bluuebunny/crossref_metadata_2025 huggingface dataset:
Abstract 1624: Antigen-independent de novo prediction of cancer-associated TCR repertoire
Authors: Li Bo
Published: August 2019

Cancer-associated T cells play a critical role in mediating immune responses in the anti-tumor immunity. However, due to the complex nature of cancer antigens, and the limited experimental approaches for collecting antigen-specific T cells, it remains a difficult task in cancer immunology to detect cancer-associated T cells. In this project, we have developed an antigen-independent machine learning approach to perform de novo prediction of cancer-associated T cells. Specifically, we have discovered a signature in the CDR3 sequence that can distinguish cancer-associated T cells from others. We applied this signature to immune repertoire data to define a “cancer score”, which is related to the probability of a repertoire being cancer-associated. We applied this approach to investigate 15 sample cohorts from public domain. These cohorts cover healthy donors, viral infected individuals and cancer patients from both early and late stages. Surprisingly, we observed consistently and significantly higher cancer scores using the cancer patients’ immune repertoire data, while none of the non-cancer repertoire was significant compared to healthy donors. We therefore used repertoire cancer score as a single predictor for cancer status to distinguish cancer patients from healthy donors, and observed high prediction power measured by area under the ROC (AUROC) curves. The AUROC reached 0.90 for early breast cancer patients, which is better than a number of current early prediction methods based on cancer biomarkers, such as PSA, CA-125, CEA, etc. In addition, cancer scores derived from certain late-stage cancers are associated with patient response to checkpoint blockade therapies, suggesting that it may also be used in combination with existing biomarkers, such as PD-L1 expression or cancer neoantigen load, to improve the prediction of clinical outcome of these cancer types. We anticipate broad utilities of cancer scores in cancer diagnosis and immunotherapy prognosis with the rapidly accumulating TCR repertoire sequencing data in clinical studies.

Note: This abstract was not presented at the meeting.

Citation Format: Bo Li. Antigen-independent de novo prediction of cancer-associated TCR repertoire [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 1624.
Abstract 1627: Using internet-platform technology to train community-based researchers in developing countries: Lessons learned from a Caribbean study
Authors: Thomas-Purcell Kamilah B. , Primus-Jospeh Marva Primus , Richards Christine , Atkins Lydia S. , Blaze Julie , Wylie Patsy , James Ann Marie Burnie , Ashing Kimlin
Published: August 2019

Cancer is increasing as a health crisis in the Caribbean region. In the U.S. advocate engagement and Community Based Participatory Research (CBPR) have been used successfully to partner with community members in each stage of the research process thereby utilizing the knowledge and experience of those individuals for improved community responsive research and greater societal benefit. We utilized advocate engagement and CBPR towards building a cancer prevention program of research between U.S. and Caribbean researchers. In 2016-2017, a two-phased CBPR research study was initiated to address breast and cervical cancer screening in the four countries of the English-speaking Windward Islands of the Caribbean. The aims were to determine 1) community member’s perceptions of breast and cervical cancer screening and 2) gatekeepers’ perceptions of the quality and availability of breast and cervical cancer screening and treatment services. Mobile communication and internet-platform technologies were used to successfully train Caribbean community researchers on qualitative data collection and analysis methods. Our results showed that the incorporation of internet-based technology facilitated training, communication, social interactions, and alleviated transportation challenges. In particular, mobile platforms including GoToTraining, WhatsApp, Dedoose, Google Drive, and email were to used to deliver interactive training modules to community researchers and facilitate the collaborative development of recruitment materials, data collection instruments, data management, reports, manuscripts and results dissemination. Participatory research studies of this nature not only shed light on the cancer burden in developing nations but also builds community trust and capacity to engage in future international research.

Citation Format: Kamilah B. Thomas-Purcell, Marva Primus Primus-Jospeh, Christine Richards, Lydia S. Atkins, Julie Blaze, Patsy Wylie, Ann Marie Burnie James, Kimlin Ashing. Using internet-platform technology to train community-based researchers in developing countries: Lessons learned from a Caribbean study [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 1627.
Abstract 1629: Classification of cancer histology images using deep learning
Authors: Xie Weidong
Published: August 2019

Pathological evaluation of tumor tissue images stained with hematoxylin and eosin (H&E) is pivotal and specialists often disagree on the final diagnosis. Meanwhile, automated image analysis approaches have great potential to increase precision of diagnosis, help reduce human error and cut cost. In this study, we utilize various computational methods based on deep learning framework and build a stand-alone diagnostic tool to effectively classify different histopathology images across different types. The dataset of tissue slides from eligible patients with breast cancer/ thyroid cancer consists of 45,000 samples in our hospital. Available tissue samples above were split into a training set, for learning the CNN parameters, and test set, for evaluating its performance. An accuracy of 94% was obtained for non-cancer (i. e. normal or benign) vs malignant (i. e. invasive carcinoma or papillary thyroid carcinoma). In addition, we also demonstrated the utility of our model to discriminate between two subtypes of lung cancer. It provides pathologists or medical technicians a straightforward platform to use without requiring sophisticated computational knowledge, and cancerization would be identified which is not visible under a single microscope.

Citation Format: Weidong Xie. Classification of cancer histology images using deep learning [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 1629.
Abstract 163: Identification and characterization of TGFBI in circulating tumor cell subline from pancreatic cancer cell line
Authors: Muramatsu Tomoki , Sato Taku , Tanabe Minoru , Inazawa Johji
Published: August 2019

Distant metastasis to liver, lung, brain, or bone occurs via circulating tumor cells (CTCs). We hypothesized that a subset of CTCs had more malignant features than tumor cells at the primary site. We established a highly malignant cell line, Panc-1-CTC, derived from the human pancreatic cancer cell line Panc-1 (Panc-1-P) using an in vivo selection method. Panc-1-CTC cells exhibited more profound migratory and invasive abilities than Panc-1-P cells in vitro. In addition, Panc-1-CTC cells had a higher tumor-forming ability than Panc-1-P cells in vivo. To investigate whether a difference in malignant phenotypes exists between Panc-1-P and -CTC cells, we performed comprehensive gene expression array analysis. As a result, Panc-1-CTC significantly expressed transforming growth factor beta-induced (TGFBI), an extracellular matrix protein, more abundantly than did Panc-1-P cells. TGFBI is considered to regulate cell adhesion, but its functions remain unclear. In the present study, knockdown of TGFBI reduced cell migration and invasion abilities, whereas overexpression of TGFBI increased both abilities. Moreover, elevated expression of TGFBI was associated with poor prognosis in patients with pancreatic cancer. Taken together, TGFBI might be targeted for cancer therapy and its expression could be a biomarker for the prediction of prognosis in pancreatic cancer.

Citation Format: Tomoki Muramatsu, Taku Sato, Minoru Tanabe, Johji Inazawa. Identification and characterization of TGFBI in circulating tumor cell subline from pancreatic cancer cell line [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 163.
Abstract 1632: Deep learning functional associations using histopathology images
Authors: Noorbakhsh Javad , Farahmand Saman , Ha Mohammad Soltanieh , Namburi Sandeep , Zarringhalam Kourosh , Chuang Jeff
Published: August 2019

Histopathological images have critical value for understanding cancer subtype, local structure, and malignancy. Manual interpretation of such images can be time-consuming and error-prone, while also failing to make use of the power of image aggregation for coordinated data mining. Large-scale patient cohorts such as TCGA provide high-resolution H&E images that complement other -omics data, with the important advantage that images provide spatial information about heterogeneity and stromal cell interactions. We implemented a convolutional neural network (CNN) to classify H&E slides according to tissue type, cancer subtype, and genomic mutations. We modified the CNN architecture of Inception v3 according to our problem and trained it with tiled whole slide images from 31 solid cancers in TCGA, and evaluated our algorithm on holdout data. We first classified tumor/normal status from the images and determined AUC values for each cancer type. We then applied our method for tissue classification in a multilabel classification scenario. Furthermore, in few cancers (e.g. gastric cancer) we determined cancer subtypes using supervised learning. Finally we evaluated our model for classifying mutational status of cancer-related genes. To improve classification accuracy, we modified Inception architecture for multi-task classification by replacing the final fully-connected layer by a shared layer which provides the input to individual task layers corresponding to each gene mutation. Furthermore, we adopted image segmentation approaches (e.g.. auto-thresholding) to improve sample background removal, and used several approaches (e.g. resampling, cross entropy weighting) to rebalance the data. In some cases we achieved high classification results (e.g. AUC=0.7 for TP53 in lung adenocarcinoma). Our study suggests that histological images can be used to classify tumors according to their mutational status, and can provide biomarkers for molecular subtyping.

Citation Format: Javad Noorbakhsh, Saman Farahmand, Mohammad Soltanieh Ha, Sandeep Namburi, Kourosh Zarringhalam, Jeff Chuang. Deep learning functional associations using histopathology images [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 1632.
Abstract 1645: Data science for cancer research
Authors: Zheng W. Jim
Published: August 2019

Cancer has been studied at all levels, ranging from molecules, to cells, to individuals, to populations. However, cancer research faces significant challenges such as enormous volume and heterogeneity of the data. Furthermore, new technologies applied to cancer research can generate data at extremely high speeds. These “big data” pose a significant challenge to conventional data analysis methodologies. We established a Data Science and Informatics Core Facility for Cancer Research (DSICCR) to analyze big data and provides integrative solutions to analyze cancer data at all levels. DSICCR supports the cancer research community by establishing a powerful “big data” infrastructure using data science-oriented high-performance computing, deployed with analytic and mining algorithms and software built upon DSICCR faculty’s cutting-edge data science and informatics research. This infrastructure will support DSICCR’s data science and informatics services to the cancer research community through collaborative research, data analysis services, and outreach and education programs. DSICCR is uniquely positioned to leverage existing research networks and make this vast amount of information more available to the cancer research community - an unprecedented opportunity to support multi-scale cancer research statewide.

Citation Format: W. Jim Zheng. Data science for cancer research [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 1645.
Abstract 1654: Detection of structural variations in a cancer reference sample with multiple NGS platforms
Authors: Zhao Yongmei , Xiao Wenming ,   on behalf of Somatic Mutation Working Group of theSEQC2 Consortium
Published: August 2019

Structural Variations (SVs) are genetic variations or rearrangements in the structure of chromosome. SVs study plays an important role in cancer research as cancer genome is commonly altered with thousands of structural rearrangements such as insertions, deletions, translocation, inversions, duplications, copy number variations (CNVs). Next-generation sequencing (NGS) technology has provided a cost-effective approach for the comprehensive detection of SVs in human cancer cells.

In this study, we systematically investigated the somatic structural variations in a pair of breast cancer cell lines with multiple NGS platforms including Illumina short-read, 10x genomics linked-read, PacBio long-read, and high-throughput chromosome conformation capture HiC. We systematically evaluated the factors that impact the SVs detection accuracy. We measured the reproductivity of somatic SV detections across platforms and benchmarked the different software tools’ performance. We performed SV integration from different platforms and established a high-confident SV call set for the reference samples. To independently evaluate the accuracy of our SV call set, we used orthogonal methods such as cytogenetic array as well as fusion gene detected from RNA-seq for cross validation. From this study, we identified the unique strengths of each NGS technologies and provide a practical guide to integrate multiple platform data to improve SV detection sensitivity and accuracy in cancer genome.

Note: This abstract was not presented at the meeting.

Citation Format: Yongmei Zhao, Wenming Xiao, on behalf of Somatic Mutation Working Group of theSEQC2 Consortium. Detection of structural variations in a cancer reference sample with multiple NGS platforms [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 1654.
Abstract 1666: Developing healthcare data scientists using Veterans Health Administration (VHA) data resources: The NCI/VA Big Data Scientist Training Enhancement Program (BD-STEP)
Authors: Elder Sarah G. , Berny-Lang Michelle
Published: August 2019

Due to advances in molecular profiling and medical imaging and the increased adoption of electronic health records (EHRs), the growth in oncology-related data has surpassed the development of a workforce capable of analyzing these data. This marks a missed opportunity in cancer research to gain insights toward better prediction of disease risk and therapeutic response. The Big Data Scientist Training Enhancement Program (BD-STEP), jointly managed by the National Cancer Institute and the Veterans Health Administration, addresses this gap by training the next generation of healthcare data scientists using the VA’s healthcare data infrastructure. Post-doctoral fellows from science and engineering backgrounds are paired with VA medical centers across the country, where they are immersed in the clinical environment as they pursue high-impact clinical research questions through data science. They enrich their data science skills using VA data resources, including clinical data from the VA healthcare system, genomic data from the Million Veterans Program (MVP), and treatment and diagnosis data from the VA Central Cancer Registry. Prospective fellows, data science experts, and healthcare researchers are encouraged to learn more about the program, its training opportunities, and existing projects using VA healthcare data.

Citation Format: Sarah G. Elder, Michelle Berny-Lang. Developing healthcare data scientists using Veterans Health Administration (VHA) data resources: The NCI/VA Big Data Scientist Training Enhancement Program (BD-STEP) [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 1666.
Abstract 1667: A robust human immune profiling assay using CyTOF technology and automated data analysis software
Authors: Li Stephen K. , Majonis Daniel , Bagwell C. Bruce , Hunsberger Benjamin C. , Baranov Vladimir I. , Ornatsky Olga I.
Published: August 2019

Immune monitoring is an essential method for quantifying changes in immune cell population numbers and states over time in health and disease. A cornerstone in translational and clinical research, it is frequently used in the investigation of chronic inflammation, infectious disease, autoimmune diseases, and cancer. The diversity of immune cell populations demands a highparameter approach to more fully and efficiently quantify these changes. Mass cytometry, which utilizes CyTOF® technology, is a single-cell analysis platform that uses metal-tagged antibodies to resolve over 40 markers in a single tube of sample without the need for compensation. It is an ideal solution for routine enumeration of immune cell populations. However, development of a robust, highly multiplexed assay requires panel optimization as well as standardization of instrument setup and an analysis pipeline.

We have developed a sample-to-answer solution for human immune profiling using mass cytometry. It includes an optimized 30-marker immune profiling panel provided in a lyophilized, single-tube format, validated SOPs for human whole blood and PBMC staining, an instrument data acquisition template, instructions for data acquisition on a Helios™ system, and automated software for data analysis. The software analyzes FCS 3.0 files generated with the kit; automatically reports cell counts, percentage calculations, and staining intensity; and produces graphical elements such as histograms, dot plots, and a Cen-se′™ (t-SNE variant) graph for 36 immune cell populations.

Here we present assay analytical validation data on repeatability, reproducibility, software precision, and software accuracy. We also present a performance comparison of the lyophilized material and a liquid formulation of the same antibodies and clones used in the lyophilized format. This assay provides a robust, complete solution for broad immune profiling using mass cytometry that reduces sources of variability and subjectivity in sample preparation and data analysis.

Citation Format: Stephen K. Li, Daniel Majonis, C. Bruce Bagwell, Benjamin C. Hunsberger, Vladimir I. Baranov, Olga I. Ornatsky. A robust human immune profiling assay using CyTOF technology and automated data analysis software [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 1667.
Abstract 1669: Full length transcriptome sequencing of melanoma cell line complements long read sequencing assessment of genomic rearrangements
Authors: Tseng Elizabeth , Galvin Brendan , Hon Ting , Kloosterman Wigard P. , Ashby Meredith
Published: August 2019

Transcriptome sequencing has proven to be an important tool for understanding the biological changes in cancer genomes including the consequences of structural rearrangements. Short read sequencing has been the method of choice, as the high throughput at low cost allows for transcript quantitation and the detection of even rare transcripts. However, the reads are generally too short to reconstruct complete isoforms. Conversely, long-read approaches can provide unambiguous full-length isoforms, but lower throughput has complicated quantitation and high RNA input requirements has made working with cancer samples challenging.

Recently, the COLO 829 cell line was sequenced to 50-fold coverage with PacBio SMRT Sequencing. To validate and extend the findings from this effort, we have generated long-read transcriptome data using an updated PacBio Iso-Seq method, the results of which will be shared at the AACR 2019 General Meeting. With this complimentary transcriptome data, we demonstrate how recent innovations in the PacBio Iso-Seq method sample preparation and sequencing chemistry have made long-read sequencing of cancer transcriptomes more practical. In particular, library preparation has been simplified and throughput has increased. The improved protocol has reduced sample prep time from several days to one day while reducing the sample input requirements ten-fold. In addition, the incorporation of unique molecular identifier (UMI) tags into the workflow has improved the bioinformatics analysis. Yield has also increased, with v3 sequencing chemistry typically delivering > 30 Gb per SMRT Cell 1M. By integrating long and short read data, we demonstrate that the Iso-Seq method is a practical tool for annotating cancer genomes with high-quality transcript information.

Citation Format: Elizabeth Tseng, Brendan Galvin, Ting Hon, Wigard P. Kloosterman, Meredith Ashby. Full length transcriptome sequencing of melanoma cell line complements long read sequencing assessment of genomic rearrangements [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 1669.
Abstract 170: Loss of the ubiquitin-specific peptidase 18 (USP18) reduces lung cancer metastasis
Authors: Chen Zibo , Zheng Lin , Chen Yulong , Kawakami Masanori , Mustachio Lisa , Roszik Jason , Liu Xin , Kurie Jonathan , Liu Xi , Dmitrovsky Ethan
Published: August 2019

Metastasis is a major cause of cancer-related mortality. Yet, current antineoplastic strategies do not effectively repress metastasis. Thus, there is a pressing need to explore targets that can reduce metastasis, especially in lung cancer that is the most common cause of cancer mortality. Our prior work reported that expression of the ubiquitin-specific peptidase 18 (USP18) was augmented in diverse cancers (including lung cancers) and USP18 knock-down suppressed in vitro and in vivo growth of murine and human lung cancers. This deubiquitinase stabilizes target proteins by removing interferon-stimulated gene 15 (ISG15) from substrate proteins. We explored here whether engineered loss of USP18 decreased lung cancer metastasis. Stable USP18 knockdown was independently achieved in human (A549 and H1299) and murine (344SQ and KC2) lung cancer cells by use of small hairpin RNAs (shRNAs). Notably, knockdown of USP18 expression reduced lung cancer cellular proliferation, migration and invasion versus control shRNA transfectants (p < 0.001). Lung cancer cells selected for high metastatic potential (344SQ and KC2) were independently injected via tail vein or subcutaneously to establish metastatic mouse models. USP18 knockdown statistically-significantly decreased lung cancer metastases as compared to control shRNA transfectants. To elucidate engaged mechanisms, Reverse Phase Protein Array (RPPA) analysis was performed to interrogate over 300 growth-regulatory proteins in human (A549 and H1299) and murine (344SQ and KC2) lung cancer cells having engineered USP18 knockdown. Results were compared to control shRNA transfectants. Ingenuity pathway analysis highlighted fatty acid synthase (FASN) as a potential USP18 target that regulated lung cancer metastasis. Independent immunoblot analysis confirmed FASN expression was reduced in cancers once USP18 knockdown was achieved. Functional validation of FASN in lung metastasis is underway. These and other findings that will be presented provide a strong rationale for targeting the deubiquitinase USP18 to reduce lung cancer metastasis and combat lung cancers.

Citation Format: Zibo Chen, Lin Zheng, Yulong Chen, Masanori Kawakami, Lisa Mustachio, Jason Roszik, Xin Liu, Jonathan Kurie, Xi Liu, Ethan Dmitrovsky. Loss of the ubiquitin-specific peptidase 18 (USP18) reduces lung cancer metastasis [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 170.
Abstract 1701: Improvement of tumor mutation burden measurement by removal of deaminated bases in FFPE DNA
Authors: Tom Warren , Chaudhary Ruchi , Mittal Vinay , Cyanam Dinesh , Casuga Iris , Wong-Ho Elaine , Bennett Rob , Hyland Fiona , Sadis Seth , Au-Young Janice
Published: August 2019

Tumor mutation burden (TMB) is a positive predictive factor for response to immune-checkpoint inhibitors in certain types of cancer. The Oncomine™ Tumor Mutation Load Assay, a 1.7Mb targeted next generation sequencing (NGS) panel, measures TMB and detects mutations in 409 cancer genes. The TMB values obtained using targeted sequencing are positively correlated with TMB measured by whole exome sequencing in NSCLC, colorectal, endometrial and gastric cancers. TMB from these tumor samples are correlated with other phenotypes associated with genomic instability, specifically microsatellite instability (MSI) and mutations involved in mismatch repair and cancer related genes. Analysis of the Oncomine™ TML Assay results with Torrent Suite and Ion Reporter software uniquely measures the degree of deamination of cytosines to uracils in fixed tissues. FFPE preservation methods can lead to significant cytosine deamination of the isolated DNA, resulting in decreased sequencing quality. In these samples, uracils are propagated as thymines and result in false C>T substitutions. To minimize the influence that excess deamination has on TMB results, we have incorporated a UDG enzyme treatment to eliminate damaged targets and improve usable TMB values of DNA from damaged FFPE tumor tissue. The Oncomine™ TML assay for TMB on Ion GeneStudio™ S5 in conjunction with MSI detection is informative and potentially predictive for the use of checkpoint inhibitors in multiple cancer types.

Citation Format: Warren Tom, Ruchi Chaudhary, Vinay Mittal, Dinesh Cyanam, Iris Casuga, Elaine Wong-Ho, Rob Bennett, Fiona Hyland, Seth Sadis, Janice Au-Young. Improvement of tumor mutation burden measurement by removal of deaminated bases in FFPE DNA [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 1701.
Abstract 1703: New genetic variations discovered in KRAS wild-type cetuximab resistant Chinese colorectal cancer patients
Authors: Jing Changwen , Wang Ting , Ma Rong , Cao Haixia , Xu EnShun , Wang Zhuo , Liu Siwen , Chen Dan , Zhang Junying , Wu Yang , Zhang Yuan , Ding Ping , Sha Michael Y. , Wu Jianzhong , Feng Jifeng
Published: August 2019

The efficacy of Cetuximab therapy in colorectal cancer patients is limited by the development of therapeutic resistance. The currently known oncogenic ‘driver’ mutations do not fully explain the resistance mechanism of Cetuximab. Currently there are no reports of any studies that have explored new driver mutations in Cetuximab resistance by whole exome sequencing (WES).

In this study, we performed WES to identify common genetic factors from twenty-two Cetuximab-sensitive and ten Cetuximab-resistant patients, aiming to discover characteristic genes associated with Cetuximab resistance. For Cetuximab-sensitive patients, the mutation frequency of MUC16, FCGBP, DMBT1 was found to be 100%, 90.91% and 86.36%, respectively. MUC16, PDE4DIP and TACC2 were altered in all 10 Cetuximab-resistant samples. We also discovered there are 151 significantly mutated genes (SMGs) in Cetuximab sensitive group and 37 in the resistant group. CYP4A11 was the most frequently mutated gene in Cetuximab-resistant patients. BCAS1, GOLGA6L1 and WNT16 were found to be the second group of frequently mutated genes which found in to occur at a frequency of 60% in resistant patients. After cosine similarity analysis with 30 known signatures, three mutational signatures (signature a, b and c) were found in all CRC tumors, similar to Signature 1, 5 and 6 in COSMIC, respectively. Gene ontology analysis was performed on SMGs and found twelve enriched GO terms. Four genes are enriched in six specific KEGG pathway groups, such as metabolism of xenobiotics by cytochrome P450, Steroid hormone biosynthesis, retinol metabolism and drug metabolism. In conclusion, we show that the establishment of a WES clinical study of Cetuximab resistance CRC with prospective follow-up of patients can help to identify candidate predictive biomarkers of response.

Note: This abstract was not presented at the meeting.

Citation Format: Changwen Jing, Ting Wang, Rong Ma, Haixia Cao, EnShun Xu, Zhuo Wang, Siwen Liu, Dan Chen, Junying Zhang, Yang Wu, Yuan Zhang, Ping Ding, Michael Y. Sha, Jianzhong Wu, Jifeng Feng. New genetic variations discovered in KRAS wild-type cetuximab resistant Chinese colorectal cancer patients [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 1703.
Abstract 1708: An integrated framework for genome analysis reveals numerous previously unrecognizable structural variants in leukemia patients’ samples
Authors: Broach James R. , Xu Jie , Schleicher Emily , Pool Christopher , Hennessy Max , Sheldon Kathryn , Annageldiyev Charyguly , Sharma Arati , Chang Yuanyuan , Hastie Alex , Miller Barbara , Goldenberg David , Claxton David , Moldovan George-Lucian , Yue Feng
Published: August 2019

We have applied a combination of whole genome sequencing and optical genomic mapping to a number of adult and pediatric leukemia samples, which revealed in each of these samples a large number of structural variants not recognizable by current standard genomic analyses. We developed computational methods to determine which of those variants likely arose as somatic mutations. The method identified 97% of the translocations previously reported by karyotype analysis of these samples and revealed an additional fivefold more such somatic rearrangements. The method identified on average tens of previously unrecognizable inversions and duplications and hundreds of previously unrecognizable insertions and deletions. These structural variants affected a number of leukemia associated genes as well as cancer driver genes not previously associated with leukemia and genes not previously associated with cancer. A number of variants only affected intergenic regions but caused cis-acting alterations in expression of neighboring genes. Analysis of TCGA data indicates that several of the recurrently mutated genes significantly affect survival of AML patients. Our results suggest that current genomic analysis methods fail to identify a majority of structural variants in leukemia samples and this lacunae may hamper diagnostic and prognostic efforts.

Note: This abstract was not presented at the meeting.

Citation Format: James R. Broach, Jie Xu, Emily Schleicher, Christopher Pool, Max Hennessy, Kathryn Sheldon, Charyguly Annageldiyev, Arati Sharma, Yuanyuan Chang, Alex Hastie, Barbara Miller, David Goldenberg, David Claxton, George-Lucian Moldovan, Feng Yue. An integrated framework for genome analysis reveals numerous previously unrecognizable structural variants in leukemia patients’ samples [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 1708.
Abstract 1713: Molecular dissection of Zc3h8 functional domains and the implications for the oncogenic phenotype
Authors: Schmidt John A. , Doan Tyler , Irizarry Emanuel , Harris Emily , Danielson Keith G. , Knepper Janice E.
Published: August 2019

Zc3h8 encodes a zinc finger protein that is amplified in 2-6% of human breast tumors. Higher expression of Zc3h8 also results in lower rates of disease-free survival. Amplification of Zc3h8 expression has been shown to increase cell proliferation, migration, invasion and tumor growth in mice. Conversely, decreased expression alters cell behavior by decreasing cell proliferation, migration, invasion, and tumor growth in mice. Zc3h8 comprises three CCCH non-classical zinc finger domains at the C-terminus of the protein that we hypothesize bind to RNA. The interactions between Zc3h8 and nucleic acids may be important for the localization and/or function of Zc3h8 and therefore may be important for the cellular phenotypes observed when the gene is over or under expressed in cells. We used in vitro and in vivo assays to demonstrate that mutations in any of the three zinc finger domains results in a protein that fails to rescue aggressive cellular phenotypes in cells with reduced expression of Zc3h8, while the wild type protein can rescue these phenotypes. This implies that all three zinc finger domains are required for Zc3h8 function in promoting rapid and aggressive cell proliferation. In addition to zinc finger domains, Zc3h8 also contains a casein kinase-2 (CK2) phosphorylation site that may be important for protein localization and/or activation. We have previously shown that CK2 inhibitors alter Zc3h8 localization to nuclear PML Bodies. Mouse cells overexpressing Zc3h8 with a Thr to Ala (T32A) change that prevents CK2 phosphorylation grow very slowly in culture and cannot grow in more challenging 3D or soft agar growth chambers. However, Zc3h8 with a Thr to Glu (T32E) change that mimics constitutive CK2 phosphorylation results in rapidly growing cells that surpass overexpression of Zc3h8 wild type. Zc3h8 phospho-mutants also have altered localization with Zc3h8 T32E becoming diffuse in the nucleus and T32A localizing to nuclear foci. These data suggest that the phosphorylation state of Zc3h8 and its ability to bind nucleic acids via zinc finger domains are critical for the oncogenic behavior that results from amplified expression. We also hypothesize that Zc3h8 has an important role in establishing or maintaining PML Bodies involved in genome maintenance, transcription, and/or post-transcription regulation.

Citation Format: John A. Schmidt, Tyler Doan, Emanuel Irizarry, Emily Harris, Keith G. Danielson, Janice E. Knepper. Molecular dissection of Zc3h8 functional domains and the implications for the oncogenic phenotype [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 1713.
Abstract 1715: Sox2 is required for tumor initiation and maintenance in small cell lung cancer
Authors: Voigt Ellen , Thompson Ethan , Wollenzien Hannah , Kamp Madeline Vande , Kareta Michael S.
Published: August 2019

Some cancer prognoses have been radically improved in recent years, but little headway has been made with others. One of these diseases, small cell lung cancer (SCLC,) has a five-year survival rate of less than 7% and a standard of care that has been essentially unchanged for forty years. One promising avenue to improve SCLC outcomes is to understand the cancer’s underlying genetic alterations that drive its formation and growth. One primary driver of SCLC, is the loss of Rb gene function, one of the most common occurrences in human cancers. Normally Rb promotes differentiation by regulating lineage specific transcription factors concurrent with repression of the pluripotency factors such as Sox2. However, there is evidence that when certain tissues lose Rb, Sox2 becomes upregulated and promotes oncogenesis. To understand the contribution of Sox2 to SCLC, we have utilized a genetically engineered mouse model for SCLC to determine the consequence of Sox2 on SCLC tumor initiation and growth. We observe that Sox2 is indeed required for SCLC. Further elucidation of the Sox2 network in SCLC could identify candidates for future targeted therapies in this devastating disease.

Citation Format: Ellen Voigt, Ethan Thompson, Hannah Wollenzien, Madeline Vande Kamp, Michael S. Kareta. Sox2 is required for tumor initiation and maintenance in small cell lung cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 1715.
Abstract 1726: Structure-function analysis of retinoblastoma tumor suppressor protein in human cone precursors
Authors: Wang Sijia , Grubbs Brendan , Thornton Matthew , Cobrinik David
Published: August 2019

Background: The retinoblastoma protein, pRB, is a key cell cycle governor that is functionally impaired in most cancers, but its mechanism of suppressing tumorigenesis in a tumor cell-of-origin has not been characterized. This study aims to define pRB structural features and corresponding cellular functions that suppress cone precursor (CP) proliferation, likely the first step in retinoblastomagenesis.

Method: Intact human fetal retinae were co-transduced with lentiviruses to knockdown endogenous pRB and ectopically express wild type or structure-based substitution mutant pRBs. The ectopically expressed pRB mutants had selectively impaired interactions with E2F transactivation domains (ΔG), with the E2F1 “marked box” domain (ΔS), or with the LxCxE protein interaction motif (ΔL). At day 12-75 post-infection, transduced retinae were analyzed by quantitative immunofluorescence staining of Ki67/EdU, pRB and CP marker L/M-opsin.

Results: In intact retina, pRB knockdown induced cell cycle re-entry of L/M-opsin+ postmitotic cone precursors, whereas those reconstituted with wild type pRB did not express Ki67 indicative of a block to cell cycle entry. Unexpectedly, all three mutants (pRB-ΔG, -ΔL, and -ΔS) were able to block cell cycle re-entry when expressed at the high-normal range the of endogenous pRB. However, at the low-normal expression level, ectopic wild type but not mutant pRBs suppressed proliferation.

Conclusion: All three surface targeted mutants (pRB-ΔG, ΔL, and ΔS) retain partial ability to suppress cone precursor cell cycle entry. This may be attributed to the presence of multiple independent cell cycle inhibitory functions. These findings suggest that pRB-mediated regulation of E2F-responsive cell cycle genes, interactions with LxCxE motif-containing proteins, and EZH2 mediated repression of repetitive elements are individually dispensable for suppressing aberrant cone precursor proliferation.

Citation Format: Sijia Wang, Brendan Grubbs, Matthew Thornton, David Cobrinik. Structure-function analysis of retinoblastoma tumor suppressor protein in human cone precursors [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 1726.
Abstract 1740: Characterization of CDK9 role in the DNA damage response
Authors: Nepomuceno Thales C. , Suarez-Kurtz Guilherme , Monteiro Alvaro N. , Carvalho Marcelo A.
Published: August 2019

Introduction: The DNA damage response (DDR) is a well-coordinated pathway capable of sensing and repairing different types of DNA damage. Double-strand break (DSB) lesions activate the ATM-CHK2 axis, which is responsible for the cell cycle arrest, prompting cells for DNA repair. DSBs are primarily repaired through two distinct pathways: homology-directed recombination (HR) and non-homologous end-joining (NHEJ). BRCA1 and 53BP1 play an important role in DDR by orchestrating the decision between HR and NHEJ, but the precise mechanisms regarding both pathways are not entirely understood. Previously, our group identified the putative interaction of the cyclin-dependent kinase 9 (CDK9) with BRCA1 and BARD1 (BRCA1-associated RING domain 1). CDK9 is a component of the positive transcription elongation complex and has been implicated in genome integrity maintenance associated with the replication stress response. More recently, we characterized CDK9 as a DDR player by modulating BRCA1 recruitment to DNA damaged sites and consequently the HR pathway. We also showed that cells lacking CDK9 failure to form RAD51, but not 53BP1, ionizing radiation-induced foci (IRIF) and are characterized by an increased sensitivity to DSBs

Methods and Results: Here we show that the CDK9-BRCA1 interaction occurs through BRCA1 N-terminal region in a BRCA1-BARD1 heterodimer formation-dependent manner. We also identified a CDK9 mutant (E369A) that abrogates the CDK9-BRCA1 interaction (through BRCA1 C-terminal region). Moreover, we characterized CHK2 as a novel CDK9-interaction partner, through ectopic GST-pulldown and constitutive co-immunoprecipitation assays. Further, cells lacking CDK9 are deficient in promoting G2/M arrest after IR-induced DNA damage. We also identified new CDK9 interactions in a DDR-related context using a TAP-MS approach.

Conclusion: Collectively, our data suggest a role for CDK9 in the DDR through DNA damage repair and cell cycle checkpoint regulation

Citation Format: Thales C. Nepomuceno, Guilherme Suarez-Kurtz, Alvaro N. Monteiro, Marcelo A. Carvalho. Characterization of CDK9 role in the DNA damage response [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 1740.
Abstract 1743: Evaluating the effect of USP22 depletion on chromosome instability in colorectal cancer
Authors: Jeusset Lucile M. , McManus Kirk J.
Published: August 2019

Chromosome instability (CIN) is an aberrant phenotype defined as an increase in the rate at which whole chromosomes or large chromosomal fragments are gained or lost, and is observed in virtually all cancer types. Although CIN is associated with aggressive tumors, multi-drug resistance and poor patient prognosis, the genetic defects underlying CIN remain poorly understood. Preliminary data from our laboratory suggest that diminished USP22 (Ubiquitin-Specific Peptidase 22) expression induces CIN. Importantly, USP22 deletions and reduced USP22 expression are frequently observed in multiple cancer types, including colorectal cancer, suggesting diminished USP22 expression/function may be a pathogenic event underlying oncogenesis. Therefore, the present study seeks to evaluate the impact diminished USP22 expression has on CIN by determining whether karyotypically stable colorectal cancer (HCT116) and immortalized fibroblast (hTERT) cell lines can be converted into karyotypically unstable lines following the reduction of USP22 expression. Diminished USP22 expression was achieved by siRNA-based silencing or CRISPR-Cas9-mediated gene knockout (KO) and quantitative image-based single-cell analyses were employed to monitor changes in surrogate markers for CIN, including nuclear areas and chromosome numbers. USP22 silencing induced significant changes in nuclear area as well as increased frequencies of chromosomes gains and losses, which suggest USP22 is a CIN gene. Next, to assess the long-term impact diminished USP22 expression has on CIN, two HCT116 USP22-KO clones were monitored for 10 weeks and revealed dynamic changes in nuclear areas and chromosome numbers over time relative to controls. Collectively, these data identify USP22 as a novel CIN gene and indicate that USP22 deletions in cancer may have long-term impact on CIN and may thereby promote oncogenesis. Further analysis is ongoing to investigate the mechanism through which USP22 depletion induces CIN, and in particular its effect on H2B monoubiquitination. Characterizing the effect diminished USP22 expression has on CIN is the first step towards the development of therapeutic strategies targeting USP22-deficient cancers.

Citation Format: Lucile M. Jeusset, Kirk J. McManus. Evaluating the effect of USP22 depletion on chromosome instability in colorectal cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 1743.
Abstract 1744: SAMHD1 expression and impact on clinical outcome in diffuse large B-cell lymphoma: a potential therapeutic target
Authors: Daddacha Waaqo
Published: August 2019

Diffuse large B-cell lymphoma (DLBCL) is the most common subtype of non-Hodgkin lymphoma. While standard treatment with rituximab, cyclophosphamide, doxorubicin, vincris- tine, and prednisone (R-CHOP) can cure DLBCL, failed patients have poor outcome. Thus, a search for stand-alone or adjuvant therapy to improve patient’s outcome is important. Sam and HD domain-containing protein 1 (SAMHD1) is a well-established deoxyribonucleotide triphosphate (dNTP) triphosphohydrolase. Its dNTPase activity has been associated with cellular defence mechanism against infection by depleting cellular dNTP pool bellow level required for viral replication. SAMHD1 mutations have been associated with Aicardi Goutières (AGS) and cancers such as chronic lymphocytic leukemia (CLL), demonstrating its relevance beyond viral infection. In addition, it has been shown that SAMHD1 expression in Recently, our lab has defined a novel role for SAMHD1 in DNA end resection to facilitate DNA double strand break (DSB) repair by homologous recombination (HR). SAMHD1 expression and its diagnostic or therapeutic relevance in DLBCL is not known. Thus, we analyzed SAMHD1 expression in patients with DLBCL and determined its correlation with clinical outcome. In addition, we studied the SAMHD1 expression in germinal center B cell (GCB) and activated B cell (ABC) DLBCL cells lines. Also, we examined the possibility of depleting SAMHD1 using a virus like particles (VLPs) containing viral protein x (Vpx) in DLBCL cell lines. Finally, we determined the effect on cells sensitivity to standard DLBCL therapy, R-CHOP, and other DNA damage inducing agents. Low SAMHD1 expression correlates with improved overall survival. SAMHD1 was downregulated in ABC as compared to GCB DLBCL cell lines and SAMHD1 depletion sensitizes DLBCL cell lines to R-CHOP and other DNA damage inducing agents. These findings suggest that SAMHD1 is a potential therapeutic target to improve the DLBCL patient’s clinical outcome.

Citation Format: Waaqo Daddacha. SAMHD1 expression and impact on clinical outcome in diffuse large B-cell lymphoma: a potential therapeutic target [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 1744.