Evidence mapPaperPMID 37635765Full record

ArticleComputational and structural biotechnology journal2023

Large-scale assessment of pros and cons of autopsy-derived or tumor-matched tissues as the norms for gene expression analysis in cancers.

Maksim Sorokin, Anton A Buzdin, Anastasia Guryanova, Victor Efimov, Maria V Suntsova, Marianna A Zolotovskaia, Elena V Koroleva, Marina I Sekacheva, Victor S Tkachev, Andrew Garazha and 18 more

Open access · goldAbstract read
In one paragraph

Article in Computational and structural biotechnology journal, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
2.9field-weighted citation impact, top 9% of its field
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

11 citing papers in PubMed, 19 citations in OpenAlex.

  1. Review
  2. Article
  3. Integration of Bulk and Single-Cell RNA Sequencing Analyses in Biomedicine.International journal of molecular sciences · 2026
    Review
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
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

28 authors at 10 institutions in 6 countries.

Maksim SorokinMoscow Institute of Physics and Technology, Dolgoprudny, Moscow Region 141701, Russia.
Anton A BuzdinMoscow Institute of Physics and Technology, Dolgoprudny, Moscow Region 141701, Russia.
Anastasia GuryanovaMoscow Institute of Physics and Technology, Dolgoprudny, Moscow Region 141701, Russia.
Victor EfimovWorld-Class Research Center "Digital biodesign and personalized healthcare", Sechenov First Moscow State Medical University, Moscow, Russia.
Maria V SuntsovaMoscow Institute of Physics and Technology, Dolgoprudny, Moscow Region 141701, Russia.
Marianna A ZolotovskaiaMoscow Institute of Physics and Technology, Dolgoprudny, Moscow Region 141701, Russia.
Elena V KorolevaMoscow Institute of Physics and Technology, Dolgoprudny, Moscow Region 141701, Russia.
Marina I SekachevaMoscow Institute of Physics and Technology, Dolgoprudny, Moscow Region 141701, Russia.
Victor S TkachevOmicsway Corp., Walnut, CA 91789, USA.
Andrew GarazhaOmicsway Corp., Walnut, CA 91789, USA.
Kristina KremenchutckayaMoscow Institute of Physics and Technology, Dolgoprudny, Moscow Region 141701, Russia.
Aleksey DrobyshevI.M. Sechenov First Moscow State Medical University, Moscow 119991, Russia.
Aleksander SeryakovMedical Holding SM-Clinic, 105120 Moscow, Russia.
Alexander GudkovI.M. Sechenov First Moscow State Medical University, Moscow 119991, Russia.
Irina V AlekseenkoShemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Moscow 117997, Russia.
Olga RakitinaShemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Moscow 117997, Russia.
Maria B KostinaShemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Moscow 117997, Russia.
Uliana VladimirovaI.M. Sechenov First Moscow State Medical University, Moscow 119991, Russia.
Aleksey MoisseevI.M. Sechenov First Moscow State Medical University, Moscow 119991, Russia.
Dmitry BulginResearch Institute of Medical Primatology, 177 Mira str., Veseloye, Sochi 354376, Russia.
Elena RadomskayaResearch Institute of Medical Primatology, 177 Mira str., Veseloye, Sochi 354376, Russia.
Viktor ShestakovResearch Institute of Medical Primatology, 177 Mira str., Veseloye, Sochi 354376, Russia.
Vladimir P BaklaushevFederal Research and Clinical Center, FMBA of Russia, Russia.
Vladimir PrassolovCenter 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 ShegayNational Medical Research Radiological Center of the Ministry of Health of the Russian Federation, 249036 Obninsk, Russia.
Xinmin LiUCLA Technology Center for Genomics & Bioinformatics, Department of Pathology & Laboratory Medicine, 650 Charles E Young Dr., Los Angeles, CA 90095, USA.
Elena V PoddubskayaI.M. Sechenov First Moscow State Medical University, Moscow 119991, Russia.
Nurshat GaifullinDepartment of Physiology and General Pathology, Faculty of Medicine, Lomonosov Moscow State University, Moscow 119991, Russia.
Moscow Institute of Physics and Technology · RUSechenov University · RUFederal State Budgetary Scientific Institution Research Institute of Medical Primatology · RUInstitute of Bioorganic Chemistry · RUEngelhardt Institute of Molecular Biology · RUKurchatov Institute · RULomonosov Moscow State University · RUMinistry of Health of the Russian Federation · RUState Research Institute of Highly Pure Biopreparations · RUUCLA Medical Center · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

AutopsyCancer researchDifferential gene expression analysisHealthy tissue controlsMolecular pathologyMolecular pathwaysRNA sequencingTumor matched pathologically normal tissues

Identifiers

PMID37635765
PMCPMC10448432
OpenAlexW4385556020

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
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.