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Related Concept Videos

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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Spatial Profiling of Protein and RNA Expression in Tissue: An Approach to Fine-Tune Virtual Microdissection
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Spatial transcriptomics identifies SPARC as a prognostic marker in interstitial lung diseases.

Takayuki Niitsu1,2, Toshiaki Kataoka3, Kiyoharu Fukushima1,2

  • 1Department of Respiratory Medicine and Clinical Immunology, Osaka University Graduate School of Medicine, Suita, Japan.

The Journal of Pathology
|July 28, 2025
PubMed
Summary

Spatial transcriptomics identified SPARC as a key molecule in progressive lung fibrosis across interstitial lung diseases (ILDs). Higher SPARC levels indicate poor prognosis in unclassifiable ILDs (uILDs), suggesting its potential as a prognostic marker.

Keywords:
SPARCfibrosisinterstitial lung diseases (ILDs)single‐cell RNA sequencing (scRNA‐seq)spatial transcriptomics (ST)unclassifiable ILDs (uILDs)

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Area of Science:

  • Pulmonary Medicine
  • Molecular Biology
  • Genomics

Background:

  • Interstitial lung diseases (ILDs) are a group of lung disorders characterized by progressive fibrosis and poor prognosis.
  • Identifying molecular drivers of fibrosis is crucial for understanding ILD pathogenesis and developing treatments.

Purpose of the Study:

  • To identify key molecules involved in progressive fibrosis across various ILDs using spatial transcriptomics (ST).
  • To evaluate the prognostic significance of identified molecules, particularly in unclassifiable ILDs (uILDs).

Main Methods:

  • Spatial transcriptomics (Visium) and high-dimensional weighted gene coexpression network analysis (hdWGCNA) on lung cryobiopsy specimens.
  • Integration with public single-cell RNA sequencing datasets for enrichment and cell-cell communication analysis.
  • Immunohistochemical staining for validation and prognostic assessment in a cohort of 71 uILD patients.

Main Results:

  • A distinct gene module (SM2) enriched in active fibrotic lesions was identified, characterized by fibroblast activation.
  • Key hub genes including COL1A2, COL3A1, COL1A1, and SPARC formed a coexpression network.
  • SPARC was highly expressed in early fibrotic lesions and associated with poor overall survival in uILD patients.

Conclusions:

  • An integrated ST approach revealed key gene expression patterns in active fibrosis.
  • SPARC is identified as a significant prognostic marker for ILDs, especially uILDs.
  • This study provides insights into the molecular mechanisms of lung fibrosis and offers a potential biomarker for patient stratification.