bluuebunny/crossref_metadata_2025_split huggingface dataset:
Abstract B22: Exposure of AZD4547 FGFR-TKI to a lung squamous carcinoma cell line induces resistance by small cell lung cancer-like transformation associated with ASCL1
Authors: Amano Yosuke , Ando Takahiro , Maemura Keita , Sakatini Toshio , Sunohara Mitsuhiro , Watanabe Kosuke , Kage Hidenori 
Published: February 2019

Abstract
Molecular targeted medicine has progressed in non-small cell lung cancer in recent years, and acquired resistance to molecular targeted therapy has become a major problem. Several mechanisms of acquired resistance have been described, such as secondary mutation of targeted genes, bypass pathway activation, and phenotypic transformation, including epithelial-mesenchymal transition and small cell lung cancer transformation. However, detailed mechanisms and the strategy to overcome the resistance have yet to be clarified thoroughly. In this study, we established a squamous lung cancer cell line with acquired resistance to FGFR tyrosine kinase inhibitor in vitro and identified achaete-scute family bHLH transcription factor 1 (ASCL1) overexpression as a mechanism of the resistance to tyrosine kinase inhibitor treatment.
We identified LK-2 as a squamous cell lung cancer cell line that is highly sensitive to FGFR tyrosine kinase inhibitor AZD4547, which is currently evaluated in clinical trial in squamous cell lung cancer, and established its resistant clone in vitro by exposing gradually increasing concentration of AZD4547. The resistant clone was morphologically more round-shaped and expressed ASCL1 significantly higher than the original LK-2 in a microarray analysis, but did not have additional mutations in putative genes responsible for resistance in RNA-sequencing. ASCL1 inhibition with shRNA lentivirus did not restore the sensitivity to AZD4547, but significantly suppressed the growth of the resistant clone compared to the original LK-2. Cyclin A1 (CCNA1) expression was also increased in the resistant clone and was regulated by ASCL1. CCNA1 inhibition also suppressed the growth of the resistant clone.
These results suggest that ASCL1 was one of the key molecules for the acquired resistance to tyrosine kinase inhibitor therapy, and considering the evidence that ASCL1 is a master regulator of small cell lung cancer-like phenotype, it may be related to small cell lung cancer transformation as a mechanism of the resistance. ASCL1 and its downstream molecule CCNA1 may be candidates to overcome the resistance to tyrosine kinase inhibitor therapy.
Citation Format: Yosuke Amano, Takahiro Ando, Keita Maemura, Toshio Sakatini, Mitsuhiro Sunohara, Kosuke Watanabe, Hidenori Kage. Exposure of AZD4547 FGFR-TKI to a lung squamous carcinoma cell line induces resistance by small cell lung cancer-like transformation associated with ASCL1 [abstract]. In: Proceedings of the Fifth AACR-IASLC International Joint Conference: Lung Cancer Translational Science from the Bench to the Clinic; Jan 8-11, 2018; San Diego, CA. Philadelphia (PA): AACR; Clin Cancer Res 2018;24(17_Suppl):Abstract nr B22.
Abstract B25: Decoding tumor microenvironment to enhance NSCLC targeted therapy
Authors: Hu Haichuan , Sequist Lecia , Piotrowska Zofia , Mulvey Hillary , Noeen Sundus , Hare Patricia , Kodack David , Hata Aaron , Niederst Matt , Benes Cyril , Engelman Jeff 
Published: February 2019

Abstract
This abstract is being presented as a short talk in the scientific program. A full abstract is printed in the Proffered Abstracts section (PR04) of the Conference Proceedings.
Citation Format: Haichuan Hu, Lecia Sequist, Zofia Piotrowska, Hillary Mulvey, Sundus Noeen, Patricia Hare, David Kodack, Aaron Hata, Matt Niederst, Cyril Benes, Jeff Engelman. Decoding tumor microenvironment to enhance NSCLC targeted therapy [abstract]. In: Proceedings of the Fifth AACR-IASLC International Joint Conference: Lung Cancer Translational Science from the Bench to the Clinic; Jan 8-11, 2018; San Diego, CA. Philadelphia (PA): AACR; Clin Cancer Res 2018;24(17_Suppl):Abstract nr B25.
Abstract IA03: Functional lung cancer genomics through in vivo genome editing
Authors: Winters Ian P. , Rogers Zoë N. , McFarland Christopher D. , Lalgudi Pranav V. , Chiou Shin-Heng , Kay Mark A. , Petrov Dmitri , Winslow Monte M. 
Published: February 2019

Abstract
Cancer genome sequencing has been instrumental in identifying the genomic alterations that occur in human tumors. However, the functional importance of the vast majority of these alterations, both alone and in combination, remains unknown. I will describe methods that integrate tumor barcoding with CRISPR/Cas9-mediated genome editing and ultradeep barcode sequencing to interrogate multiple tumor genotypes simultaneously in autochthonous mouse models of human cancer. We initially used this method to quantify the effects of eleven of the most frequently inactivated genes in human lung adenocarcinoma on tumor growth in vivo. We also investigated the in vivo fitness advantage conferred by inactivation of each of these eleven genes in combination with inactivation of p53 or Lkb1. This map of tumor-suppressive effects for &gt;30 common lung adenocarcinoma genotypes revealed a complex landscape of context dependence and variability in effect strength. I will also describe a platform that integrates multiplexed Cas9-mediated homology-directed repair (HDR) with DNA barcoding and high-throughput sequencing to simultaneously investigate multiple oncogenic alterations in parallel. Using this approach, we introduced a library of nonsynonymous mutations into endogenous Kras in adult somatic cells to initiate tumors. High-throughput sequencing of barcoded Kras HDR alleles from bulk tumor-bearing lung uncovered surprising diversity in Kras variant oncogenicity. These in vivo approaches may redefine our ability to understand how diverse genomic alterations impact tumor initiation, growth, malignant transformation, and therapy responses.
Citation Format: Ian P. Winters, Zoë N. Rogers, Christopher D. McFarland, Pranav V. Lalgudi, Shin-Heng Chiou, Mark A. Kay, Dmitri Petrov, Monte M. Winslow. Functional lung cancer genomics through in vivo genome editing [abstract]. In: Proceedings of the Fifth AACR-IASLC International Joint Conference: Lung Cancer Translational Science from the Bench to the Clinic; Jan 8-11, 2018; San Diego, CA. Philadelphia (PA): AACR; Clin Cancer Res 2018;24(17_Suppl):Abstract nr IA03.
Abstract IA06: Molecular mechanisms of lung cancer development: Between metabolic reprogramming and genomic instability in the field of cancerization
Authors: Rahman Jamshed , Ji Xiangming , Patel Chirayu , Young Jamey , Massion Pierre P. 
Published: February 2019

Abstract
Airway epithelial cells are prone to assault by risk factors and considered to be the primary cell type involved in the field of cancerization. To investigate risk-associated changes in the bronchial epithelium proteome that may offer new insights into molecular pathogenesis of lung cancer, proteins were identified in the airway epithelial cells of bronchial brushings specimens from risk-stratified individuals by shotgun proteomics. Differential expression of selected proteins was validated by parallel reaction monitoring mass spectrometry in an independent set of individual bronchial brushings. We identified over 300 proteins with a significant trend in expression. Pathway analysis revealed enrichment of carbohydrate metabolic enzymes in high-risk individuals. Glucose consumption and lactate production were increased in human bronchial epithelial BEAS2B cells treated with cigarette smoke condensate for seven months. Increased lipid biosynthetic capacity and net reductive carboxylation were revealed by metabolic flux analyses of [U-13C5] glutamine in this in vitro model, suggesting profound metabolic reprogramming in the airway epithelium of high-risk individuals. These results also pointed towards a fundamental role of glutamine and cysteine metabolism in lung cancer progression. Two amino acid transporters, specifically SLC1A5 and SLC7A11, captured our attention for their high level of expression in lung cancer. These transporters are associated with worse survival in lung cancer. A small-molecular inhibitor of SLC1A5 prevents tumor progression in nude mice, and a glutaminase inhibitor CB-839 exhibits radiosensitization to lung cancer cells, an effect that may be mediated by decreased GSH production. Taken together, these studies provide a rationale for new chemopreventive strategies, selection of patients for surveillance programs, and determining how metabolic reprogramming may contribute genomic instability a requirement to cancer development. Further investigation into how glutamine and cystine metabolism contribute to lung cancer development and progression may lead to novel early-interception strategies in lung cancer. This work is supported by NCI CA186145, CA152662, and DoD W81XWH-11-2-0161.
Citation Format: Jamshed Rahman, Xiangming Ji, Chirayu Patel, Jamey Young, Pierre P. Massion. Molecular mechanisms of lung cancer development: Between metabolic reprogramming and genomic instability in the field of cancerization [abstract]. In: Proceedings of the Fifth AACR-IASLC International Joint Conference: Lung Cancer Translational Science from the Bench to the Clinic; Jan 8-11, 2018; San Diego, CA. Philadelphia (PA): AACR; Clin Cancer Res 2018;24(17_Suppl):Abstract nr IA06.
Abstract IA08: Individualized risk based lung cancer screening: The way forward
Authors: Berg Christine D. 
Published: February 2019

Abstract
The United States Preventive Services Task Force (USPSTF) recommends annual low-dose computed tomography (CT) lung-cancer screening, as does the Center for Medicare and Medicaid Services (CMS) and many major medical organizations. The USPSTF criteria, similar to those used for entry into the definitive National Lung Screening Trial, are for persons aged 55-80 years, who currently smoke or quit within the past 15 years, and who have accumulated at least 30 pack-years of cigarette smoking. Risk calculators as compared to micro-simulation modeling as used for the USPSTF can more specifically account for demographic, clinical, and smoking characteristics and personalize risk. The USPSTF criteria may miss smokers at high risk for lung cancer who would have been selected for CT screening by individual risk calculators. Recently, the National Comprehensive Cancer Network guidelines for lung cancer screening added consideration of use of risk models to select ever-smokers for screening. Online risk tools are available to assist individuals and health care providers as to whether lung cancer screening may be helpful.
Several lung cancer risk models are available, and comparisons across them have been done. In this presentation, a comparison we performed of the statistical predictive properties of 8 published risk models in 2 large prospective U.S. cohorts will be presented. Identifying a consensus cost-effective risk threshold to define screening eligibility is crucial. Another issue is how best to account for competing morbidities that might make screening less useful. Perhaps a life-years gained approach could help to adjust for this. Additionally, risk models require accurate risk factor data, which are rarely available in electronic health records and may require special collection. It also poses challenges in the health care delivery setting given its complexity.
To better capture high-risk smokers and prevent premature deaths from lung cancer, eligibility for lung cancer screening should be based on exceeding a cost-effective risk threshold that balances CT screening benefits and harms, using a lung cancer risk tool validated in the U.S. population.
Citation Format: Christine D. Berg. Individualized risk based lung cancer screening: The way forward [abstract]. In: Proceedings of the Fifth AACR-IASLC International Joint Conference: Lung Cancer Translational Science from the Bench to the Clinic; Jan 8-11, 2018; San Diego, CA. Philadelphia (PA): AACR; Clin Cancer Res 2018;24(17_Suppl):Abstract nr IA08.
Abstract IA28: The genomic landscape of SCLC and other neuroendocrine lung tumors
Authors: George Julie 
Published: February 2019

Abstract
Small cell lung cancer (SCLC) accounts for 15% of all lung cancers and belongs to the family of pulmonary neuroendocrine tumors. This tumor subgroup additionally includes large-cell neuroendocrine carcinomas (LCNEC) and pulmonary carcinoids (PCA), which occur in 3% and 2% of all lung cancer patients, respectively. Carcinoids are usually clinically benign, whereas SCLC and LCNEC are characterized as high-grade malignant tumors. Clinical and histologic studies have suggested similarities between SCLC and LCNECs: Both lung tumor subtypes are associated with heavy smoking and reveal an aggressive tumor growth resulting in a poor overall survival.
We have performed comprehensive and multilevel genomic profiling on SCLC and LCNECs, including genome, exome, and transcriptome sequencing. SCLC and LCNEC tumors reveal high mutation rates with an average of 9.5 and 8.6 mutations per megabase, respectively. Our sequencing studies have shown that SCLC tumors are characterized by bi-allelic inactivation of TP53 and RB1 in almost 100% of the cases. LCNECs, on the other hand, are composed of two mutually exclusive subgroups, which we categorized as “type I LCNECs” and “type II LCNECs.” Type I LCNECs harbor TP53 and STK11 or KEAP1 alterations. Despite sharing genomic alterations with lung adenocarcinomas and squamous cell carcinomas, type I LCNECs exhibit a high neuroendocrine profile with close similarity to SCLC tumors. Type II LCNECs harbor loss of TP53 and RB1, thus showing genetic resemblance to SCLC. However, these tumors were revealed to be different from the majority of SCLC with reduced levels of neuroendocrine markers, an upregulated immune signaling profile, and high activity of the NOTCH pathway. Conclusively, our studies show marked biologic differences between high-grade neuroendocrine lung tumors and we emphasize the precise distinction of LCNEC subgroups from SCLC.
Citation Format: Julie George. The genomic landscape of SCLC and other neuroendocrine lung tumors [abstract]. In: Proceedings of the Fifth AACR-IASLC International Joint Conference: Lung Cancer Translational Science from the Bench to the Clinic; Jan 8-11, 2018; San Diego, CA. Philadelphia (PA): AACR; Clin Cancer Res 2018;24(17_Suppl):Abstract nr IA28.
Abstract IA31: Radiation therapy in lung cancer: Recent trends and future directions
Authors: Gomez Daniel R. 
Published: February 2019

Abstract
Radiation techniques for lung cancer have evolved substantially over the past decade. While previously many patients were treated with 3D conformal therapy, with large uniform margins placed to estimate respiratory motion in the “average” tumor, patients are now simulated with sophisticated, real-time monitoring of internal motion such that treatment volumes can be individualized to maximize normal tissue sparing through image-guided radiation therapy (IGRT). In addition, many patients are now treated with intensity-modulated radiation therapy (IMRT), which has served to drastically improve conformality in select cases and increase the proportion of patients in which high doses are achievable. Concurrent with these advances, proton beam therapy (PBT) has been implemented in a limited number of centers, with the hope of utilizing the dosimetric distribution advantage of the Bragg Peak to further reduce toxicity. The role of PBT in both early-stage and locally advanced non-small cell lung cancer continues to be defined, as results from a phase II multicenter randomized trial predominantly in patients with stage II-III disease did not demonstrate superiority with PBT and concurrent chemotherapy when compared to similar regimens with IMRT. Finally, there have been much data produced with regard to dosing regimens. In early-stage disease, there has been increased implementation of stereotactic ablative body radiation (SABR), with prospective data emerging for both peripheral and central lesions. In the locally advanced setting, results from RTOG 0617 demonstrated no difference when comparing 60 Gy vs. 74 Gy in the setting of chemoradiation. There has also been a trend towards hypofractionation for patients who are unable to tolerate concurrent chemoradiation or those with oligometastatic disease, yet the benefit of hypofractionated radiation sequentially vs. combined modality treatment will need to be further assessed in prospective randomized trials, particularly in the era of immunotherapy.
Citation Format: Daniel R. Gomez. Radiation therapy in lung cancer: Recent trends and future directions [abstract]. In: Proceedings of the Fifth AACR-IASLC International Joint Conference: Lung Cancer Translational Science from the Bench to the Clinic; Jan 8-11, 2018; San Diego, CA. Philadelphia (PA): AACR; Clin Cancer Res 2018;24(17_Suppl):Abstract nr IA31.
Abstract IA32: Multiscale modeling of lung cancer
Authors: Gevaert Olivier 
Published: February 2019

Abstract
Vast amounts of biomedical data are now routinely available for lung cancer patients ranging from sequencing of lung tissues to liquid biopsies. In addition, new computational tools for quantitatively analyzing immunohistochemistry (IHC) and radiology images are now available. Multi-scale data is now available for complex diseases at molecular, cellular and tissue scale to establish a more comprehensive view of key biological processes. Intra and inter individual heterogeneities are often quoted as the main challenge for studying cancer. These heterogeneities exist at all scales, from microscopic to macroscopic. However, the technologies used to generate data at a particular scale don’t equally assess the heterogeneity. A single biopsy of a lung tumor does not reflect the potential cellular and spatial heterogeneity. Radiology images on the other hand provide a global picture of the heterogeneity of the complete tumor at the tissue scale.
We propose multi-scale modeling to counter heterogeneity and uncover potentially untapped synergies between different data modalities by integrating information across spatial scales. Multi-scale modeling involves linking information from molecules, cells, tissues, and organs all the way to the organism and the population. We propose to use high dimensional molecular data with cellular and tissue scale image data to develop a statistical multi-scale modeling approach of cancer by tapping the previously understudied information in IHC and radiology images. For example, recent reports showed how to integrate transcriptomic data and CT images resulting in intriguing associations between gene expression signatures and CT image phenotypes. Secondly, multiple studies have shown that EGFR mutation status can be predicted from CT images features, opening up avenues for non-invasive therapy monitoring. In addition, computational analysis of IHC and radiology images is able to predict the overall survival of lung cancer patients. Each of these single reports have shown the potential of multi-scale modeling, however a complete multi-scale model of lung cancer is still under development. Overall, multi-scale modeling can have profound contributions toward predicting diagnosis and treatment by revealing synergies and previously unappreciated relationships. Multi-scale modeling also can contribute to a more fundamental understanding of lung cancer development and can reveal novel insights in how data at different scales are linked to each other.
Citation Format: Olivier Gevaert. Multiscale modeling of lung cancer [abstract]. In: Proceedings of the Fifth AACR-IASLC International Joint Conference: Lung Cancer Translational Science from the Bench to the Clinic; Jan 8-11, 2018; San Diego, CA. Philadelphia (PA): AACR; Clin Cancer Res 2018;24(17_Suppl):Abstract nr IA32.
Abstract IA34: Targeting cellular heterogeneity in lung adenocarcinoma
Authors: Marjanovic Nemanja , Hofree Matan , Canner David , Trakala Marianna , Wu Katherine , Smith Olivia , Kim Jonathan , Amon Angelika , Regev Aviv , Jacks Tyler , Tammela Tuomas 
Published: February 2019

Abstract
Cancer arises from a single cell through a series of acquired mutations, and gradually develops into a complex tissue comprising phenotypically heterogeneous societies of cancer cells. The phenotype, or state, of each tumor cell is influenced by multiple cell-autonomous and cell-extrinsic factors; the diversity of these cellular states poses a challenge for effective cancer therapies. We characterized the evolution of transcriptomes at the single-cell level in genetically engineered murine lung tumors driven by oncogenic Kras. Tumor progression was accompanied by a dramatic increase in cellular heterogeneity, which was further exacerbated upon deletion of the p53 tumor suppressor, allowing tumor progression into advanced adenocarcinomas. This heterogeneity was manifested by the emergence of de-differentiated or transdifferentiated populations, the activation of latent developmental or regenerative programs, as well as heterogeneous activation of signaling pathways. Surprisingly, similar heterogeneous populations emerged in independent tumors irrespective of considerable intertumoral differences in genetic copy number alterations, suggesting a remarkable degree of convergence to achieve a common evolutionary endpoint. We used these data to computationally model cell-state transitions. Finally, treatment of the lung tumors with chemotherapy enabled the identification of cellular states associated with intrinsic sensitivity or resistance. These results associate tumor progression with increasing transcriptional heterogeneity. The identification of unique gene expression programs in cancer cell subpopulations provides a path towards reducing cellular heterogeneity in cancer.
Citation Format: Nemanja Marjanovic, Matan Hofree, David Canner, Marianna Trakala, Katherine Wu, Olivia Smith, Jonathan Kim, Angelika Amon, Aviv Regev, Tyler Jacks, Tuomas Tammela. Targeting cellular heterogeneity in lung adenocarcinoma [abstract]. In: Proceedings of the Fifth AACR-IASLC International Joint Conference: Lung Cancer Translational Science from the Bench to the Clinic; Jan 8-11, 2018; San Diego, CA. Philadelphia (PA): AACR; Clin Cancer Res 2018;24(17_Suppl):Abstract nr IA34.