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Sepsis-associated pathways segregate cancer groups.

Himanshu Tripathi1, Samanwoy Mukhopadhyay1, Saroj Kant Mohapatra2

  • 1National Institute of Biomedical Genomics, P.O. NSS, Kalyani, Nadia, West Bengal, 741251, India.

BMC Cancer
|April 16, 2020
PubMed
Summary
This summary is machine-generated.

Sepsis and cancer share biological pathways. A study found that some cancers (Sepsis-Like Cancer) have similar gene expression to Septic Shock, unlike other cancers (Cancer Alone). This discovery aids in understanding disease links.

Keywords:
CancerGEOKEGG pathwaySepsisSeptic shockTCGA

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Area of Science:

  • Systems biology
  • Transcriptomics
  • Oncology
  • Infectious disease

Background:

  • Sepsis and cancer are leading causes of death, with each condition increasing the risk of the other.
  • Shared biological mechanisms likely underlie the increased susceptibility between sepsis and cancer.
  • Previous research indicated cancer-related pathways are upregulated in Septic Shock (SS).

Purpose of the Study:

  • To comprehensively compare the transcriptomes of Septic Shock (SS) and various cancer types.
  • To identify shared biological pathways and transcriptomic similarities between sepsis and cancer.
  • To classify cancer types based on their transcriptomic relationship to sepsis.

Main Methods:

  • Gene Set Enrichment Analysis (GSEA) to identify enriched pathways in SS and cancer.
  • Hierarchical clustering to segregate 17 cancer types based on transcriptomic profiles relative to SS.
  • Network analysis for biological significance and survival analysis for clinical significance of pathways.
  • Machine learning for developing a robust classifier to distinguish cancer groups.

Main Results:

  • 66 pathways were enriched in both SS and cancer.
  • Cancer types were segregated into two groups: Sepsis-Like Cancer (SLC) and Cancer Alone (CA), based on transcriptomic changes.
  • SLC, primarily gastrointestinal cancers often linked to infection, showed upregulation similar to SS; CA did not.
  • A machine learning classifier accurately (>98%) distinguished between SLC and CA groups.
  • Pathway upregulation correlated with improved survival in the SLC group.

Conclusions:

  • A systems biology approach using transcriptomics successfully categorizes cancers into SLC and CA based on similarity to SS.
  • Host response to infection is crucial in the pathogenesis of both SS and SLC.
  • A component of the host response may offer protection in both SS and SLC conditions.