1. Introduction
Tumor-associated inflammation is intimately linked with tumor progression and therapy response [1]. Interleukin (IL)-1β is an important mediator of tumor-associated inflammation and its inhibition via the monoclonal antibody canakinumab was recently shown to possess strong protective effects against incident lung cancer in an exploratory analysis of the canakinumab anti-inflammatory thrombosis outcomes study (CANTOS) [2]. Unexpectedly, the phase III CANOPY-2 trial (
Multiple lines of evidence dictate that tumor genomic alterations largely define tumor-associated inflammation and the efficacy of immune-directed therapies [1]. To this end, NSCLC with high mutation burden and a smoking-associated trinucleotide signature were found to display more favorable and durable responses to the immune checkpoint inhibitor pembrolizumab targeting programmed cell death-1 (PD-1) [4]. Moreover, STK11/LKB1 alterations were reported to be cardinal drivers of primary resistance to PD-1 inhibitors in KRAS-mutant LUAD, the most frequent and lethal histologic subtype of NSCLC [5]. Experimental evidence supports that the immune landscape and vulnerabilities of various tumor types can rely on single mutated driver oncogenes such as KRAS and MYC that orchestrate distinct transcriptional programs, dictate a tumor’s specific pro-inflammatory mediator secretory profile, and largely define the cellular composition of the tumor microenvironment [6,7]. In this regard, oncogenic KRAS is known to cooperate with pro-inflammatory nuclear factor (NF)-κB signaling in cancer cells to drive stemness, pro-inflammatory mediator elaboration, and responsiveness to IL-1β signaling [8,9,10,11], and is ideally positioned as a biomarker of therapeutic response to anti-IL-1β therapy.
Here, we show that KRAS-mutant cancers display specific non-oncogene addiction to host-provided IL-1β in humans and mice. We further elucidate how these tumors activate NF-κB in tumor-associated macrophages in order to elicit the IL-1β they require for sustained growth. Mutant KRAS-IL-1β addiction is mediated via secretion of the glycoprotein versican (VCAN) by tumor cells, which inhibits the NF-κΒ kinase (IKK) β in macrophages, resulting in IL-1β release into the tumor microenvironment. Importantly, the VCAN-IKKβ axis is shown to be required for the sustained growth of KRAS-mutant tumors and to constitute a diagnostic and prognostic biomarker of these tumors. Finally, we show how non-oncogene addiction of KRAS-mutant cancers to myeloid IL-1β can be abolished by pharmacologic inhibition of IL-1β or the VCAN target toll-like receptor (TLR) 2. Our findings can be directly translated to, and tested, in clinical trials of IL-1β inhibition against genomically stratified LUAD.
2. Materials and Methods
2.1. Murine and Human Study Approval
All mice used for these studies were bred at the Department of Medicine of the University of Patras, Greece. Experiments were prospectively approved by the Veterinary Administration of the Prefecture of Western Greece (approval #276134/14873/2) and were conducted according to the European Union Directive 2010/63/EU [12]. Male and female experimental mice were sex-, weight (20–25 g)-, and age (6–12 weeks)-matched. Exact sample sizes (n) are included in the figures and their legends. Animals were assigned to experimental groups by randomization (when n ≥ 20) or alternation (when n < 20) with controls and experimental mice always being littermates, and transgenic animals enrolled case-control-wise. Data were collected by at least two blinded investigators from samples coded by non-blinded investigators. The Munich lung adenocarcinoma and Patras pleural effusion [13,14] clinical studies were conducted in accordance with the Helsinki Declaration [15], were approved by the Ludwig-Maximilians-University Munich Ethics Committee (approval #623-15) and the University of Patras Ethics Committee (approval #22699/21.11.2013), were registered with the German Clinical Trials Register (Deutsches Register Klinischer Studien; #DRKS00012649 [16]) and with
2.2. Reagents
D-Luciferin potassium salt CAS# 115144-35-9 was from Biosynth (Lake Constance, Switzerland). Clodronate (Dichloromethylenediphosphonic acid disodium salt, CAS# 22560-50-5) and Hoechst 33258 nuclear dye (CAS# 23491-45-4), were from Sigma-Aldrich (St. Louis, MO, USA). Egg-phosphatidylcholine (CAS# 97281-44-2) was from Avanti Polar Lipids (Alabaster, AL, USA). Lentiviral shRNA, puromycin (CAS# 58-58-2) and lipopolysaccharide (LPS; catalogue # sc-3535) were from Santa Cruz (Dallas, TX, USA). Geneticin (G418; catalogue # 10131035) was from Thermo Fisher Scientific (Waltham, MA, USA). Recombinant human active versican (VCAN; catalogue # RPB817Mu01) and osteopontin (secreted phosphoprotein 1, SPP1; catalogue # APA899Hu61) were from Cloud-Clone Corp (Houston, TX, USA) and all other recombinant proteins were from Immunotools (Friesoythe, Germany). Bortezomib (CAS# 179324-69-7) was from Selleckchem (Houston, TX, USA). IL-1β ELISA (catalogue # 900-K47) was from Peprotech (London, UK). Primers were from VBC Biotech (Vienna, Austria). Isunakinra (EBI-005), a recombinant protein that binds to the interleukin-1 receptor 1 (IL1R1) and potently blocks IL-1α and IL-1β beta [18], was from Buzzard Pharmaceutical (Stockholm, Sweden), and the TLR1/TLR2 antagonist Cu-CPT22 or 3,4,6-Trihydroxy-2-methoxy-5-oxo-5H-benzocycloheptene-8-carboxylic acid hexyl ester (CAS# 1416324-85-0) [19] was from Merck (Darmstadt, Germany). Primers and lentiviral shRNA pool sequences are listed in Tables S4 and S5 and antibodies in the respective methods sections.
2.3. Cells
Lewis lung carcinoma (LLC, RRID:CVCL_4358), B16F10 skin melanoma (male, RRID:CVCL_0159), and PAN02 pancreatic adenocarcinoma cells (male, RRID:CVCL_D627) were from the National Cancer Institute Tumor Repository (Frederick, MD, USA). RAW264.7 murine myelomonocytic leukaemia (male, RRID:CVCL_0493) and mouse lung epithelial 12 (MLE12, female, RRID:CVCL_3751) cells were from ATCC (Manassas, VA). MC38 colon adenocarcinoma (female, RRID: CVCL_B288) and AE17 mesothelioma (female, RRID:CVCL_4408) cells were gifts from Dr. Barbara Fingleton (Vanderbilt University, Nashville, TN, USA) and Dr. Y.C. Gary Lee (University of Western Australia, Perth, Australia), respectively. FVB urethane-induced lung adenocarcinoma (FULA1) cells were produced in our laboratories (female, RRID: CVCL_A9KV). The cells were cultured at 37 °C in 5% CO2-95% air using Dulbecco’s modified Eagle’s medium (DMEM) supplemented with 10% fetal bovine serum, 2 mM L-glutamine, 1 mM pyruvate, 100 U/mL penicillin, and 100 mg/mL streptomycin. For in vivo injections, the cells were trypsinized, incubated with Trypan blue, counted with a grid hemocytometer according to the Neubauer method, and only 95% viable cells were used for the experiments. All in vitro experiments were repeated independently at least three times and the stated n always reflects the biological and not technical sample size. All cell lines have been repeatedly reported, were re-sequenced for Kras mutations and their status was verified to be the same as previously reported, and were tested annually for identity by short tandem repeats and for Mycoplasma spp. by PCR using primers GGGAGCAAACAGGATTAGATACCCT and TGCACCATCTGTCACTCTGTTAACCTC (amplicon size 270 bp) [10,11,20,21,22,23].
2.4. Experimental Mice
NGL and HLL NF-κΒ reporter mice are described elsewhere [24,25]. Mice obtained from Jackson Laboratories (Bar Harbor, Lake Shore, MN, USA) were wild–type (WT) C57BL/6J mice (C57BL/6; #000664), B6.129(Cg)-Gt(ROSA)26Sortm4(ACTB-tdTomato,-EGFP)Luo/J dual membranous fluorescent Cre-recombinase reporter mice (mT/mG; #007676) [26], B6.129P2-Lyz2tm1(cre)Ifo/J mice that express Cre-recombinase under control of the Lyz2 promoter (Lyz2.Cre; #004781) [21,27], B6.129P2-Gt(ROSA)26Sortm1(DTA)Lky/J mice that express Diphtheria toxin upon Cre-mediated recombination that results in cell suicide (Dta; #009669) [21,28], and B6;129S-Tnftm1Gkl/J Tnf-deficient mice (Tnf−/−; #005540) [11,29]. B6.B4B6-Chuk<tm1Mpa>/Cgn (Chukf/f) and B6.B4B6-Ikbkb<tm2.1Mpa>/Cgn (Ikbkbf/f) mice that carry conditional Chuk and Ikbkb alleles that are deleted upon Cre-recombinase expression [30,31], as well as Il1btm1Yiw Il1b-deficient mice (Il1b−/−; MGI #215739631) [32] and Cpa3.Cre+/– mast cell-deficient mice in which mast cells undergo Trp53-mediated apoptosis (Cpa3.Cre) [33] were described elsewhere and were kindly donated by their founders. All mice used for these studies were originated from or back-crossed > F12 generations to the C57BL/6 background. For these studies, n = 929 mice were used.
2.5. Mouse Tumor Models
For the generation of solid tumors, mice were injected subcutaneously (s.c.) in the shaven rear flank dermis with 5 × 105 tumor cells in 100 μL of phosphate-buffered saline (PBS), as described elsewhere [10,11,20,22]. Mice were weekly examined for tumor volume (V) by measuring three vertical tumor diameters (d1, d2, d3) using the formula V = π × d1 × d2 × d3 and were killed when the tumor volume reached 1 cm3 (PANO2 cells) or 2 cm3 (all other cell lines). For the induction of malignant pleural effusions (MPE), mice received intrapleural injections of 2 × 105 cancer cells suspended in 100 μL PBS and were sacrificed when showing signs of sickness or at the time-points indicated (14–28 days post-tumor cell delivery depending on the cell line used) [10,11,22]. In all models, both the mice and the inoculated cancer cells were always syngeneic to avoid inflammatory allograft rejection and artificial NF-κB activation.
2.6. Bioluminescence and Biofluorescence Imaging
Mice were imaged for NF-κB reporter bioluminescent signal daily starting at day 10 post-tumor cell injection until sacrifice. For this, mice were anesthetized by isoflurane inhalation and were imaged for bioluminescence on a Xenogen Lumina II (PerkinElmer, Waltham, MA, USA) 5–20 min after delivery of 1 mg D-Luciferin potassium salt diluted in 100 μL of sterile water into a retro-orbital vein. Pleural tumors isolated from NGL mice were also imaged ex vivo for green biofluorescence using 410–440 nm background control excitation, 445–490 nm experimental excitation, and 515–575 nm emission passbands on a Xenogen Lumina II. Cells were imaged for bioluminescence on a Xenogen Lumina II 0, 4, 8, 16, and 24 h after a single addition of 300 μg/mL (equivalent to 1 mM) D-luciferin to the culture media. Data were analyzed using Living Image v.4.2 (PerkinElmer, Waltham, MA, USA) as described previously [10,11,20,21,22,34].
2.7. Sequencing
Genomic DNA was extracted from cell lines using the GenElute Mammalian Genomic DNA Miniprep Kit (Sigma-Aldrich). Kras exons 1–3 were amplified by PCR using Phusion Polymerase (New England Biolabs, Ipswich, MA, USA) and 60 °C annealing temperature. Primers are described in Table S4. PCR products were analyzed on 1% agarose gels, purified by QIAquick Gel Extraction Kit (Qiagen, Hilden, Germany) and sequenced by Eurofins Genomics (Ebersberg, Germany).
2.8. Constructs and Transfections
Control shRNA (shC, sc-108080-V; target sequences are proprietary of the manufacturer) and anti-mouse Vcan shRNA (shVcan, sc-41904–V) pools were from Santa Cruz. The pNGL construct and lentiviral shRNA pools for the silencing of Kras, Chuk, Ikbkb, Ikbke, and Tbk1 were described previously [11]. Lentiviral shRNA catalog numbers and target sequences are listed in Table S5. For stable plasmid transfections, 105 RAW264.7 cells were transfected with 5 μg DNA using Xfect (Takara, Mountain View, CA, USA), followed by selection by G418 (400–800 μg/mL). For stable shRNA transfection, 105 tumor cells were transfected with lentiviral particles, and clones were selected by puromycin (2–10 μg/mL) [10,11].
2.9. Intrapleural Catheter
For in vivo MPE drainage, a 1.2 cm-long catheter bearing serial fenestrations at 1 mm intervals was used, according to the detailed model description reported previously [35]. Mice were anesthetized using isoflurane and the catheter insertion site was shaved and disinfected using 70% ethanol and 10% povidone iodide, and the catheter was then installed into the pleural space and sutured under the skin. Mice were imaged pre- and post-MPE drainage and were sacrificed thereafter.
2.10. Cytology
MPE fluid was treated with red blood cell lysis buffer (155 mM NH4Cl, 12 mM NaHCO3, 0.1 mM EDTA) and MPE cells were centrifuged and stained with May-Grünwald-Giemsa. Slides were then mounted with Entellan (Merck Millipore, Darmstadt, Germany) and microscopically analyzed for the differential counting of pleural cells. Pleural lavage was performed by injecting 1 mL of saline intrapleurally and recovering it after 30 s. Pleural cells were enumerated with a haemocytometer, were centrifuged, were stained with May-Grünwald-Giemsa or with anti-rabbit F4/80 antibody (ab111101; Abcam, London, UK; RRID:AB_10859466) and hematoxylin, and were microscopically analyzed for the differential counting of pleural cells.
2.11. Flow Cytometry
Pleural effusion cells were treated with red blood cell lysis buffer (155 mM NH4Cl, 12 mM NaHCO3, 0.1 mM EDTA), enumerated, and 0.5–1.0 × 106 cells were processed for antibody staining. Pleural tumors were dissociated using 70 μm strainers (BD Bioscience, San Jose, CA, USA), enumerated, and 0.5–1.0 × 106 cells were processed for antibody staining. BMDM were enumerated and 0.5–1.0 × 106 cells were processed for antibody staining. All of the samples were suspended in 50 μL PBS with 2% FBS and 0.1% NaN3, and stained with the following antibodies: anti-CD45 (11-0451-85; eBioscience, Santa Clara, CA, USA; RRID:AB_465051), anti-CD11b (12-0112-82; eBioscience; RRID:AB_2734869), anti-Ly6C (45-5932-82; eBioscience; RRID:AB_2723343), anti-F4/80 (123128; Biolegend, San Diego, CA, USA; RRID:AB_893484), anti-Ly6G (127624; Biolegend; AB_10640819), anti-GFP eFluor® 660 (50-6498-82; eBioscience; RRID:AB_11043268), anti-MHC Class II (17-5321; eBioscience; RRID:AB_469454), Alexa Fluor® 647 anti-CD206 (141712; Biolegend; RRID:AB_10900420), biotinylated anti-firefly Luciferase (ab634; Abcam, London, UK; RRID:AB_305434), and streptavidin (17-4317-82; eBioscience), for 20 min in the dark at a concentration of 0.1 μg/106 cells. Samples were analyzed on a CyFlowML flow cytometer using the FloMax Software (Partec, Darmstadt, Germany; RRID:SCR_014437), Flowing Software v.2.5.1 ([36]; RRID:SCR_015781) and FlowJo Software v10.6.2 (BD Bioscience, San Jose, CA, USA; RRID:SCR_008520).
2.12. Immunohistochemistry
For dark field immunofluorescence, pleural tumors were fixed in 4% paraformaldehyde overnight at 4 °C, cryoprotected with 30% sucrose, embedded in Tissue-Tek (Sakura, Tokyo, Japan) and stored at −80 °C. Cryosections of 10 μm were then post-fixed in 4% paraformaldehyde for 10 min, treated with 0.3% Triton X-100 for 5 min, blocked for 1 h in 1× phosphate-buffered saline (PBS) containing 10% fetal bovine serum (FBS), 3% bovine serum albumin (BSA), and 0.1% Tween 20, and then incubated with the indicated primary antibodies overnight at 4 °C. Sections were subsequently treated with fluorescent secondary antibodies, counterstained with Hoechst 33258 (CAS# 23491-45-4) and mounted with Mowiol 4-88 (Calbiochem, Darmstadt, Germany; CAS# 9002-89-5). The following primary antibodies were used: mouse anti-GFP (1:200 dilution; sc-9996; Santa Cruz, Dallas, TX, USA; RRID:AB_627695), rat anti-CD68:Alexa Fluor® 488 (MCA1957A488T; AbD Serotec, Kidlington, UK; RRID:AB_1102282), mouse anti-CD45 FITC (11-0451-85; eBioscience; RRID:AB_465051), and rabbit anti-PCNA (1:3000 dilution; ab18197; Abcam, London, UK; RRID:AB_444313). Alexa Fluor donkey anti-mouse 488 (A21202; RRID:AB_141607), Alexa Fluor goat anti-rat 568 (A11077; RRID:AB_141874), and Alexa Fluor donkey anti-rabbit 568 (A10042; RRID:AB_2534017) secondary antibodies used at 1:500 dilution were from Thermo Fisher Scientific (Waltham, MA, USA). For isotype control, the primary antibody was omitted. Fluorescent microscopy was carried out either on an AxioObserver D1 inverted fluorescent microscope (Zeiss, Jena, Germany) or a TCS SP5 confocal microscope (Leica, Wetzlar, Germany) with 20×, 40×, and 63× lenses. Digital images were processed with Fiji academic freeware (RRID:SCR_002285) [37]. All quantifications of cellular populations were obtained by counting at least five random non-overlapping tumor-containing fields of view per section. Bright field immunohistochemistry was done as described previously [10,21,22], and the following antibodies were used: rabbit anti-versican (1:100; E-AB-36300; Elabscience, Wuhan, China), and mouse secondary anti-rabbit (1:5000; ab191866; Abcam, London, UK; RRID:AB_2650595). All quantifications of cellular populations were obtained by counting at least five random non-overlapping tumor-containing fields of view per section.
2.13. Bone Marrow Transfer (BMT) and Liposomal Clodronate
For adoptive BMT experiments described in detail elsewhere [10,11,20], wild-type (WT) and NF-κΒ.eGFP.LUC (NGL) recipient mice on the C57BL/6 background received total body irradiation (1100 Rad) followed 12 h later by 107 intravenous (via retro-orbital injection) whole bone marrow cells obtained from WT and NGL donors. One irradiated mouse per group was not transplanted with BMT to control for effective elimination of endogenous bone marrow and died 5–15 days post-irradiation. After one month, allowing for complete bone marrow reconstitution by chimeric bone marrow cells, liposomal clodronate was prepared as described previously [25,38] and 500 μg were administered intrapleurally. After yet another month required for the replacement of pleural myeloid cells by transplanted bone marrow cells [38], the mice were injected with tumor cells.
2.14. Bone Marrow Derived Macrophages (BMDM)
For BMDM generation, 107 bone marrow cells were plated and cultured for 7 days in the presence of 100 ng/mL macrophage colony stimulating factor (M-CSF). Where appropriate, at day 6 of the culture, recombinant human versican (1 nM) was added to the culture medium or, alternatively, the culture medium was removed and BMDM were exposed to cancer cell-conditioned media for 4 h. Culture supernatants were then isolated for ELISA and cells were processed for western blot, flow cytometry, or qPCR.
2.15. Immunoblotting
Nuclear and cytoplasmic protein extracts were prepared using the NEPER Extraction Kit (Thermo Fisher Scientific, Waltham, MA, USA), separated by SDS-PAGE and electroblotted to PVDF membranes (Merck Millipore, Darmstadt, Germany). Membranes were probed with the following primary antibodies: anti-IKKα (1:1000 dilution; 2682; Cell Signaling, Danvers, MA, USA; RRID:AB_331626), anti-IKKβ (1:1000 dilution; 2684; Cell Signaling; RRID:AB_2122298), anti-VCAN (1:200 dilution; ab19345; Abcam, London, UK; RRID:AB_444865), anti-β-actin (1:500 dilution; sc-47778; Santa Cruz, Dallas, TX, USA; RRID:AB_2714189), and anti-α-tubulin (TUBA; 1:4000 dilution; T5168; Sigma-Aldrich, St. Louis, MO, USA; RRID:AB_477579), followed by incubation with secondary goat anti-mouse (1:8000 dilution; 1030-05; Southern Biotech, Birmingham, AL, USA; RRID:AB_2619742) or goat anti-rabbit (1:8000 dilution; 4030-05; Southern Biotech; RRID:AB_2687483) HRP-conjugated antibodies. Membranes were visualized by chemiluminescent film exposure after incubation with enhanced chemiluminescence substrate (Merck Millipore, Darmstadt, Germany).
2.16. qPCR and Microarrays
Triplicate cultures of 106 cells were subjected to RNA extraction using Trizol (Thermo Fisher Scientific, Waltham, MA, USA) followed by column purification and DNA removal (RNeasy Mini Kit, Qiagen, Hilden, Germany). Pooled RNA (5 μg) was quality tested on an ABI 2000 bioanalyzer (Agilent Technologies, Sta. Clara, CA, USA), labelled, and hybridized to GeneChip Mouse Gene 2.0 ST arrays (Affymetrix, Sta. Clara, CA, USA). All data were analyzed on the Affymetrix Expression and Transcriptome Analysis Consoles (RRID:SCR_018718). RNA was reverse transcribed with Superscript III (Thermo Fisher Scientific) and qPCR was performed using first-strand synthesis and SYBR FAST qPCR Kit (Kapa Biosystems, Wilmington, MA, USA) in a StepOne cycler (Applied Biosystems, Carlsbad, CA, USA). Primers for qPCR are listed in Table S4. Ct values from triplicate reactions were analyzed with the relative quantification method 2−ΔΔCT relative to mouse Gusb or human ACTB transcripts [39].
2.17. Shotgun Proteomics
Supernatants obtained from murine KrasMUT (LLC, MC38, AE17) and KrasWT (B16F10 and PANO2) cell cultures (pooled triplicate cultures for each cell line; 5 million cells/175 cm2 culture flask/24 h in full DMEM followed by 24 h in FBS-free DMEM) were analyzed. For this, 600 μL of cell culture supernatant were enzymatically digested using a modified filter-aided sample preparation (FASP) protocol [40,41]. Peptides were stored at −20 °C until mass spectrometry (MS) measurements. MS data were acquired in data-dependent acquisition (DDA) mode on a Q Exactive (QE) high field (HF) mass spectrometer (Thermo Fisher Scientific). Approximately 0.5 μg per sample were automatically loaded to the online coupled RSLC (Ultimate 3000, Thermo Fisher Scientific) HPLC system. A nano trap column was used (300 μm inner diameter (ID) × 5 mm, packed with Acclaim PepMap100 C18, 5 μm, 100 Å (LC Packings, Sunnyvale, CA, USA) before separation by reversed phase chromatography (Acquity UPLC M-Class HSS T3 Column 75 µm ID × 250 mm, 1.8 µm; Waters, Eschborn, Germany) at 40 °C. Peptides were eluted from 3% to 40% over a 95 min gradient. The MS spectrum was acquired with a mass range from 300 to 1500 m/z at resolution 60,000 with AGC set to 3 × 106 and a maximum of 50 ms IT. From the MS pre-scan, the 10 most abundant peptide ions were selected for fragmentation (MSMS) if at least doubly charged, with a dynamic exclusion of 30 s. MSMS spectra were recorded at 15,000 resolution with AGC set to 1 × 105 and a maximum of 100 ms IT. CE was set to 28 and all spectra were recorded in profile type. Label-free quantification of DDA-MS data was performed with the Proteome discoverer (version 2.3; Thermo Fisher Scientific) using Sequest HT (as node in PD) and searching against the UniProtKB/Swiss-Prot Mouse database (release 2017_2, 16872 sequences). Searches were performed with a precursor mass tolerances of 10 ppm and fragment mass tolerances of 0.02 Da. Carbamidomethylation (C) was set as static modification, deamidation (N,Q), oxidation (M), and N-terminal Met-loss+Acetyl were selected as dynamic modifications and two missed cleavages were allowed. Percolator [42] was used for validating peptide spectrum matches and peptides, accepting only the top-scoring hit for each spectrum, and satisfying the cut-off values for FDR < 1%, and posterior error probability < 0.01. The final list of proteins complied with the strict parsimony principle. The quantification of proteins, after precursor recalibration, was based on abundance values (area under curve) for unique peptides. Abundance values were normalized in a retention time-dependent manner. The protein abundances were calculated summing the abundance values for admissible peptides. Comparisons between KrasMUT (LLC, MC38, AE17) and KrasWT (B16F10 and PANO2) cell lines were done using only the proteins detected in all five cell lines.
2.18. Cellular Treatments
Cells were exposed to tumor-conditioned media diluted 1:1 in DMEM. Bortezomib pre-treatment was applied 1 h prior to exposure to conditioned media at 1 μg/mL (equivalent to 3 μM). Cells were exposed to potential NF-κΒ ligands at the following concentrations: lipopolysaccharide, LPS, 1 μg/mL (equivalent to 10–20 nM); secreted phosphoprotein 1, SPP1, 100 ng/mL (equivalent to 1.25–2.5 nM); tumor necrosis factor, TNF, 20 ng/mL (equivalent to 1 nM); versican, VCAN, 360 ng/mL (equivalent to 1 nM); interleukin (IL)-1β, 30 ng/mL (equivalent to 1 nM); and C-C-motif chemokine ligand 2, CCL2, 20 ng/mL (equivalent to 1.5 nM), and were imaged for bioluminescence or processed for other assays after 4 h. The pNGL RAW264.7 macrophages were exposed to 1 nM VCAN followed by treatment with increasing concentrations of TLR1/TLR2 antagonist Cu-CPT22.
2.19. Mouse Treatments
The IL-1 receptor antagonist isunakinra [18] was given via daily intraperitoneal injections of 20–50 mg/kg drug diluted in 100 μL PBS. Therapy was initiated at 10–17 days post s.c. tumor cells or at 5 days post-intrapleural tumor cells, allowing for efficient tumor take and a therapeutic study design. Treatment with the TLR1/TLR2 antagonist Cu-CPT22 [19] was initiated 3 days after the intrapleural cancer cell injection and consisted of daily intraperitoneal injections of 100 μL corn oil containing 10% DMSO or 20 mg/kg Cu-CPT22 diluted in 100 μL corn oil containing 10% DMSO.
2.20. Data Availability
Microarray data generated during this study (GEO datasets GSE94847, GSE94880, GSE130624, and GSE130716) or published previously (GEO datasets GSE43458 and GSE103512), as well as proteomic data generated for this study (PXD019883) are available at
2.21. Transcription Factor Binding Site Analyses
We downloaded the RELA and RELB binding sequence motifs from the ENCODE portal [43] with the identifiers: ENCFF507YCV (CHIP-seq on HuH-7.5 cells) and ENCFF615HZF (CHIP-seq on 8988T cells), respectively, and queried the ChIPseq datasets from the ChIP-X Enrichment Analysis (CHEA) Transcription Factor Targets dataset [44,45,46].
2.22. Statistics
Sample size was calculated using power analysis on G*power [47], assuming α = 0.05, β = 0.05, and effect size d = 1.5. No data were excluded from analyses. Pooled data from repeated in vivo experiments are shown. All in vitro experiments were repeated independently at least three times and the stated n always reflects the biological and not technical sample size. Animals were allocated to treatments by randomization (when n ≥ 20) or alternation (when n < 20) and transgenic animals were enrolled case-control-wise. Data were collected by at least two blinded investigators from samples coded by non-blinded investigators. All data were tested for normality of distribution by the Kolmogorov–Smirnov test, are given as violin plots or mean ± SD, and sample size (n) always refers to the biological and not technical replicates. Differences in frequency were examined by Fischer’s exact and χ2 tests, in medians by Mann–Whitney or Kruskal–Wallis tests with Dunn’s post-tests, and in means by t-test or one-way ANOVA with Bonferroni post-tests. Changes over time and the interaction between two variables were examined by two-way ANOVA with Bonferroni post-tests. Hypergeometric tests were done at the Graeber Lab website [48]. All probability (p) values are two-tailed and were considered significant when p < 0.05. All analyses and plots were done on Prism v8.0 (GraphPad, La Jolla, CA, USA; RRID:SCR_002798).
3. Results
3.1. Non-Oncogene Addiction of KRAS-Mutant Human and Murine Cancers to IL-1β
Puzzled by the negative results of the CANOPY-2 trial, we focused on published mutation data from incident LUAD from the CANTOS trial [49] and cross-examined them with the cancer genome atlas (TCGA) LUAD dataset [50], hypothesizing that IL-1β neutralization with canakinumab would specifically prevent the development of incipient KRAS-mutant (MUT) LUAD. Indeed, KRAS, but not TP53, EGFR, and BRAF, mutations were statistically significantly under-enriched in CANTOS versus TCGA patients (Figure 1A,B). We next analyzed TCGA pan-cancer transcriptome data to discover that IL1B mRNA levels were elevated in KRASMUT and amplified cancers, and performed IL-1β immunohistochemistry in our own patients with resected LUAD [13] to find increased IL-1β protein expression in KRASMUT LUAD compared with KRAS-wild-type (WT) LUAD and adjacent lung tissues (Figure 1C,D). We next injected C57BL/6 mice competent (WT) and diploinsufficient for Il1b alleles (Il1b−/−) [32] with syngeneic cancer cell lines carrying KrasWT and KrasMUT alleles [10,11]. Both subcutaneous (s.c.) and pleural routes of tumor cell injection were employed, since we previously identified that malignant pleural effusions (MPE) in mice are exclusively elicited by KrasMUT tumor cells [10,11]. All cell lines were verified for Kras, Mycoplasma spp., and identity status multiple times during these investigations (Figure S1A,B). These experiments showed that specifically KrasMUT tumors were dependent on host IL-1β (Figure 1E). Taken together, these results show that IL-1β neutralization prevents the development of incipient KRASMUT LUAD in humans, that KRASMUT human cancers contain elevated IL-1β levels, and that mouse KrasMUT cancers are specifically dependent on host IL-1β signaling, supporting the hypothesis of a selective non-oncogene addiction of KRASMUT cancers to IL-1β.
3.2. Tumor-Associated Macrophages as a Source of Tumorigenic IL-1β
We next investigated the source of increased IL-1β in KRASMUT cancers, since both the host immune and tumor cells are capable of IL-1β production [20,53,54]. We were also, based on previous work, documenting that the IL-1β promoter lies under transcriptional control of NF-κB [55], a fact we validated in ChIPseq datasets from the ChIP-X Enrichment Analysis (CHEA) dataset [46] and the ENCyclopedia Of DNA Elements (ENCODE) portal [44] (Figure S1C). For this, we first searched TCGA pan-cancer transcriptomes (n = 10,071) for associations between mRNA levels of IL1B and established cancer and immune cellular lineage markers. IL1B mRNA levels were not correlated with mRNA levels of the neutrophil marker ELANE, the mast cell marker KIT, the fibroblast marker ACTA2, and the endothelial marker F8, were significantly associated with mRNA levels of KRAS per se, of the pan-lymphocyte marker CD3D, and the cancer cell marker KRT18, but showed the tightest correlation (coefficient = 0.4; p < 10−300) with mRNA levels of the macrophage marker ADGRE1 (Figures S2 and S3). To further test this, we sought to identify the host cells that respond to KRASMUT tumor cells with NF-κB activation, since the transcription factor controls IL-1β transcription [55] and is central to innate immune responses [56]. For this, we initiated in vivo screens of murine tumor cell lines with known Kras mutation status (Figure 2A and Figure S1 [10]) by transplanting them into two strains of bioluminescent NF-κB reporter mice expressing ubiquitous HIV-LTR.Luciferase (HLL mice) [24] or NF-κB.GFP.Luciferase (NGL mice) [25] transgenes. Pleural injections were selected for tumor cell inoculation because they generate MPE with overt cancer-induced inflammation [10,11,20]. Serial imaging showed time-dependent NF-κB activation in host cells of recipient mice, conditional on the presence of Kras mutations in tumor cells (Figure 2B–E and Figure S4A,B). The NF-κB reporter signal was emitted from pleural tumors and fluid, both containing cancer and immune cells (Figure 2F and Figure S4C–F) [10,11,20]. Histologic and flow cytometric analysis and quantification localized the NF-κB reporter signal to tumor-infiltrating macrophages of mice with KrasMUT pleural tumors and effusions (Figure 2G–I and Figure S5–S7). Mast cells that foster MPE development [20] were not involved in the observed NF-κB response (Figure S8A,B). Time-dependent NF-κB activation in host cells was stronger in pleural compared with s.c. tumor models, and required expression of mutant Kras by tumor cells (Figures S8C,D and S9A–C). Adoptive bone marrow transfer corroborated myeloid cells as the origin of tumor-induced NF-κB activation, and pharmacologic killing of pleural macrophages prevented host NF-κB activation and pleural carcinomatosis (Figures S10 and S11A,B).
The pro-tumor function of pleural macrophages was also consistent with the phenotype of macrophage-depleted Lyz2.Cre;Dta mice [21] (Figure S11C,D). Tumor-secreted solute factors are responsible for NF-κB activation in macrophages, since murine RAW264.7 macrophages stably expressing the NGL reporter responded with robust in vitro NF-κB activation to cell-free media conditioned by KrasMUT, but not by KrasWT or Kras-silenced, tumor cells (Figure 3A,B and Figure S9A,D,E). This NF-κB response requires canonical NF-κB signaling, since it involved IKKβ and was attenuated by the proteasome inhibitor bortezomib (Figure 3C,D, Figures S9A,D,E and S12A–C). Proteasome-dependent canonical NF-κB activity was also documented in bone marrow-derived macrophages (BMDM) derived from NGL mice (Figure 3E,F). Differential gene expression (ΔGE) analyses (GEO datasets GSE94847, GSE94880, GSE130624, and GSE130716; total n = 32) identified 13 BMDM-specific transcripts that were further induced by incubation with tumor-conditioned media (ΔGE > 5; ANOVA p < 0.05) and included Il1b but not Il6 and Tnf reported elsewhere [57] (Figure 3G and Table S1). In addition, NGL mice diploinsufficient in Il1b alleles [32] were resistant to tumor-induced NF-κB activation (Figure 3H). Incubation of BMDM with KrasMUT tumor-conditioned media promoted their differentiation as assessed by flow cytometry for markers MHCII and CD206, and Il1b mRNA and IL-1β protein expression (Figure 3I–L). These data directly show that KRASMUT tumor cells can activate NF-κB in macrophages via solute mediator(s) that trigger IKKβ-mediated NF-κB activation, differentiation, and IL-1β elaboration.
3.3. Tumor-Secreted Versican as a Key Macrophage Effector
We next compared KrasMUT with KrasWT cancer cells for secretory molecules triggering macrophage NF-κB activation. Microarrays identified 25 transcripts over-represented in KrasMUT tumor cells, and a proteomic screen of tumor cell-conditioned media detected 226 proteins secreted > 10-fold by KrasMUT over KrasWT cells, with the glycoprotein versican (VCAN; encoded by the human/murine VCAN/Vcan genes) emerging from both screens and withstanding validation (Figure 4A–E and Figure S12D,E, Table S2, and Data S1). Multiple NF-κΒ ligands were also screened using pNGL-expressing RAW264.7 macrophages, revealing that the toll-like receptor (TLR)2 ligand VCAN potently activates macrophage NF-κΒ-driven transcription to the same degree as the TLR4 ligand lipopolysaccharide (LPS) (Figure 4F,G). VCAN also induced IKKβ in primary murine BMDM, which were verified by microarray to overexpress > 10-fold over cancer cells TLR1, TLR2, TLR6-9, and TLR13 (Figure 4H, Figures S12F,G and S13). Importantly, shRNA-mediated Vcan silencing in LLC cells diminished their ability to trigger NF-κB activation in NGL mice and to precipitate MPE (Figure 4I–M and Figure S12I–J). VCAN overexpression is not restricted to mouse KrasMUT cancers, since VCAN transcripts are also over-represented in human cancers with high KRASMUT frequencies (derived from the catalogue of somatic mutations in cancer, COSMIC), such as LUAD from smokers (GEO dataset GSE43458), and NSCLC and colorectal adenocarcinoma (COAD/READ; GEO dataset GSE103512) (Figure S14A,B) [58,59,60]. High VCAN mRNA expression also portended poor survival in a number of human cancers from the KMplot pan-cancer RNAseq dataset (Figures S14C and S15) [61]. Analysis of samples from two of our own clinical studies [13,14] showed that VCAN protein expression was significantly increased in LUAD compared with adjacent lung tissues and that VCAN mRNA expression was significantly increased in human MPE compared with benign pleural effusions (BPE) (Figure 4N,O). To test whether the proposed inflammatory loop can serve as a diagnostic tool to distinguish MPE from BPE, which is an unmet clinical need [14], pNGL-expressing RAW264.7 macrophages were exposed to cell-free supernatants from human pleural effusions. After 4 h, a robust NF-κB reporter signal was triggered selectively by MPE supernatants (Figure 4P). Taken together, these data indicate that VCAN secreted by cancer cells triggers IKKβ-mediated NF-κB activation in tumor-associated macrophages and promotes metastasis. Moreover, VCAN is overexpressed in human KRASMUT cancers and can serve as a diagnostic and prognosis biomarker.
3.4. Myeloid IKKB as the VCAN Accessory
To identify the IKK responsible for NF-κB signaling in macrophages, we silenced the four main IKKs (encoded by the murine Chuk, Ikbkb, Ikbke, and Tbk1 genes) in RAW264.7 macrophages and identify IKKβ as the main mediator of NF-κB activation in these cells (Figure 5A,B). To further define myeloid IKKβ functions, we obtained BMDM from intercrosses of Lyz2.Cre mice with mice carrying conditionally-deleted alleles of IKKα (Chukf/f) and IKKβ (Ikbkbf/f), as well as with Cre-reporter mice switching from red to green fluorescence upon Cre-mediated recombination (mT/mG), all reported previously [21,22]. Treatment of bone marrow cells from mT/mG;Lyz2.Cre mice with macrophage-colony stimulating factor (M-CSF; 100 ng/mL) to drive them towards macrophage differentiation and lysozyme 2 (LYZ2) expression yielded efficient Cre-mediated recombination (Figure 5C). Flow cytometric assessment of BMDM derived from these mice showed that intact IKKβ signaling in primary macrophages is essential for their differentiation and expression of critical pro-inflammatory genes including Lyz2, Il1b, and C3 (Figure 5D–F and Table S3). Finally, two different syngeneic KrasMUT tumor cell lines featuring VCAN overexpression were inoculated into the pleural space of the above myeloid IKK-deleted mice, to reveal that intact IKKβ signaling in macrophages is required for MPE (Figure 5G). Thus, VCAN-driven IKKβ activation mediates NF-κB signaling, IL-1β expression, differentiation, and pro-tumor function of macrophages (Figure 5H). To further query the proposed KRAS-VCAN-IKKβ connection, we interrogated mutations, copy number alterations, and fusions of the encoding genes in the TCGA pan-cancer dataset. Interestingly, VCAN and IKBKB alterations (mostly missense mutations) each occur in 5% of all cancer patients and are significantly mutually enriched (VCAN in KRAS and IKBKB in VCAN mutations) suggesting mutual addiction (Figure S16A–C). In addition, KRAS, IKBKB, and VCAN alteration frequencies across 32 human cancer types are tightly correlated, and were highest in LUAD, COAD/READ, and uterine corpus endometrial carcinoma (UCEC), cancers that commonly cause MPE (Figure S16D). In the latter tumor types featuring KRAS, IKBKB, and VCAN alteration frequencies, addiction of IKBKB and VCAN mutations persisted, and patients with VCAN and/or IKBKB-altered cancers displayed decreased body mass (cachexia), higher mutation burden, microsatellite instability, and hypoxia indices (Figure S17). Collectively, these data support that tumor cell VCAN cooperates with myeloid IKKβ in mouse and human cancers.
3.5. Non-oncogene Addiction of KRAS-Mutant Tumors to IL-1β Is Actionable
To block the proposed inflammatory loop, we employed the novel IL-1 receptor antagonist isunakinra [18]. Systemic delivery of isunakinra to mice with already established tumors specifically inhibited s.c. growth of KrasMUT tumors (Figure 6A). In addition, isunakinra limited NF-κΒ activation in KrasMUT cancer cells in vivo, a phenomenon we previously showed to be fueled by myeloid IL-1β, as well as their ability for lethal MPE induction (Figure 6B–D). Since VCAN is a known TLR2 ligand [57], the pro-inflammatory loop proposed here was also targeted with the TLR1/2 inhibitor Cu-CPT22 [19]. The drug effectively inhibited VCAN-induced NF-κΒ activation and cellular survival in RAW264.7 macrophages at the low micromolar range and blocked tumor growth in vivo at clinically relevant concentrations (Figure 6E–H). Hence, VCAN-IKKβ-mediated addiction of KRASMUT cancers to host IL-1β can be used to indirectly target these tumors.
4. Discussion
Here, we show how KRAS-mutant tumors are dependent on IL-β provided by tumor-associated macrophages. Importantly, we show that tumor-secreted versican causes IKKβ activation in myeloid cells to foster this pro-inflammatory circuitry. Notwithstanding cancers with other mutations and other myeloid cells like neutrophils and mast cells that might also fuel tumors with IL-1β, we define here a non-oncogene addiction of KRAS and IL-1β, in tandem with their partners in crime VCAN and IKKβ. The findings stress the need for molecular stratification of current clinical trials of IL-1β inhibition against lung cancer. Unique experimental models for the study of tumor genome-host immunity interactions are provided, and novel diagnostic platforms and prognostic biomarkers are described for further validation.
Although sotorasib was recently approved in the U.S. against KRASG12C-mutant NSCLC [62], KRAS-mutant cancers from multiple sites of origin remain notoriously aggressive and undruggable [63] and direct KRAS inhibition is associated with some toxicity that likely renders such treatments unsuitable for chemoprevention [64]. On the contrary, anti-IL-1β-directed therapies hold promise for chemoprevention, as shown by the CANTOS trial, (where tri-monthly administration of the IL-1β-neutralizing antibody canakinumab over 3.7 years of observation decreased overall and lung cancer mortality by 51% and 77%, respectively) based on their excellent safety profile [2]. The pro-inflammatory interplay between VCAN in tumor cells and IKKβ in macrophages described here is not only mechanistically intriguing, but also promising for innovations in cancer therapy and diagnosis. We identify cancer cell VCAN and myeloid IKKβ as the accomplices of KRAS that trigger secretion of IL-1β in the milieu of KRAS-mutant cancers. The results position these cancers as favorable candidates for anti-IL-1β therapy, and versican as a diagnostic and prognostic biomarker, as well as a therapeutic target in this tumor category that comprises 9% of all human cancers, alone or in combination with anti-IL-1β agents. In addition, since early diagnosis of metastasis is key to effective cancer therapy [57], VCAN can serve as a biomarker of metastasis. This might be achieved by monitoring local or systemic VCAN levels in patients at risk, or by using our NF-κB-reporter macrophages as a diagnostic platform. Indeed, our data indicate that the latter can accurately discriminate pleural metastasis from other pleural inflammatory processes, highlighting the clinical relevance of our findings.
NF-κB signaling in cancer and myeloid cells impacts modes of tumor progression and metastasis in various tumor types and is intimately addicted with oncogenic KRAS signaling [65,66]. However, the lessons learnt from clinical trials of proteasome (and hence also canonical NF-κB pathway) inhibitors against multiple myeloma dictate that therapeutic interventions into the NF-κB pathway are also associated with significant toxicity, since the pathway acts simultaneously in epithelial and immune cells in opposing fashions [67,68]. In addition to previous work elucidating the oncogenic functions of IKKβ in tumor cells [6,11,22,34,53,65,66], here we show how myeloid IKKβ functions to fuel tumor cell NF-κB signaling with IL-1β, further emphasizing the complex and multifaceted pro-tumor functions of NF-κB and the need for its therapeutic targeting against cancer.
5. Conclusions
In conclusion, KRAS-mutant cancers rely on host IL-1β, which they elicit from host macrophages via secretory versican that activates myeloid IKKβ. This inflammatory loop provides multiple opportunities for improved diagnosis, prognostication, and identification of therapeutic vulnerabilities of KRAS-mutant cancers.
Conceptualization, M.S. and G.S.; Funding acquisition, M.S., F.E.Y., T.S.B. and G.T.S.; Investigation, M.S., G.N., G.S., A.-S.L., M.V., A.M., I.L., E.B., G.A.G., M.A.A.P., S.A.I.W., A.P., S.M.H., K.A.M.A., I.G., D.B., R.S. and G.T.S.; Methodology, M.S., A.-S.L., I.K., M.L., R.A.H., J.B., K.A.M.A., D.E.J., M.d.C., F.E.Y., T.S.B. and G.T.S.; Project administration, M.S., A.-S.L., M.d.C. and G.T.S.; Supervision, M.S. and G.T.S.; Visualization, M.S., G.N., G.S., M.V., S.A.I.W., K.A.M.A. and G.T.S.; Writing—original draft, M.S. and G.T.S.; Writing—review and editing, M.S., G.N., G.S., A.-S.L., M.V., A.M., I.L., G.A.G., M.A.A.P., S.A.I.W., A.P., S.M.H., I.K., M.L., R.A.H., J.B., K.A.M.A., I.G., D.B., R.S., D.E.J., M.d.C., F.E.Y., T.S.B. and G.T.S. All authors have read and agreed to the published version of the manuscript.
All mice used for these studies were bred at the Department of Medicine of the University of Patras, Greece. Experiments were prospectively approved by the Veterinary Administration of the Prefecture of Western Greece (approval #276134/14873/2 17 January 2013) and were conducted according to the European Union Directive 2010/63/EU [
Informed consent was prospectively obtained from all subjects involved in the study.
Microarray data generated during this study (GEO datasets GSE94847, GSE94880, GSE130624, and GSE130716) or published previously (GEO datasets GSE43458 and GSE103512), as well as proteomic data generated for this study (PXD019883) are available at
The authors cordially thank Manolis Pasparakis (University of Cologne, Cologne, Germany) for providing Chukf/f and Ikbkbf/f mice, Yoichiro Iwakura (Tokyo University of Science, Tokyo, Japan) for providing Il1b−/− mice, and Hans-Reimer Rodewald (German Cancer Research Center, Heidelberg, Germany) for providing Cpa3.Cre+/– mice.
M.d.C. is the CEO of Buzzard Pharmaceuticals, the manufacturer and provider of isunakinra for these studies. The remaining authors declare no conflict of interest.
Footnotes
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.
![View Image - Figure 1. Non-oncogene addiction of KRAS-mutant cancers to interleukin (IL)-1β. (A,B) TP53, KRAS, EGFR, and BRAF mutation frequencies in the canakinumab anti-inflammatory thrombosis outcomes study (CANTOS) and the cancer genome atlas (TCGA) lung adenocarcinoma (LUAD) patients. Data from [2,50,51,52]. Shown are patient and mutation numbers (n) and percentages (%), as well as probabilities (P), χ2 test (A) or hypergeometric test (B). (C) Data summary of KRAS alterations (G12, G13, Q61) versus IL1B mRNA expression in the cancer genome atlas (TCGA) pan-cancer dataset (n = 10,967 samples from 10,953 patients with 31 different cancers) from the US. Data from [51,52]. RSEM, RNA-Seq by Expectation-Maximization. Note the elevated IL1B mRNA expression of KRAS-altered cancers. (D) Data summary (left) and representative images (right; inlays: isotype controls) of KRAS alterations versus IL-1β protein expression in lung adenocarcinoma (LUAD) and adjacent lung tissue from n = 36 resected patients from Munich, Germany. Note the elevated IL-1β protein expression of KRAS-altered LUAD. (E) Data summary of subcutaneous (s.c.) tumor and malignant pleural effusion (MPE) volume of C57BL/6 mice competent (WT) or diploinsufficient (Il1b-/-) in Il1b alleles at the indicated time-points after s.c. or intrapleural injection of 5 or 2 × 105 tumor cells, respectively, with (left; n from left to right = 10, 10, 30, 30, 10, 10, 20, and 20) or without (right; n = 10/group) Kras mutations. Note the requirement of Kras-altered tumors for host IL-1β. Shown are raw data (circles), rotated kernel density distributions (violins), medians (dashed lines), quartiles (dotted lines), and p, probabilities, Kolmogorov–Smirnov or Kruskal–Wallis test (A), two-way ANOVA (B, above graph) and Bonferroni post-tests (B, in graph), or unpaired t-tests (C). *, *** and ****: p < 0.05, p < 0.001 and p < 0.0001, respectively, compared with diploid patients, Dunn’s post-tests.](https://media.proquest.com/media/hms/THUM/2/Tk3zQ?_a=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%2FICAPoCAVmCAwNXZWKKAxxDSUQ6MjAyNTA1MDgwODAyNDYwNTA6NDY3NTc1&_s=bh%2FHL26nMNm5Gn9D4DAdC9EzMhQ%3D "View Image - Figure 1. Non-oncogene addiction of KRAS-mutant cancers to interleukin (IL)-1β. (A,B) TP53, KRAS, EGFR, and BRAF mutation frequencies in the canakinumab anti-inflammatory thrombosis outcomes study (CANTOS) and the cancer genome atlas (TCGA) lung adenocarcinoma (LUAD) patients. Data from [2,50,51,52]. Shown are patient and mutation numbers (n) and percentages (%), as well as probabilities (P), χ2 test (A) or hypergeometric test (B). (C) Data summary of KRAS alterations (G12, G13, Q61) versus IL1B mRNA expression in the cancer genome atlas (TCGA) pan-cancer dataset (n = 10,967 samples from 10,953 patients with 31 different cancers) from the US. Data from [51,52]. RSEM, RNA-Seq by Expectation-Maximization. Note the elevated IL1B mRNA expression of KRAS-altered cancers. (D) Data summary (left) and representative images (right; inlays: isotype controls) of KRAS alterations versus IL-1β protein expression in lung adenocarcinoma (LUAD) and adjacent lung tissue from n = 36 resected patients from Munich, Germany. Note the elevated IL-1β protein expression of KRAS-altered LUAD. (E) Data summary of subcutaneous (s.c.) tumor and malignant pleural effusion (MPE) volume of C57BL/6 mice competent (WT) or diploinsufficient (Il1b-/-) in Il1b alleles at the indicated time-points after s.c. or intrapleural injection of 5 or 2 × 105 tumor cells, respectively, with (left; n from left to right = 10, 10, 30, 30, 10, 10, 20, and 20) or without (right; n = 10/group) Kras mutations. Note the requirement of Kras-altered tumors for host IL-1β. Shown are raw data (circles), rotated kernel density distributions (violins), medians (dashed lines), quartiles (dotted lines), and p, probabilities, Kolmogorov–Smirnov or Kruskal–Wallis test (A), two-way ANOVA (B, above graph) and Bonferroni post-tests (B, in graph), or unpaired t-tests (C). *, *** and ****: p < 0.05, p < 0.001 and p < 0.0001, respectively, compared with diploid patients, Dunn’s post-tests.")
Enlarge this image.Figure 1. Non-oncogene addiction of KRAS-mutant cancers to interleukin (IL)-1β. (A,B) TP53, KRAS, EGFR, and BRAF mutation frequencies in the canakinumab anti-inflammatory thrombosis outcomes study (CANTOS) and the cancer genome atlas (TCGA) lung adenocarcinoma (LUAD) patients. Data from [2,50,51,52]. Shown are patient and mutation numbers (n) and percentages (%), as well as probabilities (P), χ2 test (A) or hypergeometric test (B). (C) Data summary of KRAS alterations (G12, G13, Q61) versus IL1B mRNA expression in the cancer genome atlas (TCGA) pan-cancer dataset (n = 10,967 samples from 10,953 patients with 31 different cancers) from the US. Data from [51,52]. RSEM, RNA-Seq by Expectation-Maximization. Note the elevated IL1B mRNA expression of KRAS-altered cancers. (D) Data summary (left) and representative images (right; inlays: isotype controls) of KRAS alterations versus IL-1β protein expression in lung adenocarcinoma (LUAD) and adjacent lung tissue from n = 36 resected patients from Munich, Germany. Note the elevated IL-1β protein expression of KRAS-altered LUAD. (E) Data summary of subcutaneous (s.c.) tumor and malignant pleural effusion (MPE) volume of C57BL/6 mice competent (WT) or diploinsufficient (Il1b-/-) in Il1b alleles at the indicated time-points after s.c. or intrapleural injection of 5 or 2 × 105 tumor cells, respectively, with (left; n from left to right = 10, 10, 30, 30, 10, 10, 20, and 20) or without (right; n = 10/group) Kras mutations. Note the requirement of Kras-altered tumors for host IL-1β. Shown are raw data (circles), rotated kernel density distributions (violins), medians (dashed lines), quartiles (dotted lines), and p, probabilities, Kolmogorov–Smirnov or Kruskal–Wallis test (A), two-way ANOVA (B, above graph) and Bonferroni post-tests (B, in graph), or unpaired t-tests (C). *, *** and ****: p < 0.05, p < 0.001 and p < 0.0001, respectively, compared with diploid patients, Dunn’s post-tests.
Enlarge this image.Figure 2. Kras-mutant tumors activate NF-κB in tumor-infiltrating macrophages. (A) Color-coded cancer cell lines used with tissues of origin and Kras mutation status. (B–E) Bioluminescent images with pseudo color scales (B,C) and data summaries (D,E) from WT and HIV-LTR.Luciferase (HLL: B and D), and NF-κB.GFP.Luciferase (NGL; C and E) NF-κB reporter mice at 14 days (B,D) or serial time-points (C,E) post-pleural injection of tumor cells. Note that in these models, bioluminescence is exclusively emitted by the host and not the tumor cells. (B,C) Dashed areas delineate the thorax. (F) Photographic/biofluorescent image overlay with pseudo color scale of NGL mouse lung explant 14 days post-pleural LLC cells shows NF-κB reporter GFP signal (κB.eGFP) over pleural tumors (outlines; n = 10). (G) GFP immunoreactivity of pleural tumor sections co-localizes with the macrophage marker CD68 (arrows; n = 10). (H,I) Flow cytometric contour plots (H) and data summary (I) of pleural tumor cells from NGL mice obtained 14 days post-pleural injection stained for the myeloid marker CD11b and the κB.LUC reporter. Percentages in (H) pertain to CD11b+LUC+ cells. Data in (D,E,I) are given as raw data (circles), median (dashed lines), quartiles (dotted lines), and kernel density distributions (violin plots) color-coded as in (A). Sample size (n) = 5–10/group; p, probability, one- or two-way ANOVA; *, **, ***, and ****, p < 0.05, p < 0.01, p < 0.001, and p < 0.0001, respectively, compared with mice injected with RAW264.7, PANO2, or B16F10 cells at the same time-points, Bonferroni post-tests.
Enlarge this image.Figure 3. Tumor-secreted factors drive IKKβ activation, differentiation, and IL-1β secretion in macrophages. (A) Color-coded cancer cells with Kras mutation status. (B–E) Bioluminescent images with pseudo color scale (B,E), immunoblots (C), and data summaries (D,E) from exposure of RAW264.7 macrophages stably expressing pNGL (B–D) and murine bone marrow-derived macrophages (BMDM) obtained from NGL mice after one-week 100 ng/mL M-CSF exposure (E) to cell-free tumor-conditioned media or DMEM (white boxes) with or without bortezomib pretreatment (1 μg/mL~3 μM for 1 h). (D,E) n = 5/group; P, probability, one- or two-way ANOVA; **** and ####, p < 0.0001 compared with other groups or saline-treated cells, respectively, Bonferroni post-tests. (F) Flow cytometry-assessed differentiation marker expression of murine bone marrow cells before (day 0) and after (day 7) one-week M-CSF exposure. (G) Microarray strategy and top-five differentially expressed genes (ΔGE) of murine BMDM compared with cancer cells (ΔGE1) and of tumor-conditioned BMDM compared with naïve BMDM (ΔGE2). n = 5/group; P, probability, one-way ANOVA. (H) Bioluminescent images and data summary of NGL, NGL; Tnf−/−, and NGL; Il1b−/− mice 14 days post-pleural injection of LLC cells. n = 13/group; P, probability, one-way ANOVA; ** and ***, p < 0.01 and p < 0.001, respectively, compared with NGL mice, Bonferroni post-tests. (I–L) Histograms (I) and data summaries (J–L) of naïve or tumor-conditioned BMDM for macrophage differentiation markers (I,J), Tnf and Il1b mRNA (K), and IL-1β protein (L) expression. n = 5–10/group; P, probability, one-way ANOVA; *** and ****, p < 0.001 and p < 0.0001, respectively, compared with DMEM and B16F10-conditioned media, Bonferroni post-tests. Data are given as raw data (circles), medians (dashed lines), quartiles (dotted lines), and kernel density distributions (violin plots) color-coded as in (A). The uncropped blots are shown in Figure S12.
Enlarge this image.Figure 4. Tumor-secreted versican drives macrophage IKKβ, metastasis, and is a cancer biomarker. (A–E) Kras-mutant and wild-type cancer cell RNA and supernatants were subjected to microarray and LC-MSMS analyses, respectively. Shown are the experimental design (A), top-20 over-represented transcripts (B) and secretory proteins (C), and Vcan/VCAN mRNA/protein expression (D,E). n = 2–3/group; P, probability, two-way ANOVA; Bold letters, false discovery rate (FDR) q < 0.05 compared with Kras-wild-type cells, two-stage linear step-up procedure of Benjamini, Hochberg, and Yekutieli. (F,G) Representative bioluminescent images (F) and data summary (G) from pNGL RAW264.7 cells exposed to lipopolysaccharide (LPS; 1 μg/mL) or recombinant proteins (1–2 nM). n = 5/group; P, probability, two-way ANOVA; ****, p < 0.0001 compared with other groups, Bonferroni post-tests. (H) Immunoblots of mouse BMDM exposed to VCAN. n = 5/group. (I–M) LLC cells stably expressing control (shC) and anti-Vcan (shVcan) shRNA were validated and injected intrapleurally into NGL mice. Shown are immunoblots (I), Vcan mRNA expression (J), and data summaries (K,L) and representative photographic and bioluminescent images (M) taken 14 days post-tumor cells. (I,J) n = 5/group; (K–M) n = 16/group; P, probability, unpaired Student’s t-test. (N) Images and data summary of VCAN expression of n = 41 tumor/normal tissue pairs from patients with resected lung adenocarcinoma. (O) VCAN mRNA expression of 10 benign and 15 malignant pleural effusions. (P) Data summary and representative image of bioluminescence of pNGL RAW264.7 cells after exposure to benign (n = 6; top triplicates) and malignant (n = 11; bottom triplicates) pleural effusions and tumor-conditioned media (each triplicate column is one patient). (N–P) P, probability, unpaired Student’s t-test. (B–D,G,J–L,N–P) Shown are raw data (circles), kernel density distributions (violins), and medians/quartiles (dashed/dotted lines). The uncropped blots are shown in Figure S12.
Enlarge this image.Figure 5. IKKβ mediates pro-tumor NF-κΒ activity, differentiation, and IL-1β secretion in macrophages. (A,B) Bioluminescent image with pseudo color scale (A) and data summary (B) of pNGL RAW264.7 cells 72 h post-infection with control (shC), anti-GFP (shGFP), or anti-inhibitor of NF-κB kinase (shChuk, shIkbkb, shIkbke, or shTbk1)-specific shRNAs. n = 8 independent experiments/group; P, probability, one-way ANOVA; ****, p < 0.0001 compared with shC, Bonferroni post-tests. (C–F) Bone marrow-derived macrophages (BMDM) were derived from mT/mG; Lyz2.Cre, Chukf/f; Lyz2.Cre, and Ikbkbf/f; Lyz2.Cre mice using one-week exposure to 100 ng/mL M-CSF. Shown are images and mean ± SD % green cells of bone marrow cells from mT/mG; Lyz2.Cre mice during/after weekly treatment with M-CSF (C), flow cytometric histograms (left) and data summary (right) of marker expression (D), top-differentially expressed genes by microarray (E), and interleukin (IL)-1β secretion by ELISA (F). (C,D) n = 5 independent experiments/group; P, probability, Fisher’s exact test or one-way ANOVA; **, p < 0.01 compared with other groups, Bonferroni post-tests. (E) n = 1 pooled triplicate/group; P, probabilities, two-way ANOVA. (F) n = 10 independent experiments; P, probability, one-way ANOVA; ** and ***, p < 0.01 and p < 0.001, respectively, compared with controls, Bonferroni post-tests. (G) Chukf/f; Lyz2.Cre and Ikbkbf/f; Lyz2.Cre mice received intrapleural LLC or MC38 cells, and were evaluated after 14 days for malignant pleural effusions (MPE). Data summary of n = 40, 15, and 21 single transgenic control, Chukf/f; Lyz2.Cre, and Ikbkbf/f; Lyz2.Cre mice injected with LLC cells, respectively, and of n = 40, 15, and 25 respective mice injected with MC38 cells. P, probability, two-way ANOVA; *, **, and ****, p < 0.05, p < 0.01, and p < 0.0001, respectively, compared with controls, Bonferroni post-tests. (H) Schematic of the proposed mechanism for non-oncogene addiction of KRAS-mutant cancers to IL-1β. To this end, KRAS-mutant cancers secrete VCAN to co-opt IKKβ in macrophages within the metastatic niche, which drives IL-1β secretion by macrophages to foster tumor progression.
Enlarge this image.Figure 6. Pharmacologic abolition of non-oncogene addiction of Kras-mutant tumors to IL-1β. (A–D) The IL-1 receptor antagonist isunakinra limits nuclear factor (NF)-κΒ activation and tumor growth of Kras-mutant cancer cells. (A) FVB (n = 10) and C57BL/6 (n = 45) mice received subcutaneous injections of 5 × 106 FULA1 (FVB mice) or LLC, MC38, B16F10, or PANO2 (C57BL/6 mice) cells that carry G12C, G13R, Q61R, or wild-type (WT) Kras alleles. Mice were allowed 10–23 days for tumor take (solid circles) and were treated with daily intraperitoneal PBS or 20 mg/Kg isunakinra until control tumor volume reached 1 cm3 (PANO2 cells) or 2 cm3 (all other cell lines). Shown are mouse numbers (n), tumor volume as mean (circles) and SD (bars), two-way ANOVA probability (P) for treatment effects, and average isunakinra effect at the last time-points (%). ** and ***: p < 0.01 and p < 0.001, respectively, Bonferroni post-tests. (B–D) C57BL/6 mice received intraperitoneal PBS or 20 mg/Kg isunakinra (n = 7/group) followed 1 h later by 106 intrapleural LLC cells stably expressing a κΒ.LUC reporter (NGL), and were imaged for bioluminescence 4 h later. Shown in (B) are representative chest (dotted lines) bioluminescent images with pseudo color scale. In addition, FVB mice (n = 48) received 2 × 105 intrapleural FULA1 cells, were allowed 5 days for tumor take and received daily intraperitoneal PBS or 20 mg/Kg isunakinra. Mice were sacrificed when morbid for survival analyses (n = 17/treatment) or at day 14 post-tumor cells for malignant pleural effusion (MPE) analyses (n = 7/treatment). Shown in (C) are Kaplan–Meier survival estimates (curves) with log-rank probability (P) and hazard ratio (HR), and in (D) data summary of chest bioluminescence and MPE volume, shown as raw data points (circles), medians (dashed lines), quartiles (dotted lines), kernel density distributions (violins), and probability (P), unpaired Student’s t-test. (E–H) The toll-like receptor 1/2 (TLR1/2) inhibitor Cu-CPT22 blocks versican (VCAN)-induced myeloid NF-κΒ activation and MPE of Kras-mutant cancer cells in vivo. (E,F) Representative bioluminescent image with pseudo color scale (E) and results summary (F) of RAW264.7 macrophages stably expressing NGL that were pre-treated with 1% DMSO or increasing Cu-CPT22 concentrations in 1% DMSO and were exposed (1 h latency) to 10 nM lipopolysaccharide (LPS) or 1 nM recombinant VCAN. Cells were assessed for bioluminescence at 24 h and for MTT reduction at 72 h post-LPS/VCAN treatments. The n = 3 and n = 6 independent experiments/group for κΒ.LUC and MTT, respectively, are shown as 50% inhibitory/lethal concentrations (IC50/LC50), mean (circles), and SD (bars). (G,H) Representative images (G) and data summary (H) of chest bioluminescence and MPE volume of κΒ.luc mice at 14 days post-pleural injection of 2 × 105 LLC cells followed by treatment with daily intraperitoneal injections of 100 μL corn oil containing 10% DMSO (n = 10) or 20 mg/kg Cu-CPT22 diluted in 100 μL corn oil containing 10% DMSO (n = 10) initiated 5 days post-LLC cells. t, intrapleural tumors. Shown are raw data points (circles), medians (dashed lines), quartiles (dotted lines), kernel density distributions (violins), and probability (P), unpaired Student’s t-test.
Supplementary Materials
The following supporting information can be downloaded at:
References
1. Diakos, C.I.; Charles, K.A.; McMillan, D.C.; Clarke, S.J. Cancer-related inflammation and treatment effectiveness. Lancet Oncol.; 2014; 15, pp. e493-e503. [DOI: https://dx.doi.org/10.1016/S1470-2045(14)70263-3]
2. Ridker, P.M.; MacFadyen, J.G.; Thuren, T.; Everett, B.M.; Libby, P.; Glynn, R.J. Effect of interleukin-1beta inhibition with canakinumab on incident lung cancer in patients with atherosclerosis: Exploratory results from a randomised, double-blind, placebo-controlled trial. Lancet; 2017; 390, pp. 1833-1842. [DOI: https://dx.doi.org/10.1016/S0140-6736(17)32247-X]
3. Available online: https://www.novartis.com/news/media-releases/novartis-provides-update-phase-iii-study-evaluating-canakinumab-acz885-second-or-third-line-treatment-combination-chemotherapy-non-small-cell-lung-cancer (accessed on 7 July 2021).
4. Rizvi, N.A.; Hellmann, M.D.; Snyder, A.; Kvistborg, P.; Makarov, V.; Havel, J.J.; Lee, W.; Yuan, J.; Wong, P.; Ho, T.S. et al. Cancer immunology. Mutational landscape determines sensitivity to PD-1 blockade in non-small cell lung cancer. Science; 2015; 348, pp. 124-128. [DOI: https://dx.doi.org/10.1126/science.aaa1348]
5. Skoulidis, F.; Goldberg, M.E.; Greenawalt, D.M.; Hellmann, M.D.; Awad, M.M.; Gainor, J.F.; Schrock, A.B.; Hartmaier, R.J.; Trabucco, S.E.; Gay, L. et al. STK11/LKB1 Mutations and PD-1 Inhibitor Resistance in KRAS-Mutant Lung Adenocarcinoma. Cancer Discov.; 2018; 8, pp. 822-835. [DOI: https://dx.doi.org/10.1158/2159-8290.CD-18-0099]
6. Seguin, L.; Kato, S.; Franovic, A.; Camargo, M.F.; Lesperance, J.; Elliott, K.C.; Yebra, M.; Mielgo, A.; Lowy, A.M.; Husain, H. et al. An integrin beta(3)-KRAS-RalB complex drives tumour stemness and resistance to EGFR inhibition. Nat. Cell Biol.; 2014; 16, pp. 457-468. [DOI: https://dx.doi.org/10.1038/ncb2953]
7. Soucek, L.; Lawlor, E.R.; Soto, D.; Shchors, K.; Swigart, L.B.; Evan, G.I. Mast cells are required for angiogenesis and macroscopic expansion of Myc-induced pancreatic islet tumors. Nat. Med.; 2007; 13, pp. 1211-1218. [DOI: https://dx.doi.org/10.1038/nm1649] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/17906636]
8. Bang, D.; Wilson, W.; Ryan, M.; Yeh, J.J.; Baldwin, A.S. GSK-3alpha promotes oncogenic KRAS function in pancreatic cancer via TAK1-TAB stabilization and regulation of noncanonical NF-kappaB. Cancer Discov.; 2013; 3, pp. 690-703. [DOI: https://dx.doi.org/10.1158/2159-8290.CD-12-0541] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/23547054]
9. Ling, J.; Kang, Y.; Zhao, R.; Xia, Q.; Lee, D.F.; Chang, Z.; Li, J.; Peng, B.; Fleming, J.B.; Wang, H. et al. KrasG12D-induced IKK2/beta/NF-kappaB activation by IL-1alpha and p62 feedforward loops is required for development of pancreatic ductal adenocarcinoma. Cancer Cell; 2012; 21, pp. 105-120. [DOI: https://dx.doi.org/10.1016/j.ccr.2011.12.006]
10. Agalioti, T.; Giannou, A.D.; Krontira, A.C.; Kanellakis, N.I.; Kati, D.; Vreka, M.; Pepe, M.; Spella, M.; Lilis, I.; Zazara, D.E. et al. Mutant KRAS promotes malignant pleural effusion formation. Nat. Commun.; 2017; 8, 15205. [DOI: https://dx.doi.org/10.1038/ncomms15205] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/28508873]
11. Marazioti, A.; Lilis, I.; Vreka, M.; Apostolopoulou, H.; Kalogeropoulou, A.; Giopanou, I.; Giotopoulou, G.A.; Krontira, A.C.; Iliopoulou, M.; Kanellakis, N.I. et al. Myeloid-derived interleukin-1beta drives oncogenic KRAS-NF-kappaBeta addiction in malignant pleural effusion. Nat. Commun.; 2018; 9, 672. [DOI: https://dx.doi.org/10.1038/s41467-018-03051-z]
12. Available online: https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=celex%3A32010L0063 (accessed on 17 January 2013).
13. Klotz, L.V.; Courty, Y.; Lindner, M.; Petit-Courty, A.; Stowasser, A.; Koch, I.; Eichhorn, M.E.; Lilis, I.; Morresi-Hauf, A.; Arendt, K.A.M. et al. Comprehensive clinical profiling of the Gauting locoregional lung adenocarcinoma donors. Cancer Med.; 2019; 8, pp. 1486-1499. [DOI: https://dx.doi.org/10.1002/cam4.2031]
14. Marazioti, A.; Voulgaridis, A.; Psallidas, I.; Lamort, A.S.; Iliopoulou, M.; Krontira, A.C.; Lilis, I.; Asciak, R.; Kanellakis, N.I.; Rahman, N.M. et al. Clinical identification of malignant pleural effusions. medRxiv; 2021; [DOI: https://dx.doi.org/10.1101/2020.05.31.20118307]
15. Available online: https://www.wma.net/policies-post/wma-declaration-of-helsinki-ethical-principles-for-medical-research-involving-human-subjects/ (accessed on 19 March 2016).
16. Available online: https://www.drks.de/drks_web/navigate.do?navigationId=trial.HTML&TRIAL_ID=DRKS00012649 (accessed on 23 April 2017).
17. Available online: https://clinicaltrials.gov/ct2/show/NCT03319472?term=NCT03319472&rank=1 (accessed on 24 October 2017).
18. Hou, J.; Townson, S.A.; Kovalchin, J.T.; Masci, A.; Kiner, O.; Shu, Y.; King, B.M.; Schirmer, E.; Golden, K.; Thomas, C. et al. Design of a superior cytokine antagonist for topical ophthalmic use. Proc. Natl. Acad. Sci. USA; 2013; 110, pp. 3913-3918. [DOI: https://dx.doi.org/10.1073/pnas.1217996110]
19. Cheng, K.; Wang, X.; Zhang, S.; Yin, H. Discovery of small-molecule inhibitors of the TLR1/TLR2 complex. Angew. Chem. Int. Ed. Engl.; 2012; 51, pp. 12246-12249. [DOI: https://dx.doi.org/10.1002/anie.201204910] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/22969053]
20. Giannou, A.D.; Marazioti, A.; Spella, M.; Kanellakis, N.I.; Apostolopoulou, H.; Psallidas, I.; Prijovich, Z.M.; Vreka, M.; Zazara, D.E.; Lilis, I. et al. Mast cells mediate malignant pleural effusion formation. J. Clin. Investig.; 2015; 125, pp. 2317-2334. [DOI: https://dx.doi.org/10.1172/JCI79840] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/25915587]
21. Spella, M.; Lilis, I.; Pepe, M.A.; Chen, Y.; Armaka, M.; Lamort, A.S.; Zazara, D.E.; Roumelioti, F.; Vreka, M.; Kanellakis, N.I. et al. Club cells form lung adenocarcinomas and maintain the alveoli of adult mice. eLife; 2019; 8, e45571. [DOI: https://dx.doi.org/10.7554/eLife.45571] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/31140976]
22. Vreka, M.; Lilis, I.; Papageorgopoulou, M.; Giotopoulou, G.A.; Lianou, M.; Giopanou, I.; Kanellakis, N.I.; Spella, M.; Agalioti, T.; Armenis, V. et al. IkappaB Kinase alpha Is Required for Development and Progression of KRAS-Mutant Lung Adenocarcinoma. Cancer Res.; 2018; 78, pp. 2939-2951. [DOI: https://dx.doi.org/10.1158/0008-5472.CAN-17-1944]
23. Kanellakis, N.I.; Giannou, A.D.; Pepe, M.A.A.; Agalioti, T.; Zazara, D.E.; Giopanou, I.; Psallidas, I.; Spella, M.; Marazioti, A.; Arendt, K.A.M. et al. Tobacco chemical-induced mouse lung adenocarcinoma cell lines pin the prolactin orthologue proliferin as a lung tumour promoter. Carcinogenesis; 2019; 40, pp. 1352-1362. [DOI: https://dx.doi.org/10.1093/carcin/bgz047]
24. Blackwell, T.S.; Yull, F.E.; Chen, C.L.; Venkatakrishnan, A.; Blackwell, T.R.; Hicks, D.J.; Lancaster, L.H.; Christman, J.W.; Kerr, L.D. Multiorgan nuclear factor kappa B activation in a transgenic mouse model of systemic inflammation. Am. J. Respir. Crit. Care Med.; 2000; 162, pp. 1095-1101. [DOI: https://dx.doi.org/10.1164/ajrccm.162.3.9906129]
25. Everhart, M.B.; Han, W.; Sherrill, T.P.; Arutiunov, M.; Polosukhin, V.V.; Burke, J.R.; Sadikot, R.T.; Christman, J.W.; Yull, F.E.; Blackwell, T.S. Duration and intensity of NF-kappaB activity determine the severity of endotoxin-induced acute lung injury. J. Immunol.; 2006; 176, pp. 4995-5005. [DOI: https://dx.doi.org/10.4049/jimmunol.176.8.4995]
26. Muzumdar, M.D.; Tasic, B.; Miyamichi, K.; Li, L.; Luo, L. A global double-fluorescent Cre reporter mouse. Genesis; 2007; 45, pp. 593-605. [DOI: https://dx.doi.org/10.1002/dvg.20335] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/17868096]
27. Clausen, B.E.; Burkhardt, C.; Reith, W.; Renkawitz, R.; Forster, I. Conditional gene targeting in macrophages and granulocytes using LysMcre mice. Transgenic Res.; 1999; 8, pp. 265-277. [DOI: https://dx.doi.org/10.1023/A:1008942828960]
28. Voehringer, D.; Liang, H.E.; Locksley, R.M. Homeostasis and effector function of lymphopenia-induced “memory-like” T cells in constitutively T cell-depleted mice. J. Immunol.; 2008; 180, pp. 4742-4753. [DOI: https://dx.doi.org/10.4049/jimmunol.180.7.4742] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/18354198]
29. Pasparakis, M.; Alexopoulou, L.; Episkopou, V.; Kollias, G. Immune and inflammatory responses in TNF alpha-deficient mice: A critical requirement for TNF alpha in the formation of primary B cell follicles, follicular dendritic cell networks and germinal centers, and in the maturation of the humoral immune response. J. Exp. Med.; 1996; 184, pp. 1397-1411. [DOI: https://dx.doi.org/10.1084/jem.184.4.1397]
30. Gareus, R.; Huth, M.; Breiden, B.; Nenci, A.; Rosch, N.; Haase, I.; Bloch, W.; Sandhoff, K.; Pasparakis, M. Normal epidermal differentiation but impaired skin-barrier formation upon keratinocyte-restricted IKK1 ablation. Nat. Cell Biol.; 2007; 9, pp. 461-469. [DOI: https://dx.doi.org/10.1038/ncb1560]
31. Pasparakis, M.; Courtois, G.; Hafner, M.; Schmidt-Supprian, M.; Nenci, A.; Toksoy, A.; Krampert, M.; Goebeler, M.; Gillitzer, R.; Israel, A. et al. TNF-mediated inflammatory skin disease in mice with epidermis-specific deletion of IKK2. Nature; 2002; 417, pp. 861-866. [DOI: https://dx.doi.org/10.1038/nature00820]
32. Horai, R.; Asano, M.; Sudo, K.; Kanuka, H.; Suzuki, M.; Nishihara, M.; Takahashi, M.; Iwakura, Y. Production of mice deficient in genes for interleukin (IL)-1alpha, IL-1beta, IL-1alpha/beta, and IL-1 receptor antagonist shows that IL-1beta is crucial in turpentine-induced fever development and glucocorticoid secretion. J. Exp. Med.; 1998; 187, pp. 1463-1475. [DOI: https://dx.doi.org/10.1084/jem.187.9.1463] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/9565638]
33. Feyerabend, T.B.; Weiser, A.; Tietz, A.; Stassen, M.; Harris, N.; Kopf, M.; Radermacher, P.; Moller, P.; Benoist, C.; Mathis, D. et al. Cre-mediated cell ablation contests mast cell contribution in models of antibody- and T cell-mediated autoimmunity. Immunity; 2011; 35, pp. 832-844. [DOI: https://dx.doi.org/10.1016/j.immuni.2011.09.015] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/22101159]
34. Stathopoulos, G.T.; Sherrill, T.P.; Cheng, D.S.; Scoggins, R.M.; Han, W.; Polosukhin, V.V.; Connelly, L.; Yull, F.E.; Fingleton, B.; Blackwell, T.S. Epithelial NF-kappaB activation promotes urethane-induced lung carcinogenesis. Proc. Natl. Acad. Sci. USA; 2007; 104, pp. 18514-18519. [DOI: https://dx.doi.org/10.1073/pnas.0705316104]
35. Merrick, C.; Sherrill, T.; Kanellakis, N.I.; Asciak, R.; Stathopoulos, G.T.; Maldonado, F.; Rahman, N.M.; Blackwell, T.; Psallidas, I. Novel mouse model of indwelling pleural catheter in mice with malignant pleural effusion. ERJ Open Res.; 2019; 5, 00226-2018. [DOI: https://dx.doi.org/10.1183/23120541.00226-2018] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/31149621]
36. Available online: http://flowingsoftware.btk.fi/ (accessed on 17 May 2018).
37. Schindelin, J.; Arganda-Carreras, I.; Frise, E.; Kaynig, V.; Longair, M.; Pietzsch, T.; Preibisch, S.; Rueden, C.; Saalfeld, S.; Schmid, B. et al. Fiji: An open-source platform for biological-image analysis. Nat. Methods; 2012; 9, pp. 676-682. [DOI: https://dx.doi.org/10.1038/nmeth.2019]
38. Everhart, M.B.; Han, W.; Parman, K.S.; Polosukhin, V.V.; Zeng, H.; Sadikot, R.T.; Li, B.; Yull, F.E.; Christman, J.W.; Blackwell, T.S. Intratracheal administration of liposomal clodronate accelerates alveolar macrophage reconstitution following fetal liver transplantation. J. Leukoc. Biol.; 2005; 77, pp. 173-180. [DOI: https://dx.doi.org/10.1189/jlb.1203647]
39. Pfaffl, M.W. A new mathematical model for relative quantification in real-time RT-PCR. Nucleic Acids Res.; 2001; 29, e45. [DOI: https://dx.doi.org/10.1093/nar/29.9.e45] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/11328886]
40. Wisniewski, J.R.; Zougman, A.; Nagaraj, N.; Mann, M. Universal sample preparation method for proteome analysis. Nat. Methods; 2009; 6, pp. 359-362. [DOI: https://dx.doi.org/10.1038/nmeth.1322] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/19377485]
41. Grosche, A.; Hauser, A.; Lepper, M.F.; Mayo, R.; von Toerne, C.; Merl-Pham, J.; Hauck, S.M. The Proteome of Native Adult Muller Glial Cells From Murine Retina. Mol. Cell. Proteom.; 2016; 15, pp. 462-480. [DOI: https://dx.doi.org/10.1074/mcp.M115.052183]
42. Kall, L.; Canterbury, J.D.; Weston, J.; Noble, W.S.; MacCoss, M.J. Semi-supervised learning for peptide identification from shotgun proteomics datasets. Nat. Methods; 2007; 4, pp. 923-925. [DOI: https://dx.doi.org/10.1038/nmeth1113]
43. Available online: https://www.encodeproject.org/ (accessed on 23 January 2020).
44. ENCODE Project Consortium. The ENCODE (ENCyclopedia Of DNA Elements) Project. Science; 2004; 306, pp. 636-640. [DOI: https://dx.doi.org/10.1126/science.1105136]
45. Lachmann, A.; Xu, H.; Krishnan, J.; Berger, S.I.; Mazloom, A.R.; Ma’ayan, A. ChEA: Transcription factor regulation inferred from integrating genome-wide ChIP-X experiments. Bioinformatics; 2010; 26, pp. 2438-2444. [DOI: https://dx.doi.org/10.1093/bioinformatics/btq466]
46. Available online: https://maayanlab.cloud/Harmonizome/dataset/CHEA+Transcription+Factor+Targets (accessed on 26 January 2020).
47. Faul, F.; Erdfelder, E.; Lang, A.G.; Buchner, A. G*Power 3: A flexible statistical power analysis program for the social, behavioral, and biomedical sciences. Behav. Res. Methods; 2007; 39, pp. 175-191. [DOI: https://dx.doi.org/10.3758/BF03193146]
48. Available online: https://systems.crump.ucla.edu/hypergeometric/index.php (accessed on 18 February 2020).
49. Wong, C.C.; Baum, J.; Silvestro, A.; Beste, M.T.; Bharani-Dharan, B.; Xu, S.; Wang, Y.A.; Wang, X.; Prescott, M.F.; Krajkovich, L. et al. Inhibition of IL1beta by Canakinumab May Be Effective against Diverse Molecular Subtypes of Lung Cancer: An Exploratory Analysis of the CANTOS Trial. Cancer Res.; 2020; 80, pp. 5597-5605. [DOI: https://dx.doi.org/10.1158/0008-5472.CAN-19-3176] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/33023946]
50. Campbell, J.D.; Alexandrov, A.; Kim, J.; Wala, J.; Berger, A.H.; Pedamallu, C.S.; Shukla, S.A.; Guo, G.; Brooks, A.N.; Murray, B.A. et al. Distinct patterns of somatic genome alterations in lung adenocarcinomas and squamous cell carcinomas. Nat. Genet.; 2016; 48, pp. 607-616. [DOI: https://dx.doi.org/10.1038/ng.3564]
51. Available online: https://www.cbioportal.org/ (accessed on 22 November 2018).
52. Available online: https://bit.ly/3uSO0D4 (accessed on 23 October 2018).
53. McLoed, A.G.; Sherrill, T.P.; Cheng, D.S.; Han, W.; Saxon, J.A.; Gleaves, L.A.; Wu, P.; Polosukhin, V.V.; Karin, M.; Yull, F.E. et al. Neutrophil-Derived IL-1beta Impairs the Efficacy of NF-kappaB Inhibitors against Lung Cancer. Cell Rep.; 2016; 16, pp. 120-132. [DOI: https://dx.doi.org/10.1016/j.celrep.2016.05.085]
54. Voigt, C.; May, P.; Gottschlich, A.; Markota, A.; Wenk, D.; Gerlach, I.; Voigt, S.; Stathopoulos, G.T.; Arendt, K.A.M.; Heise, C. et al. Cancer cells induce interleukin-22 production from memory CD4(+) T cells via interleukin-1 to promote tumor growth. Proc. Natl. Acad. Sci. USA; 2017; 114, pp. 12994-12999. [DOI: https://dx.doi.org/10.1073/pnas.1705165114]
55. Hiscott, J.; Marois, J.; Garoufalis, J.; D’Addario, M.; Roulston, A.; Kwan, I.; Pepin, N.; Lacoste, J.; Nguyen, H.; Bensi, G. et al. Characterization of a functional NF-kappa B site in the human interleukin 1 beta promoter: Evidence for a positive autoregulatory loop. Mol. Cell. Biol.; 1993; 13, pp. 6231-6240. [DOI: https://dx.doi.org/10.1128/mcb.13.10.6231-6240.1993] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/8413223]
56. Manthiram, K.; Zhou, Q.; Aksentijevich, I.; Kastner, D.L. The monogenic autoinflammatory diseases define new pathways in human innate immunity and inflammation. Nat. Immunol.; 2017; 18, pp. 832-842. [DOI: https://dx.doi.org/10.1038/ni.3777]
57. Kim, S.; Takahashi, H.; Lin, W.W.; Descargues, P.; Grivennikov, S.; Kim, Y.; Luo, J.L.; Karin, M. Carcinoma-produced factors activate myeloid cells through TLR2 to stimulate metastasis. Nature; 2009; 457, pp. 102-106. [DOI: https://dx.doi.org/10.1038/nature07623]
58. Kabbout, M.; Garcia, M.M.; Fujimoto, J.; Liu, D.D.; Woods, D.; Chow, C.W.; Mendoza, G.; Momin, A.A.; James, B.P.; Solis, L. et al. ETS2 mediated tumor suppressive function and MET oncogene inhibition in human non-small cell lung cancer. Clin. Cancer Res.; 2013; 19, pp. 3383-3395. [DOI: https://dx.doi.org/10.1158/1078-0432.CCR-13-0341] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/23659968]
59. Brouwer-Visser, J.; Cheng, W.Y.; Bauer-Mehren, A.; Maisel, D.; Lechner, K.; Andersson, E.; Dudley, J.T.; Milletti, F. Regulatory T-cell Genes Drive Altered Immune Microenvironment in Adult Solid Cancers and Allow for Immune Contextual Patient Subtyping. Cancer Epidemiol. Biomark. Prev.; 2018; 27, pp. 103-112. [DOI: https://dx.doi.org/10.1158/1055-9965.EPI-17-0461] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/29133367]
60. Forbes, S.A.; Beare, D.; Bindal, N.; Bamford, S.; Ward, S.; Cole, C.G.; Jia, M.; Kok, C.; Boutselakis, H.; De, T. et al. COSMIC: High-Resolution Cancer Genetics Using the Catalogue of Somatic Mutations in Cancer. Curr. Protoc. Hum. Genet.; 2016; 91, pp. 10-11. [DOI: https://dx.doi.org/10.1002/cphg.21]
61. Nagy, A.; Lanczky, A.; Menyhart, O.; Gyorffy, B. Validation of miRNA prognostic power in hepatocellular carcinoma using expression data of independent datasets. Sci. Rep.; 2018; 8, 9227. [DOI: https://dx.doi.org/10.1038/s41598-018-27521-y]
62. Sotorasib Edges Closer to Approval. Cancer Discov.; 2021; 11, OF2. [DOI: https://dx.doi.org/10.1158/2159-8290.CD-NB2021-0309] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/33547148]
63. Stephen, A.G.; Esposito, D.; Bagni, R.K.; McCormick, F. Dragging ras back in the ring. Cancer Cell; 2014; 25, pp. 272-281. [DOI: https://dx.doi.org/10.1016/j.ccr.2014.02.017]
64. Hong, D.S.; Fakih, M.G.; Strickler, J.H.; Desai, J.; Durm, G.A.; Shapiro, G.I.; Falchook, G.S.; Price, T.J.; Sacher, A.; Denlinger, C.S. et al. KRAS(G12C) Inhibition with Sotorasib in Advanced Solid Tumors. N. Engl. J. Med.; 2020; 383, pp. 1207-1217. [DOI: https://dx.doi.org/10.1056/NEJMoa1917239] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/32955176]
65. Greten, F.R.; Eckmann, L.; Greten, T.F.; Park, J.M.; Li, Z.W.; Egan, L.J.; Kagnoff, M.F.; Karin, M. IKKbeta links inflammation and tumorigenesis in a mouse model of colitis-associated cancer. Cell; 2004; 118, pp. 285-296. [DOI: https://dx.doi.org/10.1016/j.cell.2004.07.013]
66. Yang, J.; Hawkins, O.E.; Barham, W.; Gilchuk, P.; Boothby, M.; Ayers, G.D.; Joyce, S.; Karin, M.; Yull, F.E.; Richmond, A. Myeloid IKKbeta promotes antitumor immunity by modulating CCL11 and the innate immune response. Cancer Res.; 2014; 74, pp. 7274-7284. [DOI: https://dx.doi.org/10.1158/0008-5472.CAN-14-1091]
67. Miyakoshi, S.; Kami, M.; Yuji, K.; Matsumura, T.; Takatoku, M.; Sasaki, M.; Narimatsu, H.; Fujii, T.; Kawabata, M.; Taniguchi, S. et al. Severe pulmonary complications in Japanese patients after bortezomib treatment for refractory multiple myeloma. Blood; 2006; 107, pp. 3492-3494. [DOI: https://dx.doi.org/10.1182/blood-2005-11-4541] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/16410442]
68. Moreau, P.; Mateos, M.V.; Berenson, J.R.; Weisel, K.; Lazzaro, A.; Song, K.; Dimopoulos, M.A.; Huang, M.; Zahlten-Kumeli, A.; Stewart, A.K. Once weekly versus twice weekly carfilzomib dosing in patients with relapsed and refractory multiple myeloma (A.R.R.O.W.): Interim analysis results of a randomised, phase 3 study. Lancet Oncol.; 2018; 19, pp. 953-964. [DOI: https://dx.doi.org/10.1016/S1470-2045(18)30354-1]
© 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.
Details
; Ntaliarda, Giannoula 1
; Skiadas, Georgios 1
; Anne-Sophie Lamort 1 ; Vreka, Malamati 1 ; Marazioti, Antonia 1 ; Lilis, Ioannis 1 ; Bouloukou, Eleni 1 ; Giotopoulou, Georgia A 1 ; Pepe, Mario A A 1 ; Weiss, Stefanie A I 2 ; Petrera, Agnese 3 ; Hauck, Stefanie M 3
; Koch, Ina 4 ; Lindner, Michael 4 ; Hatz, Rudolph A 4 ; Behr, Juergen 5 ; Arendt, Kristina A M 1 ; Giopanou, Ioanna 1
; Brunn, David 6 ; Savai, Rajkumar 7
; Jenne, Dieter E 8 ; de Château, Maarten 9
; Yull, Fiona E 10
; Blackwell, Timothy S 11 ; Stathopoulos, Georgios T 12
1 Department of Physiology, Faculty of Medicine, University of Patras, 26504 Rio, Greece; Comprehensive Pneumology Center and Institute for Lung Biology and Disease, Helmholtz Center Munich-German Research Center for Environmental Health, 81377 Munich, Germany
2 Comprehensive Pneumology Center and Institute for Lung Biology and Disease, Helmholtz Center Munich-German Research Center for Environmental Health, 81377 Munich, Germany
3 Research Unit Protein Science-Core Facility Proteomics, Helmholtz Center Munich–German Research Center for Environmental Health, 80939 Munich, Germany
4 Center for Thoracic Surgery Munich, Ludwig-Maximilians-University of Munich and Asklepios Medical Center, 82131 Gauting, Germany
5 Department of Internal Medicine V, Ludwig-Maximilian-University of Munich, 81377 Munich, Germany
6 Max Planck Institute for Heart and Lung Research, 61231 Bad Nauheim, Germany
7 Max Planck Institute for Heart and Lung Research, 61231 Bad Nauheim, Germany; Frankfurt Cancer Institute (FCI), Goethe University, 60596 Frankfurt am Main, Germany; Department of Internal Medicine and Institute for Lung Health (ILH), Justus Liebig University, 35392 Giessen, Germany
8 Comprehensive Pneumology Center and Institute for Lung Biology and Disease, Helmholtz Center Munich-German Research Center for Environmental Health, 81377 Munich, Germany; Max-Planck-Institute of Neurobiology, 82152 Planegg, Germany
9 Buzzard Pharmaceutical, 17165 Stockholm, Sweden
10 Department of Pharmacology, Vanderbilt University School of Medicine, Nashville, TN 37240, USA
11 Department of Medicine, Division of Allergy, Pulmonary and Critical Care Medicine, Vanderbilt University School of Medicine, Nashville, TN 37240, USA
12 Department of Physiology, Faculty of Medicine, University of Patras, 26504 Rio, Greece; Comprehensive Pneumology Center and Institute for Lung Biology and Disease, Helmholtz Center Munich-German Research Center for Environmental Health, 81377 Munich, Germany; Department of Medicine, Division of Allergy, Pulmonary and Critical Care Medicine, Vanderbilt University School of Medicine, Nashville, TN 37240, USA