Evidence map›Paper›PMID 29935311›Full record

ReviewSeminars in cancer biology2018

Molecular pathway activation - New type of biomarkers for tumor morphology and personalized selection of target drugs.

Anton Buzdin, Maxim Sorokin, Andrew Garazha, Marina Sekacheva, Ella Kim, Nikolay Zhukov, Ye Wang, Xinmin Li, Souvik Kar, Christian Hartmann and 3 more

Abstract readReview
PubMed Publisher
In one paragraph

Review in Seminars in cancer biology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 53 papers.

0numbers the graph read from it
0cells of the map it votes in
53citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

53 citing papers in PubMed.

  1. Article
  2. Observational
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  12. Review
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  19. Case of multifocal glioblastoma with four fusion transcripts ofCold Spring Harbor molecular case studies · 2021
    Article
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

13 authors.

Anton BuzdinI.M. Sechenov First Moscow State Medical University, Moscow, Russia; Omicsway Corp., Walnut, CA, USA; Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Moscow, Russia. Electronic address: buzdin@oncobox.com.
Maxim SorokinI.M. Sechenov First Moscow State Medical University, Moscow, Russia.
Andrew GarazhaOmicsway Corp., Walnut, CA, USA.
Marina SekachevaI.M. Sechenov First Moscow State Medical University, Moscow, Russia.
Ella KimJohannes Gutenberg University Mainz, Mainz, Germany.
Nikolay ZhukovD. Rogachev Federal Research Center of Pediatric Hematology, Oncology and Immunology, Moscow, 117198, Russia.
Ye WangQingdao Central Hospital, 127 Siliu Road South, Qingdao, Shandong, 266042, China. Electronic address: 329207564@qq.com.
Xinmin LiDepartment of Pathology and Laboratory Medicine, University of California Los Angeles, CA, 90095, USA. Electronic address: xinminli@mednet.ucla.edu.
Souvik KarInternational Neuroscience Institute, Hannover, Germany.
Christian HartmannInstitute of Neuropathology at Hannover Medical School, Hannover, Germany.
Amir SamiiInternational Neuroscience Institute, Hannover, Germany.
Alf GieseInternational Neuroscience Institute, Hannover, Germany.
Nicolas BorisovI.M. Sechenov First Moscow State Medical University, Moscow, Russia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Anticancer target drugs (ATDs) specifically bind and inhibit molecular targets that play important roles in cancer development and progression, being deeply implicated in intracellular signaling pathways. To date, hundreds of different ATDs were approved for clinical use in the different countries. Compared to previous chemotherapy treatments, ATDs often demonstrate reduced side effects and increased efficiency, but also have higher costs. However, the efficiency of ATDs for the advanced stage tumors is still insufficient. Different ATDs have different mechanisms of action and are effective in different cohorts of patients. Personalized approaches are therefore needed to select the best ATD candidates for the individual patients. In this review, we focus on a new generation of biomarkers - molecular pathway activation - and on their applications for predicting individual tumor response to ATDs. The success in high throughput gene expression profiling and emergence of novel bioinformatic tools reinforced quick development of pathway related field of molecular biomedicine. The ability to quantitatively measure degree of a pathway activation using gene expression data has revolutionized this field and made the corresponding analysis quick, robust and inexpensive. This success was further enhanced by using machine learning algorithms for selection of the best biomarkers. We review here the current progress in translating these studies to clinical oncology and patient-oriented adjustment of cancer therapy.

Indexed as

Antineoplastic AgentsBiomarkers, TumorGene Expression ProfilingGene Expression Regulation, NeoplasticHumansMolecular Targeted TherapyNeoplasmsPrecision MedicineSignal TransductionAntineoplastic AgentsBiomarkers, TumorAnticancer target drugsBig data analyticsBioinformaticsBiomarkersCancerEpigeneticsGene expressionIntracellular molecular pathwaysMachine learningMicro RNAmiRProteomicsResponse to cancer therapySystems biologyTranscriptomics

Identifiers

What Socratic holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.