - Dmitry Bulgin
- Research Institute of Medical Primatology, 177 Mira str., Veseloye, Sochi 354376, Russia
| | - Elena Radomskaya
- Research Institute of Medical Primatology, 177 Mira str., Veseloye, Sochi 354376, Russia
| | - Viktor Shestakov
- Research Institute of Medical Primatology, 177 Mira str., Veseloye, Sochi 354376, Russia
| | | | - Vladimir Prassolov
- Center for Precision Genome Editing and Genetic Technologies for Biomedicine, Engelhardt Institute of Molecular Biology, Russian Academy of Sciences, 32 Vavilova str., Moscow 119991, Russia
| | - Petr V. Shegay
- National Medical Research Radiological Center of the Ministry of Health of the Russian Federation, 249036 Obninsk, Russia
| | - Xinmin Li
- UCLA Technology Center for Genomics & Bioinformatics, Department of Pathology & Laboratory Medicine, 650 Charles E Young Dr., Los Angeles, CA 90095, USA
| | | | - Nurshat Gaifullin
- Department of Physiology and General Pathology, Faculty of Medicine, Lomonosov Moscow State University, Moscow 119991, Russia
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Pan-cancer antagonistic inhibition pattern of ATM-driven G2/M checkpoint pathway vs other DNA repair pathways. DNA Repair (Amst) 2023; 123:103448. [PMID: 36657260 DOI: 10.1016/j.dnarep.2023.103448] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2022] [Revised: 12/22/2022] [Accepted: 01/08/2023] [Indexed: 01/15/2023]
Abstract
DNA repair mechanisms keep genome integrity and limit tumor-associated alterations and heterogeneity, but on the other hand they promote tumor survival after radiation and genotoxic chemotherapies. We screened pathway activation levels of 38 DNA repair pathways in nine human cancer types (gliomas, breast, colorectal, lung, thyroid, cervical, kidney, gastric, and pancreatic cancers). We took RNAseq profiles of the experimental 51 normal and 408 tumor samples, and from The Cancer Genome Atlas and Clinical Proteomic Tumor Analysis Consortium databases - of 500/407 normal and 5752/646 tumor samples, and also 573 normal and 984 tumor proteomic profiles from Proteomic Data Commons portal. For all the samplings we observed a congruent trend that all cancer types showed inhibition of G2/M arrest checkpoint pathway compared to the normal samples, and relatively low activities of p53-mediated pathways. In contrast, other DNA repair pathways were upregulated in most of the cancer types. The G2/M checkpoint pathway was statistically significantly downregulated compared to the other DNA repair pathways, and this inhibition was strongly impacted by antagonistic regulation of (i) promitotic genes CCNB and CDK1, and (ii) GADD45 genes promoting G2/M arrest. At the DNA level, we found that ATM, TP53, and CDKN1A genes accumulated loss of function mutations, and cyclin B complex genes - transforming mutations. These findings suggest importance of activation for most of DNA repair pathways in cancer progression, with remarkable exceptions of G2/M checkpoint and p53-related pathways which are downregulated and neutrally activated, respectively.
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Sorokin M, Rabushko E, Rozenberg JM, Mohammad T, Seryakov A, Sekacheva M, Buzdin A. Clinically relevant fusion oncogenes: detection and practical implications. Ther Adv Med Oncol 2022; 14:17588359221144108. [PMID: 36601633 PMCID: PMC9806411 DOI: 10.1177/17588359221144108] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2022] [Accepted: 11/22/2022] [Indexed: 12/28/2022] Open
Abstract
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.
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Affiliation(s)
| | - Elizaveta Rabushko
- Moscow Institute of Physics and Technology,
Dolgoprudny, Moscow Region, Russia,I.M. Sechenov First Moscow State Medical
University, Moscow, Russia
| | | | - Tharaa Mohammad
- Moscow Institute of Physics and Technology,
Dolgoprudny, Moscow Region, Russia
| | | | - Marina Sekacheva
- I.M. Sechenov First Moscow State Medical
University, Moscow, Russia
| | - Anton Buzdin
- Moscow Institute of Physics and Technology,
Dolgoprudny, Moscow Region, Russia,I.M. Sechenov First Moscow State Medical
University, Moscow, Russia,Shemyakin-Ovchinnikov Institute of Bioorganic
Chemistry, Moscow, Russia,PathoBiology Group, European Organization for
Research and Treatment of Cancer (EORTC), Brussels, Belgium
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5
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Sorokin M, Zolotovskaia M, Nikitin D, Suntsova M, Poddubskaya E, Glusker A, Garazha A, Moisseev A, Li X, Sekacheva M, Naskhletashvili D, Seryakov A, Wang Y, Buzdin A. Personalized targeted therapy prescription in colorectal cancer using algorithmic analysis of RNA sequencing data. BMC Cancer 2022; 22:1113. [PMCID: PMC9623986 DOI: 10.1186/s12885-022-10177-3] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2021] [Accepted: 09/26/2022] [Indexed: 12/24/2022] Open
Abstract
Background: Overall survival of advanced colorectal cancer (CRC) patients remains poor, and gene expression analysis could potentially complement detection of clinically relevant mutations to personalize CRC treatments. Methods: We performed RNA sequencing of formalin-fixed, paraffin-embedded (FFPE) cancer tissue samples of 23 CRC patients and interpreted the data obtained using bioinformatic method Oncobox for expression-based rating of targeted therapeutics. Oncobox ranks cancer drugs according to the efficiency score calculated using target genes expression and molecular pathway activation data. The patients had primary and metastatic CRC with metastases in liver, peritoneum, brain, adrenal gland, lymph nodes and ovary. Two patients had mutations in NRAS, seven others had mutated KRAS gene. Patients were treated by aflibercept, bevacizumab, bortezomib, cabozantinib, cetuximab, crizotinib, denosumab, panitumumab and regorafenib as monotherapy or in combination with chemotherapy, and information on the success of totally 39 lines of therapy was collected. Results: Oncobox drug efficiency score was effective biomarker that could predict treatment outcomes in the experimental cohort (AUC 0.77 for all lines of therapy and 0.91 for the first line after tumor sampling). Separately for bevacizumab, it was effective in the experimental cohort (AUC 0.87) and in 3 independent literature CRC datasets, n = 107 (AUC 0.84–0.94). It also predicted progression-free survival in univariate (Hazard ratio 0.14) and multivariate (Hazard ratio 0.066) analyses. Difference in AUC scores evidences importance of using recent biosamples for the prediction quality. Conclusion: Our results suggest that RNA sequencing analysis of tumor FFPE materials may be helpful for personalizing prescriptions of targeted therapeutics in CRC. Supplementary Information The online version contains supplementary material available at 10.1186/s12885-022-10177-3.
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Affiliation(s)
- Maxim Sorokin
- grid.448878.f0000 0001 2288 8774I.M. Sechenov First Moscow State Medical University, 119991 Moscow, Russia ,grid.18763.3b0000000092721542Moscow Institute of Physics and Technology, 141701 Moscow Region, Russia ,OmicsWay Corp, 91789 Walnut, CA USA
| | - Marianna Zolotovskaia
- grid.18763.3b0000000092721542Moscow Institute of Physics and Technology, 141701 Moscow Region, Russia
| | - Daniil Nikitin
- OmicsWay Corp, 91789 Walnut, CA USA ,grid.418853.30000 0004 0440 1573Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, 117997 Moscow, Russia
| | - Maria Suntsova
- grid.448878.f0000 0001 2288 8774World-Class Research Center “Digital biodesign and personalized healthcare”, Sechenov First Moscow State Medical University, 119991 Moscow, Russia
| | - Elena Poddubskaya
- grid.448878.f0000 0001 2288 8774I.M. Sechenov First Moscow State Medical University, 119991 Moscow, Russia ,Clinical Center Vitamed, 121309 Moscow, Russia
| | - Alexander Glusker
- grid.448878.f0000 0001 2288 8774I.M. Sechenov First Moscow State Medical University, 119991 Moscow, Russia
| | | | - Alexey Moisseev
- grid.448878.f0000 0001 2288 8774I.M. Sechenov First Moscow State Medical University, 119991 Moscow, Russia
| | - Xinmin Li
- grid.19006.3e0000 0000 9632 6718Department of Pathology and Laboratory Medicine, University of California, 90095 Los Angeles, CA USA
| | - Marina Sekacheva
- grid.448878.f0000 0001 2288 8774World-Class Research Center “Digital biodesign and personalized healthcare”, Sechenov First Moscow State Medical University, 119991 Moscow, Russia
| | - David Naskhletashvili
- grid.466904.90000 0000 9092 133XN.N. Blokhin Russian Cancer Research Center, 115478 Moscow, Russia
| | | | - Ye Wang
- grid.410645.20000 0001 0455 0905Core Laboratory, The Affiliated Qingdao Central Hospital of Qingdao University, Qingdao, China
| | - Anton Buzdin
- grid.18763.3b0000000092721542Moscow Institute of Physics and Technology, 141701 Moscow Region, Russia ,grid.418853.30000 0004 0440 1573Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, 117997 Moscow, Russia ,grid.448878.f0000 0001 2288 8774World-Class Research Center “Digital biodesign and personalized healthcare”, Sechenov First Moscow State Medical University, 119991 Moscow, Russia
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6
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Experimentally Deduced Criteria for Detection of Clinically Relevant Fusion 3′ Oncogenes from FFPE Bulk RNA Sequencing Data. Biomedicines 2022; 10:biomedicines10081866. [PMID: 36009413 PMCID: PMC9405289 DOI: 10.3390/biomedicines10081866] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2022] [Revised: 07/15/2022] [Accepted: 07/29/2022] [Indexed: 11/25/2022] Open
Abstract
Drugs targeting receptor tyrosine kinase (RTK) oncogenic fusion proteins demonstrate impressive anti-cancer activities. The fusion presence in the cancer is the respective drug prescription biomarker, but their identification is challenging as both the breakpoint and the exact fusion partners are unknown. RNAseq offers the advantage of finding both fusion parts by screening sequencing reads. Paraffin (FFPE) tissue blocks are the most common way of storing cancer biomaterials in biobanks. However, finding RTK fusions in FFPE samples is challenging as RNA fragments are short and their artifact ligation may appear in sequencing libraries. Here, we annotated RNAseq reads of 764 experimental FFPE solid cancer samples, 96 leukemia samples, and 2 cell lines, and identified 36 putative clinically relevant RTK fusions with junctions corresponding to exon borders of the fusion partners. Where possible, putative fusions were validated by RT-PCR (confirmed for 10/25 fusions tested). For the confirmed 3′RTK fusions, we observed the following distinguishing features. Both moieties were in-frame, and the tyrosine kinase domain was preserved. RTK exon coverage by RNAseq reads upstream of the junction site were lower than downstream. Finally, most of the true fusions were present by more than one RNAseq read. This provides the basis for automatic annotation of 3′RTK fusions using FFPE RNAseq profiles.
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7
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Sarma RJ, Subbarayan S, Zohmingthanga J, Chenkual S, Zomuana T, Lalruatfela ST, Pautu JL, Maitra A, Kumar NS. Transcriptome analysis reveals SALL4 as a prognostic key gene in gastric adenocarcinoma. J Egypt Natl Canc Inst 2022; 34:11. [PMID: 35284980 DOI: 10.1186/s43046-022-00108-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2021] [Accepted: 01/28/2022] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Stomach adenocarcinoma (STAD) dominates 80-90% of gastric cancer (GC). Over the years, it has been realized that the identification of the genes responsible for gastric carcinogenesis is essential to understand the biomarker discovery. METHODS This study aims to identify candidate genes for biomarker discovery in STAD. RNA-Seq was performed on three paired tumor-normal and one unpaired tumor samples from four GC patients and investigated for differentially expressed genes (DEGs) using DESeq2. Gene set enrichment analysis were performed. The DEGs were compared with two STAD microarray datasets available on Gene Expression Omnibus (GEO) database. Survival study (OS) were performed using KM-Plotter on the common genes between all the datasets. RESULTS Totally, 148 DEGs were identified, wherein 55 genes were upregulated and 93 genes were downregulated with |log2foldchange| > 1 and Benjamini-Hochberg (BH) Adjusted P value < 0.01. Cell adhesion molecule (CAM) Pathway was found to be the most significant among the upregulated genes. Gastric acid secretion and mineral absorption pathways were the most significant pathways among the downregulated genes. Comparison with two GEO datasets followed by OS analysis revealed two upregulating genes, APOC1 and SALL4 with prognostic significance. CONCLUSION Upregulation of APOC1 is associated with marginal overall survival (OS) and SALL4 over-expression was associated with the poor OS using KM-Plotter during 5 years data period. Our study suggests that SALL4 could be a promising biomarker candidate in STAD.
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Affiliation(s)
- Ranjan Jyoti Sarma
- Department of Biotechnology, Mizoram University, Aizawl, Mizoram, 796 004, India
| | | | | | - Saia Chenkual
- Department of Surgery, Civil Hospital Aizawl, Aizawl, Mizoram, 796 001, India
| | - Thomas Zomuana
- Department of Surgery, Civil Hospital Aizawl, Aizawl, Mizoram, 796 001, India
| | | | - Jeremy L Pautu
- Department of Medical Oncology, Mizoram State Cancer Institute, Aizawl, Mizoram, 796017, India
| | - Arindam Maitra
- National Institute of Biomedical Genomics, Kalyani, West Bengal, 741251, India.
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8
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Gudkov A, Shirokorad V, Kashintsev K, Sokov D, Nikitin D, Anisenko A, Borisov N, Sekacheva M, Gaifullin N, Garazha A, Suntsova M, Koroleva E, Buzdin A, Sorokin M. Gene Expression-Based Signature Can Predict Sorafenib Response in Kidney Cancer. Front Mol Biosci 2022; 9:753318. [PMID: 35359606 PMCID: PMC8963850 DOI: 10.3389/fmolb.2022.753318] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2021] [Accepted: 01/28/2022] [Indexed: 01/07/2023] Open
Abstract
Sorafenib is a tyrosine kinase inhibitory drug with multiple molecular specificities that is approved for clinical use in second-line treatments of metastatic and advanced renal cell carcinomas (RCCs). However, only 10–40% of RCC patients respond on sorafenib-containing therapies, and personalization of its prescription may help in finding an adequate balance of clinical efficiency, cost-effectiveness, and side effects. We investigated whether expression levels of known molecular targets of sorafenib in RCC can serve as prognostic biomarker of treatment response. We used Illumina microarrays to profile RNA expression in pre-treatment formalin-fixed paraffin-embedded (FFPE) samples of 22 metastatic or advanced RCC cases with known responses on next-line sorafenib monotherapy. Among them, nine patients showed partial response (PR), three patients—stable disease (SD), and 10 patients—progressive disease (PD) according to Response Evaluation Criteria In Solid Tumors (RECIST) criteria. We then classified PR + SD patients as “responders” and PD patients as “poor responders”. We found that gene signature including eight sorafenib target genes was congruent with the drug response characteristics and enabled high-quality separation of the responders and poor responders [area under a receiver operating characteristic curve (AUC) 0.89]. We validated these findings on another set of 13 experimental annotated FFPE RCC samples (for 2 PR, 1 SD, and 10 PD patients) that were profiled by RNA sequencing and observed AUC 0.97 for 8-gene signature as the response classifier. We further validated these results in a series of qRT-PCR experiments on the third experimental set of 12 annotated RCC biosamples (for 4 PR, 3 SD, and 5 PD patients), where 8-gene signature showed AUC 0.83.
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Affiliation(s)
- Alexander Gudkov
- I. M. Sechenov First Moscow State Medical University, Moscow, Russia
| | | | | | - Dmitriy Sokov
- Moscow City Clinical Oncological Dispensary №. 1, Moscow, Russia
| | | | | | | | - Marina Sekacheva
- World-Class Research Center “Digital Biodesign and Personalized Healthcare”, Sechenov First Moscow State Medical University, Moscow, Russia
| | - Nurshat Gaifullin
- Department of Pathology, Faculty of Medicine, Lomonosov Moscow State University, Moscow, Russia
| | | | - Maria Suntsova
- World-Class Research Center “Digital Biodesign and Personalized Healthcare”, Sechenov First Moscow State Medical University, Moscow, Russia
| | - Elena Koroleva
- Moscow Institute of Physics and Technology, Moscow, Russia
| | - Anton Buzdin
- Moscow Institute of Physics and Technology, Moscow, Russia
- World-Class Research Center “Digital Biodesign and Personalized Healthcare”, Sechenov First Moscow State Medical University, Moscow, Russia
- OmicsWay Corp, Walnut, CA, United States
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Moscow, Russia
| | - Maksim Sorokin
- I. M. Sechenov First Moscow State Medical University, Moscow, Russia
- Moscow Institute of Physics and Technology, Moscow, Russia
- OmicsWay Corp, Walnut, CA, United States
- European Organization for Research and Treatment of Cancer (EORTC), Biostatistics and Bioinformatics Subgroup, Brussels, Belgium
- *Correspondence: Maksim Sorokin,
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9
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Sorokin M, Rabushko E, Efimov V, Poddubskaya E, Sekacheva M, Simonov A, Nikitin D, Drobyshev A, Suntsova M, Buzdin A. Experimental and Meta-Analytic Validation of RNA Sequencing Signatures for Predicting Status of Microsatellite Instability. Front Mol Biosci 2021; 8:737821. [PMID: 34888350 PMCID: PMC8650122 DOI: 10.3389/fmolb.2021.737821] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2021] [Accepted: 10/19/2021] [Indexed: 01/16/2023] Open
Abstract
Microsatellite instability (MSI) is an important diagnostic and prognostic cancer biomarker. In colorectal, cervical, ovarian, and gastric cancers, it can guide the prescription of chemotherapy and immunotherapy. In laboratory diagnostics of susceptible tumors, MSI is routinely detected by the size of marker polymerase chain reaction products encompassing frequent microsatellite expansion regions. Alternatively, MSI status is screened indirectly by immunohistochemical interrogation of microsatellite binding proteins. RNA sequencing (RNAseq) profiling is an emerging source of data for a wide spectrum of cancer biomarkers. Recently, three RNAseq-based gene signatures were deduced for establishing MSI status in tumor samples. They had 25, 15, and 14 gene products with only one common gene. However, they were developed and tested on the incomplete literature of The Cancer Genome Atlas (TCGA) sampling and never validated experimentally on independent RNAseq samples. In this study, we, for the first time, systematically validated these three RNAseq MSI signatures on the literature colorectal cancer (CRC) (n = 619), endometrial carcinoma (n = 533), gastric cancer (n = 380), uterine carcinosarcoma (n = 55), and esophageal cancer (n = 83) samples and on the set of experimental CRC RNAseq samples (n = 23) for tumors with known MSI status. We found that all three signatures performed well with area under the curve (AUC) ranges of 0.94–1 for the experimental CRCs and 0.94–1 for the TCGA CRC, esophageal cancer, and uterine carcinosarcoma samples. However, for the TCGA endometrial carcinoma and gastric cancer samples, only two signatures were effective with AUC 0.91–0.97, whereas the third signature showed a significantly lower AUC of 0.69–0.88. Software for calculating these MSI signatures using RNAseq data is included.
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Affiliation(s)
- Maksim Sorokin
- Laboratory For Clinical and Genomic Bioinformatics, I.M. Sechenov First Moscow State Medical University, Moscow, Russia.,Moscow Institute of Physics and Technology, Dolgoprudny, Russia.,OmicsWay Corp., Walnut, CA, United States
| | - Elizaveta Rabushko
- Laboratory For Clinical and Genomic Bioinformatics, I.M. Sechenov First Moscow State Medical University, Moscow, Russia.,Faculty of Biology, Lomonosov Moscow State University, Moscow, Russia
| | - Victor Efimov
- Moscow Institute of Physics and Technology, Dolgoprudny, Russia.,World-Class Research Center "Digital Biodesign and Personalized Healthcare", Sechenov First Moscow State Medical University, Moscow, Russia.,Oncobox Ltd., Moscow, Russia
| | - Elena Poddubskaya
- World-Class Research Center "Digital Biodesign and Personalized Healthcare", Sechenov First Moscow State Medical University, Moscow, Russia
| | - Marina Sekacheva
- World-Class Research Center "Digital Biodesign and Personalized Healthcare", Sechenov First Moscow State Medical University, Moscow, Russia
| | - Alexander Simonov
- World-Class Research Center "Digital Biodesign and Personalized Healthcare", Sechenov First Moscow State Medical University, Moscow, Russia.,Oncobox Ltd., Moscow, Russia
| | - Daniil Nikitin
- Oncobox Ltd., Moscow, Russia.,Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Moscow, Russia
| | - Aleksey Drobyshev
- Laboratory For Clinical and Genomic Bioinformatics, I.M. Sechenov First Moscow State Medical University, Moscow, Russia
| | - Maria Suntsova
- Moscow Institute of Physics and Technology, Dolgoprudny, Russia.,World-Class Research Center "Digital Biodesign and Personalized Healthcare", Sechenov First Moscow State Medical University, Moscow, Russia
| | - Anton Buzdin
- Moscow Institute of Physics and Technology, Dolgoprudny, Russia.,OmicsWay Corp., Walnut, CA, United States.,World-Class Research Center "Digital Biodesign and Personalized Healthcare", Sechenov First Moscow State Medical University, Moscow, Russia.,Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Moscow, Russia
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10
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Sorokin M, Gorelyshev A, Efimov V, Zotova E, Zolotovskaia M, Rabushko E, Kuzmin D, Seryakov A, Kamashev D, Li X, Poddubskaya E, Suntsova M, Buzdin A. RNA Sequencing Data for FFPE Tumor Blocks Can Be Used for Robust Estimation of Tumor Mutation Burden in Individual Biosamples. Front Oncol 2021; 11:732644. [PMID: 34650919 PMCID: PMC8506044 DOI: 10.3389/fonc.2021.732644] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2021] [Accepted: 09/06/2021] [Indexed: 01/16/2023] Open
Abstract
Tumor mutation burden (TMB) is a well-known efficacy predictor for checkpoint inhibitor immunotherapies. Currently, TMB assessment relies on DNA sequencing data. Gene expression profiling by RNA sequencing (RNAseq) is another type of analysis that can inform clinical decision-making and including TMB estimation may strongly benefit this approach, especially for the formalin-fixed, paraffin-embedded (FFPE) tissue samples. Here, we for the first time compared TMB levels deduced from whole exome sequencing (WES) and RNAseq profiles of the same FFPE biosamples in single-sample mode. We took TCGA project data with mean sequencing depth 23 million gene-mapped reads (MGMRs) and found 0.46 (Pearson)–0.59 (Spearman) correlation with standard mutation calling pipelines. This was converted into low (<10) and high (>10) TMB per megabase classifier with area under the curve (AUC) 0.757, and application of machine learning increased AUC till 0.854. We then compared 73 experimental pairs of WES and RNAseq profiles with lower (mean 11 MGMRs) and higher (mean 68 MGMRs) RNA sequencing depths. For higher depth, we observed ~1 AUC for the high/low TMB classifier and 0.85 (Pearson)–0.95 (Spearman) correlation with standard mutation calling pipelines. For the lower depth, the AUC was below the high-quality threshold of 0.7. Thus, we conclude that using RNA sequencing of tumor materials from FFPE blocks with enough coverage can afford for high-quality discrimination of tumors with high and low TMB levels in a single-sample mode.
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Affiliation(s)
- Maxim Sorokin
- Biostatistics and Bioinformatics Subgroup, European Organization for Research and Treatment of Cancer (EORTC), Brussels, Belgium.,The Laboratory of Clinical and Genomic Bioinformatics, I.M. Sechenov First Moscow State Medical University, Moscow, Russia.,Laboratory for Translational Genomic Bioinformatics, Moscow Institute of Physics and Technology, Dolgoprudny, Russia.,OmicsWay Corp., Walnut, CA, United States
| | - Alexander Gorelyshev
- Laboratory for Translational Genomic Bioinformatics, Moscow Institute of Physics and Technology, Dolgoprudny, Russia.,OmicsWay Corp., Walnut, CA, United States
| | - Victor Efimov
- Laboratory for Translational Genomic Bioinformatics, Moscow Institute of Physics and Technology, Dolgoprudny, Russia
| | - Evgenia Zotova
- The Laboratory of Clinical and Genomic Bioinformatics, I.M. Sechenov First Moscow State Medical University, Moscow, Russia
| | - Marianna Zolotovskaia
- Laboratory for Translational Genomic Bioinformatics, Moscow Institute of Physics and Technology, Dolgoprudny, Russia
| | - Elizaveta Rabushko
- The Laboratory of Clinical and Genomic Bioinformatics, I.M. Sechenov First Moscow State Medical University, Moscow, Russia
| | - Denis Kuzmin
- Laboratory for Translational Genomic Bioinformatics, Moscow Institute of Physics and Technology, Dolgoprudny, Russia
| | | | - Dmitry Kamashev
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences, Moscow, Russia
| | - Xinmin Li
- Department of Pathology & Laboratory Medicine, University of California Los Angeles (UCLA) Technology Center for Genomics & Bioinformatics, Los Angeles, CA, United States
| | - Elena Poddubskaya
- World-Class Research Center "Digital Biodesign and Personalized Healthcare", Sechenov First Moscow State Medical University, Moscow, Russia
| | - Maria Suntsova
- World-Class Research Center "Digital Biodesign and Personalized Healthcare", Sechenov First Moscow State Medical University, Moscow, Russia
| | - Anton Buzdin
- Biostatistics and Bioinformatics Subgroup, European Organization for Research and Treatment of Cancer (EORTC), Brussels, Belgium.,Laboratory for Translational Genomic Bioinformatics, Moscow Institute of Physics and Technology, Dolgoprudny, Russia.,OmicsWay Corp., Walnut, CA, United States.,Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences, Moscow, Russia.,World-Class Research Center "Digital Biodesign and Personalized Healthcare", Sechenov First Moscow State Medical University, Moscow, Russia
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11
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Chen P, Wu S, Yu J, Tang X, Dai C, Qi H, Zhu J, Li W, Chen B, Zhu J, Wang H, Zhao S, Liu H, Kuang P, He Y. mRNA Network: Solution for Tracking Chemotherapy Insensitivity in Small-Cell Lung Cancer. JOURNAL OF HEALTHCARE ENGINEERING 2021; 2021:2105176. [PMID: 34621500 PMCID: PMC8492269 DOI: 10.1155/2021/2105176] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/24/2021] [Revised: 06/14/2021] [Accepted: 08/05/2021] [Indexed: 12/25/2022]
Abstract
Background Small-cell lung cancer (SCLC) has poor prognosis and is prone to drug resistance. It is necessary to search for possible influencing factors for SCLC chemotherapy insensitivity. Therefore, we proposed an mRNA network to track the chemotherapy insensitivity in SCLC. Methods Six samples of patients with SCLC were recruited for RNA sequencing. TopHat2 and Cufflinks were used to make differential analysis. Functional analysis was applied as well. Finally, multidimensional validation was applied for verifying the results we obtained by experiment. Results This study was a trial of drug resistance in 6 SCLC patients after first-line chemotherapy. The top 10 downregulated genes differentially expressed in the chemo-insensitive group were SERPING1, DRD5, PARVG, PRAME, NKX1-1, MCTP2, PID1, PLEKHA4, SPP1, and SLN. Cell-cell signaling by Wnt (p=6.98E - 21) was the most significantly enriched GO term in biological process, while systemic lupus erythematosus (p=6.97E - 10), alcoholism (p=1.01E - 09), and transcriptional misregulation in cancer (p=0.00227988) were the top three ones of KEGG pathways. In multiple public databases, we also highlighted and verified the vital role of glycolysis/gluconeogenesis pathway and corresponding genes in chemo-insensitivity in SCLC. Conclusion Our study confirmed some SCLC chemotherapy insensitivity-related genes, biological processes, and pathways, thus constructing the chemotherapy-insensitive network for SCLC.
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Affiliation(s)
- Peixin Chen
- Department of Medical Oncology, Shanghai Pulmonary Hospital, Tongji University Medical School Cancer Institute, Tongji University School of Medicine, Shanghai 200433, China
- Medical School, Tongji University, Shanghai 200433, China
| | - Shengyu Wu
- Department of Medical Oncology, Shanghai Pulmonary Hospital, Tongji University Medical School Cancer Institute, Tongji University School of Medicine, Shanghai 200433, China
- Medical School, Tongji University, Shanghai 200433, China
| | - Jia Yu
- Department of Medical Oncology, Shanghai Pulmonary Hospital, Tongji University Medical School Cancer Institute, Tongji University School of Medicine, Shanghai 200433, China
- Medical School, Tongji University, Shanghai 200433, China
| | - Xuzhen Tang
- Oncology and Immunology BU, Research Service Division, WuXi Apptec, Shanghai, China
| | - Chunlei Dai
- Oncology and Immunology BU, Research Service Division, WuXi Apptec, Shanghai, China
| | - Hui Qi
- Oncology and Immunology BU, Research Service Division, WuXi Apptec, Shanghai, China
| | - Junjie Zhu
- Department of Surgery, Shanghai Pulmonary Hospital, Tongji University, Tongji University School of Medicine, Shanghai 200433, China
| | - Wei Li
- Department of Medical Oncology, Shanghai Pulmonary Hospital, Tongji University Medical School Cancer Institute, Tongji University School of Medicine, Shanghai 200433, China
- Medical School, Tongji University, Shanghai 200433, China
| | - Bin Chen
- Department of Medical Oncology, Shanghai Pulmonary Hospital, Tongji University Medical School Cancer Institute, Tongji University School of Medicine, Shanghai 200433, China
- Medical School, Tongji University, Shanghai 200433, China
| | - Jun Zhu
- Department of Medical Oncology, Shanghai Pulmonary Hospital, Tongji University Medical School Cancer Institute, Tongji University School of Medicine, Shanghai 200433, China
- Medical School, Tongji University, Shanghai 200433, China
| | - Hao Wang
- Department of Medical Oncology, Shanghai Pulmonary Hospital, Tongji University Medical School Cancer Institute, Tongji University School of Medicine, Shanghai 200433, China
- Medical School, Tongji University, Shanghai 200433, China
| | - Sha Zhao
- Department of Medical Oncology, Shanghai Pulmonary Hospital, Tongji University Medical School Cancer Institute, Tongji University School of Medicine, Shanghai 200433, China
- Medical School, Tongji University, Shanghai 200433, China
| | - Hongcheng Liu
- Department of Surgery, Shanghai Pulmonary Hospital, Tongji University, Tongji University School of Medicine, Shanghai 200433, China
| | - Peng Kuang
- Department of Medical Oncology, The First Affiliated Hospital of Nanchang University, Nanchang 330006, China
| | - Yayi He
- Department of Medical Oncology, Shanghai Pulmonary Hospital, Tongji University Medical School Cancer Institute, Tongji University School of Medicine, Shanghai 200433, China
- Medical School, Tongji University, Shanghai 200433, China
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12
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Zhao Y, Hu S, Zhang J, Cai Z, Wang S, Liu M, Dai J, Gao Y. Glucoside xylosyltransferase 2 as a diagnostic and prognostic marker in gastric cancer via comprehensive analysis. Bioengineered 2021; 12:5641-5654. [PMID: 34506251 PMCID: PMC8806449 DOI: 10.1080/21655979.2021.1967067] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/08/2023] Open
Abstract
To investigate the potential role of GXYLT2 (glucoside xylosyltransferase 2) in gastric cancer (GC), the TCGA (The Cancer Genome Atlas) database and Gene Expression Omnibus (GEO) dataset were used to evaluate GXYLT2 mRNA expression, and the standardized mean difference and diagnostic value were comprehensively assessed. Survival analysis and univariate/multivariate cox regression analysis were performed to evaluate the prognostic value of GXYLT2 in GC patients. The correlation between GXYLT2 and tumor immune cells was identified by using the CIBERSORT algorithm. The results showed that GXYLT2 expression level was significantly increased in GC tissues. GXYLT2 expression was significantly correlated with the grade, stage, and invasion depth of gastric cancer. Overall survival was reduced in the high GXYLT2 expression group. Univariate and multivariate Cox regression analyses showed that GXYLT2 was a reliable prognostic factor. GSEA showed that GXYLT2 might participate in the development of GC through tumor-related pathways. The expression of GXYLT2 was positively correlated with 5 tumor-infiltrating immune cells (resting dendritic cells, m2 macrophages, monocytes, active NK cells and resting mast cells), and was negatively correlated with 6 tumor-infiltrating immune cells (plasma cells, activated memory CD4 T cells, resting NK cells, activated dendritic cells, and activated neutrophils and mast cells). Through cell experiment verification, GXYLT2 expression level in gastric cancer cells was found to be high, which verified the results from the bioinformatics analysis. Furthermore, immunohistochemical staining results also showed that GC tissues had positive GXYLT2 expression. In summary, GXYLT2 might be a potential diagnostic and prognostic biomarker for gastric cancer.
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Affiliation(s)
- Yunxia Zhao
- Department of Basic Medical College, Bengbu Medical College, Bengbu, China
| | - Shangshang Hu
- Research Center of Clinical Laboratory Science, School of Laboratory Medicine, Bengbu Medical College, Bengbu, China
| | - Jinyan Zhang
- School of Life Science, Bengbu Medical College, Bengbu, China.,Anhui Province Key Laboratory of Translational Cancer Research, Bengbu Medical College, Bengbu, China
| | - Zhaogen Cai
- Department of Pathology, First Affiliated Hospital of Bengbu Medical College, Bengbu Medical College, Bengbu, China
| | - Shuanhu Wang
- Department of Gastrointestinal Surgery, The First Affiliated Hospital of Bengbu Medical College, Bengbu, Anhui, China
| | - Mulin Liu
- Department of Gastrointestinal Surgery, The First Affiliated Hospital of Bengbu Medical College, Bengbu, Anhui, China
| | - Jing Dai
- School of Life Science, Bengbu Medical College, Bengbu, China
| | - Yu Gao
- School of Life Science, Bengbu Medical College, Bengbu, China.,Anhui Province Key Laboratory of Translational Cancer Research, Bengbu Medical College, Bengbu, China
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13
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Seryakov A, Magomedova Z, Suntsova M, Prokofieva A, Rabushko E, Glusker A, Makovskaia L, Zolotovskaia M, Buzdin A, Sorokin M. RNA Sequencing for Personalized Treatment of Metastatic Leiomyosarcoma: Case Report. Front Oncol 2021; 11:666001. [PMID: 34527573 PMCID: PMC8435728 DOI: 10.3389/fonc.2021.666001] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2021] [Accepted: 08/11/2021] [Indexed: 01/14/2023] Open
Abstract
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.
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Affiliation(s)
| | - Zaynab Magomedova
- The Laboratory of Clinical and Genomic Bioinformatics, I.M. Sechenov First Moscow State Medical University, Moscow, Russia
| | - Maria Suntsova
- World-Class Research Center “Digital Biodesign and Personalized Healthcare”, Sechenov First Moscow State Medical University, Moscow, Russia
| | - Anastasia Prokofieva
- The Laboratory of Clinical and Genomic Bioinformatics, I.M. Sechenov First Moscow State Medical University, Moscow, Russia
| | - Elizaveta Rabushko
- The Laboratory of Clinical and Genomic Bioinformatics, I.M. Sechenov First Moscow State Medical University, Moscow, Russia
| | - Alexander Glusker
- The Laboratory of Clinical and Genomic Bioinformatics, I.M. Sechenov First Moscow State Medical University, Moscow, Russia
| | - Lyudmila Makovskaia
- Faculty of Fundamental Medicine, Lomonosov Moscow State University, Moscow, Russia
| | - Marianna Zolotovskaia
- Laboratory of Translational Genomic Bioinformatics, Moscow Institute of Physics and Technology, Dolgoprudny, Russia
| | - Anton Buzdin
- World-Class Research Center “Digital Biodesign and Personalized Healthcare”, Sechenov First Moscow State Medical University, Moscow, Russia
- Laboratory of Translational Genomic Bioinformatics, Moscow Institute of Physics and Technology, Dolgoprudny, Russia
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences, Moscow, Russia
- OmicsWay Corp, Walnut, CA, United States
| | - Maxim Sorokin
- The Laboratory of Clinical and Genomic Bioinformatics, I.M. Sechenov First Moscow State Medical University, Moscow, Russia
- Laboratory of Translational Genomic Bioinformatics, Moscow Institute of Physics and Technology, Dolgoprudny, Russia
- OmicsWay Corp, Walnut, CA, United States
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14
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Chen MH, Lu SN, Chen CH, Lin PC, Jiang JK, D’yachkova Y, Lukanowski M, Cheng R, Chen LT. How May Ramucirumab Help Improve Treatment Outcome for Patients with Gastrointestinal Cancers? Cancers (Basel) 2021; 13:3536. [PMID: 34298750 PMCID: PMC8306041 DOI: 10.3390/cancers13143536] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2021] [Revised: 05/24/2021] [Accepted: 07/09/2021] [Indexed: 12/24/2022] Open
Abstract
GI cancers are characterized by high recurrence rates and a dismal prognosis and there is an urgent need for new therapeutic approaches. This is a narrative review designed to provide a summary of the efficacy as measured by overall survival, progression free survival, and safety data from phase 3 randomized controlled GI clinical trials of ramucirumab including those from important pre-specified patient subgroups and evidence from real clinical practice worldwide. Quality of life (QOL) is discussed where data are available. Our aim was to summarize the efficacy and safety of ramucirumab in the treatment of GI cancers using these existing published data with a view to demonstrating how ramucirumab may help improve treatment outcome for patients with GI cancers. The data indicate that ramucirumab is efficacious, safe, and tolerable across the intent-to-treat patient populations as a whole and across several pre-specified subgroups, even those whose disease is traditionally more difficult to treat. Furthermore, survival outcomes observed in real-world clinical practice demonstrate similar data from phase 3 clinical trials even in patients with complications, suggesting that the benefits of ramucirumab translate in actual clinical practice.
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Affiliation(s)
- Ming-Huang Chen
- Taipei Veterans General Hospital, Taipei 11217, Taiwan; (M.-H.C.); (J.-K.J.)
| | - Sheng-Nan Lu
- Kaohsiung Chang Gung Memorial Hospital, Kaohsiung City 83301, Taiwan;
| | - Chien-Hung Chen
- Department of Internal Medicine, National Taiwan University Hospital, Douliu 64041, Taiwan;
| | - Peng-Chan Lin
- National Cheng Kung University Hospital, National Cheng Kung University, Tainan 70403, Taiwan;
| | - Jeng-Kai Jiang
- Taipei Veterans General Hospital, Taipei 11217, Taiwan; (M.-H.C.); (J.-K.J.)
| | | | - Mariusz Lukanowski
- Global Medical Affairs, Eli Lilly Denmark, Hovedstaden, 2730 Herlev, Denmark;
| | - Rebecca Cheng
- Eli Lilly and Company (Taiwan) Inc., Taipe City 10543, Taiwan;
| | - Li-Tzong Chen
- National Cheng Kung University Hospital, National Cheng Kung University, Tainan 70403, Taiwan;
- National Institute of Cancer Research, National Health Research Institutes, Tainan 70456, Taiwan
- Kaohsiung Medical University Hospital, Kaohsiung Medical University, Kaohsiung City 80756, Taiwan
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15
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Lee SW, Lee T, Sul HJ, Park KC, Park J. Differences in Somatic Mutation Profiles between Korean Gastric Cancer and Gastric Adenoma Patients. J Clin Med 2021; 10:jcm10092038. [PMID: 34068652 PMCID: PMC8126162 DOI: 10.3390/jcm10092038] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2021] [Revised: 05/06/2021] [Accepted: 05/07/2021] [Indexed: 11/16/2022] Open
Abstract
BACKGROUND We aimed to investigate molecular factors potentially related to the progression of gastric adenoma (GA) to gastric cancer (GC) and compare the mutation characteristics between GC and GA. METHODS We conducted custom gene panel sequencing for 135 GC-related genes and estimated the difference in somatic mutation profiles between 20 GC and 20 GA cases. RESULTS A total of 31 somatic mutations, including 22 missense, 3 nonsense, and 6 frameshift mutations, were detected in 17 samples. We estimated an average of 1.8 mutations per sample (range, 1 to 3 mutations), with 12 in GC and 5 in GA. GC tended to have one or more mutated genes (p = 0.0217), as well as higher allele frequencies of mutated genes (p = 0.0003), compared to GA. Likewise, known driver mutations associated with GC tumorigenesis (TP53, ERBB2, PIK3CA, and RNF43) were identified in half of the GC cases (50%, 10/20; p = 0.0002). Only the mutant burden, regardless of gene type, was retained, with an odds ratio of 1.8392 (95% confidence interval (CI), 1.0071 to 3.3588; p = 0.0474). CONCLUSION Our study demonstrates that the accumulation of mutant burden contributes to tumorigenesis progression from GA to GC in Korean patients, regardless of the kind of genes. These findings may elucidate the molecular pathogenesis of gastric carcinogenesis and malignant progression.
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Affiliation(s)
- Seung Woo Lee
- Division of Gastroenterology, Department of Internal Medicine, College of Medicine, The Catholic University of Korea, Seoul 06591, Korea;
| | - Taekyu Lee
- Thermo Fisher Scientific Solutions, Seoul 06349, Korea;
| | - Hae Jung Sul
- Department of Pathology, College of Medicine, The Catholic University of Korea, Seoul 06591, Korea;
| | - Ki Cheol Park
- Clinical Research Institute, Daejeon St. Mary’s Hospital, The Catholic University of Korea, Daejeon 34943, Korea;
| | - Joonhong Park
- Department of Laboratory Medicine, Jeonbuk National University Medical School and Hospital, Jeonju 54907, Korea
- Research Institute of Clinical Medicine of Jeonbuk National University-Biomedical Research Institute of Jeonbuk National University Hospital, Jeonju 54907, Korea
- Correspondence: ; Tel.: +82-63-250-1218
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16
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Kamashev D, Sorokin M, Kochergina I, Drobyshev A, Vladimirova U, Zolotovskaia M, Vorotnikov I, Shaban N, Raevskiy M, Kuzmin D, Buzdin A. Human blood serum can donor-specifically antagonize effects of EGFR-targeted drugs on squamous carcinoma cell growth. Heliyon 2021; 7:e06394. [PMID: 33748471 PMCID: PMC7966997 DOI: 10.1016/j.heliyon.2021.e06394] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2020] [Revised: 10/29/2020] [Accepted: 02/25/2021] [Indexed: 02/09/2023] Open
Abstract
Many patients fail to respond to EGFR-targeted therapeutics, and personalized diagnostics is needed to identify putative responders. We investigated 1630 colorectal and lung squamous carcinomas and 1357 normal lung and colon samples and observed huge variation in EGFR pathway activation in both cancerous and healthy tissues, irrespectively on EGFR gene mutation status. We investigated whether human blood serum can affect squamous carcinoma cell growth and EGFR drug response. We demonstrate that human serum antagonizes the effects of EGFR-targeted drugs erlotinib and cetuximab on A431 squamous carcinoma cells by increasing IC50 by about 2- and 20-fold, respectively. The effects on clonogenicity varied significantly across the individual serum samples in every experiment, with up to 100% differences. EGF concentration could explain many effects of blood serum samples, and EGFR ligands-depleted serum showed lesser effect on drug sensitivity.
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Affiliation(s)
- Dmitry Kamashev
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences, 16/10, Miklukho-Maklaya St., Moscow 117997, Russia
- World-Class Research Center "Digital Biodesign and Personalized Healthcare", Sechenov First Moscow State Medical University, 8-2, Trubetskaya St., Moscow 119992, Russia
| | - Maksim Sorokin
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences, 16/10, Miklukho-Maklaya St., Moscow 117997, Russia
- World-Class Research Center "Digital Biodesign and Personalized Healthcare", Sechenov First Moscow State Medical University, 8-2, Trubetskaya St., Moscow 119992, Russia
- Moscow Institute of Physics and Technology (National Research University), Moscow Region 141700, Russia
| | - Irina Kochergina
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences, 16/10, Miklukho-Maklaya St., Moscow 117997, Russia
| | - Aleksey Drobyshev
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences, 16/10, Miklukho-Maklaya St., Moscow 117997, Russia
- World-Class Research Center "Digital Biodesign and Personalized Healthcare", Sechenov First Moscow State Medical University, 8-2, Trubetskaya St., Moscow 119992, Russia
- Moscow Institute of Physics and Technology (National Research University), Moscow Region 141700, Russia
| | - Uliana Vladimirova
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences, 16/10, Miklukho-Maklaya St., Moscow 117997, Russia
- World-Class Research Center "Digital Biodesign and Personalized Healthcare", Sechenov First Moscow State Medical University, 8-2, Trubetskaya St., Moscow 119992, Russia
| | - Marianna Zolotovskaia
- Moscow Institute of Physics and Technology (National Research University), Moscow Region 141700, Russia
| | - Igor Vorotnikov
- Blokhin National Medical Research Center of Oncology of the Ministry of Health of Russia
| | - Nina Shaban
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences, 16/10, Miklukho-Maklaya St., Moscow 117997, Russia
- Moscow Institute of Physics and Technology (National Research University), Moscow Region 141700, Russia
| | - Mikhail Raevskiy
- Moscow Institute of Physics and Technology (National Research University), Moscow Region 141700, Russia
- OmicsWay Corp., Walnut, CA, USA
| | - Denis Kuzmin
- Moscow Institute of Physics and Technology (National Research University), Moscow Region 141700, Russia
| | - Anton Buzdin
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences, 16/10, Miklukho-Maklaya St., Moscow 117997, Russia
- World-Class Research Center "Digital Biodesign and Personalized Healthcare", Sechenov First Moscow State Medical University, 8-2, Trubetskaya St., Moscow 119992, Russia
- Moscow Institute of Physics and Technology (National Research University), Moscow Region 141700, Russia
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17
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Sorokin M, Borisov N, Kuzmin D, Gudkov A, Zolotovskaia M, Garazha A, Buzdin A. Algorithmic Annotation of Functional Roles for Components of 3,044 Human Molecular Pathways. Front Genet 2021; 12:617059. [PMID: 33633781 PMCID: PMC7900570 DOI: 10.3389/fgene.2021.617059] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2020] [Accepted: 01/20/2021] [Indexed: 12/16/2022] Open
Abstract
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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Affiliation(s)
- Maxim Sorokin
- Omicsway Corp., Walnut, CA, United States.,Laboratory of Clinical Genomic Bioinformatics, I.M. Sechenov First Moscow State Medical University, Moscow, Russia.,Laboratory for Translational Bioinformatics, Moscow Institute of Physics and Technology, Moscow, Russia
| | - Nicolas Borisov
- Omicsway Corp., Walnut, CA, United States.,Laboratory for Translational Bioinformatics, Moscow Institute of Physics and Technology, Moscow, Russia
| | - Denis Kuzmin
- Laboratory for Translational Bioinformatics, Moscow Institute of Physics and Technology, Moscow, Russia
| | - Alexander Gudkov
- Laboratory of Clinical Genomic Bioinformatics, I.M. Sechenov First Moscow State Medical University, Moscow, Russia
| | - Marianna Zolotovskaia
- Laboratory for Translational Bioinformatics, Moscow Institute of Physics and Technology, Moscow, Russia
| | | | - Anton Buzdin
- Omicsway Corp., Walnut, CA, United States.,Laboratory for Translational Bioinformatics, Moscow Institute of Physics and Technology, Moscow, Russia.,Laboratory of Systems Biology, Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Moscow, Russia.,World-Class Research Center "Digital Biodesign and Personalized Healthcare", Sechenov First Moscow State Medical University, Moscow, Russia
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18
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Yin Z, Cai H, Wang Z, Jiang Y. Pseudolaric Acid B Inhibits Proliferation, Invasion, and Angiogenesis in Esophageal Squamous Cell Carcinoma Through Regulating CD147. DRUG DESIGN DEVELOPMENT AND THERAPY 2020; 14:4561-4573. [PMID: 33149553 PMCID: PMC7605399 DOI: 10.2147/dddt.s269915] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/29/2020] [Accepted: 09/18/2020] [Indexed: 12/11/2022]
Abstract
Background Esophageal squamous cell carcinoma (ESCC) is a common malignant tumor of the digestive system. Studies have shown that pseudolaric acid B (PAB) has several pharmacological effects like anti-microtubule, anti-angiogenesis, and antitumor functions, while the effect and mechanism of PAB on esophageal cancer are still unclear. This study was designed to investigate the effects of PAB on ESCC. Methods To study the effects of PAB on the biological function through a series of in vitro and in vivo experiments. Results The results revealed that PAB inhibited the proliferation, invasion, and migration, but promoted the apoptosis of ESCC. Moreover, PAB restrained the growth of cancer cells in vivo and inhibited the angiogenesis of HUVEC in mice with ESCC. CD147 expression was increased in the esophageal squamous cell lines, and interference with CD147 hindered the proliferation, invasion, and migration of ESCC cells, and inhibited the growth and angiogenesis of the esophageal squamous cell line. PAB reduced the expression of CD147 in vivo and in vitro. The expression of MMP2, 3, and 9 was increased after overexpression of CD147, which provided the opportunity to reverse the role of PAB in inhibiting proliferation, invasion, migration, and angiogenesis of ESCC. Discussion The results revealed that PAB inhibited the proliferation, invasion, migration, and angiogenesis of ESCC in vitro and in vivo by CD147. PAB is a promising monomer for therapy of ESCC, providing references for future research on ESCC treatment.
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Affiliation(s)
- Zhe Yin
- Department of Thoracic Surgery, Chongqing University Cancer Hospital, Chongqing 400030, China
| | - Huarong Cai
- Department of Thoracic Surgery, Chongqing University Cancer Hospital, Chongqing 400030, China
| | - Zhiqiang Wang
- Department of Thoracic Surgery, Chongqing University Cancer Hospital, Chongqing 400030, China
| | - Yuequan Jiang
- Department of Thoracic Surgery, Chongqing University Cancer Hospital, Chongqing 400030, China
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19
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Sorokin M, Kholodenko I, Kalinovsky D, Shamanskaya T, Doronin I, Konovalov D, Mironov A, Kuzmin D, Nikitin D, Deyev S, Buzdin A, Kholodenko R. RNA Sequencing-Based Identification of Ganglioside GD2-Positive Cancer Phenotype. Biomedicines 2020; 8:E142. [PMID: 32486168 PMCID: PMC7344710 DOI: 10.3390/biomedicines8060142] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2020] [Revised: 05/20/2020] [Accepted: 05/27/2020] [Indexed: 12/15/2022] Open
Abstract
The tumor-associated ganglioside GD2 represents an attractive target for cancer immunotherapy. GD2-positive tumors are more responsive to such targeted therapy, and new methods are needed for the screening of GD2 molecular tumor phenotypes. In this work, we built a gene expression-based binary classifier predicting the GD2-positive tumor phenotypes. To this end, we compared RNA sequencing data from human tumor biopsy material from experimental samples and public databases as well as from GD2-positive and GD2-negative cancer cell lines, for expression levels of genes encoding enzymes involved in ganglioside biosynthesis. We identified a 2-gene expression signature combining ganglioside synthase genes ST8SIA1 and B4GALNT1 that serves as a more efficient predictor of GD2-positive phenotype (Matthews Correlation Coefficient (MCC) 0.32, 0.88, and 0.98 in three independent comparisons) compared to the individual ganglioside biosynthesis genes (MCC 0.02-0.32, 0.1-0.75, and 0.04-1 for the same independent comparisons). No individual gene showed a higher MCC score than the expression signature MCC score in two or more comparisons. Our diagnostic approach can hopefully be applied for pan-cancer prediction of GD2 phenotypes using gene expression data.
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Affiliation(s)
- Maxim Sorokin
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences, 16/10, Miklukho- Maklaya St., 117997 Moscow, Russia; (M.S.); (D.K.); (I.D.); (D.N.); (S.D.); (A.B.)
- Sechenov First Moscow State Medical University, 8-2, Trubetskaya St., 119992 Moscow, Russia
- Omicsway Corp., 340 S Lemon Ave, 6040, Walnut, CA 91789, USA
| | - Irina Kholodenko
- Orekhovich Institute of Biomedical Chemistry, 10, Pogodinskaya St., 119121 Moscow, Russia;
| | - Daniel Kalinovsky
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences, 16/10, Miklukho- Maklaya St., 117997 Moscow, Russia; (M.S.); (D.K.); (I.D.); (D.N.); (S.D.); (A.B.)
| | - Tatyana Shamanskaya
- D. Rogachev Federal Research Center of Pediatric Hematology, Oncology and Immunology, 1, Samory Mashela St., 117997 Moscow, Russia; (T.S.); (D.K.)
| | - Igor Doronin
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences, 16/10, Miklukho- Maklaya St., 117997 Moscow, Russia; (M.S.); (D.K.); (I.D.); (D.N.); (S.D.); (A.B.)
- Real Target LLC, 108841 Moscow, Russia
| | - Dmitry Konovalov
- D. Rogachev Federal Research Center of Pediatric Hematology, Oncology and Immunology, 1, Samory Mashela St., 117997 Moscow, Russia; (T.S.); (D.K.)
| | - Aleksei Mironov
- Skolkovo Institute of Science and Technology, 3, Nobelya St., 121205 Moscow, Russia;
| | - Denis Kuzmin
- Moscow Institute of Physics and Technology (National Research University), 141700 Moscow, Russia;
| | - Daniil Nikitin
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences, 16/10, Miklukho- Maklaya St., 117997 Moscow, Russia; (M.S.); (D.K.); (I.D.); (D.N.); (S.D.); (A.B.)
| | - Sergey Deyev
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences, 16/10, Miklukho- Maklaya St., 117997 Moscow, Russia; (M.S.); (D.K.); (I.D.); (D.N.); (S.D.); (A.B.)
- Sechenov First Moscow State Medical University, 8-2, Trubetskaya St., 119992 Moscow, Russia
| | - Anton Buzdin
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences, 16/10, Miklukho- Maklaya St., 117997 Moscow, Russia; (M.S.); (D.K.); (I.D.); (D.N.); (S.D.); (A.B.)
- Sechenov First Moscow State Medical University, 8-2, Trubetskaya St., 119992 Moscow, Russia
- Moscow Institute of Physics and Technology (National Research University), 141700 Moscow, Russia;
- Oncobox ltd., 121205 Moscow, Russia
| | - Roman Kholodenko
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences, 16/10, Miklukho- Maklaya St., 117997 Moscow, Russia; (M.S.); (D.K.); (I.D.); (D.N.); (S.D.); (A.B.)
- Real Target LLC, 108841 Moscow, Russia
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20
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Moisseev A, Albert E, Lubarsky D, Schroeder D, Clark J. Transcriptomic and Genomic Testing to Guide Individualized Treatment in Chemoresistant Gastric Cancer Case. Biomedicines 2020; 8:biomedicines8030067. [PMID: 32210001 PMCID: PMC7148467 DOI: 10.3390/biomedicines8030067] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2020] [Revised: 03/20/2020] [Accepted: 03/20/2020] [Indexed: 12/20/2022] Open
Abstract
Gastric cancer is globally the fifth leading cause of cancer death. We present a case report describing the unique genomic characteristics of an Epstein–Barr virus-negative gastric cancer with esophageal invasion and regional lymph node metastasis. Genomic tests were performed first with the stomach biopsy using platforms FoundationOne, OncoDNA, and Oncopanel at Dana Farber Institute. Following neoadjuvant chemotherapy, residual tumor was resected and the stomach and esophageal residual tumor samples were compared with the initial biopsy by whole exome sequencing and molecular pathway analysis platform Oncobox. Copy number variation profiling perfectly matched the whole exome sequencing results. A moderate agreement was seen between the diagnostic platforms in finding mutations in the initial biopsy. Final data indicate somatic activating mutation Q546K in PIK3CA gene, somatic frameshifts in PIH1D1 and FBXW7 genes, stop-gain in TP53BP1, and a few somatic mutations of unknown significance. RNA sequencing analysis revealed upregulated expressions of MMP7, MMP9, BIRC5, and PD-L1 genes and strongly differential regulation of several molecular pathways linked with the mutations identified. According to test results, the patient received immunotherapy with anti-PD1 therapy and is now free of disease for 2 years. Our data suggest that matched tumor and normal tissue analyses have a considerable advantage over tumor biopsy-only genomic tests in stomach cancer.
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Affiliation(s)
- Alexey Moisseev
- Institute for personalized medicine, I.M. Sechenov First Moscow State Medical University, 119048 Moscow, Russia;
- Correspondence: ; Tel.: +7(926)1443639
| | - Eugene Albert
- Institute for personalized medicine, I.M. Sechenov First Moscow State Medical University, 119048 Moscow, Russia;
| | | | - David Schroeder
- Wellesley Internal Medicine, 372 Washington St Ste 2, Wellesley Hills, MA 02481, USA;
| | - Jeffrey Clark
- Department of Hematology and Oncology, Massachusetts General Hospital, 55 Fruit Street Boston, MA 02114, USA;
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21
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Zolotovskaia MA, Sorokin MI, Petrov IV, Poddubskaya EV, Moiseev AA, Sekacheva MI, Borisov NM, Tkachev VS, Garazha AV, Kaprin AD, Shegay PV, Giese A, Kim E, Roumiantsev SA, Buzdin AA. Disparity between Inter-Patient Molecular Heterogeneity and Repertoires of Target Drugs Used for Different Types of Cancer in Clinical Oncology. Int J Mol Sci 2020; 21:E1580. [PMID: 32111026 PMCID: PMC7084891 DOI: 10.3390/ijms21051580] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/24/2019] [Revised: 02/17/2020] [Accepted: 02/19/2020] [Indexed: 02/07/2023] Open
Abstract
Inter-patient molecular heterogeneity is the major declared driver of an expanding variety of anticancer drugs and personalizing their prescriptions. Here, we compared interpatient molecular heterogeneities of tumors and repertoires of drugs or their molecular targets currently in use in clinical oncology. We estimated molecular heterogeneity using genomic (whole exome sequencing) and transcriptomic (RNA sequencing) data for 4890 tumors taken from The Cancer Genome Atlas database. For thirteen major cancer types, we compared heterogeneities at the levels of mutations and gene expression with the repertoires of targeted therapeutics and their molecular targets accepted by the current guidelines in oncology. Totally, 85 drugs were investigated, collectively covering 82 individual molecular targets. For the first time, we showed that the repertoires of molecular targets of accepted drugs did not correlate with molecular heterogeneities of different cancer types. On the other hand, we found that the clinical recommendations for the available cancer drugs were strongly congruent with the gene expression but not gene mutation patterns. We detected the best match among the drugs usage recommendations and molecular patterns for the kidney, stomach, bladder, ovarian and endometrial cancers. In contrast, brain tumors, prostate and colorectal cancers showed the lowest match. These findings provide a theoretical basis for reconsidering usage of targeted therapeutics and intensifying drug repurposing efforts.
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Affiliation(s)
- Marianna A. Zolotovskaia
- Oncobox ltd., Moscow, 121205, Russia; (I.V.P.); (A.A.B.)
- Department of Oncology, Hematology and Radiotherapy of Pediatric Faculty, Pirogov Russian National Research Medical University, Moscow, 117997, Russia;
- Moscow Institute of Physics and Technology, Dolgoprudny, Moscow Region 141701, Russia;
| | - Maxim I. Sorokin
- I.M. Sechenov First Moscow State Medical University, Moscow, 119991, Russia (E.V.P.); (A.A.M.)
- Omicsway Corp., Walnut, CA, 91789, USA; (V.S.T.); (A.V.G.)
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Moscow, 117997, Russia
| | - Ivan V. Petrov
- Oncobox ltd., Moscow, 121205, Russia; (I.V.P.); (A.A.B.)
| | - Elena V. Poddubskaya
- I.M. Sechenov First Moscow State Medical University, Moscow, 119991, Russia (E.V.P.); (A.A.M.)
| | - Alexey A. Moiseev
- I.M. Sechenov First Moscow State Medical University, Moscow, 119991, Russia (E.V.P.); (A.A.M.)
| | - Marina I. Sekacheva
- I.M. Sechenov First Moscow State Medical University, Moscow, 119991, Russia (E.V.P.); (A.A.M.)
| | - Nicolas M. Borisov
- Moscow Institute of Physics and Technology, Dolgoprudny, Moscow Region 141701, Russia;
- I.M. Sechenov First Moscow State Medical University, Moscow, 119991, Russia (E.V.P.); (A.A.M.)
- Omicsway Corp., Walnut, CA, 91789, USA; (V.S.T.); (A.V.G.)
| | | | | | - Andrey D. Kaprin
- National Medical Research Radiological Centre of the Ministry of Health of the Russian Federation, Moscow 125284, Russia;
| | - Peter V. Shegay
- Center for Innovative Radiological and Regenerative Technologies of the Ministry of Health of the Russian Federation, Obninsk 249030, Russia;
| | - Alf Giese
- Orthocentrum Hamburg, Hamburg, Germany; or
| | - Ella Kim
- Johannes Gutenberg University Mainz, Mainz, Germany;
| | - Sergey A. Roumiantsev
- Department of Oncology, Hematology and Radiotherapy of Pediatric Faculty, Pirogov Russian National Research Medical University, Moscow, 117997, Russia;
| | - Anton A. Buzdin
- Oncobox ltd., Moscow, 121205, Russia; (I.V.P.); (A.A.B.)
- Moscow Institute of Physics and Technology, Dolgoprudny, Moscow Region 141701, Russia;
- I.M. Sechenov First Moscow State Medical University, Moscow, 119991, Russia (E.V.P.); (A.A.M.)
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Moscow, 117997, Russia
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