Abstract
RNF43 is a tumor suppressor for various cancers and is considered to drive carcinogenesis when mutated. However, the correlation between RNF43 mutation and colorectal cancer (CRC) immunotherapy remains unreported. We evaluated the role of RNF43 using publicly available data from the Cancer Genome Atlas (TCGA) and Memorial Sloan Kettering Cancer Center (MSKCC). In addition, further analysis was performed on an internal validation cohort (hcohort). The mutant profiles of RNF43 were analyzed in 873 Chinese CRC patients. The relationship between clinical pathologic features and RNF43 were analyzed using the two-sided chi-squared test or the Fisher exact test. Clinicopathologic characteristics were associated with overall survival using Cox regression and the Kaplan-Meier method. We found that RNF43 mutation was significantly associated with high TMB and high MSI score (all p-values < 0.05) in the MSKCC cohort. Additionally, RNF43 mutation was found to be enriched in MSI instability. Kaplan-Meier survival analysis revealed that patients with RNF43 mutation had better OS compared to RNF43 wild-type (not reached vs. 13 months, HR, 0.12; 95% CI 0.03 to 0.49; P = 0.0034). However, no association was observed between RNF43 and OS in the TCGA cohort (HR, 1.83; 95% CI 0.66 to 5.07; P = 0.2479). Our CRC hcohort confirmed the significance of RNF43 mutation in predicting better clinical outcomes, including ORR (45% vs. 21%, P = 0.0468). RNF43 mutation correlated with a high tumor mutation burden (P < 0.001). The mutation frequency of RNF43 in CRC patients was 8.4% (73/873); RNF43 G659Vfs*41 was found to be the most frequent mutation site. In patients with RNF43 mutations, TP53, KRAS, and TGFBR2 were genes with a high frequency of mutations. Compared with RNF43 wild-type patients, those with RNF43 mutations had a higher TMB score and a greater proportion of MSI-H, but no difference in PD-L1 expression. Moreover, the content of immune-related B cells, CD8+ T cells, neutrophils, and dendritic cells was higher in the RNF43 mutant group than in the wild-type group. Our results suggest that RNF43 mutation may correlate with better OS in CRC patients receiving PD-1/PD-L1 inhibitors. The exact mechanisms underlying RNF43 require further investigation.
Keywords: RNF43, colorectal cancer, immunotherapy, tumor mutation burden, CD8+ T cell
Introduction
Colorectal cancer (CRC) is one of the most common cancers worldwide, ranking in the top three for both incidence and mortality rates [1,2]. Although increased colonoscopy screening and removal of precursor lesions have improved the incidence and prognosis of CRC, a significant proportion of patients exist with advanced disease, and the 5-year survival rate for metastatic CRC remains below than 15% [3]. The development of immunotherapy, however, has shown promising success in enhancing long-term survival in previously refractory solid tumors, including CRC [4]. Currently, several immune checkpoint inhibitors, such as pembrolizumab and combined nivolumab and ipilimumab therapy, have demonstrated promising efficacy and have been approved by the United States Food and Drug Administration (FDA) for treating advanced CRC tumors with high levels of microsatellite instability (MSI-H) or mismatch repair deficiency (dMMR) [5,6]. While MSI/MMR status is the only well-recognized biomarker for immunotherapy in CRC, only a small proportion of CRC patients are MSI-H/dMMR, and some MSI-H/dMMR patients may still exhibit primary or acquired resistance to immunotherapy [6,7]. The independent predictive efficacies of other potential biomarkers, such as tumor mutation burden (TMB) and PD-L1 expression, remain controversial in CRC [8,9]. There is a pressing need for more effective biomarkers to guide the immunotherapy treatment of CRC patients.
RNF43 (Ring Finger Protein 43) encodes an E3 ubiquitin-protein ligase that functions to downregulate the Wnt signaling pathway by inducing degradation of the Wnt receptor Frizzled through ubiquitination [10]. RNF43 mutations have been found to be frequently mutated in various cancer types, including CRC, gastric cancer, pancreatic cancer, and ovarian cancer [11-13]. Loss-of-function RNF43 mutations result in enhanced Wnt signaling and may represent a distinct molecular subtype with aggressive tumor biology [14]. In CRC, two truncating mutations of RNF43, p.G659fs and p.R117fs, have been frequently observed, with the former accounting for nearly 8% of all patients and being especially enriched in MSI-H tumors [15]. Furthermore, RNF43 mutation combined with BRAF V600E mutation has been observed to promote tumor development and is significantly associated with worse survival in right-sided CRC [16]. However, the clinical significance of RNF43 mutations in CRC and their association with CRC immunology remain largely unexplored.
In this study, we investigate the role of RNF43 mutations in CRC survival based on two public datasets, the Cancer Genome Atlas (TCGA) and Memorial Sloan Kettering Cancer Center (MSKCC), combined with an in-house Chinese CRC dataset containing 60 patients. The mutation characteristics of RNF43 in CRC were characterized, and its predictive value for CRC immunotherapy efficacy was explored. In addition, we used a lager sample cohort (3Dcohort) to explore the mutation frequency and profile of RNF43 in Chinese CRC patients. Moreover, several immune-related characteristics, including MSI status and TMB, were further analyzed to determine their correlation with RNF43 mutations in CRC. We aim to provide a comprehensive overview of RNF43 mutations and propose a potential predictor for immunotherapeutic efficacy in CRC.
Materials and methods
Clinical cohorts and public cohorts
Genomic and clinical data of CRC patients administrated with anti-PD-L1 or anti-CTLA-4 antibodies were retrieved from publicly MSKCC accessible data. The genomic, survival, and mRNA data of 457 patients with CRC were obtained from TCGA (www.cbioportal.org). Patients with advanced CRC treated with PD-1/PD-L1 inhibitors between February 2016 and January 2020 were included in our in-house cohort. All patients underwent genomic profiling (150-gene panel) of tumor tissue prior to immunotherapy. Of these, 26 tissue samples failed quality control and were replaced with blood samples for testing. The following clinical characteristics before therapy were recorded: age, sex, histological type, tumor location, response to therapy, and survival. All human samples were collected and used in accordance with the Declaration of Helsinki Principles and approved by Shenzhen People’s Hospital (LL-KY-2021753). All participating patients provided written consent.
As for the 3Dcohort, 873 CRC patients were included from January 2017 to January 2020. Tumor tissue samples (self-blood negative control) of pan-cancer patients were analyzed by NGS for detection the RNF43 mutations using a well-designed 150-gene panel on the Illumina HiSeq sequencer (Illumina, San Diego, CA) with 800× sequencing depth in a College of American Pathologists (CAP) and Clinical Laboratory Improvement Amendments (CLIA) certified laboratory (3D Medicine Inc., Shanghai, China). Somatic alterations were identified, and clinical information, including age, gender, and tumor histology, was collected. Additionally, TMB was defined as the number of nonsynonymous somatic SNVs and indels in examined coding regions, excluding driver mutations. All SNVs and indels in the coding region of targeted genes, including missense, silent, stop gain, stop loss, in-frame, and frameshift mutations, were considered.
DNA extraction, library preparation and DNA sequencing
Experimental methods for next-generation sequencing (NGS), such as DNA extraction, library preparation, and DNA sequencing, are described in our previous work [17]. FFPE tissue sections were evaluated for tumor cell content using hematoxylin and eosin (H&E) staining. Only samples with a tumor content of ≥ 20% were eligible for subsequent analyses. Blood was centrifuged in a Streck tube at 1600 g for 20 min at room temperature to separate plasma. Then, gDNA was extracted from tumor FFPE tissue and white blood cells, respectively, following a standard protocol using the DNeasy tissue or blood kit (Qiagen). Libraries were prepared using the KAPA Hyper Prep Kit (KAPA Biosystems) as per the manufacturer’s protocol. The concentration and size distribution of each library were determined using a Qubit 3.0 fluorometer (Thermo Fisher Scientific) and a LabChip GX Touch HT Analyzer (PerkinElmer), respectively. Single nucleotide variations (SNV), insertions/deletions, copy number variations (CNV), and gene fusions were assessed. Germline alterations were excluded.
Assessment of immune signatures
Based on gene mutation analysis, the infiltration level of immune cells in CRC was analyzed using the TIMER database (https://cistrome.shinyapps.io/timer/) [18]. The gene name RNF43 under the mutation module was used to determine the relationship between RNF43 mutation and the level of immune cell infiltration. The “CIBERSORT” (R package) was used to determine the proportion of 22 tumor-infiltrating immune cells (TIICs) in each sample [19]. The proportion of 22 TIICs in each tissue was predicted based on its GEPs. Normalized CRC GEPs were transformed into the proportion of 22 TIICs. The relative expression of 22 TIICs in each sample was determined.
Statistical analyses
Overall survival (OS) was calculated from the date of first line therapy administration to the date of death from any cause. Survival was illustrated using Kaplan-Meier curves, with P-values determined by a log-rank test. Hazard ratio (HR) was determined through the univariate and multivariate Cox regression. Variables of interest with significant P-values were included in multivariate logistic regression. Continuous variables were compared using the Mann-Whitney U test. For all analyses, P-value < 0.05 was considered statistically significant, with a confidence interval of 95% (95% CI). All statistical analyses were performed using SPSS22.0 software (SPSS Inc., Chicago, IL, USA).
Results
Association of RNF43 mutation with improved OS in CRC patients undergoing immunotherapy
Detailed baseline characteristics of CRC patients in two independent cohorts (MSKCC and TCGA) are summarized in Table 1. In the MSKCC cohort, 21 patients (19%) harbored an RNF43 mutation (RNF43-MUT), while 88 were RNF43 wild-type (RNF43-WT). The TCGA cohort had 45 patients (9%) with RNF43-MUT.
Table 1.
Baseline characteristics in MSKCC and TCGA cohorts
| Characteristics | MSKCC cohort | TCGA cohort |
|---|---|---|
| Age, n (%) | ||
| ≤ 60 | 71 (65%) | 174 (35%) |
| > 60 | 38 (35%) | 329 (65%) |
| Sex, n (%) | ||
| Female | 48 (44%) | 237 (47%) |
| Male | 61 (56%) | 266 (53%) |
| Cancer type, n (%) | ||
| Colon Adenocarcinoma | 87 (80%) | 318 (63%) |
| Rectal Adenocarcinoma | 16 (15%) | 131 (26%) |
| Mucinous Adenocarcinoma of the Colon and Rectum | 4 (4%) | 53 (11%) |
| Signet Ring Cell Adenocarcinoma of the Colon and Rectum | 4 (4%) | 0 |
| Colorectal Adenocarcinoma | 1 (1%) | 0 |
| Drug type, n (%) | ||
| Combo | 10 (9.1%) | / |
| CTLA4 | 1 (0.9%) | / |
| PD-1/PDL-1 | 98 (90%) | / |
| Gene, n (%) | ||
| RNF43 mutation | 21 (19%) | 45 (9%) |
| RNF43 wild-type | 88 (81%) | 458 (91%) |
| Sample type, n (%) | ||
| Metastasis | 59 (54%) | 0 |
| Primary | 50 (46%) | 503 (100%) |
We first analyzed the association in the MSKCC cohort to explore the correlation between RNF43-MUT and the efficacy of immune checkpoint blockades (ICBs) in CRC patients. As shown in Figure 1A, RNF43 mutation was significantly associated with better OS. The median OS for RNF43-MUT vs. RNF43-WT patients were not reached and 13.0 months, respectively (HR = 0.12; 95% CI, 0.03-0.49; P = 0.0034). RNF43-MUT patients also exhibited significantly higher MSI scores than RNF43-WT patients (Figure 1B, P < 0.0001). Notably, all patients with MSS type were found in the RNF43-WT group (Figure 1C). However, in the TCGA cohort of CRC patients not treated with ICBs, RNF43 mutation was not associated with a better OS benefit. The median OS for RNF43-MUT vs. RNF43-WT patients were 70.1 months vs. 92.7 months (HR = 1.32; 95% CI, 0.71-2.46; P = 0.3805, Figure 1D).
Figure 1.
Association between RNF43 mutation and OS in CRC patients. (A) Kaplan-Meier survival curves of OS comparing CRC patients with RNF43-MUT and wild-type in MSKCC cohort. Comparison of MSI score (B) and MSI type (C) between RNF43-MUT and RNF43-WT CRC patients in MSKCC. (D) Kaplan-Meier survival curves of OS comparing CRC patients with RNF43-MUT and wild-type in TCGA cohort. OS: overall survival. MSI: microsatellite instability.
Univariate and multivariable regression analyses of OS in the MSKCC cohort are detailed in Table 2. Confounders, including age, sex, drug type, tumor location, TMB, MSI, and RNF43 mutations, were analyzed. Univariable analysis revealed significant association between better OS and male, MSI-H, and RNF43 mutation. The multivariable analysis identified RNF43 mutation as an independent predictor for OS (HR = 0.13; 95% CI, 0.025-0.747; P = 0.022). Collectively, these findings suggest that RNF43-MUT could be a potential predictor for ICBs efficacy in CRC.
Table 2.
Univariate and multivariate analyses of overall survival in MSKCC cohort
| Parameter | Univariate analysis | Multivariate analysis | ||||
|---|---|---|---|---|---|---|
|
|
|
|||||
| HR | 95% CI | P value | HR | 95% CI | P value | |
| Sex | ||||||
| Male vs. Female | 0.517 | 0.283-0.942 | 0.031 | 0.441 | 0.239-0.817 | 0.009 |
| Age | ||||||
| > 60 vs. ≤ 60 | 0.506 | 0.255-1.003 | 0.051 | |||
| RNF43 gene | ||||||
| MUT vs. WT | 0.122 | 0.032-0.552 | 0.006 | 0.128 | 0.025-0.747 | 0.022 |
| Tumor location | ||||||
| Rectum vs. others | 0.858 | 0.337-2.185 | 0.748 | |||
| Drug type | ||||||
| PD-L1/1 vs. others | 0.992 | 0.305-3.224 | 0.989 | |||
| TMB status | ||||||
| > median vs. ≤ median | 0.628 | 0.340-1.158 | 0.136 | |||
| MSI status | ||||||
| MSI-H vs. MSS | 0.264 | 0.103-0.678 | 0.006 | 0.716 | 0.244-2.104 | 0.544 |
Association between RNF43 mutation and better OS benefit in our in-house cohort who received immunotherapy
The basic characteristics of our in-house ICBs treatment cohort (N = 60) are detailed in Table S1. Of these, 22 patients had RNF43-MUT, comprising 20 cases of colorectal cancer, one case of rectal cancer, and one case of ileocecal cancer, accounting for 36.7% of the total cohort. In this CRC cohort, 36 of the 60 patients (60.0%) were male, with a median age of 47 years (range: 15-77 years). No significant clinical differences were observed between the RNF43-MUT and RNF43-WT groups. Based on RECIST 1.1, the overall response was evaluable. Notably, the ORR for patients with RNF43-MUT was more than double that of RNF43-WT patients (45.5% vs. 21.1%, P = 0.0468, Figure 2A). For DCB, 77.3% of RNF43-MUT patients underwent ICBs treatment, compared to 39.5% of RNF43-WT patients (P = 0.0070, Figure 2B). While survival of RNF43-MUT CRC patients was superior to that of RNF43-WT patients, with a median OS of undefined vs. 20.87 months, this was not statistically significant (P = 0.1962, Figure 2C). These findings demonstrate the predictive value of RNF43 mutation for ICBs treatment.
Figure 2.
Association between RNF43 mutation and OS in in-house cohort. Comparison of ORR (A) and DCB (B) between RNF43-MUT and RNF43-WT CRC patients. (C) Kaplan-Meier survival curves of OS comparing CRC patients with RNF43-MUT and wild-type. OS, overall survival; CR, Complete response; DCB, Durable clinical benefit; NDB, No durable benefit; PD, Progressive disease; PR, Partial response; SD, Stable disease.
We analyzed differential expression (DE) between RNF43 mutations and the RNF43 wild-type group in the hcohort. RNF43 mutation was more likely to co-occur with mutations in TGFBR2, ACVR2A, RAD50, BRCA1, and RB1 (Figure S1A). Moreover, the DEs were most significantly enriched in human papillomavirus infection, cancer pathways, and the PI3K-Akt signaling pathway (Figure S1B). Examining DEs, biological process (BP) terms are most significantly enriched in cellular metabolic process, metabolic process, and macromolecule biosynthetic process. Cellular component (CC) terms are most significantly enriched in intracellular, membrane-bounded organelle, and intracellular organelle. For molecular function (MF), binding, protein binding, and organic cyclic compound binding are mostly enriched (Figure S1C).
KDR-MUT was indicative of an immune-hot status
To further understand the underlying mechanism of the association between RNF43 mutation and better clinical outcomes in CRC patients who received ICBs therapy, the impact of RNF43 mutation on TMB or immune signatures was explored. Figure 3A-C demonstrate that RNF43 mutation was associated with higher TMB both in the MSKCC cohort and our in-house CRC cohort (P < 0.0001). We subsequently analyzed data from 22 TIICs, comparing mRNA expression of immune related genes between RNF43-MUT and RNF43-WT patients. By using CIBERSORT, we found that activated NK cells and CD8+ T cells were more abundant in RNF43-MUT tumors. Furthermore, B cell, neutrophil cell, and dendritic cell infiltration increased (Figure 3D).
Figure 3.
Possible mechanism of the association of RNF43 mutation and better clinical outcomes of ICBs therapy. A-C. Comparison of TMB between RNF43-MUT and RNF43-WT patients in MSKCC cohort, in-house cohort and 3Dcohort, respectively. D. Effects of RNF43 status and immune cell infiltration. E. Boxplot of differentially expressed immune-related genes in RNF43-MUT and RNF43-WT groups. F. Boxplot of differentially expressed HLA family genes in RNF43-MUT and RNF43-WT groups. G. GSEA reveals prominent enrichment of signatures related to antigen processing and presentation in CRC patients with RNF43 mutation. *P < 0.05, **P < 0.01, ***P < 0.001. TMB: tumor mutational burden.
Moreover, PD-L1 (CD274) and CTLA4 were significantly up-regulated in RNF43-MUT tumors (Figure 3E). Additionally, RNF43-MUT tumors had a higher expression of MHC I- and II-associated antigen-presenting molecules than RNF43-WT tumors (Figure 3F, 3G). These results suggest that RNF43-MUT is associated with a hot immune status and enhances the efficacy of ICBs.
Mutational profiles of RNF43 in 3Dcohort
To investigate the mutation profile of RNF43 in Chinese CRC population, 873 Chinese CRC patients with 150 cancer-related genes detected by NGS were included in this study, including 513 patients with CRC and 315 patients with rectal cancer. A total of 73 (8.4%) patients with RNF43-MUT were identified (Table S2); this was significantly lower than both the MSKCC cohort and the internal cohort (MSKCC cohort: 8.4% vs. 19.3%, P = 0.0008; in-house cohort: 8.4% vs. 36.7%, P < 0.0001), and similar to those of the TCGA cohort (8.4% vs. 9.0%, P = 0.7644). These results might be attributed to the specific cohort under study.
The genomic mutational landscape of 73 patients with RNF43 mutation is presented in Figure 4A. TP53 was the most frequently mutated gene, followed by KRAS, TGFBR2 and MSH3. In addition, 21 (22.3%) patients were confirmed harboring a p.G659VFS*41 mutation (Figure 4B). The proportion of other major RNF43 mutations were p.R132* (7.4%), p.R145* (6.4%), and p.R117Afs*41 (2.1%, Table S3). RNF43 mutations were associated with higher MSI-H in CRC patients (41.1% vs. 3.1%, P < 0.0001, Figure 4C), but not with PD-L1 status (P = 0.166, Figure 4D).
Figure 4.
The genomic characteristics of CRC patients with RNF43 mutations in 3Dcohort. A. The genomic landscape of RNF43-MUT CRC. B. RNF43 high frequency mutation site. C, D. Comparison of MSI type and PD-L1 between RNF43-MUT (mutant-type) and RNF43-WT (wild-type) CRC patients. MSI: microsatellite instability.
Discussion
In the present study, RNF43 mutations were identified for first time as a positive factor for enhanced clinical benefit in CRC patients undergoing ICB treatment. Patients who did not undergo ICB treatment did not observe a clinical benefit for OS. Both univariate and multivariate analyses further established RNF43 mutations as independent positive predictors in the MSKCC cohort. Exploratory analyses suggest that a higher TMB and elevated expression of genes related to MHC I and II-associated antigen-presenting molecules might be a potential mechanism of the predictive value of RNF43 mutations in CRC populations. GSEA also revealed that RNF43-MUT tumors have abundant immune features and microenvironment cell populations, further demonstrating that RNF43-MUT was associated with the hot tumor microenvironment. These results suggest that RNF43-MUT may be a potential positive predictor in CRC patients treated with ICBs.
CRC is a leading cause of death. Chemotherapy with or without targeted therapy has been the standard of care for CRC patients for three decades. Although immunotherapy has made great progress, it is only effective in a small number of MSI-H cancer cases, which account for only 5% of metastatic CRC (mCRC) cases [20]. RNF43 mutations are not uncommon in tumors, particularly colon cancer [21], accounting for approximately 19.3% and 36.7% of the MSKCC cohort and in-house cohort. This suggests that findings related to RNF43-MUT could be applicable to more patients than other rare mutations. Unlike PD-L1 expression or TMB, RNF43-MUT can be easily detected by NGS. Crucially, our study proposes RNF43-MUT as a potential biomarker for ICBs, highlighting an association between RNF43 gene status and ICB response in a public cohort. Importantly, this association was further verified in our in-house CRC cohort, where patients with RNF43 mutations exhibited higher ORR, DCB, and improved prognosis.
RNF43 encodes an E3 ubiquitin ligase and negatively regulates Wnt signaling [21]. The mutation and down-regulation of RNF43 may play a key role in the transformation of gastric adenoma to gastric carcinoma [22]. Similar findings were found in intestinal cancer, where Wnt signaling, activated by RNF43 mutations during the tumorigenesis phase, promoted tumor growth and was associated with high recurrence rates in CRC patients [23]. Low expression of RNF43 has been shown to be associated with a poorer prognosis in melanoma or clear cell renal cell carcinoma [24,25]. In addition, PD-L1 has been reported to be related to RNF43. For example, in biliary tract cancers, RNF43 mutations were predominantly enriched in the PD-L1 positive subgroup (7.1% vs. 1.4%, P = 0.003) [26]. Our study showed similar results, with significantly higher TMB for RNF43-MUT compared with RNF43-WT. This leads to the production of more neoantigens, which are processed by APCs and presented to T cells. The upregulation of MHC-related molecules facilitates this process. Concurrently, the expression of immune-related genes increased, with enrichment in the antigen processing and presentation pathway. This supports our belief that RNF43 mutations correlate with favorable clinical outcomes in ICBs.
To the best of our knowledge, this is the first time that the relationship between RNF43-MUT and ICBs has been explored in CRC. Our study still has some limitations, including those inherent in retrospective design. Analysis was based on the public cohort, which may have contributed to selection bias. However, our independent in-house CRC cohort serves as a robust complement to the analysis. Due to the limited number of patients, the relationship between RNF43-MUT and the efficacy of immunotherapy remains challenging for further exploration, but the overall efficacy of RNF43-MUT remains promising. These findings should be validated in larger cohorts. Additionally, the potential mechanisms by which RNF43 mutations enhance the efficacy of immunotherapy were only explored by bioinformatics analysis. Our conclusion is only that RNF43 mutation is related to an immune hot environment. The exact mechanism by which RNF43-MUT induces immune changes remains to be elucidated and deserves further study.
In conclusion, our results suggest that RNF43 mutations correlate with improved OS through increased TMB and immune-related gene signatures in CRC patients treated with ICBs. RNF43 mutations may be a crucial component of immunogenetics and should be considered as a therapeutic biomarker for immunotherapy.
Acknowledgements
We thank all the patients, their families, and the institutions for supporting this study. The study was funded by Guangdong Basic and Applied Basic Research Foundation (ID: 2021A1515110253). We would like to thank Jun-Ling Zhang (The Medical Department, 3D Medicines Inc.) for her support.
Disclosure of conflict of interest
None.
Supporting Information
References
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