Abstract Sealed Wellbore Pressure Monitoring (SWPM) has been utilized across North and South America Basins with over 16,000 stages monitored as of June 2022. Since May 2020, the analysis procedure has been automated using a cloud-based software platform designed to ingest, process, and analyze high-frequency hydraulic fracturing data (Iriarte et al., 2021). A real time option of SWPM was also developed to aid in real time fracturing decisions (Ramirez et al., 2022). The latest development is the added capability of a fracture model that can automatically history match the volume to first responses (VFRs) determined from SWPM. This next level allows for the matching of the VFRs and the visualization of the resulting fracture geometries from a fully-coupled fracture propagation, reservoir, and geomechanics simulator. The simulator is capable of accounting for complex processes such as poroelastic stress changes from depletion, allowing for evaluation of complex interactions of fracture propagation and depletion. Insights gained from this process allows the operator to optimize their completion design faster and with fewer field trials. This paper’s focus is a case study of the DOE Eagle Ford refracturing project where a range of completion designs were trialed while monitoring offset SWPM and fiber optic strain. The resulting VFRs of the SWPM project were compared to the fiber data and then used to calibrate the fracture model. Fracture model calibration was first performed assuming that restimulation fractures propagated independently of the previously created fractures. The VFR of each stage design was calculated and summarized. The model is constructed with three stage designs primarily identified by cluster count: 7-clusters, 12-clusters, and 22-clusters. The VFR for the 7-cluster stage design was then used as an objective in an automated history matching algorithm employing the fracture model. The resulting best fit model was then evaluated on VFRs for the 12 and 22-cluster stage designs. The results demonstrate the model calibrated to the VFR of the 7-cluster stage design was able to predict VFRs in the far field for 12 and 22-cluster stage designs. Further, it is shown that including the original fractures in the model and allowing crossflow between the original and newly created fractures can match the rapid VFRs observed on a minority of stages. These same results were confirmed by the fiber data (not shared with modelers prior to calibration). Conclusions of the DOE project will show the optimum cluster spacing, cluster count and stage spacing as confirmed by the SWPM analysis and the fracture modeling.
<div>Abstract<p>FGFR inhibitors are approved for the treatment of advanced cholangiocarcinoma harboring FGFR2 fusions. However, the response rate is moderate, and resistance emerges rapidly due to acquired secondary FGFR2 mutations or due to other less-defined mechanisms. Here, we conducted high-throughput combination drug screens, biochemical analysis, and therapeutic studies using patient-derived models of FGFR2 fusion–positive cholangiocarcinoma to gain insight into these clinical profiles and uncover improved treatment strategies. We found that feedback activation of EGFR signaling limits FGFR inhibitor efficacy, restricting cell death induction in sensitive models and causing resistance in insensitive models lacking secondary FGFR2 mutations. Inhibition of wild-type EGFR potentiated responses to FGFR inhibitors in both contexts, durably suppressing MEK/ERK and mTOR signaling, increasing apoptosis, and causing marked tumor regressions <i>in vivo</i>. Our findings reveal EGFR-dependent adaptive signaling as an important mechanism limiting FGFR inhibitor efficacy and driving resistance and support clinical testing of FGFR/EGFR inhibitor therapy for FGFR2 fusion–positive cholangiocarcinoma.</p>Significance:<p>We demonstrate that feedback activation of EGFR signaling limits the effectiveness of FGFR inhibitor therapy and drives adaptive resistance in patient-derived models of FGFR2 fusion–positive cholangiocarcinoma. These studies support the potential of combination treatment with FGFR and EGFR inhibitors as an improved treatment for patients with FGFR2-driven cholangiocarcinoma.</p><p><i>This article is highlighted in the In This Issue feature, p. 1171</i></p></div>
Abstract FGFR inhibitors are approved for the treatment of advanced cholangiocarcinoma harboring FGFR2 fusions. However, the response rate is moderate, and resistance emerges rapidly due to acquired secondary FGFR2 mutations or due to other less-defined mechanisms. Here, we conducted high-throughput combination drug screens, biochemical analysis, and therapeutic studies using patient-derived models of FGFR2 fusion–positive cholangiocarcinoma to gain insight into these clinical profiles and uncover improved treatment strategies. We found that feedback activation of EGFR signaling limits FGFR inhibitor efficacy, restricting cell death induction in sensitive models and causing resistance in insensitive models lacking secondary FGFR2 mutations. Inhibition of wild-type EGFR potentiated responses to FGFR inhibitors in both contexts, durably suppressing MEK/ERK and mTOR signaling, increasing apoptosis, and causing marked tumor regressions in vivo. Our findings reveal EGFR-dependent adaptive signaling as an important mechanism limiting FGFR inhibitor efficacy and driving resistance and support clinical testing of FGFR/EGFR inhibitor therapy for FGFR2 fusion–positive cholangiocarcinoma. Significance: We demonstrate that feedback activation of EGFR signaling limits the effectiveness of FGFR inhibitor therapy and drives adaptive resistance in patient-derived models of FGFR2 fusion–positive cholangiocarcinoma. These studies support the potential of combination treatment with FGFR and EGFR inhibitors as an improved treatment for patients with FGFR2-driven cholangiocarcinoma. This article is highlighted in the In This Issue feature, p. 1171
Abstract Biliary tract cancers (BTCs) are a group of deadly malignancies encompassing intrahepatic and extrahepatic cholangiocarcinoma, gallbladder carcinoma, and ampullary carcinoma. Here, we present the integrative analysis of 63 BTC cell lines via multi-omics clustering and genome- scale CRISPR screens, providing a platform to illuminate BTC biology and inform therapeutic development. We identify dependencies broadly enriched in BTC compared to other cancers as well as dependencies selective to the anatomic subtypes. Notably, cholangiocarcinoma cell lines are stratified into distinct lineage subtypes based on biliary or dual biliary/hepatocyte marker signatures, associated with dependency on specific lineage survival factors. Transcriptional analysis of patient specimens demonstrates the prognostic significance of these lineage subtypes. Additionally, we delineate strategies to enhance targeted therapies or to overcome resistance in cell lines with key driver gene mutations. Furthermore, clustering based on dependencies and proteomics data elucidates unexpected functional relationships, including a BTC subgroup with partial squamous differentiation. Thus, this cell line atlas reveals potential therapeutic targets in molecularly defined BTCs, unveils biologically distinct disease subtypes, and offers a vital resource for BTC research.
<div>Abstract<p>Isocitrate dehydrogenase 1 mutations (mIDH1) are common in cholangiocarcinoma. (R)-2-hydroxyglutarate generated by the mIDH1 enzyme inhibits multiple α-ketoglutarate–dependent enzymes, altering epigenetics and metabolism. Here, by developing mIDH1-driven genetically engineered mouse models, we show that mIDH1 supports cholangiocarcinoma tumor maintenance through an immunoevasion program centered on dual (R)-2-hydroxyglutarate–mediated mechanisms: suppression of CD8<sup>+</sup> T-cell activity and tumor cell–autonomous inactivation of TET2 DNA demethylase. Pharmacologic mIDH1 inhibition stimulates CD8<sup>+</sup> T-cell recruitment and interferon γ (IFNγ) expression and promotes TET2-dependent induction of IFNγ response genes in tumor cells. CD8<sup>+</sup> T-cell depletion or tumor cell–specific ablation of TET2 or IFNγ receptor 1 causes treatment resistance. Whereas immune-checkpoint activation limits mIDH1 inhibitor efficacy, CTLA4 blockade overcomes immunosuppression, providing therapeutic synergy. The findings in this mouse model of cholangiocarcinoma demonstrate that immune function and the IFNγ–TET2 axis are essential for response to mIDH1 inhibition and suggest a novel strategy for potentiating efficacy.</p>Significance:<p>Mutant IDH1 inhibition stimulates cytotoxic T-cell function and derepression of the DNA demethylating enzyme TET2, which is required for tumor cells to respond to IFNγ. The discovery of mechanisms of treatment efficacy and the identification of synergy by combined CTLA4 blockade provide the foundation for new therapeutic strategies.</p><p><i>See related commentary by Zhu and Kwong, p. 604</i>.</p><p><i>This article is highlighted in the In This Issue feature, p. 587</i></p></div>
