A WNT mimetic with broad spectrum FZD-specificity decreases fibrosis and improves function in a pulmonary damage model.

BACKGROUND: Wnt/ß-catenin signaling is critical for lung development and AT2 stem cell maintenance in adults, but excessive pathway activation has been associated with pulmonary fibrosis, both in animal models and human diseases such as idiopathic pulmonary fibrosis (IPF). IPF is a detrimental interstitial lung disease, and although two approved drugs limit functional decline, transplantation is the only treatment that extends survival, highlighting the need for regenerative therapies. METHODS: Using our antibody-based platform of Wnt/ß-catenin modulators, we investigated the ability of a pathway antagonist and pathway activators to reduce pulmonary fibrosis in the acute bleomycin model, and we tested the ability of a WNT mimetic to affect alveolar organoid cultures. RESULTS: A WNT mimetic agonist with broad FZD-binding specificity (FZD1,2,5,7,8) potently expanded alveolar organoids. Upon therapeutic dosing, a broad FZD-binding specific Wnt mimetic decreased pulmonary inflammation and fibrosis and increased lung function in the bleomycin model, and it impacted multiple lung cell types in vivo. CONCLUSIONS: Our results highlight the unexpected capacity of a WNT mimetic to effect tissue repair after lung damage and support the continued development of Wnt/ß-catenin pathway modulation for the treatment of pulmonary fibrosis.

Fibroblast growth factor receptor 4 (FGFR4) deficiency improves insulin resistance and glucose metabolism under diet-induced obesity conditions.

The role of fibroblast growth factor receptor 4 (FGFR4) in regulating bile acid synthesis has been well defined; however, its reported role on glucose and energy metabolism remains unresolved. Here, we show that FGFR4 deficiency in mice leads to improvement in glucose metabolism, insulin sensitivity, and reduction in body weight under high fat conditions. Mechanism of action studies in FGFR4-deficient mice suggest that the effects are mediated in part by increased plasma levels of adiponectin and the endocrine FGF factors FGF21 and FGF15, the latter of which increase in response to an elevated bile acid pool. Direct actions of increased bile acids on bile acid receptors, and other potential indirect mechanisms, may also contribute to the observed metabolic changes. The results described herein suggest that FGFR4 antagonists alone, or in combination with other agents, could serve as a novel treatment for diabetes.

Effects of Fc glycosylation on the activity of WNT mimetic agonistic antibodies.

Monoclonal antibodies have been explored in a broad range of applications including receptor agonism. Given the importance of receptor conformation in signaling, the agonistic activity of antibodies that engage these receptors are influenced by many parameters. Tetravalent bispecific antibodies that target the frizzled and lipoprotein receptor-related protein receptors and subsequently activate WNT ("Wingless-related integration site" or "Wingless and Int-1" or "Wingless-Int") signaling have been constructed. Because WNT activation stimulates stem cell proliferation and tissue regeneration, immune effector functions should be eliminated from therapeutic antibodies targeting this pathway. Here, we report an unexpected effect of Fc glycosylation on the agonistic activity of WNT mimetic antibodies. Our findings underscore the importance of antibody format, geometry and epitope in agonistic antibody design, and highlight the need to establish appropriate early discovery screening strategies to identify hits for further optimization.

Targeted protein degradation systems to enhance Wnt signaling.

Molecules that facilitate targeted protein degradation (TPD) offer great promise as novel therapeutics. The human hepatic lectin asialoglycoprotein receptor (ASGR) is selectively expressed on hepatocytes. We have previously engineered an anti-ASGR1 antibody-mutant RSPO2 (RSPO2RA) fusion protein (called SWEETS) to drive tissue-specific degradation of ZNRF3/RNF43 E3 ubiquitin ligases, which achieved hepatocyte-specific enhanced Wnt signaling, proliferation, and restored liver function in mouse models, and an antibody-RSPO2RA fusion molecule is currently in human clinical trials. In the current study, we identified two new ASGR1- and ASGR1/2-specific antibodies, 8M24 and 8G8. High-resolution crystal structures of ASGR1:8M24 and ASGR2:8G8 complexes revealed that these antibodies bind to distinct epitopes on opposing sides of ASGR, away from the substrate-binding site. Both antibodies enhanced Wnt activity when assembled as SWEETS molecules with RSPO2RA through specific effects sequestering E3 ligases. In addition, 8M24-RSPO2RA and 8G8-RSPO2RA efficiently downregulate ASGR1 through TPD mechanisms. These results demonstrate the possibility of combining different therapeutic effects and degradation mechanisms in a single molecule.

Novel Frizzled-specific antibody-based Wnt mimetics and Wnt superagonists selectively activate WNT/ß-catenin signaling in target tissues.

WNTs are essential factors for stem cell biology, embryonic development, and for maintaining homeostasis and tissue repair in adults. Difficulties in purifying WNTs and their lack of receptor selectivity have hampered research and regenerative medicine development. While breakthroughs in WNT mimetic development have overcome some of these difficulties, the tools developed so far are incomplete and mimetics alone are often not sufficient. Here, we developed a complete set of WNT mimetic molecules that cover all WNT/ß-catenin-activating Frizzleds (FZDs). We show that FZD1,2,7 stimulate salivary gland expansion in vivo and salivary gland organoid expansion. We further describe the discovery of a novel WNT-modulating platform that combines WNT and RSPO mimetics' effects into one molecule. This set of molecules supports better organoid expansion in various tissues. These WNT-activating platforms can be broadly applied to organoids, pluripotent stem cells, and in vivo research, and serve as bases for future therapeutic development.

A pathology order interface based on the transmission of texts obtained from pathology requisitions and just-in-time construction of HL7 messages.

Background: A pathology order interface using Health Level 7 standards (HL7) generally has an HL7 client program that gathers information from the clinical electronic medical record system, packages the information in the form of HL7 message, and sends the message using secure communication protocols to an HL7 interface engine located on the pathology side. We describe an alternative approach that transmits the texts obtained from requisitions, with subsequent just-in-time construction of HL7 messages. Materials and methods: The order interface is between a dermatology clinic EMR and pathology information system. A text acquisition and processing program runs in the background in desktop computers in dermatology clinic so that a copy of pathology requisition text is obtained each time when the clinic prints a pathology requisition. Discrete elements of the data are extracted from this text, prepended to the text and saved on a shared drive within the dermatology office intranet. This text file is then transferred to pathology intranet using secure File Transfer Protocol (sFTP). Once received, an HL7 message construction program extracts the discrete data elements to construct an HL7 message. The HL7 message is then forwarded to an HL7 interface engine and entered into the pathology information system as an order. Results: Using an actual case as an example, the content and format of the information flowing through different steps of the interface are demonstrated. Conclusions: The construction of such an interface does not involve the clinic EMR vendor, thus avoiding its associated cost and potential delay. This interface has advantages over our other order interfaces constructed using the conventional approach in that it does not require a change of order process and it avoids duplicate orders.

SZN-413, a FZD4 Agonist, as a Potential Novel Therapeutic for the Treatment of Diabetic Retinopathy.

Purpose: There remains a high unmet need for therapies with new mechanisms of action to achieve reperfusion of ischemic retina in diabetic retinopathy. We examined whether a novel frizzled class receptor 4 (FZD4) agonist could promote regeneration of functional blood vessels in animal models of retinopathy. Methods: We developed a novel Norrin mimetic (SZN-413-p) targeting FZD4 and low-density lipoprotein receptor-related protein 5 (LRP5) and examined its effect on retinal and brain endothelial cells in vitro. SZN-413-p was subsequently humanized, resulting in the therapeutic candidate SZN-413, and was examined in animal models of retinopathy. In an oxygen-induced retinopathy mouse model, avascular and neovascularization areas were measured. Furthermore, in a vascular endothelial growth factor (VEGF)-induced retinal vascular leakage rabbit model, the impact on vascular leakage by SZN-413 was examined by measuring fluorescein leakage. Results: SZN-413-p induced Wnt/ß-catenin signaling and upregulated blood-brain barrier/blood-retina barrier gene expressions in endothelial cells. In the oxygen-induced retinopathy mouse model, SZN-413-p and SZN-413 significantly reduced the neovascularization area size (P < 0.001) to a level comparable to, or better than the positive control aflibercept. Both agonists also showed a reduction in avascular area size compared to vehicle (P < 0.001) and aflibercept groups (P < 0.05 and P < 0.01 for SZN-413-p and SZN-413, respectively). In the VEGF-induced retinal vascular leakage rabbit model, SZN-413 reduced retinal vascular leakage by ∼80%, compared to the vehicle-treated group (P < 0.01). Conclusions: Reduction of neovascular tufts and avascular areas and of VEGF-driven retinal vascular leakage suggests that SZN-413 can simultaneously address retinal non-perfusion and vascular leakage. Translational Relevance: FZD4 signaling modulation by SZN-413 is a novel mechanism of action that can offer a new therapeutic strategy for diabetic retinopathy.

Using Timestamp Data to Assess the Impact of Voice Recognition on the Efficiency of Grossing Biopsies.

CONTEXT.­: Studies on the adoption of voice recognition in health care have mostly focused on turnaround time and error rate, with less attention paid to the impact on the efficiency of the providers. OBJECTIVE.­: To study the impact of voice recognition on the efficiency of grossing biopsy specimens. DESIGN.­: Timestamps corresponding to barcode scanning for biopsy specimen bottles and cassettes were retrieved from the pathology information system database. The time elapsed between scanning a specimen bottle and the corresponding first cassette was the length of time spent on the gross processing of that specimen and is designated as the specimen time. For the first specimen of a case, the specimen time additionally included the time spent on dictating the clinical information. Therefore, the specimen times were divided into the following 2 categories: first-specimen time and subsequent-specimen time. The impact of voice recognition on specimen times was studied using both univariate and multivariate analyses. RESULTS.­: Specimen complexity, prosector variability, length of clinical information text, and the number of biopsies the prosector grossed that day were the major determinants of specimen times. Adopting voice recognition had a negligible impact on specimen times. CONCLUSIONS.­: Adopting voice recognition in the gross room removes the need to hire transcriptionists without negatively impacting the efficiency of the prosectors, resulting in an overall cost saving. Using computer scripting to automatically enter clinical information (received through the electronic order interface) into report templates may potentially increase the grossing efficiency in the future.

Tissue-targeted R-spondin mimetics for liver regeneration.

R-spondin (RSPO) proteins amplify Wnt signaling and stimulate regeneration in a variety of tissues. To repair tissue in a tissue-specific manner, tissue-targeted RSPO mimetic molecules are desired. Here, we mutated RSPO (RSPO2 F105R/F109A) to eliminate LGR binding while preserving ZNRF3/RNF43 binding and targeted the mutated RSPO to a liver specific receptor, ASGR1. The resulting bi-specific molecule (αASGR1-RSPO2-RA) enhanced Wnt signaling effectively in vitro, and its activity was limited to ASGR1 expressing cells. Systemic administration of αASGR1-RSPO2-RA in mice specifically upregulated Wnt target genes and stimulated cell proliferation in liver but not intestine (which is more responsive to non-targeted RSPO2) in healthy mice, and improved liver function in diseased mice. These results not only suggest that a tissue-specific RSPO mimetic protein can stimulate regeneration in a cell-specific manner, but also provide a blueprint of how a tissue-specific molecule might be constructed for applications in a broader context.

Construction and Utilization of a Neural Network Model to Predict Current Procedural Terminology Codes from Pathology Report Texts.

BACKGROUND: At our department, each specimen was assigned a tentative current procedural terminology (CPT) code at accessioning. The codes were subject to subsequent changes by pathologist assistants and pathologists. After the cases had been finalized, their CPT codes went through a final verification step by coding staff, with the aid of a keyword-based CPT code-checking web application. Greater than 97% of the initial assignments were correct. This article describes the construction of a CPT code-predicting neural network model and its incorporation into the CPT code-checking application. MATERIALS AND METHODS: R programming language was used. Pathology report texts and CPT codes for the cases finalized during January 1-November 30, 2018, were retrieved from the database. The order of the specimens was randomized before the data were partitioned into training and validation set. R Keras package was used for both model training and prediction. The chosen neural network had a three-layer architecture consisting of a word-embedding layer, a bidirectional long short-term memory (LSTM) layer, and a densely connected layer. It used concatenated header-diagnosis texts as the input. RESULTS: The model predicted CPT codes in both the validation data set and the test data set with an accuracy of 97.5% and 97.6%, respectively. Closer examination of the test data set (cases from December 1 to 27, 2018) revealed two interesting observations. First, among the specimens that had incorrect initial CPT code assignments, the model disagreed with the initial assignments in 73.6% (117/159) and agreed in 26.4% (42/159). Second, the model identified nine additional specimens with incorrect CPT codes that had evaded all steps of checking. CONCLUSIONS: A neural network model using report texts to predict CPT codes can achieve high accuracy in prediction and moderate sensitivity in error detection. Neural networks may play increasing roles in CPT coding in surgical pathology.

Computational Algorithms that Effectively Reduce Report Defects in Surgical Pathology.

BACKGROUND: Pathology report defects refer to errors in the pathology reports, such as transcription/voice recognition errors and incorrect nondiagnostic information. Examples of the latter include incorrect gender, incorrect submitting physician, incorrect description of tissue blocks submitted, report formatting issues, and so on. Over the past 5 years, we have implemented computational algorithms to identify and correct these report defects. MATERIALS AND METHODS: Report texts, tissue blocks submitted, and other relevant information are retrieved from the pathology information system database. Two complementary algorithms are used to identify the voice recognition errors by parsing the gross description texts to either (i) identify previously encountered error patterns or (ii) flag sentences containing previously-unused two-word sequences (bigrams). A third algorithm based on identifying conflicting information from two different sources is used to identify tissue block designation errors in the gross description; the information on actual block submission is compared with the block designation information parsed from the gross description text. RESULTS: The computational algorithms identify voice recognition errors in approximately 8%-10% of the cases and block designation errors in approximately 0.5%-1% of all the cases. CONCLUSIONS: The algorithms described here have been effective in reducing pathology report defects. In addition to detecting voice recognition and block designation errors, these algorithms have also be used to detect other report defects, such as wrong gender, wrong provider, special stains or immunostains performed but not reported, and so on.

Structure-guided Discovery of Dual-recognition Chemibodies.

Small molecules and antibodies each have advantages and limitations as therapeutics. Here, we present for the first time to our knowledge, the structure-guided design of "chemibodies" as small molecule-antibody hybrids that offer dual recognition of a single target by both a small molecule and an antibody, using DPP-IV enzyme as a proof of concept study. Biochemical characterization demonstrates that the chemibodies present superior DPP-IV inhibition compared to either small molecule or antibody component alone. We validated our design by successfully solving a co-crystal structure of a chemibody in complex with DPP-IV, confirming specific binding of the small molecule portion at the interior catalytic site and the Fab portion at the protein surface. The discovery of chemibodies presents considerable potential for novel therapeutics that harness the power of both small molecule and antibody modalities to achieve superior specificity, potency, and pharmacokinetic properties.

Pathology report data extraction from relational database using R, with extraction from reports on melanoma of skin as an example.

BACKGROUND: Different methods have been described for data extraction from pathology reports with varying degrees of success. Here a technique for directly extracting data from relational database is described. METHODS: Our department uses synoptic reports modified from College of American Pathologists (CAP) Cancer Protocol Templates to report most of our cancer diagnoses. Choosing the melanoma of skin synoptic report as an example, R scripting language extended with RODBC package was used to query the pathology information system database. Reports containing melanoma of skin synoptic report in the past 4 and a half years were retrieved and individual data elements were extracted. Using the retrieved list of the cases, the database was queried a second time to retrieve/extract the lymph node staging information in the subsequent reports from the same patients. RESULTS: 426 synoptic reports corresponding to unique lesions of melanoma of skin were retrieved, and data elements of interest were extracted into an R data frame. The distribution of Breslow depth of melanomas grouped by year is used as an example of intra-report data extraction and analysis. When the new pN staging information was present in the subsequent reports, 82% (77/94) was precisely retrieved (pN0, pN1, pN2 and pN3). Additional 15% (14/94) was retrieved with certain ambiguity (positive or knowing there was an update). The specificity was 100% for both. The relationship between Breslow depth and lymph node status was graphed as an example of lesion-specific multi-report data extraction and analysis. CONCLUSIONS: R extended with RODBC package is a simple and versatile approach well-suited for the above tasks. The success or failure of the retrieval and extraction depended largely on whether the reports were formatted and whether the contents of the elements were consistently phrased. This approach can be easily modified and adopted for other pathology information systems that use relational database for data management.

Artificial Intelligence for Pathologists Is Not Near--It Is Here: Description of a Prototype That Can Transform How We Practice Pathology Tomorrow.

CONTEXT: Pathologists' daily tasks consist of both the professional interpretation of slides and the secretarial tasks of translating these interpretations into final pathology reports, the latter of which is a time-consuming endeavor for most pathologists. OBJECTIVE: To describe an artificial intelligence that performs secretarial tasks, designated as Secretary-Mimicking Artificial Intelligence (SMILE). DESIGN: The underling implementation of SMILE is a collection of computer programs that work in concert to "listen to" the voice commands and to "watch for" the changes of windows caused by slide bar code scanning; SMILE responds to these inputs by acting upon PowerPath Client windows (Sunquest Information Systems, Tucson, Arizona) and its Microsoft Word (Microsoft, Redmond, Washington) Add-In window, eventuating in the reports being typed and finalized. Secretary-Mimicking Artificial Intelligence also communicates relevant information to the pathologist via the computer speakers and message box on the screen. RESULTS: Secretary-Mimicking Artificial Intelligence performs many secretarial tasks intelligently and semiautonomously, with rapidity and consistency, thus enabling pathologists to focus on slide interpretation, which results in a marked increase in productivity, decrease in errors, and reduction of stress in daily practice. Secretary-Mimicking Artificial Intelligence undergoes encounter-based learning continually, resulting in a continuous improvement in its knowledge-based intelligence. CONCLUSIONS: Artificial intelligence for pathologists is both feasible and powerful. The future widespread use of artificial intelligence in our profession is certainly going to transform how we practice pathology.

Proliferating pilar tumors: a clinicopathologic study of 76 cases with a proposal for definition of benign and malignant variants.

We studied proliferating pilar tumors (PPTs) to establish histologic criteria that could predict behavior. We reviewed all cases in our consultation files (1989-2000) and evaluated 76 cases with meaningful follow-up information. Histologic examination involved attention to tumor silhouette, degree of nuclear atypia, mitotic activity, necrosis, and perineurial or angiolymphatic invasion. Tumors were stratified as follows: group 1 PPTs, circumscribed silhouettes with "pushing " margins, modest nuclear atypia, and an absence of pathologic mitoses, necrosis, and invasion of nerves or vessels; group 2 PPTs, similar to group 1 but manifested irregular, locally invasive silhouettes with involvement of the deep dermis and subcutis; group 3, invasive growth patterns, marked nuclear atypia, pathologic mitotic forms, and geographic necrosis, with or without involvement of nerves or vascular structures. Recurrence occurred in none of 48 group 1 PPTs; 3 (15%) of 20 group 2 PPTs had local regrowth; 4 (50%) of 8 of group 3 PPTs recurred and/or metastasized to regional lymph nodes. The differences between groups 1 and 3 and between 2 and 3 were statistically significant (P = .0002, P < .05, respectively). It seems justifiable to regard group 1 PPTs as benign, group 2 as having potential for locally aggressive growth, and group 3 also as having metastatic potential. The latter 2 categories might be equated with low and high grades of malignancy among PPTs of the skin.

Challenges and opportunities in the adoption of College of American Pathologists checklists in electronic format: perspectives and experience of Reporting Pathology Protocols Project (RPP2) participant laboratories.

CONTEXT: The site-specific cancer checklists developed by the College of American Pathologists have the potential to improve the quality of data derived from pathology reports and incorporated into cancer registry databases and are now mandated report elements by various accrediting bodies. A pilot project, funded by the Centers for Disease Control National Project for Cancer Registries in 2004, brought 4 pathology services in 3 states, with differing baseline implementations of the checklists, the opportunity to partner with their state National Project for Cancer Registry and their laboratory information system vendors to evaluate the feasibility of using electronically encoded College of American Pathologists cancer checklists for melanoma and tumors of the breast and prostate. OBJECTIVES: To identify existing and potential barriers to adoption of electronically encoded checklists and to also identify unique benefits not associated with text-only uses of the checklists. DESIGN: Participants mapped an implementation process from their current state to an electronic checklist-capable state. For a sample of cases of melanoma, prostate, and breast cancers, the checklist elements were captured and transmitted to the registry using Health Level 7 (version 2.3.1). Process assessments with adoption of electronic checklists were conducted to assess pathologist effect and other potential barriers. An evaluation of the utility and usefulness of electronic checklists was performed after the project. RESULTS: All 4 laboratories successfully performed the capture of individual data elements from the College of American Pathologists checklist into a discrete format suitable for electronic transmission. The effect on pathologist performance and laboratory workflow was neutral. Points of resistance were identified in the checklists and in individual users. Specific challenges in individual laboratories varied according to the personnel and the baseline system in use. Clinical responses to implemented changes were generally positive. Analysis of the postproject experiences of the laboratories showed expansion of use and additional utility in some, but not all, laboratories. CONCLUSIONS: Pathology laboratory adoption of the College of American Pathologists cancer checklists in an electronic format suited to direct transmission to cancer registries poses business case, information technology, and human resource challenges. Laboratory information system vendor readiness to upgrade systems to facilitate this process helps to reduce some of these challenges. Personalities and preferences in practices may yet pose barriers to widespread adoption.

A chemical approach to the pharmaceutical optimization of an anti-HIV protein.

Chemical protein synthesis is important for dissecting the molecular basis of protein function. Here we advance its scope by demonstrating the significant improvement of the multifaceted pharmaceutical profile of small proteins exclusively via a chemical-based approach. The focus of this work centered on CCL-5 (RANTES) derivatives with potent anti-HIV activity. The overall chemical strategy involved a combination of coded and noncoded amino acid mutagenesis, peptide backbone engineering, and site-specific polymer attachment. The ability to alter specific protein residues, as well as precise control of the position and type of polymer attachment, allows for the exploration of specific molecular designs and resulted in novel CCL-5 analogues with significant differences in their respective biochemical and pharmaceutical properties. Using this approach, the complex-interplay of variables contributing to the noncovalent self-association (aggregation) state, CCR-5 specificity, in vivo elimination half-life, and anti-HIV activity of CCL-5-based protein analogues could be empirically evaluated via total chemical synthesis. This work has led to the identification of potent (sub-nanomolar) anti-HIV proteins with significantly improved pharmaceutical profiles, and illustrates the increasing value of protein chemical synthesis in contemporary therapeutic discovery. These antiviral molecules provide a novel mechanism of action for the development of a new generation of anti-HIV therapeutics which are still desperately needed.