State-Specific Cancer Gene Dynamics and Their Clinical Implications
Metastatic cancer is a leading cause of mortality, yet most genomics research focuses on primary tumors, limiting our understanding of cancer genes across cancer states. In this study, we analyzed interactions between mutations and copy-number alterations within genes across 25,000 tumor samples in both primary and metastatic states. Our findings reveal distinct interaction strengths across cancer types in primary versus metastatic tumors. Notably, many genes, including ARID1A, FBXW7, and SMARCA4, transition between one-hit and two-hit drivers to optimize cancer fitness depending on the state. We also identified state-specific third-order genetic interactions modulating interaction strength in the presence of other mutations. Our study underscores the dynamic roles of cancer genes and their adaptability as tumors progress, offering insights for more precise therapeutic strategies. This analysis enhances understanding of cancer gene dynamics and underscores the need to consider cancer state and treatment conditions in targeted therapies, as demonstrated by survival analysis.
Authors :
Adrián Maqueda Real, Laia Ollé Monràs and Solip Park.
Contact :
Adrián Maqueda Real (amaqueda@cnio.es) and Solip Park (solippark@cnio.es).
Analysis across cancer types and states
The table shows the results for tested mutation:CNA pairs across cancer types and stages. Pairs were tested if the gene had a mutation frequency >= 1% and a copy-number frequency >= 10%.
Effect of single genes
The figure shows the effect size of the selected gene across tested cancer types and stages. Two types of copy-number alterations are shown. Select a gene to display the corresponding plot.
Class information across cancer stages
Genes were classified whether they had significan co-ocurrences between mutations and CNAs or not. This figure shows the class distribution of all the genes that were classified across both cancer states.
Analysis across cancer types and states dividing primary samples
The table shows the results for tested mutation:CNA pairs across cancer types and stages. In this case, primary samples were divided according to whether they came from patients that developed metastasis (Primary_W_Metastasis) or not (Primary_WO_Metastasis). Pairs were tested using the same thresholds (gene mutation frequency >= 1% and gene copy-number frequency >= 10%.
Gene classification distribution
Genes were classified whether they had significan co-ocurrences between mutations and CNAs or not. This figure shows the class distribution of all the genes that were classified across both cancer states, including the different classifications of primary samples: all primary samples together ("Primary"), primary samples without metastasis ("P no met") and primary samples with metastasis ("P met").
Distribution of perturbed and consistent genes considering different classification of primary samples
Some genes were tested in both cancer states. Genes that belong to the same class in both states were classified as consistent, whereas they were classified as perturbed if the class differs. The figure shows the proportion of consistent and perturbed across different classifications of primary samples.
Average effect size analysis
Comparison of the average effect size across cancer types and different state-treatment conditions. Significance lines are shown when P-value <= 0.05.
Analysis across cancer types, states and treatment condition
The table shows the results for tested mutation:CNA pairs across cancer types and different stages and treatment conditions. As in previous cases, pairs were tested if the gene had a mutation frequency >= 1% and a copy-number frequency >= 10%.
Effect of single genes on treatment analysis
The figure shows the effect size of the selected gene across tested cancer types, stages and treatment conditions. Two types of copy-number alterations are shown. Select a gene to display the corresponding plot.
Odds ratio heterogeneity analysis
Results for the selected odds ratio heterogeneity test. Pairs tested in both conditions (i.e. mutation frequency >= 1% and copy-number frequency >= 10%) were selected for this analysis.
Three way analysis
The table shows the results for tested three way pairs across cancer types and stages. Pairs were tested if the first gene (GeneA) had a mutation frequency >= 1% and a copy-number frequency >= 10%, and if the second gene (GeneB) had a mutation frequency >= 1%.
Effect size in 2-way and 3-way analyses
Figure showing the effect size of significant 3-way interactions at FDR 10%. 3way is the effect size of the 3-way interaction, 2wMutB the effect size of the 2-way interaction for samples with GeneB mutated, 2wNoMutB the effect size of the 2-way for samples with GeneB not mutated and 2way the effect of the 2-way interaction for all the samples (same results as shown in the second tab). You can select one of the significant pairs at FDR 10% to show its network (select gene, tissue and state on the left menu).