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Predicting treatment response from longitudinal images using multi-task deep learning

Radiographic imaging is routinely used to evaluate treatment response in solid tumors. Current imaging response metrics do not reliably predict the underlying biological response. …

DeepCC: a novel deep learning-based framework for cancer molecular subtype classification

Molecular subtyping of cancer is a critical step towards more individualized therapy and provides important biological insights into cancer heterogeneity. Although gene expression …

Feng GAO

• Aug 16, 2019 • 1 min read

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Gene expression signature in surgical tissues and endoscopic biopsies identifies high-risk T1 colorectal cancers

Genome-wide discovery of a novel gene-expression signature for the identification of lymph node metastasis in esophageal squamous cell carcinoma

**Objective:** This study aimed to develop a gene-expression signature for identification of lymph node (LN) metastasis in esophageal squamous cell carcinoma (ESCC) patients. …

A genomewide transcriptomic approach identifies a novel gene expression signature for the detection of lymph node metastasis in patients with early stage gastric cancer

**BACKGROUND:** Although identification of lymph node (LN) metastasis is a well-recognized strategy for improving outcomes in patients with gastric cancer (GC), currently there is …

Genome-wide discovery and identification of a novel miRNA signature for recurrence prediction in stage II and III colorectal cancer

## Abstract **Purpose:** The current tumor–node–metastasis (TNM) staging system is inadequate at identifying patients with high-risk colorectal cancer. Using a systematic and …

A microRNA signature associated with metastasis of T1 colorectal cancers to lymph nodes