Reliability and Variability of Ki-67 Digital Image Analysis Methods for Clinical Diagnostics in Breast Cancer.

Ki-67 is a nuclear protein associated with proliferation, and a strong potential biomarker in breast cancer, but is not routinely measured in current clinical management owing to a lack of standardization. Digital image analysis (DIA) is a promising technology that could allow high-throughput analysis and standardization. There is a dearth of data on the clinical reliability as well as intra- and interalgorithmic variability of different DIA methods. In this study, we scored and compared a set of breast cancer cases in which manually counted Ki-67 has already been demonstrated to have prognostic value (n = 278) to 5 DIA methods, namely Aperio ePathology (Lieca Biosystems), Definiens Tissue Studio (Definiens AG), Qupath, an unsupervised immunohistochemical color histogram algorithm, and a deep-learning pipeline piNET. The piNET system achieved high agreement (interclass correlation coefficient: 0.850) and correlation (R = 0.85) with the reference score. The Qupath algorithm exhibited a high degree of reproducibility among all rater instances (interclass correlation coefficient: 0.889). Although piNET performed well against absolute manual counts, none of the tested DIA methods classified common Ki-67 cutoffs with high agreement or reached the clinically relevant Cohen's κ of at least 0.8. The highest agreement achieved was a Cohen's κ statistic of 0.73 for cutoffs 20% and 25% by the piNET system. The main contributors to interalgorithmic variation and poor cutoff characterization included heterogeneous tumor biology, varying algorithm implementation, and setting assignments. It appears that image segmentation is the primary explanation for semiautomated intra-algorithmic variation, which involves significant manual intervention to correct. Automated pipelines, such as piNET, may be crucial in developing robust and reproducible unbiased DIA approaches to accurately quantify Ki-67 for clinical diagnosis in the future.

Probabilistic HIV recency classification-a logistic regression without labeled individual level training data.

Accurate HIV incidence estimation based on individual recent infection status (recent vs long-term infection) is important for monitoring the epidemic, targeting interventions to those at greatest risk of new infection, and evaluating existing programs of prevention and treatment. Starting from 2015, the Population-based HIV Impact Assessment (PHIA) individual-level surveys are implemented in the most-affected countries in sub-Saharan Africa. PHIA is a nationally-representative HIV-focused survey that combines household visits with key questions and cutting-edge technologies such as biomarker tests for HIV antibody and HIV viral load which offer the unique opportunity of distinguishing between recent infection and long-term infection, and providing relevant HIV information by age, gender, and location. In this article, we propose a semi-supervised logistic regression model for estimating individual level HIV recency status. It incorporates information from multiple data sources - the PHIA survey where the true HIV recency status is unknown, and the cohort studies provided in the literature where the relationship between HIV recency status and the covariates are presented in the form of a contingency table. It also utilizes the national level HIV incidence estimates from the epidemiology model. Applying the proposed model to Malawi PHIA data, we demonstrate that our approach is more accurate for the individual level estimation and more appropriate for estimating HIV recency rates at aggregated levels than the current practice - the binary classification tree (BCT).

Using factor analyses to estimate the number of female sex workers across Malawi from multiple regional sources.

PURPOSE: Human immunodeficiency virus (HIV) risks are heterogeneous in nature even in generalized epidemics. However, data are often missing for those at highest risk of HIV, including female sex workers. Statistical models may be used to address data gaps where direct, empiric estimates do not exist. METHODS: We proposed a new size estimation method that combines multiple data sources (the Malawi Biological and Behavioral Surveillance Survey, the Priorities for Local AIDS Control Efforts study, and the Malawi Demographic Household Survey). We used factor analysis to extract information from auxiliary variables and constructed a linear mixed effects model for predicting population size for all districts of Malawi. RESULTS: On average, the predicted proportion of female sex workers among women of reproductive age across all districts was about 0.58%. The estimated proportions seemed reasonable in comparing with a recent study Priorities for Local AIDS Control Efforts II (PLACE II). Compared with using a single data source, we observed increased precision and better geographic coverage. CONCLUSIONS: We illustrate how size estimates from different data sources may be combined for prediction. Applying this approach to other subpopulations in Malawi and to countries where size estimate data are lacking can ultimately inform national modeling processes and estimate the distribution of risks and priorities for HIV prevention and treatment programs.

Author Correction: Transcription phenotypes of pancreatic cancer are driven by genomic events during tumor evolution.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Transcription phenotypes of pancreatic cancer are driven by genomic events during tumor evolution.

Pancreatic adenocarcinoma presents as a spectrum of a highly aggressive disease in patients. The basis of this disease heterogeneity has proved difficult to resolve due to poor tumor cellularity and extensive genomic instability. To address this, a dataset of whole genomes and transcriptomes was generated from purified epithelium of primary and metastatic tumors. Transcriptome analysis demonstrated that molecular subtypes are a product of a gene expression continuum driven by a mixture of intratumoral subpopulations, which was confirmed by single-cell analysis. Integrated whole-genome analysis uncovered that molecular subtypes are linked to specific copy number aberrations in genes such as mutant KRAS and GATA6. By mapping tumor genetic histories, tetraploidization emerged as a key mutational process behind these events. Taken together, these data support the premise that the constellation of genomic aberrations in the tumor gives rise to the molecular subtype, and that disease heterogeneity is due to ongoing genomic instability during progression.

A Four-Chemokine Signature Is Associated with a T-cell-Inflamed Phenotype in Primary and Metastatic Pancreatic Cancer.

PURPOSE: The molecular drivers of antitumor immunity in pancreatic ductal adenocarcinoma (PDAC) are poorly understood, posing a major obstacle for the identification of patients potentially amenable for immune-checkpoint blockade or other novel strategies. Here, we explore the association of chemokine expression with effector T-cell infiltration in PDAC. EXPERIMENTAL DESIGN: Discovery cohorts comprised 113 primary resected PDAC and 107 PDAC liver metastases. Validation cohorts comprised 182 PDAC from The Cancer Genome Atlas and 92 PDACs from the Australian International Cancer Genome Consortium. We explored associations between immune cell counts by immunohistochemistry, chemokine expression, and transcriptional hallmarks of antitumor immunity by RNA sequencing (RNA-seq), and mutational burden by whole-genome sequencing. RESULTS: Among all known human chemokines, a coregulated set of four (CCL4, CCL5, CXCL9, and CXCL10) was strongly associated with CD8+ T-cell infiltration (P < 0.001). Expression of this "4-chemokine signature" positively correlated with transcriptional metrics of T-cell activation (ZAP70, ITK, and IL2RB), cytolytic activity (GZMA and PRF1), and immunosuppression (PDL1, PD1, CTLA4, TIM3, TIGIT, LAG3, FASLG, and IDO1). Furthermore, the 4-chemokine signature marked tumors with increased T-cell activation scores (MHC I presentation, T-cell/APC costimulation) and elevated expression of innate immune sensing pathways involved in T-cell priming (STING and NLRP3 inflammasome pathways, BATF3-driven dendritic cells). Importantly, expression of this 4-chemokine signature was consistently indicative of a T-cell-inflamed phenotype across primary PDAC and PDAC liver metastases. CONCLUSIONS: A conserved 4-chemokine signature marks resectable and metastatic PDAC tumors with an active antitumor phenotype. This could have implications for the appropriate selection of PDAC patients in immunotherapy trials.

9t18:1 and 11t18:1 activate the MAPK pathway to regulate the expression of PLA2 and cause inflammation in HUVECs.

trans fatty acids (TFAs) have been reported to promote vascular diseases mainly by promoting apoptosis and inflammation of vascular endothelial cells. However, it has been reported in recent years that elaidic acid (9t18:1) and vaccenic acid (11t18:1) may have different effects on vascular health. This study investigated the effects of 9t18:1 and 11t18:1 on human umbilical vein endothelial cell (HUVEC) function and the possible mechanism of inflammation by analyzing the changes in the phospholipid composition and the relationship between phospholipase A2 (PLA2) and MAPK pathway. Here we found that the effect of 11t18:1 on cell viability, membrane damage and cellular inflammation was significantly lower than that of 9t18:1 (p < 0.05). And 9t18:1 and 11t18:1 had different effects on phospholipid composition. Both 9t18:1 and 11t18:1 significantly increased the protein expression of PLA2. Moreover, the MAPK pathway regulated the expression of PLA2, inflammatory cytokines and cyclooxygenase-2 (COX-2) and the secretion of prostaglandin E2 (PGE2) in HUVECs induced by 9t18:1 and 11t18:1. In conclusion, 9t18:1 and 11t18:1 activated the MAPK pathway which regulated the expression of PLA2 to cause inflammation in HUVECs.

Comparison of HIV prevalence among antenatal clinic attendees estimated from routine testing and unlinked anonymous testing.

In 2015, WHO and UNAIDS released new guidance recommending that countries transition from conducting antenatal clinic (ANC) unlinked anonymous testing (ANC-UAT) for tracking HIV prevalence trends among pregnant women to using ANC routine testing (ANC-RT) data, which are more consistent and economic to collect. This transition could pose challenges for distinguishing whether changes in observed prevalence are due to a change in underlying population prevalence or due to a change in the testing approach. We compared the HIV prevalence measured from ANC-UAT and ANCRT in 15 countries that had both data sources in overlapping years. We used linear mixed-e effects model (LMM) to estimate the RT-to-UAT calibration parameter as well as other unobserved quantities. We summarized the results at different levels of aggregation (e.g., country, urban, rural, and province). Based on our analysis, the HIV prevalence measured by ANC-UAT and ANC-RT data are consistent in most countries. Therefore, if large discrepancy is observed between ANC-UAT and ANC-RT at the same location, we recommend that people should be cautious and investigate the reason. For countries that lack information to estimate the calibration parameter, we propose an informative prior distribution of mean 0 and standard deviation 0.2 for the RT-to-UAT calibration parameter.

Integration of Genomic and Transcriptional Features in Pancreatic Cancer Reveals Increased Cell Cycle Progression in Metastases.

We integrated clinical, genomic, and transcriptomic data from 224 primaries and 95 metastases from 289 patients to characterize progression of pancreatic ductal adenocarcinoma (PDAC). Driver gene alterations and mutational and expression-based signatures were preserved, with truncations, inversions, and translocations most conserved. Cell cycle progression (CCP) increased with sequential inactivation of tumor suppressors, yet remained higher in metastases, perhaps driven by cell cycle regulatory gene variants. Half of the cases were hypoxic by expression markers, overlapping with molecular subtypes. Paired tumor heterogeneity showed cancer cell migration by Halstedian progression. Multiple PDACs arising synchronously and metachronously in the same pancreas were actually intra-parenchymal metastases, not independent primary tumors. Established clinical co-variates dominated survival analyses, although CCP and hypoxia may inform clinical practice.

9c11tCLA modulates 11t18:1 and 9t18:1 induced inflammations differently in human umbilical vein endothelial cells.

Endothelial inflammation is recognized as the initial stage of a multistep process leading to coronary heart disease (CHD). Recently, the different effects of industrial trans fatty acids (elaidic acid, 9t18:1) and ruminant trans fatty acids (vaccenic acid, 11t18:1) on CHD have been reported in epidemiological and animal studies, however, the mechanism was not fully studied. Therefore, the objective of this study was to explore the underlying mechanism by which 9t18:1 and 11t18:1 affect human umbilical vein endothelial cells (HUVECs) inflammation. We found that 9c11t-CLA modulated the inflammation of HUVECs induced by 9t18:1 and 11t18:1. Fatty acid composition, pro-inflammatory factors, phosphorylation of MAPKs, and the TLR4 level in HUVECs altered by 11t18:1 induction, collectively suggest that the bio-conversion of 11t18:1 to 9c11tCLA might be the cause why 11t18:1 and 9t18:1 have distinct influences on endothelial injuries. It was concluded that it is biosynthesis of 9c11t CLA from11t18:1, and the modulation of TLR4-MAPK pathway by 9c11t CLA, which at least partially account for the slight effect of 11t18:1 on endothelial inflammation.

Genomics-Driven Precision Medicine for Advanced Pancreatic Cancer: Early Results from the COMPASS Trial.

Purpose: To perform real-time whole genome sequencing (WGS) and RNA sequencing (RNASeq) of advanced pancreatic ductal adenocarcinoma (PDAC) to identify predictive mutational and transcriptional features for better treatment selection.Experimental Design: Patients with advanced PDAC were prospectively recruited prior to first-line combination chemotherapy. Fresh tumor tissue was acquired by image-guided percutaneous core biopsy for WGS and RNASeq. Laser capture microdissection was performed for all cases. Primary endpoint was feasibility to report WGS results prior to first disease assessment CT scan at 8 weeks. The main secondary endpoint was discovery of patient subsets with predictive mutational and transcriptional signatures.Results: Sixty-three patients underwent a tumor biopsy between December 2015 and June 2017. WGS and RNASeq were successful in 62 (98%) and 60 (95%), respectively. Genomic results were reported at a median of 35 days (range, 19-52 days) from biopsy, meeting the primary feasibility endpoint. Objective responses to first-line chemotherapy were significantly better in patients with the classical PDAC RNA subtype compared with those with the basal-like subtype (P = 0.004). The best progression-free survival was observed in those with classical subtype treated with m-FOLFIRINOX. GATA6 expression in tumor measured by RNA in situ hybridization was found to be a robust surrogate biomarker for differentiating classical and basal-like PDAC subtypes. Potentially actionable genetic alterations were found in 30% of patients.Conclusions: Prospective genomic profiling of advanced PDAC is feasible, and our early data indicate that chemotherapy response differs among patients with different genomic/transcriptomic subtypes. Clin Cancer Res; 24(6); 1344-54. ©2017 AACR.

Statistical models for incorporating data from routine HIV testing of pregnant women at antenatal clinics into HIV/AIDS epidemic estimates.

OBJECTIVE: HIV prevalence data collected from routine HIV testing of pregnant women at antenatal clinics (ANC-RT) are potentially available from all facilities that offer testing services to pregnant women and can be used to improve estimates of national and subnational HIV prevalence trends. We develop methods to incorporate these new data source into the Joint United Nations Programme on AIDS Estimation and Projection Package in Spectrum 2017. METHODS: We develop a new statistical model for incorporating ANC-RT HIV prevalence data, aggregated either to the health facility level (site-level) or regionally (census-level), to estimate HIV prevalence alongside existing sources of HIV prevalence data from ANC unlinked anonymous testing (ANC-UAT) and household-based national population surveys. Synthetic data are generated to understand how the availability of ANC-RT data affects the accuracy of various parameter estimates. RESULTS: We estimate HIV prevalence and additional parameters using both ANC-RT and other existing data. Fitting HIV prevalence using synthetic data generally gives precise estimates of the underlying trend and other parameters. More years of ANC-RT data should improve prevalence estimates. More ANC-RT sites and continuation with existing ANC-UAT sites may improve the estimate of calibration between ANC-UAT and ANC-RT sites. CONCLUSION: We have proposed methods to incorporate ANC-RT data into Spectrum to obtain more precise estimates of prevalence and other measures of the epidemic. Many assumptions about the accuracy, consistency, and representativeness of ANC-RT prevalence underlie the use of these data for monitoring HIV epidemic trends and should be tested as more data become available from national ANC-RT programs.

A renewed model of pancreatic cancer evolution based on genomic rearrangement patterns.

Pancreatic cancer, a highly aggressive tumour type with uniformly poor prognosis, exemplifies the classically held view of stepwise cancer development. The current model of tumorigenesis, based on analyses of precursor lesions, termed pancreatic intraepithelial neoplasm (PanINs) lesions, makes two predictions: first, that pancreatic cancer develops through a particular sequence of genetic alterations (KRAS, followed by CDKN2A, then TP53 and SMAD4); and second, that the evolutionary trajectory of pancreatic cancer progression is gradual because each alteration is acquired independently. A shortcoming of this model is that clonally expanded precursor lesions do not always belong to the tumour lineage, indicating that the evolutionary trajectory of the tumour lineage and precursor lesions can be divergent. This prevailing model of tumorigenesis has contributed to the clinical notion that pancreatic cancer evolves slowly and presents at a late stage. However, the propensity for this disease to rapidly metastasize and the inability to improve patient outcomes, despite efforts aimed at early detection, suggest that pancreatic cancer progression is not gradual. Here, using newly developed informatics tools, we tracked changes in DNA copy number and their associated rearrangements in tumour-enriched genomes and found that pancreatic cancer tumorigenesis is neither gradual nor follows the accepted mutation order. Two-thirds of tumours harbour complex rearrangement patterns associated with mitotic errors, consistent with punctuated equilibrium as the principal evolutionary trajectory. In a subset of cases, the consequence of such errors is the simultaneous, rather than sequential, knockout of canonical preneoplastic genetic drivers that are likely to set-off invasive cancer growth. These findings challenge the current progression model of pancreatic cancer and provide insights into the mutational processes that give rise to these aggressive tumours.

Molecular target characterization and antimyeloma activity of the novel, insulin-like growth factor 1 receptor inhibitor, GTx-134.

PURPOSE: Therapeutic strategies that target insulin-like growth factor 1 receptor (IGF-1R) hold promise in a wide variety of cancers including multiple myeloma (MM). In this study, we describe GTx-134, a novel small-molecule inhibitor of IGF-1R and insulin receptor (IR) and characterized its antitumor activity in preclinical models of MM. EXPERIMENTAL DESIGN: The activity of GTx-134 as a single agent and in combination was tested in MM cell lines and primary patient samples. Downstream effector proteins and correlation with apoptosis was evaluated. Cytotoxcity in bone marrow stroma coculture experiments was assessed. Finally, the in vivo efficacy was evaluated in a human myeloma xenograft model. RESULTS: GTx-134 inhibited the growth of 10 of 14 myeloma cell lines (<5 µmol/L) and induced apoptosis. Sensitivity to GTx-134 correlated with IGF-1R signal inhibition. Expression of MDR-1 and CD45 were associated with resistance to GTx-134. Coculture with insulin-growth factor-1 (IGF-1) or adherence to bone marrow stroma conferred modest resistance, but did not overcome GTx-134-induced cytotoxicity. GTx-134 showed in vitro synergies when combined with dexamethasone or lenalidomide. Further, GTx-134 enhanced the activity of PD173074, a fibroblast growth factor receptor 3 (FGFR3) inhibitor, against t(4;14) myeloma cells. Therapeutic efficacy of GTx-134 was shown against primary cells and xenograft tumors. Although dysregulation of glucose homeostasis was observed in GTx-134-treated mice, impairment of glucose tolerance was modest. CONCLUSIONS: These studies support the potential therapeutic efficacy of GTx-134 in MM. Further, they provide a rationale for clinical application in combination with established antimyeloma treatments and novel targeted therapies.

Cyproheptadine displays preclinical activity in myeloma and leukemia.

D-cyclins are regulators of cell division that act in a complex with cyclin-dependent kinases to commit cells to a program of DNA replication. D-cyclins are overexpressed in many tumors, including multiple myeloma and leukemia, and contribute to disease progression and chemoresistance. To better understand the role and impact of D-cyclins in hematologic malignancies, we conducted a high throughput screen for inhibitors of the cyclin D2 promoter and identified the drug cyproheptadine. In myeloma and leukemia cells, cyproheptadine decreased expression of cyclins D1, D2, and D3 and arrested these cells in the G(0)/G(1) phase. After D-cyclin suppression, cyproheptadine induced apoptosis in myeloma and leukemia cell lines and primary patient samples preferentially over normal hematopoietic cells. In mouse models of myeloma and leukemia, cyproheptadine inhibited tumor growth without significant toxicity. Cyproheptadine-induced apoptosis was preceded by activation of the mitochondrial pathway of caspase activation and was independent of the drug's known activity as an H1 histamine and serotonin receptor antagonist. Thus, cyproheptadine represents a lead for a novel therapeutic agent for the treatment of malignancy. Because the drug is well tolerated and already approved in multiple countries for clinical use as an antihistamine and appetite stimulant, it could be moved directly into clinical trials for cancer.

[Role and significance of pelvic four-contrast defecography in the diagnosis of outlet obstructive constipation].

OBJECTIVE: To study the changes in pelvic floor morphology and relationships of the pelvic organs in patients with outlet obstructive constipation (OOC). METHODS: Fifty-nine OOC patients and 12 healthy volunteers were examined by simultaneous pelvic four-contrast defecography, including pelvicography, vaginal opacification, voiding cystography and defecography. The levels of perineum, peritoneum and bladder, and anorectal angle were measured and recorded. RESULTS: Among the 59 OOC patients, 46 cases of internal rectal prolapse (IRP), 29 cases of pelvic floor hernia, 7 cases of rectocele (RC), 7 cases of spastic pelvic floor syndrome (SPFS), 5 cases of descending perineum syndrome were diagnosed by pelvic four-contrast defecography. Six cystoceles and 10 uterine prolapses were also found by pelvic four-contrast defecography. Compared with healthy volunteers, OOC patients had significantly large anorectal angles during defecation (P<0.05), abnormality descending of perineum during rest and defecation (P<0.05, P<0.01), and a deep pouch of Douglas during defecation (P<0.01). OOC patients combined with urinary system symptoms had an abnormal descent of the bladder during rest and defecation (P<0.05, P<0.01). CONCLUSION: Pelvic four-contrast defecography is an effective method for the diagnosis of IRP, RC, pelvic floor hernia, peritoneocele, cystocele and uterine prolapse, and is helpful in the selection of proper surgical procedures for the treatment of OOC.

Multiple reduced-intensity conditioning regimens facilitate correction of Fabry mice after transplantation of transduced cells.

Hematopoietic cell transplantation can impact lysosomal storage disorders (LSDs) and will be enhanced by gene therapy. Transduced cells in LSDs often secrete the therapeutic hydrolase, which can be used by bystander cells. However, toxicity associated with myeloablative transplant preparative regimens limits many applications of this approach in gene therapy. We hypothesized that reduced-intensity (RI) conditioning regimens would allow stable engraftment of therapeutically transduced cells and allow correction of Fabry disease. We transplanted transduced cells into Fabry mice receiving eight different clinically relevant chemotherapy- and/or radiotherapy-based RI conditioning regimens generating modest and transient lymphoid/myeloid cell depletion. Two comprehensive transplantation Protocols were performed. Firstly, transplantation of 0.38 x 10(6) gene-modified stem/progenitor cells was nominally effective; none of the RI regimens led to stable alpha-galactosidase A (alpha-gal A) correction. Secondly, transduced cells were preselected for functional transgene expression and transplanted at a higher dose (0.72 x 10(6) cells). Each RI regimen yielded engraftment of functional transgene-positive cells through 180 days along with increased plasma alpha-gal A activity. Importantly, the RI regimens mediated broad organ enzyme correction and were not associated with immune responses against alpha-gal A. RI conditioning thus has an important role in gene therapy for LSDs; a variety of regimens can be effective in this context.

The Bcl-2 family protein inhibitor, ABT-737, has substantial antimyeloma activity and shows synergistic effect with dexamethasone and melphalan.

PURPOSE: The aim of this study is to investigate the antimyeloma activity of a novel Bcl-2 family inhibitor, ABT-737, in preclinical treatment of multiple myeloma. EXPERIMENTAL DESIGN: The antimyeloma activity of ABT-737 was evaluated in cultured myeloma cell lines and patient myeloma samples, and in a xenograft mouse myeloma model. Drug combination therapy using ABT-737 with other commonly used myeloma drugs was also investigated. RESULTS: MY5 and JJN3 cell lines exhibited the most sensitivity to ABT-737 with an EC(50) of 0.2 and 0.5 micromol/L, respectively, with increased cell apoptosis and elevated activated caspase-3. We identified two distinct groups of myeloma patient samples that were either sensitive or resistant to the drug. Four of 15 patient bone marrow samples (27%) were highly sensitive to ABT-737 at doses of 0.25 and 0.5 micromol/L, which eliminated 80% to 90% of myeloma cells as a result of cellular apoptosis 3 days after drug treatment. ABT-737 showed a synergistic effect when combined with dexamethasone or melphalan in inducing myeloma cell death. Furthermore, the dexamethasone-resistant MM1(Dex)R myeloma cell line was highly sensitive to 0.2 micromol/L ABT-737. As determined by colony assay, little or no detectable toxicity to patient hematologic progenitor cells was observed at 1 micromol/L ABT-737. ABT-737 dose dependently suppressed tumor growth in a xenograft MY5 mouse model. CONCLUSIONS: These studies show substantial antimyeloma activity of ABT-737 as a single agent or in combination with dexamethasone or melphalan and suggest a rationale for future clinical trials.

The inhibitory anti-FGFR3 antibody, PRO-001, is cytotoxic to t(4;14) multiple myeloma cells.

The association of fibroblast growth factor receptor 3 (FGFR3) expression with t(4;14) multiple myeloma (MM) and the demonstration of the transforming potential of this receptor tyrosine kinase (RTK) make it a particularly attractive target for drug development. We report here a novel and highly specific anti-FGFR3-neutralizing antibody (PRO-001). PRO-001 binds to FGFR3 expressed on transformed cells and inhibits FGFR3 autophosphorylation and downstream signaling. The antibody inhibited the growth of FGFR3-expressing FDCP cells (IC(50) of 0.5 microg/mL) but not that of cells expressing FGFR1 or FGFR2, and potently inhibited FGFR3-dependent solid tumor growth in a mouse xenograft model. Furthermore, PRO-001 inhibited the growth of the FGFR3-expressing, human myeloma cell line, UTMC2. Inhibition of viability was still observed when cells were cocultured with stroma or in the presence of IL-6 or IGF-1. PRO-001 did not inhibit constitutive activation of K650E, G384D, and Y373C FGFR3 in myeloma cell lines and failed to inhibit the growth of these cells. Most importantly, however, PRO-001 induced cytotoxic responses in primary t(4;14)(+) MM samples with an increase in apoptotic index of 20% to 80% as determined by annexin V staining. The data demonstrate that PRO-001 is a potent and specific inhibitor of FGFR3 and deserves further study for the treatment of FGFR3-expressing myeloma.