Evidence map›Paper›PMID 26624979›Full record

ArticleOncotarget2016

Molecular pathway activation features linked with transition from normal skin to primary and metastatic melanomas in human.

Denis Shepelin, Mikhail Korzinkin, Anna Vanyushina, Alexander Aliper, Nicolas Borisov, Raif Vasilov, Nikolay Zhukov, Dmitry Sokov, Vladimir Prassolov, Nurshat Gaifullin and 3 more

Abstract read
In one paragraph

Article in Oncotarget, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing 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

17 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors.

Denis ShepelinPathway Pharmaceuticals, Wan Chai, Hong Kong, Hong Kong SAR.
Mikhail KorzinkinPathway Pharmaceuticals, Wan Chai, Hong Kong, Hong Kong SAR.
Anna VanyushinaLaboratory of Bioinformatics, D. Rogachyov Federal Research Center of Pediatric Hematology, Oncology and Immunology, Moscow, Russia.
Alexander AliperLaboratory of Bioinformatics, D. Rogachyov Federal Research Center of Pediatric Hematology, Oncology and Immunology, Moscow, Russia.
Nicolas BorisovFirst Oncology Research and Advisory Center, Moscow, Russia.
Raif VasilovNational Research Centre "Kurchatov Institute", Centre for Convergence of Nano-, Bio-, Information and Cognitive Sciences and Technologies, Moscow, Russia.
Nikolay ZhukovFirst Oncology Research and Advisory Center, Moscow, Russia.
Dmitry SokovMoscow 1st Oncological Hospital, Moscow Russia.
Vladimir PrassolovEngelhardt Institute of Molecular Biology, Russian Academy of Sciences, Mosow, Russia.
Nurshat GaifullinMoscow State University, Faculty of Fundamental Medicine, Moscow, Russia.
Alex ZhavoronkovInsilico Medicine, Inc, ETC, Johns Hopkins University, Baltimore, MD, USA.
Bhupinder BhullarNovartis Institute for Biomedical Research, Basel, Switzerland.
Anton BuzdinPathway Pharmaceuticals, Wan Chai, Hong Kong, Hong Kong SAR.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Melanoma is the most aggressive and dangerous type of skin cancer, but its molecular mechanisms remain largely unclear. For transcriptomic data of 478 primary and metastatic melanoma, nevi and normal skin samples, we performed high-throughput analysis of intracellular molecular networks including 592 signaling and metabolic pathways. We showed that at the molecular pathway level, the formation of nevi largely resembles transition from normal skin to primary melanoma. Using a combination of bioinformatic machine learning algorithms, we identified 44 characteristic signaling and metabolic pathways connected with the formation of nevi, development of primary melanoma, and its metastases. We created a model describing formation and progression of melanoma at the level of molecular pathway activation. We discovered six novel associations between activation of metabolic molecular pathways and progression of melanoma: for allopregnanolone biosynthesis, L-carnitine biosynthesis, zymosterol biosynthesis (inhibited in melanoma), fructose 2, 6-bisphosphate synthesis and dephosphorylation, resolvin D biosynthesis (activated in melanoma), D-myo-inositol hexakisphosphate biosynthesis (activated in primary, inhibited in metastatic melanoma). Finally, we discovered fourteen tightly coordinated functional clusters of molecular pathways. This study helps to decode molecular mechanisms underlying the development of melanoma.

Indexed as

AlgorithmsCell Transformation, NeoplasticCluster AnalysisComputational BiologyGene Expression ProfilingHumansMachine LearningMelanomaMetabolic Networks and PathwaysNeoplasm MetastasisPrincipal Component AnalysisSignal TransductionSkinSkin NeoplasmsTranscriptomeintracellular molecular networksmachine learning algorithmsmetabolic and signaling pathwaysOncoFindertransition from nevus to primary and metastatic melanoma

Identifiers

PMID26624979
PMCPMC4808024

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Registered trials

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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 OpenQuestion graph.