Unknown

Dataset Information

0

Prediction of recurrence-free survival using a protein expression-based risk classifier for head and neck cancer.


ABSTRACT: Loco-regional recurrence in 50% of oral squamous cell carcinoma (OSCC) patients poses major challenge for oncologists. Lack of biomarkers that can predict disease aggressiveness and recurrence risk makes the scenario more dismal. On the basis of our earlier global proteomic analyses we identified five differentially expressed proteins in OSCC. This study aimed to develop protein biomarkers-based prognostic risk prediction model for OSCC. Sub-cellular expression of five proteins, S100A7, heterogeneous nuclear ribonucleoproteinK (hnRNPK), prothymosin ? (PTMA), 14-3-3? and 14-3-3? was analyzed by immunohistochemistry in test set (282 Indian OSCCs and 209 normal tissues), correlated with clinic-pathological parameters and clinical outcome over 12 years to develop a risk model for prediction of recurrence-free survival. This risk classifier was externally validated in 135 Canadian OSCC and 96 normal tissues. Biomarker signature score based on PTMA, S100A7 and hnRNPK was associated with recurrence free survival of OSCC patients (hazard ratio=1.11; 95% confidence interval 1.08, 1.13, P<0.001, optimism-corrected c-statistic=0.69) independent of clinical parameters. Biomarker signature score stratified OSCC patients into high- and low-risk groups with significant difference for disease recurrence. The high-risk group had median survival 14 months, and 3-year survival rate of 30%, whereas low-risk group survival probability did not reach 50%, and had 3-year survival rate of 71%. As a powerful predictor of 3-year recurrence-free survival in OSCC patients, the newly developed biomarkers panel risk classifier will facilitate patient counseling for personalized treatment.

SUBMITTER: Chauhan SS 

PROVIDER: S-EPMC4491610 | biostudies-literature | 2015 Apr

REPOSITORIES: biostudies-literature

altmetric image

Publications

Prediction of recurrence-free survival using a protein expression-based risk classifier for head and neck cancer.

Chauhan S S SS   Kaur J J   Kumar M M   Matta A A   Srivastava G G   Alyass A A   Assi J J   Leong I I   MacMillan C C   Witterick I I   Colgan T J TJ   Shukla N K NK   Thakar A A   Sharma M C MC   Siu K W M KW   Walfish P G PG   Ralhan R R  

Oncogenesis 20150420


Loco-regional recurrence in 50% of oral squamous cell carcinoma (OSCC) patients poses major challenge for oncologists. Lack of biomarkers that can predict disease aggressiveness and recurrence risk makes the scenario more dismal. On the basis of our earlier global proteomic analyses we identified five differentially expressed proteins in OSCC. This study aimed to develop protein biomarkers-based prognostic risk prediction model for OSCC. Sub-cellular expression of five proteins, S100A7, heteroge  ...[more]

Similar Datasets

| S-EPMC4381614 | biostudies-literature
| S-EPMC9477219 | biostudies-literature
| S-EPMC7918727 | biostudies-literature
2023-04-05 | E-MTAB-12431 | biostudies-arrayexpress
| S-EPMC10425733 | biostudies-literature
| S-EPMC5664005 | biostudies-literature
| S-EPMC3086939 | biostudies-literature
| S-EPMC8010242 | biostudies-literature
| S-EPMC6235739 | biostudies-literature
| S-EPMC3650639 | biostudies-literature