ArticleOncotarget2016
A prognostic classifier for patients with colorectal cancer liver metastasis, based on AURKA, PTGS2 and MMP9.
Article in Oncotarget, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.
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Who cites it
11 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Systematic Review of the Prognostic Role of the Immune System After Surgery of Colorectal Liver Metastases.Frontiers in oncology · 2019Pooled it
- Identifying Key Genes Involved in Axillary Lymph Node Metastasis in Breast Cancer Using Advanced RNA-Seq Analysis: A Methodological Approach with GLMQL and MAS.International journal of molecular sciences · 2024Article
- Comprehensive analysis reveals a four-gene signature in colorectal cancer.Translational cancer research · 2020Article
- Impacts ofJournal of Cancer · 2019Article
- Collagen IV-conveyed signals can regulate chemokine production and promote liver metastasis.Oncogene · 2018Article
- Combining statistical techniques to predict postsurgical risk of 1-year mortality for patients with colon cancer.Clinical epidemiology · 2018Article
- Article
- Novel roles of DC-SIGNR in colon cancer cell adhesion, migration, invasion, and liver metastasis.Journal of hematology & oncology · 2017Article
- Knockdown of Decoy Receptor 3 Impairs Growth and Invasiveness of Hepatocellular Carcinoma Cell Line of HepG2.Chinese medical journal · 2016Article
- Protective effects of Huangqin Decoction against ulcerative colitis and associated cancer in mice.Oncotarget · 2016Article
- Extracellular translationally controlled tumor protein promotes colorectal cancer invasion and metastasis through Cdc42/JNK/ MMP9 signaling.Oncotarget · 2016Article
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Authors and funding
14 authors.
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No grant is acknowledged in the PubMed record.
Abstract
backgroundPrognosis of patients with colorectal cancer liver metastasis (CRCLM) is estimated based on clinicopathological models. Stratifying patients based on tumor biology may have additional value.
methodsTissue micro-arrays (TMAs), containing resected CRCLM and corresponding primary tumors from a multi-institutional cohort of 507 patients, were immunohistochemically stained for 18 candidate biomarkers. Cross-validated hazard rate ratios (HRRs) for overall survival (OS) and the proportion of HRRs with opposite effect (P(HRR < 1) or P(HRR > 1)) were calculated. A classifier was constructed by classification and regression tree (CART) analysis and its prognostic value determined by permutation analysis. Correlations between protein expression in primary tumor-CRCLM pairs were calculated.
resultsBased on their putative prognostic value, EGFR (P(HRR < 1) = .02), AURKA (P(HRR < 1) = .02), VEGFA (P(HRR < 1) = .02), PTGS2 (P(HRR < 1) = .01), SLC2A1 (P(HRR > 1) < 01), HIF1α (P(HRR > 1) = .06), KCNQ1 (P(HRR > 1) = .09), CEA (P (HRR > 1) = .05) and MMP9 (P(HRR < 1) = .07) were included in the CART analysis (n = 201). The resulting classifier was based on AURKA, PTGS2 and MMP9 expression and was associated with OS (HRR 2.79, p < .001), also after multivariate analysis (HRR 3.57, p < .001). The prognostic value of the biomarker-based classifier was superior to the clinicopathological model (p = .001). Prognostic value was highest for colon cancer patients (HRR 5.71, p < .001) and patients not treated with systemic therapy (HRR 3.48, p < .01). Classification based on protein expression in primary tumors could be based on AURKA expression only (HRR 2.59, p = .04).
conclusionA classifier was generated for patients with CRCLM with improved prognostic value compared to the standard clinicopathological prognostic parameters, which may aid selection of patients who may benefit from adjuvant systemic therapy.
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