<figure><img src="image_1.png" /></figure>

HAL
open science

# RIP140 and LCoR expression in gastrointestinal cancers

Mouna Triki, Dorra Ben Ayed-Guerfali, Ines Saguem, Slim Charfi, Lobna Ayedi, Tahia Sellami-Boudawara, Vincent Cavaillès, Raja Mokdad-Gargouri

► To cite this version:

Mouna Triki, Dorra Ben Ayed-Guerfali, Ines Saguem, Slim Charfi, Lobna Ayedi, et al., RIP140 and LCoR expression in gastrointestinal cancers. *Oncotarget*, 2017, 8 (67), pp.111161-111175. 10.18632/oncotarget.22686. hal-02370376

HAL Id: hal-02370376

https://hal.umontpellier.fr/hal-02370376

Submitted on 8 Jun 2021

HAL is a multi-disciplinary open access
archive for the deposit and dissemination of sci-
entific research documents, whether they are pub-
lished or not. The documents may come from
teaching and research institutions in France or
abroad, or from public or private research centers.

L'archive ouverte pluridisciplinaire HAL, est
destinée au dépôt et à la diffusion de documents
scientifiques de niveau recherche, publiés ou non,
émanant des établissements d'enseignement et de
recherche français ou étrangers, des laboratoires
publics ou privés.

<figure><img src="image_2.png" /></figure>

Distributed under a Creative Commons Attribution 4.0 International License
# RIP140 and LCoR expression in gastrointestinal cancers

Mouna Triki<sup>1,2</sup>, Dorra Ben Ayed-Guerfali<sup>2</sup>, Ines Saguem<sup>3</sup>, Slim Charfi<sup>3</sup>, Lobna Ayedi<sup>3</sup>, Tahia Sellami-Boudawara<sup>3</sup>, Vincent Cavailles<sup>1,*</sup> and Raja Mokdad-Gargouri<sup>2,*</sup>

**Correspondence to:** Vincent Cavailles, email: vincent.cavailles@inserm.fr

**Keywords:** gastrointestinal cancer; RIP140; LCoR; immunohistochemistry; patient survival

**Received:** September 04, 2017

**Accepted:** November 05, 2017

**Published:** November 25, 2017

**Copyright:** Triki et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License 3.0 (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

## ABSTRACT

The transcription coregulators RIP140 and LCoR are part of a same complex which controls the activity of various transcription factors and cancer cell proliferation. In this study, we have investigated the expression of these two genes in human colorectal and gastric cancers by immunohistochemistry. In both types of tumors, the levels of RIP140 and LCoR appeared highly correlated. Their expression tended to decrease in colorectal cancer as compared to adjacent normal tissues but was found higher in gastric cancer as compared to normal stomach. RIP140 and LCoR expression correlated with TNM and tumor differentiation. Significant correlations were observed with expression levels of key proteins involved in tumor progression and invasion namely E-cadherin and Cyclooxygenase-2. Survival analysis showed that patients with LCoR<sup>low</sup>/RIP140<sup>high</sup> colorectal tumors have a significant prolonged overall and disease-free survival. In gastric cancer, high LCoR expression was identified as an independent marker of poor prognosis suggesting a key role in this malignancy. Altogether, these results demonstrate that RIP140 and LCoR have a prognostic relevance in gastrointestinal cancers and could represent new potential biomarkers in these tumors.

## INTRODUCTION

Gastrointestinal cancers (GICs) correspond to a diverse set of diseases of the gastrointestinal tract which include colorectal cancer (CRC) and gastric cancer (GC) and are among the most common human cancers [1]. Colorectal carcinogenesis relies on step-wise genetic events leading from early adenomatous lesions to invasive carcinomas and metastatic cancers [2]. Although chromosomal and microsatellite instability pathways constitute the major genetic alteration events in CRC [3][4], epigenetic alterations play a key role in the colorectal carcinogenesis [5]. The prognosis for CRC has been improved over the past decade, especially by treatment advances, but only about 30% of patients are

diagnosed at early stages, and the prognosis still poor for patients with advanced stage of the disease [3]. GCs account for over 70% of all cancers in developing countries [1] and are subdivided into two morphologically distinct groups corresponding to diffuse and intestinal cancers according to Lauren's classification [6]. The pathogenesis of GC is closely related to environmental factors particularly *Helicobacter pylori* infection [7], and genetic predisposition occurred in a subset of GC cases [8]. Because of the prognosis variability within a clinical or pathological stage of GC, it is significant to identify specific biological markers for a better management of patients with more aggressive behavior [9].

More recently, genome wide analyses have further characterized GIC heterogeneity by defining different

<footnote n="1"><sup>1</sup>IRCM (Institute of Cancer Research of Montpellier), INSERM U1194, Montpellier University, Montpellier, France</footnote>

<footnote n="2"><sup>2</sup>Center of Biotechnology of Sfax, Laboratory of Eukaryotic Molecular Biotechnology, Sfax University, Sfax, Tunisia</footnote>

<footnote n="3"><sup>3</sup>Department of Anatomopathology, Habib Bourguiba Hospital, Sfax, Tunisia</footnote>

<footnote>*These authors have to be considered as last co-authors</footnote>
molecular subtypes through common expression signatures [10]. More precisely, this allowed the identification of subgroups with expression of mesenchymal genes, extensive immune infiltration or metabolic dysregulation. In addition to these subtypes, both CRC and GC exhibit specific molecular subtypes with characteristic features linked to the tissue of origin. Such approaches might lead to the identification of novel molecular prognostic markers which could improve our understanding of the molecular mechanisms underlying GIC tumorigenesis.

Altered gene expression is a hallmark of cancer and the identification of factors which account for the dysregulation of transcriptional programs represent a key step in the understanding of cancer pathogenesis [11]. Transcription coactivators and corepressors are involved in the fine tuning of transcription factor activity and clearly participate in establishing new patterns of gene expression in cancer cells [12]. Amongst others, RIP140 (Receptor Interacting Protein of 140kDa) also called NRIP1 (Nuclear Receptor-Interacting Protein 1) and LCoR (Ligand-dependent CoRepressor) act mainly as transcriptional repressors of nuclear receptors and other transcription factors (for a review see [13]). These two transcription coregulators act by recruiting histone deacetylases and C-terminal binding proteins [14][15][16]. RIP140 and LCoR were both isolated in interaction with agonist- activated ERα [15][17]. However, in addition to ligand-activated nuclear receptors, they also interact with other transcription factors. For instance, LCoR interacts with Kruppel-like factor 6 (KLF6) [18] and KRAB-associated protein 1 (KAP1) [19], whereas RIP140 has been reported to bind and regulate E2Fs [20], NFKB [21] or β-catenin [22].

Several studies reported that the two transcription coregulators might play important roles in human cancers. RIP140 is required for mammary gland development [23] and regulates breast cancer cell proliferation and tumor progression [24]. Its strong impact on intestinal homeostasis and tumorigenesis has been unraveled using molecular and cellular approaches, transgenic mouse models and human CRC biopsies [25]. Interestingly, we recently reported that RIP140 directly interacted with LCoR and was necessary for LCoR inhibition of gene expression and cell proliferation [26]. Moreover, RIP140 and LCoR expression were strongly correlated in breast cancer cell lines and biopsies and correlated with overall survival of patients with breast cancer thus highlighting their strong interplay for the control of gene expression and cell proliferation in breast cancer cells. Finally, a very recent study confirmed the relevance of LCoR in breast cancer by demonstrating that it inhibits mammary cancer stem cells activity [27].

In this study, we investigated by immunohistochemistry (IHC) the expression of RIP140 and LCoR in CRC and GC. We showed that the levels of the two transcription factors were highly correlated in both tumors. Interestingly, whereas their expression tended to

decrease in CRC as compared to adjacent normal tissues, an increase of RIP140 and LCoR expression was noticed in GC as compared to normal stomach. RIP140 and LCoR expression were correlated with various clinicopathological parameters in CRC and/or GC including TNM stage and tumor differentiation. Moreover, in GICs, the expression of RIP140 and LCoR correlated with E-cadherin or COX-2 (Cyclooxygenase-2). Univariate and multivariate survival analyses indicated that high LCoR expression was an independent marker of poor prognosis in GC suggesting a key role in this malignancy.

## RESULTS

### Immunodetection of RIP140 and LCoR in gastrointestinal cancers

The expression of RIP140 and LCoR was evaluated by IHC in 102 and 41 specimens of CRC and GC, respectively. Representative examples of RIP140 and LCoR immunostaining are shown in Figure 1. Based on the immunostaining scores (IS), quantification of RIP140 and LCoR expression in CRC showed that RIP140 expression levels were high in 56.9%, moderate in 29.4% and low (negative or weak) in 13.7% of tumor tissues (Table 2A and Figure 1a-1f). Amongst the 102 CRC cases, only 99 gave a convincing LCoR IHC staining. Low LCoR expression was observed in most cases (54.5%) whereas 29.3%, and 16.2% of tumor tissues displayed intense or moderate LCoR immunostaining, respectively (Table 2A and Figure 1a-1f). In GC, the expression of RIP140 was intense in 80.5% of tumors while only 18 cases (43.9%) exhibited strong LCoR immunostaining (Table 2A and Figure 1g-11). When examining the expression of both transcription factors, tumors negative for both RIP140 and LCoR were not found frequent in CRC (1.8%) or GC (2.5%) (Table 2B). Most of the tumors expressed both RIP140 and LCoR with 12.4% and 19.5% of CRC and GC respectively harboring the maximal IS. Noticeably, a significant proportion of CRC (21%) and GC (10%) only exhibited RIP140 immunostaining (Table 2B).

Very interestingly, a strong positive association was observed between RIP140 and LCoR protein levels in both CRC and GC (Figure 2A-2C). Moreover, when we compared the expression of the two proteins in tumors with the adjacent normal tissues, we only observed a significant decrease for LCoR (Figure 3A). On the contrary, RIP140 and LCoR levels increase in GC as compared to adjacent normal tissues (p<0.011 p<0.001 respectively) (Figure 3B and Supplementary Figure 1).

### Association of RIP140 and LCoR with other proteins and with clinical parameters

We next asked whether the expression levels of RIP140 and/or LCoR were correlated with the expression
of other proteins previously quantified in the same cohorts of CRC and GC patients [28][29][30][31][32]. As shown in Table 3, in CRC and GC, RIP140 correlated positively with E-cadherin (p=0.049 and p=0.013, respectively) and COX-2 (p=0.021 and p=0.004, respectively). LCoR also associated with E-cadherin in GC (p=0.043) but was

inversely correlated in CRC (p=0.006). Finally, LCoR also correlated with p53 only in CRC (p=0.003) (Table 3).

Correlations of RIP140 and LCoR expression with clinical parameters in CRC and GC were summarized in Tables 4 and 5, respectively. In CRC, the only significant association with RIP140 expression was observed

<figure><img src="image_3.png" /><figcaption>**Figure 1:** Immunohistochemical staining of RIP140 and LCoR in GICs. Representative images for low, moderate and high nuclear IHC staining of RIP140 (a-c) and LCoR (d-f) in CRC specimen. Same in GC for low, moderate and high nuclear staining of RIP140 (g-i) and LCoR (j-l).</figcaption></figure>
<table><caption>**Table 1: Clinicopathological characteristics of CRC and GC patients**</caption><thead><tr><th>Variable</th><th>CRC (n=102)</th><th>GC (n=41)</th></tr></thead><tbody><tr><td><strong>Age</strong></td><td></td><td></td></tr><tr><td>≤60</td><td>39</td><td>19</td></tr><tr><td>>60</td><td>63</td><td>22</td></tr><tr><td><strong>Sex</strong></td><td>47</td><td></td></tr><tr><td><strong>Male</strong></td><td>55</td><td>22</td></tr><tr><td><strong>Differentiation</strong></td><td>61</td><td></td></tr><tr><td><strong>Poor</strong></td><td>37</td><td>21</td></tr><tr><td><strong>TNM stage</strong></td><td></td><td></td></tr><tr><td>I-II</td><td>41</td><td>2</td></tr><tr><td>III</td><td>42</td><td>10</td></tr><tr><td>IV</td><td>17</td><td>16</td></tr><tr><td><strong>Tumor site</strong></td><td></td><td></td></tr><tr><td>Colon</td><td>64</td><td>-</td></tr><tr><td>Rectum</td><td>37</td><td>-</td></tr><tr><td><strong>Anatomical site</strong></td><td></td><td></td></tr><tr><td>Antrum</td><td>-</td><td>23</td></tr><tr><td>Body</td><td>-</td><td>12</td></tr><tr><td>Cardia</td><td>-</td><td>4</td></tr><tr><td><strong>Tumor size</strong></td><td></td><td></td></tr><tr><td>≤5cm</td><td>53</td><td>3</td></tr><tr><td>>5cm</td><td>48</td><td>31</td></tr><tr><td><strong>Lymphovascular invasion</strong></td><td></td><td></td></tr><tr><td>Yes</td><td>32</td><td>9</td></tr><tr><td>No</td><td>67</td><td>32</td></tr><tr><td><strong>Histological type</strong></td><td></td><td></td></tr><tr><td>Intestinal</td><td>-</td><td>23</td></tr><tr><td>Diffuse</td><td>-</td><td>18</td></tr><tr><td><strong>H. pylori</strong></td><td></td><td></td></tr><tr><td>Positive</td><td>-</td><td>10</td></tr><tr><td>Negative</td><td>-</td><td>13</td></tr></tbody></table>

with TNM stage (p=0.027), whereas LCoR correlated significantly with age at diagnosis (p=0.019), tumor site (p=0.037) and differentiation (p=0.011). In GC, there were significant associations between RIP140 expression and TNM (p=0.001), tumor site (p=0.033), differentiation (p=0.005) and histotype (p=0.02), as

shown in Table 5. Indeed, all diffuse tumors showed high RIP140 expression as compared to tumors of the intestinal type which displayed negative to moderate expression of RIP140 in 34.8% of the cases. Similarly, 100% of poorly differentiated tumors displayed high RIP140 expression compared to 60% of moderate to well differentiated tumors. Regarding LCoR expression, the only significant association was observed with TNM stage (p=0.042).

## Association of RIP140 and LCoR expression with patient survival

In CRC, the overall survival (OS) and disease-free survival (DFS) data were available for 99 and 80 patients respectively. Among 102 patients, 37 (35.2%) died from their disease. The median OS and DFS were 39.88 and 39.38 months, respectively. Kaplan-Meier survival curves were generated based on RIP140 and LCoR expression (Figure 4). The OS and DFS were longer for patients with tumors displaying high levels of RIP140 (Figure 4A and 4B), nevertheless a statistical significance was reached only for OS (p=0.044, Figure 4A). On the contrary, LCoR appeared likely to be not related neither to OS nor DFS in CRC (p=0.213, p=0.943 respectively) (Figure 4C and 4D). Interestingly, in the group of patients showing low LCoR immunostaining, the correlations of RIP140 expression with OS and DFS were stronger than in the whole population (p=0.003 and p=0.014, respectively) (Figure 4E and 4F). In GC, RIP140 as well as LCoR expression were significantly associated to OS but in an opposite manner to what occurred in CRC. Indeed, low expression of RIP140 (IS 0-2) conferred a benefit in terms of OS (p=0.035; Figure 5A). Likewise, the OS rate was longer for patients exhibiting low expression of LCoR compared to those with tumors showing high LCoR immunostaining (p= 0.003, Figure 5B). Interestingly, the significance of the correlation with OS was higher when patients with RIP140<sup>low</sup>/LCoR<sup>low</sup> tumors were compared to the patients with RIP140<sup>high</sup>/LCoR<sup>high</sup> tumors (p= 0.006, Figure 5C).

## Univariate and multivariate analyses of outcome predictors

Next, we conducted univariate and multivariate analyses using a Cox proportional hazard model to examine associations between age, sex, tumor location, differentiation, TNM stage, lymphovascular invasion (LVI), tumor size, RIP140 or LCoR expression and OS in CRC (Table 6). In univariate analysis, TNM stage predicted shorter OS (p = 0.001; 95% CI= 1.44- 3.76). Furthermore, differentiation and LVI were also associated with OS (p = 0.011, 95% CI, 1.23-4.86, p=0.007; 95% CI=1.30-5.10, respectively). In multivariate analysis, TNM stage (p=0.002; 95% CI=1.38-4.30), LVI (p=0.043, 95% CI=1.03-5.30), tumor size (p=0.012, 95% CI=1.25-
<table><caption>Table 2: Expression of RIP140 and LCoR in GICs</caption><thead><tr><th colspan="2"></th><th colspan="3">RIP140</th><th colspan="3">LCoR</th></tr><tr><th colspan="2"></th><th>Low</th><th>Moderate</th><th>High</th><th>Low</th><th>Moderate</th><th>High</th></tr></thead><tbody><tr><th rowspan="2">CRC</th><th>n</th><td>14</td><td>30</td><td>58</td><td>55</td><td>17</td><td>30</td></tr><tr><th>%</th><td>13.7</td><td>29.4</td><td>56.9</td><td>54.5</td><td>16.2</td><td>29.3</td></tr><tr><th rowspan="2">GC</th><th>n</th><td>4</td><td>4</td><td>33</td><td>15</td><td>8</td><td>18</td></tr><tr><th>%</th><td>9.8</td><td>9.8</td><td>80.5</td><td>36.6</td><td>19.5</td><td>43.9</td></tr></tbody></table>

<table><thead><tr><th colspan="2"></th><th colspan="3">CRC</th><th colspan="3">GC</th></tr></thead><tbody><tr><th>RIP140</th><th>-</th><th>+</th><th>+</th><th>Max</th><th>-</th><th>+</th><th>+</th><th>Max</th></tr><tr><th>LCoR</th><th>-</th><th>-</th><th>+</th><th>Max</th><th>-</th><th>-</th><th>+</th><th>Max</th></tr><tr><th>n</th><td>3</td><td>34</td><td>104</td><td>20</td><td>1</td><td>4</td><td>27</td><td>9</td></tr><tr><th>%</th><td>1.8</td><td>21</td><td>64.5</td><td>12.4</td><td>2.5</td><td>10</td><td>67.5</td><td>19.5</td></tr></tbody></table>

6.3) and RIP140 expression (p=0.034, 95% CI=0.28-0.95) were independently related to OS after adjusting for age, sex, and LCoR expression (Table 6).

Although, the number of patients was small in GC (41 samples), univariate and multivariate analyses using a Cox proportional hazards model showed that some clinical parameters were related to patient survival (Table 7). Univariate analysis showed that age at diagnosis (p=0.025, 95% CI= 1.15-7.86), TNM stage (p=0.046, 95% CI= 1.02-6.95), expression of RIP140 (p=0.039, 95% CI= 1.05-7.16) and LCoR (p=0.006, 95% CI= 1.47-10.02) correlated significantly with OS, whereas only LCoR associated with OS in multivariate analysis (p=0.004, 95% CI=1.67-14.6).

## DISCUSSION

The role of RIP140 in colon tumor progression and its cross-talk with the Wnt/β-catenin signaling has been previously reported, together with its decreased expression in CRC and its correlation with good prognosis [25]. In the present study, we further decipher by IHC, the expression of RIP140 in colon carcinomas and analyzed, for the first time, the expression of the *LCOR* gene (recently identified as a RIP140 interactor and target gene) in this malignancy. This work is also the first study which analyzed the relevance of these two transcription factors in gastric cancer.

Our data first demonstrate a significant positive association between *RIP140* and *LCOR* gene expression both in colon and gastric cancers (Figure 2). This is in perfect line with a recent study showing that the expression of the two genes were highly correlated in breast cancer cells and tumors [26]. Recently, the same observation has been made in cervical cancers (U Jeschke, unpublished observations). It thus appears that *RIP140* and *LCOR* gene

expression is strongly correlated in different cancer types. In breast cancer cells, it was demonstrated that RIP140 was able to transactivate the *LCOR* gene promoter [26]. In GICs, the exact mechanisms which account for the correlation remain unknown but preliminary experiments using luciferase reporter assays in colon and gastric cancer cell lines indicate that RIP140 exerts a positive effect on *LCOR* gene transcription (S. Jalaguier and M. Triki, unpublished observations).

The present study also showed that both *RIP140* and *LCoR* gene expression is deregulated in GICs (Figure 3). The IHC staining for both RIP140 and LCoR decreased in colorectal tumors as compared to adjacent normal tissue which is, for RIP140, in agreement with a previous study [25]. On the contrary, in GC significant higher levels of RIP140 and LCoR proteins were detected in tumors compared to adjacent normal tissues. RIP140 overexpression in GC was confirmed by reanalyzing the GDS1210 transcriptomic data available on the GEO profile database [33] (see Supplementary Figure 2). In breast cancers, RIP140 and LCoR mRNA expression were also found significantly higher in breast tumor samples as compared to normal mammary glands [26]. The difference in the patterns of *RIP140* and *LCOR* gene expression in CRC compared to GC may reflect the complexity by which the two genes are regulated both at the transcriptional and post-translational levels. Several studies have reported data concerning the regulation of RIP140 expression and post-translational modifications [34][35] whereas little is known concerning *LCOR* gene regulation in cancer cells and tissues.

It should be noted that RIP140 is engaged in several transcriptional regulatory feed-back loops involving nuclear receptors or E2F1. The regulation of RIP140 (and possibly LCoR) gene expression by these transcription
factors could be at the basis of their differential expression in GC vs CRC. Moreover, the regulation by other signaling pathways (including Wnt, Notch, Hippo and others) might also participate in these normal vs cancer dysregulations.

Regarding the prognosis relevance of RIP140 and LCoR in CRC and GC, Kaplan Meier plots showed that

high expression of RIP140 conferred a benefit in terms of OS and DFS in CRC patients (Figure 4A and 4B), which is concordant with a previous study [25]. Although the expression of the two genes was strongly correlated, it appeared that LCoR expression was rather associated with poor prognosis in CRC. In line with this observation,

<figure><img src="image_4.png" /><figcaption>**Figure 2:** Association between RIP140 and LCoR expression in colorectal and gastric cancers. (A) The correlations between RIP140 and LCoR IS have been analyzed in CRC and GC as described in Material and methods using SPSS. The correlation coefficient and *p* values are indicated. (B) Boxplot representation showing the significant association between LCoR expression in groups with low (L) and high (H) RIP140 expression in CRCs (*p* = 0.009). (C) Same representation in GC biopsies (*p* = 0.0007).</figcaption></figure>

<figure><img src="image_5.png" /><figcaption>**Figure 3:** Expression of RIP140 and LCoR in tumoral and adjacent normal mucosa. RIP140 (left panel) and LCoR (right panel) protein expression were quantified in twenty-three tumoral tissues and adjacent normal mucosa from colorectal (A) and gastric (B) biopsies. All correlations were performed using the nonparametric Mann-Whitney *U* test. Boxplots show the median and interquartile range (box) and the 10-90 percentiles (whiskers).</figcaption></figure>
<table><caption>Table 3: Correlation between RIP140 and LCoR with other proteins in CRC and GC</caption><thead><tr><th rowspan="2">Proteins</th><th colspan="2">CRC</th><th colspan="2">GC</th></tr><tr><th>RIP140</th><th>LCoR</th><th>RIP140</th><th>LCoR</th></tr></thead><tbody><tr><td>β-catenin</td><td>p=0.104<br>r=0.078</td><td>p=0.43<br>r=0.07</td><td>p=0.204<br>r=0.06</td><td>p=0.749<br>r=-0.101</td></tr><tr><td>E-cadherin</td><td>p=0.049<br>r=0.167</td><td>p=0.006<br>r=-0.23</td><td>p=0.013<br>r=0.222</td><td>p=0.043<br>r=0.32</td></tr><tr><td>APC</td><td>p=0.614<br>r=-0.051</td><td>p=0.231<br>r=-0.056</td><td>p=0.251<br>r=0.046</td><td>p=0.68<br>r=0.065</td></tr><tr><td>P53</td><td>p=0.203<br>r=0.118</td><td>p=0.003<br>r=0.254</td><td>p=0.756<br>r=-0.229</td><td>p=0.438<br>r=0.121</td></tr><tr><td>COX-2</td><td>p=0.021<br>r=0.206</td><td>p=0.359<br>r=-0.083</td><td>p=0.004<br>r=0.281</td><td>p=0.425<br>r=0.125</td></tr></tbody></table>

<table><caption>Table 4: Association between RIP140 and LCoR and clinicopathological features in colorectal cancer</caption><thead><tr><th rowspan="2">Parameters</th><th rowspan="2">n (102)</th><th colspan="3">RIP140</th><th colspan="3">LCoR</th></tr><tr><th>Low n (%)</th><th>Moderate n (%)</th><th>High n (%)</th><th>n (99)</th><th>Low n (%)</th><th>Moderate n (%)</th><th>High n (%)</th></tr></thead><tbody><tr><td>Gender</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Male</td><td>47</td><td>6(12.8)</td><td>16(34)</td><td>25(53.2)</td><td>45</td><td>25(55.6)</td><td>8(17.8)</td><td>12(26.7)</td></tr><tr><td>Female</td><td>55</td><td>8(14.5)</td><td>14(25.5)</td><td>33(60)</td><td>54</td><td>29(53.7)</td><td>8(14.8)</td><td>17(31.5)</td></tr><tr><td>p-value</td><td></td><td>0.637</td><td></td><td></td><td></td><td>0.842</td><td></td><td></td></tr><tr><td>Age</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>≤60</td><td>39</td><td>3(7.7)</td><td>15(38.5)</td><td>21(53.8)</td><td>38</td><td>19(50)</td><td>11(28.9)</td><td>8(21.1)</td></tr><tr><td>>60</td><td>63</td><td>11(17.5)</td><td>15(23.8)</td><td>37(58.7)</td><td>61</td><td>35(57.4)</td><td>5(8.2)</td><td>21(34.4)</td></tr><tr><td>p-value</td><td></td><td>0.171</td><td></td><td></td><td></td><td>0.019</td><td></td><td></td></tr><tr><td>TNM-stage</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>I-II</td><td>41</td><td>2(4.9)</td><td>16(39)</td><td>23(56.1)</td><td>40</td><td>23(57.5)</td><td>5(12.5)</td><td>12(30)</td></tr><tr><td>III</td><td>42</td><td>6(14.3)</td><td>10(23.8)</td><td>26(61.9)</td><td>42</td><td>20(47.6)</td><td>7(16.7)</td><td>15(35.7)</td></tr><tr><td>IV</td><td>17</td><td>6(35.3)</td><td>3(17.6)</td><td>8(47.1)</td><td>17</td><td>11(64.7)</td><td>4(23.5)</td><td>2(11.8)</td></tr><tr><td>p-value</td><td></td><td>0.027</td><td></td><td></td><td></td><td>0.4</td><td></td><td></td></tr><tr><td>Tumor site</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Colon</td><td>65</td><td>9(14.1)</td><td>16(25)</td><td>39(60)</td><td>64</td><td>38(59.4)</td><td>6(9.4)</td><td>20(31.3)</td></tr><tr><td>Rectum</td><td>37</td><td>5(13.5)</td><td>13(35.1)</td><td>19(51.4)</td><td>34</td><td>15(44.1)</td><td>10(29.4)</td><td>9(26.5)</td></tr><tr><td>p-value</td><td></td><td>0.544</td><td></td><td></td><td></td><td>0.037</td><td></td><td></td></tr><tr><td>Differentiation</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Poor</td><td>61</td><td>6(9.8)</td><td>20(32.8)</td><td>35(57.4)</td><td>60</td><td>37(61.7)</td><td>8(13.3)</td><td>15(25)</td></tr><tr><td>Moderate</td><td>37</td><td>7(18.9)</td><td>8(21.6)</td><td>23(59.5)</td><td>37</td><td>17(45.9)</td><td>6(16.2)</td><td>14(36.8)</td></tr><tr><td>Well</td><td>2</td><td>1(50)</td><td>1(50)</td><td>0(0)</td><td>2</td><td>0(0)</td><td>2(100)</td><td>0(0)</td></tr><tr><td>p-value</td><td></td><td>0.22</td><td></td><td></td><td></td><td>0.011</td><td></td><td></td></tr><tr><td>Tumor size</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>T≤5 cm</td><td>53</td><td>11(16.4)</td><td>20(29.9)</td><td>36(53.7)</td><td>50</td><td>35(54.7)</td><td>10(15.6)</td><td>19(29.7)</td></tr><tr><td>T>5 cm</td><td>48</td><td>3(8.8)</td><td>10(29.4)</td><td>21(61.8)</td><td>48</td><td>19(55.9)</td><td>6(17.6)</td><td>9(26.5)</td></tr><tr><td>p-value</td><td></td><td>0.549</td><td></td><td></td><td></td><td>0.936</td><td></td><td></td></tr></tbody></table>
<table><caption>Table 5: Association between RIP140, and LCoR and clinicopathological features in gastric cancer</caption><thead><tr><th rowspan="2">Parameters</th><th rowspan="2">n (41)</th><th colspan="3">RIP140</th><th rowspan="2">n (41)</th><th colspan="3">LCoR</th></tr><tr><th>Low n (%)</th><th>Moderate n (%)</th><th>High n (%)</th><th>Low n (%)</th><th>Moderate n (%)</th><th>High n (%)</th></tr></thead><tbody><tr><td>Gender</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Male</td><td>22</td><td>3(13.6)</td><td>2(9.1)</td><td>17(77.3)</td><td>22</td><td>9(40.9)</td><td>4(18.2)</td><td>9(40.9)</td></tr><tr><td>Female</td><td>19</td><td>1 (5.3)</td><td>2(10.5)</td><td>16(84.2)</td><td>19</td><td>6(31.6)</td><td>4(21.1)</td><td>9(47.4)</td></tr><tr><td>p-value</td><td></td><td>0.665</td><td></td><td></td><td></td><td>0.829</td><td></td><td></td></tr><tr><td>Age</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>≤60</td><td>19</td><td>3(15.8)</td><td>1(5.3)</td><td>15(78.9)</td><td>19</td><td>7(36.8)</td><td>4(21.1)</td><td>8(42.1)</td></tr><tr><td>>60</td><td>22</td><td>1(4.5)</td><td>3(13.6)</td><td>18(81.8)</td><td>22</td><td>8(36.4)</td><td>4(18.2)</td><td>10(45.5)</td></tr><tr><td>p-value</td><td></td><td>0.356</td><td></td><td></td><td></td><td>0.966</td><td></td><td></td></tr><tr><td>TNM-stage</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>I-II</td><td>2</td><td>0(0)</td><td>2(100)</td><td>0(0)</td><td>2</td><td>2(100)</td><td>0(0)</td><td>0(0)</td></tr><tr><td>III</td><td>10</td><td>1(10)</td><td>0(0)</td><td>9(90)</td><td>10</td><td>5(50)</td><td>3(30)</td><td>2(20)</td></tr><tr><td>IV</td><td>16</td><td>2(12.5)</td><td>1(6.3)</td><td>13(81.3)</td><td>16</td><td>2(12.5)</td><td>4(25)</td><td>10(62.5)</td></tr><tr><td>p-value</td><td></td><td>0.001</td><td></td><td></td><td></td><td>0.042</td><td></td><td></td></tr><tr><td>Tumor site</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Antrum</td><td>23</td><td>7(30.4)</td><td>4(17.4)</td><td>12(52.2)</td><td>22</td><td>9(40.9)</td><td>4(18.2)</td><td>9(40.9)</td></tr><tr><td>Body</td><td>12</td><td>0(0)</td><td>6(50)</td><td>6(50)</td><td>12</td><td>1(8.3)</td><td>3(25)</td><td>8(66.7)</td></tr><tr><td>Cardia</td><td>4</td><td>1(25)</td><td>3(75)</td><td>0(0)</td><td>4</td><td>3(75)</td><td>1(25)</td><td>0(0)</td></tr><tr><td>p-value</td><td></td><td>0.033</td><td></td><td></td><td></td><td>0.094</td><td></td><td></td></tr><tr><td>Differentiation</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Poor</td><td>21</td><td>0(0)</td><td>0(0)</td><td>21(100)</td><td>21</td><td>6(28.6)</td><td>3(14.3)</td><td>12(57.1)</td></tr><tr><td>Moderate-Well</td><td>20</td><td>4(20)</td><td>4(20)</td><td>12(60)</td><td>20</td><td>9(45)</td><td>5(25)</td><td>6(30)</td></tr><tr><td>p-value</td><td></td><td>0.005</td><td></td><td></td><td></td><td>0.215</td><td></td><td></td></tr><tr><td>Histotype</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Intestinal</td><td>23</td><td>4(17.4)</td><td>4(17.4)</td><td>15(62.5)</td><td>23</td><td>11(47.8)</td><td>5(21.7)</td><td>7(30.4)</td></tr><tr><td>Diffuse</td><td>18</td><td>0(0)</td><td>0(0)</td><td>18(100)</td><td>18</td><td>4(22.2)</td><td>3(16.7)</td><td>11(61.1)</td></tr><tr><td>P-value</td><td></td><td>0.02</td><td></td><td></td><td></td><td>0.128</td><td></td><td></td></tr><tr><td>HP</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Negatif</td><td>13</td><td>3(23.1)</td><td>4(30.8)</td><td>6(46.2)</td><td>13</td><td>7(53.8)</td><td>3(23.1)</td><td>3(23.1)</td></tr><tr><td>Positif</td><td>10</td><td>2(20)</td><td>3(30)</td><td>5(50)</td><td>10</td><td>1(10)</td><td>3(30)</td><td>6(60)</td></tr><tr><td>p-value</td><td></td><td>0.979</td><td></td><td></td><td></td><td>0.074</td><td></td><td></td></tr><tr><td>Tumor size</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>T≤5 cm</td><td>3</td><td>0(0)</td><td>0(0)</td><td>3(100)</td><td>3</td><td>0(0)</td><td>1(33.3)</td><td>2(66.7)</td></tr><tr><td>T>5 cm</td><td>31</td><td>3(9.7)</td><td>2(6.5)</td><td>26(83.9)</td><td>31</td><td>12(38.7)</td><td>6(19.4)</td><td>13(41.9)</td></tr><tr><td>p-value</td><td></td><td>0.753</td><td></td><td></td><td></td><td>0.407</td><td></td><td></td></tr></tbody></table>
A

<figure><img src="image_6.png" /></figure>

B

<figure><img src="image_7.png" /></figure>

C

<figure><img src="image_8.png" /></figure>

D

<figure><img src="image_9.png" /></figure>

E

<figure><img src="image_10.png" /></figure>

F

<figure><img src="image_11.png" /></figure>

**Figure 4:** RIP140 and LCoR as prognosis markers in colorectal cancers. Kaplan-Meier curves based on the levels of RIP140 (A-B) and LCoR (C-D) were drawn for OS (A and C) and DFS (B and D) on a cohort of 102 CRC patients. The same curves were drawn for OS (E) and DFS (F) taking into account both RIP140 and LCoR expression. The *p* values were calculated using the log-rank test and are indicated.

A

<figure><img src="image_12.png" /></figure>

B

<figure><img src="image_13.png" /></figure>

C

<figure><img src="image_14.png" /></figure>

**Figure 5:** RIP140 and LCoR as a prognosis marker in gastric cancers. Kaplan-Meier curves for overall survival (OS) in GC patients according to RIP140 (A), LCoR (B) or both RIP140 and LCoR (C) expression in a cohort of 41 GC patients. The *p* values were calculated using the log-rank test and are indicated.
<table><caption>Table 6: Univariate and multivariate Cox proportional hazard analysis of overall survival in CRC</caption><thead><tr><th rowspan="3">Variables</th><th rowspan="3">n</th><th colspan="4">OS</th></tr><tr><th colspan="2">Univariate</th><th colspan="2">Multivariate</th></tr><tr><th>HR (95%CI)</th><th>p</th><th>HR (95%CI)</th><th>p</th></tr></thead><tbody><tr><td>Age</td><td></td><td></td><td>0.208</td><td></td><td>0.064</td></tr><tr><td>&lt;60</td><td>39</td><td>1.00</td><td></td><td>1.00</td><td></td></tr><tr><td>≥60</td><td>63</td><td>1.58 (0.77-3.26)</td><td></td><td>2.1 (0.96-4.61)</td><td></td></tr><tr><td>Sex</td><td></td><td></td><td>0.796</td><td></td><td>0.753</td></tr><tr><td>Male</td><td>47</td><td>1.00</td><td></td><td>1.00</td><td></td></tr><tr><td>Female</td><td>55</td><td>1.09 (0.55-2.16)</td><td></td><td>1.13 (0.53-2.42)</td><td></td></tr><tr><td>Tumor site</td><td></td><td></td><td>0.352</td><td></td><td>0.067</td></tr><tr><td>Colon</td><td>65</td><td>1.00</td><td></td><td>1.00</td><td></td></tr><tr><td>Rectum</td><td>37</td><td>1.39 (0.69-2.78)</td><td></td><td>2.12 (0.95-4.71)</td><td></td></tr><tr><td>Differentiation</td><td></td><td></td><td>0.011</td><td></td><td>0.638</td></tr><tr><td>Moderate-Well</td><td>39</td><td>1.00</td><td></td><td>1.00</td><td></td></tr><tr><td>Poor</td><td>61</td><td>2.44 (1.23-4.86)</td><td></td><td>1.25 (0.49-3.24)</td><td></td></tr><tr><td>TNM</td><td></td><td></td><td>0.001</td><td></td><td>0.002</td></tr><tr><td>I-II</td><td>41</td><td>1.00</td><td></td><td>1.00</td><td></td></tr><tr><td>III-IV</td><td>59</td><td>2.33 (1.44-3.76)</td><td></td><td>2.44 (1.38-4.30)</td><td></td></tr><tr><td>LVI</td><td></td><td></td><td>0.007</td><td></td><td>0.043</td></tr><tr><td>No</td><td>67</td><td>1.00</td><td></td><td>1.00</td><td></td></tr><tr><td>Yes</td><td>32</td><td>2.57 (1.30-5.10)</td><td></td><td>2.33 (1.03-5.30)</td><td></td></tr><tr><td>Tumor size</td><td></td><td></td><td>0.327</td><td></td><td>0.012</td></tr><tr><td>&lt;5cm</td><td>53</td><td>1.00</td><td></td><td>1.00</td><td></td></tr><tr><td>≥5cm</td><td>48</td><td>1.42 (0.71-2.84)</td><td></td><td>2.81 (1.25-6.3)</td><td></td></tr><tr><td>RIP140</td><td></td><td></td><td>0.073</td><td></td><td>0.034</td></tr><tr><td>Low</td><td>44</td><td>1.00</td><td></td><td>1.00</td><td></td></tr><tr><td>Mod-High</td><td>58</td><td>0.58 (0.32-1.05)</td><td></td><td>0.51 (0.28-0.95)</td><td></td></tr><tr><td>LCoR</td><td></td><td></td><td>0.416</td><td></td><td>0.103</td></tr><tr><td>Low</td><td>70</td><td>1.00</td><td></td><td>1.00</td><td></td></tr><tr><td>Mod-High</td><td>29</td><td>1.17 (0.8-1.72)</td><td></td><td>1.41 (0.93-2.12)</td><td></td></tr></tbody></table>

Abbreviations: OS, overall survival; HR, hazard ratio; CI, confidence interval; CRC, colorectal cancer; LVI, lympho vascular invasion.

we noticed that the association of RIP140 expression with both OS and DFS of CRC patients was stronger in tumors expressing low levels of LCoR (Figure 4E and 4F). It has been reported that the two transcription factors could interact and act synergistically [26]. The present data may indicate that, in CRC cells, LCoR could rather antagonize RIP140 activity.

Some of the molecular mechanisms controlling tumorigenesis and involving RIP140 have been elucidated for breast and colon cancers. In breast cancer, both *in vitro* and *in vivo* studies indicate that RIP140 exerts direct transcriptional control on signaling pathways including nuclear receptors and E2F transcription factors (for a review see [36]). In colon cancer, RIP140 interferes with
<table><caption>Table 7: Univariate and multivariate Cox proportional hazard analysis of overall survival in GC</caption><thead><tr><th rowspan="3">Variables</th><th rowspan="3">n</th><th colspan="4">OS</th></tr><tr><th colspan="2">Univariate</th><th colspan="2">Multivariate</th></tr><tr><th>HR (95%CI)</th><th>p</th><th>HR (95%CI)</th><th>p</th></tr></thead><tbody><tr><td>Age</td><td></td><td></td><td>0.025</td><td></td><td>0.227</td></tr><tr><td>&lt;60</td><td>19</td><td>1.00</td><td></td><td>1.00</td><td></td></tr><tr><td>&ge;60</td><td>22</td><td>3.01 (1.15-7.86)</td><td></td><td>1.93 (0.66-5.63)</td><td></td></tr><tr><td>Sex</td><td></td><td></td><td>0.796</td><td></td><td>0.526</td></tr><tr><td>Male</td><td>22</td><td>1.00</td><td></td><td>1.00</td><td></td></tr><tr><td>Female</td><td>19</td><td>1.12 (0.47-2.71)</td><td></td><td>0.71 (0.25-2.02)</td><td></td></tr><tr><td>Histotype</td><td></td><td></td><td>0.766</td><td></td><td>0.834</td></tr><tr><td>Intestinal</td><td>23</td><td>1.00</td><td></td><td>1.00</td><td></td></tr><tr><td>Diffus</td><td>18</td><td>0.87 (0.36-2.13)</td><td></td><td>0.84 (0.16-4.37)</td><td></td></tr><tr><td>Differentiation</td><td></td><td></td><td>0.592</td><td>1.00</td><td>0.604</td></tr><tr><td>Moderate-Well</td><td>20</td><td>1.00</td><td></td><td>1.00</td><td></td></tr><tr><td>Poor</td><td>21</td><td>1.27 (0.52-3.10)</td><td></td><td>0.75 (0.25-2.21)</td><td></td></tr><tr><td>TNM</td><td></td><td></td><td>0.046</td><td></td><td>0.941</td></tr><tr><td>I-II</td><td>2</td><td>1.00</td><td></td><td>1.00</td><td></td></tr><tr><td>III-IV</td><td>26</td><td>2.65 (1.02-6.95)</td><td></td><td>0.94 (0.20-4.36)</td><td></td></tr><tr><td>RIP140</td><td></td><td></td><td>0.039</td><td></td><td>0.679</td></tr><tr><td>Low</td><td>22</td><td>1.00</td><td></td><td>1.00</td><td></td></tr><tr><td>Mod-High</td><td>19</td><td>2.74 (1.05-7.16)</td><td></td><td>0.60 (0.05-6.77)</td><td></td></tr><tr><td>LCoR</td><td></td><td></td><td>0.006</td><td></td><td>0.004</td></tr><tr><td>Low</td><td>25</td><td>1.00</td><td></td><td>1.00</td><td></td></tr><tr><td>Mod-High</td><td>16</td><td>3.84 (1.47-10.02)</td><td></td><td>4.94 (1.67-14.6)</td><td></td></tr></tbody></table>

Abbreviations: OS, overall survival; HR, hazard ratio; CI, confidence interval; GC, gastric cancer. A backward elimination with threshold of P=0.6 was to select variables in the final models.

<figure><img src="image_15.png" /><figcaption>Figure 6: Scheme comparing the expression and prognosis value of RIP140 and LCoR in CRC and GC. The variations of RIP140 and LCoR expression in tumoral tissue as compared to normal mucosa are shown by arrows for CRC and GC. The prognostic value (bad or good) of RIP140 and LCoR expression is also shown. Significant correlations are marked with asterisks (*=p≤0.05, **=p≤0.01, ***=p≤0.001).</figcaption></figure>
the Wnt/β-catenin pathway through positive regulation of
the tumor suppressor gene APC which in turn drives the
degradation of β-catenin [25]. It should be noticed that
no correlations between RIP140 and APC expression
were observed in the CRC cohort used in this study
(See Table 3) suggesting that the relationship between
RIP140 and the Wnt/β-catenin might be complex and that
further investigations are needed to better elucidate this
connection.

The difference in the correlation with survival of RIP140 and LCoR in CRC compared to GC may reflect the different contribution of the two transcriptional coregulators to tumor development and progression in these epithelia. Very interestingly, RIP140 associated positively with E-cadherin in CRC whereas LCoR exhibited a significant negative correlation (Table 3). E-cadherin is a transmembrane glycoprotein which plays an important role in maintaining the structural integrity of epithelial sheets [37]. The loss of E-cadherin expression has been reported in several GIC including advanced colorectal carcinomas [29][30][37].

Interestingly, experiments used to silence the expression of E-cadherin not only showed a morphological shift from an epithelial to a fibroblastoid phenotype, characteristic of EMT, but also a concomitant increase in invasive cell behavior [38]. The loss of E-cadherin has been considered to increase cellular dissemination and tumor metastasis. The different correlation of RIP140 and LCoR with E-cadherin expression may therefore suggest different roles on CRC metastasis and represent a clue to explain their correlation with good and bad prognosis, respectively.

Concerning GC, the ways RIP140 and LCoR are involved in the development and progression of this malignancy remain to elucidate. It could be hypothesized that other signaling pathways besides Wnt/β-catenin could be involved and might include, for instance, the Hippo pathway [39]. Interestingly, our data indicated a positive association between RIP140 and COX-2 both in CRC and GC (Table 3) suggesting a relationship between these two proteins involved in inflammation, as previously reported [40]. In GC, high expression of RIP140 (alone or in combination with LCoR *ie* RIP140<sup>high</sup>/LCoR<sup>high</sup> tumors) correlated with shorter OS rate in strong opposition with what was observed in CRC. To emphasize these results, we reanalyzed public datasets of GC using the Kaplan Meier plotter (http://kmplot.com) which allows meta-analysis based biomarker assessment using a background database which is manually curated [41]. This confirmed that both RIP140 and LCoR expression were significantly correlated with poor prognosis in GC patients (see Supplementary Figure 3). This difference in survival prognosis in CRC and GC is in perfect accordance with the opposite dysregulation of their expression between normal and tumoral epithelium in the two malignancies (see Figure 3 and Figure 6). Finally, the most important observation is that RIP140 and LCoR appeared as independent predictors

of patient survival in multivariate analyses, RIP140 being
a marker of good prognosis in CRC whereas LCoR is
a marker of poor prognosis in GC (Tables 6 and 7). In
conclusion, our data demonstrate that the expression of
RIP140 and LCoR have a prognostic relevance in GICs
and could represent new potential biomarkers or targets in
these tumors.

MATERIALS AND METHODS

Patients and tumor samples

We obtained a total of 189 tissue specimens from 143 patients including 125 colorectal tissues (102 cancers and 23 matched normal surgical margins) and 64 stomach tissues (41 cancers and 23 matched normal surgical margins). These samples were collected at the Department of Digestive Surgery of the Habib Bourguiba University Hospital (Sfax, Tunisia) from 1995 to 2012. All patients gave informed consent prior to specimen collection according to institutional guidelines. None of the patients had pre-operative or post-operative chemotherapy. Patient information were obtained from medical records and included age, gender, differentiation grade, tumor site, size and stage, histological type and *H. pylori* infection (Table 1). The histological subtypes were classified according to criteria of the World Health Organization. The tumors were staged according to the TNM (tumor, lymph node and metastases) classification adopted by the American Joint Committee on Cancer [42]. The median follow-up period was 38 months (0-96 months) for CRC patients and 9 months (0-29 months) for GC patients. Follow-up data on survival rate was available for all cases of GC and only in 96 cases of CRC.

Immunohistochemical staining

The samples obtained at surgery were routinely fixed in 10% neutral buffered formalin and embedded in paraffin. Before immunostaining, two pathologists (LA, SC) reviewed haematoxylin and eosin-stained slides in order to select blocks representing invasive adenocarcinoma. For each selected tumor, 4-µm sections attached on poly-L-lysine-coated slides were fixed in acetone for 10 min, and left to dry overnight at 37 °C. Slides were deparaffinized in xylene followed by subsequent rehydration in graded ethanol. The sections were then pre-treated with 3% hydrogen peroxide for 10 min to inactivate endogenous peroxides and washed in phosphate-buffered saline (PBS) solution. Heat-induced antigen retrieval was performed using epitope retrieval solution (Dako) at 95 °C for 40 min. After heating, slides were allowed to cool down to room temperature and were briefly washed with PBS. Blocking solution (Dako) was used for 5 min to block the non-specific binding of antibodies. Immunohistochemical staining
was performed using the streptavidin–biotin peroxidase
system (RE7280-K, Leica Biosystems). Tissue sections
were incubated overnight with the primary antibody
against RIP140 (ab42124, Abcam) or for 30 min with the
anti- LCoR antibody (ab48339, Abcam). Primary antibody
binding was visualized with biotin- labeled secondary
antibodies (Novolink Polymer, Leica Biosystems) and a
streptavidin– peroxidase complex using diaminobenzidine
as a chromogenic substrate (RE7280-K, Leica
Biosystems). Stainings with the other antibodies directed
against APC (adenomatous polyposis coli), β-catenin, p53,
COX-2 and E-cadherin were described elsewhere for the
same CRC [28][29] and GC biopsies [30][31][32].

Immunostaining scoring

Immunostainings were scored on the basis of
the percentage of positive tumor cells and the relative
immunostaining intensity [43]. The initial scoring was
graded according to the extent of immunostaining as
follows: 0, no staining or less than 5% of tumor cells
labelled; 1, 5-25% staining; 2, 25-75% staining; 3, 75-
100% staining. The staining intensity was evaluated as
follows: 0, negative; 1, low; 2, moderate; and 3, high. The
final score was determined by multiplying the intensity
of positivity and the extent of immunostaining yielding
an immunoscore (IS) that ranged from 0 to 12. The
immunostaining was determined as positive or negative
by a cutoff value. RIP140 and LCoR were interpreted as
low (IS: ≤2), moderate (IS>2 and ≤ 4) and high (IS> 4).

Statistical analysis

Statistical analyses were performed using the
SPSS 20.0 statistical software for Windows (SPSS
Inc., IBM). Chi2 test was used to correlate the IS with
clinicopathological features. Survival was estimated
using the Kaplan-Meier method and log-rank test.
Cox proportional hazard regression models were
used to determine univariate and multivariate HRs.
Statistical analysis and graphs were performed using the
nonparametric Mann–Whitney U test with GraphPad
Prism 7.0 (Ritme Informatique). Data are expressed as
boxplots showing the median and interquartile range
.box
(Box)
and the 10–90 percentiles (whiskers). Statistical
differences were assumed significant for p < 0.05 for both
tests.

Abbreviations

Adenomatous polyposis coli, APC; confidence
interval, CI; colon cancer, CRC; disease free survival,
DFS; epithelial mesenchymal transition, EMT;
gastric cancer, GC; gastrointestinal cancer, GIC;
immunohistochemistry, IHC; immunoscore, IS; Kruppel-
like factor 6, KLF6; KRAB-associated protein 1, KAP1;
ligand dependent corepressor, LCoR; lymphovascular

invasion, LVI; overall survival, OS; phosphate-buffered
saline, PBS; receptor interacting protein of 140 kDa,
RIP140; tumor, lymph node and metastases, TNM.

Author contributions

VC and RMG conceived and supervised the
project. MT and VC wrote the paper. MT performed most
experiments, with the help ofDBG and IS. RMG, MT and
VC contributed to manuscript writing and editing. SC, LA,
TSB provided the samples and the related clinical data. All
authors read and approved the final manuscript.

ACKNOWLEDGMENTS

We thank Ilhem Benbraik for technical help. We are
also grateful to Dr Stéphan Jalaguier for critical reading
of the manuscript.

CONFLICTS OF INTEREST

The authors declare that they have no competing
interests. We confirm that the authors have full control of
all primary data and agree that the journal is allowed to
review these data if requested.

FUNDING

This work was supported by the PHC UTIQUE
(grant number 16G0805), Fondation pour la Recherche
Médicale (DEQ20170336713), Institut National de la
Santé et de la Recherche Médicale and University of
Montpellier.

REFERENCES

1. Torre LA, Bray F, Siegel RL, Ferlay J, Lortet-Tieulent J, Jemal A. Global cancer statistics, 2012. CA Cancer J Clin. 2015; 65:87–108. https://doi.org/10.3322/caac.21262.

2. Fearon ER, Vogelstein B. A genetic model for colorectal tumorigenesis. Cell. 1990; 61:759–67.

3. Smith RA, Cokkinides V, Eyre HJ. American Cancer Society guidelines for the early detection of cancer, 2006. CA Cancer J Clin. 2006; 56:11–25; quiz 49–50.

4. Chung DC. The genetic basis of colorectal cancer: insights into critical pathways of tumorigenesis. Gastroenterology. 2000; 119:854–65.

5. Lengauer C, Kinzler KW, Vogelstein B. Genetic instability in colorectal cancers. Nature. 1997; 386:623–7. https://doi.org/10.1038/386623a0.

6. Panani AD. Cytogenetic and molecular aspects of gastric cancer: clinical implications. Cancer Lett. 2008; 266:99–115. https://doi.org/10.1016/j.canlet.2008.02.053.

7. Wang J, Chi DS, Kalin GB, Sosinski C, Miller LE, Burja I, Thomas E. Helicobacter pylori infection and oncogene
expressions in gastric carcinoma and its precursor lesions.
Dig Dis Sci. 2002; 47:107-13.

8. Cisco RM, Norton JA. Hereditary diffuse gastric cancer: surgery, surveillance and unanswered questions. Future Oncol. 2008; 4:553-9. https://doi.org/10.2217/14796694.4.4.553.

9. Yasui W, Oue N, Ito R, Kuraoka K, Nakayama H. Search for new biomarkers of gastric cancer through serial analysis of gene expression and its clinical implications. Cancer Sci. 2004; 95:385-92.

10. Bijlsma MF, Sadanandam A, Tan P, Vermeulen L. Molecular subtypes in cancers of the gastrointestinal tract. Nat Rev Gastroenterol Hepatol. 2017. https://doi.org/10.1038/nrgastro.2017.33.

11. Bradner JE, Hnisz D, Young RA. Transcriptional addiction in cancer. Cell. 2017; 168:629-43. https://doi.org/10.1016/j.cell.2016.12.013.

12. Battaglia S, Maguire O, Campbell MJ. Transcription factor co-repressors in cancer biology: roles and targeting. Int J Cancer. 2010; 126:2511-9. https://doi.org/10.1002/ijc.25181.

13. White JH, Fernandes I, Mader S, Yang XJ. Corepressor recruitment by agonist-bound nuclear receptors. Vitam Horm. 2004; 68:123-43.

14. Castet A, Boulaitouf A, Versini G, Bonnet S, Augereau P, Vignon F, Khochbin S, Jalaguier S, Cavailles V. Multiple domains of the Receptor-Interacting Protein 140 contribute to transcription inhibition. Nucleic Acids Res. 2004; 32:1957-66.

15. Fernandes I, Bastien Y, Wai T, Nygard K, Lin R, Cormier O, Lee HS, Eng F, Bertos NR, Pelletier N, Mader S, Han VK, Yang XJ, et al. Ligand-dependent nuclear receptor corepressor LCoR functions by histone deacetylase-dependent and -independent mechanisms. Mol Cell. 2003; 11:139-50.

16. Palijan A, Fernandes I, Bastien Y, Tang L, Verway M, Kourelis M, Tavera-Mendoza LE, Li Z, Bourdeau V, Mader S, Yang XJ, White JH. Function of histone deacetylase 6 as a cofactor of nuclear receptor coregulator LCoR. J Biol Chem. 2009; 284:30264-74. https://doi.org/10.1074/jbc.M109.045526.

17. Cavailles V, Dauvois S, L'Horset F, Lopez G, Hoare S, Kushner PJ, Parker MG. Nuclear factor RIP140 modulates transcriptional activation by the estrogen receptor. EMBO J. 1995; 14:3741-51.

18. Calderon MR, Verway M, An BS, DiFeo A, Bismar TA, Ann DK, Martignetti JA, Shalom-Barak T, White JH. Ligand-dependent corepressor (LCoR) recruitment by Kruppel-like factor 6 (KLF6) regulates expression of the cyclin-dependent kinase inhibitor CDKN1A gene. J Biol Chem. 2012; 287:8662-74. https://doi.org/10.1074/jbc.M111.311605.

19. Calderon MR, Verway M, Benslama RO, Birlea M, Bouttier M, Dimitrov V, Mader S, White JH. Ligand-dependent

corepressor contributes to transcriptional repression by C2H2 zinc-finger transcription factor ZBRK1 through association with KRAB-associated protein-1. Nucleic Acids Res. 2014; 42:7012-27. https://doi.org/10.1093/nar/gku413.

20. Docquier A, Harmand PO, Fritsch S, Chanrion M, Darbon JM, Cavaillès V. The transcriptional coregulator RIP140 represses E2F1 activity and discriminates breast cancer subtypes. Clin Cancer Res. 2010; 16:2959-70. https://doi.org/10.1158/1078-0432.CCR-09-3153.

21. Zschiedrich I, Hardeland U, Krones-Herzig A, Berriel Diaz M, Vegiopoulos A, Müggenburg J, Sombroek D, Hofmann TG, Zawatzky R, Yu X, Gretz N, Christian M, White R, et al. Coactivator function of RIP140 for NFkappaB/RelA-dependent cytokine gene expression. Blood. 2008; 112:264-76. https://doi.org/10.1182/blood-2007-11-121699.

22. Zhang D, Wang Y, Dai Y, Wang J, Suo T, Pan H, Liu H, Shen S, Liu H. Downregulation of RIP140 in hepatocellular carcinoma promoted the growth and migration of the cancer cells. Tumour Biol. 2014. https://doi.org/10.1007/s13277-014-2815-y.

23. Nautiyal J, Steel JH, Mane MR, Oduwole O, Poliandri A, Alexi X, Wood N, Poutanen M, Zwart W, Stingl J, Parker MG. The transcriptional co-factor RIP140 regulates mammary gland development by promoting the generation of key mitogenic signals. Development. 2013; 140:1079-89. https://doi.org/10.1242/dev.085720.

24. Aziz MH, Chen X, Zhang Q, DeFrain C, Osland J, Luo Y, Shi X, Yuan R. Suppressing NRIP1 inhibits growth of breast cancer cells in vitro and in vivo. Oncotarget. 2015; 6:39714-24. https://doi.org/10.18632/oncotarget.5356.

25. Lapierre M, Bonnet S, Bascoul-Mollevi C, Ait-Arsa I, Jalaguier S, Del Rio M, Plateroti M, Roepman P, Ychou M, Pannequin J, Hollande F, Parker M, Cavailles V. RIP140 increases APC expression and controls intestinal homeostasis and tumorigenesis. J Clin Invest. 2014; 124:1899-913. https://doi.org/10.1172/JCI65178.

26. Jalaguier S, Teyssier C, Nait Achour T, Lucas A, Bonnet S, Rodriguez C, Elarouci N, Lapierre M, Cavaillès V. Complex regulation of LCoR signaling in breast cancer cells. Oncogene. 2017. https://doi.org/10.1038/onc.2017.97.

27. Celià-Terrassa T, Liu DD, Choudhury A, Hang X, Wei Y, Zamalloa J, Alfaro-Aco R, Chakrabarti R, Jiang YZ, Koh BI, Smith HA, DeCoste C, Li JJ, et al. Normal and cancerous mammary stem cells evade interferon-induced constraint through the miR-199a-LCOR axis. Nat Cell Biol. 2017; 19:711-23. https://doi.org/10.1038/ncb3533.

28. Abdelmaksoud-Damak R, Miladi-Abdennadher I, Triki M, Khabir A, Charfi S, Ayadi L, Frikha M, Sellami-Boudawara T, Mokdad-Gargouri R. Expression and mutation pattern of β-catenin and adenomatous polyposis coli in colorectal cancer patients. Arch Med Res. 2015; 46:54-62. https://doi.org/10.1016/j.arcmed.2015.01.001.

29. Miladi-Abdennadher I, Abdelmaksoud-Dammak R, Ayed-Guerfali DB, Ayadi L, Khabir A, Amouri A, Frikha F, Tahri
N, Ellouz S, Frikha M, Sellami-Boudawara T, Mokdad-Gargouri R. Expression of COX-2 and E-cadherin in Tunisian patients with colorectal adenocarcinoma. Acta Histochem. 2012; 114:577-81. https://doi.org/10.1016/j. acthis.2011.11.002.

30. Ayed-Guerfali DB, Hassairi B, Khabir A, Sellami-Boudawara T, Gargouri A, Mokdad-Gargouri R. Expression of APC, β-catenin and E-cadherin in Tunisian patients with gastric adenocarcinoma: clinical significance. Tumour Biol. 2014; 35:1775-83. https://doi.org/10.1007/s13277-013-1236-7.

31. Ayed DB, Khabir A, Abid M, Bayrouti MI, Gargouri A, Sellami-Boudawara T, Mokdad-Gargouri R. Clinicopathological and prognostic significance of p53, Ki-67, and Bcl-2 expression in Tunisian gastric adenocarcinomas. Acta Histochem. 2014; 116:1244-50. https://doi.org/10.1016/j.acthis.2014.07.008.

32. Ben Ayed-Guerfali D, Charfi S, Khabir A, Sellami-Boudawara T, Gargouri A, Mokdad-Gargouri R. Clinical and prognosis relevance of COX-2 expression in Tunisian patients with primary gastric adenocarcinoma. Cancer Biomark. 2016; 17:67-73. https://doi.org/10.3233/ CBM-160618.

33. Hippo Y, Taniguchi H, Tsutsumi S, Machida N, Chong JM, Fukayama M, Kodama T, Aburatani H. Global gene expression analysis of gastric cancer by oligonucleotide microarrays. Cancer Res. 2002; 62:233-40.

34. Augereau P, Badia E, Carascossa S, Castet A, Fritsch S, Harmand PO, Jalaguier S, Cavaillès V. The nuclear receptor transcriptional coregulator RIP140. Nucl Recept Signal. 2006; 4:e024. https://doi.org/10.1621/nrs.04024.

35. Mostaqul Huq MD, Gupta P, Wei LN. Post-translational modifications of nuclear co-repressor RIP140: a therapeutic target for metabolic diseases. Curr Med Chem. 2008; 15:386-92.

36. Lapierre M, Docquier A, Castet-Nicolas A, Gitenay D, Jalaguier S, Teyssier C, Cavaillès V. The emerging role

of the transcriptional coregulator RIP140 in solid tumors. Biochim Biophys Acta. 2015; 1856:144-50. https://doi.org/10.1016/j.bbcan.2015.06.006.

37. Wijnhoven BP, Dinjens WN, Pignatelli M. E-cadherin-catenin cell-cell adhesion complex and human cancer. Br J Surg. 2000; 87:992-1005. https://doi.org/10.1046/j.1365-2168.2000.01513.x.

38. Thiery JP. Epithelial-mesenchymal transitions in tumour progression. Nat Rev Cancer. 2002; 2:442-54. https://doi.org/10.1038/nrc822.

39. Kang W, Cheng AS, Yu J, To KF. Emerging role of Hippo pathway in gastric and other gastrointestinal cancers. World J Gastroenterol. 2016; 22:1279-88. https://doi.org/10.3748/wjg.v22.i3.1279.

40. Ho PC, Tsui YC, Feng X, Greaves DR, Wei LN. NF-κB-mediated degradation of the coactivator RIP140 regulates inflammatory responses and contributes to endotoxin tolerance. Nat Immunol. 2012; 13:379-86. https://doi.org/10.1038/ni.2238.

41. Györffy B, Lanczky A, Eklund AC, Denkert C, Budczies J, Li Q, Szallasi Z. An online survival analysis tool to rapidly assess the effect of 22,277 genes on breast cancer prognosis using microarray data of 1,809 patients. Breast Cancer Res Treat. 2010; 123:725-31. https://doi.org/10.1007/s10549-009-0674-9.

42. Greene FL, Stewart AK, Norton HJ. A new TNM staging strategy for node-positive (stage III) colon cancer: an analysis of 50,042 patients. Ann Surg. 2002; 236:416-21; discussion 421. https://doi.org/10.1097/01.SLA.0000029243.59219.7E.

43. Krajewska M, Krajewski S, Epstein JI, Shabaik A, Sauvageot J, Song K, Kitada S, Reed JC. Immunohistochemical analysis of bcl-2, bax, bcl-X, and mcl-1 expression in prostate cancers. Am J Pathol. 1996; 148:1567-76.