Genome-Scale CRISPR-Cas9 Analysis Reveals Tumor Heterogeneity and Identifies NDC80 as Novel Biomarker in HCC.

Abstract

Background and aims: Hepatocellular carcinoma (HCC) is a malignant tumor with a poor prognosis and is characterized by severe intratumoral heterogeneity. Identifying key genomic features and more reliable classifications is helpful for clinical management.

Methods: Cancer essential genes (CEGs) were identified using genome-scale CRISPR-Cas9 and univariate Cox regression analyses. Based on gene expression, nonnegative matrix factorization (NMF) was used to generate distinct molecular subtypes. The nearest template prediction (NTP) algorithm was used to validate the accuracy and robust classifications among three independent cohorts, including GSE14520, GSE54236, and ICGC-LIRI. Specifically, potential biomarkers were screened for clinical transformation based on their prognostic characteristics and biological function features. EdU, colony formation, and Transwell assays were utilized to confirm the effect of biomarkers in vitro.

Results: The C1 subtype had the worst prognosis and was characterized by advanced AJCC stages and high genomic instability. The NTP approach confirmed that the molecular subtypes were practical, robust, and reproducible. We further identified NDC80 as a gene specifically expressed in C1 subtype, indicative of prognosis solely for this subtype. Based on overrepresentation analysis (ORA), it was found that the biological function of NDC80 was mainly enriched in proliferation. In vitro cellular assays verified that promoted tumor growth and migration.

Conclusions: Our study identified three robust molecular subtypes and revealed tumor heterogeneity. Meanwhile, the potential biomarker NDC80 served as a characteristic gene of the C1 subtype, correlating with poor prognosis and promoting tumor growth and migration, providing new insights for prognostic treatment strategies in HCC.