Evidence map›Paper›PMID 35469389›Full record

ArticleMolecular biology reports2022

Unravelling of the comparative Transcriptomic Profile of Gallbladder Cancer using mRNA sequencing.

Ruhi Dixit, Manoj Pandey, Monika Rajput, Vijay Kumar Shukla

Abstract read
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In one paragraph

Article in Molecular biology reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed, 1 pooled it
3.1field-weighted citation impact, top 8% 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

17 citing papers in PubMed, 1 synthesis or guideline pooled it, 16 citations in OpenAlex.

  1. Pooled it
  2. Genomic landscape and clinicopathological predictors of survival in gallbladder cancer.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2026
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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

4 authors at 1 institution in 1 country.

Ruhi DixitDepartment of General Surgery, Institute of Medical Sciences, Banaras Hindu University, 221 005, Varanasi, India.
Manoj PandeyDepartment of Surgical Oncology, Institute of Medical Sciences, Banaras Hindu University, 221005, Varanasi, India.
Monika RajputDepartment of Surgical Oncology, Institute of Medical Sciences, Banaras Hindu University, 221005, Varanasi, India.
Vijay Kumar ShuklaDepartment of General Surgery, Institute of Medical Sciences, Banaras Hindu University, 221 005, Varanasi, India. vkshuklabhu@gmail.com.ORCID http://orcid.org/0000-0002-2585-3478
Institute of Medical Sciences · IN

Funding

Department and Health Research New Delhi Ref. No. R.12013/06/2019-HR
6 · The paper itself

Abstract

backgroundGallbladder cancer (GBC) represents a wide geographical diversity as well as heterogeneity in clinical and genomic landscape. There seems to be little progress in the development of diagnostic biomarkers, targeted therapies or individualized approaches to GBC management. In this study, we investigated the whole transcriptome profile of GBC patients using RNA sequencing and identified key genes and pathways associated with gallbladder cancer using bioinformatics. METHODOLOGY: A total of 10 cases of GBC were collected and sequenced. The raw reads of the gallbladder sample was compared with the gallbladder normal control (SRA Database ID: ERX288537: HPA RNA-seq normal tissues gallbladder). Using Gene ontology analysis the differentially expressed genes were categorized into the biological pathway, cellular component, and molecular function. Pathway enrichment analyses, protein-protein interaction, transcription factor and miRNA interaction that regulate the expression of hub genes were conducted using bioinformatics tool.

resultsA total of 954 differentially expressed mRNA transcripts were identified, including overexpression of REG4, TMEM238, S100A2, LYPD2, and KRT17, as well as underexpressed genes like CCKAR, IGSF10, CHRM2, CRISP3, and FGF19. Enrichment analysis showed the metabolic pathways to be the top five cancer pathways in gallbladder carcinogenesis besides PI3k-Akt signalling pathway, cAMP signalling pathway, miRNAs in cancer, and cell adhesion profile of GBC.

conclusionsCCKAR, CDKN2A and LRRK2 were found to be most involved genes in its progression and development through different regulatory pathways. Further, most of the genes were significantly involved in PI3k-Akt, Wnt and hedgehog signaling pathways which have a key role in gallbladder cancer development.

Indexed as

Gallbladder NeoplasmsMicroRNAsHedgehog ProteinsHumansPhosphatidylinositol 3-KinasesProto-Oncogene Proteins c-aktRNA, MessengerTranscriptomeHedgehog ProteinsMicroRNAsPhosphatidylinositol 3-KinasesProto-Oncogene Proteins c-aktRNA, MessengerDifferentially expressed genes (DEGs)Gallbladder Cancer (GBC)Pathway Enrichment AnalysisRNA sequencingTranscriptome Profile

Identifiers

PMID35469389
OpenAlexW4224780985

What OpenQuestion holds

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Read underepoch 390

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.