MDPI
Article The BRCAness Landscape of Cancer
Maoni Guo and San Ming Wang *
MoE Frontiers Science Center for Precision Oncology, Cancer Centre and Institute of Translational Medicine, Faculty of Health Sciences, University of Macau, Macau 999078, China
* Correspondence: sanmingwang@um.edu.mo; Tel .: +853-88224836; Fax: +853-88222314
Abstract: BRCAness refers to the damaged homologous recombination (HR) function due to the de- fects in HR-involved non-BRCA1/2 genes. BRCAness is the important marker for the use of synthetic lethal-based PARP inhibitor therapy in breast and ovarian cancer treatment. The success provides an opportunity of applying PARP inhibitor therapy to treat other cancer types with BRCAness features. However, systematic knowledge is lack for BRCAness in different cancer types beyond breast and ovarian cancer. We performed a comprehensive characterization for 40 BRCAness-related genes in 33 cancer types with over 10,000 cancer cases, including pathogenic variation, homozygotic deletion, promoter hypermethylation, gene expression, and clinical correlation of BRCAness in each cancer type. Using BRCA1/BRCA2 mutated breast and ovarian cancer as the control, we observed that BRCAness is widely present in multiple cancer types. Based on the sum of the BRCAneass features in each cancer type, we identified the following 21 cancer types as the potential targets for PARPi therapy: adrenocortical carcinoma, bladder urothelial carcinoma, brain lower grade glioma, colon adenocarcinoma, esophageal carcinoma, head and neck squamous carcinoma, kidney chromophobe, kidney renal clear cell carcinoma, kidney renal papillary cell carcinoma, liver hepatocellular carci- noma, lung adenocarcinoma, lung squamous cell carcinoma, mesothelioma, rectum adenocarcinoma, pancreatic adenocarcinoma, prostate adenocarcinoma, sarcoma, skin cutaneous melanoma, stomach adenocarcinoma, uterine carcinosarcoma, and uterine corpus endometrial carcinoma.
Keywords: BRCA1/2; BRCAness; genetic defects; synthetic lethal; PARP inhibitors
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Citation: Guo, M .; Wang, S.M. The BRCAness Landscape of Cancer. Cells 2022, 11, 3877. https://doi.org/ 10.3390/cells11233877
Academic Editor: Amancio Carnero
Received: 31 October 2022
Accepted: 29 November 2022 Published: 1 December 2022
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affil- iations.
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Copyright: @ 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).
1. Introduction
BRCA1 and BRCA2 (BRCA1/2) play essential roles in repairing double-strand DNA breaks through homologous recombination (HR) [1,2]. Pathogenic variants in BRCA1/2 damage their function, leads to genome instability, and increased the risk of breast and ovarian cancer [3-6]. The defected BRCA1/2 is the specific marker for the use of a synthetic lethal-based PARPi (poly ADP ribose polymerase inhibitors) therapy in cancer treatment. In the process, the PARP inhibitors block PARP function of repairing single-strand breaks and cause the formation of double-strand break upon replication, which cannot be repaired by homologous recombination due to the defected BRCA1/2 function leading to the death of cancer cells [7-11]. BRCA1/2 defects are present in about 5% of breast cancer and 20% of ovarian cancer patients, which are the major beneficiaries for the PARP inhibitor therapy [12-14].
Homologous recombination pathway involves multiple genes besides BRCA1/2. Fur- ther, many genes not in HR pathway can also directly or indirectly be involved in HR [15]. In principle, defects in these non-BRCA1/2 genes could also result in the same consequences caused by the detected BRCA1/2. This is described as BRCAness [16]. Based on the stud- ies in breast and ovarian cancer, BRCAness are present in about 20% of breast cancer and 45% of ovarian cancer [17,18], such as the mutations in RAD51C, NBS1, BRIP1, and PALB2 [19]. Cancer with defected BRCAness shared many features such as the cancer with defected BRCA1/2. For instance, BRCAness cancer genome had high abundant C-to-T transitions [20], shared the “Signature 3” of mutation signatures in cancer [21,22], and
contained high level of promoter hypermethylation [23], prone to triple-negative breast cancer (TNBC) and “Basal” subtypes, and benefited from PARPi treatment [24-28].
The success of PARPi therapy in BRCA1/2 defected breast and ovarian cancer attracts great interests in exploring its potential to treat other cancer types with BRCAness features. Indeed, it was observed that BRCAness was present in prostate cancer, colon cancer and pancreatic cancer [29-31], PARP inhibitor treatment improved survival of pancreatic cancer carrying mutated HRR deficient-related genes of ATM, BRCA1/2, CHEK2, PALB2, RAD51C, RAD51D [32], and enhanced treatment response in metastatic prostate cancer carrying mutated HRR deficient-related genes ATM, BRCA1/2, BRIP1, BARD1, CDK12, CHEK1, CHEK2, FANCL, PALB2, RAD5C [33-35]. However, systematic knowledge is lack for BRCAness across cancer type spectrum. This largely restricts the use of synthetic lethal-based PARPi therapy as a universal option in cancer treatment.
We hypothesized that BRCAness could be a common phenomenon in cancer. To test our hypothesis, we performed a BRCAness characterization in 33 cancer types, covering pathogenic variation, homozygotic deletion, promoter hypermethylation and expression, copy number variation, and clinical correlation for BRCAness-related genes. By using BRCA1/2-mutated breast and ovarian cancer as the references, we observed the wide presence of BRCAness signatures in multiple cancer types. Our study provides a foundation to further test the potential of using PARPi therapy to treat the cancer types with BRCAness features.
2. Materials and Methods
2.1. Sources of Genome Data across 33 Cancer Types
We identified 40 BRCAness genes from literatures (ATM, ATR, AURKA, BAP1, BARD1, BLM, BRCA1, BRCA2, BRIP1, CDK12, CHD4, CHEK1, CHEK2, EMSY, ERCC1, FANCA, FANCC, FANCD2, FANCE, FANCF, FANCI, KMT2A, MRE11A, MYC, NBS1, PALB2, PARP1, PAXIP1, PLK1, PTEN, RAD50, RAD51, RAD51B, RAD51C, RAD51D, RAD52, SAMHD1, SEM1, TP53, TP53BP1, WEE1, WRN) [16,36,37]. We collected the BRCAness genomic and clinical information from these two resources: UCSC xena (http://xena.ucsc.edu/, accessed on 18 November 2020) and PanCanAtlas (https://gdc.cancer.gov/node/905/, accessed on 20 November 2020) covering 33 cancer types [38]. The details of data information are as follows: Variation data from over 10,000 cancer patients were from TCGA MAF file in PanCanAtlas; copy number variation (CNV) data detected by Affymetrix SNP 6.0 arrays were from UCSC xena; DNA methylation data detected by Illumina HumanMethylation450 BeadChip platform were from PanCanAtlas; RNA-seq data with normalized batch effects and log2 (norm_value+1) gene expression for all 33 cancer types were from PanCanAtlas; Clinical survival data were from UCSC xena. GISTIC2 was used to identify the genomic regions with significant gain or loss [39].
2.2. Pathogenic Variant Data in BRCAness Genes
To identify pathogenic and likely pathogenic variants (PLPs) for each BRCAness gene across each cancer type, we first extracted the variants that passed filtering and belonged to non-silent subtypes from TCGA pan-cancer variation data. We further downloaded all variations from ClinVar (https://www.ncbi.nlm.nih.gov/clinvar/, accessed on 25 January 2021) and COSMIC (the Catalogue of Somatic Mutations in Cancer, https://cancer.sanger. ac.uk/cosmic, accessed on 25 January 2021) databases and extracted the “Pathogenic” and “Likely Pathogenic” variants from ClinVar and “Pathogenic” variants from COSMIC (PLP). We compared the TCGA variants to ClinVar/COSMIC PLP variants to identify germline and somatic PLPs for the BRCAness genes in each cancer type. We calculated variation frequency for the PLP variants in each BRCAness gene in each cancer type and tested the correlation of PLP variation frequencies between BRCAness genes and BRCA1/2 in all 33 cancer types by Pearson’s correlation coefficient analysis. p-value < 0.05 was considered as statistically significant.
2.3. CNV Data in BRCAness Genes
We used GISTIC2 to identify CNV at gene-level [39], with gene count of “-2” defined as homozygotic mutation. We retained homozygous deletion for CNV analysis across all 33 cancer types. We calculated homozygous deletion frequency for each BRCAness gene in each cancer type, and clustered homozygous deletion frequencies for all 33 cancer types using R package “ComplexHeatmap” [40]. We also tested the correlation of frequencies for homozygous deletions between BRCA1/2 and BRCAness genes in all 33 cancer types by Pearson’s correlation coefficient analysis. p-value < 0.05 was used as statistically significant in correlation analyses.
2.4. DNA Methylation Data in BRCAness Genes
We used DNA methylation data from the HumanMethylation450 arrays. We mapped the probes to each BRCAness genes using the Illumina GPL13534 platform (https://www. ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GPL13534, accessed on 23 May 2021). Promoter for BRCA1/2 and BRCAness genes was defined as within 10 kb surrounding transcription start site (TSS) for each gene. We obtained hypermethylated data with mean gene-level promoter methylation values > 0.3. We clustered promoter methylation levels (mean promoter methylation values) for BRCA1/2 and BRCAness genes in 33 cancer types using R package “ComplexHeatmap” [40].
2.5. Gene Expression and Functional Enrichment Analysis
We used the Wilcox’s rank sum test to identify differentially expressed genes (DEGs) in each cancer type. We adjusted the p-values by Benjamini-Hochberg (BH) method [41]. We defined the differentially expressed genes with adjusted p-values < 0.01 and at least two-fold changes in expression level. We also performed Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) functional enrichment annotation using the DAVID tool (http://david.abcc.ncifcrf.gov/, accessed on 23 May 2021, version 6.8), with Benjamini p.adjust < 0.05 as statistically significance [42].
2.6. Clinical Relevance of BRCAness Genes
We divided the patients into high-risk and low-risk groups based on the median expression of each BRCAness gene. We used the Kaplan-Meier method to generate survival curves, and two-sided log-rank tests to assess the differences in overall survival between the high-risk and low-risk groups by using the R package “survival” and p-value < 0.05 as significant difference. We calculated the hazard ratio and 95% confidence level and plotted the results by R “forestplot” package.
2.7. Identifying Candidate Cancer Types for PARPi Therapy
Taking breast cancer and ovarian cancer as the references, we ranked the 33 cancer types based on following six integrated features: for somatic and germline pathogenic variation, and homozygous deletion, we calculated the frequencies of all BRCAness genes in each cancer type; for promoter methylation, we calculated the total promoter methylation level of all BRCAness genes in each cancer type; for gene expression, we calculated the total number of differentially expressed BRCAness genes in each cancer type; for prognostics, we located the number of risky BRCAness genes in each cancer type. We set BRCA/OV = 1 to identify BRCAness cancer types that only the cancer type with >=1 qualified as BRCAness cancer types.
3. Results
3.1. Overview of the Study
Functional enrichment analysis showed that the 40 BRCAness genes were involved in homologous recombination, DNA repair, cell cycle, and Fanconi anemia pathways (Figure 1A). Using the TCGA multi-omics data from 33 cancer types derived from over 10,000 cancer cases, we characterized BRCAness genes and their clinical relevance (Figure 1B,
A
strand displacement
DNA synthesis involved in DNA repair
B
DNA repair
cellular response to DNA damage stimulus
signal transduction regulation by p53 class mediator
DSB repair via homologous recombination
interstrand cross-link repair
double-strand break repair
DNA recombination
BRCAness genes pathways
DNA damage checkpoint
DNA replication
DNA double-strand break processing
DSB repair via nonhomologous end joining
reciprocal meiotic recombination
response to gamma radiation
replicative senescence
mitotic recombination
DNA duplex unwinding
response to ionizing radiation
cellular response to gamma radiation
response to X-ray
protein sumoylation
regulation of cell cycle
GO_BP
telomere maintenance via recombination
telomere maintenance
nucleotide-excision repair
positive regulation of transcription, DNA-templated
G2/M transition of mitotic cell cycle
negative regulation of apoptotic process
cell proliferation
Fanconi anemia pathway
Homologous recombination
Cell cycle
p53 signaling pathway
KEGG
0
3
6
9
13
17
21
25
7
-log(P value)
| Cancer | No. | Cancer | No. |
|---|---|---|---|
| ACC | 92 | LUSC | 504 |
| BLCA | 413 | MESO | 87 |
| BRCA | 1104 | OV | 600 |
| CESC | 309 | PAAD | 186 |
| CHOL | 36 | PCPG | 184 |
| COAD | 460 | PRAD | 499 |
| DLBC | 48 | READ | 167 |
| ESCA | 186 | SARC | 265 |
| GBM | 601 | SKCM | 477 |
| HNSC | 530 | STAD | 443 |
| KICH | 66 | TGCT | 139 |
| KIRC | 537 | THCA | 515 |
| KIRP | 292 | THYM | 124 |
| LAML | 200 | UCEC | 548 |
| LGG | 529 | UCS | 57 |
| LIHC | 379 | UVM | 80 |
| LUAD | 521 |
Figure 1. Scheme of the analysis. (A) Functional enrichment analysis for BRCAness genes. It shows the barplot for the top 30 significant GO functional enriched biological processes (BPs), and KEGG pathways. (B) The number of patients included each cancer type.
3.2. Pathogenic Variation in BRCAness Genes in Different Cancer Types
Pathogenic variation in BRCAness gene is the direct indication for the presence of BRCAness in cancer. We searched for both germline and somatic pathogenic variants in BRCA1/2 and BRCAness genes in each of the 33 cancer types and identified a total of 808 germline and 4017 somatic pathogenic mutations in BRCA1, BRCA2 and 37 of the 38 BRCAness genes distributed in 33 cancer types. On average, there were 24 germline and 122 somatic mutations per cancer type distributed at different frequencies in different cancer types (Tables S2-S4). As expected, BRCA1/2 had both germline and somatic pathogenic variation in breast and ovarian cancer, whereas BRCAness genes had high prevalence of somatic pathogenic variation distributed in cancer type-specific manners (Figure 2, Table S2). The prevalence of somatic pathogenic variation in BRCAness genes ranged between 0.14% and 39.81%, with TP53 as the highest among all BRCAness genes, followed by PTEN, ATM, CHD4, KMT2A, ATR, CDK12, BAP1 and TP53BP1 higher than BRCA2, and FANCD2, RAD50, MYC, BRIP1, FANCI, PLK1, PAXIP1, CHEK2, PARP1 and SAMHD1, all of which were higher than BRCA1 (Figure 2, Table S2). Of the 33 cancer types, 6 had higher prevalence of BRCAness pathogenic variation than breast cancer (BRCA) and 19 higher than ovarian cancer (OV), with UCEC as the highest of 1787 among all 33 cancer types (Figure 2, Table S2). LAML, TGCT, PCPG, UVM, CHOL, and THYM had very low prevalence of BRCAness somatic and germline pathogenic variation. For example, LAML (acute myeloid leukemia) had neither somatic nor germline pathogenic variation in BRCAness genes, although AML has consistent cytogenetic abnormality (Figure 2, Table S2). Therefore, these cancer types were unlikely relevant with BRCAness. Then, we performed the variation frequency correlation analysis to explore whether similar variant patterns exist between BRCAness genes and BRCA1/2. We performed Pearson correlation analysis to test the correlation between BRCAness pathogenic variation and BRCA1/2 genes. Except TP53,
BAP1, PALB2, ERCC1 with the somatic pathogenic variation, nearly all BRCAness genes had significant correlation with BRCA1 and/or BRCA2 (Figure 3A,B), and about a third of BRCAness genes with germline pathogenic variation had significant correlation with BRCA1 and/or BRCA2 (Figure 3C,D).
· UCEC
· BLCA
· LUSC
Somatic
Germline
# HNSC
STAD
. COAD
350
BRCA
# SKCM
. LGG
300
. LUAD
· GBM
ESCA
No. of pathogenic variants
· CESC
250
· LIHC
· READ
· PAAD
· SARC
200
PRAD
UCS
KIRC
· OV
150
· KIRP
KICH
MESO
100
UCEC
· THCA
STAD
DLBC
LGGBRCA
ACC
CESC
Cancer types
. CHOL
50
SARC
THYM
OV
UVM
THCA
· PCPG
THYM
· TGCT
. LAML
O
LAML
TP53
PTEN
ATM
KMT2A
CHD4
ATR
CDK12
TP53BP1
BAP1
BRCA2
RAD50
FANCD2
BRIP1
FANCI
PARP1
PAXIP1
CHEK2
PLK1
BLM
WRN
SAMHD1
BRCA1
MYC
FANCA
WEE1
CHEK1
NBS1
BARD1
FANCC
PALB2
RAD51
RAD51B RAD51C
ERCC1
AURKA
RAD51D
FANCF
FANCE RAD52
TP53
PTEN
ATM
BRCA2
BRCA1
KMT2A
BAP1
PALB2
RAD50
WRN
BRIP1
FANCA
NBS1
CHEK2
BLM
BARD1
FANCC
CHD4
MYC
RAD51C
SAMHD1
FANCI
FANCE
ATR
ERCC1
RAD51
Genes
Cells 2022, 11, 3877
A
-log10(PValue)
10
8
6
4
2
0
abs(Coeff)
0.8
IPS3
PTEN
AX
0.4
CHD
Somatic PLP frequency significance between BRCAness genes and BRCA1
AMTS
0.0
COLP COKin
TP53BF O3BP
O
00
SRC
PANCO-
-log10(PValue)
TP53
RAD50
PTEN
15
NM CHD4
Somatic PLP frequency coefficient between
A MY
OMp,
10
KMTZA
PANO
5
AIR CUK12
BRCAness genes and BRCA1
REK-
0
TP53BP1 ANP1 PRCAZ
SAMHD
FANCD2
WRA
RAD50
abs(Coeff)
WER
0.8
TP
PT PIEN
MYC
FANA
Somatic PLP frequency significance between
BRID
FANC PLY
CHEK,
0.4
CHD
KMTS 2
PAXIP, CHE CHICK2 PARP
NBS A/b.
DARD
0.0
COLT -OK19
BRCAness genes and BRCA2
FAND
SAMHD1
RADE
P53RD
VAD51F
FANCD
WRN
RADS1
TPS P53
RADSO
OLM
WEE1 FANA FANCA
CRO
0
C
MY
AUP
RAD51D
PTEN
Somatic PLP frequency coefficient between
CHEK1
ANA WNYC
PANE
NBS1
PANCA
CHO
KMTZA MIZA
Ok 20
PALBS
RAD52
6
BRCAness genes and BRCA2
-log10(PValue)
A
CH NEK
BARD;
COMP
PADS
PANCO
RADS
A
SAMHD
IP53BP
RAD51B
ORCA
RADS1
2
FANCD-
WRA
RAD50
8
CRCC AUŇKA
A
0
WEL
RAD51D
BRIS
ANCA
FANCE
PANO
CHEK,
FANCE
289 PAPI
RAD52
abs(Coeff)
0.8
PAVIA
0.6
3
PTEN
Germline PLP frequency significance between
HEKS
BARD
PASS
SAMHD1 BRCA
PANO
ATM
RADE
YADS18
BRCA2
Figure 3. Correlation of pathogenic variation of BRCAness genes across 33 cancer types.
BRCAness genes and BRCA1
WRN
MADS10
0.2
BAP
BLM WEF1 FANCA
SACA AUDY
0
0.0
KMT2A
RAD51
CASA CHEK1
MYC
with p-value < 0.05 were regarded as significant. The pairs with an absolute coefficient > 0.5 were
(A,B) Significant correlation for the frequencies of somatic and germline pathogenic variants be- tween individual BRCAness gene and BRCA1. (C,D). Significant correlation for the frequencies of somatic and germline pathogenic variants between individual BRCAness gene and BRCA2. The pairs
NBS1 PATRO
PANO PANCE
-log10(PValue)
TP53
RAD50
RAD52
8
PTEN
ANCC RADS RAND1 RAD51B RADS10
6
Germline PLP frequency coefficient between
BRIP1
BARD.
regarded as significantly correlated.
ATM
CHEK2
4
BRCA2
3.3. Homozygotic Deletion Patterns between BRCA1/2 and BRCAness Genes in Different Cancer Types
2
BRCAness genes and BRCA1
PALB2
BAP1
WRN
CROP
HURKA RAD51D
0
KMT2A
NBS1
PANCE FANA PANCA
variation. From the homozygotic deletion identified in BRCAness genes, we observed low
an important indicator to test the similarity between BRCAness and BRCA1/2 pathogenic
embryo lethal effects of BRCA1/2 homozygotic variation. Therefore, homozygosity provides
MYC
FANCA
Pathogenic variation in human BRCA is predominantly heterozygotic due to the
abs(Coeff)
0.8
RAD50
BLM
RAD52
TP53
PTEN
BRIP1
FANCC
BARD1
0.4
Germline PLP frequency significance between BRCAness genes and BRCA2
CHEK2
ATM
6 of 14
PALB2
FANCI
BAP1
PARP1, WEE1, FANCC, RAD52, CDK12, ERCC1, CHD4, NBS1, PLK1, FANCF, ATR, RAD51C,
frequency of 0.01-1.16% homozygotic deletion in BRCAness genes, comparing to 0.16% in BRCA1 and 0.32% in BRCA2 (Figure 4A). Of the 40 BRCAness genes, 21 (RAD51D,
KMT2A
WRN
CHD4
FANCE, PALB2, BRIP1, BLM, SAMHD1, FANCI, MYC, AURKA) had lower than the 0.16%
0.0
SAMHD1
BRCA1
NBS1
in BRCA1 and 29 (TP53BP1, PAXIP1, RAD51B, FANCD2, MRE11A, CHEK2, RAD50, BARD1,
FANCA
RAD51
MYC
RAD51D, PARP1, WEE1, FANCC, RAD52, CDK12, ERCC1, CHD4, NBS1, PLK1, FANCF,
RAD50
BLM
FANCE
TP53
ATR, RAD51C, FANCE, PALB2, BRIP1, BLM, SAMHD1, FANCI, MYC, AURKA) had lower
RAD51C
PTEN
BRIP1
FANCC
Germline PLP frequency coefficient between
CHEK2
BARD1
ERCC1
ATM
than the 0.32% in BRCA2 (Figure 4A). Nine BRCAness genes had significant correlation with BRCA1 and 15 with BRCA2 (Figure 4B-E). Of the 33 cancer types, 23 (LUAD, KIRC,
BAP1
PALB2
FANCI
ATR
KMT2A
BRCAness genes and BRCA2
WRN
CHD4
SAMHD1
STAD, ESCA, UVM, TGCT, ACC, COAD, LIHC, HNSC, UCEC, LGG, GBM, UCS, LAML, READ, KIRP, THYM, PAAD, THCA, PCPG, KICH, CHOL) were higher than BRCA cancer
BRCA1
NBS1 FANCA
RAD51
1
FANCE
and OV cancer (Table S5). The results showed that like BRCA and the related cancer types, homozygotic variation was insignificantly present in BRCAness genes and their related
RAD50
BLM
cancer types.
BRIP1
FANCC
RAD51C
ERCC1
CHEK2
BARD1
PALB2
FANCI
ATR
WRN
CHD4
NBS1
SAMHD1
FANCA
RAD51
BLM
FANCE
FANCC
RAD51C
BARD1
ERCC1
FANC
ATR
CHD4
SAMHD1
RAD51
FANCE
RAD51C
ERCC1
A
A
Homozygous deletion
1 P
1
Total
BRCAness gene homozygous deletion frequency
-
1
-
PTEN
T
1.16
frequency
WRN
0.71
PTEN
0.50
WRN
TP53
TP53
0.06
BAP1
0.46
0.04
CHEK1
0.43
BAP1
CHEK1
0.02
FANCA
0.37
KMT2A
0.36
FANCA
KMT2A
0
ATM
0.36
RAD51
0.34
ATM
BRCA2
0,32
RAD51
TP53BP1
0.30
BRCA2
0.22
TP53BP1
BRCAness frequency higher than BRCA1
PAXIP1
0.20
PAXIP1
RAD51B
RAD51B
<5
FANCD2
0.20
FANCD2
ERCC1
PALB2
MRE11A
0.19
CHD4
BRIP1
CHEK2
0.19
MRE11A
NBS1
BLM
RAD50
0.18
CHEK2
BARD1
0.17
RAD50
PLK1
SAMHD1
0.16
BARD1
FANCF
FANCI
BRCA1
RAD51D
0.13
BRCA1
RAD51D
FANCD2 BARD1
ATR
MYC
0.13
5-10
FANCO
RAD51C
AURKA
PARP1
WEE1
0,13
PARP1
WEE1
BRCA1
RAD52
FANCE
FANCC
0.11
FANCC
RAD51D
CDK12
PTEN
>30
RAD52
PARP1
25-30
0.11
WRN
CDK12
0.10
RAD52
0.09
CDK12
WEE1
TP53
ERCC1
ERCC1
FANCĄ
20-25
CHD4
0.07
RAD51
B
0.06
CHD4
BRCA2
TP53BP1
MRE1
A
BAP1
ATM
NBS1
NBS1
RAXIP1
CHEK2
CHEK1 RAD5
PLK1
0.05
PLK1
KMT2A RAD50
FANCF
0.04
FANCF
ATR
0.04
RAD51C
0.03
ATR
10-15
15-20
FANCE
0.03
RAD51C
0.03
FANCE
PALB2
BRIP1
0.02
PALB2
BLM
0.02
BRIP1
SAMHD1
0.02
BLM
0.02
SAMHD1
FANCI
MYC
0.01
FANCI
AURKA
0.01
MYC
AURKA
PRAD
DLBC
SARC LUSC
GBM
BLCA
ESCA
STAD
HNSC
UCEC
OV
BRCA
LUAD
UCS
LIHC
COAD
READ
ACC
LGG
LAML
THYM
KIRP
PAAD
THCA
PCPG
KICH
CHOL
CESC
SKCM
UVM
TGCT
MESO
KIRC
0
0.2
0.4
0.6
0.8
1.0
1.2
B
Significance of homozygous deletion frequency between BRCAness genes and BRCA1
C
Significance of homozygous deletion frequency between BRCAness genes and BRCA2
8
-log10(PValue)
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Coefficient of homozygous deletion frequency between BRCAness genes and BRCA1
Coefficient of homozygous deletion frequency between BRCAness genes and BRCA2
abs(Coeff)
0.0 0.2 0.4 0.6 0.8
m
0.8
abs(Coeff)
0.4
D
0
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12050.
A
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0.0
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1000.
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S
ORIS
SASAM
BLA
SAMHD
PAND
AURKA
0
3.4. Methylation and Expression Patterns between BRCA1/2 and BRCAness Genes in Different Cancer Types
Promoter methylation plays important roles in de-regulation of BRCA1/2 expression in breast and ovarian cancer [43]. We investigated promoter methylation in BRCAness genes across all 33 cancer types. By using promoter methylation level in BRCA2 as the cutoff, 16 of the 40 BRCAness gene promoters were hypermethylated across nearly all cancer types (Figure 5A, Table S6). We then tested the effects of promoter hypermethylation on BRCAness gene expression. In the 19 cancer types with expression data available from at least 5 normal samples as control, 10 cancer types of PRAD, READ, KIRP, COAD, STAD, LUAD, THCA, LIHC, ESCA, PAAD had lower expression of BRCAness genes than their normal controls by referring to breast cancer (ovarian cancer was not included due to the
lack of expression data from normal ovarian control) (Figure 5B). Of the 33 cancer types, BRCA cancer had total levels of BRCA1/2 and BRCAness gene promoter hypermethylation of 14.244 and OV cancer had 13.926. By using OV cancer as the cutoff, 20 of the 33 cancer types had promoter hypermethylation (Table S6). The hypermethylation in OV had distinct features from other cancer types: a group of BRCAness genes of MER11A, RAD51, PALB2, CHD4, BRIP1, MYC, and FANCE were increasingly expressed whereas another group of WRN, CDK12, CHEK2, FANCA, and TP53 was decreasingly expressed (Figure 5C). Each cancer type also had specific hypermethylated BRCAness genes (Figure 5C). For example, FANCF promoter was hypermethylated and had decreased expression in eight cancer types of BLCA, CESC, COAD, DLBC, ESCA, HNSC, UCEC, and UCS (Figure 5C). The results highlighted that BRCA1/2 and BRCAness genes shared high similarity of promoter hypermethylation across multiple cancer types.
A
BRCAness gene promoter methylation level
B
BRCAness gene expression log(fold-change)
mean
1
P
P
T
P
log2FC
1
SAMHD1
2
M
FANCA
0.8
PAXIP1
1
RAD51
FANCA
L
0.6
0
BLM
0.4
NBS1
FANCI
0.2
BRIP1
-1
I
FANCD2
BARD1
-2
PLK1
0
RAD52
L
PARP1
AURKA
FANCC
L
BRCA2
AURKA
BRIP1
1
RAD51D
T
CHEK1
BRCA1
BRCA1
MRE11A
L
CHEK2
1
TP53
r
PAXIP1
RAD51C
I
PALB2
CHEK2
ATR
D
FANCE
[
FANCE
BRCA2
RAD52
PLK1
Genes
FANCF
CHEK1
IN
FANCC
ERCC1
A
TP53
CHD4
PARP1
FANCI
L
CDK12
PTEN
RAD51B
I
ERCC1
ATR
RAD51C
WRN
1
BAP1
MYC
CHD4
WEE1
BARD1
FANCF
r
TP53BP1
ATM
RAD50
RAD50
ATM
PALB2
I
PTEN
BLM
NBS1
CDK12
MRE11A
KMT2A
L
WRN
BAP1
SAMHD1
RAD51
WEE1
FANCD2
MYC
LAML
THYM
KIRP
THCA
LIHC
KIRC
CHOL
ACC
SKCM
LGG
OV
GBM
UVM
COAD
READ
UCEC
STAD
BRCA
PRAD
LUAD
HNSC
CESC
LUSC
ESCA
BLCA
MESO
PAAD
SARC
KICH
DLBC
PCPG
UCS
TGCT
BLCA
UCEC
SARC
CHOL
KICH
HNSC
LUSC
KIRC
BRCA
PRAD
READ
KIRP
COAD
STAD
LUAD
THCA
LIHC
ESCA
PAAD
C
0.8
MRE11A
TP53
0.6
RAD51
Enhencing events Coefficient
PALB2
PAXIP1
BRIP
CHD4
CDK12
PAXIP
NBN
AURKA
BRCA1
FANCE
MYC
0.4
0.2
0.0
ACC
BLCA
BRCA
CESC
CHOL
COAD
DLBC
ESCA
GBM
HNSC
KICH
KIRC
KIRP
LAML
LGG
LIHC
LUAD
LUSC
MESO
OV
PAAD
PCPG
PRAD
READ
SARC
SKCM
STAD
TGCT
THCA
THYM
UCEC
UCS
UVM
0.0
-0.2
Silening events Coefficient
-0.4
FANCF
CHEK2
MRE11A
PTEN
PTEN
ATM
FANCF
RAD50
FANCE
CDK12
FANCF
TP53
ANCA
SAMHD1
FANCA
RAD52
-0.6
FANCF
CHEK2
FANCE
NBS1
BAP1
ATM
FANCF
FANCF
CDK12
PAXIP1
·PTEN
FANCF
FANCF
WRN
-0.8
sites. Red: hypermethylated genes; blue: hypomethylated genes. By using BRCA2 as the cutoff, 18 BRCAness genes were hypermethylated and 24 were hypomethylated. (B) Altered expression of BRCAness genes in 19 cancer types with available expression data from normal controls. Red: up- regulated genes; blue: down-regulated genes. (C) Cancer type-specific silencing effects of promoter methylation in BRCAness genes. It showed that promoter methylation silenced the expression in the majority of BRCAness genes, except the enhanced expression in 13 BRCAness genes, and the silencing effects were highly cancer type specific. Blue: silencing; red: enhancing. Pearson’s correlation coefficient > 0.5 represents significant associations.
3.5. Prognostics of BRCAness Gene Expression across Different Cancer Types
We analyzed the prognostic potential of altered BRCAness gene expression across different cancer types. We observed that the altered expression of each BRCAness gene was significantly correlated with the overall survival in at least one cancer type except TGCT, THCA, and UCS (Figure 6A). For example, increased expression of AURKA was correlated with worse survival in 16 of the 33 cancer types including KIRP (log-rank p = 3.41 × 10-8, KICH (log-rank p = 5.20 × 10-6), and KIRC (log-rank p = 1.11 × 10-10) (Figure 6B); increased expression of PTEN was correlated with better survival in 6 cancer types including LGG (log-rank p = 4.44 × 10-9), KIRC (log-rank p = 4.21 × 10-3), LIHC (log- rank p = 2.64 × 10-2), UCEC (log-rank p = 4.25 × 10-5), PRAD (log-rank p = 7.07 × 10-2) and LAML (log-rank p = 3.64 x 10-2) (Figure 6B). Altered expression of BRCAness genes can classify cancer patients into high- and low-risk groups. For example, based on altered expression of BRCAness genes, KIRC patients were divided into the lower expression group of 112 patients and the higher expression group of 422 patients (Figure 6C), in which the lower expression subgroup had significantly better survival than the higher expression subgroup (Figures 6D and S1). The results showed that similar to BRCA1/2 in breast and ovarian cancer, BRCAness genes were the prognostic markers for multiple cancer types.
3.6. BRCAness Cancer Types Sharing High Similarity with BRCA and OV Cancer
Data from above analyses identified multiple cancer types enriched with BRCAness features. We ranked the 33 cancer types based on the sum of BRCAneass features in the six features of somatic pathogenic variation, germline pathogenic variation, homozygous deletion, expression, and clinical prognosis. By using the sum in both BRCA cancer and OV cancer values = 1 as the cut-off, we observed that the following 21 cancer types had BRCAness features higher than BRCA cancer and OV cancer: UCEC, BLCA, PAAD, LGG, SARC, LUAD, KICH, UCS, ACC, COAD, LIHC, ESCA, HNSC, READ, STAD, SKCM, LUSC, MESO, KIRC, KIRP, and PRAD (Table 1). Of the 21 cancer types, UCEC (uterine corpus endometrial carcinoma) was the highest as referred by BRCA cancer and OV cancer.
A
C
KIRC
AURKA
FANCA
FANCI
RAD51
FANCD2
BLM
CHEK1
n=112
PLK1
BRCA1
PARP1
MYC
BRCA2
BRIP1
BARD1
CDK12
WEE1
MRE11A
PALB2
CHEK2
FANCC
FANCE
RAD51C
BAP1
CHD4
FANCF
ATR
WRN
PAXIP1
SAMHD1
TP53BP1
ATM
ERCC1
TP53
RAD52
NBS1
RAD50
PTEN
LGG
PAAD
LUAD
KIRP
KICH
MESO
KIRC
ACC
LIHC
SARC
UCEC
PCPG
PRAD
UVM
CHOL
HNSC
COAD
OV
CESC
TGCT
UCS
THCA
ESCA
LUSC
STAD
BRCA
GBM
BLCA
DLBC
LAML
SKCM
THYM
READ
Risky P < 0.05
Protective P < 0.05
P > 0.05
B
n=422
AURKA Hazard Ratio
P-values
PTEN Hazard Ratio
P-values
LGG
3.99 x 10-1
4.44 × 10-9
PAAD
1.82 × 104
0.146
LUAD
7.66 × 104
0.426
KIRP
3.41 × 10€
0.108
KICH
5.28 x 405,
0.383
MESO
9.84 x 10°
0.150
KIRC
1.11 x 10-10
4.21 × 103
ACC
2.29 × 107
1.97 x 10-2
LIHC
6.88 × 103
2.64 × 10-2
SARC
1.90 × 102
0.225
UCEC
1.09 × 104
4.25 × 10€
Cancer_types
PCPG
2.10 × 102
0.921
BRCAness genes
PRAD
2.20 × 102
0.707
UVM
4.57 × 10$
0.127
CHOL
0.082
0.250
D
HNSC
9.75 × 10-3
KIRC survival
0.501
COAD
0.086
0.304
1.0
OV
0.364
0.119
CESC
0.548
0.528
TGCT
+ 0.554
0.749
0.8
UCS
0.620
0.119
THCA
0.420
0.1121
Survival
Log-rank p = 7.31 x 10-8
0.6
ESCA
0.180
0.409
LUSC
0.778
0.309
Low-risk group n=422
STAD
0.298
0.971
0.4
BRCA
0.288
0.822
GBM
0.438
0.939
High-risk group n=112
BLCA
0.078
0.498
0.2
DLBC
0.136
0.966
LAML
0.099
3.64 × 10-2
SKCM
2.00 × 102
0.252
0.0
THYM
0.054
0.109
READ
0.364
0.406
0
2
4
6
8
10
12
Years
0
0.5
1
1.5
2
2.5
3
3.5
4
4.5
8
9.5
0
1
2
3
4
5
6
7
20
OR (95% CI)
OR (95% CI)
| Cancer | Rank by BRCA Cancer Rank by OV Cancer Somatic Germline Homozygotic Methylation Expression Prognosis Somatic Germline Homozygotic Methylation Expression Prognosis Sum | ||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| UCEC | 5.9 | 4.7 | 0.7 | 1.0 | 7.0 | 3.0 | 11.0 | 17.2 | 0.5 | 1.0 | 7.0 | 3.0 | 62.1 |
| BLCA | 3.8 | 2.0 | 1.3 | 1.0 | 10.5 | 1.0 | 4.8 | 14.6 | 1.0 | 1.0 | 10.5 | 1.0 | 52.6 |
| PAAD | 1.5 | 1.9 | 0.2 | 1.0 | 5.5 | 9.0 | 4.5 | 6.1 | 0.1 | 1.0 | 5.5 | 9.0 | 45.3 |
| LGG | 1.5 | 1.9 | 0.7 | 1.0 | - | 12.0 | 4.6 | 5.7 | 0.5 | 1.1 | - | 12.0 | 41.0 |
| SARC | 1.1 | 1.2 | 1.8 | 1.0 | 8.5 | 4.5 | 2.9 | 4.0 | 1.4 | 1.0 | 8.5 | 4.5 | 40.5 |
| LUAD | 1.8 | 1.5 | 1.0 | 1.0 | 0.0 | 7.0 | 3.5 | 6.9 | 0.8 | 1.0 | 0.0 | 7.0 | 31.6 |
| KICH | 1.2 | 1.2 | 0.1 | 1.0 | 3.0 | 6.5 | 2.9 | 4.2 | 0.1 | 1.0 | 3.0 | 6.5 | 30.5 |
| UCS | 3.2 | 4.0 | 0.7 | 0.9 | - | 0.0 | 9.6 | 10.1 | 0.5 | 0.9 | - | 0.0 | 30.0 |
| ACC | 0.4 | 0.7 | 0.8 | 1.0 | - | 10.0 | 1.6 | 1.4 | 0.6 | 1.0 | - | 10.0 | 27.4 |
| COAD | 2.9 | 2.2 | 0.7 | 1.0 | 0.0 | 1.0 | 5.3 | 11.0 | 0.6 | 1.0 | 0.0 | 1.0 | 26.8 |
| LIHC | 1.1 | 0.8 | 0.7 | 1.0 | 0.5 | 7.0 | 1.8 | 4.4 | 0.6 | 1.0 | 0.5 | 7.0 | 26.4 |
| ESCA | 2.0 | 3.3 | 1.0 | 1.0 | 1.0 | 0.0 | 7.7 | 7.7 | 0.8 | 1.0 | 1.0 | 0.0 | 26.4 |
| HNSC | 2.5 | 2.4 | 0.7 | 1.0 | 0.5 | 1.0 | 5.8 | 9.5 | 0.5 | 1.0 | 0.5 | 1.0 | 26.4 |
| READ | 2.3 | 2.4 | 0.5 | 1.0 | 2.0 | 0.0 | 5.8 | 8.5 | 0.4 | 1.0 | 2.0 | 0.0 | 25.9 |
| STAD | 2.8 | 2.6 | 1.0 | 1.0 | 0.0 | 0.0 | 6.0 | 10.5 | 0.8 | 1.0 | 0.0 | 0.0 | 25.6 |
| SKCM | 2.5 | 0.8 | 1.1 | 1.0 | - | 3.5 | 1.9 | 9.3 | 0.9 | 1.0 | - | 3.5 | 25.5 |
| LUSC | 2.7 | 2.6 | 1.1 | 1.0 | 0.0 | 0.0 | 6.3 | 9.9 | 0.8 | 1.0 | 0.0 | 0.0 | 25.3 |
| MESO | 0.7 | 0.8 | 1.2 | 1.0 | - | 7.0 | 1.9 | 2.4 | 0.9 | 1.0 | - | 7.0 | 23.9 |
| KIRC | 0.5 | 0.3 | 1.0 | 1.0 | 0.5 | 7.0 | 0.8 | 1.8 | 0.8 | 1.0 | 0.5 | 7.0 | 22.3 |
| KIRP | 0.4 | 0.1 | 0.5 | 1.0 | 0.0 | 7.5 | 0.3 | 1.5 | 0.4 | 1.1 | 0.0 | 7.5 | 20.3 |
| PRAD | 0.5 | 0.5 | 3.1 | 1.0 | 1.0 | 3.0 | 1.1 | 2.0 | 2.4 | 1.0 | 1.0 | 3.0 | 19.6 |
| BRCA&OV | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 12.0 |
4. Discussion
By characterizing pathogenic variants, somatic variants, homozygotic deletion, pro- moter methylation, gene expression, and clinical prognosis, our study portraits a com- prehensive view for BRCAness landscape in cancer and reveals that BRCAness is widely present in different cancer types. We observed that genetic variation was widely presence in BRCAness genes in multiple cancer types, homozygotic variation was rare event in BRCAness genes as in BRCA, promoter methylation was common in BRCAness genes and caused alterative expression, the defects in BRCAness genes were strong prognostics markers as BRCA. By referring to the sum of BRCAness features higher than BRCA defected breast and ovarian cancer, we identified 21 BRCAness cancer types as the candidate targets for PARPi trial to further determine the efficacy of PARPi therapy in each cancer type.
By targeting multiple oncogenic components, synthetic lethal has shown promising potential as best exemplified by using PARPi to treat BRCA1/2 mutated breast and ovar- ian cancer. In our current study, we analyzed the potential of using PARPi therapy to treat other cancer types with BRCAness features. Through analyzing multiple features in 33 cancer types, our study provided the following evidence showing high similarity between BRCAness and BRCA1/2 mutation in multiple cancer types: (1) Genetic variation was widely present in BRCAness genes in multiple cancer types as represented by UCEC, BLCA, LUSC, HNSC, STAD, and COAD [44]; (2) homozygotic variation was a rare event in BRCAness genes as in BRCA1/2 mutation. Similar to the embryonic lethal effects in BRCA1/2, homozygous variation in BRCAness genes was not common across different can- cer types although homozygous deletions in some BRCAness genes (FANCD2, PTEN, TP53, BRCA2) could be present [45]; (3) promoter methylation was common in many BRCAness genes and caused alterative expression [46]. Similar to the promoter methylation occurred in BRCA1/2, promoter methylation was present in nearly half of the BRCAness genes, and their expression were silenced in many cancer types in cancer type-specific manner; (4) the defects in BRCAness genes were strong prognostics markers as BRCA1/2 mutation, as shown in the BRCAness genes of CHEK2, ATM, RAD51D, EMSY, PALB2, BRIP1, ERCC1, RAD50, ATR, RAD51C in ovarian cancer [47].
Our study reveals that BRCAness defects are commonly present in multiple cancer types as BRCA1/2 defects in breast and ovarian cancer. Therefore, it opens a possibility to
further test the potential of expanding PARPi therapy from breast and ovarian cancer to more cancer types with BRCAness features.
Supplementary Materials: The following supporting information can be downloaded at: https: //www.mdpi.com/article/10.3390/cells11233877/s1. The data underlying this article are available in the article and in its online Supplementary Tables S1-S6 and Supplementary Figure S1.
Author Contributions: M.G .: conceptualization, methodology, investigation, visualization, writing. S.M.W .: conceptualization, supervision, funding, writing. All authors have read and agreed to the published version of the manuscript.
Funding: This work was supported by Macau Science and Technology Development Fund (085/2017/ A2, 0077 /2019/ AMJ, 0032/2022/A1), University of Macau (SRG2017-00097-FHS, MYRG2019-00018-FHS, MYRG2020-00094-FHS), Faculty of Health Sciences, University of Macau (FHSIG/SW/0007/2020P, Startup fund) (SMW), Faculty of Health Sciences, University of Macau (FHSIG/SW/0007/2020P, MoE Frontiers Science Center for Precision Oncology pilot grant, and Startup fund).
Institutional Review Board Statement: Not applicable.
Informed Consent Statement: Not applicable.
Data Availability Statement: Not applicable.
Acknowledgments: We are thankful to the Information and Communication Technology Office (ICTO), University of Macau for providing the High-Performance Computing Cluster (HPCC) re- source and facilities for the study.
Conflicts of Interest: The authors declare no conflict of interest.
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