Level C· Early human research exploring benefitsProspective StudyEurope PMCOpen access

Transcriptome Analysis of Subcutaneous Adipose Tissue from Severely Obese Patients Highlights Deregulation Profiles in Coding and Non-Coding Oncogenes

Rey F., Messa L., Pandini C., Launi R., Barzaghini B., Micheletto G.

Prospective Study on Type 2 Diabetes, published in Int J Mol Sci (2021) — summary generated from the PubMed abstract.

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Level C· Early human research exploring benefitsEvidence level of this study

Early human evidence such as case series or small samples is exploring possible benefits.

  • Level A · Stronger Clinical Evidence
  • Level B · Emerging clinical evidence with positive signals
  • Level C · Early human research exploring benefits
  • Level D · Scientific groundwork from lab and animal studies
  • Emerging · Emerging topic under active research
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This page is generated from the PubMed record. The Thai description is an automated summary of bibliographic fields and the abstract, not a full translation, and is not medical advice.

Study type
Prospective Study
Journal
Int J Mol Sci (2021)
Reported sample size
—
Source database
Europe PMC
PMID
33671464
PMCID
PMC7922682
DOI
10.3390/ijms22041989
Citations
14

Abstract (original English)

Obesity is a major risk factor for a large number of secondary diseases, including cancer. Specific insights into the role of gender differences and secondary comorbidities, such as type 2 diabetes (T2D) and cancer risk, are yet to be fully identified. The aim of this study is thus to find a correlation between the transcriptional deregulation present in the subcutaneous adipose tissue of obese patients and the oncogenic signature present in multiple cancers, in the presence of T2D, and considering gender differences. The subcutaneous adipose tissue (SAT) of five healthy, normal-weight women, five obese women, five obese women with T2D and five obese men were subjected to RNA-sequencing, leading to the identification of deregulated coding and non-coding RNAs, classified for their oncogenic score. A panel of DE RNAs was validated via Real-Time PCR and oncogene expression levels correlated the oncogenes with anthropometrical parameters, highlighting significant trends. For each analyzed condition, we identified the deregulated pathways associated with cancer, the prediction of possible prognosis for different cancer types and the lncRNAs involved in oncogenic networks and tissues. Our results provided a comprehensive characterization of oncogenesis correlation in SAT, providing specific insights into the possible molecular targets implicated in this process. Indeed, the identific

What this study does not prove

  • • This study does not prove SVF is an approved treatment or a replacement for standard care.

Evidence level

Early human evidence such as case series or small samples is exploring possible benefits.

How we grade evidence
HumansNeoplasmsDiabetes Mellitus, Type 2ObesityPrognosisGene Expression ProfilingSignal TransductionTranscription, GeneticGene Expression RegulationSex Characteristics

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