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Article

Downregulation of ORP3 Correlates with Reduced Survival of Colon Cancer Patients with Advanced Nodal Metastasis and of Female Patients with Grade 3 Colon Cancer

by
Pengfei Xu
1,
Julia Richter
1,
Annette Blatz
1,
Fabian Gärtner
1,
Roland Alberts
1,
Anca Azoitei
2,
Wycliffe Arika Makori
2,
Sabine Meessen
2,
Uwe Knippschild
1,* and
Cagatay Günes
2,*
1
Department of General and Visceral Surgery, Surgery Center, Ulm University Hospital, 89081 Ulm, Germany
2
Department of Urology, Surgery Center, Ulm University Hospital, 89081 Ulm, Germany
*
Authors to whom correspondence should be addressed.
Int. J. Mol. Sci. 2020, 21(16), 5894; https://doi.org/10.3390/ijms21165894
Submission received: 13 July 2020 / Revised: 12 August 2020 / Accepted: 13 August 2020 / Published: 16 August 2020
(This article belongs to the Special Issue Biological Interfaces in Gastrointestinal Cancer)
Browse Figures
Versions Notes

Abstract

:
Genome instability is an essential hallmark in tumor development, including colorectal cancer. We have recently identified the oxysterol binding protein-related protein 3 (ORP3), also known as oxysterol binding protein-like 3 (OSBPL3), as a novel ploidy-control gene, whose knock-out leads to aneuploidy induction and promotes tumor formation, indicating that ORP3 is a bona fide tumor suppressor protein. Here we analyzed expression of ORP3 in a cohort (n = 206) of colon cancer patients in relation to patient survival. We show that low ORP3 mRNA levels correlate with reduced survival of patients with advanced nodal metastasis (N2). While patient survival does not associate with grading when the whole cohort is evaluated, importantly, low ORP3 mRNA levels associate with worse survival of female patients with grade 3 colon cancer. Similarly, low ORP3 mRNA levels associate with worse survival of grade 3 colon cancer patients 70 years of age and younger while low ORP3 mRNA levels seem to be beneficial for colon cancer patients with a T2 tumor size. Together, the data show that ORP3 expression is downregulated during colon cancer progression, which correlates with reduced patient survival. Thus, ORP3 mRNA levels may be a prognostic marker for better stratification of colon cancer patients.

1. Introduction

Colorectal cancer (CRC) characterized as a multifactorial and heterogeneous disease is the third most common cancer worldwide and the second deadliest in malignancy [1]. Several environmental components, as well as genetic risk factors, are known to be associated with CRC [2,3,4,5]. Whereas 75% are sporadic cases, 20% of the cases have a family history of CRC, and 3–5% of CRCs are hereditary, characterized by germline mutations linked to cancer-predisposition syndromes, among them the Lynch syndrome (1–3%) and familiar adenomatous polyposis (FAP) [6,7]. Especially, chromosomal instability, mismatch repair, and hypermethylation contribute to CRC development and progression. While chromosomal instability results in an unbalanced equilibrium between oncogenes and tumor suppressors, deficiency of deoxyribonucleic acid (DNA) mismatch repair (dMMR), especially of the Mut L homolog1 (MLH1) or the Mut S homolog 2 (MSH2), contributes to an increase of errors within the genome and DNA hypermethylation and can lead to the reactivation or silencing of genes, among them proto-oncogene B-raf (BRAF) and MLH1 [8,9,10,11]. Defective dMMR finally results in a strong mutator phenotype, indicated by microsatellite instability (MSI), which drives tumorigenesis. In MSI-driven tumorigenesis of CRC, positively, as well as negatively, selected driver gene mutations have been identified [12,13]. Approximately, 15% of CRC show high microsatellite instability (MSI-H) due to germline mutations in genes involved in DNA mismatch repair or somatic inactivation of the same signal pathway, often induced through hypermethylation of MLH1. Although it has been shown that, MSI-H CRCs represent a heterogeneous group, they exhibit several unique biologic characteristics when compared to microsatellite stable (MSS) colon cancer [14,15,16,17,18]. They all share some distinct histologic cancer features with high amounts of tumor-infiltrating lymphocytes [19]. In addition, Lynch syndrome patients exhibit a high risk of synchronous or metachronous tumors [20]. Prognostically, patients with hereditary non-polyposis colorectal cancer (HNPCC) have an increased overall survival compared to stage-matched sporadic CRCs [21,22].
The cancer stage at the time of diagnosis is most important for prognosis underlined by the fact that CRC patients with a localized stage exhibit a five-year survival rate of 90 % whereas the five-year survival rate of patients with metastasis amounts to 11%. Surgery, as well as chemotherapy, are still the most common treatment options for CRC. Although therapy improvements contributed to prolonged median survival for CRC patients, the prognosis for patients with advanced stages is still not satisfactory due to high apoptotic resistance and metastatic potential of their tumors. Therefore, there is a high interest to identify new targets for drug development for personalized therapy concepts with enhanced selectivity, efficacy, and reduced toxicity. In this context, Oxysterol binding protein-related protein 3 (ORP3), also referred to as oxysterol binding protein-like 3 (OSBPL3), could serve as a new target for drug development underlined by the finding that ORP3 expression correlates with benefits from a lomustine (CCNU)/bevacizumab combination treatment in a specific molecular subtype of gliomoblastoma [23]. This study provides evidence for a potential benefit of patient stratification using ORP3 as a molecular marker.
ORP3 is a cytosolic lipid-binding/transfer protein that is targeted to the plasma membrane by its pleckstrin–homology (PH) domain, while its FFAT motif (two phenylalanine in an acidic tract) targets it to the endoplasmic reticulum (ER) [24,25,26]. Previous studies revealed ORP’s function as scaffolds for the protein phosphatases, protein phosphatase 2 (PP2A), and haematopoetic protein tyrosine kinase (HePTP), regulating the activity of extracellular signal-regulated kinases (ERK), thereby indicating a role of ORPs in tumor cell signaling [27]. Members of this family have been shown to impact cell migration and adhesion. ORP3 was shown to interact with R-Ras [25,26], and to regulate cell adhesion [25]. Increasing evidence indicates putative roles of ORP family members in cancer [28,29]; this is summarized in [30]. However, direct analysis of its potential role in cancer has not been conducted. Recently, we have identified a role of ORP3 in ploidy-control [31]. Although the exact mechanisms how ORP3 contributes to ploidy-control is yet to be elucidated, we could show that knock-down or loss of ORP3 induced genome instability and promoted tumorigenesis in vitro and in vivo, respectively [31,32]. Importantly, Orp3 knockout mice develop B-cell lymphoma indicating a tumor suppressor function of ORP3 [32].
Since a role of ORP3 in colon cancer has not been addressed in detail so far, its role for survival of colon patients was characterized in the present study. The evaluation of the whole colon cancer cohort (n = 206) indicates that low ORP3 mRNA levels associate with worse survival of patients with advanced nodal metastasis (N2). While patient survival does not associate with grading when the whole cohort is evaluated, importantly, low ORP3 mRNA levels associate with worse patient survival in female patients with grade 3 colon cancer. Similarly, low ORP3 mRNA levels associate with worse survival of grade 3 colon cancer patients under 70 years, while low ORP3 mRNA levels seem to be beneficial for colon cancer patients with T2 tumor size.
In summary, in colon cancer, high ORP3 levels may serve as a survival marker in combination with N2 status. In addition, there is a significant association for better survival for females and patients under 70 years with higher ORP3 mRNA levels among grade 3 colon cancer patients.

2. Results

2.1. ORP3 mRNA Levels Are Downregulated in Colon Cancer

To test the possible relevance of the newly identified ploidy-control gene ORP3 for colon cancer we firstly aimed to determine its mRNA levels in a set of matched normal and tumor samples of 44 colon patients (31 males and 13 females) with a median age of 65 years (minimum: 29 years/maximum: 93 years). Whereas the group sizes of the different UICC stages are almost similar (UICC I:5, UICC II: 13, UICC III: 12, and UICC IV: 14), distribution by gender and tumor grade (grade 2:33, grade 3:9, grade 4:2) resulted in dissimilar groups. Box plot analysis of ORP3 mRNA levels of these 44 patients revealed that ORP3 expression is statistically significant downregulated in tumor samples in comparison to matched normal tissue (p = 0.0001) (Figure 1).

2.2. Significance of ORP3 mRNA Levels for Patient’s Survival

To evaluate the significance of ORP3 mRNA levels for patients’ survival we used a cohort of CRC patients (n = 206, Table 1, see Materials and Methods for details) and determined ORP3 mRNA levels by RT-qPCR. Patients were recruited constitutively in the time period from 2003 until 2014.

2.3. Description of Study Population

The clinical and histopathological parameters of the colon cancer patient cohort are listed in Table 1. Altogether, 206 colon cancer patients (110 males, 96 females) with a median age of 70.41 years (range 29.81–89.67 years) and a median survival of 48.12 months (range 0.33–175.49 months) were considered in all analyses. Whereas gender ratio, group sizes of Union for International Cancer Control (UICC) stages, as well as ratios of tumors with and without invasion to lymph nodes are nearly similar within the respective subgroups, distribution by tumor grade leads to dissimilar groups with 135 patients in grade 2 group and 54 patients in grade 3 group, whereas grade 1 and 4 groups only encompasses 12, and 5 patients, respectively.
The ratio of metastasizing tumors to non-metastasizing tumors is 1:2.6. There are no statistically significant differences regarding median ORP3 RNA levels within groups of gender, histological grade, tumor localization, and lymph node invasion (p = 0.666, p = 0.323, p = 0.878, p = 0.789, respectively; Table 1). Whereas the detected differences in ORP3 RNA levels in the different UICC stages did not reach statistical significance (p = 0.055), the differences within the metastasis groups were statistically significant (p = 0.033). Furthermore, statistically significant differences in the median age of the patients were detected for the follow up (p = 0.001), the tumor localization (p = 0.014) and the lymph node groups (p = 0.032). Furthermore, the median survival for the follow-up (p = 0.001), the UICC stage (p = 0.001), the lymph nodes (p = 0.001) and metastasis (p = 0.001) groups were significantly different (Table 1).
This univariate analysis of the cancer patients’ cohort shows an influence of several parameters on patient’s survival. Due to the multivariate nature of this data set, a cox proportional-hazards analysis was conducted to cope with the potential of several covariables potentially affecting the prognosis of the patient (Figure 2). The multivariate analysis excludes the two patients with carcinoma in situ (CIS), ending up with n = 204. Additionally, the factor “expression level of ORP3” was introduced based on an expression threshold of the median ORP3 RNA expression (RQ = 0.0082). This median was used to subdivide the samples into low (RQ < 0.0082) and high (RQ ≥ 0.0082) expression of ORP3. Furthermore, the patient’s cohort was tested for correlation between the different variables. The focus was put on correlation between the gene level of ORP3 and N status, T status, grade and age. However none of the parameters age (correlation coefficient = 0.092, p = 0.187), N status (correlation coefficient = −0.015, p = 0.829), T status (correlation coefficient = −0.030, p = 0.669), and grade (correlation coefficient = 0.059, p = 0.397) correlates with the level of ORP3 (Figure S3).

2.4. Survival Analysis in Relation to ORP3 mRNA Levels

Kaplan–Meier survival analyses were performed to evaluate the relevance of ORP3 RNA levels for patient’s survival, comparing their survival rates with low and high ORP3 RNA levels in the tumor samples.
There was no significant difference in patient’s survival in relation to ORP3 mRNA levels for the entire cohort (p = 0.881; Figure 3A). However, patients with grade 3 tumors expressing high ORP3 mRNA levels showed significantly higher survival rates compared to patients with low ORP3 mRNA levels (p = 0.020, Figure 3B). Importantly, patient´s survival was gender specific. Whereas high ORP3 mRNA levels in grade 3 tumors significantly correlated with better survival rate of females, this was not the case for males with grade 3 tumors with high ORP3 mRNA levels (females: p = 0.014, males: p = 0.516) (Figure 3C,D). Similarly, patient´s survival reached a higher significance when ORP3 mRNA levels were analyzed in correlation to age-dependent survival rates of grade 3 patients. There is an age-specific survival benefit among the grade 3 group with high ORP3 mRNA levels. Whereas patients below 70 years with grade 3 tumors and high ORP3 RNA levels had significantly better overall survival (p = 0.008), no statistically significant correlation between ORP3 mRNA levels and overall survival of over 70 years old patients was detected (p = 0.563) (Figure 3E,F). Of note, ORP3 mRNA levels of grade 2 patients did not significantly correlate with patient survival (Supplementary Figure S1). No predication for patient´s survival in correlation to ORP3 mRNA levels was possible for patients with grade 1 and grade 4 tumors due to low group numbers (n = 12 and n = 5, respectively). Similarly, there was no significant correlation between ORP3 mRNA levels and patient´s survival in relation to the different UICC stages, UICC I (p = 0.218), UICC II (p = 0.198), UICC III (p = 0.798) and UICC IV (p = 0.988), respectively (Supplementary Figure S2).
A hazard ratio was also calculated for the whole cohort using a cox proportional-hazards analysis. The graphical evaluation as well as the calculated values show that the mRNA expression level of ORP3 is not a predictive gene for the survival of the patient, if the whole patients’ cohort is analyzed. However, several other factors like high age and metastasis turn out to a risk for the patient´s survival. These results are in accordance with the univariate analysis depicted in Table 1. Importantly, however, the prognostic feature of ORP3 mRNA levels for patient survival was confirmed by a multivariate analysis and cox proportional-hazards analysis when patients with grade 3 tumor were evaluated (Figure 4).
The multivariate analysis of the data set presented in Figure 4, containing only patients with a grade 3 tumor confirms the results acquired with a univariate analysis (Figure 3B). Patients with a grade 3 tumor and a low expression of ORP3 mRNA (RQ < 0.0082) show a 3.05 times higher risk of death. The calculated values for each parameter are shown in the Supplementary Table S1.
Another interesting observation was made when ORP3 levels were analyzed in correlation to lymph-node metastasis in the whole group. Importantly, patients classified as N2 nodal metastasis with high ORP3 mRNA levels had significantly better survival rates in comparison to patients with low ORP3 mRNA levels (p = 0.015), whereas ORP3 mRNA levels did not impact survival of patients of the N0 (p = 0.173) and N1 subgroups (p = 0.995) (Figure 5). Of note, there are no sex-specific differences among the groups (see legend to Figure 5).
On the other hand, reduced ORP3 mRNA levels seemed to be beneficial for the survival of patients with small tumor size: while patients, whose tumor size was classified as T2, had significantly increased survival rates when ORP3 RNA levels were low (p = 0.044) (Figure 6). No significant correlation between ORP3 mRNA levels and survival rates of patients with T3 and T4 tumors could be observed. These differences were not sex-specific (see legend to Figure 3).

3. Discussion

The incidence and progression of colon cancer in humans has been shown to result from accumulation of genetic changes, accompanied by chromosomal instability (CIN). CIN, mostly characterized by increased aneuploidy, is a hallmark of cancer cells that goes along with the acquisition of defects in chromosomal segregation, by deregulated expression of various oncogenes and tumor suppressor factors and mutations in DNA damage response genes. However, the full composition of genes underlying aneuploidy remains incompletely described and the exact molecular mechanisms of carcinogenesis in colon carcinomas are still not fully understood. In addition, patient stratifications using molecular and histological markers are required for more efficient therapy of patients with colon cancer. In the current study, we addressed the potential impact of ORP3 on colon cancer to evaluate the prognostic benefit based on complete long-term follow-up data regarding tumor progression and overall survival. ORP3 was identified in a genetic screen as a novel ploidy-control gene and its down-regulation induced aneuploidy and promotes tumor formation [31,32].
The role of ORP3 in colon cancer has not been addressed in detail so far. Of note, a recent study which combines proteomic and genomic analysis on colon cancer [33] revealed deregulation of ORP3 in 6.6% of colon cancer patients (4.72% mutations and 1.89% amplifications), as determined by the cBio Cancer Genomics Portal [34,35], supporting the idea that ORP3 may contribute to colon cancer initiation and/or progression. The molecular mechanisms how ORP3 may contribute to colon cancer remain to be elucidated. Interestingly, it was shown that the nuclear receptor, the liver receptor homologue 1, a member of nuclear receptor of subfamily 5 group A (LRH-1 or NR5A2), which acts upstream of ORP3 in liver hepatocytes and promotes non-alcoholic fatty liver disease by activating de novo lipogenesis via ORP3 [36], is a novel prognostic marker in colon cancer patients [37,38,39]. Although a direct regulation of ORP3 by LRH-1/NR5A2 in colon cancer was not demonstrated so far, it is conceivable to assume that ORP3 expression may be modulated by LRH-1/NR5A2 during colon cancer initiation and/or progression.
The measured values of ORP3 mRNA expression in the tumor tissue describe a snapshot at the time of diagnosis after primary oncological resection. The study shows that patients with advanced lymph node metastasis (N2) and low ORP3 mRNA levels exhibit reduced survival probability compared to patients of the same group but high ORP3 mRNA levels. Moreover, in female patients and patients under 70 years of age with grade 3 tumors, high ORP3 mRNA levels correlate with an increased overall survival. On the other hand, high ORP3 levels correlate with worse survival in combination with smaller tumor size (T2) in colon cancer. In summary, our data show clear evidence that the altered expression of ORP3 may be involved in the pathogenesis and progression of colon cancer. These data are in line with the potential tumor suppressive function of ORP3. Of note, ORP3 was shown to interact with R-Ras, a Ras-related cell signaling factor, which controls Ras signaling that is known to be one of the most often deregulated pathways in colon cancer [13,40,41,42]. In fact, we demonstrated that loss of ORP3 expression activates Ras signaling and promotes tumor formation in Orp3 knockout mice [32]. The Orp3 knockout mice primarily developed B-cell leukemia, probably due to high Orp3 mRNA expression in hematopoietic stem cells of C57BL/6 mice (C. Günes, unpublished results). Whether Orp3 knockout promotes colon cancer initiation and progression needs to be elucidated in future studies. In addition, potential association of RAS mutations with ORP3 mutations and/or expression levels need to be elucidated in future studies.
Taken together, ORP3 mRNA levels may help to improve stratification of patients with grade 3 colon cancer for an improved therapy option. In this line, it was shown that ORP3 expression correlates with benefit from CCNU/bevacizumab combination treatment in a specific molecular subtype of glioma [23]. This study provides evidence for a potential benefit of patient stratification using ORP3 as a molecular marker, although we have to admit that the sample size is low in specific subgroups (i.e., grade 3 tumor patients with gender and age discrimination). Questions remain towards the relationship of patient survival with altered ORP3 levels and specific patient subgroups. We have previously shown that the knock-down and the knockout of ORP3 induces aneuploidy, promoting tumorigenesis. It seems conceivable to speculate that increased genome instability due to lower ORP3 levels accelerates tumor malignancy and is disadvantageous for survival of patients with advanced tumor progression (grade 3) or nodal metastasis (N2). Further prospective analyses of the relationships between the expression of ORP3 and the course of the disease in colon carcinoma are useful in order to demonstrate the importance of ORP3 as a potential marker for predicting the prognosis in colon carcinoma.

4. Materials and Methods

4.1. Human Tumor Tissue

The cohort encompasses 206 patients suffering from colon cancer who were operated in the Department of General and Visceral Surgery of the University Hospital Ulm between 2003 and 2014. Patients were constitutively recruited for the study but only in the case that they had given their consent for collecting patient´s blood, tissue and clinical data for this study prior to surgery. The patients were informed verbally and in writing about the planned measures using a separate information sheet. Patients were also informed that they could withdraw their consent at any time and that their personal data would be treated with strict confidentiality and in compliance with data protection regulations. Exclusion criteria were no informed consent, withdraw of patient´s consent, and age under 18 years. The study was performed with the permission of the independent local ethics committee of the University of Ulm (approvals 211/2002, 16 December 2002, and 268/2008, 15 December 2008).
Tumor tissues from 206 patients stored in our tissue bank were used. Routine pathological analyses from all tissue samples collected during operation were performed and the following variables were considered for further analysis: sex, median survival, local tumor stage (according the Union for International Cancer Control, UICC [43,44], histological grade, localization, lymph node invasion, and metastasis.

4.2. RNA Extraction, cDNA Synthesis and Determination of cDNA Purity

Total RNA was isolated from frozen tumor tissue sections of colon cancer patients using the RNeasy Mini Kit (Qiagen, Hilden, Germany) according to the manufacturer’s protocol. RNA was extracted in 30 µL of RNase free H2O and stored at −80 °C. In total, 1 µg of total RNA was transcribed into cDNA using the AffinityScript cDNA Synthesis Kit (Agilent Technologies, Santa Clara, CA, USA) according to the manufacturer’s instructions. cDNA samples were kept at −20 °C until they were used for PCR. All PCR reactions were performed in thermal cycler (LabCycler SensoQuest, Göttingen, Germany) in a total volume of 25 µL (quantitative) or 50 µL (preparative) containing 1× polymerase-specific buffer, 0.25 mM dNTP mix, 100 ng of template DNA, 100 nM forward and reverse primers and 2 U DNA polymerase. (Thermo Fisher Scientific, Schwerte, Germany). For verifing cDNA quality and genomic DNA contamination the β-ACTIN primer pairs β-ACTIN_for (GGC ATC CTC ACC CTG AAG TA)/β-ACTIN-rev (GTC AGG CAG CTC GTA GCT CT) and β-ACTIN_I (CGA GCA GGA GAT GGC CAC TGC)/β-ACTIN_E (GTG AGC TCT CTG GGT GCT GGG), as well as Taq polymerase (5 PRIME, Hilden, Germany) were used. Cycling conditions were as following: initial denaturation 3 min at 94 °C, denaturation (40 s at 94 °C), annealing (40 s at 62 °C), elongation (1 min at 72 °C) 35 cyles, and final elongation 5 min at 72 °C. Experiments were done in duplicate. Results are shown as ∆Ct values.

4.3. Determination of ORP3 mRNA Levels by Polymerase Chain Reaction (PCR) in Tumor Samples of 206 Colon Cancer Patients

All PCR reactions were performed in a total volume of 25 µL (quantitative) or 50 µL (preparative) containing 1x polymerase-specific buffer, 0.25 mM dNTP mix, 100 ng of template DNA, 100 nM forward and reverse primers and 2 U DNA polymerase. (Thermo Fisher Scientific, Schwerte, Germany). For checking cDNA quality and genomic DNA contamination the β-ACTIN primer pairs β-ACTIN_for (GGC ATC CTC ACC CTG AAG TA)/β-ACTIN-rev (GTC AGG CAG CTC GTA GCT CT) and β-ACTIN_I (CGA GCA GGA GAT GGC CAC TGC)/β-ACTIN_E (GTG AGC TCT CTG GGT GCT GGG), as well as Taq polymerase (5 PRIME, Hilden, Germany) were used. Quantitative gene expression of OSBPL3 (ORP3) was performed using the LC480 cycler (Roche Applied Science, Mannheim, Germany), QuantiFast SYBR Green PCR Kit (Qiagen, Hilden, Germany), and QuantiTect Primer Assay (Hs_OSBPL3_1_SG Cat.no. QT00084070; Qiagen, Hilden, Germany) according to the manufacturer’s protocol. Primers for β-ACTIN (Hs_ACTB_2_SG Cat.no. QT01680476, Qiagen; Hilden, Germany) and HPRT (Hs_HPRT_1_SG Cat.no. QT00059066; Qiagen, Hilden, Germany) were used as endogenous controls. The efficiency of all three primer pairs was tested and resulted in the following efficiencies: HPRT = 103%, β-ACTIN = 101%, and OSBPL3 (ORP3) = 109%. Furthermore, in order to exclude primer dimers and to guarantee reaction specificity, melting points were analyzed after amplification. The experiments were carried out using the following protocol: initial denaturation phase (15 min, 95 °C), PCR cycle (45 times: 15 s denaturation at 95 °C, 30 s annealing at 55 °C, 30 s elongation at 72 °C), melt phase (15 s at 95 °C, 1 min at 65 °C, continuous acquisition during temperature ramp up to 97 °C). Experiments were done in duplicate. Results are shown as ∆Ct values.

4.4. Determination of ORP3 mRNA Levels by RT-qPCR in Matched Normal and Tumor Tissue of 44 Colon Cancer Patients

Following primer pairs were used to quantify ORP3 and HPRT1, respectively: ORP3-F: 5′-GTCATCCGCCCTAGCACAAAA and ORP3-R: 5′-AGAGACTCGGCATGGATTCTG; HPRT1-F: 5′- TGAGGATTTGGAAAGGGTGT and HPRT1-R: 5′- GAGCACACAGAGGGCTACAA. Quantitative PCR (qPCR) was performed using the iQ SYBRgreen super mix (Bio-Rad; 170–8880) by Applied Biosystem 7300 real-time PCR system. Experiments were performed as three technical replicates. Results are shown as ∆Ct values. Cycling conditions were as above.

4.5. Statistical Analyses

Exploratory data analysis was performed using IBM SPSS Statistics 25 (SPSS Inc., Armonk, NY, USA). Exploratory data were depicted as median (minimum/maximum). For statistical analysis of overall survival, a Kaplan–Meier estimation was created, and significance was tested using log-rank test. Group comparisons were performed by applying Wilcoxon test. p values < 0.05 were considered statistically significant. No correction for multiple testing was done. Correlation analysis was performed using the Spearman–Rho correlation. For each analysis, the correlation coefficient was displayed in addition to the p-value (two-sided). The graphs were edited by using CORELDRAW Version 12 (Corel Corporation, Ottawa, Canada).
Multivariate analysis was performed using R4.0.0 (R Core Team, 2020) using the following packages: survival (3.2–3) [45], survminer (0.4.8) [46] and dplyr (1.0.0) [47]. The full reproducible code is depicted as part of the Supplementary Table S2.

5. Conclusions

In this study, we show that low ORP3 mRNA levels correlate with reduced survival of colon cancer patients with advanced nodal metastasis (N2). In addition, the study revealed that low ORP3 mRNA levels associate with worse survival of female patients with grade 3 colon cancer. Moreover, we found an age-dependent correlation for patient survival, as low ORP3 mRNA levels associate with worse survival of grade 3 colon cancer patients 70 years of age and younger. In summary, the data show that ORP3 expression is downregulated during colon cancer progression, which correlates with reduced patient survival. We conclude that ORP3 mRNA levels may be a prognostic marker for better stratification of colon cancer patients.

Supplementary Materials

Supplementary materials can be found at https://www.mdpi.com/1422-0067/21/16/5894/s1. Supplementary Figure S1: ORP3 mRNA levels of grade 2 patients did not significantly correlate with patient´s survival. No predication for patient´s survival in correlation to ORP3 mRNA levels was possible for patients with grade 1 and grade 4 tumors due to low group numbers (n = 12 and n = 5, respectively); Supplementary Figure S2: Impact of ORP3 RNA expression on prognosis of the different UICC subgroups of colon cancer patients. Kaplan–Meier plot display the overall survival of patients with UICCI, UICC II, UICC III, and UICC IV tumors of colon cancer patients, divided according to the relative ORP3 RNA expression quantified by qPCR using specific primers. HPRT gene served as reference gene. Graphs were created using IBM SPSS Statistics 25; * p ≤ 0.05; Supplementary Figure S3: The figure shows the box plots representing average expression of ORP3 in separate groups of N0–N2, T1–T4 and grades 1–4; Supplementary Table S1: Output of the cox proportional-hazards analysis for the whole cohort. Results for the code coxph(formula = Surv(Time, Outcome) ~ factor(“Expression level of ORP3”) + Sex + Grade + factor(Localization) + UICC + “Invaded Lymph nodes” + Metastasis + Age, data = Cohort). Significance levels are shown as follows: * indicates p < 0.05, ** indicates p < 0.01, *** indicates p < 0.001; Supplementary Table S2: Output of the cox proportional-hazards analysis of patients with a grade 3 tumor. Results for the code: coxph (formula = Surv(Time, Outcome) ~ factor(“Expression level of ORP3”) + Sex + factor(Localization) + UICC + “Invaded Lymph nodes” + Metastasis + Age, data = Grade3). Significance levels are shown as follows: * indicates p < 0.05, ** indicates p < 0.01, *** indicates p < 0.001.

Author Contributions

Conceptualization, C.G. and U.K.; formal analysis, A.B., R.A., S.M., J.R., F.G., and W.A.M.; investigation, P.X., J.R. and A.A.; writing—original draft preparation, C.G., U.K.; visualization, A.B.; supervision, C.G. and U.K. All authors have read and agreed to the published version of the manuscript.

Funding

Cagatay Günes is supported by the Wilhelm Sander Stiftung (Funding Nr. 2019.038.1).

Conflicts of Interest

The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.

Abbreviations

ORP3oxysterol binding protein-related protein 3
CRCColorectal cancer
FAPfamiliar adenomatous polyposis
dMMRDNA mismatch repair
MLH1Mut L homolog1
MSH2Mut S homolog 2
BRAFProto-oncogene B-raf
OSBPL3oxysterol binding protein-like 3
ERendoplasmic reticulum
UICCUnion for International Cancer Control
cisCarcinoma in situ
CINChromosomal instability
PP2AProtein phosphatase 2
HePTPhematopoietic protein tyrosine kinase
ERKextracellular signal-regulated kinases
CCNUlomustine
MDPIMultidisciplinary Digital Publishing Institute
DOAJDirectory of open access journals
TLAThree letter acronym
LDlinear dichroism
DNAdeoxyribonucleic acid
HPRTHypoxanthine Phosphoribosyltransferase
MSImicrosatellite instability
MSI-Hhigh microsatellite instability
HNPCChereditary non-polyposis colorectal cancer
MSSmicro-satellite stable
PHpleckstrin–homology
minminimum
maymaximum
NR5A2nuclear receptor of subfamily 5 group A
LRH-1liver receptor homologue 1

References

  1. Kuipers, E.J.; Grady, W.M.; Lieberman, D.; Seufferlein, T.; Sung, J.J.; Boelens, P.G.; van de Velde, C.J.; Watanabe, T. Colorectal cancer. Nat. Rev. Dis. Primers 2015, 1, 15065. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  2. Divella, R.; De Luca, R.; Abbate, I.; Naglieri, E.; Daniele, A. Obesity and cancer: The role of adipose tissue and adipo-cytokines-induced chronic inflammation. J. Cancer 2016, 7, 2346–2359. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  3. Song, M.; Chan, A.T.; Sun, J. Influence of the Gut Microbiome, Diet, and Environment on Risk of Colorectal Cancer. Gastroenterology 2020, 158, 322–340. [Google Scholar] [CrossRef] [PubMed]
  4. Abdel-Rahman, W.M.; Faris, M.E.; Peltomaki, P. Molecular Determinants of Colon Cancer Susceptibility in the East and West. Curr. Mol. Med. 2017, 17, 34–45. [Google Scholar] [CrossRef] [PubMed]
  5. Afrasanie, V.A.; Marinca, M.V.; Alexa-Stratulat, T.; Gafton, B.; Paduraru, M.; Adavidoaiei, A.M.; Miron, L.; Rusu, C. KRAS, NRAS, BRAF, HER2 and microsatellite instability in metastatic colorectal cancer - practical implications for the clinician. Radiol. Oncol. 2019, 53, 265–274. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  6. Sinicrope, F.A. Lynch Syndrome-Associated Colorectal Cancer. N. Engl. J. Med. 2018, 379, 764–773. [Google Scholar] [CrossRef]
  7. Ma, H.; Brosens, L.A.A.; Offerhaus, G.J.A.; Giardiello, F.M.; de Leng, W.W.J.; Montgomery, E.A. Pathology and genetics of hereditary colorectal cancer. Pathology 2018, 50, 49–59. [Google Scholar] [CrossRef]
  8. Nojadeh, J.N.; Behrouz Sharif, S.; Sakhinia, E. Microsatellite instability in colorectal cancer. EXCLI J. 2018, 17, 159–168. [Google Scholar]
  9. Wright, M.; Beaty, J.S.; Ternent, C.A. Molecular Markers for Colorectal Cancer. Surg. Clin. N. Am. 2017, 97, 683–701. [Google Scholar] [CrossRef]
  10. Reilly, N.M.; Novara, L.; Di Nicolantonio, F.; Bardelli, A. Exploiting DNA repair defects in colorectal cancer. Mol. Oncol. 2019, 13, 681–700. [Google Scholar] [CrossRef] [Green Version]
  11. Rhee, Y.Y.; Kim, K.J.; Kang, G.H. CpG Island Methylator Phenotype-High Colorectal Cancers and Their Prognostic Implications and Relationships with the Serrated Neoplasia Pathway. Gut Liver 2017, 11, 38–46. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  12. Jonchere, V.; Marisa, L.; Greene, M.; Virouleau, A.; Buhard, O.; Bertrand, R.; Svrcek, M.; Cervera, P.; Goloudina, A.; Guillerm, E.; et al. Identification of Positively and Negatively Selected Driver Gene Mutations Associated With Colorectal Cancer With Microsatellite Instability. Cell. Mol. Gastroenterol. Hepatol. 2018, 6, 277–300. [Google Scholar] [CrossRef] [PubMed]
  13. Bonnot, P.E.; Passot, G. RAS mutation: Site of disease and recurrence pattern in colorectal cancer. Chin. Clin. Oncol. 2019, 8, 55. [Google Scholar] [CrossRef] [PubMed]
  14. Gatalica, Z.; Vranic, S.; Xiu, J.; Swensen, J.; Reddy, S. High microsatellite instability (MSI-H) colorectal carcinoma: A brief review of predictive biomarkers in the era of personalized medicine. Fam. Cancer 2016, 15, 405–412. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  15. Cheng, L. Molecular Genetic Pathology; Humana Press: Totowa, NJ, USA, 2009. [Google Scholar]
  16. Hewish, M.; Lord, C.J.; Martin, S.A.; Cunningham, D.; Ashworth, A. Mismatch repair deficient colorectal cancer in the era of personalized treatment. Nat. Rev. Clin. Oncol. 2010, 7, 197–208. [Google Scholar] [CrossRef]
  17. Ligtenberg, M.J.; Kuiper, R.P.; Chan, T.L.; Goossens, M.; Hebeda, K.M.; Voorendt, M.; Lee, T.Y.; Bodmer, D.; Hoenselaar, E.; Hendriks-Cornelissen, S.J.; et al. Heritable somatic methylation and inactivation of MSH2 in families with Lynch syndrome due to deletion of the 3′ exons of TACSTD1. Nat. Genet. 2009, 41, 112–117. [Google Scholar] [CrossRef]
  18. Devaud, N.; Gallinger, S. Chemotherapy of MMR-deficient colorectal cancer. Fam. Cancer 2013, 12, 301–306. [Google Scholar] [CrossRef]
  19. Smyrk, T.C.; Watson, P.; Kaul, K.; Lynch, H.T. Tumor-infiltrating lymphocytes are a marker for microsatellite instability in colorectal carcinoma. Cancer 2001, 91, 2417–2422. [Google Scholar] [CrossRef]
  20. Gatalica, Z.; Torlakovic, E. Pathology of the hereditary colorectal carcinoma. Fam. Cancer 2008, 7, 15–26. [Google Scholar] [CrossRef]
  21. Maccaroni, E.; Bracci, R.; Giampieri, R.; Bianchi, F.; Belvederesi, L.; Brugiati, C.; Pagliaretta, S.; Del Prete, M.; Scartozzi, M.; Cascinu, S. Prognostic impact of mismatch repair genes germline defects in colorectal cancer patients: Are all mutations equal? Oncotarget 2015, 6, 38737–38748. [Google Scholar] [CrossRef] [Green Version]
  22. Ribic, C.M.; Sargent, D.J.; Moore, M.J.; Thibodeau, S.N.; French, A.J.; Goldberg, R.M.; Hamilton, S.R.; Laurent-Puig, P.; Gryfe, R.; Shepherd, L.E.; et al. Tumor microsatellite-instability status as a predictor of benefit from fluorouracil-based adjuvant chemotherapy for colon cancer. N. Engl. J. Med. 2003, 349, 247–257. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  23. Erdem-Eraslan, L.; van den Bent, M.J.; Hoogstrate, Y.; Naz-Khan, H.; Stubbs, A.; van der Spek, P.; Bottcher, R.; Gao, Y.; de Wit, M.; Taal, W.; et al. Identification of Patients with Recurrent Glioblastoma Who May Benefit from Combined Bevacizumab and CCNU Therapy: A Report from the BELOB Trial. Cancer Res. 2016, 76, 525–534. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  24. Lehto, M.; Tienari, J.; Lehtonen, S.; Lehtonen, E.; Olkkonen, V.M. Subfamily III of mammalian oxysterol-binding protein (OSBP) homologues: The expression and intracellular localization of ORP3, ORP6, and ORP7. Cell Tissue Res. 2004, 315, 39–57. [Google Scholar] [CrossRef]
  25. Lehto, M.; Mayranpaa, M.I.; Pellinen, T.; Ihalmo, P.; Lehtonen, S.; Kovanen, P.T.; Groop, P.H.; Ivaska, J.; Olkkonen, V.M. The R-Ras interaction partner ORP3 regulates cell adhesion. J. Cell Sci. 2008, 121 Pt 5, 695–705. [Google Scholar] [CrossRef] [Green Version]
  26. Weber-Boyvat, M.; Kentala, H.; Lilja, J.; Vihervaara, T.; Hanninen, R.; Zhou, Y.; Peranen, J.; Nyman, T.A.; Ivaska, J.; Olkkonen, V.M. OSBP-related protein 3 (ORP3) coupling with VAMP-associated protein A regulates R-Ras activity. Exp. Cell Res. 2015, 331, 278–291. [Google Scholar] [CrossRef] [PubMed]
  27. Wang, P.Y.; Weng, J.; Anderson, R.G. OSBP is a cholesterol-regulated scaffolding protein in control of ERK 1/2 activation. Science 2005, 307, 1472–1476. [Google Scholar] [CrossRef]
  28. Charman, M.; Colbourne, T.R.; Pietrangelo, A.; Kreplak, L.; Ridgway, N.D. Oxysterol-binding protein (OSBP)-related protein 4 (ORP4) is essential for cell proliferation and survival. J. Biol. Chem. 2014, 289, 15705–15717. [Google Scholar] [CrossRef] [Green Version]
  29. Koga, Y.; Ishikawa, S.; Nakamura, T.; Masuda, T.; Nagai, Y.; Takamori, H.; Hirota, M.; Kanemitsu, K.; Baba, Y.; Baba, H. Oxysterol binding protein-related protein-5 is related to invasion and poor prognosis in pancreatic cancer. Cancer Sci. 2008, 99, 2387–2394. [Google Scholar] [CrossRef]
  30. Liu, H.; Huang, S. Role of oxysterol-binding protein-related proteins in malignant human tumours. World J. Clin. Cases 2020, 8, 1–10. [Google Scholar] [CrossRef]
  31. Meena, J.K.; Cerutti, A.; Beichler, C.; Morita, Y.; Bruhn, C.; Kumar, M.; Kraus, J.M.; Speicher, M.R.; Wang, Z.Q.; Kestler, H.A.; et al. Telomerase abrogates aneuploidy-induced telomere replication stress, senescence and cell depletion. EMBO J. 2015, 34, 1371–1384. [Google Scholar] [CrossRef] [Green Version]
  32. Njeru, S.N.; Kraus, J.; Meena, J.K.; Lechel, A.; Katz, S.F.; Kumar, M.; Knippschild, U.; Azoitei, A.; Wezel, F.; Bolenz, C.; et al. Aneuploidy-inducing gene knockdowns overlap with cancer mutations and identify Orp3 as a B-cell lymphoma suppressor. Oncogene 2020, 39, 1445–1465. [Google Scholar] [CrossRef] [PubMed]
  33. Vasaikar, S.; Huang, C.; Wang, X.; Petyuk, V.A.; Savage, S.R.; Wen, B.; Dou, Y.; Zhang, Y.; Shi, Z.; Arshad, O.A.; et al. Proteogenomic Analysis of Human Colon Cancer Reveals New Therapeutic Opportunities. Cell 2019, 177, 1035–1049.e19. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  34. Cerami, E.; Gao, J.; Dogrusoz, U.; Gross, B.E.; Sumer, S.O.; Aksoy, B.A.; Jacobsen, A.; Byrne, C.J.; Heuer, M.L.; Larsson, E.; et al. The cBio cancer genomics portal: An open platform for exploring multidimensional cancer genomics data. Cancer Discov. 2012, 2, 401–404. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  35. Gao, J.; Aksoy, B.A.; Dogrusoz, U.; Dresdner, G.; Gross, B.; Sumer, S.O.; Sun, Y.; Jacobsen, A.; Sinha, R.; Larsson, E.; et al. Integrative analysis of complex cancer genomics and clinical profiles using the cBioPortal. Sci. Signal. 2013, 6, l1. [Google Scholar] [CrossRef] [Green Version]
  36. Stein, S.; Lemos, V.; Xu, P.; Demagny, H.; Wang, X.; Ryu, D.; Jimenez, V.; Bosch, F.; Luscher, T.F.; Oosterveer, M.H.; et al. Impaired SUMOylation of nuclear receptor LRH-1 promotes nonalcoholic fatty liver disease. J. Clin. Investig. 2017, 127, 583–592. [Google Scholar] [CrossRef]
  37. Bayrer, J.R.; Mukkamala, S.; Sablin, E.P.; Webb, P.; Fletterick, R.J. Silencing LRH-1 in colon cancer cell lines impairs proliferation and alters gene expression programs. Proc. Natl. Acad. Sci. USA 2015, 112, 2467–2472. [Google Scholar] [CrossRef] [Green Version]
  38. Kramer, H.B.; Lai, C.F.; Patel, H.; Periyasamy, M.; Lin, M.L.; Feller, S.M.; Fuller-Pace, F.V.; Meek, D.W.; Ali, S.; Buluwela, L. LRH-1 drives colon cancer cell growth by repressing the expression of the CDKN1A gene in a p53-dependent manner. Nucleic Acids Res. 2016, 44, 582–594. [Google Scholar] [CrossRef] [Green Version]
  39. Wu, C.; Feng, J.; Li, L.; Wu, Y.; Xie, H.; Yin, Y.; Ye, J.; Li, Z. Liver receptor homologue 1, a novel prognostic marker in colon cancer patients. Oncol. Lett. 2018, 16, 2833–2838. [Google Scholar] [CrossRef] [Green Version]
  40. Ahlquist, T.; Bottillo, I.; Danielsen, S.A.; Meling, G.I.; Rognum, T.O.; Lind, G.E.; Dallapiccola, B.; Lothe, R.A. RAS signaling in colorectal carcinomas through alteration of RAS, RAF, NF1, and/or RASSF1A. Neoplasia 2008, 10, 680–686. [Google Scholar] [CrossRef] [Green Version]
  41. Tariq, K.; Ghias, K. Colorectal cancer carcinogenesis: A review of mechanisms. Cancer Biol. Med. 2016, 13, 120–135. [Google Scholar] [CrossRef] [Green Version]
  42. Cancer Genome Atlas, N. Comprehensive molecular characterization of human colon and rectal cancer. Nature 2012, 487, 330–337. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  43. Sobin, L.H.; Gospodarowicz, M.K.; Wittekind, C. TNM Classification of Malignant Tumours, 7th ed.; Sobin, L.H., Gospodarowicz, M.K., Eds.; Wiley-Liss Inc: New York, NY, USA, 2009. [Google Scholar]
  44. Bosman, F.T.; Carneiro, F.; Hruban, R.H.; Theise, N.D. WHO Classification of Tumors of the Digestive System. World Health Organization Classification of Tumours, 4th ed.; International Agency for Research on Cancer (IARC): Lyon, France, 2010. [Google Scholar]
  45. Therneau, T.M.; Grambsch, P.M. Modeling Survival Data: Extending the Cox Model; Springer: New York, NY, USA, 2000. [Google Scholar]
  46. Kassambra, A.; Kosinski, M.; Biecek, P. survminer: Drawing Survival Curves Using ‘ggplot2′. R package version 0.4.8. Available online: https://CRAN.R-project.org/package=survminer (accessed on 5 August 2020).
  47. Wickham, H.; François, R.; Henry, L.; Müller, K. A Grammar of Data Manipulation. Available online: https://CRAN.R-project.org/package=dplyr (accessed on 5 August 2020).
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Figure 1. ORP3 mRNA levels are downregulated in the tumor tissue of human colorectal cancer (CRC) patients. ORP3 mRNA levels were determined in samples derived from matched normal and tumor tissues of the same patients in a cohort of 44 patients. Box plot analysis show the group comparison of relative ORP3 RNA expression in normal and tumor tissues of CRC patients. (Wilcoxon test). Black dots represent normal tissue samples and red dots represent tumor tissue samples.
Figure 1. ORP3 mRNA levels are downregulated in the tumor tissue of human colorectal cancer (CRC) patients. ORP3 mRNA levels were determined in samples derived from matched normal and tumor tissues of the same patients in a cohort of 44 patients. Box plot analysis show the group comparison of relative ORP3 RNA expression in normal and tumor tissues of CRC patients. (Wilcoxon test). Black dots represent normal tissue samples and red dots represent tumor tissue samples.
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Figure 2. Hazard ratio calculated using a cox proportional-hazards analysis of the combined cohort. Hazard ratios > 1 indicate an increased risk of dying. While hazard ratios < 1 indicate a beneficial outcome for the patient. p-values of each individual factor based on the multivariate analysis is depicted on the right of the figure with the values: *** indicates p < 0.001.
Figure 2. Hazard ratio calculated using a cox proportional-hazards analysis of the combined cohort. Hazard ratios > 1 indicate an increased risk of dying. While hazard ratios < 1 indicate a beneficial outcome for the patient. p-values of each individual factor based on the multivariate analysis is depicted on the right of the figure with the values: *** indicates p < 0.001.
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Figure 3. Impact of ORP3 mRNA levels on prognosis of colon cancer patients. (A) ORP3 mRNA levels in the whole cohort of colon cancer patients in correlation to patient´s survival, (B) ORP3 mRNA levels in grade 3 human colorectal patients in correlation to patient’s survival; (C,D) ORP3 mRNA levels in grade 3 tumors in correlation to female (C) and male (D) colon cancer patient’ survival; (E,F) ORP3 mRNA levels in grade 3 human colorectal patients in correlation to patient’s age, (E) patients younger than 70 years old and (F) patients older than 70 years old. ORP3 mRNA levels were determined by quantitative gene expression analysis in the whole cohort and in the subgroup of patients with grade 3 colon cancer. Patient’s cumulative survival was plotted against ORP3 mRNA levels. The median value was used to group patients with high and low ORP3 expression. Statistical analysis: Exploratory data analysis was performed using IBM SPSS Statistics 25 (SPSS Inc., Armonk, NY, USA). For statistical analysis of overall survival, Kaplan–Meier estimations were created and a significance was tested using log-rank test. p-values < 0.05 were considered statistically significant. No correction for multiple testing was done. Black: high ORP3 expression levels, grey: low ORP3 expression levels.
Figure 3. Impact of ORP3 mRNA levels on prognosis of colon cancer patients. (A) ORP3 mRNA levels in the whole cohort of colon cancer patients in correlation to patient´s survival, (B) ORP3 mRNA levels in grade 3 human colorectal patients in correlation to patient’s survival; (C,D) ORP3 mRNA levels in grade 3 tumors in correlation to female (C) and male (D) colon cancer patient’ survival; (E,F) ORP3 mRNA levels in grade 3 human colorectal patients in correlation to patient’s age, (E) patients younger than 70 years old and (F) patients older than 70 years old. ORP3 mRNA levels were determined by quantitative gene expression analysis in the whole cohort and in the subgroup of patients with grade 3 colon cancer. Patient’s cumulative survival was plotted against ORP3 mRNA levels. The median value was used to group patients with high and low ORP3 expression. Statistical analysis: Exploratory data analysis was performed using IBM SPSS Statistics 25 (SPSS Inc., Armonk, NY, USA). For statistical analysis of overall survival, Kaplan–Meier estimations were created and a significance was tested using log-rank test. p-values < 0.05 were considered statistically significant. No correction for multiple testing was done. Black: high ORP3 expression levels, grey: low ORP3 expression levels.
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Figure 4. Hazard ratio calculated using a cox proportional-hazards analysis of patients with a grade 3 tumor. The factor grade was, therefore, masked from this analysis. Hazard ratios > 1 indicate an increased risk of dying. While hazard ratios < 1 indicate a beneficial outcome for the patient. p-values of each individual factor based on the multivariate analysis is depicted on the right of the figure with the values: * indicates p < 0.05, ** indicates p < 0.01.
Figure 4. Hazard ratio calculated using a cox proportional-hazards analysis of patients with a grade 3 tumor. The factor grade was, therefore, masked from this analysis. Hazard ratios > 1 indicate an increased risk of dying. While hazard ratios < 1 indicate a beneficial outcome for the patient. p-values of each individual factor based on the multivariate analysis is depicted on the right of the figure with the values: * indicates p < 0.05, ** indicates p < 0.01.
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Figure 5. Low ORP3 mRNA levels associate with reduced survival of advanced nodal metastasis of colon cancer patients. Relative quantification of ORP3 RNA expression in N0 (low ORP3 expression: 24 female, 26 male and high ORP3 expression: 25 female, 26 male) (A), N1 (low ORP3 expression: 14 female, 18 male and high ORP3 expression: 15 female, 15 male) (B), and N2 (low ORP3 expression: 9 female, 13 male and high ORP3 expression: 9 female, 12 male) (C) classified tumors of colon cancer patients was performed by qRT-PCR using ORP3 specific primers. HPRT and β-ACTIN were used as reference genes. Kaplan–Meier survival plots were generated using IBM SPSS Statistics 25. Black: high ORP3 expression levels; grey: low ORP3 expression levels.
Figure 5. Low ORP3 mRNA levels associate with reduced survival of advanced nodal metastasis of colon cancer patients. Relative quantification of ORP3 RNA expression in N0 (low ORP3 expression: 24 female, 26 male and high ORP3 expression: 25 female, 26 male) (A), N1 (low ORP3 expression: 14 female, 18 male and high ORP3 expression: 15 female, 15 male) (B), and N2 (low ORP3 expression: 9 female, 13 male and high ORP3 expression: 9 female, 12 male) (C) classified tumors of colon cancer patients was performed by qRT-PCR using ORP3 specific primers. HPRT and β-ACTIN were used as reference genes. Kaplan–Meier survival plots were generated using IBM SPSS Statistics 25. Black: high ORP3 expression levels; grey: low ORP3 expression levels.
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Figure 6. Influence of ORP3 RNA expression on survival of colon patients with T2, T3, or T4 tumors. Relative quantification of ORP3 RNA expression in T2 (low ORP3 expression: 9 female, 11 male and high ORP3 expression: 8 female, 11 male) (A), T3 (low ORP3 expression: 22 female, 34 male and high ORP3 expression: 33 female, 27 male) (B), and T4 (low ORP3 expression: 12 female, 13 male and high ORP3 expression: 7 female, 13 male) (C) tumors of colon cancer patients was performed by qRT-PCR using ORP3 specific primers. HPRT and β-ACTIN were used as reference genes. Kaplan–Meier survival plots were generated using IBM SPSS Statistics 25.
Figure 6. Influence of ORP3 RNA expression on survival of colon patients with T2, T3, or T4 tumors. Relative quantification of ORP3 RNA expression in T2 (low ORP3 expression: 9 female, 11 male and high ORP3 expression: 8 female, 11 male) (A), T3 (low ORP3 expression: 22 female, 34 male and high ORP3 expression: 33 female, 27 male) (B), and T4 (low ORP3 expression: 12 female, 13 male and high ORP3 expression: 7 female, 13 male) (C) tumors of colon cancer patients was performed by qRT-PCR using ORP3 specific primers. HPRT and β-ACTIN were used as reference genes. Kaplan–Meier survival plots were generated using IBM SPSS Statistics 25.
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Table
Table 1. Clinical parameters of colon cancer patients’ cohort. Clinical parameters of the colon cancer patients in regard to UICC stage, tumor grade, sex, and localization of tumor within the colon referring to median age, survival and expression level of ORP3. Expression levels are calculated as relative quantification (RQ) using hypoxanthine phosphoribosyltransferase (HPRT) and β-ACTIN as housekeeping genes by using LightCycler®480 Multiplate Analysis Software. Abbreviations: cis: carcinoma in situ; min: minimum; max: maximum; ORP3: oxysterol binding protein-related protein 3, also known as oxysterol binding protein-like 3 (OSBPL3), UICC: Union for International Cancer Control, n.d.: not determined.
Table 1. Clinical parameters of colon cancer patients’ cohort. Clinical parameters of the colon cancer patients in regard to UICC stage, tumor grade, sex, and localization of tumor within the colon referring to median age, survival and expression level of ORP3. Expression levels are calculated as relative quantification (RQ) using hypoxanthine phosphoribosyltransferase (HPRT) and β-ACTIN as housekeeping genes by using LightCycler®480 Multiplate Analysis Software. Abbreviations: cis: carcinoma in situ; min: minimum; max: maximum; ORP3: oxysterol binding protein-related protein 3, also known as oxysterol binding protein-like 3 (OSBPL3), UICC: Union for International Cancer Control, n.d.: not determined.
TotalMedian ORP3 mRNA Levels [RQ] (Min/Max)Median Age [Years] (Min/Max)Median Survival [Months] (Min/Max)
Follow-up p = 0.526p = 0.001 *p < 0.001 *
alive920.008 (0.001/0.019)67.32 (29.81/88.23)91.05 (0.46/175.49)
dead1140.008 (0.0005/0.1088)73.55 (39.21/89.68)17.02 (0.33/114.41)
Sex p = 0.666p = 0.293p = 0.102
M1100.008 (0.0005/0.1088)70.37 (29.81/88.58)38.91 (0.39/175.49)
F960.008 (0.0006/0.102970.87 (39.69/89.67)56.01 (0.33/164.77)
Stage (UICC) p = 0.113p = 0.073p < 0.001 *
I370.00811 (0.0016/0.0191)75.37 (45.31/89.67)64.57 (0.52/175.49)
II520.008273 (0.0020/0.0248)70.82 (32.34/87.95)67.75 (1.18/164.05)
III580.009395 (0.0009/0.1088)69.00 (40.17/88.23)64,16 (0.33/153.48)
IV570.007249 (0.0005/0.1029)67.58 (29.81/87.59)14.50 (0.65/140.23)
cis2
Stage (UICC) female p = 0.005 *p = 0.504p < 0.001 *
I190.0077 (0.0015/0.0148)74.28 (51.42/89.68)64.57 (1.15/164.77)
II240.0096 (0.0024/0.0165)68.82 (40.35/87.95)74.54 (1.18/156.09)
III290.0107 (0.0027/0.0299)71.55 (42.13/88.23)69.57 (0.33/153.49)
IV230.0069 (0.0006/0.1029)68.32 (39.70/86.49)12.01 (1.31/81.09)
cis1
Stage (UICC) male p = 0.936p = 0.123p = 0.002
I180.0084 (0.0038/0.0191)77.65 (45.31/88.58)57.48 (0.52/175.49)
II280.0073 (0.0019/0.0248)73.05 (32.34/84.79)67.75 (4.51/164.04)
III290.0081 (0.0009/0.1087)67.34 (40.17/84.67)62.50 (0.39/134.17)
IV340.0080 (0.0005/0.033)66.37 (29.81/87.59)15.42 (0.66/140.23)
CIS1
Grade p = 0.323p = 0.360p = 0.092
1120.008211 (0.0006/0.0165)74.99 (39.69/88.09)54.39 (3.91/164.77)
21350.008082 (0.0005/0.0325)70.17 (40.17/89.67)47.53 (0.39/175.49)
3540.008264 (0.0019/0.1088)69.19 (29.81/88.23)61.74 (0.33/167.37)
450.015794 (0.0042/0.0248)75.56 (58.98/87.95)4.93 (0.76/30.36)
Localization p = 0.245p = 0.041 *p = 0.557
descendens1040.0079 (0.0005/0.0313)68.20 (39.21/88.58)54.58 (0.39/175.49)
ascendens1020.0085 (0.0006/0.1087)72.86 (29.81/89.68)40.90 (0,32/167.37)
Lymph nodes p = 0.789p = 0.032 *p = 0.001 *
not invaded1010.008204 (0.0016/0.0248)73.74 (32.33/89.67)64.57 (0.53/175.49)
invaded1050.008124 (0.0005/0.1088)67.87 (29.81/88.23)27.96 (0.33/153.49)
Metastasis p = 0.033 *p = 0.128p < 0.001 *
negative1490.008587 (0.0010/0.1088)71.54 (32.33/89.67)64.64 (0.33/175.49)
positive570.007250 (0.0005/0.1029)67.58 (29.81/87.58)14.50 (0.66/140.23)
Total2060.008126 (0.0005/0.1088)70.41 (29.81/89.67)48.12 (0.33/175.49)
* p < 0.05 in the Mann–Whitney U Test or Kruskal–Wallis Test.

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Xu, P.; Richter, J.; Blatz, A.; Gärtner, F.; Alberts, R.; Azoitei, A.; Makori, W.A.; Meessen, S.; Knippschild, U.; Günes, C. Downregulation of ORP3 Correlates with Reduced Survival of Colon Cancer Patients with Advanced Nodal Metastasis and of Female Patients with Grade 3 Colon Cancer. Int. J. Mol. Sci. 2020, 21, 5894. https://doi.org/10.3390/ijms21165894

AMA Style

Xu P, Richter J, Blatz A, Gärtner F, Alberts R, Azoitei A, Makori WA, Meessen S, Knippschild U, Günes C. Downregulation of ORP3 Correlates with Reduced Survival of Colon Cancer Patients with Advanced Nodal Metastasis and of Female Patients with Grade 3 Colon Cancer. International Journal of Molecular Sciences. 2020; 21(16):5894. https://doi.org/10.3390/ijms21165894

Chicago/Turabian Style

Xu, Pengfei, Julia Richter, Annette Blatz, Fabian Gärtner, Roland Alberts, Anca Azoitei, Wycliffe Arika Makori, Sabine Meessen, Uwe Knippschild, and Cagatay Günes. 2020. "Downregulation of ORP3 Correlates with Reduced Survival of Colon Cancer Patients with Advanced Nodal Metastasis and of Female Patients with Grade 3 Colon Cancer" International Journal of Molecular Sciences 21, no. 16: 5894. https://doi.org/10.3390/ijms21165894

APA Style

Xu, P., Richter, J., Blatz, A., Gärtner, F., Alberts, R., Azoitei, A., Makori, W. A., Meessen, S., Knippschild, U., & Günes, C. (2020). Downregulation of ORP3 Correlates with Reduced Survival of Colon Cancer Patients with Advanced Nodal Metastasis and of Female Patients with Grade 3 Colon Cancer. International Journal of Molecular Sciences, 21(16), 5894. https://doi.org/10.3390/ijms21165894

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