Backgrounds: Colorectal cancer (CRC) with high incidence, has the third highest mortality of tumors. DNA damage and repair influence a variety of tumors. However, the role of these genes in colon cancer prognosis has been less systematically investigated. Here, we aim to establish a corresponding prognostic signature providing new therapeutic opportunities for CRC.Method: After related genes were collected from GSEA, univariate Cox regression was performed to evaluate each gene’s prognostic relevance through the TCGA-COAD dataset. Stepwise COX regression was used to establish a risk prediction model through the training sets randomly separated from the TCGA cohort and validated in the remaining testing sets and two GEO datasets (GSE17538 and GSE38832). A 12-DNA-damage-and-repair-related gene-based signature able to classify COAD patients into high and low-risk groups was developed. The predictive ability of the risk model or nomogram were evaluated by different bioinformatics‐ methods. Gene functional enrichment analysis was performed to analyze the co-expressed genes of the risk-based genes.Result: A 12-gene based prognostic signature established within 160 significant survival-related genes from DNA damage and repair related gene sets performed well with an AUC of ROC 0.80 for 5 years in the TCGA-CODA dataset. The signature includes CCNB3, ISY1, CDC25C, SMC1B, MC1R, LSP1P4, RIN2, TPM1, ELL3, POLG, CD36, and NEK4. Kaplan-Meier survival curves showed that the prognosis of the risk status owns more significant differences than T, M, N, and stage prognostic parameters. A nomogram was constructed by LASSO regression analysis with T, M, N, age, and risk as prognostic parameters. ROC curve, C-index, Calibration analysis, and Decision Curve Analysis showed the risk module and nomogram performed best in years 1, 3, and 5. KEGG, GO, and GSEA enrichment analyses suggest the risk involved in a variety of important biological processes and well-known cancer-related pathways. These differences may be the key factors affecting the final prognosis.Conclusion: The established gene signature for CRC prognosis provides a new molecular tool for clinical evaluation of prognosis, individualized diagnosis, and treatment. Therapies based on targeted DNA damage and repair mechanisms may formulate more sensitive and potential chemotherapy regimens, thereby expanding treatment options and potentially improving the clinical outcome of CRC patients.
Diverse software and heterogeneous hardware pose new challenges in systems and architecture management. Managers benefit from improving introspective capabilities, which provide data across a spectrum of platforms, from software and datacenter profilers to performance counters and canary circuits. Despite this wealth of data, management has become more difficult as sophisticated decisions are demanded.To address these challenges, we present modeling strategies for integrated hardware-software analysis. These strategies include (i) identifying shared software behavior; (ii) quantifying that behavior in a portable, microarchitecture-independent manner; (iii) inferring generalized trends with statistical regression models; and (iv) automatically constructing/updating these models as new software profiles are obtained.Models produced by these strategies are accurate for general SPEC2006 applications with median errors of 8-10%. Predicted and actual performance are strongly correlated with coefficients of ρ > 0.9. Moreover, when we exploit application semantics and domain-specific software parameters, model accuracy improves and model complexity falls. In a case study for sparse linear algebra, we present models with 5% median error and new capabilities in coordinated hardware-software tuning.
We present an unusual case of a 41-year-old male patient with a large lymphangioma of the esophagus. Endoscopy revealed that the structure measured 60 × 10 mm in the mucosa and the submucosa and had a heterogenous echo pattern. The esophageal mass was successfully resected by endoscopic piecemeal mucosal resection. However, most esophageal lymphangiomas that are larger than 2 cm in diameter reported in the literature can be removed only through open surgery. Thus far, we know of no reported cases of endoscopic resection as a treatment for this case.
Objective. Brain metastasis (BM) is associated with a high mortality in patients with breast cancer (BC). Nevertheless, the molecular mechanisms of BM in BM remain uncertain. The study aims to identify the key genes in BC in relation to BM and to assess their prognostic value. Methods. Two microarray datasets GSE125989 and GSE100534 were downloaded from the Gene Expression Omnibus (GEO) database to identify differentially expressed genes (DEGs) between primary BC and BM samples. The function enrichment analysis and protein-protein interaction (PPI) network were performed. We mapped hub genes into the Kaplan–Meier database for their correlations with BC survival. Results. Venn diagram analysis showed an overlapped upregulated DEG and 18 overlapped downregulated ones between primary BC and BM samples. We constructed the PPI network, and top 5 hub genes were sorted out according to the node degree, including type I collagen α1 chain (COL1A1), lumican (LUM), type III collagen α1 chain (COL3A1), type V collagen α2 chain (COL5A2), and periosteal protein (POSTN). The Kaplan–Meier database analysis found that COL1A1, COL3A1, and POSTN were significantly correlated with overall survival of BC patients. Conclusion. The study suggests that COL1A1, COL3A1, and POSTN may be key genes associated with BM in patients with BC.
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