Skip to main content
NCBI home page
NIHPA Author Manuscripts logoLink to NIHPA Author Manuscripts
. Author manuscript; available in PMC: 2023 Dec 25.
Published in final edited form as: Biochem Biophys Res Commun. 2022 Nov 8;636(Pt 2):71–78. doi: 10.1016/j.bbrc.2022.10.108

The differentially expressed gene signatures of the Cullin 3-RING ubiquitin ligases in neuroendocrine cancer

Jong-Uk Park 1, Dong-Kyu Kim 1, Ji-Ye Kim 1, Jae-Hyun Jo 1, Yeong-Mu Kim 1, Dong-Hyun Jung 1, Hye-Ji Kim 1, Seon-Mi Ok 1, Hyo Je Cho 1, Sangjune Kim 2, Christophe E Redon 3, Mirit I Aladjem 3, Sang-Min Jang 1,*
PMCID: PMC9671844  NIHMSID: NIHMS1848685  PMID: 36368157

Abstract

Cullin-RING ubiquitin E3 ligase (CRLs) composed of four components including cullin scaffolds, adaptors, substrate receptors, and RING proteins mediates the ubiquitination of approximately 20% of cellular proteins that are involved in numerous biological processes. While CRLs deregulation contributes to the pathogenesis of many diseases, including cancer, how CRLs deregulation occurs is yet to be fully investigated. Here, we demonstrate that components of CRL3 and its transcriptional regulators are possible prognosis marker of neuroendocrine (NE) cancer. Analysis of Cancer Cell Line Encyclopedia (CCLE) through the CellMinerCDB portal revealed that expression of CRL3 scaffold Cullin 3 (CUL3) highly correlates with NE signature, and CUL3 silencing inhibited NE cancer proliferation. Moreover, subset of 151 BTB (Bric-a-brac, Tramtrack, Broad complex) domain-containing proteins that have dual roles as substrate receptors and adaptor subunits in CRL3, as well as the expression of transcription factors (TFs) that control the transcription of BTB genes were upregulated in NE cancer. Analysis using published ChIP-sequencing data in small cell lung cancer (SCLC), including NE- or non-NE SCLC verified that gene promoter of candidates which show high correlation with NE signature enriched H3K27Ac. These observations suggest that CRL3 is a master regulator of NE cancer and knowledge of specifically regulated CRL3 genes in NE cancer may accelerate new therapeutic approaches.

Keywords: Neuroendocrine cancer, CRL3, BTB genes, transcription factors

Introduction

Neuroendocrine (NE) cancer, arising from the malignant transformation of various types of NE cells that produce peptides and amines in almost all organs, including the pancreas, lung, prostate, and thyroid, is a heterogeneous group of rare malignancies comprising approximately 2% of all malignant cancers diagnosed in the western world [1–5]. The major characteristic of NE cancer is rather slow growth, but it tends to become more aggressive over time with high metastatic abilities and unpredictable course compared to common epithelial cancers [6,7]. Although chromogranin A (CHGA) secreted by neurons and NE cells is a well-known NE marker [8], current treatment or diagnosis options depending on CHGA levels have limitations because the induced level of CHGA has also been reported in pancreatic adenocarcinoma, hepatocellular cancer, and non-neoplastic conditions, including kidney failure, cardiovascular and inflammatory diseases, and chronic atrophic gastritis [9–11]. Therefore, additional analyses are needed to uncover new therapeutic vulnerabilities of NE cancer.

Cullin-RING ubiquitin E3 ligase (CRLs), the largest family of ubiquitin ligases, spatiotemporally controls ubiquitination of approximately 20% of cellular proteins involved in diverse cellular processes, including genome stability, DNA damage/repair, cell cycle progression, and DNA replication [12–14]. Mammalian cells contain eight classes of CRL complexes, each containing a specific central scaffold cullin protein (CUL1, CUL2, CUL3, CUL4A/B, CUL5, CUL7, and CUL9). In addition to a scaffold cullin, each CRLs is composed of a RING-containing E2-conjugating enzyme (RBX1/2) and an adaptor protein that binds to a range of specific substrate receptor [14–17]. Cullins are regarded as attractive targets for cancer therapies because cullin expression is often deregulated in many cancer types [12]. Cullins are also at the forefront of new inhibitors targeting the components of the ubiquitin proteasome system with drugs targeting NEDD8-activating enzyme (cullins are the primary substrates for NEDD8 modification). For example, pevonedistat (MLN4924) and TAS4464 are currently being tested in phase I and phase II clinical trials, respectively. MLN4924 is a small molecule inhibitor of NEDD8-activating enzyme (NAE), which covalently binds to NEDD8 to block NEDD8 conjugation to cullins, resulting in Cullin deneddylation, preventing CRL activation, and ultimately preventing the degradation of CRL substrates [18–20]. Since these drugs affect the activities of all CRLs and block neddylation of non-Cullin proteins, their use may disturb many cellular pathways leading to severe side effects. Thus, a more efficient therapeutic approach may be to target a single CRL by inhibiting specific interactions between CRLs components and/or CRLs and their substrates [21–26].

In this study, we report that CRL3 is a potential candidate for future targeted therapies for NE cancer. Our analysis using an expression profiling database revealed that CUL3 is significantly overexpressed in NE cancer. We also analyzed 151 BTB domain-containing proteins and components of CRL3 and revealed that subgroups of BTB proteins are upregulated or downregulated in NE cancer. Upregulated transcription factors involved in BTB gene expression were also identified in our screen. Thus, our findings provide a new NE cancer gene expression signature of CRL3 components that could help future targeted therapies to benefit patients with NE.

Materials and methods

Database analysis

Gene expression of CULs, BTBs, and TFs was analyzed across the Cancer Cell Line Encyclopedia (CCLE) dataset using the CellMiner cross-database (CellMinerCDB, https://discover.nci.nih.gov/cellminercdb/). The expression of these genes was also compared to that of the seven types of cancer signatures in CCLE. Gene expression of CULs, BTBs, and TFs was also analyzed across NE and non-NE cancers in SCLC, NSCLC, and other types of cancer, as well as four SCLC subtypes defined by the expression of the master transcription factors ASCL1, NEUROD1, POU2F3, and YAP1(NAPY). Gene copy number and DNA methylation of CULs, BTBs, and TFs were also analyzed in NE and non-NE cancers using the CCLE dataset. Enrichment of H3K27Ac on BTB and TF gene promoters in selected NE or non-NE SCLC cell lines covering the four SCLC subtypes was visualized using the Integrative Genomics Viewer (IGV) from published ChIP-Sequencing data (GSE115123) [27]. All data are available online.

Cell culture and siRNA

Human SCLC H69, H146, H82, and H209 for NE cancer, H211, DMS114, and H196 for non-NE cancer, and NSCLC NCI-H1299 cell lines were cultured in RPMI medium (Invitrogen, 11875–119). The human non-NE cancer cell lines osteosarcoma U2OS and SAOS2, colon cancer HCT116, myelogenous leukemia K562, prostate cancer DU145, immortalized lung fibroblast VA13/WI38, and immortalized embryonic kidney HEK293 cells were cultured in Dulbecco’s modified Eagle’s medium (Invitrogen, 11965–092). Media were supplemented with 10% heat-inactivated fetal bovine serum (FBS)(Invitrogen, 10082–147) and 1×penicillin/streptomycin (Invitrogen, 10378–016), and maintained at 37°C in 5% CO2 humidified incubator. All original cancer cell lines were obtained from ATCC (www.atcc.org) and tested negative for mycoplasma (Lonza LT07–418). The human CUL3-targeting Accell SMARTpool siRNA was purchased from Horizon Discovery (E010224). siRNA protocols were performed according to the manufacturer’s instructions using Accell siRNA Delivery media (B005000).

Quantitative real-time polymerase chain reaction (qRT-PCR)

Total RNA extraction and qRT-PCR were performed according to the manufacturer’s instructions provided by Qiagen (RNeasy R Mini Kit, 74104), Takara (PrimeScript RT Master Mix, RR036A), and Invitrogen (SYBR Green PCR Master Mix, 4309155). The expression levels of human BTB genes in the cells were determined by qRT-PCR using GAPDH as an internal control. Primer sequences are listed in Supplementary Table 1.

Colony formation assay

Two thousand H69, H146, H196, and DMS114 cells, treated with siRNA-CTL or siRNA-CUL3 for 3 days, were mixed in 1 ml RPMI medium containing 0.35% top agar and plated in a 24-well plate overlaid with the same volume of 0.5% base agar medium (Invitrogen, 16500500). The cells were incubated at 37°C in a moist atmosphere containing 5% CO2 for 3 weeks. Colonies were then stained with 0.005% crystal violet and counted using ImageJ software.

Immunoblot analysis

Whole cell lysates were immunodetected using sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE). The following primary antibodies were used: anti-CUL3 (ab75851, 1:20, 000; Abcam), anti-KCTD16 (HPA050154, 1:2, 500; Sigma), anti-α-tubulin (T9026, 1:10, 000; Sigma), and anti-histone H3 (Millipore, 07–690, 1:25,000; Millipore). Horseradish peroxidase (HRP)-linked anti-rabbit IgG (Cell Signaling, 7074, 1:5000) and HRP-linked anti-mouse IgG (Cell Signaling, 7076, 1:5000) were used as secondary antibodies according to the manufacturer’s instructions.

Results

CUL3 is upregulated in NE cancer

We first compared the expression of CULs across various cancer cell lines using the CCLE via the CellMinerCDB database. Compared to other CULs, the expression of CUL3 transcripts was highly correlated with the NE signature (Fig. 1A). Consistently, CUL3 expression was significantly higher in NE cancer than in non-NE cancer in 1,036 cancer cell lines from 22 different cancer tissues from the CCLE dataset, whereas high expression of CUL4B, CUL7, or CUL9 was observed in non-NE cancer (Fig. 1B). As previously reported, NE cancer involves the lung, brain, CNS, ovary, uterus, esophagus, stomach, thyroid, pancreas, prostate, and bowel-derived cancers (Fig. 1C). Since NE cancer contains the majority of SCLC (Fig. 1C), higher CUL3 expression was observed in SCLC than in other groups (Fig. 1D). We further divided these groups into NE signatures and found that the expression of CUL3 transcripts was observed at high levels in all NE cancer types, whereas CUL7 and CUL9 transcripts were highly expressed in non-NE cancer cells (Fig. 1D). High levels of CUL3 in NE cancer showed no clear correlation with DNA copy number or CUL3 methylation (Supplementary Fig. 1). To directly evaluate whether the proliferation of NE cancer cells was affected by CUL3 expression, we performed colony formation analysis using four SCLC cell lines in which CUL3 was depleted using CUL3-targeting siRNA. Compared to transcript expression, CUL3 protein was remarkably higher in NE-SCLC than in non-NE SCLC, and all tested SCLC cell lines were impaired in colony growth, especially prominent in NE-SCLC cell lines except for H196 cell lines (Fig. 1E–H). These results show that CUL3 is required for the proliferation of NE cancer cells and provide evidence that high levels of CUL3 can be regarded as possible biomarkers for NE cancer.

Figure 1. CUL3 is highly expressed in NE cancer.

Figure 1.

Open in a new tab

(A) Cullin 3 (CUL3) expression is highly correlated with NE signature. Expression of CUL transcripts was compared with seven types of cancer signature in all cancer dataset based on Cancer Cell Line Encyclopedia (CCLE) database using CellMinerCDB (n = 1,036 in all cancer)(NE: neuroendocrine, HRD_LOH: Homologous recombination deficiency score based on LOH regions, NtAI: Number of telomeric imbalances, LST: Large scale transition, HRD_SUM: Sum of HRD_LOH, NtAI, and LST homologous recombination deficiency signature scores, EMT: 1st principal component of non-hematopoietic cell line expression data matrix for 38 EMT genes, APM: Antigen presentation machinery transcript expression signature score). (B-D) CUL3 transcripts are highly expressed in NE cancer. Expression of transcripts for each Cullin was analyzed in NE cancer (n=72) and non-NE (n=964) cancer cell lines. Average of transcription level and P-value was indicated (B). Large portion of SCLC in NE cancer (C). Expression of Cullin transcripts was analyzed in SCLC, NSCLC and other cancer cell lines as well as divided as NE, non-NE cancer or SCLC NAPY (*p-value < 0.05, **p < 0.01. ***p < 0.001, ****p < 0.0001)(D). (E-H) CUL3 is required for NE cancer proliferation. SiRNA-CUL3 was introduced into two NE cancer including H69 and H146 or two non-NE cancer including H196 and DMS114 and colony forming ability was observed. Representative images of colony formation (E). Immunoblot analysis using CUL3 antibodies (F). Quantification of CUL3 protein expression in siRNA-CTL introduced cells (G). Quantification of images in (E) by measuring colony number as well as relative ratio of covered area from three independent experiments (*p-value < 0.05, ***p < 0.001)(H).

Subgroups of BTBs are upregulated in NE cancer

Next, we analyzed the expression levels of genes encoding BTB proteins. We first examined 151 different BTB proteins (BTB only, BTB with Zn finger, kelch, and MATH domain-containing) and performed an in silico analysis by comparing the correlation between signatures and BTBs in all cancer types based on mRNA expression levels. Among the 151 candidates, 8 BTB including KLHL8, KLHL23, KLHL32, KLHDC3, KLHL15, ZBTB18, KBTBD8 and ZBTB39, and 4 BTB including ABTB2, ZBTB4, NACC2 and KCTD11 genes showed positive and negative correlations with NE signature in all cancer cell lines, respectively (Fig. 2A), in a line with opposite expression of their transcripts in NE or non-NE cancer (Fig. 2B). These BTB genes were also highly correlated with CHGA and dihydropyrimidinase-like 5 (DPYSL5), an NE marker (Supplementary Fig. 2). In parallel with CUL3 analysis, eight BTBs that showed high correlation with the NE signature were highly expressed in SCLC than in NSCLC or other cancer types, but there were no remarkable changes between different tissues of NE cancer (Fig. 2C). NAPY analysis also showed that these BTB genes were expressed at low levels in YAP1-positive SCLC, known as non-NE SCLC (Fig. 2C). In contrast, the expression of four BTBs, which showed negative correlation with the NE signature, was prominent in NSCLC and other cancer types, especially in non-NE cell lines regardless of origin, as well as in YAP1-positive SCLC (Fig. 2C). Our further analysis showed that high levels of the eight BTBs in NE cancer generally correlated with high copy number and low DNA methylation ratio, but we could not observe a clear correlation between expression and DNA copy number or DNA methylation (Fig. 2D, E). Our analysis suggests that a subset of BTBs may be a possible biomarker for NE cancer.

Figure 2. Subgroups of BTBs are upregulated in NE cancer.

Figure 2.

Open in a new tab

(A) Subgroups of BTBs are highly correlated with NE signature. One hundred-fifty one BTB genes were collected, and correlation analysis was performed between expression of BTBs and seven types of cancer signature in CCLE dataset. 8 BTB genes showing high correlation value (R > 0.4) and 4 BTB genes which show low correlation (R < −0.4) were selected for further analysis. (B, C) Subgroups of BTB transcripts are highly expressed in NE cancer. Expression of selected BTBs was analyzed in all NE (n=72) and non-NE (n=964) cancer cell lines. Average of transcription level was indicated (****p < 0.0001)(B). Expression of selected BTBs in SCLC, NSCLC and other cancer cell lines together with NE, non-NE signature or NAPY in SCLC NAPY (*p-value < 0.05, **p < 0.01. ***p < 0.001, ****p < 0.0001)(C). (D-E) Correlation analysis between selected BTB expression score (Exp) and its DNA copy number (Cop)(D) or methylation levels (Met)(E) in NE- or non-NE cancer cell lines. Average score for DNA copy number and methylation was indicated. Pink boxes represent variables which are able to determine expression.

BTB-controlling TFs are upregulated in NE cancer database

Next, we analyzed the expression levels of transcription factors that can modulate the transcription of upregulated BTB genes in NE cancer. Transcription binding site analysis showed that 33 BTB genes highly correlated with CHGA (Pearson correlation R > 0.3) were regulated by 102 TFs (Supplementary Fig. 3). Among these 102 TFs, 7 TFs including PAX5, HSF2, POU2F1, TCF4, E2F2, MYEF2 and ZBTB18 show high correlation with NE signature whereas 4 TFs that involve FOXQ1, PPARG, TGIF1 and AHR negatively correlated with NE signature (Fig. 3A). Consistently, these TF candidates showed high and low expression in the NE and non-NE cancer cell lines, respectively (Fig. 3B). Next, we analyzed the enrichment pattern of H3K27Ac, which is associated with high transcriptional activation across NE-SCLC and non-NE SCLC cell lines using the published ChIP-Sequencing dataset [27]. Importantly, upregulated TF PAX5 showed higher H3K27Ac promoter signals in NE-SCLC than in non-NE SCLC although remarkable enrichment of H3K27Ac was also observed in non-NE SCLC (Fig. 3C, upper panel). The TGIF1 gene promoter also showed H3K27Ac signals in NE-SCLC, but the signal intensity was higher in non-NE SCLC, except for DMS79 cell lines (Fig. 3C, bottom panel).

Figure 3. BTB-controlling TFs are upregulated in NE cancer database.

Figure 3.

Open in a new tab

(A) BTB-controlling TFs are highly correlated with NE signature. One hundred-two TFs which have recognition sequences on promoter of BTB genes which show highly correlated with CHGA (Pearson correlation R > 0.3) were collected and were compared their expression with seven types of cancer signature in CCLE dataset. 7 TF genes showing high correlation value (R > 0.4) and 4 TF genes which show low correlation (R < −0.4) were selected for further analysis. (B) TF transcripts are highly expressed in NE cancer. Expression of selected TFs was analyzed in all NE (n=72) and non-NE (n=964) cancer cell lines. Average of transcription level was indicated (****p < 0.0001). (C) H3K27Ac ChIP-Sequencing tracks on PAX5 or TGIF1 gene promoter in three NE cancer (H146, H526 and DMS79) and in two non-NE cancer (DMS114 and H1048) were visualized by Integrative Genomics Viewer browser. (D-E) Correlation analysis between TFs expression score (Exp) and its DNA copy number (Cop)(D) or methylation levels (Met)(E) in NE- or non-NE cancer cell lines. Average score for DNA copy number and methylation was indicated. Pink boxes represent variables which are able to determine expression.

Our further analysis showed that differential expression of 11 TFs candidates in NE cancer had no clear correlation with DNA copy number and promoter methylation, although upregulated PAX5 and TCF4 generally correlated with high copy number and low DNA methylation ratio (Fig. 3D, E). Although more comprehensive studies are needed, our analysis suggests that TFs that may be responsible for BTB transcription are also upregulated in NE cancer.

A subset of BTB genes show high H3K27 acetylation in promoter regions

Our analyses revealed that subgroups of BTB genes and TFs that could control their transcription were upregulated in NE cancer. In parallel with the above analysis, we analyzed the H3K27Ac enrichment pattern across the four types of SCLC cell lines, including NE and non-NE signatures, using the published ChIP-Sequencing dataset [27]. Importantly, upregulated BTB genes, including KBTBD8 and KLHL32, showed high H3K27Ac promoter signals in NE-SCLC including ASCL1 and NEUROD1-expressing SCLC cell lines, even though non-NE SCLC, including POU2F3 and YAP1-expressing SCLC also showed distinct H3K27Ac signals (Supplementary Fig. 4A). Similarly, H3K27Ac was enriched in the KCTD16 promoter of a subset of NE-SCLC cell lines (H69, H146, and H446)(Fig. 4A). The latter observation was validated by immunoblotting for KCTD16 in 14 cell lines, including H69, H82, H211, and DMS114, which showed that both H69 and H146 had the highest levels of this protein (Fig. 4B). In contrast, KLHL16, which showed a negative correlation with the NE signature, did not possess H3K27Ac peaks on its promoter, but remarkable enrichment of H3K27Ac was observed in DMS114 cell lines (Supplementary Fig. 4A). To validate our analysis, we selected 12 BTB genes by correlating them with the NE signature (11 BTBs for positive correlation vs. KLHL16 for negative correlation), and performed quantitative real-time PCR on a set of 13 representative cancer cell lines including six SCLC (NE-SCLC:3 ASCL1-positive: H69, H146, and H209; 1 NEUROD1-positive: H82; non-NE SCLC:1 POU2F3-positive: H211; 1 YAP1-positive: DMS114), other origins of non-NE cancer cell lines that include 1 NSCLC (H1299), 1 osteosarcoma (U2OS), 1 colon cancer (HCT116), 1 erythroleukemia (K562), 1 prostate cancer (DU145), and 2 immortalized normal cell lines (lung fibroblast VA13/WI38, human embryonic kidney HEK293). Consistent with our analysis, the identified upregulated BTB genes generally showed higher real-time PCR signals in NE-SCLC, whereas transcripts in DMS114 were relatively lower than those in NE-SCLC, except for another non-NE H211 (Fig. 4C and Supplementary Fig. 4B). In contrast, the transcription signal of KLHL16, the BTB that did not show a positive correlation with the NE signature, was comparable between all the cell lines (Supplementary Fig. 4B). Taken together, our in silico analysis and validation provides new evidence of upregulated CRL3 components in NE cancer and could pinpoint the specific role of this CRL complex in NE cancer.

Figure 4. A subset of BTB genes show high H3K27 acetylation in promoter regions.

Figure 4.

Open in a new tab

(A) H3K27Ac ChIP-Sequencing tracks on KCTD16 gene promoter from the NE cancer that includes ASCL1-positive (DMS79, H510, H69 and H146), NEUROD1-positive (H446, H524 and H82), and POU2F3-positive (H526), or non-NE cancer including POU2F3-positive (H1048 and H211) and YAP1-positive DMS114 cell lines in published ChIP-Sequencing dataset (GSE115123). Enrichment of H3K27Ac was visualized by Integrative Genomics Viewer browser. (B) KCTD16 protein is highly expressed in subset of NE cancer cell lines. Immunoblot analysis with antibodies against KCTD16 was performed and quantification of KCTD16 protein expression was represented as relative density by normalizing KCTD16 level in U2OS cell line. Average of KCTD16 level was indicated. Histone H3 was used for loading control (****p-value < 0.0001). (C) High transcriptional expression of selected BTB genes in NE cancer cell lines. Transcript level of selected BTB genes (KLHL8, KLHL23, KLHL32, ZBTB18, KBTBD8 and KCTD16) was examined by qRT-PCR using 3 different primer set in various cancer cell lines that includes 4 NE and 9 non-NE cancer cell lines. GAPDH was used as an endogenous control, and relative expression of each transcription level was normalized by the each BTB transcription level in U2OS cell line. Average of transcription level was indicated. All error bars represent the standard deviation (*p-value < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001, n.s.; not significant). (D) Highly expressed BTB proteins mediated by its specific TFs that also induced in NE or non-NE cancer are incorporated into CRL3, followed by recognition and ubiquitination of multiple effector proteins that promote survival in NE or non-NE cancer, respectively. Schematic model represents components in TFs-BTBs-CRL3 axis as a putative NE cancer biomarkers.

Discussion

CRL3 plays key roles in a myriad of biological processes, such as mitosis, regulation of cell cycle, antioxidant response, apoptosis, and vesicle trafficking [28]. Therefore, CRL deregulation is expected to cause uncontrolled proliferative diseases, such as cancer. While it is thought that over 400 CRL complexes may exist, only a few components of CRLs have been well studied for their involvement in cancer. Therefore, a better understanding of how different CRL components is distributed in cancer may help to develop new therapeutic tools against specific cancer types. For example, molecular tools can be used to inhibit specific interactions between the components of CRL that is highly expressed in cancer. While other CRLs have distinct substrate adaptors and receptors, CRL3 is unique among CRLs using BTB domain-containing proteins as both substrate adaptors and receptors [12]. The BTB domain proteins include Kelch-like (KLHL) proteins, zinc finger and BTB domain (ZBTB) proteins, and potassium channel tetramerization domain (KCTD) proteins. While 114 of the 188 BTB proteins are predicted to bind CUL3 [29], at least 38 of these proteins may be part of the CRL3 complex [28]. Because additional BTB proteins may be reported to be part of CRL3 in the future, we considered including all BTB proteins in our screen.

This study showed that potential components of CRL3 (i.e., CUL3, a subset of BTB and TFs that regulate their transcription) are upregulated in NE cancer, while others are under expression (Fig. 4D). Consistent with our analysis, previous studies have reported strong expression of the transcription factors PAX5 and POU3F2 in SCLC [30,31]. Most importantly, substantial PAX5 expression has been noted in tumors of NE origin, such as SCLC and neuroblastoma, with aggressive neuroblastoma showing the highest levels [32]. Interestingly, PAX5 is a direct transcriptional activator of the receptor tyrosine kinase c-Met, a protein that is also overexpressed in SCLC and plays a significant role in lung tumorigenesis and metastasis [33,34]. POU3F2 is involved in neuronal migration during development [35]. Thus, it would be interesting to determine whether POU3F2 is involved in NE cancer proliferation, migration, and metastasis.

Our screen revealed a subgroup of BTB genes that were specifically upregulated in NE cancer (Fig. 4D).While a comprehensive analysis of the role of different BTB proteins in different cancer types is unavailable, the roles of several BTB proteins in cancer have been identified in the past. For example, the high expression of KLHL20 in prostate cancer is linked to its anti-apoptotic function by inducing proteasomal degradation of death-associated protein kinase (DAPK) [36–42]. Speckle type BTB/POZ protein (SPOP) is significantly upregulated in renal cell carcinoma (RCC), and its expression is positively correlated with cancer metastasis [43]. SPOP-containing CRL3 promotes ubiquitination and proteasomal degradation of various tumor suppressors, including PTEN, DUSP7, GLI2, and DAXX, facilitating proliferation and blocking apoptosis in RCC cells [44]. Both KLHL20 and SPOP expression are mediated by hypoxia-inducible factor-1α (HIF-1α), which promotes carcinogenesis [44–46]. The most comprehensive role of CRL3 in cancer comes from the adaptor Kelch Like ECH Associated protein 1 (KEAP1). KEAP1 brings the transcription factor nuclear factor erythroid 2-related factor 2 (NRF2) to CRL3 to promote its ubiquitylation and subsequent degradation by the 26S proteasome [47]. NRF2 is a key player in cellular antioxidant responses [28]. NRF2 controls the expression of over 200 genes that regulate survival, proliferation, DNA repair, redox homeostasis, energy metabolism, iron metabolism, amino acid metabolism, proteasomal degradation, and mitochondrial physiology, among others [48,49]. Studies profiling lung tumors found that KEAP1 was mutated in 11.3%–19% of cases [50,51]. Future studies should investigate whether these BTB genes are involved in the proliferation of NE cancer. Our findings uncover CRL3 targets in NE cancer, laying the foundation for new therapeutic strategies.

Supplementary Material

1
2
3
4

Highlights.

  • Cullin 3 is highly expressed in neuroendocrine cancer

  • Subgroups of BTBs are highly expressed in neuroendocrine cancer

  • Multiple modules in the transcription factors-BTBs-CRL3 axis are promising novel biomarkers in neuroendocrine cancer

Acknowledgements

This work was supported by a National Research Foundation of Korea (NRF) grant funded by the Korean government (MSIT)(NRF-2021R1C1C1004165). We would like to thank Editage (www.editage.co.kr) for English language editing.

Footnotes

Publisher's Disclaimer: This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

Conflict of Interest

The authors have no potential conflict of interest to declare in this paper.

References

  • [1].Basu B, Sirohi B, Corrie P, Systemic therapy for neuroendocrine tumours of gastroenteropancreatic origin, Endocr Relat Cancer 17 (2010) R75–90. 10.1677/ERC-09-0108. [DOI] [PubMed] [Google Scholar]
  • [2].DeLellis RA, The neuroendocrine system and its tumors: an overview, Am J Clin Pathol 115 Suppl (2001) S5–16. 10.1309/7GR5-L7YW-3G78-LDJ6. [DOI] [PubMed] [Google Scholar]
  • [3].Falkmer S, Phylogeny and ontogeny of the neuroendocrine cells of the gastrointestinal tract, Endocrinol Metab Clin North Am 22 (1993) 731–752. [PubMed] [Google Scholar]
  • [4].Hofsli E, Thommesen L, Yadetie F, Langaas M, Kusnierczyk W, Falkmer U, Sandvik AK, Laegreid A, Identification of novel growth factor-responsive genes in neuroendocrine gastrointestinal tumour cells, Br J Cancer 92 (2005) 1506–1516. 10.1038/sj.bjc.6602535. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [5].Wick MR, Neuroendocrine neoplasia. Current concepts, Am J Clin Pathol 113 (2000) 331–335. 10.1309/ETJ3-QBUK-13QD-J8FP. [DOI] [PubMed] [Google Scholar]
  • [6].Wang Z, Howell RM, Burgett EA, Kry SF, Hertel NE, Salehpour M, Calibration of indium response functions in an Au-In-BSE system up to 800 MeV, Radiat Prot Dosimetry 139 (2010) 565–573. 10.1093/rpd/ncp282. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [7].Van Eeden S, Quaedvlieg PF, Taal BG, Offerhaus GJ, Lamers CB, Van Velthuysen ML, Classification of low-grade neuroendocrine tumors of midgut and unknown origin, Hum Pathol 33 (2002) 1126–1132. 10.1053/hupa.2002.129204. [DOI] [PubMed] [Google Scholar]
  • [8].Taupenot L, Harper KL, O’Connor DT, The chromogranin-secretogranin family, N Engl J Med 348 (2003) 1134–1149. 10.1056/NEJMra021405. [DOI] [PubMed] [Google Scholar]
  • [9].Lawrence B, Gustafsson BI, Kidd M, Pavel M, Svejda B, Modlin IM, The clinical relevance of chromogranin A as a biomarker for gastroenteropancreatic neuroendocrine tumors, Endocrinol Metab Clin North Am 40 (2011) 111–134, viii. 10.1016/j.ecl.2010.12.001. [DOI] [PubMed] [Google Scholar]
  • [10].Malaguarnera M, Cristaldi E, Cammalleri L, Colonna V, Lipari H, Capici A, Cavallaro A, Beretta M, Alessandria I, Luca S, Motta M, Elevated chromogranin A (CgA) serum levels in the patients with advanced pancreatic cancer, Arch Gerontol Geriatr 48 (2009) 213–217. 10.1016/j.archger.2008.01.014. [DOI] [PubMed] [Google Scholar]
  • [11].Modlin IM, Gustafsson BI, Moss SF, Pavel M, Tsolakis AV, Kidd M, Chromogranin A--biological function and clinical utility in neuro endocrine tumor disease, Ann Surg Oncol 17 (2010) 2427–2443. 10.1245/s10434-010-1006-3. [DOI] [PubMed] [Google Scholar]
  • [12].Jang SM, Redon CE, Aladjem MI, Chromatin-Bound Cullin-Ring Ligases: Regulatory Roles in DNA Replication and Potential Targeting for Cancer Therapy, Front Mol Biosci 5 (2018) 19. 10.3389/fmolb.2018.00019. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [13].Jang SM, Redon CE, Thakur BL, Bahta MK, Aladjem MI, Regulation of cell cycle drivers by Cullin-RING ubiquitin ligases, Exp Mol Med 52 (2020) 1637–1651. 10.1038/s12276-020-00508-4. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [14].Sarikas A, Hartmann T, Pan ZQ, The cullin protein family, Genome Biol 12 (2011) 220. 10.1186/gb-2011-12-4-220. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [15].Bulatov E, Ciulli A, Targeting Cullin-RING E3 ubiquitin ligases for drug discovery: structure, assembly and small-molecule modulation, Biochem J 467 (2015) 365–386. 10.1042/BJ20141450. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [16].Bennett EJ, Rush J, Gygi SP, Harper JW, Dynamics of cullin-RING ubiquitin ligase network revealed by systematic quantitative proteomics, Cell 143 (2010) 951–965. 10.1016/j.cell.2010.11.017. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [17].Lydeard JR, Schulman BA, Harper JW, Building and remodelling Cullin-RING E3 ubiquitin ligases, EMBO Rep 14 (2013) 1050–1061. 10.1038/embor.2013.173. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [18].Soucy TA, Smith PG, Milhollen MA, Berger AJ, Gavin JM, Adhikari S, Brownell JE, Burke KE, Cardin DP, Critchley S, Cullis CA, Doucette A, Garnsey JJ, Gaulin JL, Gershman RE, Lublinsky AR, McDonald A, Mizutani H, Narayanan U, Olhava EJ, Peluso S, Rezaei M, Sintchak MD, Talreja T, Thomas MP, Traore T, Vyskocil S, Weatherhead GS, Yu J, Zhang J, Dick LR, Claiborne CF, Rolfe M, Bolen JB, Langston SP, An inhibitor of NEDD8-activating enzyme as a new approach to treat cancer, Nature 458 (2009) 732–736. 10.1038/nature07884. [DOI] [PubMed] [Google Scholar]
  • [19].Brownell JE, Sintchak MD, Gavin JM, Liao H, Bruzzese FJ, Bump NJ, Soucy TA, Milhollen MA, Yang X, Burkhardt AL, Ma J, Loke HK, Lingaraj T, Wu D, Hamman KB, Spelman JJ, Cullis CA, Langston SP, Vyskocil S, Sells TB, Mallender WD, Visiers I, Li P, Claiborne CF, Rolfe M, Bolen JB, Dick LR, Substrate-assisted inhibition of ubiquitin-like protein-activating enzymes: the NEDD8 E1 inhibitor MLN4924 forms a NEDD8-AMP mimetic in situ, Mol Cell 37 (2010) 102–111. 10.1016/j.molcel.2009.12.024. [DOI] [PubMed] [Google Scholar]
  • [20].Yoshimura C, Muraoka H, Ochiiwa H, Tsuji S, Hashimoto A, Kazuno H, Nakagawa F, Komiya Y, Suzuki S, Takenaka T, Kumazaki M, Fujita N, Mizutani T, Ohkubo S, TAS4464, A Highly Potent and Selective Inhibitor of NEDD8-Activating Enzyme, Suppresses Neddylation and Shows Antitumor Activity in Diverse Cancer Models, Mol Cancer Ther 18 (2019) 1205–1216. 10.1158/1535-7163.MCT-18-0644. [DOI] [PubMed] [Google Scholar]
  • [21].Zheng N, Schulman BA, Song L, Miller JJ, Jeffrey PD, Wang P, Chu C, Koepp DM, Elledge SJ, Pagano M, Conaway RC, Conaway JW, Harper JW, Pavletich NP, Structure of the Cul1-Rbx1-Skp1-F boxSkp2 SCF ubiquitin ligase complex, Nature 416 (2002) 703–709. 10.1038/416703a. [DOI] [PubMed] [Google Scholar]
  • [22].Skaar JR, Pagan JK, Pagano M, Mechanisms and function of substrate recruitment by F-box proteins, Nat Rev Mol Cell Biol 14 (2013) 369–381. 10.1038/nrm3582. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [23].Zimmerman ES, Schulman BA, Zheng N, Structural assembly of cullin-RING ubiquitin ligase complexes, Curr Opin Struct Biol 20 (2010) 714–721. 10.1016/j.sbi.2010.08.010. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [24].Harper JW, Tan MK, Understanding cullin-RING E3 biology through proteomics-based substrate identification, Mol Cell Proteomics 11 (2012) 1541–1550. 10.1074/mcp.R112.021154. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [25].Pintard L, Willems A, Peter M, Cullin-based ubiquitin ligases: Cul3-BTB complexes join the family, EMBO J 23 (2004) 1681–1687. 10.1038/sj.emboj.7600186. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [26].Stogios PJ, Downs GS, Jauhal JJ, Nandra SK, Prive GG, Sequence and structural analysis of BTB domain proteins, Genome Biol 6 (2005) R82. 10.1186/gb-2005-6-10-r82. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [27].Huang YH, Klingbeil O, He XY, Wu XS, Arun G, Lu B, Somerville TDD, Milazzo JP, Wilkinson JE, Demerdash OE, Spector DL, Egeblad M, Shi J, Vakoc CR, POU2F3 is a master regulator of a tuft cell-like variant of small cell lung cancer, Genes Dev 32 (2018) 915–928. 10.1101/gad.314815.118. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [28].Wang P, Song J, Ye D, CRL3s: The BTB-CUL3-RING E3 Ubiquitin Ligases, Adv Exp Med Biol 1217 (2020) 211–223. 10.1007/978-981-15-1025-0_13. [DOI] [PubMed] [Google Scholar]
  • [29].Zhuang M, Calabrese MF, Liu J, Waddell MB, Nourse A, Hammel M, Miller DJ, Walden H, Duda DM, Seyedin SN, Hoggard T, Harper JW, White KP, Schulman BA, Structures of SPOP-substrate complexes: insights into molecular architectures of BTB-Cul3 ubiquitin ligases, Mol Cell 36 (2009) 39–50. 10.1016/j.molcel.2009.09.022. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [30].Kanteti R, Nallasura V, Loganathan S, Tretiakova M, Kroll T, Krishnaswamy S, Faoro L, Cagle P, Husain AN, Vokes EE, Lang D, Salgia R, PAX5 is expressed in small-cell lung cancer and positively regulates c-Met transcription, Lab Invest 89 (2009) 301–314. 10.1038/labinvest.2008.168. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [31].Ishii J, Sato H, Yazawa T, Shishido-Hara Y, Hiramatsu C, Nakatani Y, Kamma H, Class III/IV POU transcription factors expressed in small cell lung cancer cells are involved in proneural/neuroendocrine differentiation, Pathol Int 64 (2014) 415–422. 10.1111/pin.12198. [DOI] [PubMed] [Google Scholar]
  • [32].Baumann Kubetzko FB, Di Paolo C, Maag C, Meier R, Schafer BW, Betts DR, Stahel RA, Himmelmann A, The PAX5 oncogene is expressed in N-type neuroblastoma cells and increases tumorigenicity of a S-type cell line, Carcinogenesis 25 (2004) 1839–1846. 10.1093/carcin/bgh190. [DOI] [PubMed] [Google Scholar]
  • [33].Rygaard K, Nakamura T, Spang-Thomsen M, Expression of the proto-oncogenes c-met and c-kit and their ligands, hepatocyte growth factor/scatter factor and stem cell factor, in SCLC cell lines and xenografts, Br J Cancer 67 (1993) 37–46. 10.1038/bjc.1993.7. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [34].Olivero M, Rizzo M, Madeddu R, Casadio C, Pennacchietti S, Nicotra MR, Prat M, Maggi G, Arena N, Natali PG, Comoglio PM, Di Renzo MF, Overexpression and activation of hepatocyte growth factor/scatter factor in human non-small-cell lung carcinomas, Br J Cancer 74 (1996) 1862–1868. 10.1038/bjc.1996.646. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [35].McEvilly RJ, de Diaz MO, Schonemann MD, Hooshmand F, Rosenfeld MG, Transcriptional regulation of cortical neuron migration by POU domain factors, Science 295 (2002) 1528–1532. 10.1126/science.1067132. [DOI] [PubMed] [Google Scholar]
  • [36].Yuan WC, Lee YR, Huang SF, Lin YM, Chen TY, Chung HC, Tsai CH, Chen HY, Chiang CT, Lai CK, Lu LT, Chen CH, Gu DL, Pu YS, Jou YS, Lu KP, Hsiao PW, Shih HM, Chen RH, A Cullin3-KLHL20 Ubiquitin ligase-dependent pathway targets PML to potentiate HIF-1 signaling and prostate cancer progression, Cancer Cell 20 (2011) 214–228. 10.1016/j.ccr.2011.07.008. [DOI] [PubMed] [Google Scholar]
  • [37].Eisenberg-Lerner A, Kimchi A, DAP kinase regulates JNK signaling by binding and activating protein kinase D under oxidative stress, Cell Death Differ 14 (2007) 1908–1915. 10.1038/sj.cdd.4402212. [DOI] [PubMed] [Google Scholar]
  • [38].Eisenberg-Lerner A, Kimchi A, PKD is a kinase of Vps34 that mediates ROS-induced autophagy downstream of DAPk, Cell Death Differ 19 (2012) 788–797. 10.1038/cdd.2011.149. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [39].Inbal B, Bialik S, Sabanay I, Shani G, Kimchi A, DAP kinase and DRP-1 mediate membrane blebbing and the formation of autophagic vesicles during programmed cell death, J Cell Biol 157 (2002) 455–468. 10.1083/jcb.200109094. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [40].Inbal B, Cohen O, Polak-Charcon S, Kopolovic J, Vadai E, Eisenbach L, Kimchi A, DAP kinase links the control of apoptosis to metastasis, Nature 390 (1997) 180–184. 10.1038/36599. [DOI] [PubMed] [Google Scholar]
  • [41].Kuo JC, Wang WJ, Yao CC, Wu PR, Chen RH, The tumor suppressor DAPK inhibits cell motility by blocking the integrin-mediated polarity pathway, J Cell Biol 172 (2006) 619–631. 10.1083/jcb.200505138. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [42].Lee YR, Yuan WC, Ho HC, Chen CH, Shih HM, Chen RH, The Cullin 3 substrate adaptor KLHL20 mediates DAPK ubiquitination to control interferon responses, EMBO J 29 (2010) 1748–1761. 10.1038/emboj.2010.62. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [43].Zhao W, Zhou J, Deng Z, Gao Y, Cheng Y, SPOP promotes tumor progression via activation of beta-catenin/TCF4 complex in clear cell renal cell carcinoma, Int J Oncol 49 (2016) 1001–1008. 10.3892/ijo.2016.3609. [DOI] [PubMed] [Google Scholar]
  • [44].Li G, Ci W, Karmakar S, Chen K, Dhar R, Fan Z, Guo Z, Zhang J, Ke Y, Wang L, Zhuang M, Hu S, Li X, Zhou L, Li X, Calabrese MF, Watson ER, Prasad SM, Rinker-Schaeffer C, Eggener SE, Stricker T, Tian Y, Schulman BA, Liu J, White KP, SPOP promotes tumorigenesis by acting as a key regulatory hub in kidney cancer, Cancer Cell 25 (2014) 455–468. 10.1016/j.ccr.2014.02.007. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [45].Keith B, Johnson RS, Simon MC, HIF1alpha and HIF2alpha: sibling rivalry in hypoxic tumour growth and progression, Nat Rev Cancer 12 (2011) 9–22. 10.1038/nrc3183. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [46].Semenza GL, Hypoxia-inducible factors in physiology and medicine, Cell 148 (2012) 399–408. 10.1016/j.cell.2012.01.021. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [47].Furukawa M, Xiong Y, BTB protein Keap1 targets antioxidant transcription factor Nrf2 for ubiquitination by the Cullin 3-Roc1 ligase, Mol Cell Biol 25 (2005) 162–171. 10.1128/MCB.25.1.162-171.2005. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [48].Zhu M, Fahl WE, Functional characterization of transcription regulators that interact with the electrophile response element, Biochem Biophys Res Commun 289 (2001) 212–219. 10.1006/bbrc.2001.5944. [DOI] [PubMed] [Google Scholar]
  • [49].de la Vega M. Rojo, Chapman E, Zhang DD, NRF2 and the Hallmarks of Cancer, Cancer Cell 34 (2018) 21–43. 10.1016/j.ccell.2018.03.022. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [50].Cancer N Genome Atlas Research, Comprehensive molecular profiling of lung adenocarcinoma, Nature 511 (2014) 543–550. 10.1038/nature13385. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [51].Frank R, Scheffler M, Merkelbach-Bruse S, Ihle MA, Kron A, Rauer M, Ueckeroth F, Konig K, Michels S, Fischer R, Eisert A, Fassunke J, Heydt C, Serke M, Ko YD, Gerigk U, Geist T, Kaminsky B, Heukamp LC, Clement-Ziza M, Buttner R, Wolf J, Clinical and Pathological Characteristics of KEAP1- and NFE2L2-Mutated Non-Small Cell Lung Carcinoma (NSCLC), Clin Cancer Res 24 (2018) 3087–3096. 10.1158/1078-0432.CCR-17-3416. [DOI] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

1
NIHMS1848685-supplement-1.xlsx (11KB, xlsx)
2
NIHMS1848685-supplement-2.xlsx (6.6MB, xlsx)
3
NIHMS1848685-supplement-3.pdf (16.8MB, pdf)
4
NIHMS1848685-supplement-4.docx (16.5KB, docx)

RESOURCES