Cell competition is an emerging mechanism in which mammalian tissues maintain homeostasis by eliminating less fit (loser) cells through direct interactions with fitter (winner) neighbouring cells. In cancer, these competitive interactions may drive tumour evolution; however, spatial organisation and clinical relevance of these events remain poorly understood. One mechanism by which winner cells eliminate loser cells is engulfment, resulting in cell-in-cell (CIC) formation. Although CICs have been observed in many tumour types for over a century, their cellular composition, spatial context, interactions with the tumour microenvironment, and biological significance in human cancers remain unclear. Here, we systematically characterised the cellular identity and functional states of CICs in situ, examined their spatial interactions within the tumour microenvironment, and assessed their clinical relevance using spatially resolved single-cell data from a large cohort of colorectal cancer patients. We demonstrated that CICs occurred predominantly between cancer cells but also involved cancer stem cell (CSC)-like populations and cytotoxic T cells. Engulfed (inner) cancer and CSC-like cells displayed molecular features consistent with a loser-cell phenotype, including increased apoptosis and reduced proliferation, whereas outer cancer cells exhibited winner-cell features such as upregulated glycolysis. Live-cell time-lapse experiments demonstrated that glucose accumulated in inner cells during lysosomal degradation following cell engulfment. Spatial analysis further revealed distinct CIC neighbourhoods, which we defined based on proximity to engulfment events. Cells within these regions, particularly CSC-like cells and cytotoxic T cells, exhibited increased metabolic stress, suggesting local competition for nutrients. Importantly, the presence of cytotoxic T cells within CIC neighbourhoods and spatial co-occurrence between cancer cells and CSC-like populations were associated with improved patient outcomes. Together, our findings demonstrate that cell engulfment defines spatially organised competitive niches and may reflect cell competition within complex tumour microenvironments.

Abstract In colorectal cancer (CRC), tumours classified as consensus molecular subtype 4 (CMS4) have the worst prognosis and derive negligible benefit from chemotherapy. We previously described how repressed interferon-related signalling is associated with increased relapse in CMS4 tumours. Although the viral mimetic polyinosinic:polycytidylic acid, poly(I:C), can reduce liver metastasis in vivo, the initial phenotypic changes that underpin its anti-metastatic response remain poorly described, particularly in the immunosuppressed CMS4 tumour microenvironment. Here we characterise lineage-specific anti-metastatic responses induced by poly(I:C), including acute macrophage polarisation and a novel CMS1-like regenerative stem cell state, which drive pro-inflammatory microenvironmental changes in CRC. These insights enabled the development of tractable biomarkers that identify an “immune-warm” patient subset most likely to respond to poly(I:C), enriched for mismatch-repair proficient (pMMR), anti-inflammatory macrophages and CMS4-like features. The viral mimetic poly(I:C) offers a tailored treatment option for poor-prognostic tumours, by reprogramming stem cell states and activation of an innate-adaptive anti-metastatic response.

Background:Stage III colorectal cancer poses a significant threat of metastasis development, as tumour resection and adjuvant chemotherapy do not guarantee prolonged disease-free survival. Objective:The spatial, quantitative, and qualitative characteristics of various cell types within tumour tissues could be key to developing accurate prognostic AI models. Design:Tissue microarrays created from primary tumour tissues collected during surgical resection from a cohort of 493 stage III colorectal cancer (CRC) patients were analysed for 61 protein markers at the single-cell level using multiplexed immunofluorescence imaging via the Cell DIVE™ platform. Subsequent cell-type classification enabled quantitative cell-type analyses, co-localisation neighbourhood assessments, and cell-type-specific protein signature discoveries that distinguish between early and late/non-recurring patient samples. Results:This study identifies a stem cell protein profile that drives tumour relapse. A deep neural network (DNN) model, based on a stem cell protein signature composed of BAX, MLKL, FLIP, GLUT1, and CDX2, provided accurate prognosis for stage III CRC patients in both discovery and validation cohorts and in an independent validation cohort. Nodal count-based metric further increased prognosis accuracy. Our study also revealed distinct spatial arrangements of immune, endothelial, and stem cells that were linked to early tumour recurrence. Conclusion:Our findings propose a clinically promising prognostic tool based on a five-protein stem cell signature. These markers not only predict chemotherapy resistance in cancer stem cells but also suggest potential therapeutic strategies such as combinatorial treatments incorporating small molecule inhibitors targeting FLIP and GLUT1.

The Bcl-2 protein family defines cellular competence for mitochondrial outer membrane permeabilization (MOMP) and apoptotic cell death. In proliferating cells, the Bcl-2 family member Mcl-1 accumulates across the cell cycle and confers trans-mitotic resistance to extrinsic apoptosis. We show here that Mcl-1, but not Bcl-xL, additionally undergoes a coordinated redistribution from the cytosol to mitochondria, concomitant with its over-proportional accumulation late in the cell cycle. Live-cell monitoring of Mcl-1 dynamics at single-cell resolution, combined with mathematical modelling, enabled us to quantify that Mcl-1 redistribution substantially contributes to elevating MOMP thresholds. Furthermore, we found that Mcl-1 accumulation and redistribution act concomitantly but independently to increase MOMP thresholds as cells approach mitosis and this elevated resistance is reset in daughter cells after division. Notably, heterogeneities in Mcl-1 abundance and subcellular distribution are pronounced even among isogenic cells within the same cell-cycle phase, and thus contribute to substantial cell-to-cell variability in MOMP susceptibility. Analysis of colorectal cancer tissue samples showed that variability in Mcl-1 expression and distribution is likewise prominent between cells in patient tumors and were predicted to drive intra-tumour heterogeneity in responses to treatments that induce MOMP. Overall, we demonstrate how changes in Mcl-1 amounts and localisation integrate with cell-cycle progression to modulate apoptotic susceptibility, thereby shaping cell-fate outcomes and contributing to cell-to-cell heterogeneities in death decision making.

Abstract Mutations in KRAS represent the most common oncogenic event in human cancer and occur in approximately 30% of lung adenocarcinomas. The mechanisms by which lung tumours evade apoptosis induced by oncogenic KRAS-driven stress remain incompletely understood. Here, we identify the anti-apoptotic regulator FLIP ( CFLAR ) as a critical dependency in KRAS-mutant lung cancers. We demonstrate that KRAS-mutant human lung cancer cell lines exhibit elevated FLIP expression and enhanced dependence on FLIP for survival compared to KRAS wild-type counterparts. Subsequently, using genetically engineered mouse models (GEMMs), we show that FLIP is essential for Kras -driven lung tumour development in vivo . In vitro, FLIP-deficient lung cancer cells display spontaneous, caspase-8- dependent apoptosis and hyper-sensitivity to the immune/inflammatory cytokines TNFα and TRAIL. Strikingly, FLIP-null lung cancer cells fail to engraft even in highly immunodeficient orthotopic models that lack TRAIL-expressing immune cells but retain TNFα-expressing monocytes. Moreover, silencing of TNFR1 or TNFα but not TRAIL-R2 rescued constitutive caspase-8-dependent apoptosis in FLIP null lung cancer cells, implicating TNFα/TNFR1 in mediating this apoptotic response. Mechanistically, we find that mutant KRAS sustains FLIP expression via ERK1/2 signalling, thereby protecting cells from caspase-8 activation. Notably, KRAS inhibition downregulates FLIP, sensitising cells to TNFα- and TRAIL-induced apoptosis. These findings uncover a novel KRAS–ERK–FLIP axis that protects tumour cells from caspase-8-mediated apoptosis and reveal FLIP as a key survival factor co-opted by KRAS -mutant lung cancers. Beyond identifying FLIP as a promising therapeutic target in KRAS mutant lung cancer, our work also provides mechanistic insight into the pro-apoptotic effects of KRAS inhibitors and suggests that FLIP expression may serve as a predictive biomarker to enhance patient stratification and the therapeutic efficacy of these agents in lung cancer.

Therapy resistance is attributed to over 80% of cancer deaths per year, emphasizing the urgent need to overcome this challenge for improved patient outcomes. Despite its widespread use in colorectal cancer (CRC) treatment, resistance to 5-fluorouracil (5FU) remains poorly understood. As an antimetabolite, 5FU imposes substantial metabolic stress, forcing cells that survive treatment to rapidly adapt. We explored acute 5FU-driven changes in mitochondria, the organelle critical for coordinating metabolic stress responses. Here we demonstrate in a range of CRC models that 5FU treatment promotes mitochondrial biogenesis and increases mitochondrial function in surviving cells. Furthermore, we show that targeting mitochondrial metabolism, particularly by inhibiting Complex I, sensitizes CRC cells to 5FU, resulting in delayed tumour growth and prolonged survival in preclinical models. Additionally, analysis of patient data suggests that oxidative metabolism signatures may predict responses to 5FU-based chemotherapy. These findings shed light on mechanisms underlying 5FU resistance and propose a rational strategy for combination therapy in CRC, emphasizing the potential clinical benefit of targeting mitochondrial metabolism to overcome resistance and enhance patient outcomes.

VEGF and IL8 expression is altered and plays a role in resistance in enzalutamide-resistant prostate cancer cell lines. Cells were treated with anti-IL8 nAb (5 μg/mL), anti-VEGF nAb (10 μg/mL), or the highest concentration of isotype-matched human IgG antibody. A, qRT-PCR data comparing basal expression of VEGFA and CXCL8 (IL8) expression in LNCaP-Parental (PAR), LNCaP-EnzR, CWR-R1-Par, and CWR-R1-EnzR cell lines. B, ELISA data comparing basal secretion of VEGF and IL8 in LNCaP-Par, LNCaP-EnzR, CWR-R1-Par, and CWR-R1-EnzR cells. Data shown are the mean±SEM of N = 4 experiments. C–F, Bar graphs demonstrating the effect of combined treatment with anti-IL8 nAb and anti-VEGF nAb on the response of LNCaP-Par, LNCaP-EnzR, CWR-R1-Par, and CWR-R1-EnzR cells to 10 μmol/L Enz over 72 hours in (C and D) normoxia and (E and F) hypoxia. All experiments data represented as the mean ± SEM of N = 3 experiments, unless otherwise stated and statistical analysis was carried out using a Mann-Whitney U test: *, P < 0.05; **, P < 0.01.

Enzalutamide treatment directly modulates tumor vasculature. LNCaP in vivo tumors (N = 4/group) treated with enzalutamide (Enz) in the presence or absence of anti-IL8 nAb (50 μg/mL) and/or anti-VEGF nAb (100 μg/mL) for 28 days and measured time-dependent changes in (A) intratumoral oxygenation concentration (mmHg) and (B) tumor vessel density. Values shown are mean±SD. Treatment schematic is illustrated above the graph. Stereological methods were used to analyze the change in vessel density over time in all treatment groups and values were used to calculate percentage area covered by vessels. C, qRT-PCR data demonstrating detectable basal AR expression in LNCaP and HUVEC cells. Data shown are mean±SEM; N = 4 experiments. D, Representative images of prostate tumor stained for (i, ii) AR (20X and 40X), (iii, iv) CD31 (20X and 40X), and (v) hematoxylin and eosin (20X). Endothelial cells (EC) and vessels are marked by black arrows in the prostate tumor. E, Effect of 10 μmol/L Enz on in vitro tubule formation over 10 days. The number of junctions was measured using AngioSys 2.0 software. Data presented are mean±SEM of N = 8 fields of view; N = 4 experiments (F) Effect of 10 μmol/L Enz on viability of HUVEC cells following either 72-hour normoxic or hypoxic conditions. Data shown are mean±SEM; N = 3 experiments. G, Effect of 10 μmol/L Enz on apoptosis in HUVEC cells following either 72-hour normoxic or hypoxic conditions. Data shown are mean±SEM; N = 3 experiments. H, Effect of 10 μmol/L Enz on the colonization of PC3 cells over 5 days in the in ovo assay. Data shown are mean ± SEM of N = 17 embryos for DMSO and N = 23 embryos for the Enz. For all data, control cells were treated with equivalent volume of DMSO and statistically significant differences were determined using a Student two-tailed t test or Mann–Whitney U test: *, P < 0.05; **, P < 0.01; ***, P < 0.001.

Treatment-mediated hypoxia-promoted VEGF and IL8 signaling influences AR expression and activity, angiogenesis and enzalutamide response. A and B, Effect of 10 μmol/L enzalutamide (Enz) on viability of LNCaP (A) or C4-2B (B) cells under normoxia and hypoxia for 72 hours. Control cells are presented as 100% for either untreated normoxic cells (left y-axis) or cells treated with hypoxia alone (right y-axis). As a control, were treated with an equivalent volume of DMSO. Data shown are mean ± SEM of N = 3 experiments. C, Cell-cycle analysis of 10 μmol/L Enz treated LNCaP and C4–2B cells following 72 hours. Control cells were treated with an equivalent volume of DMSO. Data are mean±SEM of N = 4 experiments. D, Effect of hypoxia on expression of the AR in LNCaP cells (top), and ARFL and AR-V7 expression in 22Rv1 (middle), and CWR-R1 (bottom) cells. Blots shown are representative of N = 3 experiments. Equal loading was assessed using β-Actin. Relative expression was determined by densitometry using Image J software. E, Luciferase reporter assay demonstrating the effect of 2 to 24-hour hypoxia on AR transcriptional activity in LNCaP and 22Rv1 cells. Data are mean±SEM of N = 3 experiments. F, Luciferase reporter assay demonstrating the effect of hypoxia (6 hours) on AR transcriptional activity in LNCaP and 22Rv1 cells. Data are mean±SEM of N = 3 experiments. G, Immunofluorescent analysis of AR distribution in LNCaP cells cultured under normoxia or hypoxia (6 hours). Images present a merged image, DAPI staining (Blue), and AR-related fluorescence (Red). H, qRT-PCR data demonstrating detectable KLK3 (PSA) expression in LNCaP, 22Rv1, and CWRR1 cells. Data shown are mean±SEM of N = 3 experiments. For all experiments, statistical analysis was carried out using a Student two-tailed t test, Mann–Whitney U test, or 2-way ANOVA with Bonferroni post-tests: *, P < 0.05; **, P < 0.01; ***, P < 0.001.

In vivo expression of CASP8 and CFLAR (FLIP) modulate response to MEDI3039 in PDX models. A, Change in percent tumor growth from baseline was measured at day 18 in 18 CRC PDX models treated with a fixed dose of MEDI3039. B, Tumor plots of responder, nonresponder, and partial response models. x-axis, days; y-axis, tumor volume. Arrows indicate treatment with MEDI3039. Red line, MEDI039-treated mice; blue line, untreated mice. C, Tumor CASP8 mRNA expression in PDX nonresponders (red) and responders (blue) with MEDI3039 (each circle represents a tumor from a single mouse). D, Comparison of CASP8:CFLAR ratio in MEDI3039 responder (blue) and nonresponder (red) PDX models.

Background:Identification of the consensus molecular subtypes (CMS) opened significant potential for understanding the tumor biology and intertumoral heterogeneity of colorectal cancer (CRC). However, molecular subtyping in CRC traditionally relies on bulk transcriptomics, therefore, lacks spatial and single-cell level aspect. Methods:We constructed tissue microarrays using tumor cores from 222 CRC patients. Arrays were stained and imaged using 54 cell identity and cancer hallmark markers, delivering spatially resolved protein profiles of >2 million cells. RNA sequencing data and CMS classification were also available for these patients. After segmentation of cancer, stromal and immune cells, we investigated intratumoral heterogeneity within CMS subtypes using spatially resolved single-cell protein profiling (>2 million cells). We compared cell types, their spatial organization and their expression of cancer hallmark-related proteins in CMS 1-4 subtypes. Results:We revealed tissue atlases illustrating the cell types/states, spatial heterogeneity, cellular neighborhoods, cellular network, and single-cell protein profiles of CMS tumors. CMS1 tumors had more CD3+, CD8+, and PD1+ immune cells that were found in the epithelial layer frequently. CMS1 was also associated with higher levels of metabolic reprogramming markers such as upregulated glycolysis. CMS2 showed immune segregation, reactive stroma patterns and higher levels of apoptotic and proliferative signaling proteins. CMS3 exhibited clustered cancer cells with high RIP3 levels, suggesting a pro-inflammatory microenvironment. CMS4 displayed stromal-centric and immune-evasive tumors characterized by decreased HLA-1 levels and regulatory T-cell exclusion from epithelium. Conclusion:We present a spatial protein atlas of CRC at single-cell resolution and demonstrate novel aspects of CMS tumour structures.

Death receptor 5 (DR5) is a key mediator of the extrinsic apoptotic pathway that is often upregulated in tumors, rendering it an attractive target for cancer therapy. Activation of DR5 requires oligomerization, which can be achieved through multivalent presentation of DR5 ligands on nanoparticles. DR5-targeted nanoparticles can efficiently agonize DR5 to inhibit the growth of human xenografts, although it remains unclear whether these effects would translate to a syngeneic tumor model with an immunocompetent microenvironment. Here, we develop camptothecin-loaded polymeric nanoparticles coated with the murine DR5 antibody MD5-1 and demonstrate their pro-apoptotic effects in murine cell lines in vitro. Moreover, we show that these nanoparticles inhibit the growth of MC38 colorectal allografts in vivo by >90% relative to control nanoparticles. Collectively, our work confirms that the antitumor efficacy of DR5-targeted nanoparticles extends to syngeneic models, paving the way for future studies to explore their impact on tumor immunity and the surrounding microenvironment.

The thiol-ene reaction between an alkene and a thiol can be exploited for selective labelling of cysteine residues in protein profiling applications. Here, we explore thiol-ene activation in systems from chemical models to complex cellular milieus, using UV, visible wavelength and redox initiators. Initial studies in chemical models required an oxygen-free environment for efficient coupling and showed very poor activation when using a redox initiator. When thiol-ene activation was performed in protein and cell lysate models, all three initiation methods were successful. Faster thiol-ene reaction was observed as the cysteine and alkene were brought into proximity by a binding event prior to activation, leading to quicker adduct formation in the protein model system than the chemical models. Furthermore, in the protein-protein coupling, none of the activators required an oxygen-free environment. Taken together, these observations demonstrate the broad potential for thiol-ene coupling to be used in protein profiling.

MEDI3039 sensitivity is significantly affected by FLIP(L)–caspase-8 ratio. A, Percentage cell death at 24 hours post MEDI3039 10 pmol/L in a panel of colorectal cell lines. B, Scatter plot of summary correlation analysis of cell death protein expression and percent cell death induced in response to MEDI3039 across panel of colorectal cancer cell lines. C, CASP8/FLIP or CASP8/MCL1 ratio protein expression versus MEDI3039-induced cell death. Each circle indicates a cell line. MEDI3039 AUC for cell lines for different cell types split according to discretized CASP8/FLIP (D) or CASP8/MCL1 (E) ratio (mRNA expression).

IL8 and VEGF signaling sustain AR pathway activation and modulate response to enzalutamide. Cells were treated with anti-IL8 nAb (5 μg/mL), anti-VEGF nAb (10 μg/mL) or the highest concentration of isotype-matched human IgG antibody. A, Effect of anti-IL8 nAb/anti-VEGF nAb on the response of hypoxic or normoxic LNCaP cells to 10 μmol/L Enazlutamide (Enz) over 72 hours. Data shown are mean ± SEM of N = 3 experiments. B, Effect of anti-IL8 nAb and/or anti-VEGF nAb on hypoxia (6 hours)-induced AR and AR-V7 expression in LNCaP and CWRR1 cells. Blots are representative of N = 3 experiments. Equal loading was assessed using GAPDH. Relative expression was determined by densitometry using Image J software. C, Effect of 10 μmol/L E (Enz) with anti-IL8 nAb (5 μg/mL), anti-VEGF nAb (10 μg/mL) or the highest concentration of isotype-matched human IgG antibody on viability of LNCaP cells under normoxia and hypoxia for 72 hours. D, Effect of VEGF (2 ng/mL) or rhIL8 (3 nmol/L) on tubule formation over 10 days. Suramin (20 μmol/L) was included as a negative control. E, Effect of CM harvested from LNCaP cells cultured in hypoxia for 24 hours, in the presence or absence of anti-IL8 nAb and/or anti-VEGF nAb, on tubule formation over 10 days. For both experiments (D and E), number of junctions was measured using AngioSys 2.0 software. Data are mean±SEM of N = 8 fields of view. F, Tumor growth data (N = 5/group), obtained by measuring tumor volume every 2 days for 28 days. Treatment groups were: vehicle-only (VC); Enz (4 mg/kg); Enz (4 mg/kg) + IgG (150 μg/mL); Enz (4 mg/kg) + anti-VEGF nAb (100 μg/mL); and Enz (4 mg/mL) + anti-VEGF (100 μg/mL) and anti-IL8 (50 μg/mL) nAbs. Treatment schematic is shown above graph. Data points represent mean ± SEM. G, Average tumor weights at study completion. Values are mean ± SEM (N = 5/group). For all experiments statistical analysis was carried out using Student two-tailed t test or Mann–Whitney U test: *, P < 0.05; **, P < 0.01; ***, P < 0.001.

OBJECTIVES:To evaluate the mechanisms and signalling pathways involved in the pathogenesis of oral squamous cell carcinoma (OSCC) that are promoted by Fusobacterium nucleatum infection across human participant, in vivo and in vitro studies. DESIGN:This systematic review was conducted in accordance with the PRISMA guidelines to address the question: What mechanisms and potential signalling pathways are implicated in the pathogenesis of OSCC facilitated by F. nucleatum infection, compared with non-infected controls? Searches were performed across three electronic databases: Scopus, Web of Science, and MEDLINE. RESULTS:Sixty-three studies met the inclusion criteria for the systematic review. Studies involving human participants revealed alterations in bacterial genes related to lipopolysaccharide (LPS) synthesis, bacterial mobility and flagellar assembly. Additionally, alteration in host genes including DNA repair, tumour protein P53 (TP53), toll-like receptors and proinflammatory genes such as interleukin (IL)1β, IL8, and IL6 were reported. In vivo studies reported upregulation of cyclin D1 and IL6 following F. nucleatum infection. In vitro studies demonstrated changes in epithelial-mesenchymal transition markers such as E-cadherin, N-cadherin, vimentin, and zinc finger E-box binding homeobox (ZEB)1/2, along with increased expression of inflammatory markers, including IL-8 and IL-6 following F. nucleatum infection. CONCLUSION:The findings from this systematic review highlight a significant molecular response to F. nucleatum infection in oral cancer. The results underscore the complex interaction between F. nucleatum and host molecular pathways, offering valuable insights into how this bacterium may contribute to oral cancer development and progression.

Silencing of apoptotic pathway genes confers resistance to agonists of the death receptor pathway. Volcano plots of genes enriched or depleted for gRNA when rTRAIL-treated cells were compared with DMSO vehicle control cells following transduction with a genome-wide CRISPR/Cas9 library in MSTO-211H mesothelioma (A) and PC-9 lung adenocarcinoma (B) cells. Each dot represents gene-wise scores for MAGeCK gene level analysis with genes of interest highlighted. The dotted line indicates an FDR of 0.1. x-axis, log2 fold change of mean gRNA reads per genes comparing treatment to DMSO replicates. y-axis, −log10 FDR for genes based upon their negative (pink and red dots) and positive (blue dots) fold change and FDR calculated by the MAGeCK algorithm. C, Confirmation of deletion of target apoptotic genes following transfection with synthetic crRNA in MSTO-211H, NCI-H28, and H2804 cancer cells. D, Six-day viability assay in MSTO-211H cells following deletion of specific apoptotic genes and treatment with either rTRAIL or MEDI3039. y-axis: viability effect relative to control cells. E, Volcano plots as in A and B illustrating results of SAM CRISPR activatory screen in PC-9 cells treated with rTRAIL. F, MSTO-211H isogenic cell lines were screened versus the parental cell line with a concentration range of 60 compounds and viability measured at day 6. The AUC values for each isogenic cell line and the matched parental Cas9 line were subtracted to calculate a ΔAUC value, with high (positive) values indicating increased resistance to that compound in the isogenic lines, and low (negative) values increased sensitivity. x-axis: name of compounds screened. y-axis: ΔAUC values.

Sensitivity of cancer cell lines to MEDI3039. A panel of 758 cancer cell lines was treated for 6 days with a concentration range of the death receptor agonist MEDI3039 and viability measured as AUC. A, Frequency distribution plot illustrating bimodal distribution of MEDI3039 AUC values for solid (green) and hematopoietic (blue) cell lines. B, AUC values with SD error bars for each cell line (circles) in 19 tissue types and individually colored according to high or low CASP8 mRNA expression as defined by the bimodal mid-point. C, Plot of cell line expression of most significant CASP8 microarray probeset ranked on the basis of sensitivity to MEDI3039. D, A two-tailed t test was calculated for 30 tissue types using MEDI3039 AUC values and CASP8 expression, and the P value indicated (E) predictive 9 probeset (7 gene) predictive geneset identified by vSURF random forest analysis of microarray data. F, AUC plot demonstrating ability of 9 probeset predictive geneset to classify solid cell lines as “sensitive” or “resistant.” See Supplementary Fig. S2B for description of cancer type abbreviations used in B and D.

Drug combinations to overcome rTRAIL resistance in isogenic cell lines. A, Isogenic MSTO-211H cell lines were screened against 59 compounds in combination with a fixed dose of MEDI3039 (100 pmol/L). Viability was measured at day 6. For each combination, a ΔAUC was calculated by subtracting the observed from the expected AUC (based upon the activity of the MEDI3039 concentration as a single agent). Values >0.2 are indicative of synergy. x-axis: name of compounds screened. Bid-KO MSTO-211H or Bid-mutant Sup-T1 cells were treated with a concentration range of the IAP inhibitor AZD5582 (B) or LCL161 (C) for 6 days (blue line) or in combination with a fixed concentration of MEDI3039 (green, IC90 values of parental cell line). Indicated is the effect of the fixed concentration of MEDI3039 (red dotted) and the expected (additive) effect of the combination (gray dotted). x-axis: log10 scale concentration range. y-axis: relative viability effect. D, Clonogenic survival assays at day 14 in Cas9 versus crBID MSTO-211H and PC-9 cells treated with the indicated IAP inhibitors AZD and LCL161 as single agents or combined with MEDI3039. AZD, AZD5582. E, Annexin V/PI staining of Cas9 versus BID KO MSTO-211H and PC-9 cells following 24-hour treatment with MEDI3039 ±10 nmol/L AZD5582.