IQGAP1 is an oncogenic target in canine melanoma.

Canine oral mucosal melanoma is an aggressive malignant neoplasm and is characterized by local infiltration and a high metastatic potential. The disease progression is similar to that of human oral melanomas. Whereas human cutaneous melanoma is primarily driven by activating mutations in Braf (60%) or Nras (20%), human mucosal melanoma harbors these mutations much less frequently. This makes therapeutic targeting and research modeling of the oral form potentially different from that of the cutaneous form in humans. Similarly, research has found only rare Nras mutations and no activating Braf mutations in canine oral melanomas, but they are still reliant on MAPK signaling. IQGAP1 is a signaling scaffold that regulates oncogenic ERK1/2 MAPK signaling in human Ras- and Raf- driven cancers, including melanomas. To investigate whether IQGAP1 is a potential target in canine melanoma, we examined the expression and localization of IQGAP1 in primary canine melanomas and canine oral melanoma cell lines obtained from the University of California-Davis. Using CRISPR/Cas9 knockout of IQGAP1, we examined effects on downstream ERK1/2 pathway activity and assayed proliferation of cell lines when treated with a peptide that blocks the interaction between IQGAP1 and ERK1/2. We observed that canine IQGAP1 is expressed and localizes to a similar extent in both human and canine melanoma by qPCR, Western blot, and immunofluorescence. Deletion of IQGAP1 reduces MAPK pathway activation in cell lines, similar to effects seen in human BrafV600E cell lines. Additionally, we demonstrated reduced proliferation when these cells are treated with a blocking peptide in vitro

IQGAP1 is an oncogenic target in canine melanoma

<div><p>Canine oral mucosal melanoma is an aggressive malignant neoplasm and is characterized by local infiltration and a high metastatic potential. The disease progression is similar to that of human oral melanomas. Whereas human cutaneous melanoma is primarily driven by activating mutations in Braf (60%) or Nras (20%), human mucosal melanoma harbors these mutations much less frequently. This makes therapeutic targeting and research modeling of the oral form potentially different from that of the cutaneous form in humans. Similarly, research has found only rare Nras mutations and no activating Braf mutations in canine oral melanomas, but they are still reliant on MAPK signaling. IQGAP1 is a signaling scaffold that regulates oncogenic ERK1/2 MAPK signaling in human Ras- and Raf- driven cancers, including melanomas. To investigate whether IQGAP1 is a potential target in canine melanoma, we examined the expression and localization of IQGAP1 in primary canine melanomas and canine oral melanoma cell lines obtained from the University of California-Davis. Using CRISPR/Cas9 knockout of IQGAP1, we examined effects on downstream ERK1/2 pathway activity and assayed proliferation of cell lines when treated with a peptide that blocks the interaction between IQGAP1 and ERK1/2. We observed that canine IQGAP1 is expressed and localizes to a similar extent in both human and canine melanoma by qPCR, Western blot, and immunofluorescence. Deletion of IQGAP1 reduces MAPK pathway activation in cell lines, similar to effects seen in human Braf^V600E cell lines. Additionally, we demonstrated reduced proliferation when these cells are treated with a blocking peptide in vitro.</p></div

Canine melanoma lines are dependent on ERK1/2 similar to human Braf^V600E melanoma lines.

<p>(A) Immunoblot for human Braf^V600E melanoma cells (SK28) and two canine mucosal melanoma cell lines (CMM3, CMM5) treated with DMSO or GSK1120212 (Trametinib) for 8hrs. (B) Growth curves for two canine mucosal melanoma cell lines (CMM3, CMM5) and human Braf^V600E melanoma cells (SK-mel-28) treated with GSK1120212 ranging from 0.0001μM to 30μM. Values represent 3 biological replicates for CMM lines and 2 biological replicates from SK-Mel-28. (C) IC50 values from 4-day proliferation assays in cells as in (A).</p

Canine IQGAP1 is more highly conserved than mouse IQGAP1, particularly within the WW domain.

<p>(A) Schematic of function of WW peptide interruption of binding between IQGAP1 and ERK1/2. (B) IQGAP1 genomic locus with mouse and canine conservation tracks. Specific amino acid alignments of the WW domain [inset]. (C) Diagram of WW peptide mutations. (D) Immunoblot of primary human keratinocytes infected with either the full-length WW domain, one with two mutated central YY residues, a 5’ truncation missing 5AA and a 3’ truncation missing 3AA. (E) Histology and IQGAP1 immunohistochemistry from normal canine oral mucosa and primary canine mucosal melanoma. Scale bar = 100μm.</p

Canine Melanoma lines express IQGAP1 similar to human Braf^V600E melanoma lines.

<p>(A) Gel electrophoresis (top) from IQGAP1 RT-qPCR for five human Braf^V600E melanoma cell lines and and two canine mucosal melanoma cell lines (CMM3, CMM5). (B) IQGAP1 immunoblot from cell lines as for the qPCR. (C) Quantitation of human and canine IQGAP1 protein expression normalized to actin from western blot in (B). (D) Immunofluorescence for IQGAP1 in human Braf^V600E melanoma cells (Skmel28) and two canine mucosal melanoma cell lines (CMM3, CMM5). Scale bar = 50μm.</p

IQGAP1 deletion or interruption of IQGAP1-ERK1/2 interaction reduces ERK1/2 pathway signaling and proliferation in canine melanoma lines.

<p>(A) IQGAP1 Immunofluorescence in CMM5 melanoma cell line treated with either EV or IQGAP1 targeting sgRNA. Scale bar = 50μm. (B) Immunoblot for pERK1/2 and IQGAP1 in cells from (A). (C) Quantitation of human and canine pERK1/2 protein expression in IQGAP1 CRISPR canine melanoma cells normalized to ERK1/2 from western blot in (B). (D) Six-day proliferation assays in CMM3 or CMM5 with IQGAP1-targeting CRISPR, ** p-val <0.01. (E) Six-day proliferation assays in CMM5 (left) or CMM3 (right) cells treated with either Scr or WW peptide, ** p-val <0.01.</p

FasTag: Automatic text classification of unstructured medical narratives.

Unstructured clinical narratives are continuously being recorded as part of delivery of care in electronic health records, and dedicated tagging staff spend considerable effort manually assigning clinical codes for billing purposes. Despite these efforts, however, label availability and accuracy are both suboptimal. In this retrospective study, we aimed to automate the assignment of top-level International Classification of Diseases version 9 (ICD-9) codes to clinical records from human and veterinary data stores using minimal manual labor and feature curation. Automating top-level annotations could in turn enable rapid cohort identification, especially in a veterinary setting. To this end, we trained long short-term memory (LSTM) recurrent neural networks (RNNs) on 52,722 human and 89,591 veterinary records. We investigated the accuracy of both separate-domain and combined-domain models and probed model portability. We established relevant baseline classification performances by training Decision Trees (DT) and Random Forests (RF). We also investigated whether transforming the data using MetaMap Lite, a clinical natural language processing tool, affected classification performance. We showed that the LSTM-RNNs accurately classify veterinary and human text narratives into top-level categories with an average weighted macro F1 score of 0.74 and 0.68 respectively. In the "neoplasia" category, the model trained on veterinary data had a high validation accuracy in veterinary data and moderate accuracy in human data, with F1 scores of 0.91 and 0.70 respectively. Our LSTM method scored slightly higher than that of the DT and RF models. The use of LSTM-RNN models represents a scalable structure that could prove useful in cohort identification for comparative oncology studies. Digitization of human and veterinary health information will continue to be a reality, particularly in the form of unstructured narratives. Our approach is a step forward for these two domains to learn from and inform one another