Proteomic characterization of non-small cell lung cancer in a comprehensive translational thoracic oncology database
2011

Proteomic Study of Non-Small Cell Lung Cancer

Sample size: 1323 publication 10 minutes Evidence: moderate

Author Information

Author(s): Surati Mosmi, Robinson Matthew, Nandi Suvobroto, Faoro Leonardo, Demchuk Carley, Rolle Cleo E, Kanteti Rajani, Ferguson Benjamin D, Hasina Rifat, Gangadhar Tara C, Salama April K, Arif Qudsia, Kirchner Colin, Mendonca Eneida, Campbell Nicholas, Limvorasak Suwicha, Villaflor Victoria, Hensing Thomas A, Krausz Thomas, Vokes Everett E, Husain Aliya N, Ferguson Mark K, Karrison Theodore G, Salgia Ravi

Primary Institution: Pritzker School of Medicine, University of Chicago

Hypothesis

How can clinical data be combined with proteomic analyses to determine the functional relevance of protein expression in non-small cell lung cancer?

Conclusion

The study suggests that a comprehensive database can enhance understanding of cancer biology and help identify targets for thoracic malignancies.

Supporting Evidence

  • Clinical data for 1323 patients with non-small cell lung cancer has been captured.
  • Proteomic studies have been performed on tissue samples from 105 of these patients.
  • 15 potential biomarkers were found to be significantly higher in tumor versus matched normal tissue.
  • Proteins belonging to the receptor tyrosine kinase family were particularly likely to be over expressed in tumor tissues.
  • The over expression of the glucocorticoid receptor was associated with improved overall survival.

Takeaway

Researchers looked at tissue samples from lung cancer patients to see how proteins behave in tumors compared to normal tissues, which can help find new ways to treat cancer.

Methodology

Clinical data were collected from patients with non-small cell lung cancer, and proteomic studies were performed on tissue samples analyzed for 33 protein biomarkers using tissue microarrays.

Potential Biases

Potential bias due to the retrospective nature of data collection and the lack of comprehensive vital status information.

Limitations

The study's sample size for each protein biomarker was limited, and there was a lack of true normal controls.

Participant Demographics

{"gender":{"male":688,"female":635},"race":{"caucasian":587,"african_american":377,"other":38,"non_specified":321},"mean_age_at_diagnosis":"64 years","median_survival":"17 months"}

Statistical Information

P-Value

p<0.05

Confidence Interval

95% CI: 0.59, 0.97

Statistical Significance

p<0.05

Digital Object Identifier (DOI)

10.1186/2043-9113-1-8

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