The genetic alterations of rectal neuroendocrine tumor and indications for therapy and prognosis: a systematic review

Abstract

Neuroendocrine tumors (NETs) are a type of rare tumor that can occur at multiple organs. Rectal NETs are the most common NETs in gastrointestinal tract. Due to the rarity of rectal NETs in rectal cancer, the molecular features and the correlation with patient therapeutic response and prognosis have not been investigated in detail. In this review, we focused on the molecular features, potential therapeutic targets and prognosis of rectal NETs. By summarizing the relevant studies, we established the mutational landscape of rectal NETs and identified a series of large fragment variations. Driver genes including TP53, APC, KRAS, BRAF, RB1, CDKN2A and PTEN were found as the top mutated genes. Large fragment alterations mainly involved known driver genes, including APC, TP53, CCNE1, MYC, TERT, RB1 and ATM. Germline mutations of APC, MUTYH, MSH6, MLH1 and MSH2 associated with Lynch syndrome or FAP were also found in rectal NETs. The BRAF-V600E mutation was reported as an actionable target in rectal NETs, and the combined BRAF/MEK inhibitors were found to be effective targeting BRAF-V600E in advanced or metastatic NETs. The known prognostic risk factors of rectal adenocarcinoma, including a series of demographic and clinicopathological factors were also prognostic factors for rectal NETs. Furthermore, three types of markers, including genetic alterations, protein expression levels and methylation, were also suggested as prognostic factors for rectal NETs. In summary, we established the landscape of mutations and large-fragment alterations of rectal NETs, and identified potential therapeutic targets and a series of prognostic factors. Future studies may focus on the optimization of therapeutic strategies based on potential actionable biomarkers.

NEUROENDOCRINE TUMORS (NETs) originate from neuroendocrine cells and are a type of rare tumors with high heterogeneity. According to statistics from the SEER database, in the United States, the annual incidence of NETs increased from 1.09/100,000 in 1973 to 5.25/100,000 in 2004 [1]. The incidence of NETs varies among ethnic groups. The incidence of rectal NETs is 4.99 times higher among Asians, including Chinese, compared with non-Asians [2]. NETs can be found in many organs, and the gastrointestinal tract is one of the most common sites of NETs, accounting for approximately 50.6% of all NETs. The rectum is the most common site of NETs in the gastrointestinal tract [1]. A recent epidemiological report from Japan showed that rectal NETs account for 60%–89% of all gastrointestinal NETs [3]. A single-center retrospective analysis in South Korea showed that the rectum is the most prevalent site of NETs in the digestive tract, accounting for 55.8% of NETs in the gastrointestinal tract [4].

NETs can be divided into the well-differentiated neuroendocrine tumor (NET), poorly differentiated neuroendocrine carcinoma (NEC), and mixed adeno-neuroendocrine carcinoma (MANEC, with both adenocarcinoma and neuroendocrine carcinoma) based on the degree of pathological differentiation [5]. Each type accounts for more than 30% of all NETs. Based on the pathological mitotic status and Ki-67 expression in immunohistochemistry, NETs can be divided into three grades, namely G1, G2, and G3 [6]. In recent years, immunohistochemistry has played an irreplaceable role in the diagnosis of NETs, among which synapsin (Syn) and chromogranin A (CgA) can help to determine the neuroendocrine properties of tumors [7]. At present, most cases of rectal NETs are confirmed by endoscopic diagnosis and immunohistochemical examinations.

Rectal NETs account for 0.7%–1.3% of rectal tumors. The proportion of male and female patients with rectal NETs is equal. Tumors are most common between the ages of 40 and 70 [8]. Patients with inflammatory bowel disease (IBD) are more likely to develop NETs [9]. The association between neuroendocrine neoplasms and IBD is suggested by the finding of increased number of neuroendocrine cells in the inflamed mucosa. Long-standing mucosa inflammation may be responsible for the development of pancellular dysplasia involving epithelial, goblet, Paneth and neuroendocrine cells [10-13]. Tumor size is the most significant prognostic indicator. Metastasis rarely occurs in patients with a tumor diameter of <1 cm (metastasis incidence of 0%–3%). The rate of metastasis in 1–1.9 cm tumors is 10%–15% [14]. Local lymph node metastasis or liver metastasis occurs in 60%–100% of patients with a tumor size of ≥2 cm. Metastatic sites include the lungs, liver, lymph nodes, bone, skull, and endocrine organs [14]. The main therapeutic strategy for rectal NETs is surgery. Due to the high heterogeneity and clonal expansion of rectal NET, 40%–50% of patients with rectal NETs have distant metastasis at the time of diagnosis [14]. Somatostatin analogs, targeted drugs, chemotherapeutic agents, and peptide receptor radionuclide therapy should be applied comprehensively in clinical practice, especially for advanced and unresectable tumors [15].

Due to the low incidence of rectal NETs among all rectal cancers, its molecular characteristics have not been investigated systematically and in detail in a large sample size. Current findings on the molecular landscape of rectal NETs are fragmented, because of high heterogeneity and multiple pathological classifications. Moreover, the significance of molecular characteristics in the treatment and prognosis of NETs is not clear. Thus, this review aims to summarize the molecular features of rectal NETs, identify the targetable signaling pathways, and suggest markers for the tumor therapeutic response and prognosis.

The mutational landscape of rectal NETs

To obtain a deep insight into the molecular characteristics of rectal NET, we have summarized recent findings about the main mutations reported in the literature in Table 1, including the list of mutated genes, mutation frequency (rate) in each study, and the number of subjects involved. The mutational frequency of the main driver genes has been summarized in Table 2. Comprehensive molecular characterization of rectal NETs depends on the development of NGS technology. To find the potential treatments of rectal NETs before the large-scale use of NGS, researchers searched for known specific mutations using PCR, Sanger’s sequencing, or array-based methods [16]. This mainly involved the search for BRAF mutations because BRAF mutations were suggested to be present in rectal NEC. Table 1 shows that BRAF mutations were reported in 9 out of 11 studies. Predominantly V600E, followed by D594G, and other rare sites have been implicated in rectal NETs [17-27]. Although the sample size of these studies varied, the frequency of BRAF mutations exhibited high consistency, ranging from 7.1% to 33.3%, with a median of 9% and a mean of 14.7%, Table 2 [17-19, 21-24, 26, 27]. It appears that the BRAF mutation in rectal NETs is not prevalent, and only a small proportion of patients with the mutation may benefit from BRAF-related targeted drugs (please refer to the section “Potential targeted therapies for rectal NETs” for details). In addition, BRAF mutations are present not only in benign tumor (NET) but also in malignant tumor (NEC) [17-19, 21-24, 26, 27], indicating its presence throughout tumor development. Since the BRAF gene is a known driver gene in cancer, these observations suggest that BRAF mutations may only be one of the factors for tumor development, and other factors, possibly other driver genes or large fragment alterations may also be involved in tumor development.

Table 1 The status of main mutations identified in literatures on rectal NETs

Main mutated genes	Mutation rate of main driver genes	Total number of subjects	Publication year	Reference number
BRAF V600E	9.1%	33	2015	17
BRAF V600E	9.0%	108	2016	18
SMARCB1, TP53, STK11, RET, BRAF	SMARCB1 (14.3%), TP53 (14.3%), STK11 (7.1%), RET (7.1%), BRAF (7.1%)	14	2016	19
ADAM9, MAT2A, RABEP1, SLC11A2, SMARCA1, and OBSL1	n/a	n/a	2016	20
BRAF V600E and D594G	V600E (33.3%); D594G (11.1%)	9	2017	21
RB1, TP53, APC	Group1: RB1 (11/14, 79%), TP53 (8/14, 57%), APC (10/14, 71%), and KRAS (5/14, 36%) or BRAF (1/14, 7%) Group2: RB1 (0/4, 0%), TP53 (4/4, 100%), APC (2/4.50%). Group3: RB1 (0/7, 0%), TP53 (0/7, 0%)	Group1: 14; Group2: 4; Group3: 7	2018	22
BRAF V600E	n/a	2	2018	23
BRAF V600E	n/a	3	2019	24
TP53, PTEN, CDKN2A, FBXW7, AKT1, KIT, SMAD4, ALK, VHL, IDH1	TP53 (7/69, 10.1%), FBXW7 (5/69, 7.2%), PTEN (4/69, 5.8%), CDKN2A (4/69, 5.8%)	69	2019	25
BRAF, KRAS, NRAS, TP53, RB1, APC, PIK3CA, PTEN, CDKN2A, SMAD4, FBXW7	BRAF (7/30, 23.3%), RAS (16/30, 53.3%), TP53 (13/30, 43%), RB1 (14/30, 46.7%), APC (11/30, 36.7%), PIK3CA (3/30, 10%), PTEN (1/30, 3.3%), CDKN2A (1/30, 3.3%)	30	2021	26
TP53, APC, FBXW7, KRAS, KMT2D, NF1, EPHA3, SOX9, BRAF	TP53 (61%), APC (53%), FBXW7 (25%), KRAS (25%), KMT2D, NF1, EPHA3, SOX9 and BRAF (8–14%)	36	2021	27

NETs: neuroendocrine tumors; n/a: not applicable

Table 2 Summary of mutational frequency of the main driver genes in NET

Reference number	BRAF	TP53	APC	KRAS	RB1	CDKN2A	PTEN
17	9.1%
18	9.0%
19	7.1%	14.3%
21	33.3%
22	7.0%	57.0%	71%	36%	79%
25		10.1%				5.8%	5.8%
26	23.3%	43.0%	36.7%	53.3%	46.7%	3.3%	3.3%
27	14%	61%	53%	25%
Mean	14.7%	37.1%	53.6%	38.1%	62.9%	4.6%	4.6%

NGS technology makes it possible to study the full mutational landscape in tumors. Table 1 shows several studies examining the mutational landscape of rectal NET. It can be seen that in 6 studies reporting mutational landscape, the top mutated driver genes included TP53 in 5 studies, APC in 3 studies, KRAS in 3 studies, RB1 in 2 studies, CDKN2A in 2 studies, and PTEN in 2 studies [19, 20, 22, 25-27]. The mutational frequency of these main driver genes and the mean values have been summarized in Table 2. The mutational frequency of TP53 was 10.1%, 14.3%, 43%, 57%, and 61%, respectively, with the mean at 37.1%. It exhibited a huge fluctuation, which may be caused by different ratios of samples with distinct pathological grades. For example, the studies reporting 10.1% and 14.3% mutational frequency focused on G1 and G2 NETs [19, 25], while the studies reporting 43%, 57%, and 61% often focused on NEC [22, 26, 27]. Similarly, the mutation frequency of APC was 36.7%, 53% and 71%, respectively, with the mean at 53.6%, and all three studies focused on NEC [22, 26, 27]. These studies also reported the KRAS mutation frequency of 25%, 36%, and 53.3%, respectively [22, 26, 27], with a mean of 38.1%. RB1 mutation has been identified in NET, and it was reported to be co-mutated with TP53 in small cell lung cancer, which is regarded as a cancer with neuroendocrine cell origin [28]. The mutation frequency of RB1 was reported 79% and 46.7% in two studies, respectively, exhibiting high prevalence in NETs [22, 26]. In contrast, the mutational frequency of CDKN2A and PTEN was much lower than BRAF, TP53, APC, KRAS and RB1. Therefore, it can be concluded from these findings that the main driver genes are those with high mutational frequency in NET. In addition, NEC may have a higher mutational burden than NET, which is consistent with the observations in other benign and malignant tumors [29]. Although the high-frequency driver genes have been largely consistent in the previous studies, heterogeneity still existed among different studies. This may be due to low-frequency driver gene mutations in individual studies. For instance, mutation of RET, FBXW7, PIK3CA, and KMT2D, was reported in only one study [19, 25-27]. Similar to BRAF mutations, the low-frequency mutations in these driver genes may indicate multiple mechanisms of tumorigenesis and high clonal heterogeneity in rectal NETs.

Interestingly, NETs from different locations share common mutations but exhibit considerable discrepancies in the mutational landscape. For example, BRAF-V600E mutation is similarly found in the NETs of the pancreas and upper digestive tract [17], while MEN1 mutation is reported in the pancreas and rarely observed in the rectum [30]. In addition, TP53 and RB1 mutations are commonly observed in rectal NETs, rarely found in pancreatic NETs, and more common in pancreatic NEC. It may be related to the degree of differentiation of pancreatic NETs [31]. A whole-genome study on pancreatic NETs showed that somatic mutations, including point mutations and gene fusions, are commonly found in genes involved in four major pathways: chromatin remodeling, DNA damage repair, activation of mTOR signaling, including previously undescribed EWSR1 gene fusions, and telomere maintenance [32]. In contrast, abnormally regulated Notch signaling [29], Wnt signaling [30], and RAS/RAF/MEK/ERK signaling [33] are the main pathways in rectal NETs, although aberrant mTOR signaling is also involved [34]. Therefore, NETs in different organs exhibit common but distinct aberrant signaling pathways, with enormous heterogeneity.

The CNV and LOH alterations of rectal NETs

Studies on large fragment alterations, including copy number variation (CNV) and loss of heterozygosity (LOH), were not sufficiently compared with the studies on the mutational landscape in rectal NETs. Table 3 lists all the large fragment variants that have been discovered in rectal NETs so far [19, 22, 27, 35, 36]. It can be seen from the literature that these reported large fragment alterations mainly involved known driver genes, including APC, TP53, CCNE1, MYC, TERT, RB1, ATM, etc. Both amplification and deletion (LOH) were present. Amplification mainly involved CCNE1, MYC, and TERT, while LOH mainly involved APC, DCC, TP53, RB1, ARID1A, ESR1, ATM, PHLDA3, MEN1, and SMARCB1 [19, 22, 27, 35, 36]. The frequency of amplification or LOH varied greatly across different studies. For example, the variation rates reported by Kim et al. in 2016 [19] and Shamir et al. in 2019 [22] (Table 3) were less than 10%, while the variation rates reported in other studies were much higher [27, 35, 36]. This variation could be caused by different research methods detecting the large fragment alterations. It is known that the sensitivity of NGS method in detecting amplification and deletion is not satisfactory since NGS is not a method for absolute quantification. The size of NGS panel and the design and sensitivity of probes can affect fragment recognition, especially when the fragment alterations are not significant. This means that many factors affect the NGS recognition of fragment amplification or deletion, resulting in low detection efficacy [37]. In addition, the setting of the threshold also affects the ability of NGS to detect the copy number changes. In contrast, PCR, particularly digital PCR or traditional FISH, may be more suitable for detecting copy number variations for single genes, but they cannot be used for high-throughput multiple gene detection across the whole genome [38].

Table 3 The status of main CNVs, fusions and LOH identified in literatures on rectal NETs

Main alterations	Alteration rate of main driver genes	Total number of subjects	Publication year	Reference number
LOH of APC, DCC, and p53	75% for all genes	8	1997	35
CCNE1 amplification	7.1%	14	2016	19
CCNE1, MYC, MYCN, TERT amplification, SMARCB1 LOH	CCNE1, MYC, MYCN amp (8%), TERT amp (4%), SMARCB1 LOH (4%)	25	2018	22
PHLDA3 and MEN1 LOH	PHLDA3 (60.0%); MEN1 (66.7%)	79	2019	36
RB1, ARID1A, ESR1 and ATM copy number loss. MYC and KDM5A copy number gain or amplification	RB1 (34%), ARID1A (35%), ESR1 (25%), ATM (31%), MYC (51%), KDM5A (45%)	37	2021	27

CNVs: copy number variations; LOH: loss of heterozygosity; NETs: neuroendocrine tumors; amp: amplification

Copy number variation and LOH are common abnormalities in NETs and other tumors. Copy number changes can occur early during tumor development or happen before tumor development [39]. A seesaw effect has been observed between CNV and mutations, which suggests that tumors with predominant CNV changes may show low mutational burdens. In contrast, tumors with high mutational burdens may exhibit less CNV changes [40-42]. In addition, many studies revealed that high copy number changes are more often in advanced, metastatic, or highly malignant tumors [40-42]. The impact of copy number changes is genome-wide and significant. CNV changes affecting major driver genes are both markers for tumor prognosis and potential indicators of therapeutic response [40-42].

Hereditary rectal NETs with germline mutations

Hereditary colorectal cancers, including Lynch syndrome (LS) and familial adenomatous polyposis (FAP), belong to a group of hereditary tumors caused by known germline genetic variations [43]. In this review, we found that germline mutations can cause rectal NETs, categorized as Lynch syndrome or FAP. Due to the low incidence of rectal NETs among colorectal cancers, studies on germline mutations in rectal NETs were all case reports. We found six cases reporting rectal NEC with germline mutations. This included two patients with confirmed FAP diagnosis and four patients with LS diagnosis [44, 45]. The two FAP cases included one patient diagnosed with large cell NEC with APC P.Q1406X (C.4216C>T) mutation, and another patient diagnosed with MYH-associated polyposis (MAP) with MUTYH c.1437_1439delGGA (p.Glu480del) mutation [44]. The four cases of LS included one patient with poorly-differentiated large cell NEC with MSH-6 1634_1637delAAGA mutation, one patient with mixed adenoneuroendocrine carcinoma (MANEC) with MLH1 c.1456dupT mutations, one patient with a well-differentiated carcinoid NET with MLH1 (deletion of exons 3–6) mutation [44], and another patient with neuroendocrine carcinoma with MSH2 c.1808A>T (Asp603Val) (likely pathogenic) mutation [45]. Thus, it appeared that Lynch syndrome and FAP are not limited to adenocarcinoma and can be found in NETs or mixed pathologies. For patients of NETs with a family history, early onset or high degree of malignancy, the possibility of germline mutations should be considered.

Potential targeted therapies for rectal NETs

Currently, the main treatment is surgery or neoadjuvant chemotherapy followed by surgery for local resectable rectal NET. Either octreotide or lanreotide (somatostatin analogs) is recommended to potentially control tumor growth for those with locoregional advanced and/or metastatic gastrointestinal tract primary NETs with clinically significant tumor burden or progressive disease [46]. The recommendation for octreotide in these patients is based on the results of the PROMID study [47], and the recommendation for lanreotide is based on the results of the CLARINET study [48]. However, it is still of significance to explore targeted therapeutic strategies for patients who have lost the opportunity for surgery due to advanced disease or metastasis.

We found that almost all reports on targeted therapies in rectal NETs focused on BRAF V600E mutations. BRAF gene is an oncogene, and V600E is the most common mutation of the BRAF gene, which is commonly found in solid tumors such as melanoma (50%), papillary thyroid carcinoma (45%), colorectal cancer (approximately 10%), and non-small cell lung cancer (approximately 10%) [49, 50]. BRAF protein and KRAS protein are both RAS-RAF-MEK-activated extracellular signal-regulating kinases, which play key roles in MAPK/ERK signaling pathway [51]. The BRAF V600E mutation results in continuous activation of BRAF protein, increasing BRAF activity by approximately 500 times. V600E mutation activates BRAF, independent of upstream RAS kinase, resulting in continuous activation of ERK. ERK translocation into the nucleus activates the transcription of various downstream genes, leading to dysregulated cell proliferation and division [52]. In patients with advanced colorectal cancer, EGFR-TKI can generally be used as systemic therapy if no KRAS resistant mutations are present, but tumors with BRAF V600E mutations can resist EGFR-TKI [53]. Therefore, the current treatment strategy of combined BRAF and MEK inhibitors can achieve a good therapeutic response in many solid tumors in patients with BRAF V600E mutation [52, 53].

BRAF mutations lead to constitutive activation of the MAPK pathway, consisting of a series of protein kinases, including RAS, RAF, MEK, and ERK, which stimulate cell growth [54]. Identification of therapies targeting the BRAF V600E mutation, such as dabrafenib and vemurafenib, has provided a major therapeutic strategy in patients with this mutation. Both vemurafenib and dabrafenib showed impressive response rates and improved progression-free survival when used alone [55-58]. However, resistance emerged in the half of the patients by 6 months, mediated by overactivation of the MAPK pathway due to dysregulation of MAPK pathway proteins such as NRAS [59, 60] or MEK [60], CRAF [61], and COT [62]. Changes in BRAF itself such as dimerization and variant splicing may also cause resistance [63]. Compared with chemotherapy, Trametinib improved survival in patients with BRAF V600E or V600K mutations naïve to targeted therapies [64]. Trametinib is an inhibitor of MAPK-ERK kinase (MEK), downstream of BRAF. Therefore, combined blockade with dabrafenib/trametinib and vemurafenib/trametinib may mitigate resistance, increase disease control duration, and improve response rates and tolerability to some toxicities [65].

As discussed previously, the mutational frequency of BRAF V600E ranges from 7.1 to 33.3% in rectal NETs. BRAF V600E mutation can cause resistance to chemotherapy by pazopanib but may be a potentially actionable mutation in metastatic NETs patients [17]. Furthermore, combination therapy with dabrafenib/trametinib or vemurafenib/trametinib has been effective in five patients with rectal neuroendocrine carcinoma. These patients were resistant to first-line chemotherapy [23], had metastatic NEC [18], or experienced cancer relapse after surgery [66]. Although no clinical trial has been conducted in patients with rectal NETs carrying BRAF V600E mutations, case reports strongly suggest that combined inhibition of BRAF and MEK is effective in patients with rectal NETs, not only for those with advanced or relapsing tumors but also for those with first-line resistant to chemotherapy.

Due to the lack of reports on MSI and TMB status in rectal NETs, the potential therapeutic response of late-stage or metastatic rectal NETs with MSI-H or TMB-H to immunotherapy cannot be assessed. Based on previous reports on CRC and other solid tumors [67], we suppose that patients with late-stage or metastatic rectal NETs and MSI-H or TMB-H may benefit from immunotherapy or combined therapy comprising immunotherapy, but this speculation needs further evidence.

Potential indicators of rectal NET prognosis

Many studies introduced prognostic factors for rectal cancer, including age, gender, family history, tumor stage, grade, pathological classification, vascular and neural invasion, and lymphatic and distal metastasis [68, 69]. Regarding genetic variations, major driver gene mutations, including but not limited to KRAS, BRAF, PIK3CA, germline MMR gene variation in hereditary CRC, and the status of MSI and TMB, are known prognostic risk factors [67]. Rectal NETs shares common demographic and clinicopathological prognostic factors with rectal adenocarcinoma [26, 70, 71]. However, due to the low incidence of rectal NETs, its molecular prognostic factors are not well understood. Based on previous findings, we identified three types of molecular markers that may predict the prognosis of rectal NETs. The first group includes mutations or large fragment variants. It was reported that a unique subtype with MLH1/PMS2 loss and BRAF mutation, absence of Epstein–Barr virus is associated with a better prognosis of colorectal large cell neuroendocrine carcinoma [24]. Another study found that LOH at PHLDA3 is associated with the presence of multiple cancers and poor prognosis [36].

The second class of markers is protein-based. A study suggested that PROX1 and connexin A1 may be involved in the malignant progression of rectal neuroendocrine neoplasms through the Wnt pathway. The expression of thymidylate synthase, P27, P16, Gα15, PROX1, and Annexin A1 in gastrointestinal neuroendocrine tumors is associated with prognosis [34]. Another study found that abnormal PAX5 expression in CRNEC predicts a poor prognosis. CCL5 is an immunosuppressive factor strongly expressed in CRNEC patients with prolonged survival [72]. The third group of markers involved aberrant methylation. It was found that CpG island methylator phenotype (CIMP) activity is found in 13% of carcinoid tumors, and the presence of CIMP significantly correlated with lymphatic and vascular invasion [73].

Conclusions

In this review, we summarized the findings in mutational landscape and large-fragment alterations of rectal NETs at both somatic and germline levels. The landscape of main driver genes mutations, with high prevalence of large-fragment alterations, distinguished rectal NETs from rectal adenocarcinoma. We also identified potential therapeutic targets for late-stage or metastatic rectal NETs and a series of prognostic factors, which may facilitate the establishment of therapeutic strategies and prognosis prediction of rectal NETs. Future studies may focus on the optimization of therapeutic strategies based on potential actionable biomarkers.

Declarations

Ethics approval and consent to participate

Ethics approval and written consent to participate were not required as this study is a systematic review.

Consent to publish

Written consent to publish was not required as this study is a systematic review.

Availability of data and materials

The datasets generated and/or analyzed during the current study are available from the corresponding author upon reasonable request.

Competing interests

All authors claim no conflict of interest.

Funding

No funding is applicable for this study.

Authors’ contributions

Ke Li and Xiuyuan Zhang participated in the design of the study. Ke Li, Ying Liu, Junge Han, Jianhua Gui, Xiuyuan Zhang contributed to literature collection, paper summary, data collection and table making. Ke Li, Ying Liu, Junge Han, Jianhua Gui, Xiuyuan Zhang drafted and revised the article, and gave final approval of the version to be published, agreed to the submitted journal, and agree to be accountable for all aspects of the work. Ke Li, Ying Liu, Junge Han, Jianhua Gui, Xiuyuan Zhang proof read the manuscript. Xiuyuan Zhang submitted the manuscript.

Acknowledgements

Not applicable.

References

• 1   Yao  JC,  Hassan  M,  Phan  A,  Dagohoy  C,  Leary  C, et al. (2008) One hundred years after “carcinoid”: epidemiology of and prognostic factors for neuroendocrine tumors in 35,825 cases in the United States. J Clin Oncol 26: 3063–3072.
• 2   Wang  AY,  Ahmad  NA (2006) Rectal carcinoids. Curr Opin Gastroenterol 22: 529–535.
• 3   Ito  T,  Sasano  H,  Tanaka  M,  Osamura  RY,  Sasaki  I, et al. (2010) Epidemiological study of gastroenteropancreatic neuroendocrine tumors in Japan. J Gastroenterol 45: 234–243.
• 4   Lim  T,  Lee  J,  Kim  JJ,  Lee  JK,  Lee  KT, et al. (2011) Gastroenteropancreatic neuroendocrine tumors: incidence and treatment outcome in a single institution in Korea. Asia Pac J Clin Oncol 7: 293–299.
• 5   Volante  M,  Grillo  F,  Massa  F,  Maletta  F,  Mastracci  L, et al. (2021) Neuroendocrine neoplasms of the appendix, colon and rectum. Pathologica 113: 19–27.
• 6   Marchevsky  AM,  Hendifar  A,  Walts  AE (2018) The use of Ki-67 labeling index to grade pulmonary well-differentiated neuroendocrine neoplasms: current best evidence. Mod Pathol 31: 1523–1531.
• 7   Smith  TW,  Nikulasson  S,  De Girolami  U,  De Gennaro  LJ (1993) Immunohistochemistry of synapsin I and synaptophysin in human nervous system and neuroendocrine tumors. Applications in diagnostic neuro-oncology. Clin Neuropathol 12: 335–342.
• 8   Maione  F,  Chini  A,  Milone  M,  Gennarelli  N,  Manigrasso  M, et al. (2021) Diagnosis and management of rectal neuroendocrine tumors (NETs). Diagnostics (Basel) 11: 771.
• 9   Grassia  R,  Bodini  P,  Dizioli  P,  Staiano  T,  Iiritano  E, et al. (2009) Neuroendocrine carcinomas arising in ulcerative colitis: coincidences or possible correlations? World J Gastroenterol 15: 4193–4195.
• 10   Sigel  JE,  Goldblum  JR (1998) Neuroendocrine neoplasms arising in inflammatory bowel disease: a report of 14 cases. Mod Pathol 11: 537–542.
• 11  (2000) Case records of the Massachusetts General Hospital. Weekly clinicopathological exercises. Case 28-2000. A 34-year-old man with ulcerative colitis and a large perirectal mass. N Engl J Med 343: 794–800.
• 12   van der Woude  CJ,  van Dekken  H,  Kuipers  EJ (2007) Bleeding - not always a sign of relapse of long-standing colitis. Endoscopy 39 Suppl 1: E121–E122.
• 13   Rubin  A,  Pandya  PP (1990) Small cell neuroendocrine carcinoma of the rectum associated with chronic ulcerative colitis. Histopathology 16: 95–97.
• 14   Cheng  X,  Li  J,  Xu  T,  Li  K,  Li  J (2021) Predicting survival of patients with rectal neuroendocrine tumors using machine learning: a SEER-based population study. Front Surg 8: 745220.
• 15   La Salvia  A,  Espinosa-Olarte  P,  Riesco-Martinez  MDC,  Anton-Pascual  B,  Garcia-Carbonero  R (2021) Targeted cancer therapy: what’s new in the field of neuroendocrine neoplasms? Cancers (Basel) 13: 1701.
• 16   Gao  J,  Wu  H,  Shi  X,  Huo  Z,  Zhang  J, et al. (2016) Comparison of next-generation sequencing, quantitative PCR, and sanger sequencing for mutation profiling of EGFR, KRAS, PIK3CA and BRAF in clinical lung tumors. Clin Lab 62: 689–696.
• 17   Park  C,  Ha  SY,  Kim  ST,  Kim  HC,  Heo  JS, et al. (2016) Identification of the BRAF V600E mutation in gastroenteropancreatic neuroendocrine tumors. Oncotarget 7: 4024–4035.
• 18   Klempner  SJ,  Gershenhorn  B,  Tran  P,  Lee  TK,  Erlander  MG, et al. (2016) BRAFV600E Mutations in high-grade colorectal neuroendocrine tumors may predict responsiveness to BRAF-MEK combination therapy. Cancer Discov 6: 594–600.
• 19   Kim  ST,  Lee  SJ,  Park  SH,  Park  JO,  Lim  HY, et al. (2016) Genomic profiling of metastatic gastroenteropancreatic neuroendocrine tumor (GEP-NET) patients in the personalized-medicine era. J Cancer 7: 1044–1048.
• 20   Koşaloğlu  Z,  Zörnig  I,  Halama  N,  Kaiser  I,  Buchhalter  I, et al. (2016) Identification of immunotherapeutic targets by genomic profiling of rectal NET metastases. Oncoimmunology 5: e1213931.
• 21   Idrees  K,  Padmanabhan  C,  Liu  E,  Guo  Y,  Gonzalez  RS, et al. (2018) Frequent BRAF mutations suggest a novel oncogenic driver in colonic neuroendocrine carcinoma. J Surg Oncol 117: 284–289.
• 22   Shamir  ER,  Devine  WP,  Pekmezci  M,  Umetsu  SE,  Krings  G, et al. (2019) Identification of high-risk human papillomavirus and Rb/E2F pathway genomic alterations in mutually exclusive subsets of colorectal neuroendocrine carcinoma. Mod Pathol 32: 290–305.
• 23   Burkart  J,  Owen  D,  Shah  MH,  Abdel-Misih  SRZ,  Roychowdhury  S, et al. (2018) Targeting BRAF mutations in high-grade neuroendocrine carcinoma of the colon. J Natl Compr Canc Netw 16: 1035–1040.
• 24   Chetty  R,  Capo-Chichi  JM,  Serra  S (2019) Colorectal large-cell neuroendocrine carcinoma with lymphoid stroma: further evidence confirming a unique subtype associated with MLH1/PMS2 loss, BRAF mutation, Epstein-Barr virus negativity, and the possibility of a better prognosis. Histopathology 75: 247–253.
• 25   Park  HY,  Kwon  MJ,  Kang  HS,  Kim  YJ,  Kim  NY, et al. (2019) Targeted next-generation sequencing of well-differentiated rectal, gastric, and appendiceal neuroendocrine tumors to identify potential targets. Hum Pathol 87: 83–94.
• 26   Lee  SM,  Sung  CO (2021) Comprehensive analysis of mutational and clinicopathologic characteristics of poorly differentiated colorectal neuroendocrine carcinomas. Sci Rep 11: 6203.
• 27   Venizelos  A,  Elvebakken  H,  Perren  A,  Nikolaienko  O,  Deng  W, et al. (2021) The molecular characteristics of high-grade gastroenteropancreatic neuroendocrine neoplasms. Endocr Relat Cancer 29: 1–14.
• 28   George  J,  Lim  JS,  Jang  SJ,  Cun  Y,  Ozretić  L, et al. (2015) Comprehensive genomic profiles of small cell lung cancer. Nature 524: 47–53.
• 29   Kang  NW,  Tan  KT,  Li  CF,  Kuo  YH (2021) Complete and durable response to nivolumab in recurrent poorly differentiated pancreatic neuroendocrine carcinoma with high tumor mutational burden. Curr Oncol 28: 4587–4596.
• 30   Fujii  T,  Kawai  T,  Saito  K,  Hishima  T,  Hayashi  Y, et al. (1999) MEN1 gene mutations in sporadic neuroendocrine tumors of foregut derivation. Pathol Int 49: 968–973.
• 31   Tang  LH,  Untch  BR,  Reidy  DL,  O’Reilly  E,  Dhall  D, et al. (2016) Well-differentiated neuroendocrine tumors with a morphologically apparent high-grade component: a pathway distinct from poorly differentiated neuroendocrine carcinomas. Clin Cancer Res 22: 1011–1017.
• 32   Scarpa  A,  Chang  DK,  Nones  K,  Corbo  V,  Patch  AM, et al. (2017) Whole-genome landscape of pancreatic neuroendocrine tumours. Nature 543: 65–71.
• 33   Wang  H,  Chen  Y,  Fernandez-Del Castillo  C,  Yilmaz  O,  Deshpande  V (2013) Heterogeneity in signaling pathways of gastroenteropancreatic neuroendocrine tumors: a critical look at notch signaling pathway. Mod Pathol 26: 139–147.
• 34   Song  Y,  Li  X,  Song  T,  Lin  G,  Chen  Y (2016) Basic and translational research progress of gastrointestinal neuroendocrine neoplasmas. Zhonghua Wei Chang Wai Ke Za Zhi 19: 1217–1221 (In Chinese).
• 35   Vortmeyer  AO,  Lubensky  IA,  Merino  MJ,  Wang  CY,  Pham  T, et al. (1997) Concordance of genetic alterations in poorly differentiated colorectal neuroendocrine carcinomas and associated adenocarcinomas. J Natl Cancer Inst 89: 1448–1453.
• 36   Kojima  M,  Chen  Y,  Ikeda  K,  Tsukada  Y,  Takahashi  D, et al. (2019) Recommendation of long-term and systemic management according to the risk factors in rectal NETs patients. Sci Rep 9: 2404.
• 37   Moreno-Cabrera  JM,  Del Valle  J,  Castellanos  E,  Feliubadaló  L,  Pineda  M, et al. (2020) Evaluation of CNV detection tools for NGS panel data in genetic diagnostics. Eur J Hum Genet 28: 1645–1655.
• 38   Hayes  JL,  Tzika  A,  Thygesen  H,  Berri  S,  Wood  HM, et al. (2013) Diagnosis of copy number variation by Illumina next generation sequencing is comparable in performance to oligonucleotide array comparative genomic hybridisation. Genomics 102: 174–181.
• 39   Van Loo  P,  Nordgard  SH,  Lingjærde  OC,  Russnes  HG,  Rye  IH, et al. (2010) Allele-specific copy number analysis of tumors. Proc Natl Acad Sci U S A 107: 16910–16915.
• 40   Cancer Genome Atlas  Network (2012) Comprehensive molecular characterization of human colon and rectal cancer. Nature 487: 330–337.
• 41   Cancer Genome Atlas Research  Network (2014) Comprehensive molecular profiling of lung adenocarcinoma. Nature 511: 543–550.
• 42   Gerstung  M,  Jolly  C,  Leshchiner  I,  Dentro  SC,  Gonzalez  S, et al. (2020) The evolutionary history of 2,658 cancers. Nature 578: 122–128.
• 43   Ma  H,  Brosens  LAA,  Offerhaus  GJA,  Giardiello  FM,  de Leng  WWJ, et al. (2018) Pathology and genetics of hereditary colorectal cancer. Pathology 50: 49–59.
• 44   Kidambi  TD,  Pedley  C,  Blanco  A,  Bergsland  EK,  Terdiman  JP (2017) Lower gastrointestinal neuroendocrine neoplasms associated with hereditary cancer syndromes: a case series. Fam Cancer 16: 537–543.
• 45   Sekine  R,  Shimazu  K,  Nakano  D,  Yamaguchi  T,  Suzuki  Y, et al. (2022) A novel Lynch syndrome pedigree bearing germ-line MSH2 missense mutation c.1808A>T (Asp603Val). Jpn J Clin Oncol 52: 81–85.
• 46   Shah  MH,  Goldner  WS,  Halfdanarson  TR,  Bergsland  E,  Berlin  JD, et al. (2018) NCCN guidelines insights: neuroendocrine and adrenal tumors, version 2.2018. J Natl Compr Canc Netw 16: 693–702.
• 47   Rinke  A,  Müller  HH,  Schade-Brittinger  C,  Klose  KJ,  Barth  P, et al. (2009) Placebo-controlled, double-blind, prospective, randomized study on the effect of octreotide LAR in the control of tumor growth in patients with metastatic neuroendocrine midgut tumors: a report from the PROMID Study Group. J Clin Oncol 27: 4656–4663.
• 48   Caplin  ME,  Pavel  M,  Ćwikła  JB,  Phan  AT,  Raderer  M, et al. (2014) Lanreotide in metastatic enteropancreatic neuroendocrine tumors. N Engl J Med 371: 224–233.
• 49   Routhier  CA,  Mochel  MC,  Lynch  K,  Dias-Santagata  D,  Louis  DN, et al. (2013) Comparison of 2 monoclonal antibodies for immunohistochemical detection of BRAF V600E mutation in malignant melanoma, pulmonary carcinoma, gastrointestinal carcinoma, thyroid carcinoma, and gliomas. Hum Pathol 44: 2563–2570.
• 50   Takahashi  M (2021) Therapeutic strategy for BRAF-mutated cancer. Gan To Kagaku Ryoho 48: 861–865 (In Japanese).
• 51   Degirmenci  U,  Wang  M,  Hu  J (2020) Targeting aberrant RAS/RAF/MEK/ERK signaling for cancer therapy. Cells 9: 198.
• 52   Morris  EJ,  Jha  S,  Restaino  CR,  Dayananth  P,  Zhu  H, et al. (2013) Discovery of a novel ERK inhibitor with activity in models of acquired resistance to BRAF and MEK inhibitors. Cancer Discov 3: 742–750.
• 53   Corcoran  RB,  André  T,  Atreya  CE,  Schellens  JHM,  Yoshino  T, et al. (2018) Combined BRAF, EGFR, and MEK inhibition in patients with BRAFV600E-mutant colorectal cancer. Cancer Discov 8: 428–443.
• 54   Wan  PT,  Garnett  MJ,  Roe  SM,  Lee  S,  Niculescu-Duvaz  D, et al. (2004) Mechanism of activation of the RAF-ERK signaling pathway by oncogenic mutations of B-RAF. Cell 116: 855–867.
• 55   Flaherty  KT,  Puzanov  I,  Kim  KB,  Ribas  A,  McArthur  GA, et al. (2010) Inhibition of mutated, activated BRAF in metastatic melanoma. N Engl J Med 363: 809–819.
• 56   Falchook  GS,  Long  GV,  Kurzrock  R,  Kim  KB,  Arkenau  TH, et al. (2012) Dabrafenib in patients with melanoma, untreated brain metastases, and other solid tumours: a phase 1 dose-escalation trial. Lancet 379: 1893–1901.
• 57   Chapman  PB,  Hauschild  A,  Robert  C,  Haanen  JB,  Ascierto  P, et al. (2011) Improved survival with vemurafenib in melanoma with BRAF V600E mutation. N Engl J Med 364: 2507–2516.
• 58   Hauschild  A,  Grob  JJ,  Demidov  LV,  Jouary  T,  Gutzmer  R, et al. (2012) Dabrafenib in BRAF-mutated metastatic melanoma: a multicentre, open-label, phase 3 randomised controlled trial. Lancet 380: 358–365.
• 59   Nazarian  R,  Shi  H,  Wang  Q,  Kong  X,  Koya  RC, et al. (2010) Melanomas acquire resistance to B-RAF(V600E) inhibition by RTK or N-RAS upregulation. Nature 468: 973–977.
• 60   Trunzer  K,  Pavlick  AC,  Schuchter  L,  Gonzalez  R,  McArthur  GA, et al. (2013) Pharmacodynamic effects and mechanisms of resistance to vemurafenib in patients with metastatic melanoma. J Clin Oncol 31: 1767–1774.
• 61   Montagut  C,  Sharma  SV,  Shioda  T,  McDermott  U,  Ulman  M, et al. (2008) Elevated CRAF as a potential mechanism of acquired resistance to BRAF inhibition in melanoma. Cancer Res 68: 4853–4861.
• 62   Johannessen  CM,  Boehm  JS,  Kim  SY,  Thomas  SR,  Wardwell  L, et al. (2010) COT drives resistance to RAF inhibition through MAP kinase pathway reactivation. Nature 468: 968–972.
• 63   Poulikakos  PI,  Persaud  Y,  Janakiraman  M,  Kong  X,  Ng  C, et al. (2011) RAF inhibitor resistance is mediated by dimerization of aberrantly spliced BRAF(V600E). Nature 480: 387–390.
• 64   Flaherty  KT,  Robert  C,  Hersey  P,  Nathan  P,  Garbe  C, et al. (2012) Improved survival with MEK inhibition in BRAF-mutated melanoma. N Engl J Med 367: 107–114.
• 65   Spain  L,  Julve  M,  Larkin  J (2016) Combination dabrafenib and trametinib in the management of advanced melanoma with BRAFV600 mutations. Expert Opin Pharmacother 17: 1031–1038.
• 66   Nakano  M,  Shimada  Y,  Matsumoto  Y,  Saiki  T,  Zhou  Q, et al. (2022) Efficacy of BRAF inhibitor and anti-EGFR antibody in colorectal neuroendocrine carcinoma. Clin J Gastroenterol 15: 413–418.
• 67   Luchini  C,  Bibeau  F,  Ligtenberg  MJL,  Singh  N,  Nottegar  A, et al. (2019) ESMO recommendations on microsatellite instability testing for immunotherapy in cancer, and its relationship with PD-1/PD-L1 expression and tumour mutational burden: a systematic review-based approach. Ann Oncol 30: 1232–1243.
• 68   Marisa  L,  de Reyniès  A,  Duval  A,  Selves  J,  Gaub  MP, et al. (2013) Gene expression classification of colon cancer into molecular subtypes: characterization, validation, and prognostic value. PLoS Med 10: e1001453.
• 69   Shan  T,  Chen  S,  Chen  X,  Lin  W,  Li  W, et al. (2019) Association of family history of tumors with clinicopathological characteristics and prognosis of colorectal cancer. Eur J Cancer Prev 28: 258–267.
• 70   Folkert  IW,  Sinnamon  AJ,  Concors  SJ,  Bennett  BJ,  Fraker  DL, et al. (2020) Grade is a dominant risk factor for metastasis in patients with rectal neuroendocrine tumors. Ann Surg Oncol 27: 855–863.
• 71   Özaslan  E,  Bayram  F,  Karaca  H,  Gürsoy  Ş,  Öztürk  F, et al. (2016) Best prognostic factor of neuroendocrine tumors: grade or stage? A multidisciplinary single-center study. Turk J Gastroenterol 27: 509–514.
• 72   Chen  D,  Bao  X,  Zhang  R,  Ding  Y,  Zhang  M, et al. (2021) Depiction of the genomic and genetic landscape identifies CCL5 as a protective factor in colorectal neuroendocrine carcinoma. Br J Cancer 125: 994–1002.
• 73   Mitsuhashi  K,  Yamamoto  I,  Kurihara  H,  Kanno  S,  Ito  M, et al. (2015) Analysis of the molecular features of rectal carcinoid tumors to identify new biomarkers that predict biological malignancy. Oncotarget 6: 22114–22125.