Volume 261, Issue 4 p. 477-489
Original Article
Open Access

Canonical Kaiso target genes define a functional signature that associates with breast cancer survival and the invasive lobular carcinoma histological type

Thijmen Sijnesael

Thijmen Sijnesael

Department of Pathology, University Medical Center Utrecht, Utrecht, The Netherlands

Equal contribution.

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François Richard

François Richard

Laboratory for Translational Breast Cancer Research, Katholieke Universiteit Leuven, Leuven, Belgium

Equal contribution.

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Max AK Rätze

Max AK Rätze

Department of Pathology, University Medical Center Utrecht, Utrecht, The Netherlands

Equal contribution.

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Thijs Koorman

Thijs Koorman

Department of Pathology, University Medical Center Utrecht, Utrecht, The Netherlands

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Blessing Bassey-Archibong

Blessing Bassey-Archibong

Department of Biology, McMaster University, Hamilton, ON, Canada

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Christa Rohof

Christa Rohof

Department of Pathology, University Medical Center Utrecht, Utrecht, The Netherlands

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Juliet Daniel

Juliet Daniel

Department of Biology, McMaster University, Hamilton, ON, Canada

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Christine Desmedt

Christine Desmedt

Laboratory for Translational Breast Cancer Research, Katholieke Universiteit Leuven, Leuven, Belgium

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Patrick WB Derksen

Corresponding Author

Patrick WB Derksen

Department of Pathology, University Medical Center Utrecht, Utrecht, The Netherlands

Correspondence to: PWB Derksen, Department of Pathology, UMC Utrecht, H04.312, Heidelberglaan 100, 3584 CX, Utrecht, The Netherlands.

E-mail: [email protected]

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First published: 22 September 2023

No conflicts of interest were declared.

Abstract

Invasive lobular carcinoma (ILC) is a low- to intermediate-grade histological breast cancer type caused by mutational inactivation of E-cadherin function, resulting in the acquisition of anchorage independence (anoikis resistance). Most ILC cases express estrogen receptors, but options are limited in relapsed endocrine-refractory disease as ILC tends to be less responsive to standard chemotherapy. Moreover, ILC can relapse after >15 years, an event that currently cannot be predicted. E-cadherin inactivation leads to p120-catenin-dependent relief of the transcriptional repressor Kaiso (ZBTB33) and activation of canonical Kaiso target genes. Here, we examined whether an anchorage-independent and ILC-specific transcriptional program correlated with clinical parameters in breast cancer. Based on the presence of a canonical Kaiso-binding consensus sequence (cKBS) in the promoters of genes that are upregulated under anchorage-independent conditions, we defined an ILC-specific anoikis resistance transcriptome (ART). Converting the ART genes into human orthologs and adding published Kaiso target genes resulted in the Kaiso-specific ART (KART) 33-gene signature, used subsequently to study correlations with histological and clinical variables in primary breast cancer. Using publicly available data for ERPOSHer2NEG breast cancer, we found that expression of KART was positively associated with the histological ILC breast cancer type (p < 2.7E-07). KART expression associated with younger patients in all invasive breast cancers and smaller tumors in invasive ductal carcinoma of no special type (IDC-NST) (<2 cm, p < 6.3E-10). We observed associations with favorable long-term prognosis in both ILC (hazard ratio [HR] = 0.51, 95% CI = 0.29–0.91, p < 3.4E-02) and IDC-NST (HR = 0.79, 95% CI = 0.66–0.93, p < 1.2E-04). Our analysis thus defines a new mRNA expression signature for human breast cancer based on canonical Kaiso target genes that are upregulated in E-cadherin deficient ILC. The KART signature may enable a deeper understanding of ILC biology and etiology. © 2023 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Introduction

Mutational inactivation of E-cadherin and a subsequent dismantling of the cellular adhesive structure called the adherens junction (AJ) causes the development and progression of invasive lobular carcinoma (ILC) (reviewed in [1]). Due to the functional inactivation of E-cadherin-based cell–cell contacts, ILC cells invade diffusely as noncohesive cells in trabecular structures or in a single-file pattern [2]. Recent evidence has established that E-cadherin inactivation leads to increased and concomitant activation of PI3K/AKT signals independently of activating mutations [3-5], which provide a mechanism for the previously observed AKT phosphorylation in lobular breast cancers [6]. In addition, E-cadherin loss leads to direct translocation of p120-catenin (p120) from the cell membrane to the cytoplasm and nucleus [7-9], a process that is further promoted by loss of cell-matrix contacts [10]. In healthy cells, the main function of p120 includes providing stability for all classical cadherin family members, including E-cadherin [11, 12], and spatial regulation of RhoA-dependent actomyosin contraction at the cleavage furrow during cytokinesis [13]. Importantly, p120 can also bind and relieve transcriptional repression of Kaiso (ZBTB33), a bimodal regulator of transcription [14]. Kaiso can repress mRNA transcription through binding to the canonical Kaiso-binding sequence (cKBS) TCCTGCNA or modulate a noncanonical function through the CGCG-containing consensus KBS TCTCGCGAGA [15, 16].

The ability of p120 to relieve canonical Kaiso-dependent transcriptional repression relies on nuclear translocation of p120 through a conserved nuclear localization sequence (NLS) [17, 18]. Canonical p120-dependent KBS targets such as Siamois [19], Wnt11 [20], and Cyclin D1 [19, 21] have been associated with tissue homeostasis in frogs, flies, and/or mammalian cells. Although the exact mechanism remains unclear, nuclear influx of p120 increases upon transfer of cells to anchorage-independent culture conditions [10]. Under these conditions, the cKBS target Wnt11 is transcribed as a direct consequence of E-cadherin loss and Kaiso de-repression by p120, to subsequently promote autocrine RhoA-dependent-anoikis resistance in lobular breast cancer cells [10].

Although the histological subtypes of ILC and invasive ductal carcinoma of no special type (IDC-NST) display distinct molecular landscapes [6, 22, 23], this has not yet evolved into specific classifiers that can contribute to the development of a tailored clinical intervention for ILC. Here, we present a functional and experimentally derived transcriptional signature based on 33 canonical Kaiso target genes (KART) that associates with the lobular histological subtype. We show that high KART signatures associate with a favorable prognosis in breast cancer, irrespective of the histological type.

Materials and methods

ERBB3 promoter analysis

Promoter analysis of human ERBB3 was performed using the Eukaryotic Promoter Database (EPD) [24], with evaluation of the 1,000 upstream base pairs of the gene and exploration of the ZBTB33 (Kaiso)-binding sites (full KBS sequence TCCTGCNA and core KBS sequence CTGCNA), and plotted using Adobe Illustrator (Adobe Inc, San Jose, CA, USA). Promoter analysis of mouse Erbb3 gene was performed using the NCBI Genome Data Viewer (NCBI, Bethesda, MD, USA) [25].

KBS anoikis resistance transcriptome (KART)

The mouse ILC anoikis resistance transcriptome (ART) was described in van de Ven et al 2015 [10]; we derived the human counterparts from 27 candidate mouse KBS-containing ART genes through Ensemble (EMBL-EBI, Hinxton, UK) [26] and extracted the promoter regions using the EPD (SIB, Eclubens, Switzerland) [24].

Kaiso chromatin immunoprecipitations (ChIP) and PCR

ChIP procedures and PCR analyses were conducted as described previously [27]. The following primers were used for amplification of the target promoter sequences: cKBS Forward (5’–3’) TTGAAATGCAAGGCCGTCTG and Reverse (5’–3’) CCACAGAGACCGCGTGAAAT, non-cKBS Forward (5’–3’) GTTGGGGTAAGGTCACAGA, and Reverse (5’–3’) GGAATAGAAAGGCGGGAAAG.

Cell culture

MCF7 cells were obtained from the American Type Culture Collection (ATCC, Manassas, VA, USA), STR-type verified by PCR, and cultured as described previously [9]. Generation of E-cadherin knockout MCF7::∆CDH1 cells using CRISPR-Cas9 editing has been described previously [5]. Designed primer pairs are shown in supplementary material, Table S1.

CRISPR/Cas9-mediated knockout of kaiso (ZBTB33)

Baculoviruses expressing Cas9 were produced as described previously [28]. Two guide (g)RNAs were tested in MCF7 cells, and after tracking of indels by decomposition analysis [29] the cells with the highest gRNA efficiency were clonally expanded and screened for Kaiso expression using western blotting.

Western blotting

Western blotting was performed as described previously [10]. The following primary antibodies were used for western blot analysis: monoclonal rabbit HER3/ERBB3 clone D22C5 (#12708; 1:1,000; Cell Signaling Technology, Leiden, The Netherlands), monoclonal mouse anti-Kaiso 6F/6F8 (#12723; 1:10000; Abcam, Amsterdam, The Netherlands), and polyclonal goat anti-Akt1 C-20 (sc-1618; 1:1,000; Santa Cruz Biotechnology, Heidelberg, Germany).

RT-qPCR

Total RNA was extracted from cell or organoid pellets using Trizol (15596026, Thermo Fisher Scientific, Bleiswijk, The Netherlands). Poly-T primers and a cDNA reverse transcription kit (iScript Synthesis kit, 1708890, BioRad, Lunteren, The Netherlands) were used to generate cDNA. Two ERBB3-specific primer sets (supplementary material, Table S1) were used to evaluate expression values for human ERBB3 using PCR. Primer efficiency was assessed by serial dilution. Expression values were generated using ∆∆Ct values normalized to GAPDH for control and ERBB3. Experiments were performed in triplicate over three independent biological and technical settings using the BioRad CFX96 Real-Time System (Bio-Rad Laboratories Hercules, CA, USA) and BioRad CFX manager software (Bio-Rad Laboratories). For each comparison, unpaired two-tailed Student's t-tests were used to determine statistical significance.

Bioinformatics analysis of patient data

The METABRIC [30] dataset, including clinical data and normalized gene expression, and the clinical data of The Cancer Genome Atlas (TCGA) dataset [31] were retrieved through cBioPortal [32] in August 2022. The TCGA normalized expression data were retrieved from the GDC data portal (https://gdc.cancer.gov/) in September 2021. Breast cancer types were assessed according to ER immunohistochemistry and ERBB2/HER2 immunohistochemistry or FISH status. Only patients with ER-positive/HER2-negative IDC-NST and ILC breast cancers were kept in the downstream analysis. This resulted in data from 227 IDC-NST and 98 ILC patients for TCGA and data from 979 IDC-NST and 118 ILC patients in METABRIC. Gene expression signatures were retrieved from the literature (ESR1_signature, AURKA, PLAU, STAT1 [33]; DCN [34]; gene expression grade index (GGI) [35]; SDDP [36]; Immune_Perez [37]; IRM [38]; immune cell signatures [39]; GENE21 [40]; LobSig [41], and computed as described in [42]). Wilcoxon tests were performed to compare continuous to categorical variables. Correlations were assessed using Spearman coefficients. In the heat maps, only significant correlations are colored: red, anticorrelated; blue correlated. Associations with disease-free survival (DFS) and overall survival (OS) were assessed using stratified log-rank test and Cox proportional hazard regression. Multivariable Cox models were adjusted for age (>50 versus ≤50), tumor size (≥2 versus <2), and nodal status (positive versus negative). The follow-up was curtailed at 8 and 20 years for the TCGA and METABRIC datasets, respectively, in consideration of the declining numbers of patients after that time point. P values were two-sided and statistical significance considered for p < 0.05. All analyses were performed using R version 4.0.2 (R Foundation for Statistical Computing, Vienna, Austria) [43].

Results

Defining an anchorage-independent transcriptome driven by E-cadherin loss and canonical Kaiso target genes

We have used mouse ILC cells to couple anchorage independence upon loss of E-cadherin to the activation of a gene set in anchorage-independent (suspension) conditions [10, 44]. Because mutational E-cadherin inactivation leads to a p120-dependent activation of Kaiso target genes (Figure 1A), we had used this gene set to define a set of 27 candidate mouse Kaiso targets based on the presence of a cKBS within a region 1 kb upstream of the transcriptional start site (TSS) [10]. These mouse ILC candidate Kaiso targets [10] were converted to human orthologs, and the presence of cKBS sites in these promoters was confirmed using the EPD (SIB) [24] (Table 1).

Details are in the caption following the image
ERBB3 is a direct Kaiso transcriptional target gene in breast cancer cells. (A) Control over p120-dependent Kaiso transcriptional repression in the context of E-cadherin expression. Cartoon depicting E-cadherin-positive ductal breast cancer (left panel), where p120-catenin (p120) is retained at the membrane in the adherens junction (AJ) complex. In this setting, Kaiso represses expression of its target genes by KBS-dependent binding. In E-cadherin mutant lobular breast cancer (right panel), p120 is translocated to the cytosol and nucleus. Under anchorage-independent (suspension) conditions, nuclear influx of p120 is increased approximately twofold, leading to a relief of Kaiso transcriptional repression. (B) Shown is the ERBB3 promoter region (up to −1,000 base pairs) that was analyzed for the presence of canonical Kaiso binding sites (cKBS; CTGCNA), plotted in base pairs upstream of the transcription start site (TSS). (C) Kaiso specific chromatin immunoprecipitation (ChIP) and subsequent PCR analyses on lysates from MDA-MB-231 (MM231) and MCF7 reveal that Kaiso binds the ERBB3 promoter. (D) Western blot analysis depicting loss of Kaiso expression upon knockout in MCF7 cells (MCF7::∆Kaiso). AKT was used as loading control. (E) Bar graph showing ERBB3 mRNA expression in parental MCF7 and MCF7::∆Kaiso. **** = p < 0.0001. (F) Kaiso controls ERBB3 protein levels. Shown are western blot analyses of ERBB3 expression levels in parental MCF7 cells, MCF7::∆Kaiso cells, and MCF7::∆CDH1 cells grown under adherent conditions. The fold increase in ERBB3 expression relative to the loading control (AKT) is shown below the ERBB3 blot in bold typeface.
Table 1. Combined KBS anoikis resistance transcriptome (KART).
No. Gene symbol Ensembl entry Origin PMID reference
1 CCND1* ENSG00000110092 Xenopus laevis/Homo sapiens 15935774/27694442 + 23226276
2 CCNE1* ENSG00000105173 Homo sapiens 27694442
3 FOS* ENSG00000170345 Xenopus laevis 15935774
4 MMP7* ENSG00000137673 Homo sapiens 23251453 + 18653469
5 MYC* ENSG00000136997 Xenopus laevis 15935774
6 WNT11* ENSG00000085741 Xenopus laevis/Mus musculus 15543138/25713299
7 ID2* ENSG00000115738 Homo sapiens/Mus musculus 35610485/25713299
8 ERBB3* ENSG00000065361 Homo sapiens Described in this article
9 AGT ENSG00000135744 Mus musculus 25713299
10 ALDH1A3 ENSG00000184254
11 ALDH3B2 ENSG00000132746
12 ASPRV1 ENSG00000244617
13 CAMK2N1 ENSG00000162545
14 CCPG1 ENSG00000260916
15 CDSN ENSG00000204539
16 DNAJB9 ENSG00000128590
17 FABP5 ENSG00000164687
18 GABRP ENSG00000094755
19 IL33 ENSG00000137033
20 KRT78 ENSG00000170423
21 LGR4 ENSG00000205213
22 LY6D ENSG00000167656
23 MAN1C1 ENSG00000117643
24 MXD1 ENSG00000059728
25 MYLIP ENSG00000007944
26 RORC ENSG00000143365
27 SECTM1 ENSG00000141574
28 SLC43A2 ENSG00000167703
29 TACSTD2 ENSG00000184292
30 TGFB3 ENSG00000119699
31 TMEM176A ENSG00000002933
32 TMEM176B ENSG00000106565
33 TRIM29 ENSG00000137699
  • * Validated by ChIP and/or functional analyses.

Because ERBB3 activation recently was associated with ILC [23] and the ERBB3 promoter contains a cKBS at position –904 (Figure 1B), we next verified whether ERBB3 was a cKBS Kaiso target gene. For this we performed chromatin immunoprecipitations (ChIP) with monoclonal Kaiso antibodies, followed by an ERBB3 promoter-specific PCR, which demonstrated that ERBB3 was a bona fide canonical Kaiso target gene in E-cadherin-negative (MDA-MB-231) and E-cadherin-positive (MCF7) cells (Figure 1C). Next, we generated CRISPR/Cas9-mediated MCF7 Kaiso knockout cells (MCF7::∆Kaiso) using primers described in supplementary material, Table S1 (Figure 1D), and observed that Kaiso knockout induced a sixfold increase in ERBB3 mRNA expression compared to control cells (Figure 1E). Moreover, E-cadherin loss or Kaiso knockout both increase ERBB3 protein expression by 2.1- and 5.0-fold, respectively (Figure 1F). In sum, we have identified ERBB3 as a canonical Kaiso target, which we added to the ART signature (Table 1).

To develop an mRNA signature for human breast cancer, we added the published p120-dependent cKBS target genes such as WNT11 [20], CCND1 [19, 21], CCNE1 [45], FOS [19], MYC [19], MMP7 [46, 47], and ID2 [44] to define a comprehensive KART signature consisting of 33 genes (Table 1).

Expression of KART signature associates with histological subtype ILC and clinicopathological parameters in breast cancer

We next analyzed expression of the KART signature in the publicly available ERPOS/HER2NEG mRNA expression datasets from TCGA (IDC-NST: n = 227 and ILC: n = 98) and METABRIC (IDC-NST: n = 979 and ILC: n = 118) to probe for possible associations with clinicopathological parameters. We found that the KART signature was positively associated with the ILC subtype in both the TCGA (p = 1.1E-11) and METABRIC (p = 2.7E-07) datasets (Figure 2A). Interestingly, KART is also associated with younger age at diagnosis (<50 years), both in patients with ILC (p = 8.3E-02 and p = 1.8E-02 in TCGA and METABRIC, respectively) and IDC-NST (p = 1.1E-02 and p = 5.5E-08 in TCGA and METABRIC, respectively) (Figure 2B,C), and smaller tumors in IDC-NST only (p = 2.1E-02 and p = 6.3E-10 in TCGA and METABRIC, respectively) (Figure 2B,C). In METABRIC, KART positively associates with low-grade tumors in both the ILC and IDC-NST cohorts (p = 9.8E-03 and p = 6.7E-05) (Figure 2C). In short, we show that the KART signature associates with the histological subtype ILC, younger patients, lower-grade tumors in all breast cancers, and smaller tumor size in the histological group IDC-NST.

Details are in the caption following the image
The KART signature associates with the histological subtype ILC, with young patients, small tumors, and low- to intermediate-grade tumors. (A) Shown are the associations of normalized KART expression with IDC-NST and ILC in the TCGA (left) and METABRIC (right) datasets. All points are confirmed ERPOS and HER2NEG breast cancers. TCGA: IDC-NST n = 227; ILC n = 98. (B and C) Associations of normalized KART expression with clinicopathological features in breast cancer. Shown are violin plots for age, tumor size, and grading associations for IDC-NST (green bullets) and ILC (pink bullets) in the TCGA (B) and METABRIC (C) cohorts. All statistics were performed using the Wilcoxon signed-rank test.

Individual contributions of KART signature genes to clinical associations

To investigate how much individual KART genes contribute to breast cancer histological subtypes, we analyzed the expression of the separate genes associated with ductal or lobular diagnosis in the TCGA breast cancer dataset. From the nine most abundantly expressed KART genes, seven individual genes (TACSTD2, ERBB3, FOS, MYC, ID2, ALDH3B2, and CAMK2N1) are significantly associated with ILC (p ≤ 0.05), while expression levels of CCND1 and TMEM176B have no specific association with either IDC-NST or ILC (p ≥ 0.05) (Figure 3). In total, there are 22 upregulated genes within KART that contribute to the specific association with the histological subtype ILC (Figure 3 and supplementary material, Figure S2).

Details are in the caption following the image
Individual gene contributions to KART signature and their associations to ILC histological phenotype. Violin plots showing nine highest expressed genes within KART in TCGA database in IDC-NST (green bullets) and ILC (pink bullets), ranked on overall mRNA expression levels. The dashed blue lines represent the 97th percentile of the sequenced mRNA. Statistics were performed using the Wilcoxon signed-rank test.

KART expression correlates with stromal and immune expression signatures in breast cancer

Next, we investigated whether the KART signature correlates with specific known transcriptional signatures related to estrogen signaling, proliferation, and immunity [33, 35-39]. We defined correlations based on Spearman coefficients, where red squares represent anticorrelations and blue squares represent positive correlations, as previously described [48]. In TCGA, KART positively correlated with the stroma derived prognostic predictor (SDPP) and DCN.up stromal signatures (0.51 and 0.41), the Perez immune signature (0.58), and the PLAU invasion signature (0.41), and anticorrelates with ESR1 (−0.34) and AURKA proliferation signatures (−0.43) in IDC-NST (Figure 4 and supplementary material, Figure S3). Similar correlations were found in the METABRIC dataset, but with an additional correlation with the DCN stromal signature (0.49) (Figure 4). Anticorrelations with the ESR1 (−0.53) and AURKA (−0.49) modules were also noted for ILC in TCGA, while the SDPP stromal module (0.41) and the Perez immune module (0.53) positively correlated with KART for ILC (Figure 4 and supplementary material, Figure S3). In METABRIC, KART was anticorrelated with GGI grading (−0.5) while positively correlating with the DCN stroma signature for ILC (0.46) (Figure 4 and supplementary material, Figure S3). We then examined the correlations of the established LobSig signature [41] to the aforementioned signatures including KART. We found a uniform inverse correlation between KART and LobSig for both the TCGA (supplementary material, Figure S3A) and METABRIC datasets (supplementary material, Figure S3B). Overall, in both datasets, positive correlation for KART in invasion and immune signatures are linked to negative correlations for LobSig, whereas the negative correlations for KART with proliferation and estrogen signature are positively linked to LobSig (supplementary material, Figure S3).

Details are in the caption following the image
The KART signature positively correlates with stroma, invasion, and immune expression signatures and negatively with proliferation expression profiles. Condensed heat maps showing significant gene expression signature correlations for IDC-NST and ILC in the TCGA and METABRIC databases. Numbers inside squares represent Pearson coefficients. Red indicates negative correlations, blue represents positive correlations, white represents no significant association.

In short, KART correlates, independently of the histopathological subtype, with stromal, immune, and invasion signatures, but anticorrelated with proliferation, grading, and the estrogen receptor signature.

KART associates with a favorable DFS and OS in breast cancer

The association of the KART signature with the ILC histological type and the fact that ILC is a generally low-grade disease prompted us to assess whether KART was associated with favorable prognosis in breast cancer survival. We observed that KART was prognostic for improved DFS in the TCGA IDC-NST dataset in multivariable analyses (hazard ratio [HR] = 0.50, 95% CI = 0.23–1.09, p = 7.1E-03) (Figure 5A and supplementary material, Table S2) when considering KART expression around the median. The direction of this association was conserved for OS; however, significance was not reached (HR = 0.72, 95% CI = 0.28–1.81, p = 1.5E-01) (Figure 5B and supplementary material, Table S2). For ILC, higher KART expression was significantly associated with better prognosis in multivariable analyses for DFS in TCGA (HR = 0.18, 95% CI = 0.04–0.76, p = 2.5E-02) (Figure 5C and supplementary material, Table S2). This trend was also observed for OS in TCGA (HR = 0.10, 95% CI = 0.02–1.00, p = 7.6E-03) (Figure 5D and supplementary material, Table S2). In the METABRIC dataset, we found that higher KART expression associated with better OS in multivariable analyses for both the IDC-NST (HR = 0.79, 95% CI = 0.66–0.93, p = 1.2E-04) and the ILC (HR = 0.51, 95% CI = 0.29–0.91, p = 3.4E-02) cohorts (Figure 6A–C and supplementary material, Table S2). In short, we found that high KART expression predicted favorable prognosis for both DFS and OS in IDC-NST and ILC patients. When comparing KART to the performance of the LobSig signature, we again found an inverse association in both datasets. Interestingly, in contrast to KART, we found that high LobSig inversely associated with the histological ILC type when compared to KART, with a lower significance in TCGA (p = 8.3E-11 versus p = 1.1E-11) and METABRIC (p = 2.1E-05, versus p = 2.7E-07) (supplementary material, Figures S4A and S5A). Moreover, while high KART associates with good survival, high LobSig associates with poor survival in both the TCGA and METABRIC datasets (supplementary material, Figures S4B and S5B). Although LobSig showed a slightly stronger association with OS in ILC than KART in TCGA (HR = 6.94, 95% CI = 1.75–27.57, p = 1.7E-04, versus HR = 0.10, 95% CI = 0.01–0.68, p = 7.6E-03) and METABRIC (HR = 2.52, 95% CI = 1.55–4.09, p = 2.4E-04 versus HR = 0.44, 95% CI = 0.25–0.76, p = 3.4E-02), we observed an inverse but similar significance for OS and DFS between the two signatures (supplementary material, Figure S4B,C). Both LobSig and KART showed an association with DFS in ILC (HR = 5.02, 95% CI = 1.93–13.04, p = 1.8E-03 versus HR = 0.15, 95% CI = 0.04–0.62, p = 2.5E-02). In short, KART and LobSig showed inverse associations of similar significance with the main histological breast cancer types IDC-NST and ILC and clinicopathological parameters in TCGA and METABRIC datasets.

Details are in the caption following the image
KART expression correlates with DFS and OS for IDC-NST and ILC in TCGA dataset. (A–D) Kaplan–Meier graphs depicting DFS (A and C) and OS (B and D) for IDC-NST (A and B) or ILC patients respectively (C and D) regarding KART expression categorized around median with corresponding forest plots. Significant p values are depicted in bold. IDC-NST: n = 227 and ILC: n = 98.
Details are in the caption following the image
KART expression associates with long-term OS for IDC-NST and ILC in METABRIC dataset. (A and B) OS Kaplan–Meier curves for IDC-NST (A) and ILC (B) cohorts in METABRIC dataset regarding KART expression categorized around median with corresponding forest plots. Significant p values are depicted in bold. (C) Table depicting longitudinal patient numbers of the data shown in (A) and (B). IDC-NST: n = 979 and ILC: n = 118.

Discussion

The transcriptional modifier Kaiso has been implicated in cancer due to its role as a transcriptional regulator of genes such as CCND1 [19, 21], MYC [19], WNT11 [10, 20], MMP7 [46, 47], and ID2 [44]. In this study, we combined candidate and established Kaiso target genes that were either detected in the context of anchorage-independent mouse ILC cells or Kaiso targets that were functionally identified and verified. Interestingly, several canonical Kaiso targets (genes regulated through the cKBS consensus) from these studies play a role in the regulation of Wnt signaling. Both canonical and noncanonical Wnt targets are mostly associated with cellular differentiation, development, or specific functions of terminally differentiated cells. Examples are Rapsyn, a critical effector of acetylcholine receptor signals in the neuromuscular junction [49], and Wnt11, Cyclin D1, and Myc, which control a plethora of developmental and differentiation processes in breast and other tissues [50-53].

Although Cyclin D1 is essential for cell cycle progression, it is well known that high expression of Cyclin D1 is strongly associated with low-grade luminal-type breast cancers [54, 55]. Given that Cyclin D1 is the second most abundantly expressed cKBS target in all breast cancers, its high expression likely strongly contributes to our finding that KART is positively associated with better OS and DFS in breast cancer regardless of the histological type. The relatively weak individual contribution of Cyclin D1 to histological differentiation between IDC-NST and ILC also corroborates this assumption, although a study by Tobin et al indicated that low Cyclin D1 protein expression in ILC associated with improved outcome [56]. In contrast, ID2 showed a lower level of expression (ranked 7/33) but strongly associated with the ILC phenotype. These findings are in line with reports that link ID2 as an inhibitor of ILC cell proliferation while facilitating anoikis resistance, a hallmark of metastatic ILC [44, 57].

Concomitant high ID2 and Cyclin D1 expression in ILC [54, 56, 58, 59] might be explained by the finding that cytosolic ID2 functions as a CDK4/6 antagonist in ILC cells through binding to hypo-phosphorylated Rb and subsequent dampening of cell cycle progression [44]. In this context, ID2 functions as a CDK4/6 inhibitor, which potentially induces a compensatory upregulation of Cyclin D1. Because high Cyclin D1 expression levels mostly associate with favorable short-term prognosis in ILC [54] and CDK4/6 inhibitors induce an upregulation of Cyclin D1 in lobular-type breast cancer cell lines [60], we postulate that the Kaiso target ID2 may propel further compensatory upregulation of Cyclin D1 expression. This codependence may therefore partly underpin the observed associations of the KART signature with good prognosis and low proliferation in ILC.

Our work has identified ERBB3 as a cKBS Kaiso target gene. Interestingly, somatic oncogenic ERBB3 mutations have recently been linked to ILC by multiple studies [23, 41, 61, 62]. It is well established that loss of E-cadherin leads to autocrine activation of growth factor receptor signals [3, 4]. Since E-cadherin-dependent cell–cell adhesion inhibits activation of multiple receptor tyrosine kinases [3, 4, 63, 64] and ILC is a slow proliferating disease, we hypothesize that ERBB3 mostly propels pro-survival cues in ILC through PI3K/AKT. Because ERBB3 signaling depends on heterodimerization and activation through other ERBB family members [65, 66], it is tempting to speculate that the Kaiso target ERBB3 may conspire with low levels of ERBB2 to foster sustained AKT activation and subsequent anchorage independence in metastatic ILC.

Although ILC is unfortunately still mostly defined as a histomorphological breast cancer type, it has become evident that lobular carcinoma is in fact a unique entity within the breast cancer spectrum. Apart from the obvious phenotypical differences, multiple studies have shown that ILC presents a specific genomic and transcriptional landscape [23, 67-69] that drives a distinct biochemistry [3, 4, 6, 70, 71]. As a result, the identification of targetable oncological cues has instigated ILC-specific trials that require reproducible inclusion criteria for ILC. Interestingly, a recent multicenter concordance study showed that interobserver agreement for histological differential breast cancer diagnosis for ILC is moderate if no additional immunohistochemistry for E-cadherin status is provided [72]. Given the essential roles of E-cadherin loss within ILC etiology, we think that the KART signature represents a functional supportive tool that, on a biological basis and through unbiased selection and clinical associations, results in a better understanding of ILC biology and, potentially, future predictions regarding treatment responses.

To conclude, we present the cKBS KART, a novel 33-gene signature based on a combined set of functional and experimentally established, as well as candidate canonical Kaiso target genes. High KART expression associates with the ILC breast cancer type and is associated with improved long-term OS and DFS in IDC-NST and ILC.

Acknowledgements

We thank members of the Derksen, Desmedt, and Juliet laboratories for help and critical input. This work was made possible through financial support from the Netherlands Organization for Scientific Research (NWO/ZonMW-VIDI 016.096.318), the Dutch Cancer Society (KWF-UU-2011-5230, KWF-UU-2014-7201 and KWF-UU-2016-10456), and Breast Cancer Now (2018NovPCC1297). F.R. is funded by the Fonds voor Wetenschappelijk Onderzoek Vlaanderen (FWO: 1297322N). This publication is based upon work from COST Action LOBSTERPOT (CA19138), supported by COST (European Cooperation in Science and Technology). COST (European Cooperation in Science and Technology) is a funding agency for research and innovation networks https://www.cost.eu.

    Author contributions statement

    TS, MAKR, TK and PWBD, designed the study, performed experiments, and wrote the manuscript. BB and JD designed and performed the ChIP experiments and analysis. TK and CR performed biochemical experiments. FR and CD designed and performed bioinformatic analysis on breast cancer data. All authors read the manuscript and were given the opportunity to provide input.

    Data availability statement

    The METABRIC and TCGA data, including both clinical and gene expression data, can be found online on cBioPortal (https://www.cbioportal.org/study/summary?id=brca_metabric) and the GDC data portal (https://portal.gdc.cancer.gov/projects/TCGA-BRCA).