Evidence map›Paper›PMID 29404790›Full record

ArticleJournal of gastrointestinal cancer2019

MicroRNA Expression Levels and Histopathological Features of Colorectal Cancer.

Sahar Sarmasti Emami, Abolfazl Akbari, Ali-Akbar Zare, Shahram Agah, Mohsen Masoodi, Atefeh Talebi, Sara Minaeian, Azam Fattahi, Farahnaz Moghadamnia

Abstract read
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Article in Journal of gastrointestinal cancer, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
1.6field-weighted citation impact, top 19% 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

10 citing papers in PubMed, 30 citations in OpenAlex.

  1. Article
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  4. Article
  5. Review
  6. Article
  7. Function and mechanisms of microRNA-20a in colorectal cancer.Experimental and therapeutic medicine · 2020
    Review
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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

9 authors at 3 institutions in 1 country.

Sahar Sarmasti EmamiDepartment of Medical Biotechnology, School of Allied Medicine, Iran University of Medical Sciences, Tehran, Iran.
Abolfazl AkbariColorectal Research Center, Iran University of Medical Sciences, Tehran, Iran. akbariia2006@gmail.com.
Ali-Akbar ZareYoung Researchers and Elites Club, Science and Research Branch, Islamic Azad University, Tehran, Iran. aa.zare322@gmail.com.
Shahram AgahColorectal Research Center, Iran University of Medical Sciences, Tehran, Iran.
Mohsen MasoodiColorectal Research Center, Iran University of Medical Sciences, Tehran, Iran.
Atefeh TalebiColorectal Research Center, Iran University of Medical Sciences, Tehran, Iran.
Sara MinaeianAntimicrobial Resistance Research Center, Institute of Immunology and Infectious Diseases, Iran University of Medical Sciences, Tehran, Iran.
Azam FattahiResearch Center of Pediatric Infectious Diseases, Institute of Immunology and Infectious Diseases, Iran University of Medical Sciences, Tehran, Iran.
Farahnaz MoghadamniaDepartment of Genetics, Tehran Medical Sciences Branch, Islamic Azad University, Tehran, Iran.
Iran University of Medical Sciences · IRIslamic Azad University Medical Branch of Tehran · IRMotamed Cancer Institute · IR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionNon-coding RNAs have opened a new window in cancer biology. MicroRNAs (miRNAs), as a family of non-coding RNAs, play an important role in the gene regulation. The aberrant expression of these small molecules has been documented to involve in colorectal cancer (CRC) pathogenesis. This study aimed to examine the expression of miRNAs in CRC and to correlate their expression levels with histological markers (Ki-67 and CD34). MATERIALS AND

methodsTumor tissues and matched normal adjacent tissues were collected from 36 patients with newly diagnosed CRC. Immunohistochemical (IHC) staining of tumor tissues was performed for Ki-67 (proliferation) and CD34 (angiogenesis) markers, and the immunoexpression staining scores were obtained. A polyadenylation SYBER Green quantitative real-time PCR technique was used to quantify the expression of a panel of five CRC-related miRNAs (hsa-miR-21, 31, 20a, 133b, and 145). Histopathological (H) scores and miRNA expression levels were correlated with clinicopathological features including the degree of differentiation, staging, and lymphovascular invasion.

resultsOur results showed the significant difference between the two groups for the expression level of hsa-miR-21, hsa-miR-31, hsa-miR-145, and miR-20a (P < 0.001), but not for hsa-miR-133b (P = 0.57). Further analysis revealed an inverse significant correlation between hsa-miR-145 and Ki-67 (r = - 0.942, P < 0.001). While a positive correlation was observed between hsa-miR-21 and Ki-67 (r = 0.920, P < 0.001), and hsa-miR-21 and CD34 (r = 0.981, P < 0.001). Also, a positive correlation between hsa-miR-31 and Ki-67 (r = 0.913, P < 0.001), hsa-miR-31 and CD34 (r = 0.798, P < 0.05), hsa-miR-20a and Ki-67 (r = 0.871, P < 0.001), and hsa-miR-20a and CD34 (r = 0.890, P < 0.001) was found.

conclusionDysregulation of miRNAs and correlation with molecular histopathology indicate a biological role for miRNAs in various cellular processes including cell proliferation and angiogenesis in CRC development. On the other hand, the pattern of miRNA expression and its correlation with histological markers are potentially valuable to apply as diagnostic biomarkers for CRC.

Indexed as

Gene Expression Regulation, NeoplasticAntigens, CD34Biomarkers, TumorCell ProliferationColorectal NeoplasmsFemaleGene Expression ProfilingHumansKi-67 AntigenMaleMicroRNAsMiddle AgedNeoplasm StagingNeovascularization, PathologicAntigens, CD34Biomarkers, TumorKi-67 AntigenMicroRNAsCD34Colorectal cancerKi-67MicroRNA

Identifiers

PMID29404790
OpenAlexW2792621083

What OpenQuestion holds

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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.