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lncRNA - Long Non-coding RNAs02:39

lncRNA - Long Non-coding RNAs

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In humans, more than 80% of the genome gets transcribed. However, only around 2% of the genome codes for proteins. The remaining part produces non-coding RNAs which includes ribosomal RNAs, transfer RNAs, telomerase RNAs, and regulatory RNAs, among other types. A large number of regulatory non-coding RNAs have been classified into two groups depending upon their length – small non-coding RNAs, such as microRNA, which are less than 200 nucleotides in length, and long non-coding RNA...
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  1. Home
  3. Correlation Between Ct Spectral Quantitative Parameters And Expression Levels Of Hif-1α And Alx1 In Non-small Cell Lung Cancer.
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  3. Correlation Between Ct Spectral Quantitative Parameters And Expression Levels Of Hif-1α And Alx1 In Non-small Cell Lung Cancer.

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Correlation between CT spectral quantitative parameters and expression levels of HIF-1α and ALX1 in non-small cell

Yulin Jia1, Qiulian Sun2, Yiqiao Wang3

  • 1Radiology Department, The First Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang, China.

Medicine
|November 29, 2024

View abstract on PubMed

Summary
This summary is machine-generated.

Spectral CT imaging can predict non-small cell lung cancer's biological characteristics by correlating quantitative parameters with hypoxia-inducible factor-1alpha (HIF-1α) and aristaless-like homeobox 1 (ALX1) expression levels. This non-invasive approach aids in tumor evaluation.

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Area of Science:

  • Radiology
  • Oncology
  • Molecular Biology

Background:

  • Non-small cell lung cancer (NSCLC) characterization relies on invasive methods.
  • Hypoxia-inducible factor-1alpha (HIF-1α) and aristaless-like homeobox 1 (ALX1) are key markers in tumor biology.
  • Spectral CT offers quantitative imaging insights.

Purpose of the Study:

  • To assess HIF-1α and ALX1 expression in NSCLC.
  • To correlate spectral CT quantitative parameters with these biomarkers.
  • To evaluate spectral CT for predicting NSCLC biological characteristics.

Main Methods:

  • Collected spectral CT data and tissue samples from 50 NSCLC patients.
  • Quantified CT parameters: spectral curve slope, effective atomic number, iodine concentration.
  • Measured HIF-1α and ALX1 expression via immunohistochemistry.

    • Main Results:

    • HIF-1α expression differed significantly with tumor differentiation (P<.001).
    • Spectral CT parameters showed significant differences across HIF-1α and ALX1 expression levels (P<.01).
    • Positive correlations were found between CT spectral parameters and biomarker expression levels.

    Conclusions:

    • Spectral CT quantitative parameters can differentiate NSCLC based on HIF-1α and ALX1 expression.
    • Spectral CT imaging shows promise for non-invasively predicting NSCLC biological features.
    • This technique may enhance understanding and management of NSCLC.