Evidence map›Paper›PMID 38676768›Full record

ArticleEndocrine2024

Identification of potential targetable genes in papillary, follicular, and anaplastic thyroid carcinoma using bioinformatics analysis.

Shipra Agarwal, Shikha Gupta, Rishav Raj

Abstract read
PubMed Publisher
In one paragraph

Article in Endocrine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed, 1 pooled it
0.4field-weighted citation impact, top 39% 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

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

  1. Guideline
  2. 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

3 authors at 2 institutions in 1 country.

Shipra AgarwalDepartment of Pathology, All India Institute of Medical Sciences, Ansari Nagar, New Delhi, India.
Shikha GuptaDepartment of Computer Science, S.S. College of Business Studies, University of Delhi, New Delhi, India. shikhagupta@sscbsdu.ac.in.
Rishav RajDepartment of Computer Science, S.S. College of Business Studies, University of Delhi, New Delhi, India.
All India Institute of Medical Sciences · INUniversity of Delhi · IN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeTo perform an extensive exploratory analysis to build a deeper insight into clinically relevant molecular biomarkers in Papillary, Follicular, and Anaplastic thyroid carcinomas (PTC, FTC, ATC).

methodsThirteen Thyroid Cancer (THCA) datasets incorporating PTC, FTC, and ATC were derived from the Gene Expression Omnibus. Genes differentially expressed (DEGs) between THCA and normal were identified and subjected to GO and KEGG analyses. Multiple topological properties were harnessed and protein-protein interaction (PPI) networks were constructed to identify the hub genes followed by survival analysis and validation.

resultsThere were 70, 87, and 377 DEGs, and 23, 27, and 53 hub genes for PTC, FTC, and ATC samples, respectively. Survival analysis detected 39 overall and 49 relapse-free survival-relevant hub genes. Six hub genes, BCL2, FN1, ITPR1, LYVE1, NTRK2, TBC1D4, were found common to more than one THCA type. The most significant hub genes found in the study were: BCL2, CD44, DCN, FN1, IRS1, ITPR1, MFAP4, MKI67, NTRK2, PCLO, TGFA. The most enriched and significant GO terms were Melanocyte differentiation for PTC, Extracellular region for FTC, and Extracellular exosome for ATC. Prostate cancer for PTC was the most significantly enriched KEGG pathway. The results were validated using TCGA data.

conclusionsThe findings unravel potential biomarkers and therapeutic targets of thyroid carcinomas.

Indexed as

Adenocarcinoma, FollicularComputational BiologyThyroid Carcinoma, AnaplasticThyroid NeoplasmsBiomarkers, TumorGene Expression ProfilingGene Expression Regulation, NeoplasticGene Regulatory NetworksHumansProtein Interaction MapsThyroid Cancer, PapillaryBiomarkers, TumorGene expression analysisGEOMicroarrayRNA-seq dataStatistical learningTCGA

Identifiers

PMID38676768
OpenAlexW4395688574

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.