Background
Antibody therapies that target tumour antigens are now well established in the arsenal of anti-cancer treatments. However, a major challenge in expanding the range of tumours treatable by this product class is the identification of new, antibody-tractable targets. Transcriptomics and proteomics can assist in identifying potential antigens, but these methods do not reveal whether an antibody-mediated therapy will have any impact on tumours. An alternative approach to finding novel targets is phenotypic antibody screening, where panels of antibodies selected against disease cell types are screened in a target-agnostic manner for a desired functional effect on tumour cells, prior to performing target identification. Similar approaches are well established for identifying small molecule therapeutics, where they are recognised in particular for their ability to find first-in-class therapies [
1]. Antibody-based phenotypic screening has been described previously by ourselves [
2], and others [
3‐
5], but all reports to date have focussed on established tumour cell lines as a screening platform. Here we report a functional antibody screen using primary cells from non-small cell lung cancer (NSCLC) patients, grown in spheroids and in anchorage-independent culture conditions that aim to replicate more closely the phenotypes of tumours in patients.
Immortalised tumour cell lines grown in two-dimensional (2-D, monolayer) cultures are a popular platform for
in vitro screening of novel anti-cancer therapeutics, due to their ease of culture, reproducibility and analysis, which all facilitate the performance of high-throughput discovery campaigns. However, these cells have intrinsic limitations for drug discovery, as their response to therapy often differs from disease tissue in patients, and hence 2-D cell-line based assays do not consistently predict efficacy of therapeutics in clinical trials [
6]. To help avoid late-stage drug development failures, more relevant
in vitro screens are being sought, using primary cells or co-cultures, grown in more complex culture formats, to model the disease mechanisms in real tissues more closely [
7]. The choice of xenograft models used for assessing therapeutic efficacy
in vivo has a similar bearing on disease relevance. Patient-derived xenograft (PDX) models, using primary tumours directly transferred from the patient into an immunodeficient mouse and maintained by passaging cells from mouse to mouse, can retain more closely the phenotype of real patient tumours when compared to cell line-derived xenografts, including gene expression profiles [
8] and histology [
9‐
11]. Even limited passage in tissue culture can be detrimental to xenografts models–a study of small cell lung cancer (SCLC) xenografts found that PDX models retained a tumour-specific gene expression signature also seen in primary SCLC tissue, which was irreversibly lost when the cells were transitioned to tissue culture and then re-established as secondary xenografts [
6].
For high-throughput drug discovery programs, the cell culture models need to be compatible with the requirements of the screening platform. Complex 3-D culture methods are now well established for both normal cells [
12‐
14] and tumour models [
15], but it is still challenging to use them in large-scale screens, where reproducibility and the sensitivity of detection methods are essential to the success of a screening campaign. In this study, we investigated screening models developed from primary non-small cell lung carcinoma (NSCLC) cells from human donors, and characterised their suitability for screening biologics in different culture formats. Two models proved to be suitable for screening in spheroid cell cultures, anchorage-independent cultures, and in standard monolayer cultures. Spheroid cultures (reviewed by Fennema et al. [
14]) use cells grown in small aggregates that are thought to allow more natural cell-cell and cell-matrix contacts to develop. The anchorage-independent cultures were used to test for antibodies interfering with anoikis resistance–the ability of cells to avoid apoptosis in the absence of normal cell-cell contacts, an important pre-requisite for metastasis [
16]. We generated a panel of antibodies in two molecular formats by performing phage-display selections against the primary NSCLC cells; a designed ankyrin repeat protein (DARPin) antibody mimetic library was used, in addition to a scFv library. The selected molecules were then screened for anti-proliferative and pro-apoptotic effects in assays, without knowledge of their targets, using primary NSCLC tumour cells grown in spheroids, monolayers and in anchorage-independent culture. We believe this is the first report of a large-scale target-naïve functional screen for novel biologics performed using primary cells in complex assay formats.
In order to enrich the phenotypic information on the effects of these molecules, a subset of the DARPins was also profiled in an image-based high content screen using a tumour cell line cultured in a complex 3-D matrix. Multi-parametric phenotypic profiling [
17‐
19] was applied to construct statistical models to discriminate the phenotypes induced by treatment, without prior selection of the measurement parameters. We compared treatment-induced effects of the DARPins on cell morphology and invasion phenotypes, and through this analysis identified distinct effects within a set of DARPins that bind to CUB-domain containing protein 1 (CDCP1). CDCP1 is a cell surface transmembrane protein that is widely expressed on many cell types, but also upregulated on many tumour cells and cell lines. Its function has been associated with invasive and metastatic phenotypes (reviewed by Uekita and Sakai [
20]), including models of prostate cancer [
21‐
23], and it was recently linked to Ras-driven invasiveness and upregulation of matrix degradation [
24].
Finally, we tested an anti-CDCP1 IgG antibody derived from our panel in a NSCLC PDX model, both as a single agent and in combination with cisplatin treatment. We saw no efficacy from antibody treatment alone in inhibiting growth of this patient-derived tumour model, in contrast to similar studies performed using other CDCP1 antibodies in cell line xenograft models [
25]. However, the antibody treatment led to significant enhancement of tumour growth inhibition when co-administered with cisplatin.
Discussion
In order to meet the significant unmet need for novel therapeutics in all disease areas, including oncology, there remains a desire to identify new, drug-tractable targets for both small molecule and biologic drugs. Biological therapeutic discovery is currently dominated by a target-based paradigm, often built on targets identified from expression data in disease models. In recent years, however, there has been a renaissance in the use of target-agnostic, phenotypic screening for small molecule drugs following analyses that showed this route is particularly effective at finding first-in-class molecules [
1]. More subtle analyses have shown that therapeutics are often discovered by combining phenotypic and target-led screens, but that an initial phenotypic screen can be an effective way to identify initial leads [
34]. Target-agnostic discovery is less common for biologics, but a growing number of reports have emerged [
2‐
5]; the hope is that such screens can provide an alternative route to novel antibody therapeutics.
The therapeutic relevance of a functional screen obviously depends on the quality of the screen itself, which to be successful should mimic the disease state as closely as possible. This can require a level of complexity that can be difficult to incorporate into a robust and reproducible screen. In order to identify novel antibody-tractable therapeutic targets by phenotypic screening, we assessed three different patient-derived NSCLC tumours for their suitability for use as a screening platform. Two models were suitable for reproducible in vitro screening, while one model could only be maintained in vivo. Biologics were selected against two of the primary cell populations by phage-display, using both scFv and DARPin antibody libraries. DARPins were included in our selections, due to in-house data showing improved levels of phage display, making it easier to perform cell-surface selections where the availability of cells was limiting. The resulting molecules were screened against primary cells grown in three different culture formats–a standard monolayer, a 3D spheroid-forming culture, which allows more native-like contacts between cells, and a low-attachment “anoikis-promoting” culture that aims to force cells to rely on survival pathways that are important during metastasis. Our data showed that efficacy of biologics against cells in monolayers often did not correlate well with efficacy against the same cells grown in spheroid or low-attachment cultures. Had our in vitro screening only used monolayer-based assays, subsequent studies could have focussed on agents that only showed activity in the least disease-relevant culture format. Instead, by including screens on other culture formats, we hope to have identified hits with higher confidence that the mechanism of action will translate to the clinic.
After screening for antibodies with functional activity against primary NSCLC cells in the proliferation and apoptosis screens, we wished to identify the most promising candidates for more detailed study. Target identification was performed using a cell-surface array of membrane proteins, presented by HEK293 cells, which should help ensure antigens were correctly folded. This method led to the identification of CDCP1 as the antigen of several of our antibodies. However, it was clear from our dose–response data that the antibody treatments routinely did not achieve their maximal or EC50 effects on the measured functional endpoints over the concentrations tested (see, for example, Fig.
2a for two anti-CDCP1 DARPins). This may be due to relatively weak antigen-binding affinities for these antibodies derived from naïve phage-display libraries without affinity maturation. We were most interested in identifying hits with novel targets or mechanisms of action, not those with the highest affinity or lowest EC50 (which is better addressed during lead optimisation). We had also noticed that additional CDCP1-binding antibodies identified in the NSCLC-selected panel had no effect in the functional assays on primary cells, and we wished to understand why. Therefore, having identified a panel of antibodies showing either binding to, or activity against the primary NSCLC tumour material, we also used a multiparametric screen to determine the phenotypic effects of the antibodies in more detail. For this, we used small volume 3-D microtissue cultures of PC-3 cells, grown in protein hydrogels that allow the cells to form a complex, invasive architecture. Although this involves a switch to a prostate cell line in place of lung cancer primary cells, which may be disadvantageous in translating the molecular effects of some antibodies in the panel, the invasive phenotype exhibited proved to be a useful platform for comparing our anti-CDCP1 molecules. The screen was performed in 384-well plates for high throughput analysis, and ultra-high content analysis was used to profile a set of antibodies across different doses, to measure their effects on tissue morphology. Intact 3D image stacks were analysed, allowing spatial information in the z-plane to be retained. Machine learning approaches selected the optimum feature sets for classifying treatment responses. The depth of feature extraction and scale of screening enabled phenotypic clustering to be performed to associate molecules with similar effects on phenotype [
33]. Interestingly, this approach successfully clustered the CDCP1-binding antibodies in the screen into two clusters, not one, which had opposite phenotypic effects on PC-3 cells. The high content screen was therefore of value in understanding why the functional screen on primary cells only identified a subset of antibodies later shown to bind to a common antigen, by highlighting differences in their biological effects. We predict that this approach will also enable the clustering of molecules that target different proteins on the same pathway or perturb the same biological process. Potential applications include performing comparisons of the phenotypes induced by novel therapeutics with reference inhibitors of specific signalling pathways to determine mechanisms of action, though profiling of larger well-annotated compound libraries will be needed to evaluate how effectively this can be achieved.
CDCP1 is a type I transmembrane protein with broad expression in normal tissues, but with an established role in cancer progression (reviewed by Uekita and Sakai–[
20]). Phosphorylation of its cytoplasmic domain is observed in proliferative cells, and its normal function may involve provision of an anti-apoptotic signal to counteract the loss of cell adhesion contacts during cell division [
35]. Proteolytic cleavage of the extracellular domain enhances phosphorylation, which leads to association with Src and PKCδ [
32,
36]. Antibodies that prevent this cleavage from occurring have been shown to prevent xenograft growth [
22,
32], while cells transfected with cleavage-resistance mutants of CDCP1 are less invasive than cells expressing the wild type protein [
32]. However, some uncertainty exists on the link between CDCP1 expression and tumour prognosis, since contradictory effects have been observed in different cancer types [
27,
37]. The reason for these differences is not yet fully clear, but recent evidence that links CDCP1 protein expression with oncogenic Ras mutants may help to clarify our understanding of this protein [
24].
We identified a group of anti-CDCP1 antibodies in our selection outputs against NSCLC primary cells that were functionally active against the primary cells (and also some established tumour cells lines, Additional file
6: Figure S5B); for example, we observed activation of caspase 3/7 in the primary NSCLC tumour cells when grown as spheroids in the presence of anti-CDCP1 antibodies. After identifying the antigen using cell-surface display of a membrane protein library, we found additional anti-CDCP1 antibodies in our anti-NSCLC selection panel that were not found via the functional screens in the primary cells. Some of these molecules were included in the multiparametric screen using 3-D cultures of PC-3 cells; here, the anti-CDCP1 molecules clustered into two groups that drove opposite phenotypes in the cells. Some molecules acted similarly to αCDCP1-Ab1, which was identified in the original primary cell screens, reducing the invasiveness of the cells and increasing the polarisation of the micro-tumours formed in the 3-D matrix. Other anti-CDCP1 molecules increased invasiveness, showing that antibodies to the same molecular target can have strikingly different effects on the cells. This interesting observation highlights the value of screening primarily for function rather than target specificity. Understanding the mechanism behind this difference in behaviour will require further study. CDCP1 expression has been shown to be induced by expression of constitutively active Ras mutants, while CDCP1 knock-down abrogates Ras-driven invasiveness and migration [
24]. PC-3 cells are K-Ras wild-type [
38], but they express CDCP1 in a mixture of the full length form and the proteolytically truncated, constitutively active form [
36]. One possibility therefore is that the antibodies differ in their modulation of the level of truncated CDCP1 present on the cells.
In contrast with
in vitro data generated from primary NSCLC cells, our anti-CDCP1 antibody did not inhibit growth of a NSCLC patient-derived xenograft model. However, when our antibody was co-administered with cisplatin, a significant retardation of xenograft growth was observed beyond that caused by cisplatin alone. The lack of xenograft growth inhibition upon anti-CDCP1 therapy as a single-agent could result from several factors, one of which is the individual sensitivity of different tumour models; the
in vitro screens were performed with cells from a stage I KRas
WT tumour, whereas the xenografts were derived from a stage IV KRas
mut-P53
mut tumour that had not been cultured
in vitro prior to implantation. Unfortunately, the cells used in the xenograft model did not establish well for
in vitro culture, so it was not possible to directly compare the effect of anti-CDCP1 treatment in both models in the same format. Previous reports have shown anti-CDCP1 treatments with other antibodies can inhibit the growth of xenografts [
25], but to our knowledge, all previous data were generated using cell-line xenografts instead of primary cells. Arguably, the primary model used here may therefore be a more representative challenge for assessing an antibody therapeutic, since it may have retained a more disease-relevant phenotype.
Despite the challenging model used in our xenograft experiment, and the lack of efficacy as a single agent, anti-CDCP1 treatment did mediate a significant enhancement of cisplatin efficacy. The mechanism underlying this result requires further investigation, but suggests CDCP1 maybe a promising target for combination therapies. One possibility is that one therapeutic sensitises the cells to the mechanism of the other–for example, anti-CDCP1 therapy may target a mechanism by which the cells adapt to cisplatin toxicity, perhaps related to CDCP1’s role in mediating anoikis-resistance. Another possibility is that the two therapies are effective against different cell populations within the xenografts. Selection for cisplatin resistance in the A2780 ovarian cancer cell line led to decreased DNA hypermethylation around the
CDCP1 gene [
39], while DNA methylation near the
CDCP1 gene promoter region negatively correlates with CDCP1 protein levels in breast cancer [
40]. A sub-population of cisplatin-insensitive cells in the xenograft, possibly enriched by the donor’s treatment with carboplatin, may therefore be sensitive to anti-CDCP1 therapy. CDCP1 has been identified on cells with phenotypic markers of mesenchymal stem cells or of neural progenitor cells [
41], and its expression in pancreatic cancer tissue has been linked to maintenance of cancer stem-cell phenotypes (including gemcitabine resistance) [
42].
Methods
Primary NSCLC cells
Fresh frozen primary NSCLC tumors were supplied by Asterand. The material was thawed and cultured in keratinocyte-SFM media (GIBCO 17005-042) containing 2 % heat inactivated FBS in standard 159 cm2 culture flasks. The cells were allowed to attach and actively divide until the flask was roughly 60–70 % confluent. The culture media was completely changed three times a week. To prevent overgrowth of fibroblasts in the heterogeneous culture, the cells were subcultured using the differential trypsinization method provided by Asterand. Several rounds of differential trypsinization provided us with a highly enriched epithelial population. Dividing cells from primary NSCLC cultures were expanded and cryopreserved in liquid nitrogen with medium at various passage numbers up to a maximum of six passages.
Phage display antibody and DARPin isolation
Phage display cell panning was performed to isolate scFv antibodies and DARPins able to bind to the primary NSCLC cells. For the isolation of scFv antibodies, a naïve human scFv phage display library [
43] was used as described previously [
44]. DARPins were isolated from a synthetic phage display library containing 1 × 10
9 unique members. Both libraries were used in cell panning against primary human NSCLC cells, in a similar manner to previously described methods using cell lines [
2]. In total, three rounds of scFv cell panning were performed, and two rounds of DARPin cell panning. A total of 1760 individual scFv-presenting colonies were picked from the round 2 and round 3 selection outputs and sequenced by Sanger pyrosequencing, yielding 591 unique sequences after eliminating duplicates. Similarly, 1056 DARPin-presenting phage were obtained, with very high sequence diversity. The unique scFv antibodies and selected DARPins were expressed in
E. coli culture supernatant and screened for cell binding using a fluorescence-linked immunosorbent assay (FLISA). Antibody binding was detected via a fluorescent secondary antibody to the C-terminal His-tag using a 8200 Cellular Detection System (Applied Biosystems, Carlsbad, CA). For subsequent screening, unique scFv antibodies and DARPins were reformatted as Fc-fusion proteins by sub-cloning into a transient mammalian expression vector, under the control of the CMV promoter, upstream of the human IgG1 Fc domain. The recombinant Fc-fusions were expressed in Human Embryonic Kidney (HEK293) cells and were purified from culture supernatant using PhyTip® columns containing Protein A affinity resin (PhyNexus, Inc, San Jose, CA), according to the manufacturer’s instructions. Prior to target antigen identification and further characterisation, the scFv antibodies were reformatted as standard human IgG1 antibodies, and expressed and purified from Chinese Hamster Ovary (CHO) cells as described previously [
2].
NSCLC tumour cell functional assays
For spheroid culture, cells were grown on tissue culture treated substrate then harvested using 0.05 % trypsin. After neutralising trypsin and pelleting the cells, the cells were resuspended at 10,000 cells per 100 μL in a 0.25 % solution of methocult (StemCell H4100) diluted with filtered culture media. One hundred microlitre of the methocult cell suspension was plated in each well of a non-tissue culture treated round bottom plate (Costar 3788). The cells were gently pelleted then the plates were incubated on a plate shaker for 2 h at 37 °C in a 5 % CO2 incubator. After 24 h, spheroids were treated with antibodies. After 96 h incubation, functional assays were performed to assess anti-proliferative and pro-apoptotic effects, using Cell Titer Glo Luminescent Cell Viability (Promega G7572) and Caspase 3/7 Glo (Promega G8092) assay reagents respectively, according to the manufacturer’s instructions.
For monolayer and low-attachment (anoikis) cultures, cells were grown on tissue culture treated substrate then harvested using 0.05 % trypsin. After neutralising trypsin and pelleting the cells, the cells were resuspended at 10,000 cells per 100 μL in filtered culture media. One hundred microlitre of the cell suspension was plated in each well of a non-tissue culture treated round bottom plate (Costar 3788) for low-attachment cultures, and standard tissue culture-treated flat bottom plates (Thermo 165306) for monolayer. Antibodies were added immediately after plating for the anoikis plates and after 24 h for the monolayer plates. The cells were placed in a 37 °C and 5 % CO2 incubator for 72 h (monolayers) and 96 h (low-attachment), after which time functional assays were performed to assess anti-proliferative and pro-apoptotic effects, using Cell Titer Glo Luminescent Cell Viability (Promega G7572) and Caspase 3/7 Glo (Promega G8092) assay reagents respectively, according to the manufacturer’s instructions.
Identification of antibody targets
Antibody targets were identified using Retrogenix Cell Microarray Technology, which employs an array of membrane protein cDNAs expressed in HEK293 cells, as described in Turner et al. [
26]. Briefly, 2505 expression vectors, each encoding a full-length human cell surface protein, were arrayed across multiple microarray slides. HEK293 cells were grown over the vector array, leading to reverse transfection at each array location. After fixing the cells, the interaction between antibodies and the cells presenting the receptor array was detected using a goat anti-human antibody conjugated to AlexaFluor 647 (Life Technologies, Paisley, UK) and analysed using ImageQuant software (GE Healthcare, Bucks, UK). zsGreen encoded within the library vector was used to define the array positions.
Transfection of NCI-H358 cells with CDCP1 targeting siRNAs and staining for flow cytometry analysis
To transfect NCI-H358 cells, either Smartpool On-Targetplus CDCP1 siRNA (Thermo/Dharmacon, Catalog # L-010732-00-0005) or On-Targetplus Control siRNA non-Targeting siRNA #1 (Thermo/Dharmacon, Catalog # D-001810-01-05) were combined with Lipofectamine RNAi Max (Life Technologies, Catalog # 13778-150) in Opti-MEM Reduced Serum Medium with GlutaMax Supplement (Life Technologies, Catalog #51985034.) The final concentration of targeting siRNAs & non-targeting siRNAs was 20nM and RNAiMax was used at 1.2 μL per 100 μL reaction. Reagents were mixed gently by pipetting the solution up and down and then incubated for 15 min at room temperature. Fifteen thousand cells/well were plated into a 6-well flat bottom plate containing 100 μL siRNA complex for a final volume of 2000 μL. Cells were incubated at 37 °C, 5 % CO2. Three days after the cells were transfected, the cells were harvested using Enzyme Free Cell Dissociation Buffer (Gibco, Catalog # 13151-014) as described in the manufacturer’s dissociation protocol. Cells were re-suspended in FACs buffer (PBS containing 2 % FBS) at 1 × 106 cells/ml. Cells were Fc-blocked with 1 μg of human IgG/105 cells for 15 min at room temperature. After blocking, the NCI-H358 cells were stained for 30 min on ice with either DARPin-Fcs at 1 μg/106 cells; allophycocyanin conjugated anti-CDCP1 antibody (R&D Systems FAB26662A/Lot LVQ0109021X) at 10 μL/106 cells, or an isotype control antibody at 1 μg/106 cells. The DARPins and isotype control antibodies were unconjugated and required secondary antibody staining. The DARPins and isotype control were stained with Alexa Fluor 647 goat anti-human IgG (H + L) (Molecular Probes A-21445) at 10 μg/mL for 45 min on ice. Cells were also stained with propidium iodide to confirm cell viability. After staining, cells were re-suspended in FACs buffer, run on a BD LSRII flow cytometer, and final flow cytometric analysis was performed using TreeStar FlowJo software.
Recombinant protein expression
DNA sequences encoding the signal peptides and extracellular domains of human CDCP1 [Uniprot:Q9H5V8-1, RefSeq:NP_073753, residues 1-667], its short splice variant [Uniprot:Q9H5V8-3, RefSeq:NP_835488], and mouse CDCP1 [Uniprot:Q5U462-1, RefSeq:NP_598735, residues 1-666] were synthesised (GeneArt) and sub-cloned into a transient mammalian expression vector, under the control of the CMV promoter, upstream of a FLAG-His10 affinity tag. The resulting vectors were transfected into HEK293 cells, and the proteins were purified from the culture supernatant by Immobilised Metal Affinity Chromatography (IMAC) using a HisTrap column (GE Healthcare, Bucks, UK). The proteins were eluted with an imidazole gradient, then further purified on a Superdex 75, 16/60 size exclusion column (GE Healthcare, Bucks, UK) pre-equilibrated in PBS.
CDCP1 ELISA
Enzyme-linked immunosorbent assays (ELISAs) were performed by immobilising 50 μL recombinant CDPC1 per well, typically at 1–5 μg/ml in PBS, on 96-well Maxisorb plates (Nunc) overnight at 4 °C. Bovine serum albumin (Sigma) at the same concentration was added as a negative control antigen to wells on the same plate. The antigen plates were washed three times with PBS and blocked in 3 % non-fat milk powder in PBS, then 50 μL/well antibodies in blocking solution were added and incubated at room temperature for at least 1 h. The plates were washed three times with PBS-Tween, then incubated with 50 μL of appropriate secondary antibody-peroxidase conjugates (goat anti-human-Fc-peroxidase conjugate, Sigma cat # A0170, at 1:10,000 dilution was used for human IgGs and DARpin-Fcs) in 3 % non-fat milk in PBS-Tween for at least 30 min at room temperature, washed again three times in PBS-Tween, and developed for 2–10 min using 50 μL 3,3′,5,5′-Tetramethylbenzidine (TMB) substrate. The reaction was quenched with 50 μL 0.5 M H2SO4, then the absorbance measured at 450 nm on an Envision microplate reader.
Matriptase digest of recombinant human CDCP1 in the presence of antibodies
50 nM recombinant human CDCP1 extracellular domain with a C-terminal FLAG-His10 tag was treated with 5 nM recombinant matriptase catalytic domain (R + D Systems, cat# 3946-SE) in the presence of 200 nM anti-CDCP1 antibodies or 100 nM aprotinin protease inhibitor. The reaction was incubated at room temperature. Aliquots were taken at specific timepoints, which were quenched in LDS loading buffer (containing reducing agent) and frozen. Samples were analysed by SDS-PAGE and Western blot, probing for the C-terminal FLAG-tag of the recombinant protein.
Effect of antibodies on CDCP1 levels and cleavage in cell lines by western blot
DU-145, NCI-H358 and HCT116 cells were plated on 6-well plates at 3e5-5e5 cells/well and incubated overnight in media containing 10 % serum at 37 °C/5 % CO2. The following morning, the media was aspirated and the cells washed with PBS, then 1 mL media containing 10 μg/mL antibody (αCDCP1-Ab3 from our panel, mouse monoclonal antibody clones 309137 and 309121 (both from R + D Systems), negative control IgG) was added. The cells were incubated with the antibodies for a further 4 h at 37 °C/5 % CO2, then washed with PBS, lysed in Triton-X100 and analysed by SDS-PAGE and Western blot, probing for CDCP1 with an antibody to the cytoplasmic C-terminal region (CST #4115).
PC3 cell 3D tissue culture and image acquisition
PC3 cells (ATCC CRL-1435) were cultured in DMEM/F12 on tissue culture plates with 10 % FBS, detached by trypsinisation, counted and stored in frozen aliquots. Frozen cells were thawed and suspended in InvasogelO-gel-8 (OcellO B.V., The Netherlands), which was selected empirically from ten different gel formulations as supporting the optimum invasive tissue phenotype in 3D culture. Three thousand cells were seeded in 15 μl of gel per well in 384-well plates using a CyBio Selma 96-tip automated liquid handler. Plates were subsequently incubated at 37 °C and 5 % CO2 for 30 min. Test DARPin-Fcs, formulated in PBS, or dasatinib in DMSO, were diluted in DMEM/F12 containing 10 % FBS and 45 μl of each diluted antibody was added per assay well. Plates were incubated at 37 °C and 5 % CO2 for 7 days. Each plate was subsequently cooled to 4 °C and 15 μl of cooled fix-stain reagent (OcellO B.V., The Netherlands) was added to each well. Each well was washed twice with PBS and stored at 4 °C.
Plates were imaged using a Pathway-855 automated microscope (Becton Dickinson, Oxford, UK) fitted with a Nikon 4× lens (NA = 0.16) and plates were fed to the imager using a Twister-II plate handler. Two 20-section grayscale image stacks were captured from each well–one fluorescence channel for f-actin staining (EX = 548, EM = 645) and one for nuclei staining (EX = 380, EM = 435). Each section was captured as 1344 × 1024 pixels with 16-bit intensity information.
Image analysis
Image analysis was performed within OMiner™ (OcellO B.V., The Netherlands). To extract feature data from image stacks, the intensity information in each section of the image stack was scanned and a segmentation mask was generated for each section using WMC segmentation [
45]. Objects that were out-of-focus were discarded and the remaining objects from the same channel were aligned based on overlap-ratio. The nuclei were also assigned as children of each organoid based on location.
Phenotypic measurements were extracted per-object per-section. A collection of 70 morphological features were extracted from each channel. Additionally, another 7 correlative features were extracted by comparing relative phenotype between two channels. Object measurements in the same well were further aggregated (mean and standard deviation), resulting in a collection of 294 features. Volume measurements were extracted by aggregating all per-section measurements from the same object. Data for each feature were z-score normalized across the entire experiment, using buffer controls, which were distributed across the assay plates and represented 25 % of the total number of wells.
Data analysis
Firstly, accumulative phenotypic learning was used to extract a robust feature set that best described the phenotype induced by each antibody at each dose. Feature selection was performed by a pair-wise comparison of the phenotype of the buffer control to each antibody at each dose. For each pair of per-dose DARPin and buffer control measurements, a random forest feature selection [
46] was performed to identify 10 features (5 % of all features). Class-wise bootstrap sampling validation using 30 samples was included during random forest feature selection. The cross-validation was repeated 500 times to ensure that the feature selection results were stable. By repeating the feature selection for all pairs of buffer control and DARPin, the frequency estimation of the top-10 features selected from each pairwise comparison was refined to produce a frequency-estimation for all selected features. Finally, the 6 most commonly occurring features were selected that most strongly discriminated treatments based on a 5 % cut-off on the feature frequency estimation. i.e. there will be at least a 5 % chance that any one of these 6 features will be included in the top 10 features when feature selection is performed between any random pair of DARPin and buffer control measurements. This is 16 times higher than a feature being randomly selected from the entire set of 297 features. These features were defined as follows:
Secondly, unsupervised phenotypic clustering, using Ward’s method for hierarchical clustering with 2-fold cross-validation [
47,
48], was used to group the per-dosage treatment-induced phenotype into different classes, based on the 6 features. Each DARPin-Fc dose was analysed independently and per-well measurements from replicates were aggregated into a single data-entry for noise suppression. The number of clusters (five, designated A to E) was determined empirically based on the Davies–Bouldin index and the Calinski-Harabasz index [
49,
50]. These classes are defined by different contributions from the 6 selected features, as shown in Fig.
3b and Additional file
5: Table S1. The size of a partition is defined as follows:
$$ \%(i)=\frac{F_i}{\sum_{j=1}^6{F}_j} $$
where
F
i
is the z-score value of the
i-th feature, and
F
j
is the z-score of each of the top 6 features. The values of
F
i and %(
i) are both signed. Thirdly, a sequence of cluster labels was assigned to antibodies to represent the dose-dependent phenotypic profile. The phenotype at each dose was assigned to a phenotypic class previously defined using unsupervised clustering; this transformed the dose–response into a sequence of class labels.
Anti-CDCP1 treatment of NSCLC patient-derived xenografts
All procedures were performed in accordance with federal, state and Institutional guidelines and were approved by the MedImmune Institutional Animal Care and Use Committee in an AAALAC-accredited facility. XID (Harlan Laboratories, USA) mice at 4 to 6 weeks of age were implanted subcutaneously with 30 mm3 of NSCLC patient-derived tumour fragments which had been previously passaged three times in Rag-2 mice. Tumours were allowed to grow to approximately 100 mm3. The animals were then injected intravenously with antibody at 30 mg/kg twice weekly for three weeks and/or with cisplatin at 6 mg/kg every 4 days for three doses. Tumours were measured twice weekly and animals were euthanized when tumours reached 2000 mm3.
Competing interests
This work was funded by MedImmune, a wholly owned subsidiary of AstraZeneca. AMS, SR, SG, KFS, NH, CH, QH, LJ, RH & RM are MedImmune employees. LP is a founder and director of OcellO. KY & BH are employees of OcellO. JF and JS are founders and directors of Retrogenix Ltd.
The authors declare no other competing financial interests.
Authors’ contributions
AMS, SR, SG and KFS designed the experiments. RH, LJ and RM conceived of the study, and participated in its design and coordination. SR and SG performed the phage display antibody isolation. KFS, CH and NH established the primary cell cultures and performed the anti-proliferative and apoptosis assays. CH performed the in vivo xenograft study. JS, JF, AMS, KS, NH, MF, QH and SR performed target identification, confirmation and validation. LS, KY and BH performed the multi-parametric phenotypic profiling. AMS wrote the manuscript with comments from all authors. All authors read and approved the final version of the manuscript.