Synchronous recurrence of concurrent colon adenocarcinoma and dedifferentiated liposarcoma

Jung, Eunok; Heinemann, Frank; Egelston, Colt; Wang, Jennifer; Pollock, Raphael E.; Lee, Peter P.; Tseng, William W.

doi:10.1136/bcr-2018-228868

Cited by 4 publications

(1 citation statement)

References 18 publications

(18 reference statements)

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“…So far, continuous advancement of surgical technology has improved the survival rate of patients with COAD (5). However, the prognosis of patients, especially at advanced stage, remains poor due to high recurrent rate (6)(7)(8). Consequently, it is necessary to identify more characteristic and valuable biomarkers for the early prediction and treatment of COAD recurrence.…”

Section: Introductionmentioning

confidence: 99%

Integrative Proteo-Genomic Analysis for Recurrent Survival Prognosis in Colon Adenocarcinoma

Wang

Liu

et al. 2022

Front. Oncol.

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BackgroundThe survival prognosis is the hallmark of cancer progression. Here, we aimed to develop a recurrence-related gene signature to predict the prognosis of colon adenocarcinoma (COAD).MethodsThe proteomic data from the Clinical Proteomic Tumor Analysis Consortium (CPTAC) and genomic data from the cancer genomic maps [The Cancer Genome Atlas (TCGA)] dataset were analyzed to identify co-differentially expressed genes (cDEGs) between recurrence samples and non-recurrence samples in COAD using limma package. Functional enrichment analysis, including Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway was conducted. Univariate and multivariate Cox regressions were applied to identify the independent prognostic feature cDEGs and establish the signature whose performance was evaluated by Kaplan–Meier curve, receiver operating characteristic (ROC), Harrell’s concordance index (C-index), and calibration curve. The area under the receiver operating characteristic (ROC) curve (AUROC) and a nomogram were calculated to assess the predictive accuracy. GSE17538 and GSE39582 were used for external validation. Quantitative real-time PCR and Western blot analysis were carried out to validate our findings.ResultsWe identified 86 cDEGs in recurrence samples compared with non-recurrence samples. These genes were primarily enriched in the regulation of carbon metabolic process, fructose and mannose metabolism, and extracellular exosome. Then, an eight-gene-based signature (CA12, HBB, NCF1, KBTBD11, MMAA, DMBT1, AHNAK2, and FBLN2) was developed to separate patients into high- and low-risk groups. Patients in the low-risk group had significantly better prognosis than those in the high-risk group. Four prognostic clinical features, including pathological M, N, T, and RS model status, were screened for building the nomogram survival model. The PCR and Western blot analysis results suggested that CA12 and AHNAK2 were significantly upregulated, while MMAA and DMBT1 were downregulated in the tumor sample compared with adjacent tissues, and in non-recurrent samples compared with non-recurrent samples in COAD.ConclusionThese identified recurrence-related gene signatures might provide an effective prognostic predictor and promising therapeutic targets for COAD patients.

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