Purpose:

The limited knowledge of the molecular alterations that characterize poorly differentiated neuroendocrine carcinomas has limited the clinical development of targeted agents directed to driver mutations. Here we aim to identify new molecular targets in colon neuroendocrine carcinomas (co-NEC) and proof the efficacy of matching drugs.

Experimental Design:

We performed a multi-omic analysis of co-NEC to identify genetic or epigenetic alterations that could be exploited as effective drug targets. We compared co-NEC samples with colorectal carcinomas (CRC) to identify neuroendocrine-specific traits. Patients with co-NEC and patient-derived xenografts were treated with a BRAFV600E-blocking drug to demonstrate sensitivity.

Results:

co-NEC and CRC are similar in their mutational repertoire, although co-NECs are particularly enriched in BRAFV600E mutations. We report for the first time that V600EBRAF-mutant co-NECs may benefit from BRAF inhibition in monotherapy and how EGFR status is essential to predict innate sensitivity and acquired resistance by a differential methylation of its gene regulatory regions.

Conclusions:

The identification of V600E BRAF mutations in high-grade co-NECs has allowed the description of radiological responses to combination therapy of BRAF and MEK inhibitors in basket clinical trials. However, the molecular rationale for this treatment combination was based on the presence of the BRAF mutation and the efficacy observed in other cancer types such as melanoma. Future drug development in this setting should test BRAF inhibitors upfront and the addition of anti-EGFR antibodies instead of MEK inhibitors for an efficient blockade of acquired resistance.

This article is featured in Highlights of This Issue, p. 759

Translational Relevance

Targeting BRAF-mutated cancers significantly differs between tumor types regarding sensitivity and resistance mechanisms. EGFR methylation status and its related protein expression is directly correlated with response and acquired resistance to BRAF inhibitors in co-NECs that should impact in the future design of clinical trials in this setting.

The low incidence and heterogeneity of neuroendocrine neoplasms has jeopardized their genomic profiling and thus the clinical development of targeted drugs directed to driver mutations. Fortunately, the molecular alterations driving carcinogenesis in neuroendocrine tumors are being revealed in the recent years.

Efforts have been focused in most prevalent neuroendocrine tumors, including pancreatic, small intestine, and bronchopulmonary. Exome sequencing of pancreatic well-moderately differentiated tumors [European Neuroendocrine Tumor Society (ENETS)/World Health Organization (WHO) grade 1/2] showed alterations in three main pathways: DAXX-ATRX (death-domain associated protein-alpha thalassemia/mental retardation syndrome X-linked), MEN1 (multiple endocrine neoplasia), and mTOR (1). Contrarily, an equivalent genetic study on small intestine neuroendocrine grade 1/2 neoplasms described alterations in a large variety of oncogenic pathways (2). A more recent study integrating exome sequencing, methylome, and whole-gene expression data catalogued small intestine grade 1/2 neuroendocrine neoplasms in three biological subtypes with different prognosis (3). Finally, a similar multi-omic study on bronchopulmonary well-moderately differentiated neuroendocrine neoplasms (typical and atypical lung carcinoids) also demonstrated the existence of significant differences between low- and high-grade tumors, suggesting a distinct cell of origin (4).

Less frequent gastroenteropancreatic neuroendocrine tumors, such as high-grade (ENETS/WHO grade 3) neuroendocrine carcinomas are significantly less studied. This is not only due to their low incidence, but also to their poor prognosis and aggressive behavior leading to a low prevalence of advanced disease. Similarly to neuroendocrine small-cell lung cancer (5), gastroenteropancreatic neuroendocrine carcinomas are systemically managed with treatments based on platinum chemotherapy following their histopathologic characteristics. Unfortunately, gastroenteropancreatic neuroendocrine carcinomas show lower response to these standard treatments most probably due to a distinctive repertoire of molecular aberrations. Again, the lack of a detailed molecular profiling of these tumors has prevented the development of more effective target-directed therapies.

A recent study reported two BRAFV600E-mutant cases with metastatic high-grade rectal neuroendocrine carcinoma that progressed to standard chemotherapy and later responded to the BRAF inhibitor dabrafenib combined with the MEK inhibitor trametinib (6). This was an enlightening study that encouraged the identification of new drug targets by a further molecular characterization of intestinal neuroendocrine carcinomas. This would be the first step to design new matched therapies that could be effective in patients’ refractory to standard-of-care chemotherapies.

In response, we performed a multi-omic study of a cohort of advanced colon neuroendocrine carcinomas (co-NEC). We first observed a significant frequency of BRAFV600E oncogenic mutations (28%). This result positioned co-NEC as the second tumor type most frequently mutated for BRAF, between melanoma (50%) and colorectal carcinoma (CRC; 15%) as described by The Cancer Genome Atlas (TCGA). Interestingly, a significant proportion of melanomas are sensitive to single agents blocking BRAFV600E mutations, whereas CRC tumors are not. It has been described that CRC tumors present high expression of EGFR as an alternative activation of MEK oncogenic pathway and a mechanism of resistance to BRAFV600E inhibition (7). Contrarily, EGFR expression is repressed by gene methylation in melanomas and thus they respond to single BRAFV600E blockade (8). This data suggest that despite co-NEC are tumors of the intestine as CRC, they may resemble more to melanomas regarding to their response to BRAFV600E inhibitors. A more detailed characterization of co-NECs molecular traits and in particular the status of its EGFR/BRAF/MEK oncogenic pathway was crucial to understand the determinants of response to new target-directed drugs.

We profiled the mutations present in a panel of cancer-related genes and the methylome of a group of co-NECs and compared them with CRC cases. We observed that both tumor types show a similar mutational landscape with frequent mutations in TP53, APC, KRAS, or BRAF genes. However, they presented a distinct methylome, suggesting a different gene expression profile and biological behavior. Indeed, EGFR gene was methylated in co-NECs in similar manner than in melanoma cases, whereas in CRC was not. This hypermethylation correlated with lower EGFR expression in co-NEC. Furthermore, a co-NEC patient-derived xenograft (PDX) model showed much higher sensitivity to a BRAFV600E inhibitor alone than CRC PDXs. In addition, we show a case of a patient with co-NEC with a BRAFV600E mutation that responded to dabrafenib monotherapy, similarly to melanoma cases. She later progressed to treatment by increasing EGFR expression, suggesting a mechanism of resistance in co-NEC resembling that observed in CRC.

In summary, our results help to better understand the nature of co-NECs, allowing to design more precise and effective therapies targeting their molecular vulnerabilities, and predict new potential mechanisms of resistance.

Study approval

Studies were conducted in accordance with the International Ethical Guidelines for Biomedical Research Involving Human Subjects. Human tumor samples for histologic and molecular analyses and PDX were obtained after approval from the Ethics Committee of the Vall d’Hebron University Hospital [approval ID, PR(IR)79/2009]. Written informed consent was signed by all patients. Experiments with mice were conducted following the European Union's animal care directive (86/609/CEE) and were approved by the Ethical Committee of Animal Experimentation of the Vall d’Hebron Research Institute (approval ID, 40/08 CEEA, 47/08 CEEA, 06/12 CEEA, 87/12 CEEA, 17/15 CEEA, and 18/15 CEEA).

Patient recruitment

Within the Spanish Task Force for Neuroendocrine and Endocrine Tumors (GETNE) national platform, 25 formalin-fixed, paraffin-embedded primary tumor samples of untreated patients with high-grade (ENETS/WHO grade 3), poorly differentiated neuroendocrine carcinomas of colon origin (excluding rectum) were identified. All patients included in the study signed the informed consent form of the national database of the GETNE group (RGETNE), whose standard operating procedures were approved by a National Scientific and Ethics Committee (PR(AG)82/2015). A referral expert pathologist in neuroendocrine neoplasms field confirmed the ENETS/WHO classification of the 25 tumor samples before starting molecular analyses. All tumors samples that underwent molecular analyses were defined as poorly differentiated grade 3 neuroendocrine carcinomas, with Ki67 index >20% and/or >20 mitoses/10 high power fields.

Genomic analysis

Selection of tumor-enriched tissue was performed with a cutoff >30% of tumor cells. Lymphocyte infiltration was determined. DNA was obtained and quality assessed by a qPCR-based method. The working method consisted of extraction of DNA tumor samples in formalin-fixed, paraffin-embedded tissue using the Maxwell 16 Instrument (Promega), followed by whole-genome amplification (Decline-g, Qiagen) in case of obtaining <600 ng. At least 600 ng of DNA is required to perform the mutational profiling using mutational VHIOCard. VHIOCard panel was designed in the laboratory of Cancer Genomics (Vall Hebron Institute of Oncology, Barcelona, Spain) to analyze somatic mutations frequently observed in a broad panel of solid tumors, including neuroendocrine neoplasms (based on the COSMIC database: http://www.sanger.ac.uk/genetics/CGP/cosmic/). VHIOCard allows genotyping up to 700 mutations and small indels in 61 genes related to cancer (Supplementary Table S1). Briefly, after the quantification (NanoDrop) and a dilution of genomic DNA to 10 ng/mL, a PCR was performed to amplify genomic regions that were adjacent to loci genotyped (5 mL volume containing 0.1 units Taq polymerase, 20 ng of genomic DNA, 2.5 pmol of each “first” PCR, and 2.5 mmol dNTPs triphosphate, dNTPs). The amplification reaction was carried out in a thermocycler. The unincorporated dNTPs were deactivated with the addition of alkaline phosphatase (0.3 U) and incubation for 40 minutes at 37°C followed by heat inactivation of the enzyme 5 minutes at 85°C. After that, each mutation was analyzed as a product extension of one base (dNTPs were used in the presence of Taq polymerase) of a probe that hybrids immediately adjacent to the mutation position. After adding a cation exchange resin to remove residual salts from the reaction, 7 nL of the matrix extension product were deposited (3-hidroxipicoloinic acid) on a SpectroCHIP Gen II Chip (Sequenom). The Gen II SpectroCHIPs were analyzed using a mass spectrometer [matrix-assisted laser desorption/ionization–time-of-flight Mass Spectrometer (MassARRAY, Sequenom)].

Mismatch repair status

The status of mismatch repair activity was analyzed by IHC to detect repair proteins and PCR to evaluate microsatellite instability (MSI). IHC was performed for MLH1 (G219-1129 clon, BD PharMingen Biosciences), MSH2 (G168-728 clon, BD PharMingen Biosciences), MSH6/GTBP (44 clon, BD PharMingen Biosciences), and PMS2 (A16-4 clon, BD PharMingen Biosciences). For MSI analysis we first used a DNA Tissue Extraction Kit (Qiagen) and then a Promega system to evaluate by PCR the status of several microsatellites: BAT25, BAT26, NR-21, NR-24, and MONO-27.

DNA methylation analyses

DNA and methylation quality analyses identified 19 of the 25 co-NEC samples suitable for methylation study. The DNA extraction was performed using the “Infinium HD DNA FFPE Restoration” Kit (Illumina) ensuring adequate quality of genetic material. Bisulfite conversion was performed according to the manufacturer's recommendations for the Illumina Infinium Assay. The co-NEC DNA was then hybridized using the Illumina Infinium MethylationEPIC BeadChip arrays, which quantifies methylation of more than 850,000 CpG (5′-cytosine-phosphate-guanine-3′) sites, covering 99% of the reference sequence (RefSeq) genes. The obtained data were jointly analyzed and compared with that already available in the TCGA database (http://cancergenome.nih.gov/) for 30 colorectal adenocarcinoma samples previously hybridized with the former HM450K Illumina array, reporting methylation status for more than 450,000 CpG sites. Signal background and interplate variations were removed and normalized (standard GenomeStudio normalization) using internal control probes. Probes with a detection P > 0.01 or without signal in one or more of the analyzed samples were also excluded, as well as the ones containing a SNP (within the interrogation or extension bases), potentially cross-reactive or mapping to the sex chromosomes. Methylation differences between CRC adenocarcinomas and co-NECs tumors were identified through two-tailed unpaired F tests correcting them for multiple comparisons (P < 2.55e-6 for statistical significance after correction). Most representative genes between the two neoplasms were identified from its content of significantly differentially methylated related CpGs.

Genes with CpG islands differentially methylated at their transcriptional start site (TSS200/TSS1500) were interrogated by gene set enrichment analyses (GSEA) using Broad Institute online tools. In addition, leading-edge analysis were performed using GSEABase package in R. The leading-edge subset of genes are those genes that account for a specific gene set enrichment signal. The overlap between leading-edge genes in different oncogenic pathways was represented using ggplot2 R package. For multiple GSEA plots representation we used clusterProfiler R package (9).

Reverse transcription and quantitative PCR

To analyze EGFR gene expression by quantitative PCR (qPCR), RNA from tumor samples was extracted and used to synthesize cDNA using TRizol (Thermo Fisher Scientific) and iScript cDNA Synthesis Kit (Bio-Rad), respectively. A 7900HT qPCR System was used with Power SYBR-Green (Applied Biosystems). Relative gene expression was determined by the comparative Ct method (10). Primers used: forward-TATTGATCGGGAGAGCCGGA, reverse-TCGTGCCTTGGCAAACTTTC.

PDX experiments

Animal experiments were conducted following the European Union's animal care directive (2010/63/EU) and were approved by the Ethical Committee of Animal Experimentation of Vall Hebron Institute of Research (ID: 40/08 CEEA and 47/08/10). NOD/SCID (NOD.CB17-Prkdcscid/NcrCrl) mice were purchased from Charles River Laboratories. A total of 1 × 105 patient-derived cells suspended in PBS were mixed with Matrigel (1:1 v/v; BD Biosciences) and injected subcutaneously into both flanks of NOD/SCID mice. When the tumor reached 0.5 cm3 in volume, mice were randomized into different groups of treatment: vehicle, encorafenib (20mg/kg), and/or cetuximab (20 mg/kg). Cetuximab was administered by intraperitoneal injection twice per week and encorafenib diluted in 1% Tween 80 and 1% carboxymethyl cellulose and administered by oral gavage once a day. When matching, endpoint criteria mice were euthanized and complete necropsies were performed. Subcutaneous tumors were collected for histologic analysis. A sample of each tumor xenograft was frozen in liquid nitrogen immediately after the extraction and kept at −80 °C.

Genomic profiling of co-NECs

We selected tumor samples from 25 primary co-NECs from untreated patients. We first sequenced the coding region of 61 cancer-related genes in all cases (Supplementary Table S1). The frequency of mutations per gene was compared with that described by TCGA in CRC (Fig. 1; Supplementary Table S2). In general, all genes frequently mutated in CRC were also altered in co-NECs, however some differences were observed. TP53 and BRAF were more frequently mutated in co-NECs, whereas KRAS was similarly altered. APC mutations were less frequent in co-NECs mostly due to the fact that not all its coding region was sequenced by our panel (Supplementary Table S1), whereas data from TCGA on CRC represented full exome sequencing. SMAD4 gene was also mutated at lower frequency in co-NEC than in CRC despite all coding sequence was analyzed. Finally, a group of genes were mutated at a low frequency in in both co-NEC and CRC tumors. Twenty-four of these 25 tumors were evaluated for mismatch repair proficiency, all showing a preserved expression of DNA repair proteins and stable microsatellites.

Figure 1.

Mutational profile of co-NEC. Panel of cancer-related genes was sequenced and mutated cases are indicated in 25 co-NEC patients’ tumors. The type of mutation is also detailed. The frequency of cases mutated per each gene is indicated for co-NET and compared with CRC cases studied by TCGA (right).

Figure 1.

Mutational profile of co-NEC. Panel of cancer-related genes was sequenced and mutated cases are indicated in 25 co-NEC patients’ tumors. The type of mutation is also detailed. The frequency of cases mutated per each gene is indicated for co-NET and compared with CRC cases studied by TCGA (right).

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Effective targeting of BRAFV600E in co-NEC

Seven of 25 co-NECs presented BRAF mutations and six of them a V600E oncogenic alteration. This represented 28% of co-NEC, that was higher than the 15.86% observed in CRC, and the only mutation targetable with available drugs such as dabrafenib or encorafenib. We therefore tested the potential efficacy of encorafenib on a PDX model derived from a liver metastasis of a patient with co-NEC presenting a BRAFV600E mutation and stable microsatellites (Fig. 2A). Encorafenib completely blocked tumor growth in contrast with its lack of effect on a PDX model derived from a liver metastasis of a patient with a CRC also presenting a BRAFV600E mutation and stable microsatellites (Fig. 2A and B). In consequence, we decided to enroll a patient with a co-NEC presenting liver metastases with a BRAFV600E mutation (Fig. 2C) in an available clinical trial with another BRAFV600E-specificinhibitor such as dabrafenib. Again, we observed a significant response to treatment (Fig. 2E), despite her previous progression to standard-of-care treatment with cisplatin–etoposide chemotherapy combination.

Figure 2.

co-NETs respond to BRAFTV600E blockade. A, Representative images showing the histology of a CRC (CTAX002) and a co-NEC (CTAX012) PDX model and their expression of synaptophysin (SYP). Scale bars, 100 μm. B, Both PDX models were treated with the BRAFV600E inhibitor encorafenib and tumor growth is shown. Ten animals were evaluated per each treatment. ****, P < 0.0001 of an unpaired t test with Welch correction comparing the tumor volume at endpoint measurements. C, Diagram showing the lesions and histology of a patient presenting an advanced co-NEC with live metastases. D, Expression of proliferation (Ki67) and neuroendocrine carcinoma differentiation markers (Chromogranin A: ChrgA and SYP) are shown. Scale bar, 100 μm. E, CT images showing the response and progression of this same patient to BRAFV600E inhibition with dabrafenib. Arrows point to major liver lesions that are also delineated. ADK, adenocarcinoma; H/E, hematoxylin and eosin; MSS, microsatellite stable.

Figure 2.

co-NETs respond to BRAFTV600E blockade. A, Representative images showing the histology of a CRC (CTAX002) and a co-NEC (CTAX012) PDX model and their expression of synaptophysin (SYP). Scale bars, 100 μm. B, Both PDX models were treated with the BRAFV600E inhibitor encorafenib and tumor growth is shown. Ten animals were evaluated per each treatment. ****, P < 0.0001 of an unpaired t test with Welch correction comparing the tumor volume at endpoint measurements. C, Diagram showing the lesions and histology of a patient presenting an advanced co-NEC with live metastases. D, Expression of proliferation (Ki67) and neuroendocrine carcinoma differentiation markers (Chromogranin A: ChrgA and SYP) are shown. Scale bar, 100 μm. E, CT images showing the response and progression of this same patient to BRAFV600E inhibition with dabrafenib. Arrows point to major liver lesions that are also delineated. ADK, adenocarcinoma; H/E, hematoxylin and eosin; MSS, microsatellite stable.

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co-NEC present a distinctive methylome

Both CRC and co-NEC PDX models showed a completely different response to BRAF blockade despite presenting the same BRAFV600E targetable mutation, stable microsatellites, and being derived from a liver metastasis. To further investigate the biological reason for such distinctive responses, we decided to define the methylome of co-NECs and compare it with CRC.

We obtained high quality DNA methylation analyses of 19 of the 25 original co-NECs. We obtained excellent lecture quality in 391,474 CpGs positions, which were compared with TCGA data of CRC adenocarcinomas (Supplementary Table S3). Statistically significant differences (P < 2.55e-6) were observed in 16.35% of CpGs, with an enrichment on regions related with gene expression promoters (TSS200 and 5´UTR) that generally showed less methylation in co-NEC than in CRC cases. This methylome profiling permitted to distinguish co-NECs from CRC adenocarcinomas as a different cluster of samples (Fig. 3A–C). All these significant methylome differences confirmed that we were facing two biologically distinct types of intestinal tumors.

Figure 3.

co-NECs show a distinctive methylome. A, A principal component dot plot showing the differences of methylation profiles between co-NECs and CRC. B, A volcano plot showing significant differences in methylation status of CpGs island in co-NECs and CRC adenocarcinomas. C, A hierarchical cluster showing two different clusters of methylation profiles in co-NET and CRC. The types of genome region are also indicated. D, From the list of genes differentially methylated in co-NECs versus CRC, we performed GSEA using Broad Institute online tools. A list of gene sets significantly enriched in co-NEC versus CRC is shown indicating the number of genes per set (size) and their enrichment score (ES). E, GSEA plots showing enrichment of particular gene sets when comparing genes differentially methylated in co-NEC versus CRC cases. P values are indicated as well as particular genes in the leading edge.

Figure 3.

co-NECs show a distinctive methylome. A, A principal component dot plot showing the differences of methylation profiles between co-NECs and CRC. B, A volcano plot showing significant differences in methylation status of CpGs island in co-NECs and CRC adenocarcinomas. C, A hierarchical cluster showing two different clusters of methylation profiles in co-NET and CRC. The types of genome region are also indicated. D, From the list of genes differentially methylated in co-NECs versus CRC, we performed GSEA using Broad Institute online tools. A list of gene sets significantly enriched in co-NEC versus CRC is shown indicating the number of genes per set (size) and their enrichment score (ES). E, GSEA plots showing enrichment of particular gene sets when comparing genes differentially methylated in co-NEC versus CRC cases. P values are indicated as well as particular genes in the leading edge.

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Indeed, we observed that genes such as somatostatin and other neurotransmitters, typically expressed in neuroendocrine cells, were higher methylated in CRC adenocarcinomas than in co-NECs or even melanoma samples (Supplementary Fig. S1). This data may suggest that co-NEC preserved a methylome inherited from a different cell of origin than the epithelial progenitors of CRC adenocarcinomas.

We also observed that genes differentially methylated in co-NEC versus CRC adenocarcinomas were related to a variety of biological processes such as immune cell differentiation, cytoskeleton dynamics and cell polarity, DNA damage, or apoptosis (Fig. 3D and E). Future studies are required to evaluate the biological relevance of particular genes or gene sets presenting this methylation status distinctive of co-NECs.

EGFR gene is repressed by methylation in co-NEC

Considering these particularities of the co-NEC methylome and the relevance of high EGFR expression conferring resistance to BRAFV600E blockade (7), we evaluated in detail its gene methylation status. We observed that EGFR gene presented two sites with a higher methylation in co-NECs than in CRC (Fig. 4A). These same sites were previously described to be higher methylated in melanomas (8). Indeed, histologic evaluation of EGFR expression revealed a lower expression in co-NEC than in CRC adenocarcinomas (Fig. 4B and C). We also observed that EGFR protein was almost absent in cancer cells of the liver metastasis in a patient prior entering a clinical trial with dabrafenib, and it was clearly increased upon progression to BRAFV600E inhibition (Figs. 2C–E and 4D and E).

Figure 4.

EGFR gene is methylated and repressed in co-NECs conferring innate sensitivity to BRAFV600E inhibition. A, Methylation pattern of EGFR gene in co-NEC, CRC, and melanoma tumors. ****, P < 0.0001 by an unpaired t test with Welch correction. B, Histology showing the expression of EGFR in a representative co-NEC and a CRC carcinoma. C, Dot plot representing the level of EGFR protein expression measured by IHC in co-NETs and CRC carcinomas. ***, P < 0.001 by an unpaired t test with Welch correction. D, Histology showing the expression of EGFR in a co-NEC tumor at baseline or after patient progressing to BRAFV600E inhibition with dabrafenib. B and D, Scale bars, 100 μm. E, Column plot representing the quantification of IHC. F, Both PDX models (CRC-CTAX002 and co-NEC-CTAX012) were treated with the BRAFV600E inhibitor encorafenib alone or in combination with cetuximab and tumor growth is shown. Ten animals were evaluated per each treatment. ****, P < 0.0001 of an unpaired t test with Welch correction comparing the tumor volume at endpoint measures. G, mRNA expression of EGFR gene in three tumor xenografts from each indicated PDX model. H, The basal levels of EGFR and phospho-EGFR (p-EGFR) proteins were measured by Western blotting in three tumor xenografts from each indicated PDX model. Tubulin was used as loading control.

Figure 4.

EGFR gene is methylated and repressed in co-NECs conferring innate sensitivity to BRAFV600E inhibition. A, Methylation pattern of EGFR gene in co-NEC, CRC, and melanoma tumors. ****, P < 0.0001 by an unpaired t test with Welch correction. B, Histology showing the expression of EGFR in a representative co-NEC and a CRC carcinoma. C, Dot plot representing the level of EGFR protein expression measured by IHC in co-NETs and CRC carcinomas. ***, P < 0.001 by an unpaired t test with Welch correction. D, Histology showing the expression of EGFR in a co-NEC tumor at baseline or after patient progressing to BRAFV600E inhibition with dabrafenib. B and D, Scale bars, 100 μm. E, Column plot representing the quantification of IHC. F, Both PDX models (CRC-CTAX002 and co-NEC-CTAX012) were treated with the BRAFV600E inhibitor encorafenib alone or in combination with cetuximab and tumor growth is shown. Ten animals were evaluated per each treatment. ****, P < 0.0001 of an unpaired t test with Welch correction comparing the tumor volume at endpoint measures. G, mRNA expression of EGFR gene in three tumor xenografts from each indicated PDX model. H, The basal levels of EGFR and phospho-EGFR (p-EGFR) proteins were measured by Western blotting in three tumor xenografts from each indicated PDX model. Tubulin was used as loading control.

Close modal

Altogether this data indicated that in co-NECs, methylation of EGFR gene lead to its gene repression allowing a therapeutic response to BRAFV600E inhibition. Similarly to CRC adenocarcinomas presenting low EGFR methylation and innate high gene expression, a co-NEC resistant to BRAFV600E inhibition increased EGFR expression as a potential mechanism of acquired resistance.

We further confirmed that EGFR signaling was not relevant in a BRAFV600E co-NEC PDX model because its blockade by cetuximab did not added any benefit when combined with dabrafenib (Fig. 2A, B, and F). In contrast, cetuximab further reduced tumor xenograft growth of a BRAFV600E CRC PDX when combined with dabrafenib. This innate differential response to single and combined treatments is in-line with the lower expression of EGFR protein in the co-NEC PDX than in the CRC PDX model (Fig. 4G and H).

co-NECs represent a group of neuroendocrine neoplasms with high aggressiveness and poor prognosis with very limited treatment options. The standard therapy derives from its histologic similarities with small-cell lung cancer, another high-grade neuroendocrine carcinoma. However, results with platinum and etoposide in neuroendocrine carcinomas of the digestive system are significantly inferior, suggesting important biological differences between both types of neuroendocrine carcinomas. Other chemotherapies such as FOLFOXIRI are showing slightly better results than platinum–etoposide in co-NEC.

co-NECs are a rare entity whose molecular characteristics are not well defined. Here, we present the most comprehensive molecular and translational analyses of co-NECs currently reported. From genomics perspective, we observed a similar gene mutational profile compared with CRC. However, the percentage of mutated cases per each cancer-related gene was significantly different in both tumors types. Interestingly, co-NECs showed a similar mutation profile than non-hypermutated CRC tumors with the involvement of TP53, APC, and KRAS. However, the high percentage of BRAFV600E mutations (28%) found in co-NECs was more similar to MSI hypermutated CRC (47%). We have not identified MSI in co-NECs suggesting chromosomal instability instead of mismatch repair deficiency as the main source of genetic alterations.

The methylomes observed in co-NECs and CRC adenocarcinomas were far more distinctive of each tumor type than their abovementioned mutational profiles. co-NECs presented in general lower methylated genomes than CRC tumors in gene regulatory regions, showing very different profiles. Similarly, cells from different differentiation lineages present in the normal intestinal epithelia are governed by a distinctive methylation pattern. We could therefore speculate that the epigenetic fingerprint of a co-NEC is a heritage of a normal cell of origin different from the intestinal cell generating a CRC carcinoma.

Furthermore, key components of central oncogenic pathways such as RTK/KRAS/BRAF/MEK or ILR/JAK/STAT were higher methylated in co-NEC than in CRC, whereas components of the GPCR/PLC/Ca++ signaling were less methylated (Supplementary Figs. S2 and S3; Supplementary Table S4). Beyond the biological interest of these finding, we observed that the methylation pattern of particular genes central in these oncogenic pathways can determine the response of co-NECs to targeted therapies. This would be the case of EGFR gene, which is methylated and repressed in co-NEC resembling the status of melanomas and oppositely to CRC where it is less methylated and higher expressed. This is crucial for the response of co-NECs and melanomas to BRAFV600E inhibitors because high EGFR expression has been described as an alternative mechanism to activate the EGFR/BRAF/MEK pathway and thus an innate mechanisms of resistance in CRC (7). Indeed, our data with PDX confirms the clinical results indicating that CRC do not respond to anti-BRAFV600E drugs alone but in combination with antibodies such as cetuximab-blocking EGFR signaling.

On the contrary, melanoma and co-NEC with a methylated and repressed EGFR gene showed primary sensitivity to BRAFV600E inhibitors. Moreover, we show how EGFR expression is increased in a patient with co-NEC upon acquiring resistance to BRAFV600E blockade with dabrafenib.

In summary, our results indicate that EGFR status is not only essential to predict innate but also acquired resistance to BRAFV600E inhibitors and that the methylation of its regulatory regions would be the underlying mechanisms of regulating its expression in tumors of different origin.

In addition to the efficacy observed in non–small cell lung cancer (11) and melanoma (12), a recent study in co-NECs showed the first evidence of tumor shrinkage also combining BRAF and MEK inhibitors (6). Patients were treated on the basis of the prior experience in melanoma and CRC with the BRAF and MEK combination, however, no data of BRAF inhibition in monotherapy was provided.

Here, we report for the first time that co-NECs with a BRAFV600E mutation could benefit from BRAF inhibitors as monotherapy. Moreover, our results on EGFR indicate that BRAF inhibition should be combined with anti-EGFR antibodies such as cetuximab or panitumumab instead of MEK inhibitors, for an efficient blockade of later acquired resistance.

A more recent study also demonstrates that patients with metastatic CRC benefit from a triple inhibition of EGFR, BRAFV600E, and MEK in a phase III Beacon trial (13). Our results suggest that this triple combination could also be beneficial for co-NEC presenting a BRAFV600E mutation. It will be very valuable to generate new PDX models from co-NEC tumors to evaluate the efficacy of such new therapeutic strategies and confirm the relevance of EGFR methylation and expression to predict response to treatment.

J. Barriuso reports receiving other commercial research support from Array Biopharma, Roche, Pfizer, Novartis, AstraZeneca, and AAA, reports receiving speakers bureau honoraria from Pfizer, is an advisory board member/unpaid consultant for Nutricia and Eisai, and gave expert testimony for NanoString. C.L. Lopez reports receiving commercial research grants from IPSEN, reports receiving speakers bureau honoraria from IPSEN, Novartis, and Pfizer, and is an advisory board member/unpaid consultant for Ipsen. R. Garcia-Carbonero reports receiving other commercial research support from Novartis and Roche. J. Hernando reports receiving speakers bureau honoraria from Eisai, Ipsen, Roche, and Angelini Pharma. J. Tabernero is an advisory board member/unpaid consultant for Array Biopharma, AstraZeneca, Bayer, BeiGene, Boehringer Ingelheim, Chugai, Genentech, Genmab A/S, Halozyme, Imugene Limited, Inflection Biosciences Limited, Ipsen, Kura Oncology, Lilly, MSD, Menarini, Merck Serono, Merrimack, Merus, Molecular Partners, Novartis, Peptomyc, Pfizer, Pharmacyclics, ProteoDesign SL, Rafael Pharmaceuticals, F. Hoffmann-La Roche Ltd, Sanofi, SeaGen, Seattle Genetics, Servier, Symphogen, Taiho, VCN Biosciences, Biocartis, Foundation Medicine, HalioDX SAS, and Roche Diagnostics. H.G. Palmer reports receiving commercial research grants from Blueprint, Merus, Bayer, and Novartis. No potential conflicts of interest were disclosed by the other authors.

Conception and design: J. Capdevila, J. Tabernero, A. Vivancos, H.G. Palmer

Development of methodology: J. Capdevila, O. Arqués, J. Matito, J. Hernández-Losa, M. Esteller, A. Martínez-Cardús, A. Vivancos, H.G. Palmer

Acquisition of data (provided animals, acquired and managed patients, provided facilities, etc.): J. Capdevila, O. Arqués, G. Caratù, S. Landolfi, J. Barriuso, P. Jimenez-Fonseca, C.L. Lopez, R. Garcia-Carbonero, I. Matos, N. Paolo, J. Hernández-Losa, M. Esteller, J. Tabernero, A. Vivancos

Analysis and interpretation of data (e.g., statistical analysis, biostatistics, computational analysis): J. Capdevila, O. Arqués, J.R. Hernández Mora, F.M. Mancuso, J. Barriuso, R. Garcia-Carbonero, I. Matos, N. Paolo, M. Esteller, A. Martínez-Cardús, J. Tabernero, A. Vivancos

Writing, review, and/or revision of the manuscript: J. Capdevila, O. Arqués, J.R. Hernández Mora, F.M. Mancuso, S. Landolfi, J. Barriuso, P. Jimenez-Fonseca, C.L. Lopez, R. Garcia-Carbonero, J. Hernando, I. Matos, N. Paolo, J. Tabernero, A. Vivancos, H.G. Palmer

Administrative, technical, or material support (i.e., reporting or organizing data, constructing databases): J. Capdevila

Study supervision: J. Capdevila, A. Vivancos, H.G. Palmer

Authors would like to thank all the patients who participated in the National GETNE database. This work was supported by an unrestricted grant from the Spanish Task Force for Neuroendocrine and Endocrine Tumors (GETNE-G1101).

The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.

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