The genetic alteration spectrum of the SWI/SNF complex: The oncogenic roles of BRD9 and ACTL6A

Abstract

SWItch/Sucrose NonFermentable (SWI/SNF) is a set of multi-subunits chromatin remodeling complexes, playing important roles in a variety of biological processes. Loss-of-function mutations in the genes encoding SWI/SNF subunits have been reported in more than 20% of human cancers. Thus, it was widely considered as a tumor suppressor in the past decade. However, recent studies reported that some genes encoding subunits of SWI/SNF complexes were amplified and play oncogenic roles in human cancers. In present study, we summarized the genetic alteration spectrum of SWI/SNF complexes, and firstly systematically estimated both the copy number variations and point mutations of all 30 genes encoding the subunits in this complex. Additionally, the bioinformatics analyses were performed for two significantly amplified genes, ACTL6A and BRD9, to investigate their oncogenic roles in human cancers. Our findings may lay a foundation for the discovery of potential treatment targets in SWI/SNF complexes of cancers.

Fig 1. SWI/SNF complex structures.

Schematic representation of canonical BAF, PBAF and noncanonical BAF composition. The orange subunits are unique to cBAF, yellow subunits are unique to PBAF, and green subunits are unique to ncBAF.

Fig 2. SWI/SNF complex mutations are quite pervasive within a wide range of human cancers.

(A) This bar chart shows the genetic alteration frequency of the SWI/SNF complex within 25 types of cancers. Green indicates point mutations, blue indicates deletions, and red indicates amplifications. It is clear that the copy number variation (CNV) frequency of the SWI/SNF complex within 25 types of cancers constitutes a large proportion of the chart. There are 14 cancers in which the CNV frequency of the SWI/SNF complex exceeds 20%. However, for point mutations, there are only 3 types of cancers (melanoma, ccRCC, and stomach cancer) with frequencies above 20%. (B) This figure shows the genetic alteration frequency of 8 subunits among 10 cancer types. Red indicates point mutations, and green indicates CNVs. The differing sizes of the bubbles represent the genetic alteration frequency of each subunit among 10 cancer types. Larger bubbles indicate a higher genetic alteration frequency of subunits within these cancer types.

Fig 3. Comparison of ACTL6A and BRD9 mRNA expression between the normal tissues and tumor tissues.

A) ACTL6A differentially mRNA expression between some normal tissues and serval cancers. (B) BRD9 differentially mRNA expression between normal tissues and a wide range of cancers. (P value significant codes: 0≤***<0.001≤**<0.01≤*<0.05≤.<0.1). These boxplots show that the mRNA expression of ACTL6A and BRD9 within most tumors are higher than that in normal cells.

Fig 4. Relationship between ACTL6A and BRD9 mRNA expression and survival rate within each patient from TCGA.

(A) This forest plot shows the relationship between the ACTL6A mRNA expression level and the survival rate of cases. The combined HR is 1.09 (HR>1), 95% CI (0.93,1.26). (B) This forest plot represents the relationship between the BRD9 mRNA expression level and survival rate of cases. The combined HR was 1.08 (HR>1), 95% CI (0.93, 1.26).

Fig 5. ACTL6A and BRD9 statistically significantly associated biological pathways.

It is a bar chart depicting the ACTL6A- and BRD9-associated pathways. The y-axis indicates the pathway name, and the x-axis indicates the enrichment factor. This chart shows that ACTL6A and BRD9 are most significantly associated with the oxidative phosphorylation and ribosome pathways.

Fig 6. GSEA results of ACTL6A and BRD9 within oxidative phosphorylation and ribosome pathways.

(A) Enrichment plot of the oxidative phosphorylation for ACTL6A. (B) Enrichment plot of the oxidative phosphorylation for BRD9. (C) Enrichment plot of ribosome pathways for ACTL6A. (D) Enrichment plot of ribosome pathways for BRD9. Among these figures, there are two phenotypes—the positive and the negative groups in each plot. The red bar marks the upregulated group. The blue bar indicates the downregulated group. Each vertical line of two plots represents the genes involved in oxidative phosphorylation. Their enrichment score (ES) is calculated following the list genes in oxidative phosphorylation. When encountering the involved genes, the ES will increase, and vice versa for the uninvolved genes. The trend lines of the two plots are downward following the gene list. Therefore, the involved genes are mostly clustered in the downregulated zone.

Fig 7. OncoPrint plot.

This plot shows the genomic profile of the gain and amplification of TP63, ACTL6A and BRD9 in cancer patients. These TCGA datasets from cBioPortal are based on the following 3 cancer types: ovarian cancer, esophageal cancer and lung adenocarcinoma. Each vertical line indicates one genetic file of the patient. The red bar indicates the amplification, the pink bar indicates the gain, and the gray bar indicates no alteration. ACTL6A is most significantly amplified with TP63 (p<0.001, log odds ratio>3). BRD9 is also significantly amplified with ACTL6A (p<0.001, log odds ratio = 1.051) and TP63 (p<0.001, log odds ratio = 0.907).