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Deep learning-derived spatial organization features on histology images predicts prognosis in colorectal liver metastasis patients after hepatectomy

Deep learning-derived spatial organization features on histopathology images to predict prognosis in patients with colorectal liver metastasis, after hepatectomy.

Background: Histopathological images of colorectal liver metastasis (CRLM) contain rich morphometric information that may predict patient outcomes, but current indicators depend on labor-intensive and subjective visual estimation. Herein, we aimed to …

Senescence-Based Colorectal Cancer Subtyping Reveals Distinct Molecular Characteristics and Therapeutic Strategies

An immune, stroma, and epithelial--mesenchymal transition-related signature for predicting recurrence and chemotherapy benefit in stage II--III colorectal cancer

## Abstract ## Background Debates exist on the treatment decision of the stage II/III colorectal cancer (CRC) due to the insufficiency of the current TNM stage‐based risk stratification system. Epithelial–mesenchymal transition (EMT) and tumor …

Single-cell RNA-seq recognized the initiator of epithelial ovarian cancer recurrence

Identification of an autophagy-related gene signature for the prediction of prognosis in early-stage colorectal cancer

Purpose: A certain number of early-stage colorectal cancer (CRC) patients suffer tumor recurrence after initial curative resection. In this context, an effective prognostic biomarker model is constantly in need. Autophagy exhibits a dual role in …

OCaMIR—a noninvasive, diagnostic signature for early-stage ovarian cancer: a multi-cohort retrospective and prospective study

## Abstract ## Purpose: Due to the lack of effective screening approaches and early detection biomarkers, ovarian cancer has the highest mortality rates among gynecologic cancers. Herein, we undertook a systematic biomarker discovery and validation …

Genome-Wide analysis reveals hypoxic microenvironment is associated with immunosuppression in poor survival of stage II/III colorectal cancer patients

Background: Hypoxia is associated with a poorer clinical outcome and resistance to chemotherapy in solid tumors; identifying hypoxic-related colorectal cancer (CRC) and revealing its mechanism are important. The aim of this study was to assess …

Deep learning to identify a gene signature associated with molecular subtypes that predicts prognosis in colorectal cancer.

Background: Identifying robust prognostic risk groups of colorectal cancer (CRC) will significantly improve patients’ outcomes. However, CRC has been demonstrated to be molecularly heterogeneous which affected clinical decision-making. Recently, a …

Identifying an immune-related gene-pair for prognosis prediction of metastatic colorectal cancer.

Background: Few robust predictive biomarkers have been applied in clinical practice due to the heterogeneity of metastatic colorectal cancer (mCRC) . Using the gene pair method, the absolute expression value of genes can be converted into the …