Jasmin B. Post’s research while affiliated with Utrecht University and other places

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Publications (5)


Abstract B003: BRAFV600E is essential for maintenance of the CpG island methylator phenotype and DNA methylation of PRC2 target genes in colon cancer
  • Article

February 2025

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2 Reads

Cancer Research

Layla El Bouazzaoui

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In colon cancer, the BRAFV600E mutation is strongly associated with the CpG island methylator phenotype (CIMP). Here, we characterized the contribution of BRAFV600E to maintenance of aberrant DNA methylation. A reverse CRISPR gene editing approach was applied to revert the V600E mutation in BRAF back to wildtype (E600V) in organoids derived from a late-stage tumour. DNA methylation analyses identified 5187 differentially methylated CpGs within CpG islands, predominantly hypermethylated (82%) in BRAFV600E organoids, including genes associated with CIMP, as well as Polycomb Repressor Complex 2 (PRC2) target genes. RNA sequencing showed that expression of those genes was concordantly repressed. Furthermore, BRAFV600Einduced high expression of PRC2 core components (EZH2, SUZ12, EED), caused PRC2-induced H3K27 trimethylation in promoter regions, and maintained a PRC2-associated embryonic phenotype. This phenotype was lost following mutation correction or pharmacological inhibition of DNA methylation. These findings show that BRAFV600E maintains aberrant DNA and histone methylation patterns in advanced colon cancer, likely preserving the transformed phenotype by silencing of PRC2 target genes. Epigenetic therapies may have value in the treatment of BRAFV600E-mutant colon cancer. Citation Format: Layla El Bouazzaoui, Jeroen M Bugter, Emre Küçükköse, André Verheem, Jasmin B Post, Nicola Fenderico, Inne H.M Borel Rinkes, Hugo J.G Snippert, Madelon M Maurice, Onno Kranenburg. BRAFV600E is essential for maintenance of the CpG island methylator phenotype and DNA methylation of PRC2 target genes in colon cancer [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: DNA Methylation, Clonal Hematopoiesis, and Cancer; 2025 Feb 1-4; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2025;85(3 Suppl):Abstract nr B003.


CDK1/cyclinB phosphorylates EKAREV(Tq) during G2- and M-phase
a, Typical mitotic EKAREV-FRET profile in HEK293 cells, including rising phase, steep increase at nuclear envelope breakdown (NEB) and sharp decline at anaphase (Supplementary Movie 1). Corresponding snapshots of above cells with H2B-mScarlet support cell-cycle phases (20 cells; 1 experiment). 1, G2; 2, NEB; 3, metaphase; 4, anaphase; 5, cytokinesis (c.k.); 6, G1. FRET-signal relative to PMA saturation (150nM). Black, FRET-ratio of YPet(yellow)/Turq2(blue) intensities. b, As a, with cell-cycle stages recognized by EKAREV(Tq) biosensor exclusion from condensed chromosomes; consistently observed (53 cells, 4 experiments). c, As a, but EKAREV(Tq) biosensor lacking nuclear localization. Observed in 28 cells, 2 experiments. d, As a, but EKAREV(TA) control biosensor that cannot be phosphorylated. Observed in 5 cells, 1 experiment. e, EKAREV(Tq) FRET signal in mitotic arrested HEK293 cells (nocodazol, 0.83μM; 2hrs) is sensitive to CDK1 inhibitor RO-3306. In mitotic cells, recognized by absence of nuclear localization (NEB) of NLS-tagged biosensor (insert images), FRET decreased upon 10µM RO-3306 (9 cells; 2 experiments with similar results), or 3x 1µM (1 cell). e’, Loss of normalized FRET signal (ΔR, %) upon RO-3306 (10µM) or MAPK pathway inhibitors (sel+SCH, 5μM each). Box-and-whisker plots: boxes represent quartile 2 and 3, horizontal line represents median, whiskers represent minimum and maximum within 1,5x interquartile range. RO-3306: n=23 cells, sel+SCH n=16 cells. f, EKAREV(Tq) FRET signal is sensitive to CDK1-inhibition in G2-phase. Synchronized cells were imaged before, during and after incubation with RO-3306 (10µM) and retrospectively analyzed if mitotic entry was observed <15 minutes after drug washout (n=23 cells). Right, similar experiment, here inhibiting MEK and ERK (n=20 cells). Graph shows mean±s.d. of baseline-normalized traces. g, As f, monitoring G2-phase in HeLa cells (n=19) co-expressing ERK-KTR-mCherry and EKAREV(Tq). ERK-KTR biosensor suffers from same undesired CDK1-sensitivity. ***, two-sided student’s T-test, p<0.0005. Scale bar, 10μm.
Source data
Improving ERK specificity, generating EKAREN4
a, HeLa cells expressing EKAREV substrate variants Alt_ERK_Substr_1-6 (Extended Data Fig. 4b). PMA, 500nM; SCH, 10μM. Right, responses (mean±s.d.), normalized to EKAREV-GW4.0. b, HeLa cells expressing EKAREV-GW variants were arrested in mitosis (Extended Data Fig. 1e) to test CDK1/cyclinB sensitivity (RO-3306). Purple, mean of individual traces. Right, overview for several variants, mean ratio loss ± s.e.m. Best responder EKAREV-GW(Alt_substr._6) is compromised by RO-sensitivity. c, Repeat of Fig. 1e, quantifying FRET in G2- and M-phase HEK293 cells(mean ± s.d), complemented with results from third-residue-substitution variants (purple). No improvements compared to EKAREN4/EKAREN5. d, Sensor dephosphorylation kinetics, assessed by instant ERK inactivation (sel+SCH, 5μM) after initial sensor saturation (PMA). For identical experimental conditions, HEK293 stably expressing EKAREV(Tq) or EKAREN4 were mixed. H2B-mScarlet selectively marked EKAREV(Tq) (left) or EKAREN4 cells (right) (insets: scale, 25 μm). Cells analyzed individually and averaged after double normalization (baseline and PMA-plateau). e, Maximum FRET range (ΔR(%), approximated through saturation (PMA) in serum-starved HEK293 cells of widely variable expression levels. e’, Baseline and plateau ratios corresponding to cells in e. Increased FRET range of EKAREN4 likely results from elevated plateau ratios. Expression levels affect FRET range by differentially affecting baseline ratios (see slopes in a.u.). Experiment performed twice. f, As e, differential effect of expression level on FRET range is similar for ERK-insensitive control sensors EKAREV(TA) and EKAREN4(TA). g, Mean (± s.d.) ΔR per expression level category (see e). For panels a-g the n numbers represent cells and are indicated in the graph for each group. Box-and-whiskers: boxes represent quartile 2 and 3, horizontal line represents median, whiskers represent minimum and maximum within 1,5x interquartile range. Dots are outliers. P values in all relevant panels were calculated using a two-sided student’s T-test, * p<0.05; ***, p<0.0005. n.s., non-significant.
Source data
Multi-dimensional analyses comparing EKAREV, EKAREN4 and EKAREN5
a, FRET-range versus sensor expression level, as in Extended Data Fig. 2e (EKAREN4, n=80 cells; EKAREN5, n=75 cells). a’, baseline and plateau ratios corresponding to cells plotted in a. b, Means (± s.d.) of ΔR from a, calculated in three expression level categories (as in Extended Data Fig. 2g). c, Dephosphorylation kinetics of EKAREN5 were directly compared with EKAREV(Tq) (as Extended Data Fig. 2d). Retrospective unmixing was based on clustering plateau amplitudes (PMA) (see Fig. 2a). Experiment performed once. d, As in c, comparing phosphorylation and dephosphorylation kinetics of EKAREN5 with ~33-fold expression level difference. Co-seeded high and low expressors were simultaneously monitored. Experiment performed three times. e-h, Various automated analyses on autonomous ERK fluctuations of HeLa cells (dataset of Fig. 2f,g), registered simultaneously by ERK-KTR-mCherry and either of EKAREV/EKAREN FRET sensors. EKAREV, n=15 single-cell traces; EKAREN4, n=10 single-cell traces; EKAREN5, n=17 single-cell traces. e, Automated peak counting per individual cell. f, Temporal matching of rising phases in KTR versus FRET signals. g, Temporal matching of falling phases in KTR versus FRET signals. h, Counted ‘inflection’ points per trace, that is points where ERK changes accelerate or decelerate(see Methods). i, Correlation between EKAREN5-FRET and ppERK staining (mean nuclear signal). After various ERK manipulations, HeLa-EKAREN5 cells were FRET-imaged and fixed instantly after acquisition, yielding various ERK activity states between complete inhibition (MEKi+ERKi) and pathway saturation (>7 min EGF). Grey line, regression analysis (y=ax+b). Traces are mean ratios ± s.d. For panels a-i the n numbers represent cells and are indicated in the graph for each group. Box-and-whisker plots: boxes represent quartile 2 and 3, horizontal line represents median, whiskers represent minimum and maximum within 1,5x interquartile range. Dots, outliers. Scale bar, 50μm. Two-sided student’s T-tests: *, p<0.05; **, p<0.005; n.s., non-significant.
Source data
Biosensor sequences
a, Silent mutations introduced into Turquoise2 (insert) to minimize sequence homology with the YPet fluorophore in the same construct. Red ‘x’ marks silent mutations. Blue, residues discriminating Turquoise2 from parental eCFP (Goedhart et al.³⁰). Green, residues rendering Turquoise2 prone to dimerize with YPet, in analogy to EKAREV design (Komatsu et al., 2011²⁸). Dark green, the V224L mutation was added to further enhance dimerization and, hence, FRET efficiency in ON-state (Vinkenborg et al., 2007³²). b, Alternative ERK substrate sequences were derived from ERK targets RSK1 (human) and ELK1 (human) using the Kinexus website and compared to parental EKAREV-GW-4.0 (GW = GateWay) with CDC25C substrate sequence. c, Overview of generated and tested point mutant variants of EKAREV. Red, central Threonine, target of ERK phosphorylation. Blue, the Lysine at position +4 mimics the general CDK1-consensus site, mutated to Proline (K->P). Purple, the Lysine at position +6 mimics the CDK1-consensus site and mutated to bulky Trp (K->W) to create steric hindrance with cyclinB. Underlined, ERK docking domain FQFP. Purple boxed characters, rational attempts to further eliminate CDK1-sensitivity with third amino acid replacements. V422T was aimed at favoring ERK over CDK1 consensus site; L427W was aimed at further augmenting sterical hinderance of cyclinB interaction; L427E was aimed at impeding cyclinB interaction through electrostatic repulsion. The Asp (D) at position+3 was left unchanged for its reported importance for the Pin1 affinity (Komatsu et al., 2011²⁸). d, Summary of available EKAREN4 and EKAREN5 plasmid constructs (including variable targeting motifs and Thr-Ala control versions), as well as adapted version of pInducer20 (Meerbrey et al., 2011⁴⁵) to initiate expression of HRASN17 and P2A-coupled reporter fluorophore mKate2-NLS. Constructs were deposited at Addgene.
Source data
Geometric effects on raw FRET signals in 3D organoid models
a, PDO model expressing the non-phosphorylatable (hence ERK-insensitive) control sensor EKAREV(TA) was FRET-imaged to assess non-biological geometry effects on raw signals in 3D organoid FRET microscopy. YFP/CFP ratios can differ between organoids situated either far away or close to the objective (distance difference ~150 μm). Experiment performed once, this direct comparison representing general observations. b, Performing FRET acquisition, Turq2 and YPet emissions were determined from all cells of a bulky organoid (>200 cells) and plotted against their z-coordinates. YFP/CFP ratios increase subtly with increasing depth within the organoid, likely due to differential scattering-induced loss of fluorescence between the two fluorophores. Experiment performed twice with same outcome.
Source data

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Quantifying single-cell ERK dynamics in colorectal cancer organoids reveals EGFR as an amplifier of oncogenic MAPK pathway signalling
  • Article
  • Publisher preview available

April 2021

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798 Reads

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94 Citations

Nature Cell Biology

Direct targeting of the downstream mitogen-activated protein kinase (MAPK) pathway to suppress extracellular-regulated kinase (ERK) activation in KRAS and BRAF mutant colorectal cancer (CRC) has proven clinically unsuccessful, but promising results have been obtained with combination therapies including epidermal growth factor receptor (EGFR) inhibition. To elucidate the interplay between EGF signalling and ERK activation in tumours, we used patient-derived organoids (PDOs) from KRAS and BRAF mutant CRCs. PDOs resemble in vivo tumours, model treatment response and are compatible with live-cell microscopy. We established real-time, quantitative drug response assessment in PDOs with single-cell resolution, using our improved fluorescence resonance energy transfer (FRET)-based ERK biosensor EKAREN5. We show that oncogene-driven signalling is strikingly limited without EGFR activity and insufficient to sustain full proliferative potential. In PDOs and in vivo, upstream EGFR activity rigorously amplifies signal transduction efficiency in KRAS or BRAF mutant MAPK pathways. Our data provide a mechanistic understanding of the effectivity of EGFR inhibitors within combination therapies against KRAS and BRAF mutant CRC. Ponsioen et al. use a FRET‐based ERK biosensor EKAREN5 in patient‐derived organoids to show that EGFR activity amplifies signal transduction efficiency in KRAS or BRAF mutant MAPK pathways.

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Colorectal Cancer Modeling with Organoids: Discriminating between Oncogenic RAS and BRAF Variants

February 2020

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26 Reads

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14 Citations

RAS and BRAF proteins are frequently mutated in colorectal cancer (CRC) and have been associated with therapy resistance in metastatic CRC patients. RAS isoforms are considered to act as redundant entities in physiological and pathological settings. However, there is compelling evidence that mutant variants of RAS and BRAF have different oncogenic potentials and therapeutic outcomes. In this review we describe similarities and differences between various RAS and BRAF oncogenes in CRC development, histology, and therapy resistance. In addition, we discuss the potential of patient-derived tumor organoids for personalized therapy, as well as CRC modeling using genome editing in preclinical model systems to study similarities and discrepancies between the effects of oncogenic MAPK pathway mutations on tumor growth and drug response.


Diverse BRAF gene fusions confer resistance to EGFR-Targeted therapy via differential modulation of BRAF activity

January 2020

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48 Reads

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18 Citations

Molecular Cancer Research

Fusion genes can be oncogenic drivers in a variety of cancer types and represent potential targets for targeted therapy. The gene is frequently involved in oncogenic gene fusions, with fusion frequencies of 0.2%–3% throughout different cancers. However, fusions rarely occur in the same gene configuration, potentially challenging personalized therapy design. In particular, the impact of the wide variety of fusion partners on the oncogenic role of during tumor growth and drug response is unknown. Here, we used patient-derived colorectal cancer organoids to functionally characterize and cross-compare fusions containing various partner genes (AGAP3, DLG1, and TRIM24) with respect to cellular behavior, downstream signaling activation, and response to targeted therapies. We demonstrate that 5′ fusion partners mainly promote canonical oncogenic activity by replacing the auto-inhibitory N-terminal region. In addition, the 5′ partner of fusions influences their subcellular localization and intracellular signaling capacity, revealing distinct subsets of affected signaling pathways and altered gene expression. Presence of the different fusions resulted in varying sensitivities to combinatorial inhibition of MEK and the EGF receptor family. However, all fusions conveyed resistance to targeted monotherapy against the EGF receptor family, suggesting that fusions should be screened alongside other MAPK pathway alterations to identify patients with metastatic colorectal cancer to exclude from anti-EGFR–targeted treatment. Implications: Although intracellular signaling and sensitivity to targeted therapies of fusion genes are influenced by their 5′ fusion partner, we show that all investigated fusions confer resistance to clinically relevant EGFR inhibition.


Cancer modeling in colorectal organoids reveals intrinsic differences between oncogenic RAS and BRAF variants

November 2019

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92 Reads

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3 Citations

Colorectal cancers (CRCs) with oncogenic mutations in RAS and BRAF are associated with anti-EGFR therapy resistance. Consequently, all RAS mutant CRC patients are being excluded from this therapy. However, heterogeneity in drug response has been reported between RAS mutant CRC patients. It is poorly understood to what extent such differences are derived from different genetic backgrounds or intrinsic differences between the various RAS pathway mutations. Therefore, using CRISPR technology we generated an isogenic panel of patient-derived CRC organoids with various RAS pathway mutations (i.e. KRASG12D, BRAFV600E, KRASG13D and NRASG12D). All RAS pathway mutants promote ERK activation and tumor growth. However, KRASG12D and BRAFV600E mutations in particular conferred robust resistance to anti-EGFR therapy, both in vitro and in vivo. Moreover, untreated KRASG13D mutants showed fastest growth in mice but remained sensitive to anti-EGFR therapy. Together, introducing mutation-specific oncogene signaling in CRC organoids resembles clinical phenotypes and improves understanding of genotype-phenotype correlations.

Citations (4)


... Together, our development of EKAREN5-gl extends applications of geneticallyencoded fluorescent probe for ERK and highlights the biological significance of ERK activities that are barely detectable with the current probes. While continuous efforts have been made to develop reliable ERK probes, image analysis has been another drawback for the application of the probes to a wide range of researchers (Ponsioen et al., 2021). Nevertheless, future advancement both in image analyses such as artificial intelligence (Yousif et al., 2022), machine learning (Kan, 2017;Seo et al., 2020) and ERK probes such as ERK-nKTR, which monitors ERK activity solely by its nuclear signal will be promising in sensitively detecting ERK activity and finding its biological relevance. ...

Reference:

A sensitive ERK fluorescent probe reveals the significance of minimal EGF-induced transcription
Quantifying single-cell ERK dynamics in colorectal cancer organoids reveals EGFR as an amplifier of oncogenic MAPK pathway signalling

Nature Cell Biology

... The oncogenes RAS and BRAF are frequently mutated in CRC and have been associated with therapy resistance in patients with CRC. 16 In a large cohort of patients with CRC in Morocco, the current study revealed the mutation frequencies of KRAS, NRAS and BRAF to be 46.6, 5.6 and 2.4% of patients, respectively. ...

Colorectal Cancer Modeling with Organoids: Discriminating between Oncogenic RAS and BRAF Variants
  • Citing Article
  • February 2020

... BRAF fusion is a rather uncommon kind of BRAF mutation. We analyzed the NGS results of 318 colorectal cancer patients, BRAF mutation frequency was 6.92 % and BRAF fusion frequency was 0.31 %, which was consistent with the literature reports [22]. BRAF fusions rarely occur in the same gene arrangement, posing challenges for individualized therapy design. ...

Diverse BRAF gene fusions confer resistance to EGFR-Targeted therapy via differential modulation of BRAF activity
  • Citing Article
  • January 2020

Molecular Cancer Research

... Recently, differential drug sensitivities of EGFR inhibition were reported among various different RAS-mutant patient-derived CRC organoids (PDOs). The pan-human EGFR inhibitor afatinib (Afa) can eliminate ERK activity oscillations in KRAS-mutant PDOs 39,40 . To select Ras and Raf pathway mutant clones more reliably, we used Afa as an alternative EGFR inhibitor in addition to Gef. ...

Cancer modeling in colorectal organoids reveals intrinsic differences between oncogenic RAS and BRAF variants
  • Citing Preprint
  • November 2019