Genomic Profiling of 24 Colorectal Neuroendocrine Tumors Across Grades

24 colorectal neuroendocrine tumor (CRNET) samples were analyzed via whole-exome sequencing by Hongfa Xu. The dataset, last updated in May 2026, identifies somatic single nucleotide polymorphisms (SNPs), copy number variations (CNVs), and mutation signatures across G1, G2, and G3 tumor grades. It highlights grade-specific variants in genes like HYDIN and links to pathways such as RTK-RAS, Notch, WNT, and Hippo.

Use Cases

• Identifying candidate biomarkers for tumor grade based on the described HYDIN mutation patterns.
• Analyzing copy number variation patterns in genes like POP4, PPARG, MYC, F10, VOPP1, and UGT2B17 across different tumor grades.
• Investigating mutation signatures, such as signature 6 predominant in G3 tumors, for insights into carcinogenic processes.
• Studying the association of KMT2A gene mutations with potential clinical drug responses as mentioned in the description.

Strengths

• Whole-exome sequencing data from 24 tumor samples provides a molecular snapshot.
• Analysis distinguishes findings across G1, G2, and G3 tumor grades.
• The dataset is licensed under CC-BY-4.0 for open reuse.

Limitations

• The dataset is very small at 9.5 KB, indicating limited scope.
• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.

Provenance

Source

Hongfa Xu via figshare

Collection Method

Whole-exome sequencing of 24 colorectal neuroendocrine tumor samples.

Freshness

Last updated 2026-05-11 22:04:44; freshness should be verified.