Antibody-based immunotherapy of cancer.

By targeting surface antigens expressed on tumor cells, monoclonal antibodies have demonstrated efficacy as cancer therapeutics. Recent successful antibody-based strategies have focused on enhancing antitumor immune responses by targeting immune cells, irrespective of tumor antigens. We discuss these innovative strategies and propose how they will impact the future of antibody-based cancer therapy.

Phase III Prospectively Randomized Trial of Perioperative 5-FU After Curative Resection for Colon Cancer: An Intergroup Trial of the ECOG-ACRIN Cancer Research Group (E1292).

BACKGROUND: Studies suggest that adjuvant chemotherapy should be initiated at the earliest possible time. The Eastern Cooperative Oncology Group (ECOG) and Intergroup evaluated the effect of perioperative fluorouracil (5-FU) on overall survival (OS) for colon cancer. PATIENTS AND METHODS: This phase III trial randomized patients to receive continuous infusional 5-FU for 7 days starting within 24 h after curative resection (arm A) or no perioperative 5-FU (arm B). Patients with Dukes' B3 and C disease received adjuvant chemotherapy per standard of care. The primary endpoint of the trial was overall survival in patients with Dukes' B3 and C disease. The secondary objective was to determine whether a week of perioperative infusion would affect survival in patients with Dukes' B2 colon cancer with no additional chemotherapy. RESULTS: From August 1993 to May 2000, 859 patients were enrolled and 855 randomized (arm A: 427; arm B: 428). The trial was terminated early due to slow accrual. The median follow-up is 15.4 years (0.03-20.3 years). Among patients with Dukes' B3 and C disease, there was no statistically significant difference in OS [median 10.3 years (95% CI 8.4, 13.2) for perioperative chemotherapy and 9.3 years (95% CI 5.7, 12.3) for no perioperative therapy, one-sided log-rank p = 0.178, HR = 0.88 (95% CI 0.66, 1.16)] or disease-free survival (DFS). For patients with Dukes' B2 disease, there was also no significant difference in OS (median 16.1 versus 12.9 years) or DFS. There was no difference between treatment arms in operative complications. One week of continuous infusion of 5-FU was tolerable; 18% of arm A patients experienced grade 3 or greater toxicity.

Cadherin 11 Promotes Immunosuppression and Extracellular Matrix Deposition to Support Growth of Pancreatic Tumors and Resistance to Gemcitabine in Mice.

BACKGROUND & AIMS: Pancreatic ductal adenocarcinomas (PDACs) are characterized by fibrosis and an abundance of cancer-associated fibroblasts (CAFs). We investigated strategies to disrupt interactions among CAFs, the immune system, and cancer cells, focusing on adhesion molecule CDH11, which has been associated with other fibrotic disorders and is expressed by activated fibroblasts. METHODS: We compared levels of CDH11 messenger RNA in human pancreatitis and pancreatic cancer tissues and cells with normal pancreas, and measured levels of CDH11 protein in human and mouse pancreatic lesions and normal tissues. We crossed p48-Cre;LSL-KrasG12D/+;LSL-Trp53R172H/+ (KPC) mice with CDH11-knockout mice and measured survival times of offspring. Pancreata were collected and analyzed by histology, immunohistochemistry, and (single-cell) RNA sequencing; RNA and proteins were identified by imaging mass cytometry. Some mice were given injections of PD1 antibody or gemcitabine and survival was monitored. Pancreatic cancer cells from KPC mice were subcutaneously injected into Cdh11+/+ and Cdh11-/- mice and tumor growth was monitored. Pancreatic cancer cells (mT3) from KPC mice (C57BL/6), were subcutaneously injected into Cdh11+/+ (C57BL/6J) mice and mice were given injections of antibody against CDH11, gemcitabine, or small molecule inhibitor of CDH11 (SD133) and tumor growth was monitored. RESULTS: Levels of CDH11 messenger RNA and protein were significantly higher in CAFs than in pancreatic cancer epithelial cells, human or mouse pancreatic cancer cell lines, or immune cells. KPC/Cdh11+/- and KPC/Cdh11-/- mice survived significantly longer than KPC/Cdh11+/+ mice. Markers of stromal activation entirely surrounded pancreatic intraepithelial neoplasias in KPC/Cdh11+/+ mice and incompletely in KPC/Cdh11+/- and KPC/Cdh11-/- mice, whose lesions also contained fewer FOXP3+ cells in the tumor center. Compared with pancreatic tumors in KPC/Cdh11+/+ mice, tumors of KPC/Cdh11+/- mice had increased markers of antigen processing and presentation; more lymphocytes and associated cytokines; decreased extracellular matrix components; and reductions in markers and cytokines associated with immunosuppression. Administration of the PD1 antibody did not prolong survival of KPC mice with 0, 1, or 2 alleles of Cdh11. Gemcitabine extended survival of KPC/Cdh11+/- and KPC/Cdh11-/- mice only or reduced subcutaneous tumor growth in mT3 engrafted Cdh11+/+ mice when given in combination with the CDH11 antibody. A small molecule inhibitor of CDH11 reduced growth of pre-established mT3 subcutaneous tumors only if T and B cells were present in mice. CONCLUSIONS: Knockout or inhibition of CDH11, which is expressed by CAFs in the pancreatic tumor stroma, reduces growth of pancreatic tumors, increases their response to gemcitabine, and significantly extends survival of mice. CDH11 promotes immunosuppression and extracellular matrix deposition, and might be developed as a therapeutic target for pancreatic cancer.

Combining Three-Dimensional Modeling with Artificial Intelligence to Increase Specificity and Precision in Peptide-MHC Binding Predictions.

The reliable prediction of the affinity of candidate peptides for the MHC is important for predicting their potential antigenicity and thus influences medical applications, such as decisions on their inclusion in T cell-based vaccines. In this study, we present a rapid, predictive computational approach that combines a popular, sequence-based artificial neural network method, NetMHCpan 4.0, with three-dimensional structural modeling. We find that the ensembles of bound peptide conformations generated by the programs MODELLER and Rosetta FlexPepDock are less variable in geometry for strong binders than for low-affinity peptides. In tests on 1271 peptide sequences for which the experimental dissociation constants of binding to the well-characterized murine MHC allele H-2Db are known, by applying thresholds for geometric fluctuations the structure-based approach in a standalone manner drastically improves the statistical specificity, reducing the number of false positives. Furthermore, filtering candidates generated with NetMHCpan 4.0 with the structure-based predictor led to an increase in the positive predictive value (PPV) of the peptides correctly predicted to bind very strongly (i.e., K d < 100 nM) from 40 to 52% (p = 0.027). The combined method also significantly improved the PPV when tested on five human alleles, including some with limited data for training. Overall, an average increase of 10% in the PPV was found over the standalone sequence-based method. The combined method should be useful in the rapid design of effective T cell-based vaccines.

Overcoming malignant cell-based mechanisms of resistance to immune checkpoint blockade antibodies.

Traditional cancer treatment approaches have focused on surgery, radiation therapy, and cytotoxic chemotherapy. However, with rare exceptions, metastatic cancers were considered to be incurable by traditional therapy. Over the past 20 years a fourth modality - immunotherapy - has emerged as a potentially curative approach for patients with advanced metastatic cancer. However, in many patients cancer "finds a way" to evade the anti-tumor effects of immunotherapy. Immunotherapy resistance mechanisms can be employed by both cancer cells and the non-cancer elements of tumor microenvironment. This review focuses on the resistance mechanisms that are specifically mediated by cancer cells. In order to extend the impact of immunotherapy to more patients and across all cancer types, and to inhibit the development of acquired resistance, the underlying biology driving immune escape needs to be better understood. Elucidating mechanisms of immune escape may shed light on new therapeutic targets, and lead to successful combination therapeutic strategies.

The role of fibroblast activation protein in health and malignancy.

Fibroblast activation protein-α (FAP) is a type-II transmembrane serine protease expressed almost exclusively to pathological conditions including fibrosis, arthritis, and cancer. Across most cancer types, elevated FAP is associated with worse clinical outcomes. Despite the clear association between FAP and disease severity, the biological reasons underlying these clinical observations remain unclear. Here we review basic FAP biology and FAP's role in non-oncologic and oncologic disease. We further explore how FAP may worsen clinical outcomes via its effects on extracellular matrix remodeling, intracellular signaling regulation, angiogenesis, epithelial-to-mesenchymal transition, and immunosuppression. Lastly, we discuss the potential to exploit FAP biology to improve clinical outcomes.

Status of Cancer Care at Network Sites of the Nation's Academic Cancer Centers.

BACKGROUND: Cancer care coordination across major academic medical centers and their networks is evolving rapidly, but the spectrum of organizational efforts has not been described. We conducted a mixed-methods survey of leading cancer centers and their networks to document care coordination and identify opportunities to improve geographically dispersed care. METHODS: A mixed-methods survey was sent to 91 cancer centers in the United States and Canada. We analyzed the number and locations of network sites; access to electronic medical records (EMRs); clinical research support and participation at networks; use of patient navigators, care paths, and quality measures; and physician workforce. Responses were collected via Qualtrics software between September 2017 and December 2018. RESULTS: Of the 69 responding cancer centers, 74% were NCI-designated. Eighty-seven percent of respondents were part of a matrix health system, and 13% were freestanding. Fifty-six reported having network sites. Forty-three respondents use navigators for disease-specific populations, and 24 use them for all patients. Thirty-five respondents use ≥1 types of care path. Fifty-seven percent of networks had complete, integrated access to their main center's EMRs. Thirty-nine respondents said the main center provides funding for clinical research at networks, with 22 reporting the main center provides all funding. Thirty-five said the main center provided pharmacy support at the networks, with 15 indicating the main center provides 100% pharmacy support. Certification program participation varied extensively across networks. CONCLUSIONS: The data show academic cancer centers have extensive involvement in network cancer care, often extending into rural communities. Coordinating care through improved clinical trial access and greater use of patient navigation, care paths, coordinated EMRs, and quality measures is likely to improve patient outcomes. Although it is premature to draw firm conclusions, the survey results are appropriate for mapping next steps and data queries.

CancerInSilico: An R/Bioconductor package for combining mathematical and statistical modeling to simulate time course bulk and single cell gene expression data in cancer.

Bioinformatics techniques to analyze time course bulk and single cell omics data are advancing. The absence of a known ground truth of the dynamics of molecular changes challenges benchmarking their performance on real data. Realistic simulated time-course datasets are essential to assess the performance of time course bioinformatics algorithms. We develop an R/Bioconductor package, CancerInSilico, to simulate bulk and single cell transcriptional data from a known ground truth obtained from mathematical models of cellular systems. This package contains a general R infrastructure for running cell-based models and simulating gene expression data based on the model states. We show how to use this package to simulate a gene expression data set and consequently benchmark analysis methods on this data set with a known ground truth. The package is freely available via Bioconductor: http://bioconductor.org/packages/CancerInSilico/.

Targeting Multiple Receptors to Increase Checkpoint Blockade Efficacy.

Immune checkpoint blockade therapy is a powerful treatment strategy for many cancer types. Many patients will have limited responses to monotherapy targeted to a single immune checkpoint. Both inhibitory and stimulatory immune checkpoints continue to be discovered. Additionally, many receptors previously identified to play a role in tumor formation and progression are being found to have immunomodulatory components. The success of immunotherapy depends on maximizing pro-anti-tumor immunity while minimizing immunosuppressive signaling. Combining immune checkpoint targeted approaches with each other or with other receptor targets is a promising schema for future therapeutic regimen designs.

A phase 2 study of the PARP inhibitor veliparib plus temozolomide in patients with heavily pretreated metastatic colorectal cancer.

BACKGROUND: Poly(adenosine diphosphate ribose) polymerase (PARP) inhibitors such as veliparib are potent sensitizing agents and have been safely combined with DNA-damaging agents such as temozolomide. The sensitizing effects of PARP inhibitors are magnified when cells harbor DNA repair defects. METHODS: A single-arm, open-label, phase 2 study was performed to investigate the disease control rate (DCR) after 2 cycles of veliparib plus temozolomide in patients with metastatic colorectal cancer (mCRC) refractory to all standard therapies. Fifty patients received temozolomide (150 mg/m2 /d) on days 1 to 5 and veliparib (40 mg twice daily) on days 1 to 7 of each 28-day cycle. Another 5 patients with mismatch repair-deficient (dMMR) tumors were also enrolled. Twenty additional patients were then treated with temozolomide at 200 mg/m2 /d. Archived tumor specimens were used for immunohistochemistry to assess mismatch repair, phosphatase and tensin homolog deleted on chromosome 10 (PTEN), and O(6)-methylguanine-DNA methyltransferase (MGMT) protein expression levels. RESULTS: The combination was well tolerated, although some patients required dose reductions for myelosuppression. The primary endpoint was successfully met with a DCR of 24% and 2 confirmed partial responses. The median progression-free survival was 1.8 months, and the median overall survival was 6.6 months. PTEN protein expression and MGMT protein expression were not predictors of DCR. There was also a suggestion of worse outcomes for patients with dMMR tumors. CONCLUSIONS: In this heavily pretreated mCRC population, a combination of veliparib and temozolomide was well tolerated with temozolomide doses up to 200 mg/m2 /d, and it was clinically active. PARP inhibitor-based therapy merits further exploration in patients with mCRC. Cancer 2018;124:2337-46. © 2018 American Cancer Society.

Cholecystokinin receptor antagonist alters pancreatic cancer microenvironment and increases efficacy of immune checkpoint antibody therapy in mice.

Advanced pancreatic ductal adenocarcinoma (PDAC) has typically been resistant to chemotherapy and immunotherapy; therefore, novel strategies are needed to enhance therapeutic response. Cholecystokinin (CCK) has been shown to stimulate growth of pancreatic cancer. CCK receptors (CCKRs) are present on pancreatic cancer cells, fibroblasts, and lymphocytes. We hypothesized that CCKR blockade would improve response to immune checkpoint antibodies by promoting influx of tumor-infiltrating lymphocytes (TILs) and reducing fibrosis. We examined the effects of CCKR antagonists or immune checkpoint blockade antibodies alone or in combination in murine models of PDAC. Monotherapy with CCKR blockade significantly decreased tumor size and metastases in SCID mice with orthotopic PDAC, and in C57BL/6 mice, it reduced fibrosis and induced the influx of TILs. Immune-competent mice bearing syngeneic pancreatic cancer (Panc02 and mT3-2D) that were treated with the combination of CCK receptor antagonists and immune checkpoint blockade antibodies survived significantly longer with smaller tumors. Tumor immunohistochemical staining and flow cytometry demonstrated that the tumors of mice treated with the combination regimen had a significant reduction in Foxp3+ T-regulatory cells and an increase in CD4+ and CD8+ lymphocytes. Masson's trichrome stain analysis revealed 50% less fibrosis in the tumors of mice treated with CCKR antagonist compared to controls and compared to checkpoint antibody therapy. CCKR antagonists given with immune checkpoint antibody therapy represent a novel approach for improving survival of PDAC. The mechanism by which this combination therapy improves the survival of PDAC may be related to the decreased fibrosis and immune cells of the tumor microenvironment.

Protein network construction using reverse phase protein array data.

In this paper, we introduce a novel computational method for constructing protein networks based on reverse phase protein array (RPPA) data to identify complex patterns in protein signaling. The method is applied to phosphoproteomic profiles of basal expression and activation/phosphorylation of 76 key signaling proteins in three breast cancer cell lines (MCF7, LCC1, and LCC9). Temporal RPPA data are acquired at 48h, 96h, and 144h after knocking down four genes in separate experiments. These genes are selected from a previous study as important determinants for breast cancer survival. Interaction networks are constructed by analyzing the expression levels of protein pairs using a multivariate analysis of variance model. A new scoring criterion is introduced to determine relevant protein pairs. Through a network topology based analysis, we search for wiring patterns to identify key proteins that are associated with significant changes in expression levels across various experimental conditions.

An unbiased in vivo functional genomics screening approach in mice identifies novel tumor cell-based regulators of immune rejection.

The clinical successes of immune checkpoint therapies for cancer make it important to identify mechanisms of resistance to anti-tumor immune responses. Numerous resistance mechanisms have been identified employing studies of single genes or pathways, thereby parsing the tumor microenvironment complexity into tractable pieces. However, this limits the potential for novel gene discovery to in vivo immune attack. To address this challenge, we developed an unbiased in vivo genome-wide RNAi screening platform that leverages host immune selection in strains of immune-competent and immunodeficient mice to select for tumor cell-based genes that regulate in vivo sensitivity to immune attack. Utilizing this approach in a syngeneic triple-negative breast cancer (TNBC) model, we identified 709 genes that selectively regulated adaptive anti-tumor immunity and focused on five genes (CD47, TGFß1, Sgpl1, Tex9 and Pex14) with the greatest impact. We validated the mechanisms that underlie the immune-related effects of expression of these genes in different TNBC lines, as well as tandem synergistic interactions. Furthermore, we demonstrate the impact of different genes with previously unknown immune functions (Tex9 and Pex14) on anti-tumor immunity. Thus, this innovative approach has utility in identifying unknown tumor-specific regulators of immune recognition in multiple settings to reveal novel targets for future immunotherapies.

Predictive biomarkers for checkpoint inhibitor-based immunotherapy.

The clinical development of checkpoint inhibitor-based immunotherapy has ushered in an exciting era of anticancer therapy. Durable responses can be seen in patients with melanoma and other malignancies. Although monotherapy with PD-1 or PD-L1 agents are typically well tolerated, the risk of immune-related adverse events increases with combination regimens. The development of predictive biomarkers is needed to optimise patient benefit, minimise risk of toxicities, and guide combination approaches. The greatest focus has been on tumour-cell PD-L1 expression. Although PD-L1 positivity enriches for populations with clinical benefit, PD-L1 testing alone is insufficient for patient selection in most malignancies. In this Review, we discuss the status of PD-L1 testing and explore emerging data on new biomarker strategies with tumour-infiltrating lymphocytes, mutational burden, immune gene signatures, and multiplex immunohistochemistry. Future development of an effective predictive biomarker for checkpoint inhibitor-based immunotherapy will integrate multiple approaches for optimal characterisation of the immune tumour microenvironment.

G-DOC Plus - an integrative bioinformatics platform for precision medicine.

BACKGROUND: G-DOC Plus is a data integration and bioinformatics platform that uses cloud computing and other advanced computational tools to handle a variety of biomedical BIG DATA including gene expression arrays, NGS and medical images so that they can be analyzed in the full context of other omics and clinical information. RESULTS: G-DOC Plus currently holds data from over 10,000 patients selected from private and public resources including Gene Expression Omnibus (GEO), The Cancer Genome Atlas (TCGA) and the recently added datasets from REpository for Molecular BRAin Neoplasia DaTa (REMBRANDT), caArray studies of lung and colon cancer, ImmPort and the 1000 genomes data sets. The system allows researchers to explore clinical-omic data one sample at a time, as a cohort of samples; or at the level of population, providing the user with a comprehensive view of the data. G-DOC Plus tools have been leveraged in cancer and non-cancer studies for hypothesis generation and validation; biomarker discovery and multi-omics analysis, to explore somatic mutations and cancer MRI images; as well as for training and graduate education in bioinformatics, data and computational sciences. Several of these use cases are described in this paper to demonstrate its multifaceted usability. CONCLUSION: G-DOC Plus can be used to support a variety of user groups in multiple domains to enable hypothesis generation for precision medicine research. The long-term vision of G-DOC Plus is to extend this translational bioinformatics platform to stay current with emerging omics technologies and analysis methods to continue supporting novel hypothesis generation, analysis and validation for integrative biomedical research. By integrating several aspects of the disease and exposing various data elements, such as outpatient lab workup, pathology, radiology, current treatments, molecular signatures and expected outcomes over a web interface, G-DOC Plus will continue to strengthen precision medicine research. G-DOC Plus is available at: https://gdoc.georgetown.edu .

CD16xCD33 bispecific killer cell engager (BiKE) activates NK cells against primary MDS and MDSC CD33+ targets.

Myelodysplastic syndromes (MDS) are stem cell disorders that can progress to acute myeloid leukemia. Although hematopoietic cell transplantation can be curative, additional therapies are needed for a disease that disproportionally afflicts the elderly. We tested the ability of a CD16xCD33 BiKE to induce natural killer (NK) cell function in 67 MDS patients. Compared with age-matched normal controls, CD7(+) lymphocytes, NK cells, and CD16 expression were markedly decreased in MDS patients. Despite this, reverse antibody-dependent cell-mediated cytotoxicity assays showed potent degranulation and cytokine production when resting MDS-NK cells were triggered with an agonistic CD16 monoclonal antibody. Blood and marrow MDS-NK cells treated with bispecific killer cell engager (BiKE) significantly enhanced degranulation and tumor necrosis factor-α and interferon-γ production against HL-60 and endogenous CD33(+) MDS targets. MDS patients had a significantly increased proportion of immunosuppressive CD33(+) myeloid-derived suppressor cells (MDSCs) that negatively correlated with MDS lymphocyte populations and CD16 loss on NK cells. Treatment with the CD16xCD33 BiKE successfully reversed MDSC immunosuppression of NK cells and induced MDSC target cell lysis. Lastly, the BiKE induced optimal MDS-NK cell function irrespective of disease stage. Our data suggest that the CD16xCD33 BiKE functions against both CD33(+) MDS and MDSC targets and may be therapeutically beneficial for MDS patients.

Building better magic bullets--improving unconjugated monoclonal antibody therapy for cancer.

The potential of monoclonal antibodies to effectively treat cancer is beginning to be widely acknowledged. Advances in antibody engineering make it possible to produce various recombinant proteins that exploit the specificity of the antibody-combining site to manipulate tumour-related signalling, and to stimulate anti-tumour immune responses. Future advances in the field will rely on the improved identification of functional antibody targets to perturb cancer-relevant signalling, and by the improved selection of tumours that can be effectively treated. These advances will be complemented by the use of antibodies that induce clinically meaningful host-protective immune responses. But, can we afford this progress?

The clinical potential of targeted nanomedicine: delivering to cancer stem-like cells.

Cancer stem-like cells (CSCs) have been implicated in recurrence and treatment resistance in many human cancers. Thus, a CSC-targeted drug delivery strategy to eliminate CSCs is a desirable approach for developing a more effective anticancer therapy. We have developed a tumor-targeting nanodelivery platform (scL) for systemic administration of molecular medicines. Following treatment with the scL nanocomplex carrying various payloads, we have observed exquisite tumor-targeting specificity and significant antitumor response with long-term survival benefit in numerous animal models. We hypothesized that this observed efficacy might be attributed, at least in part, to elimination of CSCs. Here, we demonstrate the ability of scL to target both CSCs and differentiated nonstem cancer cells (non-CSCs) in various mouse models including subcutaneous and intracranial xenografts, syngeneic, and chemically induced tumors. We also show that systemic administration of scL carrying the wtp53 gene was able to induce tumor growth inhibition and the death of both CSCs and non-CSCs in subcutaneous colorectal cancer xenografts suggesting that this could be an effective method to reduce cancer recurrence and treatment resistance. This scL nanocomplex is being evaluated in a number of clinical trials where it has been shown to be well tolerated with indications of anticancer activity.

Cancer immunology for the clinician.

Cancer immunotherapy is coming of age. It has become abundantly clear that immunotherapy-which has been described as treating the body's immune system so the immune system can treat the cancer-can be routinely effective, and may indeed cure advanced cancers. Accordingly, it is important to understand the basic, clinically relevant principles of cancer immunology to better prepare for an increasingly exciting future. The host immune system is the only active enemy faced by a malignant cell population as it develops. So it is helpful to think of the battle between the cancer cell population and the developing cancer as a Darwinian crucible in which only the malignant cells most fit to thrive in the face of active immune system attack are able to survive in the reluctant host. All successful cancers thus have overcome the defenses mounted by host immune systems by actively thwarting the evolution of anticancer immunity. A malignant cell population that has "solved" the riddle of the host immune system need not employ all of these mechanisms in order to survive in a particular host. Hence, it may be that the dominant mechanism or mechanisms of immune evasion in fact represent potential Achilles' heels that can be therapeutically attacked to restore immune control of a cancer. To better understand where opportunities exist for immunotherapy, it is important to first consider how developing cancers overcome host immunity: by overwhelming, hiding from, subverting, shielding from, defending against, and outlasting the host immune response. Clearly, more than one of these mechanisms may be present in any particular patient, but it is likely that many cancer types employ dominant immune defense mechanisms. There can be no doubt that mobilizing the immune system to attack a cancer, remember the enemy, and continually target emerging clones represents an extremely promising path to cancer prevention and cure.

Identification of inhibitory scFv antibodies targeting fibroblast activation protein utilizing phage display functional screens.

Fibroblast activation protein (FAP) is a serine protease selectively expressed on tumor stromal fibroblasts in epithelial carcinomas and is important in cancer growth, adhesion, and metastases. As FAP enzymatic activity is a potent therapeutic target, we aimed to identify inhibitory antibodies. Using a competitive inhibition strategy, we used phage display techniques to identify 53 single-chain variable fragments (scFvs) after three rounds of panning against FAP. These scFvs were expressed and characterized for binding to FAP by surface plasmon resonance and flow cytometry. Functional assessment of these antibodies yielded an inhibitory scFv antibody, named E3, which could attenuate 35% of FAP cleavage of the fluorescent substrate Ala-Pro-7-amido-4-trifluoromethylcoumarin compared with nonfunctional scFv control. Furthermore, a mutant E3 scFv was identified by yeast affinity maturation. It had higher affinity (4-fold) and enhanced inhibitory effect on FAP enzyme activity (3-fold) than E3. The application of both inhibitory anti-FAP scFvs significantly affected the formation of 3-dimensional FAP-positive cell matrix, as demonstrated by reducing the fibronectin fiber orientation from 41.18% (negative antibody control) to 34.06% (E3) and 36.15% (mutant E3), respectively. Thus, we have identified and affinity-maturated the first scFv antibody capable of inhibiting FAP function. This scFv antibody has the potential to disrupt the role of FAP in tumor invasion and metastasis.