Precision-cut liver tissue slice (PCLS) contains all major cell types of the liver parenchyma and preserves the original cell-cell and cell-matrix contacts. It represents a promising ex vivo model to study liver fibrosis and test the antifibrotic effect of experimental compounds in a physiological environment. In this study using RNA sequencing, we demonstrated that various pathways functionally related to fibrotic mechanisms were dysregulated in PCLSs derived from rats subjected to bile duct ligation. The activin receptor-like kinase-5 (Alk5) inhibitor SB525334, nintedanib, and sorafenib each reversed a subset of genes dysregulated in fibrotic PCLSs, and of those genes we identified 608 genes whose expression was reversed by all three compounds. These genes define a molecular signature characterizing many aspects of liver fibrosis pathology and its attenuation in the model. A panel of 12 genes and 4 secreted biomarkers including procollagen I, hyaluronic acid (HA), insulin-like growth factor binding protein 5 (IGFBP5), and WNT1-inducible signaling pathway protein 1 (WISP1) were further validated as efficacy end points for the evaluation of antifibrotic activity of experimental compounds. Finally, we showed that blockade of αV-integrins with a small molecule inhibitor attenuated the fibrotic phenotype in the model. Overall, our results suggest that the rat fibrotic PCLS model may represent a valuable system for target validation and determining the efficacy of experimental compounds. NEW & NOTEWORTHY We investigated the antifibrotic activity of three compounds, the activin receptor-like kinase-5 (Alk5) inhibitor SB525334, nintedanib, and sorafenib, in a rat fibrotic precision-cut liver tissue slice model using RNA sequencing analysis. A panel of 12 genes and 4 secreted biomarkers including procollagen I, hyaluronic acid (HA), insulin-like growth factor binding protein 5 (IGFBP5), and WNT1-inducible signaling pathway protein 1 (WISP1) were then established as efficacy end points to validate the antifibrotic activity of the αV-integrin inhibitor CWHM12. This study demonstrated the value of the rat fibrotic PCLS model for the evaluation of antifibrotic drugs.
Abstract Background: Checkpoint blockade therapies like PD-1 antibodies elicit durable long-lasting immunity in a subset of patients of certain tumor types. However, many patients across a range of tumor types are resistant to checkpoint blockade. Mechanisms that confer local response or resistance to checkpoint blockade are not well understood. Mounting evidence points to local suppression of T cell function as one of the most substantial barriers to effective antitumor immunity. Methods: The study involved multiparametric flow cytometry and genomic characterization of a subset of T cells in the tumors and lymphoid organs of syngeneic tumors, genetically engineered mouse model of cancers and human tumors. Results: A significant fraction (10-40%) of α/β TCR+ CD3+ T cells do not express CD4, CD8 or NKp46 in the tumors. The presence of double-negative T-cell subset (DN T cells) is restricted to tumor microenvironment and is relatively scarce in tumor draining lymph nodes and in spleen. To identify if DN T cells are antigen-specific, we performed AH-1 tetramer staining. While a substantial fraction of CD8 T cells are AH-1 tetramer positive, majority of DN T cells are AH-1 tetramer negative in CT26 tumors. Recently, it has been shown that higher frequency of CD39-negative bystander T cells correlated to lack of response to PD-1 therapy in non-small cell lung cancer patients. Mounting evidence also reveals presence of a specific subset of CD8 T cells with features of stem cell memory in tumors as defined by CXCR5 and TCF1 expression. Efforts are under way to understand if DN T cells exhibit bystander cell and/or memory stem-like phenotype. Majority of the DN T cells are proliferating (Ki67+) and express very low levels of PD-1 (in contrast to CD8 T cells) and Granzyme B. Treatment of mice bearing syngeneic tumors with PD-1 checkpoint blockade therapy does not impact the frequency of DN T-cell subset consistent with lower levels of PD-1 expression. Moreover, a substantial frequency (30-40%) of DN T cells in both syngeneic and KPC pancreatic GEMM tumors express CD103, a tissue resident marker. Furthermore, DN T cells are CD44+ CD127+ KLRG1- and may represent a memory precursor cell population. Upon ex vivo stimulation, these DN T cell subsets proliferate and express modest levels of PD-1. Preliminary analysis of single-cell RNA sequencing data from FACS sorted murine DN T cells reveals lack of CD4, CD8 expression and retention of CD2, CD44, CD69, CCR7 and CXCR5 expression. Flow cytometry analysis of human CD2+ TILs reveals presence of DN T cells in human tumors. Single-cell transcriptome analysis of CD2+ T cells isolated from human colorectal tumors revealed presence of DN T cells. Current efforts are focused on further characterization of this subset in both mouse and human tumors. Conclusions: In this study, we describe a tumor-resident CD4 and CD8 double-negative T-cell subset that may represent a bystander cell population with features of memory precursors and potential implications in modulation of response to checkpoint blockade therapy in cancer. Citation Format: Murali Gururajan, Ravi Kandasamy, Jessica Wong, Kalpit Shah, Shuoguo Wang, Adam Bata, Amy Truong, Sunil Kuppasani, Ching-Ping Ho, Robert Graziano, Michael Quigley, Anwar Murtaza, Jinqi Liu. High-dimensional analysis of tumor-resident CD4 and CD8 double-negative T-cell subset in multiple tumor types [abstract]. In: Proceedings of the AACR Special Conference on Tumor Immunology and Immunotherapy; 2018 Nov 27-30; Miami Beach, FL. Philadelphia (PA): AACR; Cancer Immunol Res 2020;8(4 Suppl):Abstract nr B61.
Abstract Background: Integrated analysis of multi-omic data is important in understanding oncogenesis, pathology, and drug mechanism of action. Formalin-fixed, paraffin-embedded (FFPE) tissues comprise the bulk of archival specimens in hospitals and clinical trials. Commercial kits are commonly used to extract RNA, DNA, or protein for biomarker studies; however, high-quality extractions are challenging due to crosslinking. We explored the feasibility of performing proteomic, transcriptomic, and genetic analysis from limited FFPE samples collected in clinical trials through a pilot study in colorectal cancer (CRC) and normal tissue. Methods: Qiagen kits were employed, with some modifications, to extract nucleic acid and protein from FFPE sample lysates that would be amenable to next-generation sequencing and liquid chromatography/mass-spectrometry (LC/MS) proteomic profiling. Commercially sourced FFPE slides from CRC biopsies and normal colon, heart, and skin samples were processed (n = 10 each; ~600-mm2 by 5-μm/slice). RNA-seq library preparation was performed using the Illumina® TruSeq Access kit. Label-free LC/MS proteomic analysis was carried out using trypsin/Lys-C-digested protein fragments on an EASY-nLC™ 1200 coupled to a Q Exactive™ Plus (Thermo Fisher). MS data were processed with MaxQuant to estimate protein abundance (Cox and Mann, Nat Biotech 2008). Results: Of 40 samples tested, 38 yielded quantifiable nucleic acid and protein of sufficient quality for transcriptional and proteomic analyses. Mean RNA yield was ~300 ng (150 ng-1.2 µg). RNA degradation was significant, with a mean DV>200 of 45% (Agilent Bioanalyzer). Mean DNA yield was 530 ng, with a mean fragment size of 2 kb. Mean protein yield was 50 µg (1 µg-300 µg). RNA libraries had a mapping rate range of 85%-90% and a coding rate range of 70%-80%; ~16,000 genes were reliable detected (log2 TPM > 1). The number of unique proteins detected ranged from 3,000 to 4,000 for CRC, normal colon, and heart samples; skin samples averaged 1,000 proteins and had the lowest overall yield. Correlation of RNA and protein expression for the same genes was weak (Spearman's rho ~0.3-0.4) at the per-sample level but statistically significant. Using linear models, we identified differentially expressed transcripts and proteins between the CRC and normal colon samples. Pathway enrichment analysis of both modalities indicated changes in cell cycle, which is consistent with rapid growth of tumor cells. Changes in nucleoside metabolism, extracellular matrix remodeling, and innate immune response were more apparent at the protein level. Conclusion: We found that multi-omic analysis was feasible with FFPE samples, and proteomics can be used to validate RNA results. Additionally, proteomics reveal post-translational events, such as extracellular matrix remodeling, that provide unique insights into cancer pathology. Citation Format: Vishal Patel, Ji Gao, Mingyi Liu, Aiqing He, Xi-Tao Wang, Kathryn Vanderlaag, Ariella Sasson, Stefan Kirov, Sunil Kuppasani, Omar J. Jabado, Kandasamy Ravi, Ashok Dongre, Julie Carman, Heidi LeBlanc. Integrated analysis of colorectal carcinoma by co-extraction of RNA, DNA and protein from FFPE tumor samples [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 2707.
The translation of novel pulmonary fibrosis therapies from preclinical models into the clinic represents a major challenge demonstrated by the high attrition rate of compounds that showed efficacy in preclinical models but demonstrated no significant beneficial effects in clinical trials. A precision-cut lung tissue slice (PCLS) contains all major cell types of the lung and preserves the original cell-cell and cell-matrix contacts. It represents a promising ex vivo model to study pulmonary fibrosis. In this study, using RNA sequencing, we demonstrated that transforming growth factor-β1 (TGFβ1) induced robust fibrotic responses in the rat PCLS model, as it changed the expression of genes functionally related to extracellular matrix remodeling, cell adhesion, epithelial-to-mesenchymal transition, and various immune responses. Nintedanib, pirfenidone, and sorafenib each reversed a subset of genes modulated by TGFβ1, and of those genes we identified 229 whose expression was reversed by all three drugs. These genes define a molecular signature characterizing many aspects of pulmonary fibrosis pathology and its attenuation in the rat PCLS fibrosis model. A panel of 12 genes and three secreted biomarkers, including procollagen I, hyaluronic acid, and WNT1-inducible signaling pathway protein 1 were validated as efficacy end points for the evaluation of antifibrotic activity of experimental compounds. Finally, we showed that blockade of α V -integrins suppressed TGFβ1-induced fibrotic responses in the rat PCLS fibrosis model. Overall, our results suggest that the TGFβ1-induced rat PCLS fibrosis model may represent a valuable system for target validation and to determine the efficacy of experimental compounds.
S-nitrosylation, or the replacement of the hydrogen atom in the thiol group of cysteine residues by a -NO moiety, is a physiologically important posttranslational modification. In our previous work we have shown that S-nitrosylation is involved in the disruption of the endothelial nitric oxide synthase (eNOS) dimer and that this involves the disruption of the zinc (Zn) tetrathiolate cluster due to the S-nitrosylation of Cysteine 98. However, human eNOS contains 28 other cysteine residues whose potential to undergo S-nitrosylation has not been determined. Thus, the goal of this study was to identify the cysteine residues within eNOS that are susceptible to S-nitrosylation in vitro. To accomplish this, we utilized a modified biotin switch assay. Our modification included the tryptic digestion of the S-nitrosylated eNOS protein to allow the isolation of S-nitrosylated peptides for further identification by mass spectrometry. Our data indicate that multiple cysteine residues are capable of undergoing S-nitrosylation in the presence of an excess of a nitrosylating agent. All these cysteine residues identified were found to be located on the surface of the protein according to the available X-ray structure of the oxygenase domain of eNOS. Among those identified were Cys 93 and 98, the residues involved in the formation of the eNOS dimer through a Zn tetrathiolate cluster. In addition, cysteine residues within the reductase domain were identified as undergoing S-nitrosylation. We identified cysteines 660, 801, and 1113 as capable of undergoing S-nitrosylation. These cysteines are located within regions known to bind flavin mononucleotide (FMN), flavin adenine dinucleotide (FAD), and nicotinamide adenine dinucleotide (NADPH) although from our studies their functional significance is unclear. Finally we identified cysteines 852, 975/990, and 1047/1049 as being susceptible to S-nitrosylation. These cysteines are located in regions of eNOS that have not been implicated in any known biochemical functions and the significance of their S-nitrosylation is not clear from this study. Thus, our data indicate that the eNOS protein can be S-nitrosylated at multiple sites other than within the Zn tetrathiolate cluster, suggesting that S-nitrosylation may regulate eNOS function in ways other than simply by inducing dimer collapse.
Endothelial nitric oxide synthase (eNOS) is inhibited by hydrogen peroxide (H(2)O(2)), but the mechanism has not been determined. Thus, the purpose of this study was to delineate the mechanism by which H(2)O(2) inhibits eNOS activity. Using mass spectroscopy, we found that the tetrathiolate cysteine residues 94 and 99 were susceptible to oxidation by H(2)O(2). Molecular modeling predicted that these cysteic acid modifications would disrupt the van der Waals interactions and the hydrogen bonding network mediated by the tetrathiolate cysteines 94 and 99 resulting in changes in quaternary structure, zinc release, and dimer collapse. Using recombinant human eNOS (heNOS) to test the predictions of the molecular modeling we found that H(2)O(2) caused disruption of the heNOS dimer and this was accompanied by zinc release and decreased NO generation. We also found that H(2)O(2) increased the oxidation of tetrahydrobiopterin (BH(4)) to dihydrobiopterin (BH(2)), whereas preincubation of heNOS with excess BH(4) prevented the destruction of zinc tetrathiolate and dimer collapse and preserved activity. Interestingly, we found that the dimmer-stabilizing effect of BH(4) is due to its ability to act as a catalase mimetic. Further, we confirmed that, in ovine aortic endothelial cells, H(2)O(2) could also induce dimer collapse and that increasing cellular BH(4) levels could maintain eNOS in its dimeric form and NO signaling when cells were challenged with H(2)O(2). This study links the inhibitory action of H(2)O(2) on heNOS through the destruction of zinc tetrathiolate metal-binding site and dimer collapse both in vitro and in vivo.
Abstract Background: Early detection of recurrence and monitoring of MRD post-surgery is critical for clinical decision-making to tailor adjuvant therapy. In early-stage NSCLC, circulating tumor DNA (ctDNA) detection is especially challenging, requiring highly sensitive and specific assays. Therefore, we used a WGS approach (MRDetect) for ultra-sensitive ctDNA detection in NSCLC patients (pts) undergoing curative surgery. Methods: We conducted a pilot study to evaluate the MRDetect approach in serial plasma samples (including pre-surgery, post-surgery and follow-up [f/u] timepoints) from resected stage IB-IIIA NSCLC pts. Pts underwent routine surveillance by computed tomography scans. ctDNA was extracted from ~1mL plasma. MRDetect uses WGS by a tumor-informed approach (sequencing coverage 40x for tumor, 20x for plasma DNA) combined with AI-based error suppression models (trained and calibrated with a non-cancer cohort, n=17) to increase the signal to noise ratio for precise ctDNA detection, and improve the accuracy of readouts especially for low tumor burden scenarios. The assay reports the detection and quantification of ctDNA burden in blood with a prognostic value for risk of recurrence. The ability of the assay to predict recurrence from a single sample, taken at the clinical landmark point (median 1.6 mths post-surgery, range 0.1-6.5) was evaluated. Results: Overall, 52 NSCLC pts were enrolled (n=88 plasma samples) with median clinical f/u of 32.6 mths (range 3.1-98.6). There were 43 pts with post-surgery landmark samples, with median age 62 years, 70% were male, 79% were adenocarcinoma and 49% were EGFR mutated. 26% were stage IB and 37% each were stage II and III. There were 15/18 (sensitivity 83%) pts with confirmed radiological recurrence in which MRDetect was positive, including 6/7 (86%) EGFR mutated pts. The median RFS in MRDetect positive pts was 15.2 mths (range 3.7-33.4). Among 25 pts with no recurrence (median f/u 25.6 mths), MRDetect reported 4 pts to be MRD positive (specificity 84%). These results were consistent between EGFR mutated (sensitivity 86%, specificity 86%) and wildtype pts (sensitivity 82%, specificity 82%). For longitudinal samples (n=17 pts), negative ctDNA was associated with absence of recurrence in 14/15 pts (specificity 93%). At the AACR meeting, results from a planned larger validation study will be presented. Conclusion: Using a robust WGS implemented AI-based computational platform (MRDetect), we demonstrate high sensitivity and specificity detection of MRD in both EGFR mutated and wildtype NSCLC. With an increasing number of therapeutic options in the adjuvant setting for NSCLC, an ultra-sensitive MRD assay has the potential to facilitate personalized clinical decision-making for tailoring both the need and choice of adjuvant therapies. Citation Format: Aaron C. Tan, Stephanie P. Saw, Gillianne G. Lai, Kevin L. Chua, Angela Takano, Boon-Hean Ong, Tina P. Koh, Amit Jain, Wan Ling Tan, Quan Sing Ng, Ravindran Kanesvaran, Tanujaa Rajasekaran, Sunil Deochand, Dillon Maloney, Danielle Afterman, Tomer Lauterman, Noah Friedman, Imane Bourzgui, Nidhi Ramaraj, Zohar Donenhirsh, Ronel Veksler, Jonathan Rosenfeld, Ravi Kandasamy, Iman Tavassoly, Boris Oklander, Asaf Zviran, Wan-Teck Lim, Eng-Huat Tan, Anders J. Skanderup, Mei-Kim Ang, Daniel S. Tan. Ultra-sensitive detection of minimal residual disease (MRD) through whole genome sequencing (WGS) using an AI-based error suppression model in resected early-stage non-small cell lung cancer (NSCLC) [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 5114.
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