Evidence map›Paper›PMID 38285789›Full record

ArticleAsian Pacific journal of cancer prevention : APJCP2024

Transcriptomic Profiling of OSCC Patients in an Indian Subset.

Amisha Patel, Alpesh Kikani, Gautam Makadiya, Sejal Shah

Open access · goldAbstract read
In one paragraph

Article in Asian Pacific journal of cancer prevention : APJCP, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
1.6field-weighted citation impact, top 17% 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

0 citing papers in PubMed, 4 citations in OpenAlex.

No citing paper in PubMed yet.

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 2 institutions in 1 country.

Amisha PatelDepartment of Microbiology, School of Science, RK University, Rajkot, Gujarat, India.
Alpesh KikaniShashwat Haemato Onco Associates, Rajkot, Gujarat, India.
Gautam MakadiyaShashwat Haemato Onco Associates, Rajkot, Gujarat, India.
Sejal ShahDepartment of Bioinformatics, Faculty of Technology, Marwadi University, Rajkot, Gujarat, India.ORCID 0000-0002-7664-4086
Marwadi University · INRK University · IN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundTumor-specific biomarkers are needed for accomplishing antidote in early detection, as well as prognosis and designing therapeutic strategies. Comprehensive transcriptome profiling offers critical insights into the disease and reveal new avenue for drug discovery.

methodsTotal 5 cancerous and histopathological normal tissue pairs of 5 OSCC patients included in the petite study. Transcriptome sequencing was performed using Roche's 454 sequencing platform followed by CLC Genomics Workbench was used to examine gene expression in OC development.

resultsA total 2082 genes were differentially expressed across all the five tumor-control pairs collected from the OC patients during the surgery. From these 1092 upregulated and 273 downregulated genes, whereas 717 genes were found to be non-significant. The genes with pvalue <0.05 and log2foldchange > 1 or log2foldchange < -1 were considered for further enrichment analysis. Topfunn was used for gene enrichment analysis to identify gene enrichment pathway analysis found some cancer related pathways such as TNF signaling, p53 signaling pathway, cGMP-PKG signaling pathway, Apelin signaling pathway and IL-17 signaling pathway were strikingly involved in proliferation and apoptosis of tumor cells. The PPI network construction was performed and identified 8 best protein interactions.

conclusionThe current study reports molecular biomarkers including INHBA, FJX1, OLR1, CDK2, IGHM, CXCL11, SH2D5 and FABP5 associated with cancer that can led to identify potential therapeutic targets for the better prognosis of the cancer patients. The signature candidate can be translated to clinical practice to increase early diagnostic accuracy.

Indexed as

NeoplasmsTranscriptomeBiomarkers, TumorComputational BiologyFatty Acid-Binding ProteinsGene Expression ProfilingGene Expression Regulation, NeoplasticGene Regulatory NetworksGenomicsHumansBiomarkers, TumorFABP5 protein, humanFatty Acid-Binding ProteinsBiomarkersGene expressiononcogenesOSCCPrognosis

Identifiers

PMID38285789
PMCPMC10911733
OpenAlexW4391305045

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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 OpenQuestion graph.