Expression of the cGAS-STING pathway is associated with high levels of genomic instability and immune cell infiltration in breast cancer

doi:10.21203/rs.3.rs-2889818/v1

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Expression of the cGAS-STING pathway is associated with high levels of genomic instability and immune cell infiltration in breast cancer

https://doi.org/10.21203/rs.3.rs-2889818/v1

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published 02 Jan, 2024

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Genomic instability is a hallmark of cancer, and can be caused by oncogene-induced replication stress. Besides driving the evolution of cancer genomes, genomic instability can lead to the activation of inflammatory signaling, involving the cGAS-STING and JAK-STAT pathways. Inflammatory signaling has been associated with pro-tumorigenic features, but has also been associated with favorable response to treatment, including to immune checkpoint inhibitors. To improve our understanding of the relations between genomic instability and to ultimately guide patient selection for treatment, we investigated the cGAS-STING pathway in relation to markers of replication stress and immune cell infiltration in breast cancer. Immunohistochemistry was performed to determine the expression of cGAS-STING signaling components (STING, phospho-TBK1, and phospho-STAT1), replication stress markers (γH2AX and phospho-RPA32), replication stress-related oncogenes (Cyclin E1 and c-Myc) and immune cell markers (CD20, CD4, and CD57) on primary breast cancer samples (n = 380). Clinical data and mRNA expression data from two public breast cancer databases (TCGA and METABRIC) and an immune therapy trial (I-SPY2) were used to investigate the correlation between cGAS-STING pathway activation, genomic instability markers and patient response to immune therapy. We find that phospho-TBK1, and phospho-STAT1 were highly expressed in triple-negative breast cancers (TNBCs). In addition, expression of genomic instability markers γH2AX and pRPA, replication stress-related oncogenes Cyclin E1 and c-Myc, and immune cell markers were all positively correlated with phospho-STAT1 expression (P < 0.001). We also found that phospho-TBK1 was positively associated with γH2AX (P < 0.002), c-Myc (P < 0.001), CD4 (P < 0.001) and CD20 (P < 0.05). Besides, a positive correlation between perinuclear STING and CD4 was observed (P < 0.01). Accordingly, cGAS-STING pathway components also showed the highest expression levels in TNBCs in both TCGA and METABRIC cohorts. Also, cGAS-STING scores were significantly positively correlated with metrics of genomic instability, including homologous recombination deficiency (HRD) (TCGA: r = 0.296, P < 0.001) and tumor mutational burden (TMB) (TCGA: r = 0.254, P < 0.001; METABRIC: r = 0.0632, P < 0.01). Moreover, higher expression of the cGAS-STING score was also observed in patients who responded to immunotherapy. In conclusion, our study shows that the cGAS-STING pathway is highly expressed in TNBCs, and is positively correlated with genomic instability and immune cell infiltration.

Health sciences/Oncology/Cancer/Breast cancer

Health sciences/Oncology/Cancer/Tumour heterogeneity

cGAS-STING

triple-negative breast cancer

inflammatory signaling

genomic instability

Cyclin E1

pSTAT1

cGAS

STING

Breast cancer is one of the most frequent types of cancer, and the second-most common cause of cancer-related death among women¹. Triple-negative breast cancer (TNBC) is characterized by the absence of estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor-2 (HER2) expression. Due to lack of targeted therapy, TNBC is regarded as a “hard-to-treat” breast cancer subtype and is associated with poor prognosis². Importantly, TNBCs are typically characterized by high levels of genomic instability, which can be caused by various factors, including defective homologous recombination (HR) repair or oncogene-induced replication stress^3,4. Concerning oncogene-induced replication stress, Cyclin E1 overexpression in TNBC has been shown to induce replication stress, mitotic aberrancies, and genomic instability⁵. In line with this notion, Cyclin E1 expression showed significant associations with replication stress markers phospho-RPA32 (Ser33) and γH2AX in TNBC⁶.

Recently, it was demonstrated that genomic and chromosomal instability in cancer cells results in activation of the innate immune response, mediated by the cGAS-STING-TBK1 pathway, which subsequently leads to JAK/STAT signalling⁷. Mechanistically, when DNA ends up in the cytoplasm due to genomic instability, it activates the cytosolic DNA sensor cGAS (cyclic GMP-AMP synthase), triggering the synthesis of cGAMP (2’,3’-cyclic GMP-AMP)⁸. cGAMP subsequently binds the adaptor protein STING (stimulator of interferon genes), resulting in the phosphorylation of TBK1. In turn, TBK1 recruits and phosphorylates the transcription factor IRF3 (interferon regulatory factor 3) or NF-κB, thereby activating a type I interferon (IFN) response. The subsequent release of pro-inflammatory cytokines activates downstream JAK/STAT signalling⁸. For instance, genomic instability caused by BRCA1 or BRCA2 deficiency triggers cGAS-STING signalling^9,10. Moreover, activation of cGAS-STING-STAT signaling upon BRCA2 inactivation was further potentiated upon PARP inhibition¹¹. Indeed, PARP inhibitors have been shown to activate intratumoral STING signaling, resulting in the recruitment of CD8⁺ T-cells in BRCA-deficient models of TNBC¹². Likewise, treatment with chemotherapeutic agents that target DNA replication¹³ have also been shown to induce cGAS-STING signalling¹⁴.

Recently, multiple studies suggested anti-tumor effects of STING-mediated immune pathways in several types of cancer. For instance, perinuclear-localized STING in ER⁺ breast cancers has been demonstrated to be an independent predictor of favorable prognosis, associated with higher immune cell infiltration and upregulation of immune checkpoints¹⁵. In line with this observation, DNA damage response-deficient breast tumors showed higher CD4⁺ and CD8⁺ lymphocytic infiltration¹³. Similarly, STING pathway activation in non-small cell lung cancer (NSCLC) predicted response to immunotherapy and was enhanced by cisplatin treatment¹⁶. In line with this notion, STING agonists showed potential anti-tumor effects in several types of cancer^17,18

Besides triggering inflammatory signaling and immune responses in the tumor microenvironment, cGAS-STING signaling has also been shown to have pro-tumorigenic effects. Specifically, activation of the cGAS-STING pathway along with downstream non-canonical NF-κB signaling induced by chromosomal instability have been shown to drive metastasis¹⁹. Also, cGAS-dependent IL-6 secretion and IL6R signaling have recently been demonstrated to provide pro-survival signals in cancer cells, including TNBCs²⁰. In line with these observations, inflammation-driven carcinogenesis was revealed to be mediated via STING²¹.

Importantly, the JAK/STAT1 signaling that is induced upon cGAS-STING activation has been associated with response to treatment in patients with breast cancer, including response to immunotherapy or chemotherapy. For instance, chemotherapy-induced activation of the IFN/STAT1 pathway was associated with treatment response in ER⁻ breast cancer²². Phosphorylation of STAT1 at Ser727 was positively correlated with expression of programmed death-ligand 1 (PDL1) and HLA class I, and could potentially serve as a biomarker to predict response to immunotherapy²³. Moreover, in ER⁺ breast cancers, activation of the IFN signaling pathway has been associated with intrinsic resistance to CDK4/6 inhibitors and immune checkpoint activation²⁴. Mechanistically, genome-wide genetic screens showed that interferon (IFN) signaling by tumor cells is a determinant of response to PD-L1 inhibitor^{25, 26}.

Clearly, cancer-intrinsic interferon signaling is associated with genomic instability and is relevant to treatment response. However, opposing roles of interferon signaling have been described²⁷, with transient activation of inflammatory signaling inducing anti-tumor effects, whereas chronic activation may lead to tumor progression^19,28. Clearly, a better understanding is required of the tumor types that show inflammatory pathway activation, to ultimately improve patient selection for immunotherapy or targeted therapy.

In this study, we investigated the clinical significance of inflammatory signaling and its associations with genomic instability and immune cell infiltration level in breast cancer samples. We first analyzed the expression of key components of the cGAS-STING signaling pathway and their relation to replication stress markers, replication stress-inducing oncogenes, and immune cell markers in breast cancer patients. In parallel, we investigated the correlation between cGAS-STING inflammatory signaling and different molecular breast cancer subtypes, and its association with different genomic instability metrics using data from the TCGA and METABRIC cohorts. Finally, the I-SPY2 immunotherapy cohort was used to evaluate the role of cGAS-STING inflammatory signaling in predicting breast cancer patients’ response to neoadjuvant treatment.

Breast cancer patients and tissue microarray

Consecutive primary breast tumor samples of HER2+, triple negative and the first 200 ER⁺HER2⁻ primary, non-metastasized, breast carcinomas diagnosed between 2006 and 2017 in the University Medical Center Groningen (UMCG, The Netherlands) were retrospectively collected and included in a tissue microarray (TMA). In line with Dutch law and UMCG security guidelines, the retrospective collection of clinicopathological characteristics and overall survival data from patient charts and the Personal Records Database was approved by the Local Ethics Review Board Pathology non-WMO studies (UMCG research register number 201900243). Patients receiving neoadjuvant treatment, with local recurrence or metastasis at presentation were excluded. 18 samples were excluded after prior inclusion, resulting in a study population of 380 samples. Patients with two primary breast cancers were excluded from the survival analysis. The specimens used in this study were obtained from redundant diagnostic material stored at the Department of Pathology, UMCG. No objection to research on redundant tissue was recorded from these patients in the institutional record of objection.

Immunohistochemistry (IHC)

Slides (3 µm) of formalin-fixed and paraffin-embedded tissue were deparaffinized in xylene and rehydrated in decreasing ethanol solutions. Antigen retrieval was achieved by microwave heating for 15 minutes in 1 mM EDTA buffer pH 8 (10mM Tris/EDTA buffer pH 9 for pTBK1 staining). Endogenous peroxidase was blocked by incubating in 0.3% H2O2 in phosphate buffered saline (PBS) solution for 30 minutes. After one-hour incubation with diluted primary antibody, a secondary goat-anti-rabbit-HRP (DAKO, Glostrup, Denmark, 1:100 in PBS/ 1% BSA/ 1% serum) was incubated for 30 minutes, followed by a rabbit-anti-goat-HRP (DAKO, 1:100 in PBS/1% BSA/1% serum) incubation for 30 minutes. The primary antibodies in this study include anti-STING (Cell Signaling #13647, 1:100), anti-pSTAT1 (Ser727, Cell Signaling, MA, USA, #8826S, 1:200) and anti-pTBK1 (Ser172, Cell Signaling #5483, 1:50). After each step, the slides were rinsed in PBS. Staining was visualized by using 3,3’-diaminobenzidine tetrahydochloride substrate (Sigma) for 10 minutes, followed by counterstaining with haematoxylin for 2 minutes and covered by a mounting medium. For pRPA32 staining (Ser33, Bethyl #A300-246A, 1:400), the complete staining procedure was performed on an autostainer (BenchMark Ultra, Roche, AZ, USA). The antibodies and staining protocols of Cyclin E1, c-Myc, and γH2AX stainings were described previously⁶. For CD4 (SP35, Ventana), CD20 (L-26, Ventana) and CD57 (NK-1, Ventana) staining, the antibodies were pre-diluted by the manufacturer and sections were stained on a Ventana Benchmark Ultra immunostainer (Ventana) according to the manufacturer’s protocols.

Scoring was performed semi-quantitatively without knowledge of clinical data and was supervised by a breast cancer pathologist. The IHC stainings were considered evaluable when a tumor core contained at least 10% tumor cells. The H scores (range from 0-200) were calculated by intensity (negative: 0; medium: 1; high: 2) multiplied by the percentage of cells in each group. As previously described, peri-nuclear STING (pnSTING) expression was evaluated by the percentage of positive cells as a proxy for activated STING¹⁵. The percentage of pnSTING-positive tumor cells was then scored semi-quantitatively. Only the tumor cells with strong staining in perinuclear area (within 1 µm) were considered as pnSTING positive cells (Fig. S1). In addition, the nuclear and cytoplasmic Cyclin E1 expression was scored separately according to the previous studies^6,29,30. The CD4 and CD20 immune cell staining were counted by using Visiopharm Integrator System (VIS) (Visiopharm, Denmark) software. For CD57, we manually counted positive staining cells. The staining scores from the individual cores of each tumour were averaged for analysis.

TCGA, METABRIC and I-SPY2 data

Gene expression data and clinical information of breast cancer patients in the TCGA and METABRIC cohorts were obtained from cBioportal on August 10th, 2022^31,32. For the TCGA cohort, transcriptomic data, copy number data, clinic information, ER, PR, and HER2 status were obtained of 1084 breast cancers. For the METABRIC cohort, clinic data including survival, stage, tumor size, lymph node metastases status, Nottingham Prognostic Index (NPI), histological grade, and PAM50 subtypes were obtained for 1903 breast cancers³³. Also, ER, PR and HER2 status were also obtained for the METABRIC cohort. Additional details about copy number alteration analysis are described in the supplementary methods. Besides, to investigate the association between cGAS-STING scores and genomic instability level in breast cancer patients, metrics of genomic instability, including tumor mutation burden (TMB) and homologous recombination deficiency (HRD) in the TCGA cohort were also accessed from previous studies³⁴. Additional details about metrics of genomic instability are described in the supplementary methods.

In order to explore the association between cGAS-STING scores and immunotherapy response in breast cancer patients, transcriptomic data from I-SPY2 trial were analysed³⁵. Original transcriptomic and patients’ response data were accessed through GSE173839 in Gene Expression Omnibus (GEO; https://www.ncbi.nlm.nih.gov/geo/).

cGAS-STING score and gene set enrichment analysis

We assembled genes involved in the cGAS-STING pathway from previous studies³⁶, including C6orf150 (encoding cGAS/MB21D1), CCL5, CXCL10, IRF3, TBK1, TMEM173 (encoding STING1) and STAT1 (Table. S1). Gene set variation analysis (GSVA) was used to calculate the GSVA scores of these genes in the TCGA and I-SPY2 cohort by using the “GSVA” R package. Of note, TMEM173 (STING1) mRNA expression levels could not be retrieved for samples of the METABRIC database, therefore only MB21D1, CCL5, CXCL10, IRF3, TBK1, and STAT1 were used to calculate the GSVA scores in the METABRIC cohort. Additionally, to explore difference between cGAS-STING^high and cGAS-STING^low groups, Gene Set Enrichment Analysis (GSEA) was performed using the Hallmarks gene sets³⁷. Additional details about functional enrichment analysis were described in the supplementary methods.

Statistical analysis

Data were analyzed using Statistical Package for Social Sciences version 23.0 (SPSS Inc., Chicago, IL, USA). Comparison of continuous variables among different groups was analyzed by Kruskal–Wallis tests or Wilcoxon rank-sum tests as indicated. Spearman correlation was used to compare the correlation of protein expression levels. Kaplan–Meier survival curves and log-rank statistics were employed to evaluate time to tumor recurrence and breast-cancer-specific survival. Univariate and multivariate linear regression model was used to investigate the relation between pSTAT1 and markers of genomic instability. Univariate and multivariate regression analysis was performed using Cox proportional hazards model. Results were considered statistically significant when P < 0.05.

cGAS-STING signaling is higher in TNBCs

We first analyzed a cohort of 380 breast cancers, including 182 ER⁺HER2⁻, 107 HER2⁺ cases and 91 TNBC cases (Fig. 1A). Clinicopathological characteristics and treatment of the patients in this cohort are summarized in Table 1. The protein expression levels of STING, pTBK1 (Ser172), and pSTAT1 (Ser727) were evaluated using IHC. Expression levels were quantified using H-scores (Fig. 1B-1F). As expected from components within a shared pathway, pSTAT1 expression was significantly associated with perinuclear (pn)STING (Spearman r = 0.142, P = 0.006) and pTBK1 (Spearman r = 0.301, P < 0.001), across all breast cancer samples (Table S1).

Table 1

Overview of the breast cancer patient cohort in this study.
			Total(%)	ER+/HER2- (%)	HER2+ (%)
	Total	380	182	107	91
Menopausal status	Premenopausal	97(25.7)	36(19.9)	31(29.5)	30(33.0)
	Perimenopausal	38(10.0)	17(9.4)	12(11.4)	9(9.9)
	Postmenopausal	185(48.7)	93(51.4)	53(50.5)	39(42.9)
	Unknown	57(15.0)	35(19.3)	9(8.6)	13(14.3)
Histological grade	I	75(19.7)	68(37.4)	5(2.7)	2(2.2)
	II	125(32.9)	76(41.8)	34(21.8)	15(16.5)
	III	178(46.8)	38(20.9)	67(62.6)	73(80.2)
	Unknown	2(0.6)	0(0)	1(0.9)	1(1.1)
T	T1	231(61.3)	124(68.5)	58(54.7)	49(54.4)
	T2	131(34.7)	54(29.8)	42(39.6)	35(38.9)
	T3	10(2.7)	3(1.7)	5(4.7)	2(2.2)
	T4	5(1.3)	0(0)	1(0.9)	4(4.4)
N	N0	254(68.3)	129(72.5)	67(63.2)	58(65.9)
	N1	71(19.1)	32(18.0)	23(21.7)	16(18.2)
	N2	31(8.3)	10(5.6)	12(11.3)	9(10.2)
	N3	16(4.3)	7(3.9)	4(3.8)	5(5.7)
Stage	I	182(48.9)	101(57.1)	44(41.5)	37(41.6)
	II	140(37.6)	59(33.3)	46(43.4)	35(39.3)
	III	50(13.4)	17(9.6)	16(15.1)	17(19.1)
Chemotherapy	No	172(45.3)	120(65.9)	23(21.5)	29(31.9)
	Yes	208(54.7)	62(34.1)	84(78.5)	62(68.1)
Radiotherapy	No	107(28.2)	55(30.2)	22(20.6)	30(33.0)
	Yes	271(71.3)	127(69.8)	83(77.6)	61(67.0)
	Unknown	2(0.5)	0(0)	2(1.8)	0(0)

In terms of breast cancer subtypes, the total STING expression and percentage of pnSTING⁺ cells did not significantly differ among the 3 subtypes (P = 0.427, P = 0.576, respectively, Fig. 1G-1H). Notably, expression of pTBK1 was higher in TNBC compared to ER⁺/HER2⁻ cases (P = 0.002), but similar to HER2⁺ cases (P = 0.226, Fig. 1I). pSTAT1 expression was also significantly higher in TNBC cases compared to ER⁺/HER2⁻ (P < 0.001) and HER2⁺ cases (P < 0.001, Fig. 1J). The percentage of cases that expressed pTBK1 and pSTAT was also higher in TNBC (Fig. 1K).

To compare our observations to large publically available cohorts, we subsequently calculated a cGAS-STING activation score through analysis of a seven-gene mRNA expression signature, reflecting key components in the cGAS-STING pathway (C6orf150, CCL5, CXCL10, IRF3, TBK1, TMEM173, and STAT1) ³⁶ (further referred to as “cGAS-STING score”) (Fig. S2A- S2B, Table S2). We found that cGAS-STING scores were higher in the advanced-stage clinical subgroups in the METABRIC cohort, especially stage II and III&IV patients and patients with lymph node metastases (P < 0.001, Fig. S3E-S3F). However, cGAS_STING scores were not related to tumour size (Fig. S3D, P = 0.38). In the TCGA cohort of patients with breast cancer, cGAS-STING scores were not related to different clinical subgroups (tumour size, P = 0.075 Fig.S3A; clinical stage, P = 0.23 Fig.S3B; lymph node states, P = 0.684, Fig.S3C). However, cGAS-STING scores were significantly higher in TNBCs, basal-like and HER2-enriched breast cancer subtypes, both in the TCGA (P < 0.001, Fig. 1L-1M) and METABRIC cohorts (P < 0.001, Fig. 1N-1O). Moreover, cGAS-STING scores were higher in cases with higher tumour grades (i.e. NPI2, NPI3, G2, and G3 subgroups) in the METABRIC cohort (P < 0.001, Fig. S3G-S3H,). Together, these observations show that TNBCs show elevated levelsof cGAS-STING signalling.

cGAS-STING signalling is associated with expression of replication stress-inducing oncogenes in breast cancer

We next investigated whether inflammatory signaling was related to expression of oncogene-induced replication stress in our breast cancer cohort. The proto-oncogenes Cyclin E1 and c-Myc were previously shown to induce replication stress in experimental models³⁸. Moreover, overexpression of Cyclin E1 or MYC results in unscheduled origin firing within gene bodies and leads to replication-dependent DNA lesions^39,40. In line with these data, our previous analysis of breast cancers demonstrated that Cyclin E1 expression was significantly correlated with expression of replication stress markers γH2AX and pRPA32⁶. We analysed the expression of Cyclin E1 and c-Myc in relation to pSTAT1 expression in our breast cancer cohort, we observed that pSTAT1 expression was positively associated with the levels of both nuclear and cytoplasmic Cyclin E1 (nuclear Cyclin E1: Spearman r = 0.241, P < 0.001; cytoplasmic Cyclin E1: r = 0.194, P < 0.001) (Fig. 2A-2D). Also, a positive correlation was found between pSTAT1 expression and c-Myc (r = 0.295, P < 0.001). pTBK1 levels were also positively associated with c-Myc (r = 0.225, P < 0.001), but not with Cyclin E1 expression (nuclear Cyclin E1: Spearman r = 0.058, P = 0.273; cytoplasmic Cyclin E1: r = 0.086, P = 0.103). Surprisingly, pnSTING expression was not significantly correlated with these two oncogenes in our cohort (Table 2; Fig. 2E).

Table 2

Spearman correlation between inflammatory signaling activation and replication stress markers and relative oncogenes among overall samples and different subtypes.
		γH2AX	pRPA	Cyclin E1 (n)	Cyclin E1 (c)	c-Myc
Overall
pSTAT1	correlation	0.350	0.200	0.241	0.194	0.295
	P value	< 0.0001	< 0.0001	< 0.0001	< 0.0001	< 0.0001
pTBK1	correlation	0.160	0.061	0.058	0.086	0.225
	P value	0.002	0.244	0.273	0.103	< 0.0001
pnSTING	correlation	-0.003	0.000	0.011	0.004	0.036
	P value	0.959	0.997	0.840	0.933	0.493
ER + HER2-
pSTAT1	correlation	0.187	0.250	0.180	0.074	0.218
	P value	0.012	0.001	0.017	0.330	0.003
pTBK1	correlation	0.198	-0.056	-0.065	-0.068	0.256
	P value	0.008	0.459	0.392	0.373	< 0.0001
pnSTING	correlation	0.059	-0.034	-0.007	-0.004	0.024
	P value	0.437	0.656	0.928	0.656	0.749
HER2+
pSTAT1	correlation	0.212	0.150	0.054	0.005	0.140
	P value	0.029	0.124	0.581	0.963	0.154
pTBK1	correlation	0.009	0.224	0.078	0.045	0.136
	P value	0.929	0.022	0.430	0.650	0.167
pnSTING	correlation	-0.073	0.027	0.057	-0.018	-0.025
	P value	0.456	0.785	0.565	0.853	0.796
TNBC
pSTAT1	correlation	0.248	0.291	0.317	-0.179	-0.065
	P value	0.036	0.006	0.005	0.113	0.587
pTBK1	correlation	0.064	0.07	0.124	0.086	0.150
	P value	0.590	0.517	0.281	0.448	0.206
pnSTING	correlation	-0.151	0.054	-0.165	-0.128	-0.111
	P value	0.197	0.617	0.142	0.253	0.343

Since oncogene amplification is an important source of replication stress, we next explored the correlation between cGAS-STING scores and expression of oncogenes in the TCGA cohort. We found that increased mRNA expression of most oncogenes was accompanied with higher cGAS-STING scores (Fig. 2F). Also, we found that genomic amplification of various replication stress-related oncogenes was correlated to higher cGAS-STING scores in the TCGA cohort (Fig. 2G, P < 0.001). In summary, our results indicate that cGAS-STING inflammatory signalling is associated with the expression of replication-stress inducing oncogenes.

cGAS-STING signalling is associated with genomic instability in breast cancer

To address whether cGAS-STING signalling was related to levels of genomic instability in breast cancer samples, we immunohistochemically analysed replication stress markers γH2AX and phospho-RPA32 (Ser33) in our breast cancer cohort (Fig. 3A-3C). Importantly, we found that in our overall cohort, pSTAT1 expression was positively associated with γH2AX (Spearman correlation r = 0.350, P < 0.001) and pRPA (r = 0.2, P < 0.001). pTBK1 was positively associated with γH2AX (r = 0.160, P < 0.002), but not with pRPA (r = 0.061, P = 0.244). Again, pnSTING expression was not significantly correlated with replication stress markers in our cohort (Table 2; Fig. 3D).

Next, we analysed the associations in the individual breast cancer subgroups (Table 2). pSTAT1 expression was positively associated with γH2AX in all the breast cancer subgroups (r = 0.187, P = 0.012 in ER⁺/HER2⁻ cases, r = 0.212, P = 0.029 in HER2⁺ cases and r = 0.248, P = 0.036 in TNBC). In addition, pSTAT1 was associated with pRPA and nuclear Cyclin E1 in ER⁺/HER2⁻ (r = 0.25, P = 0.001 and r = 0.18, P = 0.017, respectively) in TNBC patients (r = 0.291, P = 0.006 and r = 0.317, P = 0.005, respectively). pTBK1 was significantly correlated with pRPA in HER2 + cases (r = 0.224, P = 0.022), indicating that that pSTAT1 and pTBK1 expression were strongly correlated with genomic instability. We additionally studied the relation between pSTAT1 expression and markers of genomic instability using linear regression analysis (Table 3). The covariates from univariate analysis with P < 0.05 were included for multivariate analysis. In multivariate analysis, pSTAT1 was associated with γH2AX (β = 0.250, P < 0.001), pRPA (β = 0.172, P < 0.001), nuclear Cyclin E1 (β = 0.151, P = 0.017) and c-Myc (β = 0.202, P < 0.001), when corrected for tumour subtype, stage and grade.

Table 3

Relation between pSTAT1 versus markers of genomic instability and clinicopathological characteristics among the study cohort.
pSTAT1		Univariate			Multivariate
		Beta	95% CI	P value	Beta	95% CI	P value
Tumour subtypes	ER+/HER2-	Ref.			Ref.
	HER2+	0.122	1.767–18.701	0.018	0.046	-5.077-12.116	0.421
	TNBC	0.410	27.685–45.743	< 0.0001	0.084	-5.689-20.885	0.261
Tumour grade	I	Ref.			Ref.
	II	0.084	-3.737-17.230	0.206	0.070	-4.445-14.869	0.289
	III	0.332	15.302–35.166	< 0.0001	0.147	-0.135-21.027	0.053
Stage	I	Ref.
	II	-0.027	-10.504-6.242	0.617
	III	0.051	-6.444-18.129	0.350
γH2AX		0.376	0.405–0.685	< 0.0001	0.250	0.199–0.522	< 0.0001
pRPA		0.145	0.135–0.196	0.005	0.172	0.061–0.212	< 0.0001
Cyclin E1(n)		0.221	0.092–0.248	< 0.0001	0.151	0.020–0.203	0.017
Cyclin E1(c)		0.192	0.067–0.217	< 0.0001	-0.102	-0.166-0.024	0.143
c-Myc		0.287	0.194–0.402	< 0.0001	0.202	0.091–0.316	< 0.0001

The relation between cGAS-STING signaling and genomic instability was further explored in the TCGA and METABRIC cohorts. Gene Set Enrichment Analysis (GSEA) analysis was performed on data from both TCGA and METABRIC cohorts. Interestingly, both in the TCGA and METABRIC cohorts, cGAS-STING scores were associated with proliferation pathways, including ‘E2F targets’ and ‘G2/M checkpoint pathways’; genesets that were previously also associated with genomically unstable cancers ^41,42 (Fig. 4A-B). we further analysed the relationship between the cGAS-STING scores and different genomic instability markers in the TCGA cohort. We first observed a positive correlation between cGAS-STING scores and tumor mutational burden (TMB, r = 0.254, P < 0.001), homologous recombination deficiency (HRD, r = 0.296, P < 0.001) and intratumor heterogeneity in the TCGA cohort (r = 0.28, P < 0.001) (Fig. 4C, 4F, 4E). A similar correlation between TMB and cGAS-STING score was found in the METABRIC cohort (r = 0.0632, P < 0.01) (Fig. S4C). According to previous studies^43–46, clinically-used cut-offs to define high HRD (HRD ≥ 42) or high TMB (TMB ≥ 10) were used to further analyse the expression difference of the cGAS-STING score between high and low HRD or TMB groups (supplementary methods). In line with our previous analysis, we observed that the cGAS-STING scores were higher in both TMB-High and HRD-High subgroups (TCGA:, P < 0.001, Fig. 4D, 4G; METABRIC: P < 0.001. Fig.S4D,). In addition, a positive correlation between cGAS-STING score and several mutation-related metrics were observed in the TCGA cohort, involving fraction altered’ (r = 0.157, P < 0.001), non-silent mutation rate (r = 0.256, P < 0.001) and silent mutation rate (r = 0.21, P < 0.001), indels (r = 0.067, P = 0.0497) and single nucleotide variations (SNVs) neoantigens (r = 0.239, P < 0.001) (Fig. 4H-L). Moreover, we observed a positive correlation between the cGAS-STING scores and somatic copy number alterations (sCNA) levels in the TCGA cohort (Fig. S4E). Of note, the BRCA1-mutant samples (n = 18) showed significantly higher pSTAT1 expression compared to the wildtype cases (n = 82, P < 0.001 Fig. S5). Since BRCA2 mutation was found in only 4 samples with evaluable staining, these results were not included for analysis. In summary, our combined results show that cGAS-STING inflammatory signalling is elevated in breast cancers with genomic instability.

cGAS-STING signalling is associated with immune cell infiltration

Since STING pathway activation has been associated with patients’ response to immunotherapy¹⁶, we investigated the relation between cGAS-STING signalling and immune cell infiltration. We first immunohistochemically analysed the T cell, B cell and NK cell markers CD4, CD20, and CD57, respectively, in our breast cancer cohort (Fig. 5A). Notably, we found that in our overall cohort of breast cancers, pSTAT1 expression was positively associated with the expression of all these immune cells (CD4: Spearman r = 0.349, P < 0.001; CD20: r = 0.335, P < 0.001; CD57: Spearman r = 0.189, P < 0.001). pTBK1 was positively associated with CD4 (Spearman r = 0.182, P < 0.001) and CD20 (Spearman r = 0.103, P < 0.05), but not with CD57 (Spearman r = 0.033, P = 0.529). As for pnSTING, only CD4 was positively correlated with its expression (Spearman r = 0.141, P < 0.01), but not with CD57 (Spearman r = 0.001, P = 0.993) or CD20 (Spearman r = 0.051, P = 0.326) (Fig. 5B). In addition, we noticed that the cGAS-STING scores were associated with immune-related pathways in both TCGA and METABRIC cohorts (Fig. 5C-D).

Inflammatory signalling and prognosis of breast cancer patients

Next, we analysed the prognosis of breast cancer patients in our cohort. 356 patients were included for survival analysis (Table 4). The median follow-up time of our cohort was 140.6 months (range: 2.7-179.2 months). High or low protein expression of pSTAT1, pTBK1 and STING were divided by median score. High pSTAT1 expression was associated with pre-menopausal status (P = 0.002), higher histological grade (P = 0.001), and larger tumour size (P = 0.012, Table S3). pTBK1 expression was also associated with higher tumour grade (P = 0.011, Table S3).

Table 4

Univariate and multivariate COX regression analysis of pSTAT1 of BCSS based on clinical parameters and pSTAT1 expression
		Univariate			Multivariate
		HR	95% CI	P value	HR	95% CI	P value
Tumour subtypes	ER+/HER2-	Ref.			Ref.
	HER2+	0.997	0.368–2.703	0.995	0.401	0.129–1.243	0.114
	TNBC	3.358	1.512–7.459	0.003	1.037	0.365–2.945	0.945
Tumour grade	I	Ref.
	II	1.876	0.378–9.313	0.442	1.852	0.366–9.368	0.456
	III	5.117	1.2-21.816	0.027	3.938	0.788–19.687	0.095
Stage	I	Ref.
	II	1.94	0.780–4.824	0.154	1.382	0.525–3.640	0.513
	III	6.268	2.560-15.347	< 0.001	4.816	1.898–12.238	0.001
Chemotherapy	No	Ref.
	Yes	1.219	0.525–2.829	0.645
Radiotherapy	No	Ref.
	Yes	0.677	0.319–1.440	0.311
pSTAT1	Low	0.446	0.207–0.959	0.039	0.523	0.218–1.257	0.148
	High	Ref.			Ref.
BCSS: breast cancer-specific survival

Univariate and multivariate Cox regression models were used to analyse the associations between pSTAT1 and patient survival (Table S4). In univariate analysis, lower pSTAT1 expression was associated with favourable breast cancer-specific survival (BCSS, HR: 0.446, 95% CI: 0.207–0.959, P = 0.039). Tumour subtypes, lower grade and lower stage were also associated with favourable BCSS, which were included in the multivariate analysis. However, pSTAT1 did not predict BCSS in the multivariate analysis (HR: 0.523, 95% CI: 0.218–1.257, P = 0.148). STING and pTBK1 expression were not associated with BCSS. STING, pTBK1 and pSTAT1 expression also did not predict relapse-free survival (RFS) in our cohort (Table S4). These results indicate that STING, pTBK1 and pSTAT1 were not independent prognostic markers in our cohort.

To further explore whether cGAS-STING signalling is associated with patients’ response to neoadjuvant treatment, involving immune checkpoint inhibitor treatment, in breast cancer, we analysed data from I-SPY2 study³⁵. We noticed that the cGAS-STING scores were higher in patients with pathologic complete response (pCR) to combination treatment of durvalumab, olaparib and paclitaxel (P < 0.001, Fig. 5E-F). In summary, analysis of our own TMA and publically available data showed that cGAS-STING inflammatory signalling was correlated with higher immune cell infiltration and better response to PD-L1 inhibitor combined with chemotherapy treatment in breast cancer.

In this study, we investigated the associations between replication stress markers and cGAS-STING inflammatory signalling in breast cancer. Our results show that the cGAS-STING pathway is differentially activated in different breast cancer subtypes, with TNBCs showing the highest activation both in public databases and our own cohort. Moreover, pSTAT1 expression was positively associated with markers associated with replication stress (γH2AX, pRPA, nuclear Cyclin E1, and c-Myc), even after correction for tumour subgroup, stage and grade. pTBK1 expression was also associated with γH2AX and c-Myc expression. Furthermore, pSTAT1 and pTBK1 expression was associated with more aggressive tumour features, probably because the expression was higher in TNBC. Meanwhile, the cGAS-STING scores derived from publicly available cohorts showed significant positive correlations with the genomic instability metrics HRD, TMB and SCNA. More importantly, we validated that the cGAS-STING pathway was associated with higher immune cell infiltration in breast cancer. Our observations show that inflammatory signalling is highly activated in genomically unstable breast cancers (Fig. S6).

Similar cGAS-STING scores have been used to investigate the correlation with tumour immune microenvironment features. In oral squamous cell carcinoma (n = 327), combined high expression of cGAS and STING has been associated with immune cell infiltration and the expression profiles of immune-related genes³⁶. Likewise, STING-related genes (CXCL10, CCL5, CGAS) were associated with immune activation in lung adenocarcinoma¹⁶.

Meanwhile, we validated the results from public databases on our TMA cohort. CCNE1 is amplified in approximately 9% of basal-like breast cancer³² and has been reported to induce replication stress⁴⁷. Interestingly, cytoplasmic Cyclin E1 was reported to predict breast cancer recurrence and response to neoadjuvant chemotherapy^29,48. Both nuclear and cytoplasmic Cyclin E1 expression were independently associated with γH2AX in breast cancer⁶. Therefore, we scored the nuclear and cytoplasmic Cyclin E1 separately, and found that tumours with higher nuclear Cyclin E1 showed higher pSTAT1 expression.

Surprisingly, STING expression was not associated with replication stress markers in our cohort, which might be due to several reasons. Firstly, STING was reported to be phosphorylated upon activation ^16,49. Specifically, upon CHK1 inhibition or olaparib treatment, levels of phosphorylated STING (S366) were higher, while total STING expression did not increase⁴⁹. Since we did not analyze phospho-STING levels, we may have missed these effects in our analysis. Secondly, STING is activated by cGAMP at the endoplasmic reticulum (ER), in which STING forms tetramers and translocates to ER-Golgi intermediate compartments. At the Golgi, the palymitolyation of STING has been shown to recruit TBK1 and IRF3⁸. Therefore, the cGAS-STING signature score probably better reflects the activation status of cGAS/STING signalling compared to STING levels alone.

Due to the limited response rate and efficacy of immunotherapy in breast cancer, it is of significant importance to identify patient subgroups that may respond to immune checkpoint inhibitors, and find useful biomarkers for selection⁵⁰. pSTAT1 expression was reported as a potential biomarker for anti‑PD‑1/anti‑PD‑L1 immunotherapy for breast cancer²³. In addition, one of the interferon-β-related cytokines, CXCL10, was shown to potentiate immune checkpoint blockade therapy in HR-deficient breast cancer⁵¹. Another reason to study the cGAS-STING and interferon signalling is that it may sensitize cancer patients to immunotherapy. For instance, targeting replication stress with CHK1 inhibitor promoted cGAS-STING signalling and NKT cell immune responses, and led to tumour regression⁵². Moreover, the STING agonist enhances the efficacy of PD-L1 monoclonal antibody in breast cancer immunotherapy by activating the interferon-β signalling pathway⁵³. Our results also showed that BRCA1-mutant cancers exhibited higher cGAS-STING scores and higher pSTAT1 expression. The combination treatment with PARP inhibitor with PD-L1 inhibitor has been tested in BRCA-mutated metastatic breast cancer in phase 1/2 clinical trials. The initial results showed promising antitumor activity⁵⁴.

Importantly, inflammatory signalling mediated by JAK/STAT1 can act as a double-edged sword. In fact, phosphorylation of STAT1 at Tyr701 has been associated with advanced tumour stage and worse survival in premenopausal breast cancer patients⁵⁵. In fact, STAT1 can interact directly with ERα, which results in resistance to aromatase inhibitors⁵⁶. Also, whereas transient activation of inflammatory signalling can induce anti-tumour effects, chronic activation may lead to tumour progression^19,28.

Of note, c-Myc was reported to suppress cGAS-STING mediated immune signalling¹⁰. Importantly, MYC was shown to promote immune suppression in TNBC through suppression of IFN signalling^10,57. In addition, MYC amplification and overexpression led to low immune infiltration and cytolytic activity through suppression of interferon signalling and via activating of the transcription of DNMT1⁵⁸. However, we found that pSTAT1 and pTBK1 were positively associated with c-Myc in ER⁺HER2⁻ tumours, but not in TNBC. We argue that this might be due to several reasons. Firstly, Myc-induced DNA replication stress may lead to activation of STAT1 or TBK1. Secondly, the inflammatory signalling may in return regulate MYC activity. For instance, STAT1 has been shown to upregulate MYC and functions as a pro-survival gene in serous papillary endometrial cancers⁵⁹. TBK1 can promote MYC-dependent survival pathways in acute myeloid leukemia⁶⁰. Future studies are needed to investigate the mechanisms in ER⁺HER2⁻ breast cancer.

In terms of patient prognosis, low pSTAT1 expression was associated with longer BCSS among the overall population which may be explained by the pro-tumorigenic effects of chronic inflammation¹⁹. However, pSTAT1 was not an independent prognostic marker in multivariate analysis. A previous study revealed that pnSTING is an independent predictor of favourable RFS in ER + breast cancer and is associated with immune cell infiltration and upregulation of immune checkpoints¹⁵.

In conclusion, our results showed an interplay between tumour intrinsic genomic instability and cGAS-STING innate immune signalling as well as the downstream STAT1 signalling. We also validated that higher cGAS-STING signalling is associated with higher immune cell infiltration. Further studies are still needed to elucidate the level of immune cell infiltration in CCNE1 overexpressed or other kinds of genomically unstable breast cancer. Our findings may potentially support identification of tumours which respond favourably to immunotherapy.

Authors' contributions

Study concept and design: MC, SY, BvdV, MVV; TMA preparation and IHC staining: TvdS, BvdV; Scoring of IHC staining: MC, BvdV; Clinical information collection: MZ, CS; Public data analysis: SY; Manuscript writing: MC, SY; Manuscript reviewing and editing: MvV, BvdV

Consent for publication

All patients or their legal representatives gave informed consent for the pathology analysis of tumour samples, clinical data analysis and publication of the results.

Data availability

Gene expression data and clinical information from TCGA and METABRIC can be downloaded from the cBioportal (https://www.cbioportal.org/). Upon reasonable request, other data are available from the corresponding author.

Ethical approval

This study was performed in line with the principles of the Declaration of Helsinki. Approval was granted by the Local Ethics Review Board Pathology non-WMO studies (UMCG research register number 201900243, approved on 18-8-2020).

Funding information

This work has been funded by China Scholarship Council scholarships to M.C. (201906100046) and S.Y (202106280037).

Competing interests

BvdV reports honoraria received by UMCG for expertise or scientific advisory board/consultancy (on request): Visiopharm, Philips, MSD/Merck, Daiichi-Sankyo/AstraZenica; Speaker’s fee from Visiopharm, Diaceutics, MSD/Merck. All other authors declare no competing interests.

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There is a conflict of interest BvdV reports honoraria received by UMCG for expertise or scientific advisory board/consultancy (on request): Visiopharm, Philips, MSD/Merck, Daiichi-Sankyo/AstraZenica; Speaker’s fee from Visiopharm, Diaceutics, MSD/Merck. All other authors declare no competing interests.

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Expression of the cGAS-STING pathway is associated with high levels of genomic instability and immune cell infiltration in breast cancer

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Abstract

Figures

INTRODUCTION

METHODS

Breast cancer patients and tissue microarray

Immunohistochemistry (IHC)

TCGA, METABRIC and I-SPY2 data

cGAS-STING score and gene set enrichment analysis

Statistical analysis

RESULTS

cGAS-STING signaling is higher in TNBCs

cGAS-STING signalling is associated with expression of replication stress-inducing oncogenes in breast cancer

cGAS-STING signalling is associated with genomic instability in breast cancer

cGAS-STING signalling is associated with immune cell infiltration

Inflammatory signalling and prognosis of breast cancer patients

DISCUSSION

Declarations

References

Additional Declarations

Supplementary Files

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Journal Publication

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