Intratumour ploidy heterogeneity and clonal evolution in hepatocellular carcinoma

Area of Science:

• Oncology
• Digital Pathology
• Genomics

Background:

• Hepatocellular carcinoma (HCC) is a leading cause of cancer death, necessitating biomarkers for improved prognosis and treatment prediction.
• Polyploidization, a common event in solid cancers, presents potential as a prognostic biomarker in HCC.
• Current methods for assessing HCC ploidy are limited, hindering clinical application.

Purpose of the Study:

• To develop and validate a high-throughput quantitative digital pathology approach for assessing HCC ploidy.
• To classify HCC into distinct ploidy subtypes (diploid, hyperploid, mixed) and analyze their spatial organization.
• To investigate the genomic and transcriptomic characteristics associated with different HCC ploidy subtypes.

Main Methods:

• Quantitative digital pathology on whole-slide imaging was used to assess nuclear morphometry and ploidy in 111 HCCs.
• Whole-exome sequencing (WES) and bulk RNA sequencing were performed for genomic and transcriptomic profiling.
• 3' mRNA sequencing and spatial transcriptomics were employed to study clonal evolution and spatial organization of hyperploid clones.

Main Results:

• HCCs were successfully classified into diploid (DP) and hyperploid (HP) subtypes using digital pathology.
• HP-HCCs were associated with a proliferative subclass, poor prognosis, and stemness characteristics via transcriptomic analysis.
• Spatial analysis revealed nascent hyperploid foci with transcriptomic overlap with HP-HCCs, indicating clonal evolution from diploid precursors via whole-genome doubling.

Conclusions:

• Nuclear ploidy profiling holds significant prognostic value in HCC.
• Hyperploid HCCs evolve clonally from intratumoral hyperploid foci, contributing to genomic instability in liver tumorigenesis.
• This study provides a novel digital pathology tool for HCC ploidy assessment, paving the way for new diagnostic and therapeutic strategies.