Correlation Between Molecular Genetic Analysis and Nuclear Pleomorphism in Long-Term Recurrent and Metastatic Chordoma

TL;DR

This study explores how changes in tumor cell nuclei and genetic factors can predict recurrence and metastasis in chordoma, a rare and aggressive cancer.

Contribution

The study introduces quantitative nuclear morphometry as a potential biomarker for aggressive disease progression in chordoma.

Findings

Recurrent chordoma tumors show increased nuclear size, asymmetry, and altered shape compared to non-recurrent tumors.

Loss of nuclear envelope proteins and increased proliferation are linked to pleomorphic nuclei in recurrent and metastatic tumors.

Tumor mutational burden tends to be higher in recurrent cases, though overall mutational load remains low.

Abstract

Chordomas are rare malignant tumors with high recurrence rates and scarce treatment options due to chemo- and radiation insensitivity. At present, it is difficult to predict which tumors are likely to recur because routine light microscopy and imaging do not reliably capture subtle biological changes. We measured tumor cell nuclei in primary tumors, long-term recurrences, and metastases using quantitative image-based methods. We compared the results with protein expression and genome-wide mutation load obtained from whole-exome sequencing. Recurrent tumors showed measurable pleomorphic changes and higher proliferation over time. Loss and disruption of nuclear envelope proteins were observed in highly irregular nuclei of recurrent and metastatic tumors. These results suggest that objective nuclear measurements, combined with molecular profiling, may help identify aggressive disease courses and provide a foundation for the development of automated, AI-assisted digital tools for future risk assessment.

Background/Objectives: Recurrences and metastases occur frequently in chordoma and are the main factors influencing overall survival. However, prognostic biomarkers for recurrence remain limited. This study examines whether quantitative nuclear morphometry can capture recurrence evolution and whether it aligns with immunophenotype and genomic profiling. Methods: A total of 26 specimens from 12 adults (8 patients with non-recurrent tumors and 4 patients with multiple long-term recurrences and metastases over 7 to 16 years) were analyzed using whole-exome sequencing, immunohistochemistry, and nuclear morphometry. Results: Imaging studies and routine histology showed no consistent differences between groups. Morphometry revealed substantial intertumoral variability among non-recurrent tumors and significant longitudinal nuclear remodeling throughout recurrences, dominated by increased nuclear size and asymmetry, as well as altered shape. Primary tumors from patients who later recurred had smaller, more asymmetric, and denser nuclei than non-recurrent tumors. Recurrent samples showed higher proliferation and decreased lamin A/C expression, with focal disruption and detachment from the nuclear envelope in pleomorphic nuclei. The tumor mutational burden was low overall, varied between patients and timepoints, and tended to be higher in recurrent cases. Conclusions: Quantitative nuclear morphometry, integrated with immunophenotyping and genomic profiling, captures recurrence-associated phenotypic remodeling in chordoma and may provide a quantitative framework for future digital pathology or AI approaches, pending validation in larger cohorts.

Figures