Wei Xie1, He Xiao1, Jia Luo1, Lianhua Zhao2, Feng Jin1, Jungang Ma1, Jian Li1, Kai Xiong1, Chuan Chen1, Ge Wang3. 1. Department of Cancer Center, Daping Hospital, Army Medical University, Chongqing, China. 2. Department of Pathology, Daping Hospital, Army Medical University, Chongqing, China. 3. Department of Cancer Center, Daping Hospital, Army Medical University, Chongqing, China. Electronic address: wangge70@hotmail.com.
Abstract
BACKGROUND: There is an urgent clinical need to select the patients with resectable gastrointestinal stromal tumors (GISTs) who can benefit from adjuvant treatment after complete resection based on disease recurrence risk stratification. We hypothesized that integrating biomarkers into available risk assessment tools may improve the precision of GIST prognostic predictions. METHODS: Candidate genes that may cause GIST progression were identified using the Gene Expression Omnibus dataset GSE20708. Quantitative Real-time was used to confirm the prognostic value of the candidate genes for recurrence-free survival (RFS) in a cohort of 94 patients. RESULTS: Thirty-seven differentially expressed genes between localized tumors and metastatic primary tumors were found; 14 (37.8%) were upregulated and 23 (62.2%) were downregulated in the latter tumors. Low-density lipoprotein receptor class A domain containing 4 (LDLRAD4) was selected for further prognostic analysis. Although LDLRAD4 mRNA expression was not associated with recurrence risk grades as determined by the revised NIH consensus criteria, multivariate Cox regression analysis showed that LDLRAD4 expression (hazard ratio [HR] = 4.403, 95% confidence interval [CI]: 1.822-10.641, P = 0.001), tumor size (HR = 1.174, 95% CI: 1.027-1.342, P = 0.019) and tumor location (HR = 6.291, 95% CI: 1.128-35.080, P = 0.036) were independent prognostic factors for RFS in patients with resectable GISTs. Moreover, the RFS model constructed by these three factors may effectively predict GIST prognosis within the first 2 postsurgical years. CONCLUSION: Our study identifies LDLRAD4 as a suitable prognostic marker for GISTs. The integration of biomarkers into risk assessment tools may improve the precision of GIST prognostic predictions.
BACKGROUND: There is an urgent clinical need to select the patients with resectable gastrointestinal stromal tumors (GISTs) who can benefit from adjuvant treatment after complete resection based on disease recurrence risk stratification. We hypothesized that integrating biomarkers into available risk assessment tools may improve the precision of GIST prognostic predictions. METHODS: Candidate genes that may cause GIST progression were identified using the Gene Expression Omnibus dataset GSE20708. Quantitative Real-time was used to confirm the prognostic value of the candidate genes for recurrence-free survival (RFS) in a cohort of 94 patients. RESULTS: Thirty-seven differentially expressed genes between localized tumors and metastatic primary tumors were found; 14 (37.8%) were upregulated and 23 (62.2%) were downregulated in the latter tumors. Low-density lipoprotein receptor class A domain containing 4 (LDLRAD4) was selected for further prognostic analysis. Although LDLRAD4 mRNA expression was not associated with recurrence risk grades as determined by the revised NIH consensus criteria, multivariate Cox regression analysis showed that LDLRAD4 expression (hazard ratio [HR] = 4.403, 95% confidence interval [CI]: 1.822-10.641, P = 0.001), tumor size (HR = 1.174, 95% CI: 1.027-1.342, P = 0.019) and tumor location (HR = 6.291, 95% CI: 1.128-35.080, P = 0.036) were independent prognostic factors for RFS in patients with resectable GISTs. Moreover, the RFS model constructed by these three factors may effectively predict GIST prognosis within the first 2 postsurgical years. CONCLUSION: Our study identifies LDLRAD4 as a suitable prognostic marker for GISTs. The integration of biomarkers into risk assessment tools may improve the precision of GIST prognostic predictions.
Authors: Ha T N Nguyen; Haoliang Xue; Virginie Firlej; Yann Ponty; Melina Gallopin; Daniel Gautheret Journal: BMC Cancer Date: 2021-04-12 Impact factor: 4.430
Authors: Eliana Portilla-Fernandez; Derek Klarin; Shih-Jen Hwang; Mary L Biggs; Joshua C Bis; Stefan Weiss; Susanne Rospleszcz; Pradeep Natarajan; Udo Hoffmann; Ian S Rogers; Quynh A Truong; Uwe Völker; Marcus Dörr; Robin Bülow; Michael H Criqui; Matthew Allison; Santhi K Ganesh; Jie Yao; Melanie Waldenberger; Fabian Bamberg; Kenneth M Rice; Jeroen Essers; Daniek M C Kapteijn; Sander W van der Laan; Rob J de Knegt; Mohsen Ghanbari; Janine F Felix; M Arfan Ikram; Maryam Kavousi; Andre G Uitterlinden; Anton J M Roks; A H Jan Danser; Philip S Tsao; Scott M Damrauer; Xiuqing Guo; Jerome I Rotter; Bruce M Psaty; Sekar Kathiresan; Henry Völzke; Annette Peters; Craig Johnson; Konstantin Strauch; Thomas Meitinger; Christopher J O'Donnell; Abbas Dehghan Journal: Hum Mol Genet Date: 2022-10-10 Impact factor: 5.121