bluuebunny/crossref_metadata_2025_split huggingface dataset:
Abstract 291: Functionalizing novel modulators in lung cancer
Authors: Lee Yi Fei , Yuan Ju , Lim Edwin , Chen Jianbin , Zhai Weiwei , Tan Nguan Soon , Tam Wai Leong 
Published: September 2020

Abstract
Lung cancer is the leading cause of cancer mortality globally, with lung adenocarcinoma being the most prevalent subtype. The discovery of driver mutations has paved the way for the use of targeted therapy, notably EGFR inhibitors, in the management of advanced disease. However, the effectiveness of targeted therapy is limited firstly by the eventual development of treatment resistance, and secondly by the sizeable percentage of cases in which the driver mutations remain unknown. Furthermore, lung adenocarcinoma (LUAD) in Asians is known to exhibit a molecular profile distinct from that in Caucasians, yet the majority of existing cohort studies have been focused on the latter. To address this gap, we and our collaborators have spearheaded the largest Asian LUAD cohort study, comprising genomic and transcriptomic data from 305 patients. The MutSigCV and 20/20+ driver prediction algorithms were applied to whole exome sequencing data from our cohort and yielded seven novel candidate drivers that had not been previously implicated in LUAD. We proceeded to functionally validate these drivers by overexpressing or knocking them down in patient-derived transformed lung cell lines and observing their effects on tumorigenicity via a number of in vitro and in vivo tumorigenicity assays. We have identified a poly (ADP-ribose) polymerase (PARP) gene, which was mutated at a relatively high frequency within our cohort, and show that PARP is crucial for modulating the tumorigenicity of lung cancer cells. In LUAD patients, reduced PARP expression levels were correlated with poorer prognosis, suggesting a putative tumor suppressor role. We further observed a loss of PARP copy number both within our cohort as well as the Caucasian The Cancer Genome Atlas (TCGA) LUAD cohort. We are now working to dissect the underlying mechanisms and explore PARP's clinical utility. This work illustrates the use of a platform to systematically model genetics in patient-derived models to study novel driver functions.
Citation Format: Yi Fei Lee, Ju Yuan, Edwin Lim, Jianbin Chen, Weiwei Zhai, Nguan Soon Tan, Wai Leong Tam. Functionalizing novel modulators in lung cancer [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 291.
Abstract 293: Heat shock factor 1 directly suppresses AMP-activated protein kinase to promote tumorigenesis
Authors: Su Kuo-Hui , Dai Siyuan , Tang Zijian , Xu Meng , Dai Chengkai 
Published: September 2020

Abstract
Heat shock factor 1 (HSF1), a master transcriptional regulator of the evolutionarily conserved proteotoxic stress response, preserves proteomic stability upon environmental insults. HSF1 is also a potent pro-oncogenic factor, suggesting that proteomic stability enables oncogenesis. AMP-activated protein kinase (AMPK), a key cellular metabolic sensor and downstream effector of the tumor suppressor LKB1, activates catabolic pathways but suppresses anabolic pathways, including fatty acid and cholesterol biosynthesis, thereby maintaining energy homeostasis. We previously showed that upon activation by metabolic stressors, AMPK interacts with and phosphorylates HSF1 to inactivate it and cause proteomic instability, leading to tumor suppression. Intriguingly, we also discovered that HSF1 suppresses AMPK and controls body fat mass. This study is to investigate the mechanisms by which HSF1 reciprocally suppresses AMPK and the roles of this suppression in lipid metabolism and tumorigenesis. By utilizing recombinant proteins, HSF1 peptide libraries and transcription-deficient HSF1 mutants, our in vitro studies reveal that through physical interactions HSF1 imposes multilayer regulations on AMPK, including blocking AMP binding to γ subunits, impairing LKB1-mediated Thr172 phosphorylation, promoting Thr172 de-phosphorylation by PP2A, and impeding ATP binding to catalytic α subunits. Results from circular dichroism spectroscopy reveal that HSF1 induces global AMPK conformational changes. Biologically, Hsf1 deficiency suppresses lipogenesis and decreases lipid content via AMPK activation. Moreover, Hsf1-deficient cells and mice display reduced cholesterol levels. Interestingly, this defect leads to impaired cholesteroylation of sonic hedgehog (SHH). Consequently, the oncogenic SHH signaling is impaired in HSF1-deficient cells. In vivo, Hsf1 deficiency reduces body fat mass in mice, which can be markedly rescued by either pharmacological or genetic inhibition of AMPK. Importantly, the transcription-deficient HSF1 mutant, through AMPK suppression, enhances the lipid content and SHH cholesteroylation, and promotes the in vivo growth of xenografted human melanomas. In conclusion, HSF1 is a direct AMPK antagonist. This transcription-independent interaction of HSF1 with AMPK epitomizes a reciprocal kinase-substrate regulation whereby lipid metabolism and proteomic stability intertwine and promotes cancer anabolism and oncogenesis.
Citation Format: Kuo-Hui Su, Siyuan Dai, Zijian Tang, Meng Xu, Chengkai Dai. Heat shock factor 1 directly suppresses AMP-activated protein kinase to promote tumorigenesis [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 293.
Abstract 2947: Towards advanced precision oncology assays - Selection of immunohistochemistry chromogen impacts microdissection and downstream molecular analysis of archival specimens
Authors: Laun Sarah , Roberge Adam , Weigman Robert , Lewis Aubrey , Greisman Valarie , Liu Meeiyueh , Stephens Owen , Peterson Erich , Shin Ikjae , Emmert-Buck Michael , Tangrea Michael , Johann Donald J. 
Published: September 2020

Abstract
Introduction: Precision medicine promises to improve patient treatment outcomes based on the application of molecular profiling methodologies to pathological specimens. This approach enables the development of rationally derived therapy assignments for each individual patient's tumor (versus categorical treatment assignments). Since tumors are composed of heterogeneous cells forming clusters of subtypes, dissimilar molecular profiles may emerge depending on which region is sampled and analyzed. Additionally, a manual slide scrape may result in a reduced or nearly absent molecular signal (i.e. key driver). Clearly, for cancer there is a need for an efficient, upfront enrichment method to specifically isolate specific tumor cell populations. Immuno-Laser Capture Microdissection (immuno-LCM) is a technology based on immunohistochemistry (IHC) that can isolate specific cell types from a heterogeneous cellular population. We sought to determine the impact of various IHC chromogens on the efficacy of microdissection and downstream molecular analysis from immuno-LCM samples.
Methods: Histological tissue specimens (clinical colorectal and lung cancer PDX) were processed using traditional IHC methods with a variety of chromogens, including: Vector Black, Impact Vector Red, 3-amino-9-ethylcarbazole (AEC), and 3,3'-diaminobenzidine (DAB). These chromogens were evaluated for staining quality, microdissection efficiency, biomolecular extraction, and evaluation of specific molecular targets.
Results: Interestingly, DAB, the most commonly used chromogen, demonstrated a negative impact on the retrieval of biomolecules from immuno-LCM samples. However, chromogens such as Vector Black and Impact Vector Red showed much improved biomolecule extraction compared to DAB even though the yield of microdissected material was comparable. While other chromogens, such as AEC, demonstrated a greater efficiency of biomolecule extraction but showed incomplete immuno-LCM of specific IHC-stained cells.
Conclusions: The data indicate that traditional IHC chromogens should be carefully considered when using immuno-LCM to analyze biomolecules.
Citation Format: Sarah Laun, Adam Roberge, Robert Weigman, Aubrey Lewis, Valarie Greisman, Meeiyueh Liu, Owen Stephens, Erich Peterson, Ikjae Shin, Michael Emmert-Buck, Michael Tangrea, Donald J. Johann. Towards advanced precision oncology assays - Selection of immunohistochemistry chromogen impacts microdissection and downstream molecular analysis of archival specimens [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 2947.
Abstract 299: TAK1 signaling regulates p53 through a mechanism involving ribosomal stress
Authors: Bakin Andrei V. , Zonneville Justin , Wong Vincent 
Published: September 2020

Abstract
Triple-negative breast cancer (TNBC) is among the most aggressive forms of breast cancer with limited therapeutic options. TAK1 is implicated in aggressive behavior of TNBC, while means are not fully understood. Here, we report that pharmacological blockade of TAK1 signaling hampered ribosome biogenesis (RBG) by reducing expression of RBG regulators such as RRS1, while not changing expression of ribosomal core proteins. Importantly, TAK1 blockade upregulated expression of p53 target genes in cell lines carrying wild type (wt) TP53 but not in p53-mutant cells. By examining involvement of the ribosomal stress response, we found that p53 activation by blockade of TAK1 was prevented by depletion of ribosomal protein RPL11. Further, siRNA-mediated depletion of TAK1 or RELA resulted in activation of p53 signaling and this response was dependent on RPL11. Knockdown of RRS1 disrupted nucleolar organization and resulted in activation of p53. Genomic TCGA data showed that TNBCs express high levels of ribosome biogenesis regulators, and elevated RRS1 levels correlate with unfavorable prognosis. Cytotoxicity data showed that TNBC cell lines are more sensitive to TAK1 inhibitor compared to luminal and HER2+ cell lines. Together, the data indicate that TAK1 regulates p53 activation by controlling ribosome biogenesis factors, and the TAK1-ribosome axis is a potential therapeutic target in TNBC.
Citation Format: Andrei V. Bakin, Justin Zonneville, Vincent Wong. TAK1 signaling regulates p53 through a mechanism involving ribosomal stress [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 299.
Abstract 3001: Drug resistant PDX models for new drug discovery
Authors: Zhang Feifei , Long Yuan , Wen Danyi 
Published: September 2020

Abstract
Drug resistant is one of the biggest challenge for cancer therapy. How to understand the mechanism and to overcome the drug resistant with new therapeutics represent the hot focus for oncology drug discovery. Drug resistant patient-derived xenograft (PDX) models derived from surgery samples, biopsy samples, hydrothorax or ascetic fluid provides unique tool for new therapeutics R&D. We have successfully established an array of drug resistant PDX models. Representative drug resistant PDX includes: clinically AZD9291-resistant EGFR triple mutant (Ex19del, T790M, C797S) PDX model. In vivo efficacy results show that this triple mutant NSCLC PDX model was resistant to Erlotinib and AZD9291 and sensitive to the combination of Cetuximab and Brigatinib. We also established CD74-ROS1 fusion and G2032R mutant NSCLC PDX model; EML4-ALK fusion and L1196M mutant NSCLC PDX model; Olaparib resistant Ovarian cancer PDX model; Heceptin resistant gastric PDX model; Rituximab and ABT-199 resistant DLBCL PDX model, and so on. In conclusion, these precious PDX models provide insight into resistance mechanisms as well as serve as models to develop new therapeutics drug candidates that overcome the drug resistant.
Citation Format: Feifei Zhang, Yuan Long, Danyi Wen. Drug resistant PDX models for new drug discovery [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 3001.
Abstract 3029: Population pharmacokinetics and dose regimen evaluation of monalizumab, a monoclonal antibody targeting NKG2a, in patients with advanced solid tumors
Authors: Song Xuyang 
Published: September 2020

Abstract
Background: Monalizumab (IPH2201) is a humanized IgG4 monoclonal antibody that targets NKG2a, resulting in suppression of inhibitory signaling by tumors on NK cells. We aimed to develop a population pharmacokinetics (PK) model of monalizumab and to identify and quantitate the impact of patient/disease characteristics on PK variability, and to compare body weight-based and fixed dosing regimens of monalizumab.
Methods: Data were pooled from two clinical studies: NCT02671435 (Phase 1/2; monalizumab + durvalumab in all comers) and NCT02643550 (Phase 2; monalizumab + cetuximab in SCCHN). 95 patients provided monalizumab PK data following 0.4−10 mg/kg every 2 weeks (Q2W), 22.5 mg−750 mg Q2W, or 750 mg every 4 weeks (Q4W). Population PK modeling was performed using a non-linear mixed effects modeling approach in NONMEM software (v. 7.2). Impact of demographics, clinical indices, and biomarkers on PK was explored. The appropriateness of the final model was tested using diagnostics including visual predictive check (VPC).
Results: Monalizumab PK profiles were best described using a linear 2-compartment model. The clearances (CL) and central volume of distribution (V1) were 0.27 L/day and 3.6 L with a modest between-subject variability of 40% and 30% for CL and V1, respectively. Body weight on CL and volume of distribution resulted in ~30% impact; other evaluated covariates showed no impact on PK parameters, indicating no need for dose adjustment. VPC results demonstrated good predictability of the final population PK model. Simulations indicated that similar overall PK exposures are expected following either the fixed 750 mg Q2W or the body-weight based 10 mg/kg Q2W regimens. Both regimens are projected to result in maintenance of trough exposures &gt;2 µg/mL in ≥95% of patients where nonlinear clearance is expected to be fully saturated.
Conclusions: A population PK model of monalizumab was developed and validated. No dose adjustments were needed based on patient or disease characteristics. Similar PK is expected following both body weight-based and fixed dosing regimens. These results support further evaluation of 750 mg Q2W or equivalent dose in future Phase 2/3 clinical studies.
Citation Format: Xuyang Song. Population pharmacokinetics and dose regimen evaluation of monalizumab, a monoclonal antibody targeting NKG2a, in patients with advanced solid tumors [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 3029.
Abstract 3093: Quantifying the confounders of panel-based tumor mutational burden (TMB) measurement
Authors: Budczies Jan , Kazdal Daniel , Allgäuer Michael , Christopoulos Petros , Rempel Eugen , Pfarr Nicole , Weichert Wilko , Fröhling Stefan , Thomas Michael , Peters Solange , Endris Volker , Schirmacher Peter , Stenzinger Albrecht 
Published: September 2020

Abstract
Retrospective data including subgroup analyses in clinical studies have sparked strong interest in developing tumor mutational burden (TMB) as a predictive biomarker for immune checkpoint blockade. While individual factors interfering with panel sequencing based measurement of TMB (psTMB) have been discussed in recent studies, an integrative study quantifying, comparing and combining all potential confounders is still missing. We separated different potential confounders of psTMB measurement including “panel size”, “germline mutation filtering”, “biological variance” and “technical variance” and developed a specific error model for each of these factors. Published experimental psTMB data were fitted to the error models to quantify the contribution of each of the confounders. The total psTMB variance was obtained as sum over the different variance contributions. Using a typical large panel (size 1 to 1.5 Mbp) total errors of 57%, 42%, 34% and 28% were observed for tumors with psTMB of 5, 10, 20 and 40 muts/Mbp. Even for large panels, the stochastic error connected to the panel size represented the largest of all contributions to the total psTMB variance, especially for tumors with TMB up to 20 muts/Mbp. Other sources of psTMB variability could be kept under control, but rigorous quality control, best practice laboratory workflows and optimized bioinformatics pipelines are essential. We developed an integrated framework for the analysis of psTMB variability and provide a set of recommendations for implementation of psTMB as a laboratory developed test. Our approach highlights the stochastic portion of psTMB variability. The stochastic error connected inherently with psTMB could in part explain the suboptimal performance of the biomarker in some of the recent lung cancer studies.
Citation Format: Jan Budczies, Daniel Kazdal, Michael Allgäuer, Petros Christopoulos, Eugen Rempel, Nicole Pfarr, Wilko Weichert, Stefan Fröhling, Michael Thomas, Solange Peters, Volker Endris, Peter Schirmacher, Albrecht Stenzinger. Quantifying the confounders of panel-based tumor mutational burden (TMB) measurement [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 3093.
Abstract 3094: Development of a prognostic and predictive 32 gene signature for gastric cancer
Authors: Park Sunho , Cheong Jae-Ho , Wang Sam C. , Hong ChangJin , Porembka Matthew , Hwang Tae Hyun 
Published: September 2020

Abstract
Clinical staging at initial cancer diagnosis guides the use and timing of chemotherapy and radiation. However, current pretreatment stratification modalities for gastric cancer (GC) are inadequate and improved tools are needed. In addition, while adjuvant chemotherapy after surgery improves survival of resectable gastric cancer, few predictive biomarkers exist to select patients who might benefit from the current standard chemotherapy.
To develop prognostic and/or predictive signatures that are clinically relevant for GC patients, we performed a pan-cancer analysis of somatic mutation of 6,681 patients with 19 different cancer types using the machine learning algorithm NTriPath and identified a 32-gene GC signature. To determine clinical utility of the 32-gene GC signature, we used expression of the 32-gene GC signature from 567 GC patients to discover genetic subtypes. We found that the 32-gene GC signature are prognostic and predictive of response to adjuvant 5-fluorouracil and platinum doublet and pembrolizumab. We further validated the preditive value of the 32-gene GC signature using an independent cohort with metastatic GC treated with Immune Checkpoint Blockades.
Finally, we built a genetic-subtype based risk-scoring model to predict overall survival that was validated in three independent cohorts (n = 976). The risk score accurately predicted survival as a continuous function and was significantly associated with survival independent of TNM stage, age, tumor location and Lauren type.
Taken together, the 32-gene driven genetic subtype and the genetic-subtype based risk score can guide the use of the current standard of care adjuvant chemotherapy regimen and/or immunotherapy for gastric cancer patients and should be confirmed in prospective clinical trials.
Citation Format: Sunho Park, Jae-Ho Cheong, Sam C. Wang, ChangJin Hong, Matthew Porembka, Tae Hyun Hwang. Development of a prognostic and predictive 32 gene signature for gastric cancer [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 3094.
Abstract 3243: Allogeneic anti-PTK7 CAR-T cells for the treatment of solid tumors
Authors: Levitsky Katie , Li Zejun , Pham Minh Thu , Maeng Kelly , Hanley Luke , Sagert Jason , Terrett Jon , Dutta-Simmons Jui , Allen Melanie 
Published: September 2020

Abstract
Protein Tyrosine Kinase 7 (PTK7), also known as colon cancer carcinoma kinase 4 (CCK-4), is a highly conserved catalytically inactive tyrosine kinase with inherent signal transduction activity. PTK7 is a member of the Wnt signaling pathway and thought to function in cell proliferation, adhesion, migration and apoptosis. PTK7 has been shown to be highly expressed in certain cancer types including colon, breast, lung, pancreatic, renal and ovarian. Downregulation of PTK7 by shRNA has been shown to reduce tumor growth and metastases development in xenograft mouse models. Furthermore, high PTK7 expression in triple negative breast cancer and NSCLC patients has been linked to poor prognosis. PTK7 therefore appears to be an attractive target for solid cancer therapeutic intervention and has been targeted clinically with an Antibody Drug Conjugate (PF-06647020). However, the protein is also expressed to a lesser degree in some normal adult tissues, particularly in the stromal cells of the ovary, placenta, uterus and lung. We have developed a human/murine cross-reactive anti-PTK7 CAR construct and assessed the ability of allogeneic anti-PTK7 CAR-T cells bearing that construct to target cancer cells and elicit toxicity in mice. These anti-PTK7 CAR-T cells were shown to be efficacious in vitro and in immunocompromised mouse xenograft models of breast, lung, colon, pancreatic and ovarian cancer. However, consistent in all xenograft models studied, a drop in body weight was observed shortly after injection from which all mice rapidly recovered to above baseline. Latent toxicity that was more variable amongst the xenograft experiments was also observed. Understanding and developing appropriate mitigation strategies to address the observed toxicities may be required to develop further a safe and efficacious allogeneic anti-PTK7 CAR-T cell therapy for solid tumor cancers.
Citation Format: Katie Levitsky, Zejun Li, Minh Thu Pham, Kelly Maeng, Luke Hanley, Jason Sagert, Jon Terrett, Jui Dutta-Simmons, Melanie Allen. Allogeneic anti-PTK7 CAR-T cells for the treatment of solid tumors [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 3243.