Abstract 498P
Background
Rare cancers, defined as malignant tumors with an incidence of less than 6 per 100,000 individuals per year, are complex for diagnosis and treatment due to limited clinical data. However, pan-cancer analysis suggests consistent mutational processes across diverse cancer types, offering insights into universal cancer mechanisms, regardless of their origin. To understand molecular mechanisms and inform personalized treatment strategies, this study aimed to analyze predictive models of oncogenic RNA expression based on DNA mutations, using multi-omics data from Asian rare cancer patients.
Methods
This research was a observational prospective study from the MASTER KEY Asia project, involving hospitals from Malaysia, the Philippines, and Taiwan. DNA and RNA were extracted from formalin-fixed paraffin-embedded (FFPE) specimens for next-generation sequencing (NGS) analysis using the TOP2 panel, alongside the evaluation of clinicopathological data for 128 rare cancer patients (50 ± 15 years old). RNA oncogene expression was analyzed using TPM Z-scores and Stepwise Linear Regression assessed the use of DNA alterations as predictive factors.
Results
DNA alterations predicted the RNA expression of 15 oncogenes/tumor suppressor genes. Higher BRCA1 expression correlated (p=0.001, R2 0.103) with alterations in PIK3CA (OR: 2.025, p=0.001) and KMT2D (OR: 1.696, p=0.008). ERBB2 expression was associated (p<0.001; R2 0.198) with alterations in ERBB2 (OR: 4.844, p=0.001) and ARID1A (OR: 3.110, p<0.001). TP53 alterations predicted lower expression of MDM2 (p<0.001, R2 0.143, OR: -3.159 of z-score). Patients with BRCA1 overexpression and DNA alterations in either PIK3CA or KMT2D had a higher frequency of disease progression after drug treatment (p=0.008). Additionally, patients with TP53 gain of function had a higher rate of disease progression (p=0.007), with a trend of higher MDM2 expression compared to TP53 loss of function (p=0.08).
Conclusions
In this study, DNA alterations effectively predicted the RNA expression of some oncogenes. This genomic analysis uncovers significant associations that can inform targeted therapies and personalized treatment strategies, improving outcomes for patients with rare cancers.
Clinical trial identification
Editorial acknowledgement
Legal entity responsible for the study
The authors.
Funding
Daiichi Sankyo, Eisai, Otsuka Pharmaceutical.
Disclosure
All authors have declared no conflicts of interest.