Preclinical proof of concept for VivoVec, a lentiviral-based platform for in vivo CAR T-cell engineering

Journal for immunotherapy of cancer

2023 Mar 01

Michels, KR;Sheih, A;Hernandez, SA;Brandes, AH;Parrilla, D;Irwin, B;Perez, AM;Ting, HA;Nicolai, CJ;Gervascio, T;Shin, S;Pankau, MD;Muhonen, M;Freeman, J;Gould, S;Getto, R;Larson, RP;Ryu, BY;Scharenberg, AM;Sullivan, AM;Green, S;
PMID: 36918221 | DOI: 10.1136/jitc-2022-006292

Chimeric antigen receptor (CAR) T-cell therapies have demonstrated transformational outcomes in the treatment of B-cell malignancies, but their widespread use is hindered by technical and logistical challenges associated with ex vivo cell manufacturing. To overcome these challenges, we developed VivoVec, a lentiviral vector-based platform for in vivo engineering of T cells. UB-VV100, a VivoVec clinical candidate for the treatment of B-cell malignancies, displays an anti-CD3 single-chain variable fragment (scFv) on the surface and delivers a genetic payload that encodes a second-generation CD19-targeted CAR along with a rapamycin-activated cytokine receptor (RACR) system designed to overcome the need for lymphodepleting chemotherapy in supporting successful CAR T-cell expansion and persistence. In the presence of exogenous rapamycin, non-transduced immune cells are suppressed, while the RACR system in transduced cells converts rapamycin binding to an interleukin (IL)-2/IL-15 signal to promote proliferation.UB-VV100 was administered to peripheral blood mononuclear cells (PBMCs) from healthy donors and from patients with B-cell malignancy without additional stimulation. Cultures were assessed for CAR T-cell transduction and function. Biodistribution was evaluated in CD34-humanized mice and in canines. In vivo efficacy was evaluated against normal B cells in CD34-humanized mice and against systemic tumor xenografts in PBMC-humanized mice.In vitro, administration of UB-VV100 resulted in dose-dependent and anti-CD3 scFv-dependent T-cell activation and CAR T-cell transduction. The resulting CAR T cells exhibited selective expansion in rapamycin and antigen-dependent activity against malignant B-cell targets. In humanized mouse and canine studies, UB-VV100 demonstrated a favorable biodistribution profile, with transduction events limited to the immune compartment after intranodal or intraperitoneal administration. Administration of UB-VV100 to humanized mice engrafted with B-cell tumors resulted in CAR T-cell transduction, expansion, and elimination of systemic malignancy.These findings demonstrate that UB-VV100 generates functional CAR T cells in vivo, which could expand patient access to CAR T technology in both hematological and solid tumors without the need for ex vivo cell manufacturing.

Fibroblast Growth Factor Receptor 1 and Related Ligands in Small-Cell Lung Cancer.

J Thorac Oncol. 2015 May 27.

Zhang L, Yu H, Badzio A, Boyle TA, Schildhaus HU, Lu X, Dziadziuszko R, Jassem J, Varella-Garcia M, Heasley LE, Kowalewski AA, Ellison K, Chen G, Zhou C, Hirsch FR.
PMID: 26016563 | DOI: 10.1080/15476286.2015.1053687

Introduction: Small-cell lung cancer (SCLC) accounts for 15% of all lung cancers and has been understudied for novel therapies. Signaling through fibroblast growth factors (FGF2, FGF9) and their high-affinity receptor has recently emerged as a contributing factor in the pathogenesis and progression of non-small-cell lung cancer. In this study, we evaluated fibroblast growth factor receptor 1 (FGFR1) and ligand expression in primary SCLC samples. Methods: FGFR1 protein expression, messenger RNA (mRNA) levels, and gene copy number were determined by immunohistochemistry (IHC), mRNA in situ hybridization, and silver in situ hybridization, respectively, in primary tumors from 90 patients with SCLC. Protein and mRNA expression of the FGF2 and FGF9 ligands were determined by IHC and mRNA in situ hybridization, respectively. In addition, a second cohort of 24 SCLC biopsy samples with known FGFR1 amplification by fluorescence in situ hybridization was assessed for FGFR1 protein expression by IHC. Spearman correlation analysis was performed to evaluate associations of FGFR1, FGF2 and FGF9 protein levels, respective mRNA levels, and FGFR1 gene copy number. Results: FGFR1 protein expression by IHC demonstrated a significant correlation with FGFR1 mRNA levels (p < 0.0001) and FGFR1 gene copy number (p = 0.03). The prevalence of FGFR1 mRNA positivity was 19.7%. FGFR1 mRNA expression correlated with both FGF2 (p = 0.0001) and FGF9 (p = 0.002) mRNA levels, as well as with FGF2 (p = 0.01) and FGF9 (p = 0.001) protein levels. There was no significant association between FGFR1 and ligands with clinical characteristics or prognosis. In the second cohort of specimens with known FGFR1 amplification by fluorescence in situ hybridization, 23 of 24 had adequate tumor by IHC, and 73.9% (17 of 23) were positive for FGFR1 protein expression. Conclusions: A subset of SCLCs is characterized by potentially activated FGF/FGFR1 pathways, as evidenced by positive FGF2, FGF9, and FGFR1 protein and/or mRNA expression. FGFR1 protein expression is correlated with FGFR1 mRNA levels and FGFR1 gene copy number. Combined analysis of FGFR1 and ligand expression may allow selection of patients with SCLC to FGFR1 inhibitor therapy.

The microdissected gene expression landscape of nasopharyngeal cancer reveals vulnerabilities in FGF and noncanonical NF-κB signaling

Science advances

2022 Apr 08

Tay, JK;Zhu, C;Shin, JH;Zhu, SX;Varma, S;Foley, JW;Vennam, S;Yip, YL;Goh, CK;Wang, Y;Loh, KS;Tsao, SW;Le, QT;Sunwoo, JB;West, RB;
PMID: 35394843 | DOI: 10.1126/sciadv.abh2445

Nasopharyngeal cancer (NPC) is an Epstein-Barr virus (EBV)-positive epithelial malignancy with an extensive inflammatory infiltrate. Traditional RNA-sequencing techniques uncovered only microenvironment signatures, while the gene expression of the tumor epithelial compartment has remained a mystery. Here, we use Smart-3SEQ to prepare transcriptome-wide gene expression profiles from microdissected NPC tumors, dysplasia, and normal controls. We describe changes in biological pathways across the normal to tumor spectrum and show that fibroblast growth factor (FGF) ligands are overexpressed in NPC tumors, while negative regulators of FGF signaling, including SPRY1, SPRY2, and LGALS3, are down-regulated early in carcinogenesis. Within the NF-κB signaling pathway, the critical noncanonical transcription factors, RELB and NFKB2, are enriched in the majority of NPC tumors. We confirm the responsiveness of EBV-positive NPC cell lines to targeted inhibition of these pathways, reflecting the heterogeneity in NPC patient tumors. Our data comprehensively describe the gene expression landscape of NPC and unravel the mysteries of receptor tyrosine kinase and NF-κB pathways in NPC.

iBRIDGE: A Data Integration Method to Identify Inflamed Tumors from Single-Cell RNAseq Data and Differentiate Cell Type-Specific Markers of Immune-Cell Infiltration

Cancer immunology research

2023 Apr 06

Turan, T;Kongpachith, S;Halliwill, K;McLaughlin, RT;Binnewies, M;Reddy, D;Zhao, X;Mathew, R;Ye, S;Jacob, HJ;Samayoa, J;
PMID: 37023414 | DOI: 10.1158/2326-6066.CIR-22-0283

The development of immune checkpoint-based immunotherapies has been a major advancement in the treatment of cancer, with a subset of patients exhibiting durable clinical responses. A predictive biomarker for immunotherapy response is the pre-existing T-cell infiltration in the tumor immune microenvironment (TIME). Bulk transcriptomics-based approaches can quantify the degree of T-cell infiltration using deconvolution methods and identify additional markers of inflamed/cold cancers at the bulk level. However, bulk techniques are unable to identify biomarkers of individual cell types. Although single-cell RNA sequencing (scRNAseq) assays are now being used to profile the TIME, to our knowledge there is no method of identifying patients with a T-cell inflamed TIME from scRNAseq data. Here, we describe a method, iBRIDGE, which integrates reference bulk RNAseq data with the malignant subset of scRNAseq datasets to identify patients with a T-cell inflamed TIME. Utilizing two datasets with matched bulk data, we show iBRIDGE results correlated highly with bulk assessments (0.85 and 0.9 correlation coefficients). Using iBRIDGE, we identified markers of inflamed phenotypes in malignant cells, myeloid cells, and fibroblasts, establishing type I and type II interferon pathways as dominant signals, especially in malignant and myeloid cells, and finding the TGFβ-driven mesenchymal phenotype not only in fibroblasts but also in malignant cells. Besides relative classification, per-patient average iBRIDGE scores and independent RNAScope quantifications were utilized for threshold-based absolute classification. Moreover, iBRIDGE can be applied to in vitro grown cancer cell lines and can identify the cell lines that are adapted from inflamed/cold patient tumors.

Microtubule-Driven Stress Granule Dynamics Regulate Inhibitory Immune Checkpoint Expression in T Cells.

Cell Rep. 2019 Jan 2;26(1):94-107.e7.

2019 Jan 02

Franchini DM, Lanvin O, Tosolini M, Patras de Campaigno E, Cammas A, Péricart S, Scarlata CM, Lebras M, Rossi C, Ligat L, Pont F, Arimondo PB, Laurent C, Ayyoub M, Despas F, Lapeyre-Mestre M, Millevoi S, Fournié JJ.
PMID: 30605689 | DOI: 10.1016/j.celrep.2018.12.014

Despite the clinical success of blocking inhibitory immune checkpoint receptors such as programmed cell death-1 (PD-1) in cancer, the mechanisms controlling the expression of these receptors have not been fully elucidated. Here, we identify a post-transcriptional mechanism regulating PD-1 expression in T cells. Upon activation, the PDCD1 mRNA and ribonucleoprotein complexes coalesce into stress granules that require microtubules and the kinesin 1 molecular motor to proceed to translation. Hence, PD-1 expression is highly sensitive to microtubule or stress granule inhibitors targeting this pathway. Evidence from healthy donors and cancer patients reveals a common regulation for the translation of CTLA4, LAG3, TIM3, TIGIT, and BTLA but not of the stimulatory co-receptors OX40, GITR, and 4-1BB mRNAs. In patients, disproportionality analysis of immune-related adverse events for currently used microtubule drugs unveils a significantly higher risk of autoimmunity. Our findings reveal a fundamental mechanism of immunoregulation with great importance in cancer immunotherapy.

Biomarker correlates with response to NY-ESO-1 TCR T cells in patients with synovial sarcoma

Nature communications

2022 Sep 08

Gyurdieva, A;Zajic, S;Chang, YF;Houseman, EA;Zhong, S;Kim, J;Nathenson, M;Faitg, T;Woessner, M;Turner, DC;Hasan, AN;Glod, J;Kaplan, RN;D'Angelo, SP;Araujo, DM;Chow, WA;Druta, M;Demetri, GD;Van Tine, BA;Grupp, SA;Fine, GD;Eleftheriadou, I;
PMID: 36075914 | DOI: 10.1038/s41467-022-32491-x

Autologous T cells transduced to express a high affinity T-cell receptor specific to NY-ESO-1 (letetresgene autoleucel, lete-cel) show promise in the treatment of metastatic synovial sarcoma, with 50% overall response rate. The efficacy of lete-cel treatment in 45 synovial sarcoma patients (NCT01343043) has been previously reported, however, biomarkers predictive of response and resistance remain to be better defined. This post-hoc analysis identifies associations of response to lete-cel with lymphodepleting chemotherapy regimen (LDR), product attributes, cell expansion, cytokines, and tumor gene expression. Responders have higher IL-15 levels pre-infusion (p = 0.011) and receive a higher number of transduced effector memory (CD45RA- CCR7-) CD8 + cells per kg (p = 0.039). Post-infusion, responders have increased IFNγ, IL-6, and peak cell expansion (p < 0.01, p < 0.01, and p = 0.016, respectively). Analysis of tumor samples post-treatment illustrates lete-cel infiltration and a decrease in expression of macrophage genes, suggesting remodeling of the tumor microenvironment. Here we report potential predictive and pharmacodynamic markers of lete-cel response that may inform LDR, cell dose, and strategies to enhance anticancer efficacy.

Autophagy inhibition by targeting PIKfyve potentiates response to immune checkpoint blockade in prostate cancer

Nature Cancer

2021 Aug 02

Qiao, Y;Choi, J;Tien, J;Simko, S;Rajendiran, T;Vo, J;Delekta, A;Wang, L;Xiao, L;Hodge, N;Desai, P;Mendoza, S;Juckette, K;Xu, A;Soni, T;Su, F;Wang, R;Cao, X;Yu, J;Kryczek, I;Wang, X;Wang, X;Siddiqui, J;Wang, Z;Bernard, A;Fernandez-Salas, E;Navone, N;Ellison, S;Ding, K;Eskelinen, E;Heath, E;Klionsky, D;Zou, W;Chinnaiyan, A;
| DOI: 10.1038/s43018-021-00237-1

(A) Myc-CaP wild-type (WT) and _Atg5_ knockout (_Atg5_ KO) cells were treated with increasing concentrations of ESK981 for 24 hours. Atg5 and LC3 levels were assessed by western blot from three independent experiments. GAPDH served as a loading control. (B) Representative morphology of vacuolization in Myc-CaP wild-type (WT) and _Atg5_ knockout (_Atg5_ KO) cells after treatment with control or 100 nM ESK981 for 24 hours from three independent experiments. (C) Autophagosome content of Myc-CaP WT and _Atg5_ KO cells were measured by CYTO-ID assay after being treated with increasing concentrations of ESK981 for 24 hours. Data were analyzed by two-tailed unpaired t test from three independent experiments and presented as mean ± SEM. P-value indicated. (D) Mouse cytokine array using Myc-CaP WT and _Atg5_ KO cell supernatant after treatment with 10 ng/ml mouse interferon gamma (mIFNγ) or mIFNγ + 100 nM ESK981 for 24 hours. Differential expression candidate dots are highlighted by boxes. (E) Mouse CXCL10 protein levels were measured by ELISA in Myc-CaP WT and _Atg5_ KO conditioned medium with the indicated treatment for 24 hours. Data were analyzed by two-tailed unpaired t test from three independent experiments and presented as mean ± SEM. P-value indicated. (F) mRNA levels of _Cxcl10_ and _Cxcl9_ were measured by qPCR in Myc-CaP WT and _Atg5_ KO cells with 50 nM or 100 nM ESK981 and 10 ng/ml mIFNγ treatment for 24 hours. Data were analyzed by two-tailed unpaired t test from three independent experiments and presented as mean ± SEM. P-value indicated.

Spatially organized multicellular immune hubs in human colorectal cancer

Cell

2021 Aug 24

Pelka, K;Hofree, M;Chen, JH;Sarkizova, S;Pirl, JD;Jorgji, V;Bejnood, A;Dionne, D;Ge, WH;Xu, KH;Chao, SX;Zollinger, DR;Lieb, DJ;Reeves, JW;Fuhrman, CA;Hoang, ML;Delorey, T;Nguyen, LT;Waldman, J;Klapholz, M;Wakiro, I;Cohen, O;Albers, J;Smillie, CS;Cuoco, MS;Wu, J;Su, MJ;Yeung, J;Vijaykumar, B;Magnuson, AM;Asinovski, N;Moll, T;Goder-Reiser, MN;Applebaum, AS;Brais, LK;DelloStritto, LK;Denning, SL;Phillips, ST;Hill, EK;Meehan, JK;Frederick, DT;Sharova, T;Kanodia, A;Todres, EZ;Jané-Valbuena, J;Biton, M;Izar, B;Lambden, CD;Clancy, TE;Bleday, R;Melnitchouk, N;Irani, J;Kunitake, H;Berger, DL;Srivastava, A;Hornick, JL;Ogino, S;Rotem, A;Vigneau, S;Johnson, BE;Corcoran, RB;Sharpe, AH;Kuchroo, VK;Ng, K;Giannakis, M;Nieman, LT;Boland, GM;Aguirre, AJ;Anderson, AC;Rozenblatt-Rosen, O;Regev, A;Hacohen, N;
PMID: 34450029 | DOI: 10.1016/j.cell.2021.08.003

Immune responses to cancer are highly variable, with mismatch repair-deficient (MMRd) tumors exhibiting more anti-tumor immunity than mismatch repair-proficient (MMRp) tumors. To understand the rules governing these varied responses, we transcriptionally profiled 371,223 cells from colorectal tumors and adjacent normal tissues of 28 MMRp and 34 MMRd individuals. Analysis of 88 cell subsets and their 204 associated gene expression programs revealed extensive transcriptional and spatial remodeling across tumors. To discover hubs of interacting malignant and immune cells, we identified expression programs in different cell types that co-varied across tumors from affected individuals and used spatial profiling to localize coordinated programs. We discovered a myeloid cell-attracting hub at the tumor-luminal interface associated with tissue damage and an MMRd-enriched immune hub within the tumor, with activated T cells together with malignant and myeloid cells expressing T cell-attracting chemokines. By identifying interacting cellular programs, we reveal the logic underlying spatially organized immune-malignant cell networks.

	Description
sense Example: Hs-LAG3-sense	Standard probes for RNA detection are in antisense. Sense probe is reverse complent to the corresponding antisense probe.
Intron# Example: Mm-Htt-intron2	Probe targets the indicated intron in the target gene, commonly used for pre-mRNA detection
Pool/Pan Example: Hs-CD3-pool (Hs-CD3D, Hs-CD3E, Hs-CD3G)	A mixture of multiple probe sets targeting multiple genes or transcripts
No-XSp Example: Hs-PDGFB-No-XMm	Does not cross detect with the species (Sp)
XSp Example: Rn-Pde9a-XMm	designed to cross detect with the species (Sp)
O# Example: Mm-Islr-O1	Alternative design targeting different regions of the same transcript or isoforms
CDS Example: Hs-SLC31A-CDS	Probe targets the protein-coding sequence only
EnEm	Probe targets exons n and m
En-Em	Probe targets region from exon n to exon m
Retired Nomenclature
tvn Example: Hs-LEPR-tv1	Designed to target transcript variant n
ORF Example: Hs-ACVRL1-ORF	Probe targets open reading frame
UTR Example: Hs-HTT-UTR-C3	Probe targets the untranslated region (non-protein-coding region) only
5UTR Example: Hs-GNRHR-5UTR	Probe targets the 5' untranslated region only
3UTR Example: Rn-Npy1r-3UTR	Probe targets the 3' untranslated region only
Pan Example: Pool	A mixture of multiple probe sets targeting multiple genes or transcripts

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