Tag: Science

Central control of dynamic gene circuits governs T cell rest and activation

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Primary human T cell isolation and expansion

CD4⁺ regulatory and effector T cells were isolated from fresh peripheral blood Leukopaks (70500, STEMCELL Technologies) from healthy human donors with institutional review board-approved informed written consent (STEMCELL Technologies). The contents of the Leukopaks were washed twice with a 1X volume of EasySep buffer (DPBS, 2% FBS and 1 mM EDTA (pH 8.0)) using centrifugation. The washed cells were resuspended at 200 × 10⁶ cells per millilitre in EasySep buffer and isolated with the EasySep Human CD4⁺CD127^lowCD25⁺ Regulatory T Cell Isolation Kit (18063, STEMCELL Technologies), according to the manufacturer’s protocol. Following isolation with the kit, T_reg cells were stained Alexa Fluor 647 anti-human IL-2Rα antibody (302618, BioLegend; diluted 1:25), phycoerythrin anti-human CD127 (557938, Beckon Dickinson; diluted 1:50) and Pacific Blue anti-human CD4 antibody (344620, BioLegend; diluted 1:50) and isolated with FACS performed on a BD FACS ARIA Fusion 1 (656700) to ensure a pure population without contaminating effector cells. After sorting pure CD4⁺CD127^lowCD25⁺ T_reg cells, the cells were seeded at 1 × 10⁶ cells per millilitre in XVIVO-15 (02-053Q, Lonza) supplemented with 5% FCS, 55 µM 2-mercaptoethanol, 4 mM N-acetyl l-cysteine and 200 U ml⁻¹ IL-2 (10101641, Amerisource Bergen). T_eff cells were seeded at 1 × 10⁶ cells per millilitre in RPMI-1640 supplemented with 10% FCS, 2 mM l-glutamine (25030081, Fisher Scientific), 10 mM HEPES (H0887-100ML, Sigma), 1X MEM non-essential amino acids (11140050, Fisher), 1 mM sodium pyruvate (11360070, Fisher Scientific), 100 U ml⁻¹ penicillin–streptomycin (P4333-100ML, Sigma) and 50 U ml⁻¹ IL-2 (10101641, Amerisource Bergen). Both cell subsets were then stimulated with ImmunoCult human CD3/CD28/CD2 T cell activator (10990, STEMCELL Technologies) at 25 µl ml⁻¹ for T_reg cells and 6.25 µl ml⁻¹ for T_eff cells. Cells were cultured at 37 °C with 5% CO₂. Following activation and electroporation, cells were split 1:2 every 48 h to maintain an approximate density of 1 × 10⁶ cells per millilitre and supplemented with respective doses of IL-2.

Pooled CRISPR knockout screen trans-regulator editing

Pooled screens were performed following the protocol described previously¹⁹. In brief, 24 h after stimulating and plating the T cells, the trans-regulator lentiviral library¹⁹ was added to each culture (Supplementary Table 6). The cells were counted before transduction, and virus was added at a multiplicity of infection of 0.8, using gentle mixing to disperse the viral media without disrupting cell bundling. The cells were then incubated at 37 °C for an additional 24 h, pelleted by centrifugation, and viral media were replaced with fresh media supplemented with IL-2.

Twenty-four hours after washing, the cells were pelleted by centrifugation at 150g for 10 min, resuspended at 1.5 × 10⁶ cells per 17.8 µl supplemented with P3 Primary Cell Nucleofector Buffer (component of V4SP-3960, Lonza) and combined with 7.2 µl ribonucleoprotein particle (RNP)/1.5 × 10⁶ cells in a sterile 10-ml reservoir. After mixing the cells and RNPs, 25 µl of the mixture was distributed to the wells of a 96-well Nucleocuvette Plate (component of V4SP-3960, Lonza). Cells were nucleofected using code EO-115 for T_reg cells and EH-115 for T_eff cells on the Lonza 4D-Nucleofector System with the 96-well Shuttle. Immediately after nucleofection, 90 µl pre-warmed cell-appropriate medium was added to each well, and the cells were incubated at 37 °C for 15 min. Following incubation, cells were seeded at 1 × 10⁶ cells per millilitre in media supplemented with IL-2.

IL-2Rα screen sorting and library preparation

Transduced and electroporated cells were expanded for a minimum of 6 days following editing before sorting. Cell sorting was performed 10 days following isolation for the resting screens. For the stimulated T_eff screen, cells were restimulated with ImmunoCult human CD3/CD28/CD2 T cell activator (10990, STEMCELL Technologies) 9 days following initial isolation, and sorting was performed 72 h after restimulation, at the time of peak IL-2Rα expression. Before sorting, cells were counted, washed once with EasySep buffer and stained with Alexa Fluor 647 anti-human IL-2Rα antibody (302618, BioLegend; diluted 1:25). Cells were then washed and resuspended in EasySep buffer. During sorting, cells were gated on the GFP⁺ population (lentiviral sgRNA library marker) and the top and bottom 20% of IL-2Rα-expressing cells were sorted into 15-ml conical tubes coated with FCS. Isolated cells were pelleted, counted and lysed. Genomic DNA extraction was performed using phenol-chloroform extractions, and sgRNA libraries were amplified and prepared for sequencing using custom primers. Libraries were sequenced on an Illumina HiSeq 4000 at the UCSF CAT.

Screen analysis

All pooled screens were analysed with MAGeCK⁴² (v0.5.9.5). MAGeCK count was performed on all donors using –norm-method none followed by MAGeCK test –sort-criteria pos to identify genes that resulted in a statistically significant change in IL-2Rα expression. Results are calculated as the IL-2Rα^low bin/IL-2Rα^high bin. Screen visualization is represented as the IL-2Rα^high bin/IL-2Rα^low bin by flipping the sign for the fold change. All genes with an FDR-adjusted P < 0.05 were considered significant.

Arrayed CRISPR knockout of select regulators

Guide-loaded Cas9 RNPs were assembled with custom CRISPR RNAs (crRNAs) (Dharmacon), which were resuspended in IDT duplex buffer (11-01-03-01, IDT) at 160 µM. Sequences are provided in Supplementary Table 6. Dharmacon Edit-R CRISPR–Cas9 synthetic tracrRNA (U-002005-20, Dharmacon) also resuspended in nuclease-free duplex buffer at 160 µM was combined at a 1:1 molar ratio in a 96-well plate and incubated at 37 °C for 30 min. Single-stranded donor oligonucleotides (sequence: TTAGCTCTGTTTACGTCCCAGCGGGCATGAGAGTAACAAGAGGGTGTGGTAATATTACGGTACCGAGCACTATCGATACAATATGTGTCATACGGACACG; 100 µM stock) was added to the complex at a 1:1 molar ratio and incubated at 37 °C for 5 min. Finally, Cas9 protein (MacroLab; 40 µM stock) was added at a 1:2 molar ratio and incubated at 37 °C for 15 min. The resulting RNPs were frozen at −80 °C until the day of electroporation and were thawed to room temperature before use. Forty-eight hours following T cell activation, the cells were pelleted at 100g for 10 min and resuspended in room temperature P3 Primary Cell Nucleofector Buffer (V4XP-3032, Lonza) at 1.5 × 10⁶ cells per 17.8 µl. Cells (1.5 × 10⁶) were transferred to each RNP-containing well and mixed gently. Of the combined RNP cell solution, 25 µl was transferred to a 96-well electroporation cuvette plate (VVPA-1002, Lonza) and nucleofected with pulse code DS-137. Immediately following electroporation, the cells were gently resuspended in 90 µl warmed media and incubated at 37 °C for 15 min. After recovery, the cells were cultured in 96-well round-bottom plates at 1 × 10⁶ cells per millilitre for the duration of the experiment. To prevent edge effects, the sgRNAs were randomly distributed across each plate, and the first and last columns and rows of each plate were filled with PBS to prevent evaporation. Unless otherwise specified, CRISPR–Cas9-edited cells were restimulated on day 8 following isolation for stimulation response arrayed assays with ImmunoCult human CD3/CD28/CD2 T cell activator (10990, STEMCELL Technologies).

Genotyping of arrayed knockouts

On the final day of the respective assay, genomic DNA was isolated using DNA QuickExtract (QE09050, Lucigen) according to the manufacturer’s protocol. Primers were designed to flank each sgRNA target site. Amplicons of the region were generated by adding 1.25 µl each of forwards and reverse primer at 10 µM to 5 µl of sample in QuickExtract, 12.5 µl of NEBNext Ultra II Q5 master mix (M0544L, NEB) and H₂O to a total 25 µl reaction volume. Touchdown PCR was used with the following cycling conditions: 98 °C for 3 min, 15 cycles of 94 °C for 20 s followed by 65 °C to 57.5 °C for 20 s (0.5 °C incremental decreases per cycle) and 72 °C for 1 min, and a subsequent 20 cycles at 94 °C for 20 s, 58 °C for 20 s and 72 °C for 1 min, and a final 10-min extension at 72 °C. Amplicons were diluted 1:200 and Illumina sequencing adapters were then added in a second PCR. Indexing reactions included 1 µl of the diluted PCR1 sample, 2.5 µl of each the forwards and the reverse Illumina TruSeq indexing primers at 10 µM each, 12.5 µl of NEB Q5 master mix and H₂O to a total 25 µl reaction volume. The following PCR cycling conditions were used: 98 °C for 30 s, followed by 98 °C for 10 s, 60 °C for 30 s and 72 °C for 30 s for 12 cycles, and a final extension period at 72 °C for 2 min. Samples were pooled at an equivolume ratio and SPRI purified before sequencing on an Illumina MiSeq with PE 150 reads. Analysis was performed with CRISPResso2 (v2.2.7)⁴³ CRISPRessoBatch –skip_failed –n_processes 4 –exclude_bp_from_left 5 –exclude_bp_from_right 5 –plot_window_size 10.

Flow cytometry analysis of arrayed knockouts

The BioLegend FoxP3 Fix/Perm kit (421403, BioLegend) was used for staining according to the manufacturer’s protocol. Cells were washed in EasySep buffer before extracellular staining. Cells were stained with Alexa Fluor 647 anti-human IL-2Rα (CD25) antibody diluted 1:25 (302618, BioLegend), Ghost Dye Red 780 diluted 1:1,000 (13-0865-T500, Tonbo) and BV711 anti-human CD4 diluted 1:50 (344648, BioLegend) for 20 min at 4 °C and then washed once with EasySep buffer. After fixing and permeabilizing according to the kit, intracellular staining was performed with phycoerythrin anti-mouse/human Helios antibody (137216, BioLegend), KIRAVIA Blue 520 anti-human CD152 (also known as CTLA-4) antibody (349938, BioLegend) and Pacific Blue anti-human FOXP3 antibody (320116, BioLegend) each diluted 1:50 in permeabilization buffer for 30 min at room temperature. Cells were subsequently washed in permeabilization buffer and resuspended in EasySep buffer before running on the Thermo Fisher Attune NxT flow cytometer (A29004). Analysis of flow data was performed in FlowJo (v10.8.1). Gating was performed to select for lymphocytes, singlets, live cells (Ghost Dye negative) and CD4⁺ cells in the specified order. This population was then used to calculate the median fluorescence intensity for IL-2Rα or CTLA4. Visualization was performed in R using ggplot2 (v3.4.1).

Cloning and lentivirus preparation

CRISPRi sgRNAs for Perturb-seq were selected from the Dolcetto library⁴⁴ and cloned into the LGR2.1 plasmid backbone (Addgene #108098). A lenti EF1a-Zim-3-dCas9-P2A-BSD was generated using Gibson assembly as previously described⁴⁵. Lentivirus was prepared according to the a previous protocol²⁵.

Perturb-seq

Twenty-four hours after stimulation of isolated human T_reg cells and T_eff cells from two donors, the cells were transduced with Zim3–dCas9 lentivirus at 3% v/v. The following day, Perturb-seq sgRNA library lentivirus was added at 0.75% v/v (multiplicity of infection of 0.3). Forty-eight hours after transduction with Zim3–dCas9, 10 mg ml⁻¹ blasticidin (A1113903, Gibco) was added to each sample to select for dCas9⁺ cells. Blasticidin was replenished every 48 h until the cells were processed for sequencing. Eight days after initial isolation and stimulation of cells, half of the T_reg and T_eff cell culture was restimulated with ImmunoCult human CD3/CD28/CD2 T cell activator (10990, STEMCELL Technologies). On the tenth day after initial isolation, the resting and 48-h restimulated samples were collected for 10X single-cell sequencing. First, cells from each donor within the same stimulation and cell-type condition were pooled at equal concentrations. Sorting was performed to isolate live GFP⁺ cells from each condition. Sorted cells were processed according to the Chromium Next GEM Single Cell 5′ HT Reagent Kits v2 (Dual Index) with Feature Barcode technology for CRISPR Screening and Cell Surface Protein guide User Guide, CG000513. In brief, sorted cells were pelleted and washed once with cell staining buffer (420201, BioLegend). Next, the samples were blocked with Human TruStain FcX Fc Blocking reagent (422302, BioLegend). Meanwhile, TotalSeq-C Human Universal Cocktail V1.0 (399905, BioLegend) was prepared using cell staining buffer (420201, BioLegend), and TotalSeq-C0251 anti-human hashtag antibodies 1–4 (394661, BioLegend) were added to aliquots of the cocktail. After blocking, cells were stained with TotalSeq-C cocktail including one hashtag per cell and stimulation condition. After staining, the cells were washed three times in cell staining buffer. The samples were then resuspended in PBS with 1% BSA (Gibco) for final counting. The resulting samples were pooled across conditions and approximately 65,000 cells per well were loaded into eight wells of a Chromium Next GEM Chip N Single Cell Kit (1000375, 10X Genomics) for GEM generation. The samples were prepared for sequencing using the Chromium Next GEM (Gel Bead-in-emulsion) Single Cell 5′ HT Kit v2 (1000374), 5′ Feature Barcode Kit (1000256) and 5′ CRISPR Kit (1000451) according to the manufacturer’s protocol. GEM generation and library preparation were performed by the Gladstone Genomics Core. The resulting libraries were sequenced using a NovaSeqX Series 10B flowcell (20085595, Illumina) at the UCSF CAT.

Perturb-seq analysis

Fastqs for each 10X well were concatenated across lanes and flow cells. Alignment of Perturb-seq data and count aggregation for the gene expression, CRISPR sgRNA and antibody-derived tag (ADT) libraries was performed with cellranger⁴⁶ count (v7.1.0) using the default settings and –expect-cells=45000 –chemistry=SC5P-R2. Gene expression fastqs were aligned to ‘refdata-gex-GRCh38- 2020-A’ human transcriptome reference acquired from 10X Genomics. SgRNA sequences were aligned to a custom reference file using the pattern TAGCTCTTAAAC(BC), whereas ADTs were aligned to the TotalSeq-C-Human-Universal-Cocktail-399905-Antibody-reference-UMI-counting.csv provided by BioLegend, also including the hashtag oligo (HTO) sequences, which were used to distinguish each cell-type and stimulation condition. Counts for each respective library were aggregated across wells with cellranger aggr using the default settings. Cells were assigned to a donor using genetic demultiplexing with Souporcell⁴⁷ (https://github.com/wheaton5/souporcell). For each well, souporcell_pipeline.py was run using the bam file and cellranger count output barcodes.tsv as input in addition to the reference fasta. Donor calls shared across wells were identified using shared_samples.py using the vcf file outputs from Souporcell.

Perturb-seq analysis was performed in R (v4.3.1) using Seurat⁴⁸ (v4.3.0.1) based on code previously published⁴⁹. Count matrices were imported into R using the Seurat Read10X function. After creating a Seurat object with CreateSeuratObject, quality filtering was performed to retain cells with more than 1,000 RNA features identified and less than 7.5% mitochondrial RNA. Cells without a singular donor assignment were also excluded from the object as well as cells with more than one HTO assignment as determined after running HTODemux. Low abundance transcripts were filtered using the threshold of ten cells per feature and TCR genes were removed from the primary RNA assay as they were found to be a major source of variance in the dataset. No sgRNA targets were removed as the number of cells in each condition exceeded the threshold set of 150 cells. After filtering, gene expression counts were normalized and transformed using the Seurat SCTransform function with regression of both S phase score and G2/M phase score, as described on Satija (https://satijalab.org/seurat/articles/cell_cycle_vignette.html). ADT counts were normalized using the centred log-ratio (CLR) normalization method of NormalizeData. After generating principal component analysis of both normalized and transformed RNA and ADT data, Harmony⁵⁰ (v0.1.1) was used to correct for donor-associated variability in the dataset. The resulting normalized and transformed counts were used for downstream analysis unless otherwise specified. Uniform manifold approximation and projections (UMAPs) were generated using the transformed and corrected RNA and ADT counts with Seurat function FindMultiModalNeighbors followed by RunUMAP using weighted.nn. Before cell-type-specific analysis, T_reg cells were manually filtered to include only cells belonging to clusters with FOXP3 and IKZF2 expression to maximize cell purity (clusters 1, 7, 8, 15, 6, 4, 19, 20, 17 and 23).

Activation scoring was performed according to Schmidt et al.^25,49. In brief, Seurat FindMarkers was used to identify differentially expressed genes between stimulated and resting non-targeting control cells within the T_eff cells and T_reg cells individually. Genes that had a log₂-transformed fold change of more than 0.25 and were detected in 10% of restimulated or resting cells were used to generate gene weights for the score calculated as sum(GE × GW/GM), where GE is the normalized/transformed expression count of a gene, GW is the weight of the gene, and GM is the mean expression of the gene in non-target control cells of the respective cell type. Wilcoxon tests were performed to determine significance compared with non-targeting control cells with Bonferroni correction for multiple hypothesis testing (Supplementary Table 7). To observe the effect of each sgRNA within independent cell and stimulation conditions, the cells were subset by HTO. RNA and ADT normalization, transformation and donor variability correction were repeated for each subset as described above for the combined dataset. UMAPs were generated using the transformed and corrected RNA and ADT counts with Seurat function FindMultiModalNeighbors followed by RunUMAP using weighted.nn. Cell cycle quantification for each subset was performed using cycle assignments generated using the Satija cell cycle vignette referenced above.

Pseudobulking of resting and stimulated T_reg and T_eff cell samples was performed using Seurat AggregateExpression grouped by HTO, target gene and donor pulling from the counts slot (sgRNAs targeting the same gene were collapsed within the same donor). Differential expression analysis was performed with the resulting pseudobulked raw counts for both RNA and ADTs. DESeq2 (v1.32.0)⁵¹ was used to identify differentially expressed genes and proteins between each sgRNA and non-targeting control sample within each cell-type and stimulation condition, using donor information as a covariate. Network plots of differentially expressed gene connections were visualized in R using influential⁵² (v2.2.7) and ggraph⁵³ (v2.1.0), including only genes with an adjusted P < 0.05. Other visualization of differentially expressed genes and surface proteins was performed using ggplot2 (v3.4.1).

Bulk RNA-seq

At their respective timepoints, resting and 48-h restimulated cells were pelleted and resuspended at 1 × 10⁶ cells per 300 µl of RNA lysis buffer (R1060-1-100, Zymo). Cells were pipette mixed and vortexed to lyse and frozen at −80 °C until RNA isolation was performed. RNA was isolated using the Zymo-Quick RNA micro prep kit (R1051) according to the manufacturer’s protocol with the following modifications: after thawing the samples, each sample was vortexed vigorously to ensure total lysis before loading into the extraction columns. The optional kit provided DNAse step was skipped, and instead RNA was eluted from the isolation column after the recommended washes and digested with Turbo-DNAse (AM2238, Fisher Scientific) at 37 °C for 20 min. Following digestion, RNA was purified using the RNA Clean & Concentrator-5 kit (R1016, Zymo) according to the manufacturer’s protocol. The purified RNA was submitted to the UC Davis DNA Technologies and Expression Analysis Core to generate 3′ Tag-seq libraries with unique molecular indices (UMIs). Barcoded sequencing libraries were prepared using the QuantSeq FWD kit (Lexogen) for multiplexed sequencing on a NextSeq 500 (Illumina).

Bulk RNA-seq analysis

RNA-seq data were processed using the pipeline previously described¹⁹. In brief, fastq adapter trimming was performed with cutadapt (v2.10). Low-quality bases were trimmed with seqtk (v0.5.0). Reads were then aligned with STAR⁵⁴ (v2.7.10a) and mapped to GRCh38. UMI counting and deduplication was performed with umi_tools⁵⁵ (v1.0.1) and gene counts were generated from the deduplicated reads using featureCounts (subread v2.0.1) using Gencode v41 basic transcriptome annotation. Quality control metrics were generated for each sample with Fastqc⁵⁶ (v0.11.9), rseqc⁵⁷ (v3.0.1) and Multiqc⁵⁸ (v1.9). Differentially expressed genes between Mediator knockouts and AAVS1-knockout samples as well as stimulated and resting AAVS1-knockout samples (Supplementary Table 8) were identified from the deduplicated count matrix using DESeq2 (v1.32.0)⁵¹ in R (v4.1.0). Comparisons were made within each cell-type and stimulation condition across three donors, using donor ID as a covariate in the model. Normalized counts were generated using a DESeqDataSet containing all samples, followed by estimateSizeFactors and counts(normalized=TRUE). AAVS1-knockout normalized sample counts were then subset and averaged across donors for visualization.

Differentially expressed genes for MED12-knockout versus AAVS1-knockout samples were defined by a cut-off of adjusted P < 0.05 (Supplementary Table 3). Comparison of the effects of MED12-knockout differentially expressed genes across stimulation-responsive categories was performed by grouping MED12-knockout versus AAVS1-knockout differentially expressed genes according to their stimulation-responsive behaviour in control cells (stimulation response = adjusted P < 0.05 and abs(log₂ fold change) > 1). The Bonferroni-adjusted P value resulting from a two-tailed t-test is displayed (Fig. 4a), comparing each stimulation-responsive group to the non-stimulation-responsive group. The boxplot centre line denotes the median; the box limits indicate the upper and lower quartiles; the whiskers denote the 1.5-times interquartile range (genes per group (downregulated, not stimulation responsive and upregulated) = resting T_eff cells: 272, 954 and 218; stimulated T_eff cells: 242, 1,432 and 467; resting T_reg cells: 269, 1,491 and 241; and stimulated T_reg cells: 245, 1,945 and 426).

A one-sided Fisher’s exact test for regulators of IL-2Rα within the differentially expressed genes downstream of MED12 was determined using screen results from the matched cell-type and stimulation conditions (Fig. 4b). Genes were subset to those targeted in the screen library and detected in CD4⁺ T cell bulk RNA-seq (genes per group: regulators, non-regulators = resting T_eff cells: 62 and 807; stimulated T_eff cells: 41 and 824; and resting T_reg cells: 82 and 787). Pathway analysis was performed using PathfindR⁵⁹ (v1.6.4) including KEGG, Reactome and GO-BP gene sets and the lowest P value is displayed. Visualization was performed after removing KEGG disease pathways. Apoptosis pathway visualization was performed using Cytoscape⁶⁰ (v3.8.2). Gene set enrichment analysis was performed with clusterProfiler⁶¹ (v4.10.1) using msigdbr (v7.5.1) on all human gene sets.

SEL120-34A treatment

SEL120-34A (S8840, Selleckchem) was reconstituted in ultrapure H₂O according to the manufacturer’s recommendations. Cells were treated every 48 h with a 1 µM dose, and treatment was started 48 h following cell isolation to align with the time at which cells are edited in CRISPR-based experiments. Restimulation of cells for flow cytometry and CUT&RUN was performed 10 days after initial isolation.

Endogenous immunoprecipitation of MED12

Immunoprecipitation base buffer (0.05 M Tris-HCl pH 7.5, 0.15 M NaCl, 0.001 M EDTA and AP MS water) was prepared the day of the experiment. Of resting and 48-hour restimulated cells, 20 × 10⁶ cells per sample and immunoprecipitation were washed twice with PBS. Samples were then lysed in 500 µl lysis buffer per 10 × 10⁶ cells (Base buffer, 1X PhosphoStop (04906837001, Roche), 1X Complete mini-EDTA protease inhibitor cocktail tablets (11836170001, Sigma-Aldrich), 0.50% NP-40 Surfact-Amps Detergent Solution (85124, Thermo Scientific) and incubated on nutator for 30 min at 4 °C. To digest chromatin, tip sonication was performed in round with incubation on ice between each step: 7 s 12%, 7 s 12%, 7 s 12% and 7 s 15% with four rounds of sonication total. Cell lysate was clarified by centrifugation at 3,500g for 10 min at 4 °C. A bicinchoninic acid (BCA) assay was performed for each sample, and protein concentrations were normalized across conditions. Of whole-cell lysate, 10% was reserved for input, and samples were split into MED12 (14360, Cell Signaling Technologies) immunoprecipitation and rabbit IgG isotype control (3900, Cell Signaling Technologies) immunoprecipitation conditions. In each case, 10 µg antibody was added to a 1.5 ml protein lo bind tube containing clarified protein and samples were incubated overnight at 4 °C, with rotation on a nutator. In the morning, Pierce protein A + G magnetic beads (88802, Thermo Fisher) were washed four times using 1 ml of lysis buffer per 1 ml of bead slurry, allowing the beads to bind to a magnet between each wash before removing the buffer. After the final wash, beads were resuspended in lysis buffer at the original bead slurry volume, and 50 µl was added to each sample. The lysate–antibody–bead mixture was then incubated at 4 °C for 2 h with rotation on a nutator. After incubation, beads were bound to a magnetic tube rack and washed one time with immunoprecipitation buffer + NP-40 (immunoprecipitation buffer + 0.05% NP-40) followed by three washes with a 900 µl immunoprecipitation buffer. The resulting purified proteins were processed for mass spectrometry or western blot.

Mass spectrometry

After immunoprecipitation, bound proteins were lysed in 8 M urea + 25 mM ammonium bicarbonate followed by reduction (5 mM dithiothreitol for 1 h at 37 °C), alkylation (10 mM iodoacetamide for 45 min at room temperature in the dark) and digestion overnight with 1 µg of trypsin (Promega). Peptide samples were applied to activated columns, and the columns were washed three times with 200 µl of 0.1% trifluoroacetic acid. Peptides were eluted with 140 µl of 50% acetonitrile and 0.1% trifluoroacetic acid and dried down by speedvac.

Samples were resuspended in 0.1% formic acid and separated by reversed-phase chromatography using an EASY-nLC instrument (Thermo Fisher Scientific) with a 15-cm PepSep column (inner diameter of 150 µm; Bruker). Samples were acquired by data-dependent acquisition. Mobile phase A consisted of 0.1% formic acid in water, and mobile phase B consisted of 80% acetonitrile and 0.1% formic acid. Peptides were separated at a flow rate of 500 nl min⁻¹ over the following 60 min gradient: 4–35% B in 44 min, 35–45% B in 5 min and 10 min at 88% B. Peptides were analysed by an Orbitrap Lumos MS instrument (Thermo Fisher Scientific). Data were collected in positive ion mode with MS1 resolution of 240,000, 350–1,350 m/z scan range, maximum injection time of 50 ms, radiofrequency lens of 30%. For data-dependent acquisition, MS2 fragmentation was performed on charge states 2–5 with a 20-s dynamic exclusion after a single selection and 10 ppm ± mass tolerance. All raw mass spectrometry data were searched using MaxQuant (v2.4.7) against the human proteome (UniProt canonical protein sequences, downloaded in September 2022) using default settings and with a match-between-runs enabled⁶².

Mass spectrometry analysis

Protein spectral counts as determined by MaxQuant search results were used for protein–protein interaction (PPI) confidence scoring by SAINTexpress⁶³ (v3.6.1). Rabbit IgG pulldown samples were used as control. The total list of candidate PPIs was filtered to those that met the criteria of SAINTexpress Bayesian FDR ≤ 0.05. To quantify changes in interactions between resting and stimulated T cell states, we used a label-free quantification approach in which statistical analysis was performed using MSstats (v4.8.7)⁶⁴ from the artMS (v1.18.0) R package. Visualization was performed in Cytoscape with additional connections included from the STRING database⁶⁵.

Western blots

After affinity purification of proteins, beads were resuspended in 100 µl 2X sample buffer (4× Laemmli Sample Buffer; 1610747, Bio-Rad) with 1:10 β-mercaptoethanol (63689-25ML-F, Sigma) diluted 1:1 with 500 µl lysis buffer. Samples were boiled for 5 min at 95 °C and stored at −20 °C until further processing. Western blots were performed as previously published⁶⁶. In brief, cell lysates were subjected to SDS–PAGE on 4–15% acrylamide gels and electroblotted to polyvinylidene difluoride membranes. Blocking and primary (diluted 1:1,000) and secondary antibody incubations of immunoblots were performed in Tris-buffered saline + 0.1% Tween-20 supplemented with 5% (w/v) BSA (antibodies are provided in Supplementary Table 9). Horseradish peroxidase-conjugated goat anti-rabbit and IgG (Southern Biotech) were used at a dilution of 1:30,000, and immunoreactive bands were detected using Pierce ECL Western Blotting Substrate (32106) according to the manufacturer’s instructions.

CUT&RUN

CUT&RUN was performed on resting and 48-h restimulated cells according to the manufacturer’s protocol with the EpiCypher CUTANA ChIC/CUT&RUN Kit and provided reagents. Samples for H3K27ac CUT&RUN were lightly crosslinked before isolation using 0.1% formaldehyde (252549, Sigma) for 1 min and quenched with 125 mM glycine (50046, Sigma). In brief, 5 × 10⁵ T cells per reaction were washed with PBS before nuclear isolation using the EpiCypher recommended lysis buffer consisting of 20 mM HEPES pH 7.9 (Sigma-Aldrich), 10 mM KCl (Sigma-Aldrich), 0.1% Triton X-100 (Sigma-Aldrich), 20% glycerol (Sigma-Aldrich), 1 mM MnCl₂ (Sigma-Aldrich), 1X cOmplete Mini-Tablet (11873580001, Roche) and 0.5 mM spermidine (Sigma-Aldrich). The cells were resuspended in 100 µl per reaction cold nuclear extraction buffer and incubated on ice for 10 min. Following lysis, nuclei were pelleted and resuspended in 100 µl per reaction of nuclear extraction buffer. The isolated nuclei were then frozen at −80 °C in extraction buffer until DNA isolation. After thawing the samples at 37 °C, the nuclei were bound to activated conA beads. After adsorption of nuclei to beads, permeabilization was performed with 0.01% digitonin-containing buffer. Antibodies for H3K27ac (13-0045, EpiCypher), H3K4me1 (13-0057, EpiCypher), H3K4me2 (13-0027, EpiCypher), H3K4me3 (13-0041, EpiCypher) and IgG (13-0042, EpiCypher) were added at 500 ng per reaction. Following overnight antibody binding, pAG-MNase addition and chromatin cleavage, 0.5 ng of the provided Escherichia coli DNA was added to each sample following chromatin cleavage by MNase. Before DNA isolation, crosslinked samples were digested overnight with proteinase K (AM2546, Invitrogen) as recommended. The provided spin columns and buffers were used for DNA isolation and purification. The resulting DNA was prepared for sequencing using the CUTANA CUT&RUN Library Prep Kit (14-1002) according to the manufacturer’s protocol.

CUT&RUN analysis

Pooled libraries were sequenced on a NextSeq 500 (H3K27ac) and NextSeq 2000 with 2 × 75 or 2 × 50 paired-end reads, respectively. Bcl2fastq (v2.19) with the settings –minimum-trimmed-read-length 8 was used to generate fastqs. CUT&RUN data analysis was performed according Zheng et al. with the recommended settings unless otherwise specified below⁶⁷. In brief, the fastqs were trimmed with cutadapt (v1.18). Bowtie2 (v2.2.5)⁶⁸ was used to align the trimmed fastqs to GRCh38 using settings –local –very-sensitive –no-mixed –no-discordant –phred33 –dovetail -I 10 -X 700 -p 8 -q and E. coli (EMBL accession U00096.2) with settings –local –very-sensitive –no-overlap –no-dovetail –no-mixed –no-discordant –phred33 -I 10 -X 700 -p 8 -q. Bam files were generated with SAMtools^69,70 (v1.9) view -bS -F 0 × 04 and bam-to-bed conversion performed with bedtools (v2.30.0) bamtobed -bedpe. Bedfiles were filtered to include only paired reads of less than 1,000 bp with the command awk ‘$1==$4 & & $6-$2 < 1000 {print $0}’ samplename.bed before generating bedgraph files using bedtools (v2.30.0) genomecov -bg. Peak calling was performed using the bedgraph files as input with SEACR⁷¹ (v1.3). Each target bedgraph file was compared to the respective donor and knockout condition IgG file to identify peaks above the background using the norm and stringent options for H3K27ac samples. Spike-in scaling was performed before methylation peak calling with SEACR using the IgG file as background without normalization (non option) and with the stringent option.

Before generating a peak by sample matrix for each target, ChIP–seq blacklist regions were removed from the data. The sample matrix was reduced across all peaks within the dataset, and H3K27ac peaks were segmented into regions of 5,000 bp maximum length. Regions of differential acetylation or methylation between the regulator knockouts and AAVS1-knockout samples were identified for the peaks called across any of the samples from bam files using DESeq2 (v1.32.0)⁵¹ in R (v4.1.0; Supplementary Table 10). Comparisons were made within each cell-type and stimulation condition using AAVS1s prepared in the same batch of samples. Gene annotation was performed using the gene with the nearest TSS to each region with the GenomicRanges⁷² (v1.44.0) nearest function. Final bedgraph scaling was performed based on peak coverage across all samples and conditions using DESeq2 (v1.32.0) sizefactors. SEL120-34A and H₂O treatment samples were compared as described for MED12-knockout and AAVS1-knockout samples, using the peak matrix from MED12-knockout and AAVS1-knockout samples to maximize detection of overlapping regions across datasets.

ChIP–seq

A portion of edited T_eff cells were restimulated with ImmunoCult human CD3/CD28/CD2 T cell activator (10990, STEMCELL Technologies) 10 days following isolation and collected 48 h later. Up to 1–2 × 10⁶ T_eff cells were crosslinked in PBS with 1% methanol-free formaldehyde (28908, Thermo) for 10 min at 18–22 °C followed by quenching in glycine at 125 mM final concentration. Crosslinked cell pellets were snap-frozen in liquid nitrogen and stored at –80 °C. Nuclei were isolated from thawed, crosslinked cells via sequential lysis in LB1 (50 mM HEPES-KOH pH 7.5, 140 mM NaCl, 1 mM EDTA, 10% glycerol, 0.5% IGEPAL CA-360 and 0.25% Triton X-100), LB2 (10 mM Tris-HCl pH 8, 200 mM NaCl, 1 mM EDTA and 0.5 mM EGTA) and LB3 (10 mM Tris-HCl pH 8, 100 mM NaCl, 1 mM EDTA, 0.5 mM EGTA, 1% sodium deoxycholate (NaDOC) and 0.5% N-laurylsarcosine) supplemented with 0.5 mM phenylmethylsulfonyl fluoride (PMSF; P7626, Sigma) and 0.5X protease inhibitor cocktail (PIC; P8340, Sigma). Chromatin was sheared on a Covaris E220-focused ultrasonicator using 1-ml milliTubes (520128, Covaris) with 140 W peak incident power, 5% duty factor, 200 cycles per burst, 6 °C temperature setpoint (minimum of 3 °C and maximum of 9 °C), fill level 10, and time 12–14 min to obtain a target size of 200–700 bp. Formaldehyde crosslinked, sheared mouse CD8⁺ T cell chromatin was spiked in at 2.5% of human T_eff chromatin based on fluorometric (Qubit, Q33238, Thermo) or OD260 (Nanodrop, 912A1099, Thermo) quantification. Triton X-100 was added to a final concentration of 1% before immunoprecipitation for 16 h at 4 °C with 2–8 µg of indicated antibodies (Supplementary Table 9) bound to a 1:1 mixture of protein A and protein G magnetic beads (10001D and 10003D, Thermo). Bead-bound antibody–chromatin complexes were sequentially washed three times with wash buffer 1 (20 mM Tris pH 8, 150 mM NaCl, 1 mM EDTA, 0.5 mM EGTA, 1% Triton X-100, 0.1% SDS and 0.1% NaDOC), twice with wash buffer 2 (20 mM Tris-HCl pH 8, 500 mM NaCl, 1 mM EDTA, 0.5 mM EGTA, 1% Triton X-100, 0.1% SDS and 0.1% NaDOC), twice with wash buffer 3 (20 mM Tris-HCl pH 8, 250 mM LiCl, 1 mM EDTA, 0.5% IGEPAL CA-360 and 0.5% NaDOC), twice with TET (10 mM Tris-HCl pH 8, 1 mM EDTA and 0.2% Tween-20) and once with TE0.1 (10 mM Tris-HCl pH 8, 0.1 mM EDTA, 0.5 mM PMSF and 0.5X PIC) supplemented with 0.5 mM PMSF and 0.5X PIC. Beads were resuspended in TT (10 mM Tris-HCl pH 8 and 0.05% Tween-20) before on-bead library preparation using the NEBNext Ultra II DNA Library Prep Kit (E7370L, NEB) as previously described⁷³. ChIP–seq libraries were multiplexed for paired-end (2 × 50 bp) sequencing on an Illumina NextSeq 2000 instrument.

ChIP–seq analysis

Reads were trimmed to remove adapters and low-quality sequences and aligned to the hg38 and mm10 reference genome assemblies with bwa⁷⁴ (v0.7.17-r1188) before filtering to remove duplicates and low-quality alignments including problematic genomic regions⁷⁵ using the nf-core/ChIP–seq pipeline⁷⁶ (v2.0.0; https://doi.org/10.5281/zenodo.3240506) with default parameters. Normalization to mouse spike-in chromatin was performed by scaling counts to the quotient of the ratios of human:mouse ChIP reads and human:mouse input reads as previously described⁷⁷. CXXC1 peaks for visualization were identified using bam files from all AAVS1-knockout donors for MACS2 (v2.2.6)⁷⁸ callpeak -q 0.05 with input samples used to define the background. High-confidence MED12 peaks were identified using bam files from all AAVS1-knockout donors for MACS2 callpeak -q 0.05 with MED12-knockout samples used to define the background (Supplementary Table 11). Utilization of high-confidence peaks generated from knockout controls reduced potential false-positive signals from the ChIP samples, providing a more rigorous assessment of MED12 binding^79,80. ChIP–seq blacklist regions were removed from CXXC1 and MED12 peaks before analysis.

Polymerase pausing analysis

The polymerase pausing index was calculated as previously described³³ as (TSS coverage/TSS length)/(gene body coverage/gene body length). Gencode v43 gene structures were selected for APRIS genes and filtered to include only genes expressed in T_eff bulk RNA-seq data (defined from AAVS1 T_eff RNA-seq base mean > 10). The TSS region of each gene was defined as 200 bp upstream and downstream of the TSS. The gene body was defined as the region 400 bp downstream from the TSS plus 400 bp past the final exon of the gene. Rtracklayer⁸¹ (v1.62.0) was used to import spike-in scaled RNA Pol II CTD bigwigs, and GenomicAlignments (v1.38.2) summarizeOverlaps() was used to determine the coverage within the defined gene regions.

CUT&RUN and ChIP–seq visualization

Visualization of scaled tracks was performed with rtracklayer (v1.62.0) and ggplot2 (v3.5.1) with smoothing. APRIS gene structure was used for gene annotation with gggenes (v0.5.0). CD4⁺ T_reg STAT5A ChIP–seq data were accessed from ChIP Atlas⁸², SRX212432 and GSM1056923, and generated by Hoffmann et al.³¹. Deeptools (v3.5.5)⁸³ was used to generate profile plots of ChIP–seq data using computeMatrix scale-regions -b 3000 –regionBodyLength 5000 -a 3000 –skipZeros with scaled bigwigs, and a bed file of all expressed genes (defined from AAVS1 T_eff RNA-seq base mean > 10) as input, followed by plotProfile –perGroup.

MED12 CAR activation scoring

MED12 CAR RNA-seq data from Freitas et al. was accessed from the Gene Expression Omnibus, using the downloader to retrieve the raw counts file (GSE174279_raw_counts_GRCh38.p13_NCBI.tsv.gz). First, DESeq2 (v1.32.0) was used to identify differentially expressed genes between AAVS1-knockout stimulated and resting samples. The top upregulated genes were defined using the following criteria: adjusted P < 0.01, log₂ fold change > 2 and base mean > 10. The resulting 797 genes were used to generate a gene signature of activation. Normalized counts for the MED12-knockout and AAVS1-knockout resting and stimulated samples were generated with DESeq2 vst and converted to a summarized experiment with SummarizedExperiment⁸⁴ (v1.22.0). The normalized count matrix and activation score were used as input for GSVA⁸⁵ (v1.40.1) using the gsva function with min.sz=10, max.sz=6000, kcdf = ‘Poisson’. Visualization of the resulting gene scores was performed with ggplot2(v3.4.1) and adjusted P values were generated using rstatix (v0.7.2).

Activation-induced cell death assays

Activation-induced cell death assays were performed using titrated amounts of ImmunoCult human CD3/CD28/CD2 T cell activator (10990, STEMCELL Technologies) in addition to 50 U ml⁻¹ of IL-2. Active caspase-3/7 staining was performed 72 h following addition of stimulus using the CellEvent Caspase-3/7 Green Flow Cytometry Assay Kit (C10427, Invitrogen) according to the manufacturer’s protocol. Gating of the apoptotic population was performed on the lymphocyte gate and defined as active caspase-3/7 positive and SYTOX nucleic acid stain negative. FAS staining was performed using phycoerythrin anti-human CD95 (Fas) antibody (305608, BioLegend; diluted 1:50).

Luminex assays

On day 12 following isolation for T_eff cells and day 8 following isolation for T_reg cells, cells were plated in 96-well plates in cytokine-free medium at a density of 2 × 10⁵ cells per well. Cells were restimulated with ImmunoCult human CD3/CD28/CD2 T cell activator (10990, STEMCELLl Technologies) and supernatant was collected after 24 h. The supernatant was stored at −80 °C until processing by EVE Technologies with the Luminex xMAP technology on the Luminex 200 system. After a serial titration to determine appropriate dilutions, samples were run in technical duplicate, and Luminex 48 plex human panel A was run for T_eff cells (diluted 1:20) and T_reg cells (diluted 1:5). The multi-species TGF 3 plex panel was also run for T_reg cells (undiluted). Technical replicates were averaged by EVE for each sgRNA and donor combination to determine protein concentration. Cytokines with more than one sample out of range were removed from the analysis to exclude low abundance proteins (Supplementary Table 12).

Suppression assays

Donor-matched T_eff cells were isolated and frozen at −80 °C without activation until 24 h before the assay. T_eff cells were thawed and cultured overnight at 2 × 10⁶ cells per millilitre with 10 U ml⁻¹ IL-2. On the day of the assay, T_eff cells were counted and stained with CellTrace Violet (C34557, Invitrogen) according to the manufacturer’s protocol using a 1:2,000 dilution of dye. Assay plates were assembled with 1 × 10⁵ T_eff cells per well in 96-well round bottom plates with titrated amounts of T_reg cells ranging from 1:1 to 8:1 T_eff cells:T_reg cells. One well per condition was also included of 1 × 10⁵ T_reg cells and 5 × 10⁴ T_eff cells (1:2 T_eff cells:T_reg cells), as well as resting and stimulated T_reg cells and T_eff cells individually as controls. T_reg Suppression Inspector (130-092-909, Miltenyi Biotec) iMACS particles were prepared and added to the appropriate wells according to the manufacturer’s recommendations. Assays were performed in technical triplicate for four donors, and plates were incubated for 96 h at 37 °C. At the time of readout, cells were stained with Alexa Fluor 647 anti-human IL-2Rα (302618, BioLegend), BV711 anti-human CD4 (344648, BioLegend) and Ghost Dye Red 780 (13-0865-T500, Tonbo), and analysed on the Attune NxT flow cytometer (A29004).

Analysis of flow data was performed in FlowJo (v10.8.1) with gating to select for lymphocytes, singlets, live cells (Ghost Dye negative), CD4⁺ T cells and T_eff cells (CellTrace Violet+CD25^low). A gate was then set for each donor using the non-stimulated T_eff-only control (CellTrace Violet high peak) to establish a proliferative T_eff count. A gate was also set for iMACS beads by selecting non-lymphocytes, beads using forward scatter area (FSC-A) and Ghost Dye. An absolute proliferating T_eff cell count was then established using the formula (proliferative T_eff cell count × input bead count)/(beads), which adjusts for variations in stimulation and collection abnormalities. Percentage suppression was calculated as (100 – (absolute proliferating T_eff cell count/absolute proliferating T_eff cell count of stimulated responder only condition)) × 100. The median of the technical replicate collection plates was used to calculate percent suppression and absolute proliferating T_eff cell count per donor for visualization.

Reporting summary

Further information on research design is available in the Nature Portfolio Reporting Summary linked to this article.

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December 11, 2024
Neutralizing GDF-15 can overcome anti-PD-1 and anti-PD-L1 resistance in solid tumours

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Patients and treatment

The trial was termed GDFATHER, for GDF-15 antibody-mediated human effector cell relocation (ClinicalTrials.gov NCT04725474). This study was conducted in compliance with the International Council for Harmonisation E6 guideline for Good Clinical Practice and the Declaration of Helsinki. Complete and signed written informed consent was obtained from patients for inclusion in the study. The protocol was approved by the regulatory authorities in Germany (Paul-Ehrlich-Institut), Spain (Agencia Española de Medicamentos y Productos Sanitarios) and Switzerland (Swissmedic) and the local ethics committees in charge of the clinical trial site: Comité de Ética de la Investigación con Medicamentos, Pamplona, Spain; Swissethics, Cantonal Ethics Committee, Zurich, Switzerland; and the Ethics Committee of the University of Würzburg, Würzburg, Germany. The redacted protocol is available in the Supplementary Information and publicly available at the Clinical Trials Information System, a database set up and maintained by the European Commission.

Patients were eligible for enrolment if they had advanced-stage, relapsed or refractory solid tumours; had exhausted available approved standard treatments, including being relapsed or refractory to prior anti-PD-1 or anti-PD-L1 treatment; (for phase 1; part A and selected phase 2a cohorts) presented with biopsy-accessible tumour for serial biopsy taking; were 18 years or older; and had signed the informed consent form.

The study consisted of two parts, part A (phase 1 (dose escalation)) being a classic ‘3 + 3’ dose-escalation study and part B (phase 2a (expansion)) to explore the antitumoural activity of the combination. In part A of the study, a total of 25 patients were enrolled to receive five predefined DLs and received escalating doses of visugromab intravenous infusion (0.3, 1, 3, 10 and 20 mg kg⁻¹) every 2 weeks. The first three patients for each DL received visugromab as monotherapy for one cycle (14 days) followed by the combination of visugromab and nivolumab. Nivolumab was also administered as an intravenous infusion at 240 mg every 2 weeks. Triple tumour biopsies were taken at baseline, day 14 and day 28.

In part B of the study, up to 5 cohorts with up to 27 participants per cohort with defined tumour entities expected to be GDF-15 dependent were treated with a recommended phase 2 dose, and safety and preliminary efficacy of CTL-002 monotherapy and the combination were evaluated further. To rule out significant visugromab-independent antitumoural activity of nivolumab, patients were included only if they were relapsed or refractory to prior, approved anti-PD-1- or anti-PD-L1-containing treatment as per defined, strict criteria. Patients were enrolled only if they had a minimum of 12 weeks of continuous prior exposure to anti-PD-1 or anti-PD-L1, and their relapse or progression on prior approved anti-PD-1- or anti-PD-L1-containing treatment had occurred while this anti-PD-1 or anti-PD-L1 treatment was ongoing. Based on data in the literature, the expected rate of patients responding to retreatment with an approved PD-1 or PD-L1 agent such as nivolumab in monotherapy in these populations is ≤5% for NSCLC^{10,11,12,13,14,15}.

The study was initiated in December 2020 and the first patient was enrolled on 9 December 2020. As of October 2023, phase 1 of the study has been completed and phase 2a is ongoing with a total of 174 patients enrolled overall in the study.

Endpoints

The main endpoints were safety of visugromab (CTL-002) in combination with nivolumab and antitumoural activity. Safety parameters evaluated for this purpose were the number of participants with adverse events, including serious adverse events; clinical laboratory data; vital signs; electrocardiograms; physical examination (including neurological assessment); and Eastern Cooperative Oncology Group performance status. For phase 1 (part A) dose-limiting toxicities and maximum tolerated dose were also evaluated using National Cancer Institute Common Terminology Criteria for Adverse Events (NCI-CTCAE) Version 5.0. Investigator-assessed evaluation of the antitumour activity was performed according to RECIST V1.1 including the assessment of the proportion of participants with tumour shrinkage (declared if RECIST V1.1-defined reduction in target lesions was ≥5% or more and <30%), a confirmed PR (≥30% reduction in target lesions) and/or CR, and ORR and various related parameters such as time to response, time to progression and DOR (measured from the time point of signing the informed consent). Secondary and exploratory endpoints included PK, pharmacodynamics (for example, degree of GDF-15 neutralization achieved and change in immune-cell number and composition in the tumour tissue) and cachexia-related parameters such as change in weight.

TCGA data and correlation analysis

The analysis consisted of 30 different cancer types with a varying number of solid tumours analysed. Material included in the TCGA database is derived from primary tumours of untreated (meaning immune checkpoint blockade naive) patients. The full list of abbreviations used, study names and number of samples for solid tumours is available in Extended Data Table 1.

For these indications, gene expression data (RNAseq-v2 raw counts and TPM) were downloaded from http://firebrowse.org on 1 August 2019 (Broad Institute of MIT and Harvard). Duplicated and ambiguous genes were removed, and normalized data were log₂-transformed (log₂[TPM + 1]). Correlation analyses of normalized GDF15 expression with immune-related genes and signatures (Extended Data Table 2) were performed using Spearman’s rank correlation (test) with the normalized enrichment score from single-sample gene set enrichment analyses or averaged expression levels and visualized as heat maps. GDF15 expression was analysed in different molecular subtypes and in association with clinical parameters in primary tumours of selected indications. Differences in expression between levels of molecular cancer subtypes were tested using a two-sided Wilcoxon rank sum test. Subsequently, P values were adjusted for multiple testing with the Benjamini–Hochberg method.

Change of estimated immune infiltrates between GDF15 expression groups

Fractions of immune infiltrates and other cell types (including tumour and stromal cells) were estimated through quanTIseq^38,39 using the immunodeconv R package⁴⁰ on RNA-sequencing data (TPM) corrected for purity as determined by ESTIMATE⁴¹. Average distribution within a subgroup of patients was computed according to GDF15 expression log₂[TPM + 1] (low, medium and high terciles) within the respective tumour types. The distribution of immune-cell fractions was averaged over patients in these groups and visualized as a stacked bar plot (including a fraction with other cell types such as tumour and stromal cells).

Software and resources

All calculations, correlations and visualization analyses were performed using the statistical software environment R as well as the resources outlined in Extended Data Table 4.

Measurement of chemokine levels in GDFATHER patient samples

Serum samples for assessment of chemokine levels were taken at screening and each scheduled visit day from cycle 1 until cycle 3, and at the end-of-treatment visit. At dosing days (day 1), the samples were taken within 30 min before infusion. The serum was isolated using standard procedures and cryopreserved at −80 °C until use. Concentrations of the CXCL9 (MIG) and CXCL10 (IP10) chemokines were determined using validated solid-phase sandwich enzyme-linked immunosorbent assay (ELISA) kits according to the manufacturer’s instructions (R&D Systems; human CXCL9/MIG Quantikine ELISA kit, catalogue no. DCX900; human CXCL10/IP10 Quantikine ELISA kit, catalogue no. DIP100). Both assays were conducted in compliance with the Principles of Good Laboratory Practices regulations.

Measurement of serum visugromab levels in GDFATHER patient samples

Serum samples for PK assessment of total visugromab were taken at screening and every treatment cycle within 30 min before dosing and just at the end of each infusion. The serum was isolated using standard procedures and cryopreserved at −80 °C until use. Concentrations of visugromab were determined using a validated electrochemiluminescence assay method. The PK assay was conducted in compliance with the Principles of Good Laboratory Practices regulations.

Measurement of serum GDF-15 levels in GDFATHER patient samples

Serum samples for GDF-15 assessment were taken at screening and every treatment cycle within 30 min before dosing, isolated using standard procedures and cryopreserved at −80 °C until use. Samples from patients at screening were analysed for baseline GDF-15 levels using a validated quantitative solid-phase sandwich ELISA kit according to the manufacturer’s instructions (R&D Systems; human GDF-15 DuoSet ELISA Kit, catalogue no. DY957). Total GDF-15 levels (free GDF-15 plus visugromab-GDF-15 complex) during treatment were determined by a validated ECL method, using a custom visugromab non-competitive anti-GDF-15 nanobody as a capture reagent and, following saturation with visugromab, a custom non-competitive anti-visugromab antibody as a detection reagent. Both GDF-15 assays were conducted in compliance with the Principles of Good Laboratory Practices regulations.

Measurement of serum GDF-15 levels in translational patient samples

Tumour, serum samples and patient data used in the translational part of the study were provided by the University Cancer Center Frankfurt (UCT). The study was approved by the institutional review boards of the UCT and the responsible ethical committees at the Goethe University Frankfurt (project number SUG-2-2022).

For analysis of serum GDF-15, archived samples, which were taken within 1–89 days before surgery for patients with invasive bladder cancer (n = 34) or invasive upper urinary tract carcinoma (n = 3), as well as before treatment start with systemic therapy and within 1 year before–after biopsy for patients with metastatic urothelial cancer (n = 13), were provided. The serum was analysed for GDF-15 levels using a quantitative solid-phase sandwich ELISA kit according to the manufacturer’s instructions (R&D Systems; human GDF-15 DuoSet ELISA Kit, catalogue no. DY957).

Multiplex histological analyses of GDFATHER patient biopsies

Immunohistochemical (IHC) staining and immunofluorescence staining were performed on 4-µm formalin-fixed and paraffin-embedded (FFPE) sections of tumour tissue from consenting patients. Sections were deparaffinized and pretreated by protease digestion or heat-mediated treatment before antibody incubation. Before conducting any IHC or immunofluorescence analysis, a histology assessment was performed by a board-certified medical pathologist on slides stained with haematoxylin–eosin. The slides were stained using the Ventana HE 600 automated staining system (Roche Diagnostics) and scanned using bright-field imaging on the Leica Aperio AT2 platform (Leica Biosystems) using Scanscope software (console, v102.0.7.5; controller, v102.0.8.60) and a UPlanSapo 20×/0.75 objective (plus Doppler lens for ×40 images). The assessment consisted of confirmation of tumour type, assessment of histological features, presence of invasive margin, and determination of percentage of necrotic area on the whole slide and in the malignant lesion area.

Evaluation of intratumoural pro-GDF-15 expression levels in human FFPE samples

Determination of the intratumoural pro-GDF-15 expression levels was carried out applying a rabbit polyclonal anti-GDF-15 antibody (Sigma Aldrich; product no. HPA011191) as the primary antibody for automated staining using the Ventana BenchMark Ultra platform (Roche; software version no. 12.3.1 and 12.5.4). The binding of the anti-GDF-15 antibody was visualized using a secondary horseradish peroxidase (HRP) enzyme-conjugated antibody (Roche Diagnostics; Ventana optiView Universal DAB Detection Kit, catalogue no. 760-700). This specific antibody–enzyme complex was then visualized with a precipitating enzyme reaction product. Evaluation was carried out by a board-certified pathologist. Evaluation considered cytoplasmic staining (and in cases in which it was applicable, also membranous staining) of tumour cells. Cytoplasmic staining was assessed in four staining intensity categories, ranging from 0 (no staining) to 3+ (intensive staining). The percentage of stained cells per staining intensity category (0 to 3+) was recorded. This classification provided the basis for the calculation of the H score, which describes the GDF-15 protein levels in the tumour. The H score was determined by adding the results of multiplication of the percentage of cells with their respective intensity values as follows:

$${\rm{H}}\,{\rm{score}}=[1\times (\text{percentage}\,\text{of}\,\text{intensity}\,1)]+[2\times (\text{percentage}\,\text{of}\,\text{intensity}\,2)]+[3\times (\text{percentage}\,\text{of}\,\text{intensity}\,3)]$$

IHC evaluation of PD-L1 protein expression in human FFPE samples

Determination of the PD-L1 protein expression level was performed equivalent to the pro-GDF-15 assessment using a rabbit monoclonal anti-PD-L1 (SP263) antibody (Roche Diagnostics; catalogue no. 790-4905) as a primary antibody for automated staining following the manufacturer’s protocol. A rabbit IgG monoclonal antibody (Roche Diagnostics; catalogue no. 790-4795) was used as an isotype control. PD-L1 IHC was evaluated by a board-certified pathologist applying TPS and combined positive score as previously described⁴².

Multiplex IHC evaluation of CD4, CD8 and FOXP3 expression

CD8, CD4 and FOXP3 IHC staining was performed as a triplex IHC assay on one FFPE tissue slide. CD8 staining was carried out using a monoclonal mouse anti-human CD8 antibody (clone C8/144B; Agilent Technologies; product no. M710301-2) as a primary antibody. CD4 staining was carried out using a monoclonal rabbit anti-human CD4 antibody (clone SP35; CellMarque; product no. 104R), and FOXP3 was stained using a monoclonal rabbit anti-human FOXP3 antibody (clone SP97; Abcam; product no. Ab99963).

Depending on the primary antibody, rabbit- or mouse-specific hydroxyquinoxaline (HQ)-conjugated secondary antibodies (Roche Diagnostics; anti-mouse HQ, product no. 760-4814, anti-rabbit HQ, product no. 760-4815) or rabbit-specific nitropyrazole (NP)-conjugated secondary antibodies (Roche Diagnostics; anti-rabbit NP, product no. 760-4817) were used to allow signal amplification. The binding of the specific primary antibody was visualized using a secondary HRP-conjugated antibody or alkaline phosphatase-conjugated antibody (Roche Diagnostics; anti-HQ HRP, product no. 760-4820; anti-NP alkaline phosphatase, product no. 760-4827).

The enzyme coupled to the secondary antibody catalysed a chromogenic reaction at the binding site of the actual primary antibody resulting in teal-, yellow- and purple-coloured precipitation (Roche Diagnostics; DISCOVERY Teal HRP Kit, product no. 760-247; DISCOVERY Yellow Kit, product no. 760-239; DISCOVERY Purple Kit, product no. 760-229). Triplex IHC staining was carried out on a Ventana Discovery Ultra stainer (Roche; software version 12.5.4). For the identification of tumour epithelium, additional staining for pan-cytokeratin IHC analysis was performed on a separate FFPE tissue slide using a mouse anti-human pan-keratin antibody (clone AE1/AE3/PCK26; Roche Diagnostics; product no. 05267145001). For melanoma samples, an additional SOX10 IHC staining was performed on a separate FFPE tissue slide using a monoclonal rabbit anti-human SOX10 antibody (clone SP267; Roche Diagnostics; product no. 760-4968) to support the tumour-stroma separation process in the digital image analysis. Stained slides were scanned on a Leica Aperio AT2 scanner using Scanscope software (console, v102.0.7.5; controller, v102.0.8.60) and a UPlanSapo 20×/0.75 objective (Olympus; plus Doppler lens for ×40 images).

Evaluation of the triplex IHC staining was carried out by pathologist-assisted digital image analysis of representative areas using Visiopharm software (Visiopharm; version no. 2020.01.1 or higher). Visiopharm software uses undisclosed, linear display lookup tables. Visiopharm analysis output gave a readout on the density (positively stained cells per square millimetre) of cells positive for CD4, CD8, FOXP3 and FOXP3 plus CD4 in four different annotated regions of interest (‘tumour’, ‘tumour stroma’, ‘peritumoural stroma’ and adjacent non-neoplastic ‘normal tissue’).

Multiplex immunofluorescence evaluation of CD3, GZMB, Ki67, panCK and SOX10

For the evaluation of CD3, GZMB, Ki67, panCK and SOX10 expression and a nuclear counterstain in human FFPE patient samples, the semi-quantitative UltiMapper I/O T-act kit (Ultivue; product no. ULT20104 or ULT20110) was used. The slides were stained on a Leica Bond RX (Leica Biosystems; software version Bond 6.0.0.431 or higher), and scanned on the Zeiss Axio Scan Z1 fluorescence scanner (Hamamatsu Orca Flash, v4.0, camera (Hamamatsu Photonics); Colibri7 LED light source (Carl Zeiss Microscopy)) using Zen Blue (v3.1) software and a Plan-Apochromat 20×/0.8 M27 (Carl Zeiss Microscopy) objective. The slides were subsequently analysed by pathologist-assisted digital image analysis using Visiopharm software (Visiopharm; version no. 2020.01.1 or higher). Visiopharm software uses undisclosed, linear display lookup tables. The output of the digital analysis gave information on cell densities (positively stained cells per square millimetre) in four different annotated regions of interest (‘tumour cells’, ‘tumour stroma’, ‘tumour area’ (combining ‘tumour cells’ + ‘tumour stroma’), and in adjacent non-neoplastic ‘normal tissue’, in cases in which it was applicable).

Multiplex histological analyses of biopsies from patients with UC under early-line therapy

Slides were stained with haematoxylin and eosin (Sakura Finetek). IHC staining of GDF-15 (HPA011191, polyclonal, 1:100) was performed manually on 4-µm fresh FFPE slides. Semi-quantitative evaluation of IHC results was performed by a pathologist blinded to clinical data using a semi-quantitative approach using the H score.

The multiplex immunofluorescence analysis on whole-slide images was described previously⁴³. Slides were stained with Opal 7‐Color Automation Kits (Akoya Biosciences). We stained a tumour microenvironment panel: panCK (C-11, Abcam), CD45 (polyclonal, Abcam), PD-L1 (SP142, Abcam), αSMA (1A4, Sigma), Ki67 (SP6, Abcam) and vimentin (EPR3776, Abcam); and an immune-cell panel: CD3 (D7A6E, Cell Signaling), CD8 (C8/144B, Dako/Agilent), CD4 (EPR6855, Abcam), FOXP3 (236A/E7, Abcam). The dye 4′,6‐diamidino‐2‐phenylindole (DAPI; SouthernBiotech) was used for staining of nuclei. Corresponding Opal fluorophore antibodies were used for visualization, and images were taken with the PhenoImager HT imaging system (Akoya Biosciences). Representative areas with urothelial cancer were selected and analysed with the inForm software (Akoya Biosciences). Cells were segmented and a machine learning algorithm in the inForm software was trained to identify cell populations.

Gene expression analysis of GDFATHER patient biopsies

Gene expression was measured using the NanoString nCounter PanCancer IO 360 Panel (NanoString Technologies). The PanCancer IO 360 Panel consists of 770 genes, including 20 housekeeping genes. Tissue samples were placed on glass slides as 4-μm-thick FFPE sections and five slides were subjected to RNA extraction using the RNeasy FFPE kit (QIAGEN; catalogue no. 73504) and quality control by NanoDrop (Thermo Scientific). The analysis of gene expression was conducted on the nCounter PanCancer IO 360 Panel and NanoString (NanoString Technologies) platform. A quality check had been performed using NanoStringQCpro v1.14.0 (NanoString Technologies). Raw data normalization using the R package NanoStringNorm resulted in very similar relative log expression distributions compared to normalization using nSolver v4.0 (NanoString Technologies) with standard settings. No batch effect between different runs or cartridges was observed by principal component analyses. Normalized expression data were log₂-transformed, and housekeeping genes were filtered. Differential gene expression analyses were performed using the R/Bioconductor package limma (linear models for microarray and RNA-sequencing data) between visugromab treatment (day 14) and pretreatment (baseline) by applying a paired moderated t-test. These analyses were performed for two groups of participants, one group of participants with immune-cell influx (IMM) indicated by a more than twofold increase in the numbers of CD8⁺ and CD4⁺ T cells, and another group of participants with less than twofold increases in the same T cell subsets (NOIMM). Differential expression of individual genes between IMM and NOIMM was tested using two-sided Wilcoxon rank sum test and visualized as box plots. Volcano plots were generated using the R package EnhancedVolcano. Over-represented Reactome pathways for significantly upregulated genes on visugromab treatment (day 14) versus pretreatment (baseline) in the IMM group were determined using pathway information from ConsensusPathDB (http://cpdb.molgen.mpg.de/CPDB) and a Fisher’s exact test adjusted for the PanCancer IO 360 gene panel in the statistical software environment R v4.3.1 (R Development Core Team). P values were adjusted for the number of Reactome pathways with at least two matching genes using the Benjamini–Hochberg method.

PK–PD modelling of the distribution, elimination and interaction of visugromab and GDF-15

The PK–PD model was derived from non-human primates and describes the distribution, elimination and interaction of visugromab and GDF-15 in the serum compartment and the peripheral compartment. The distribution between the two compartments was modelled with an inter-compartmental clearance. Visugromab clearance was modelled as a first-order elimination from the serum compartment. Mass action kinetics was used to describe the binding of visugromab to GDF-15, forming a complex that was assumed to be eliminated at the same rate as free visugromab from the serum compartment.

Model parameters for non-human primates were scaled to humans using allometric scaling with a 3 kg body weight for non-human primates and 70 kg body weight for human. The allometric scaling coefficients were 1 for volumes of distribution, 0.75 for clearance, 0.667 for the inter-compartmental clearance, and −0.25 for rates.

The scaled human PK–PD model was coupled to a tumour model to predict free tumour GDF-15 levels for the first-in-human dose selection, reflecting visugromab’s mechanism of action and GDF-15 biology. The tumour model included a tumour microvasculature compartment with a blood flow rate of 0.2 ml⁻¹ min⁻¹ g⁻¹, assuming a tumour size of 36 g. Visugromab was entering from the serum side, whereas free GDF-15 was released from the tumour, resulting in reported serum GDF-15 levels in patients with cancer of 0.5, 2 and 10 ng ml⁻¹ (low, medium and severe scenarios). The calculation of free GDF-15 used the duration it takes the blood to flow through the tumour.

The parameters of this PK–PD model were estimated using total visugromab and total GDF-15 concentration measurements from the dose-range-finding and Good Laboratory Practice toxicology studies. Once the clinical phase 1 study data were available, the parameters were re-estimated. Both estimations were performed using the SEAM algorithm with Monolix software version 2019R1.

Statistical analysis

This phase 1 and 2a trial was largely evaluated on a descriptive basis as antitumoural activity was unknown for this first-in-human trial.

For the phase 2a cohorts, n = 14 response-evaluable participants were to be initially recruited for each tumour indication. Assuming a true response rate of 20%, the probability of observing at least 2 responding patients out of 14 participants was 80%. For an assumed true response of 10%, the probability of observing at least 1/14 responses in the cohort was 77%.

If at least one response was observed, cohort expansion was warranted per the design (5% one-sided α-level, 80% power, 5% maximum response probability of a ‘poor drug’, 20% response probability of a ‘good drug’). An additional n = 13 participants were then to be added to a cohort. Observing at least 4/27 responses would confirm that the drug warrants further investigation in that indication.

To assess the statistical significance between two independent groups, a two-tailed Mann–Whitney test was performed with a P value of ≤0.05 deemed as statistically significant. The statistical significance between three or more groups was determined by repeated-measures ANOVA with Geisser–Greenhouse correction followed by Dunnett’s test corrected for multiple comparisons with a P value of ≤0.05 deemed as statistically significant. The correlation between two parameters was computed using a non-parametric Spearman’s rank correlation with a 95% confidence interval. All statistical analysis was performed using GraphPad Prism software version no. 10.1.2.

Reporting summary

Further information on research design is available in the Nature Portfolio Reporting Summary linked to this article.

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December 11, 2024
Small-molecule inhibition of SARS-CoV-2 NSP14 RNA cap methyltransferase

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Cell culture

HEK (HEK Flp-In T-Rex 293, Invitrogen) cells were cultured in DMEM (Sigma-Aldrich) supplemented with 10% fetal bovine serum (Gibco) under standard tissue culture conditions (37 °C, 5% CO₂). HEK293F (Thermo Fisher Scientific) cells were cultured in Freestyle medium (Thermo Fisher Scientific) at 37 °C, 8% CO₂ and 120 rpm. Cells were negative for mycoplasma contamination.

Native PAGE

For immunoblotting, when HEK cells were at about 80% confluency, they were washed twice with ice-cold PBS and scraped in PBS, pelleted by centrifugation for 5 min at 1,000g, 4 °C and resuspended in modified native lysis buffer (50 mM HEPES pH 7.4, 50 mM KCl, 1.5 mM MgCl₂, 10% glycerol, 0.1% NP-40, 1 mM PMSF, complete EDTA-free protease inhibitor cocktail and 1 mM DTT). Lysis buffer was also supplemented with 30 U ml⁻¹ benzonase to remove DNA. Lysis was performed on ice for 20 min and the lysates were clarified by centrifugation for 10 min at 12,000g at 4 °C. The protein concentration was determined using a BCA assay (Thermo Fisher Scientific). 4× NativePAGE sample buffer (Thermo Fisher Scientific) was added to a final concentration of 1×. Then, 15 µg of each sample was resolved on 3–12% Bis-Tris NativePAGE gels (Thermo Fisher Scientific). NativePAGE was soaked in 0.1% SDS buffer for 15 min, then transferred to 0.45 µM PVDF membranes presoaked in methanol for 30 s. The membranes were blocked with 5% molecular biology grade BSA (Millipore Sigma) in Tris-buffered saline supplemented with 0.1% Tween-20 (TBST) for 1 h at room temperature, then probed with specific primary antibodies 4 °C for overnight. Primary antibodies was diluted in 1% BSA/TBST as follows: 1:10,000 rabbit anti-CCT5 (Abcam, ab129016). The secondary antibody was diluted 1:10,000 in TBST. Total protein was detected with Revert total protein stain. Fluorescence signal detection was performed using Li-Cor Odyssey infrared imager.

PDCD5 knockdown

HEK cells (5 × 10⁵) were seeded into six-well plates. Then, 24 h after plating, 25 pmol siRNA (Thermo Fisher Scientific, s17467) were added with Lipofectamine RNAiMAX Transfection Reagent (Invitrogen). Cells were collected with ice-cold PBS after 48 h and then immunoblotting was run for further analysis.

Expression and purification of recombinant PDCD5 and its mutants

PDCD5 mutants were obtained using site-directed mutagenesis. A 6× His-tag was added to the C terminus of PDCD5. Plasmids containing WT and mutant PDCD5 were transformed into Escherichia coli Rosetta DE3 competent cells for expression. PDCD5 was expressed and purified as previously reported³³. In brief, cell lysates were first passed through a nickel column, then PDCD5 bound to the nickel resin was eluted in high imidazole buffer, and pure PDCD5 was obtained by passing the elution twice through a Superdex 200 size-exclusion column. Proteins were concentrated by centrifugation and then quantified using the BCA colorimetric assay.

TRiC ATPase activity

The assay was performed as previously described⁴⁸. In brief, stock solutions of 0.05% (w/v) quinaldine red, 2.32% (w/v) polyvinyl alcohol, 5.72% (w/v) ammonium heptamolybdate tetrahydrate in 6 M HCl and water were mixed in a 2:1:1:2 ratio to prepare the quinaldine red reagent fresh before each experiment. Then, 300 nM TRiC was diluted in ATPase buffer (50 mM Tris-HCl pH 7.4, 100 mM KCl, 5 mM MgCl₂, 10% glycerol, 1 mM TCEP; 30 μl total reaction volume), preheated to 37 °C and added to 3 μl water or 10 mM ATP to start the reaction, then incubated for the indicated durations in the presence or absence of 3 µM PDCD5. The reactions were stopped by the addition of 5 μl of 60 mM EDTA in a Corning 96-well opaque non-sterile polystyrene plate (Sigma-Aldrich, CLS3992) on ice. After samples at all timepoints were collected, the reactions were developed by adding 80 μl quinaldine red reagent for 10 min, then quenched by adding 10 μl 32% (w/v) sodium citrate. The fluorescence intensity was measured (excitation, 430 nm; emission, 530 nm) using the CLARIOstar plate reader (BMG Labtech). Analysis was performed by fitting a phosphate standard curve with a one-phase decay function, and we derived the parameters for calculating the amount of phosphate released from CCT complexes.

PDCD5 binding to TRiC

To probe the binding affinity of PDCD5 for TRiC, increasing amounts of recombinant PDCD5 variants were incubated with a fixed concentration of TRiC (300 nM) for 20 min at 25 °C in ATPase buffer (50 mM Tris-HCl pH 7.4, 100 mM KCl, 5 mM MgCl₂, 10% glycerol, 1 mM TCEP), in the absence of ATP. The reactions were run in native gels and immunoblotted using PDCD5 or CCT8 antibodies, as described above. To test whether PDCD5 binds to the TRiC open or closed conformations, 3 μM of WT or mutant PDCD5 was incubated with 300 nM TRiC for 20 min at 25 °C in ATPase buffer containing 1 mM of different nucleotides and ATP analogues. The reactions were run in native gels and immunoblotted using PDCD5 or CCT8 antibodies, as described above. To obtain insights about the binding kinetics of PDCD5 variants to TRiC, 3 μM of WT or mutant PDCD5 was incubated with 300 nM TRiC in ATPase buffer at 25 °C for 10, 15, 20 and 30 min. The reactions were run in native gels and immunoblotted using PDCD5 (Proteintech, 12456-1-AP, 1:1,000) and CCT8 (Santa Cruz Biotechnology, sc-377261, 1:250) antibodies, as described above.

Co-IP

For PDCD5–Flag co-IP, PDCD5-Flag constructs (GenScript) were transiently expressed in HEK293F for 48 h after transfection. Cells were washed with PBS before collection by centrifugation and frozen in liquid nitrogen. HEK293F cells were lysed in lysis buffer (PBS pH 7.4, 0.1% IGEPAL CA-630, 5 mM MgCl₂, freshly added 0.6 mM phenylmethylsulphonyl fluoride and protease inhibitors), triturated through a 24-gauge needle ten times and incubated on ice for 5 min. After lysate clearing by centrifugation, 500 μg clarified protein extract was mixed with 20 µl packed anti-Flag M2 beads (Sigma-Aldrich) and incubated for 1 h at 4 °C. After three washes with lysis buffer, bound proteins were eluted by boiling in LDS sample buffer (Invitrogen). For western blotting, input and eluate (IP) samples were loaded onto 4–12% Bis-Tris gels (Invitrogen) and subsequently transferred to nitrocellulose membranes (Bio-Rad).

CCT3 co-IP was performed with non-transfected HEK293F cells subjected to in vivo cross-linking with 1.5 mM dithiobis(succinimidyl propionate) (DSP; Thermo Fisher Scientific) at 37 °C for 10 min. The cross-linking reaction was quenched by the addition of Tris (pH 8.0) to a final concentration of 160 mM and cells were collected and lysed as described above. Then, 2 mg of clarified protein extract was mixed with 10 μg rabbit anti-CCT3 antibody (Proteintech, 10571-1-AP) or rabbit control IgG (Proteintech, 30000-0-AP) as mock IP for 1 h at 4 °C, followed by addition of 50 μl equilibrated Protein G Magnetic Beads (Thermo Fisher Scientific) and incubation for 1 h at 4 °C. The samples were washed, eluted and evaluated using SDS–PAGE as described above.

The percentage of IP efficiency was calculated by normalizing the measured intensities and the respective dilution factor of the loaded sample for western blotting (1% for the input sample and 5% for the IP sample), followed by IP/input. For the quantification, the mean ± s.d. values were as follows: PDCD5–flag (42.70 ± 16.16), CCT1 (86.66 ± 41.01), CCT2 (45.54 ± 15.25), CCT3 (45.57 ± 12.47), CCT4 (61.12 ± 15.08), CCT5 (98.98 ± 27.74), CCT6 (53.74 ± 21.34), CCT7 (65.99 ± 38.51), CCT8 (135.49 ± 64.48) and GAPDH (0.03 ± 0.06), with n representing the number of biologically independent experiments (n = 4). For the quantification of PDCD5 mutation experiments, the mean ± s.d. values were as follows: WT (100 ± 0), RKK (133.65 ± 59.63) and IL (11.04 ± 9.68), with n representing the number of biologically independent experiments (n = 4).

To induce TRiC closure during co-IP, beads bound with TRiC–PDCD5–Flag (from co-IP, see above) were incubated in ATP/AlFx buffer (lysis buffer supplemented with 5 mM Al(NO₃)₃, 30 mM NaF and 1 mM ATP) for 1 h at 37 °C, followed by three washes with ATP/AlFx buffer. As a control, the beads bound with TRiC–PDCD5–Flag (from co-IP, see above) were incubated and washed in lysis buffer without the ATP/AlFx. For western blotting, 1% of input, 25% of released proteins after ATP/AlFx incubation and 25% of eluates (denoted as beads) were loaded.

Without adding ATP in the TRiC sample before plunge freezing, around 100% TRiC particles are at open conformation based on the single-particle analysis^13,14,19. With extra ATP/AlFx in TRiC solution before plunge freezing, a portion of TRiC particles were closed, although different papers show different closed/open ratios with ATP/AlFx at different conditions. Closed/open ratio: ~1.7 in buffer (1 mM ATP, 5 mM MgCl₂, 5 mM Al (NO₃)₃ and 30 mM NaF) from ref. ¹³; ~5.1 in buffer (1 mM ATP, 1 mM Al₃(NO₃)₃, 6 mM NaF, 10 mM MgCl₂ 50 mM KCl) from ref. ²¹; ~0.6 in buffer with ATP-AlFx from ref. ¹⁴; and ~2.2 in buffer (1 mM ATP, 5 mM MgCl₂ and AlFx (5 mM Al(NO₃)₃ and 30 mM NaF) from ref. ¹⁶. In our experimental settings (Extended Data Fig. 7), we used the conditions from ref. ¹³ (1 mM ATP, 5 mM MgCl₂, 5 mM Al (NO₃)₃ and 30 mM NaF).

For the quantification in Extended Data Fig. 7, the mean ± s.d. values were as follows: PDCD5 (ATP/AlFx) (0.09 ± 0.05); PDCD5 (control) (0.10 ± 0.04); CCT1 (ATP/AlFx) (1.53 ± 0.51); and CCT1 (control) (0.38 ± 0.06); with n representing the number of biologically independent experiments (n = 4).

Thermal protein profiling (heat-shock treatment of cells)

WT (Abcam, ab255449) and PDCD5-knockout HEK293T cells (Abcam, ab266229) were used for the heart-shock assay and cultured in DMEM (Sigma-Aldrich) supplemented with 10% fetal bovine serum (Gibco) at 37 °C with 5% CO₂. The experiment was conducted as described previously^49,50. In brief, cells were collected and resuspended in PBS. Five aliquots were prepared and distributed into PCR tubes, each of the tubes containing 5 × 10⁵ cells. Each tube was incubated for 3 min at various temperatures (37.0, 44.1, 49.9, 55.5 and 62.0 °C; or 56.8, 58.3, 59.5, 60.7 and 62.1 °C). The cells were then lysed in a buffer containing 1.5 Mm MgCl₂, 0.8% NP-40, 0.4U μl⁻¹ benzonase and protease inhibitor for 40 min at 4 °C. Protein aggregations were removed, and the soluble fraction was used for western blotting. For quantification of the western blotting of thermal protein profiling, the mean ± s.d. values of actin in WT cells at 37.0 °C to 62.0 °C were as follows: 100.0 ± 0.0, 85.3 ± 5.2, 73.8 ± 7.7, 46.3 ± 2.9 and 26.3 ± 9.4; the mean ± s.d. values of actin in PDCD5-knockout cells at 37.0 °C to 62.0 °C were as follows: 100.0 ± 0.0, 100.3 ± 7.0, 109.0 ± 9.7, 83.0 ± 2.0 and 57.6 ± 9.4; the mean ± s.d. values of tubulin in WT cells at 56.8 °C to 62.1 °C were as follows: 100.0 ± 0.0, 78.2 ± 4.2, 49.3 ± 5.5, 20.0 ± 4.9 and 5.4 ± 3.8; and the mean ± s.d. values of tubulin in PDCD5-knockout cells at 56.8 °C to 62.1 °C were as follows: 138.0 ± 22.3, 99.7 ± 6.4, 63.9 ± 15.9, 34.8 ± 0.4 and 8.3 ± 4.7.

Antibodies

Membranes from western blotting were incubated with primary antibodies (mouse anti-Flag M2 (Sigma-Aldrich, F1804, 1:2,000), rabbit anti-PDCD5 (Abcam, ab126213, 1:1,000), rabbit anti-CCT1 (Abcam, ab240903, 1:10,000), rabbit anti-CCT2 (Abcam, ab92746, 1:10,000), rabbit anti-CCT3 (Proteintech, 10571-1-AP, 1:30,000), rabbit anti-CCT4 (Proteintech, 21524-1-AP, 1:5,000), rabbit anti-CCT5 (Proteintech, 11603-1-AP, 1:3,000), rabbit anti-CCT6 (Proteintech, 19793-1-AP, 1:1,000), rabbit anti-CCT7 (Abcam, ab240566, 1:30,000), rabbit anti-CCT8 (Proteintech, 12263-1-AP, 1:2,000), rabbit anti-GAPDH (Proteintech, 10494-1-AP, 1:15,000), mouse anti-actin (Invitrogen, AM4302, 1:3,000), mouse anti-tubulin (Sigma-Aldrich, T5168, 1:3,000)), followed by incubation with HRP-conjugated secondary antibodies (anti-rabbit IgG (Cell Signaling, 7074, 1:10,000), anti-mouse IgG + IgM (Jackson ImmunoResearch, 115-035-044, 1:10,000)). Uncropped western blots are provided as Source Data.

Grid preparation, data acquisition and tomogram reconstruction

Cryo-ET sample preparation, data collection and tomogram reconstruction were performed essentially as described previously²². In brief, R2/2 gold grids with 200 mesh (Quantifoil) were glow discharged for 90 s and were positioned in 3.5 cm cell culture dishes (MatTek). Then, 2 ml HEK Flp-In T-Rex 293 cell suspension, with a concentration of 175,000 cells per ml, was added to the dish. For untreated samples, cells were cultured for 5 h before plunge-freezing. For HHT-treated samples, cells were cultured without HHT for 3 h and subsequently exposed to HHT (Santa Cruz Biotechnology) at a final concentration of 100 µM for 2 h before the plunge-freezing process. The grids were blotted from the backside for 6 s using the Leica EM GP2 plunger under 70% humidity and 37 °C. The grids were rapidly plunged into liquid ethane and stored in liquid nitrogen. Grids were FIB-milled using Aquilos FIB-SEM (Thermo Fisher Scientific). The samples were sputter-coated with an organometallic protective platinum layer using the gas injection system for 15 s. Lamella preparation was performed through a stepwise milling process with gallium ion-beam currents decreasing from 0.5 nA to 30 pA.

The data acquisition area was focused on the cytoplasmic region within the cell. Tilt series were acquired on a Titan Krios G4 (Thermo Fisher Scientific) operated at 300 kV, and equipped with Selectris X imaging filter and Falcon 4 direct electron detector, at 4,000 × 4,000 pixel dimensions, pixel size of 1.188 Å, a total dose of 120 to 150 e Å⁻² per tilt series, 2° tilt increment, tilt range of −60° to 60° and target defocus of −1.5 to −4.5 µm, using SerialEM software⁵¹. Tilt series were aligned automatically using the IMOD package⁵². The alignment files generated from IMOD were used for tomogram reconstruction in Warp⁵³ v.1.0.9.

Particle localization and refinement

Template matching was performed similarly to previous studies^22,54. For this work, the parameters were set as follows: 5° angular scanning step, low-pass filter radius=20, high-pass filter radius=1, apply_laplacian=0, noise_corelation=1 and calc_ctf=1. The cryo-EM map (EMD-32822)¹⁴ of TRiC downloaded from the Electron Microscopy Data Bank (EMDB) was used as the template covered by a sphere mask. The above optimized setting produced distinguished peaks visualized in napari⁵⁵ (Extended Data Fig. 1b and Supplementary Video 1). To analyse all potential TRiC complexes within the datasets, we extracted the top 1,000 peaks per tomogram. The selection was based on the constrained cross-correlation (CCC) value from template matching, and these chosen coordinates were subsequently extracted as subtomograms in Warp. In total, 360,000 untreated and 352,000 treated subtomograms were extracted. 3D classifications (classes = 4, T = 0.5, iterations = 30, without mask) and refinements (C₁ symmetry) were performed in RELION⁵⁶ v.3.1. In total, 3,353 open TRiC particles and 4,054 closed TRiC particles in the untreated dataset, and 3,785 and 3,418 in the treated dataset were identified. Open TRiC particles from untreated and treated datasets were combined and refined to improve map resolution. Closed TRiC particles were merged from untreated and treated datasets and refined with C₁ or D₈ symmetry. Actin filaments were manually picked in ten tomograms. In total, 1,490 subtomograms were extracted and refined at bin4. Atomic models obtained from the PDB (7X3J, 7NVN, 7NVO, 7NVL, 7NVM and 8F8P)^13,16,57 were fitted into our maps. ChimeraX^58,59 was used to visualize EM maps and models.

Subtomogram classification of TRiC states

For 3,353 open TRiC particles in the untreated dataset, classification with a sphere mask covering the potential PFD region (classes = 3, T = 3, iterations = 50, C₁ symmetry) of one ring (denoted ring1) was performed (Extended Data Fig. 2a), which generated 2,874 particles without PFD and 479 particles with PFD of ring1. Independently, the same classification was performed with a mask focused on the other ring (denoted ring2), which produced 2,791 particles without PFD and 562 particles with PFD of ring2. In total, 2,395 particles without PFD, 875 particles with 1 PFD and 83 particles with 2 PFD were identified by sorting particles based on the above two classifications. The same classification strategy was applied to 3,785 open TRiC particles in the treated dataset, resulting in 2,334 particles without PFD, 1,287 particles with 1 PFD and 164 particles with 2 PFD. The atomic model (PDB: 7WU7)¹⁴ was fitted into the maps with PFD. Different classification parameters were evaluated in attempts to resolve the density in the chamber of TRiC, but this did not result in meaningful insights. The densities inside the TRiC chamber were Gaussian filtered (sDev = 2 or 4) for visualization in Figs. 1b and 4d and Extended Data Figs. 3 and 10. For closed TRiC, 3D classification (classes = 4, T = 3, iterations = 35, C₁ symmetry) was performed in untreated and treated datasets independently in RELION 3.1, which revealed several classes with different densities occupied in the chamber of the closed TRiC. Further classification with a mask focusing on the substrate position did not produce meaningful results (Supplementary Figs. 4 and 5). Fourier shell correlation (FSC) was calculated in RELION 3.1.

AlphaFold-Multimer model of the CCT3–CCT1–CCT4–PDCD5 complex

The structure of human PDCD5 in a complex with human CCT3, CCT1 and CCT4 was predicted using AlphaFold-Multimer³¹ (v.2.2.0). The prediction was executed using the default setting with AMBER relaxation, and 15 models were generated for each prediction. The same prediction setting was used for PDCD5 with the other CCT combinations. The full-length amino acid sequences of PDCD5 (UniProt: O14737)⁶⁰ and the equatorial domain of CCT1–CCT8 (the sequences were the same as PDB 7NVO) were used for the above prediction. The monomeric model of PDCD5 (AF-O14737-F1) was downloaded from the AlphaFold Protein Structure Database³⁰.

Sequence alignment

Sequence alignment of CCT1–CCT8 (UniProt: P17987, P78371, P49368, P50991, P48643, P40227, Q99832 and P50990) was executed through Clustal Omega⁶¹. Sequence alignment of PDCD5 (UniProt: M. maripaludis, A9A8D7; S. pombe, O13929; C. elegans, Q93408; mouse, P56812; bovine, Q2HJH9; and human, O14737) and CCT1 (UniProt: H. volcanii, O30561; S. pombe, O94501; C. elegans, P41988; mouse, P11983; bovine, Q32L40; and human, P17987) were performed with ClustalO in Jalview⁶². The sequence conservation score of PDCD5 was calculated using the ConSurf server⁶³.

Spatial analysis of TRiC in situ

The distance and angle examination of TRiC was performed similarly to as in previous studies^22,64,65. For TRiC cluster tracing, the coordinates of TRiC determined by subtomogram averaging were used to localize the particles in the tomograms. The TRiC cluster (containing ≥2 TRiC particles) was defined by the distance between the coordinates of one TRiC and that of its nearest neighbour using a distance cut-off of 20 nm (centre-to-centre distance). As the coordinate represents the centre of the structure, the rotation of the particles would not affect the distance measurement. The particle closest to the previous particle in terms of Euclidean distance was selected as the trailing TRiC within the cluster, provided that it fell within the permitted distance threshold. Various distance thresholds ranging from 15 nm (the minimum centre-to-centre distance between two TRiC) to 40 nm were investigated (Fig. 4b,c). For each specific distance, the threshold was confined within a range of ±0.5 nm (for example, for 17 nm, the permissible distance ranged from 16.5 nm to 17.5 nm). A distance threshold of 20 nm was used to define whether TRiC belongs to the same cluster in this study.

For the distance of TRiC pair analysis in Extended Data Fig. 9h,i, the number and the mean ± s.d. values were n₂ (cluster length = 2) = 326 (17.35 ± 1.18); n₃ = 218 (17.44 ± 1.27), n₄ = 74 (17.01 ± 1.17), n₅ = 35 (17.05 ± 1.16), n₆ = 16 (16.87 ± 1.01) and n₇ = 4 (17.33 ± 0.89), respectively, in the untreated dataset. The number and the mean ± s.d. were n₂ = 195 (17.04 ± 1.28), n₃ = 116 (17.42 ± 1.18), n₄ = 27 (16.87 ± 0.96), n₅ = 7 (17.09 ± 1.25) and n₆ = 4 (16.65 ± 1.88), respectively, in the treated dataset. TRiC pairs with distances between 15 and 20 nm were analysed.

The angle between TRiC and its closest neighbouring TRiC was investigated for particles within clusters in the untreated dataset (Extended Data Fig. 8d). The divided area of the hemisphere contains all points denoting cone rotation, described by Euler angles θ and ψ, of a vector (0, 0, 1). These rotations are projected onto the northern hemisphere (for vectors rotated with a z-coordinate greater than 0) and the southern hemisphere (for vectors rotated with a z-coordinate less than or equal to 0) using stereographic projection. The north pole corresponds to zero rotation, signifying a vector (0, 0, 1). The rotations of the neighbour TRiC were multiplied by the inverse rotations of the respective neighbour particles.

To calculate the percentage of TRiC clusters with neighbouring actin filaments. The particles from the subtomogram averaging of TRiC and actin filaments were mapped back to tomograms for analysis. The threshold of the neighbouring distance (TRiC centre to the centre of actin dimer) was set to 20 nm.

Spatial relation between ribosomes and TRiC in cells

The spatial distribution of TRiC near the ribosome exit tunnel was investigated. The coordinates of ribosome, 60S and 40S determined by subtomogram averaging were used to localize the particles in the tomograms²². The ribosome was rotated to a reference position (zero rotation) through an inverse rotation, which means it was rotated by (−ψ, −θ, −φ)_ribosome. Subsequently, TRiC underwent rotation by its respective angles (φ, θ, ψ)_TRiC, followed by another rotation of (−ψ, −θ, −φ)_ribosome, therefore aligning the ribosome–TRiC within a standard rotation frame (zero rotation of the ribosome), while maintaining their original angular relationship. The coordinates of the ribosome exit tunnel were subtracted from both the ribosome exit tunnel coordinates (setting it to zero) and TRiC coordinates. The new TRiC coordinates were rotated by (−ψ, −θ, −φ)_ribosome to illustrate their positioning relative to the zero rotation of the ribosome. For the spatial analysis of ribosome and TRiC, ribosome particles were more abundant than TRiC particles. As a result, the same TRiC can be the nearest neighbour of several ribosomes. Our analysis focused on the ribosomes that acted as the nearest neighbours of TRiC. The mean ± s.d. in Extended Data Fig. 9c,k were as follows: untreated open TRiC in the ribosome ETS (55.1 ± 0.8%); untreated closed TRiC in the ETS (55.3 ± 0.3%); untreated open TRiC in the non-ETS (44.9 ± 0.8%); untreated closed TRiC in the non-ETS (44.7 ± 0.3%); treated open TRiC in the ETS (50.4 ± 0.4%); treated closed TRiC in the ETS (49.7 ± 1.0%); treated open TRiC in the non-ETS (49.6 ± 0.4%); and treated closed TRiC in the non-ETS (50.3 ± 1.0%). Data plotting and statistical analysis were performed using GraphPad Prism (v.10, GraphPad Software).

Reporting summary

Further information on research design is available in the Nature Portfolio Reporting Summary linked to this article.

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Primary human T cell isolation and expansion

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Evaluation of intratumoural pro-GDF-15 expression levels in human FFPE samples

IHC evaluation of PD-L1 protein expression in human FFPE samples

Multiplex IHC evaluation of CD4, CD8 and FOXP3 expression

Multiplex immunofluorescence evaluation of CD3, GZMB, Ki67, panCK and SOX10

Multiplex histological analyses of biopsies from patients with UC under early-line therapy

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PK–PD modelling of the distribution, elimination and interaction of visugromab and GDF-15

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Grid preparation, data acquisition and tomogram reconstruction

Particle localization and refinement

Subtomogram classification of TRiC states

AlphaFold-Multimer model of the CCT3–CCT1–CCT4–PDCD5 complex

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