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PURPOSE To compare the predictive ability of mapping algorithms derived using cross-sectional and longitudinal data. METHODS This methodological assessment used data from a randomized controlled noninferiority trial of patients with low-risk prostate cancer, conducted by NRG Oncology (ClinicalTrials.gov identifier: NCT00331773 ), which examined the efficacy of conventional schedule versus hypofractionated radiation therapy (three-dimensional conformal external beam radiation therapy/IMRT). Health-related quality-of-life data were collected using the Expanded Prostate Cancer Index Composite (EPIC), and health utilities were obtained using EuroQOL-5D-3L (EQ-5D) at baseline and 6, 12, 24, and 60 months postintervention. Mapping algorithms were estimated using ordinary least squares regression models through five-fold cross-validation in baseline cross-sectional data and combined longitudinal data from all assessment periods; random effects specifications were also estimated in longitudinal data. Predictive performance was compared using root mean square error. Longitudinal predictive ability of models obtained using baseline data was examined using mean absolute differences in the reported and predicted utilities. RESULTS A total of 267 (and 199) patients in the estimation sample had complete EQ-5D and EPIC domain (and subdomain) data at baseline and at all subsequent assessments. Ordinary least squares models using combined data showed better predictive ability (lowest root mean square error) in the validation phase for algorithms with EPIC domain/subdomain data alone, whereas models using baseline data outperformed other specifications in the validation phase when patient covariates were also modeled. The mean absolute differences were lower for models using EPIC subdomain data compared with EPIC domain data and generally decreased as the time of assessment increased. CONCLUSION Overall, mapping algorithms obtained using baseline cross-sectional data showed the best predictive performance. Furthermore, these models demonstrated satisfactory longitudinal predictive ability.

Disrupted liver regeneration following hepatectomy represents an “undruggable” clinical challenge associated with poor patient outcomes. Yes-associated protein (YAP), a transcriptional coactivator that is repressed by the Hippo pathway, is instrumental in liver regeneration. We have previously described an alternative, Hippo-independent mechanism of YAP activation mediated by downregulation of protein tyrosine phosphatase nonreceptor type 11 (PTPN11, also known as SHP2) inhibition. Herein, we examined the effects of YAP activation with a selective SHP1/SHP2 inhibitor, NSC-87877, on liver regeneration in murine partial hepatectomy models. In our studies, NSC-87877 led to accelerated hepatocyte proliferation, improved liver regeneration, and decreased markers of injury following partial hepatectomy. The effects of NSC-87877 were lost in mice with hepatocyte-specific Yap/Taz deletion, and this demonstrated dependence on these molecules for the enhanced regenerative response. Furthermore, administration of NSC-87877 to murine models of nonalcoholic steatohepatitis was associated with improved survival and decreased markers of injury after hepatectomy. Evaluation of transcriptomic changes in the context of NSC-87877 administration revealed reduction in fibrotic signaling and augmentation of cell cycle signaling. Cytoprotective changes included downregulation of Nr4a1 , an apoptosis inducer. Collectively, the data suggest that SHP2 inhibition induces a pro-proliferative and cytoprotective enhancement of liver regeneration dependent on YAP.

As survival in breast cancer patients from newer therapies increases, concerns for chemotherapy-induced cardiotoxicity (CIC) have offset some of these benefits, manifesting as a decline in left ventricular ejection fraction (LVEF). Patients receiving anthracycline-based chemotherapy followed by trastuzumab are at risk for CIC. Previous research evaluating whether clinical biomarkers predict cardiotoxicity has been inconsistent. Recently, angiotensin II type 1 receptor (ATR1) and endothelin 1 (ET1) have been shown to play a role in breast tumor growth. We evaluated ATR1 and ET1 expression in breast cancer tissue and its association with CIC. A total of 33 paraffin-embedded breast tissue specimens from women with breast cancer treated with anthracycline-based chemotherapy and trastuzumab were analyzed by immunohistochemistry (IHC) and qRT-PCR. We found that ET1 expression was increased in patients with an LVEF ≤ 50% (p = 0.032) with a lower LVEF correlating with higher ET1 expression (r = 0.377, p = 0.031). In patients with a change in LVEF of greater than 10%, greater ET1 expression was noted compared to those without a change in LVEF (p = 0.017). Increased ET1 expression in breast tumor tissue is associated with reduced LVEF. Future studies need to examine whether ET1 may be a tissue biomarker that helps predict the risk of developing CIC in women with breast cancer.

Abstract Background: Cholangiocarcinoma is an aggressive malignancy with limited systemic therapeutics. We have recently identified LCK, a non-receptor tyrosine kinase, as a potential therapeutic target in select subtypes of cholangiocarcinoma. Proteomic profiling in other cancer types has proven beneficial in predicting response to systemic therapies. Herein, we present proteomic profiling of cholangiocarcinoma can predict sensitivity to a novel LCK inhibitor in patient derived xenograft models. Methods: Proteins from 28 unique cholangiocarcinoma patient derived xenograft models (PDX) were isolated, labeled with tandem mass tags (TMT) and then analyzed by liquid chromatography and mass spectroscopy (LC/MS). Phosphopeptides were separately evaluated both by Immobilized Metal Affinity Chromatography and pY-enrichment techniques. Following normalization, the global proteome, serine/threonine phosphoproteome, and tyrosine phosphoproteome were analyzed and a proteomic signature was created for each tumor. These signatures were compared to PDX models with known response profiles to NTRC0652-0, an LCK inhibitor (1 resistant and 1 sensitive). The top 200 differentially abundant proteins (log2FC 2.6) were then utilized to develop a sensitive and a resistant signature. Correlation indices were then calculated across the 28 PDX model library. An additional predicted resistant and predicted sensitive model was expanded. Tumor bearing mice were randomized based on tumor volume to either treatment with NTRC (30mg/kg PO daily), n=5, or vehicle, n=4, (10% Kolliphor, 10% DMSO, 80% Water, 2 mol equivalents HCl). Tumors were measured weekly with calipers and then weighed at the end of the study. Results: In the top 200 differentially abundant proteins that represented the proteomic signature there was over representation of proteins with decreased abundance. There were only 12 proteins with higher abundance in the sensitive model as compared to the resistant. Utilizing the signature developed from the global proteomics data, nine tumors were predicted to be sensitive while 17 were predicted to be resistant to NTRC. PDX115 is a an intrahepatic CCA PDX known to contain an IDH1 mutation and was predicted to be resistant by modeling. The model was resistant to single agent NTRC with no demonstrable effect on tumor growth in vivo. PDX175 is a distal CCA PDX and was predicted to be sensitive by modeling. In vivo growth was inhibited by NTRC as compared to vehicle treated mice following two weeks of treatment (983% vs 435%, p=0.03). Additionally, final tumor weight was significantly lower in NTRC treated mice (0.651 g vs 0.317 g, p=0.04). Conclusion: Cholangiocarcinoma proteomic signatures can be used to predict therapeutic response to a novel LCK inhibitor in preclinical models. Whether or not this could be applied to other treatment modalities in cholangiocarcinoma remains to be determined. Citation Format: Ryan Watkins, Roberto Alva-Ruiz, Caitlin Conboy, Dong-Gi Mun, Erik Jessen, Diep Vu, Jos de Man, Rogier Buijsman, Akhilesh Pandey, Mitesh Borad, Gregory Gores, Rory Smoot. Proteomic profiling of cholangiocarcinoma predicts response to a novel small molecule inhibitor in preclinical models [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 3094.

463 Background: Molecularly targeted therapy is gaining traction in cholangiocarcinoma with the first FDA approval of a targeted agent in 2020, the FGFR inhibitor pemigatinib. Yet response rates and efficacy are modest, and most cholangiocarcinoma patients still lack targeted therapy options. The hippo pathway effector, YAP, is an oncogene that is activated in the majority of cholangiocarcinoma, yet attempts to develop YAP inhibitors have not yet been clinically successful. Recently, we described a novel mechanism of YAP regulation, via tyrosine phosphorylation by the Src-family kinase LCK. Therefore we hypothesized that LCK inhibition by may be therapeutic in cholangiocarcinoma through suppression of YAP activity. Methods: NTRC 0652-0 is a novel tyrosine kinase inhibitor with specificity for LCK. In vitro pharmacodynamics were defined. In cholangiocarcinoma cells, specificity for LCK inhibition was determined by mass spectrometry-based unbiased analysis of the tyrosine phosphoproteome following treatment with NTRC 0652-0 or genetic deletion of LCK. YAP phosphorylation and cotranscriptional activity, cell viability, and apoptosis were assessed. A panel of eight cholangiocarcinoma patient derived organoids (PDO) were characterized and tested for sensitivity to NTRC 0652-0. Two patient-derived xenograft (PDX) models bearing FGFR2-rearrangements were utilized for in vivo assessment of pharmacokinetics, toxicity, and efficacy. Results: NTRC 0652-0 demonstrated selectivity for LCK inhibition in vitro and in cholangiocarcinoma cells. NTRC 0652-0 treatment led to YAP inhibition and apoptotic cell death in cholangiocarcinoma cell lines, associated with inhibition of MCL1 expression. PDOs demonstrated variable sensitivity to NTRC 0652-0, correlated with basal YAP tyrosine phosphorylation and drug-induced suppression of YAP co-transcriptional activity. FGFR2-altered cholangiocarcinoma was also identified as a subset with enrichment of YAP target genes. Cells from an FGFR2-altered PDX were sensitive to NTRC 0652-0 despite being primarily resistant to pemigatinib. In two PDX models of FGFR2-altered cholangiocarcinoma, daily oral treatment with NTRC 0652-0 inhibited YAP tyrosine phosphorylation, and resulted in stable plasma and tumor drug levels, acceptable toxicity, and significantly decreased tumor growth. Conclusions: A novel LCK inhibitor, NTRC 0652-0, reduced YAP signaling and demonstrated preclinical efficacy in multiple patient-derived models of cholangiocarcinoma. LCK is a novel therapeutic target in cholangiocarcinoma, and YAP activation or FGFR2-alteration are potential biomarkers for response.

AbstractPurposeTo reduce the likelihood of errors in organ delineations used for radiotherapy treatment planning, a knowledge‐based quality control (KBQC) system, which discriminates between valid and anomalous delineations is developed.Method and MaterialsThe KBQC is comprised of a group‐wise inference system and anomaly detection modules trained using historical priors from 296 locally advanced lung and prostate cancer patient computational tomographies (CTs). The inference system discriminates different organs based on shape, relational, and intensity features. For a given delineated image set, the inference system solves a combinatorial optimization problem that results in an organ group whose relational features follow those of the training set considering the posterior probabilities obtained from support vector machine (SVM), discriminant subspace ensemble (DSE), and artificial neural network (ANN) classifiers. These classifiers are trained on nonrelational features with a 10‐fold cross‐validation scheme. The anomaly detection module is a bank of ANN autoencoders, each corresponding with an organ, trained on nonrelational features. A heuristic rule detects anomalous organs that exceed predefined organ‐specific tolerances for the feature reconstruction error and the classifier's posterior probabilities. Independent data sets with anomalous delineations were used to test the overall performance of the KBQC system. The anomalous delineations were manually manipulated, computer‐generated, or propagated based on a transformation obtained by imperfect registrations. Both peer‐review–based scoring system and shape similarity coefficient (DSC) were used to label regions of interest (ROIs) as normal or anomalous in two independent test cohorts.ResultsThe accuracy of the classifiers was 99.8%, and the minimum per‐class F1‐scores were 0.99, 0.99, and 0.98 for SVM, DSE, and ANN, respectively. The group‐wise inference system reduced the miss‐classification likelihood for the test data set with anomalous delineations compared to each individual classifier and a fused classifier that used the average posterior probability of all classifiers. For 15 independent locally advanced lung patients, the system detected 79% of the anomalous ROIs. For 1320 auto‐segmented abdominopelvic organs, the anomaly detection system identified anomalous delineations, which also had low Dice similarity coefficient values with respect to manually delineated organs in the training data set.ConclusionThe KBQC system detected anomalous delineations with superior accuracy compared to classification methods that judge only based on posterior probabilities.

INTRODUCTION: Although an additional coronavirus disease 2019 vaccine dose for immunocompromised persons has been recommended in some countries, further data to guide vaccination strategies for patients with inflammatory bowel disease (IBD) are urgently needed. We sought to identify factors affecting initial humoral immune response to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccines among patients with IBD. METHODS: In this prospective cohort of SARS-CoV-2 immunized patients with IBD, we evaluated associations between participant age, sex, vaccine type, medication use, and the presence of a detectable antireceptor binding domain antibody and quantitative antibody level. RESULTS: In total, 1,909 participants were included (1,123, 692, and 94 received BNT162b2, mRNA-1273, and Ad26.COV2.S, respectively) of whom 96% achieved a positive antibody response. On multivariable analysis, factors associated with lack of antibody response were older age ( P = 0.043), BNT162b2 vs mRNA-1273 (odds ratio [OR] 2.1, 95% confidence interval [CI] 1.0–3.9), and combination therapy with anti-TNF and 6MP, azathioprine, or methotrexate (OR 4.2, 95% CI 2.4–7.3). The use of 5-aminosalicylate or sulfasalazine (OR 0.3, 95% CI 0.1–0.8) and ustekinumab (OR 0.2, 95% CI 0.05–0.8) was associated with decreased odds of lacking antibody response. DISCUSSION: Most patients with IBD mount an initial response to SARS-CoV-2 vaccination; however, older patients and those treated with anti-TNF and immunomodulator have blunted responses and may benefit the most from an additional vaccine dose. Patients treated with other classes of immunosuppressive medications have more robust initial immune responses to vaccination. These data should inform key decisions about patient selection for additional coronavirus disease 2019 vaccine doses in patients with IBD.