bluuebunny/crossref_metadata_2025_split huggingface dataset:
Abstract 6379: Dipeptidyl peptidase-4 inhibitor impairs the outcomes of patients with type 2 diabetes mellitus after curative resection for colorectal cancer
Authors: Saito Akira , Ohzawa Hideyuki , Kaneko Yuki , Tamura Kohei , Futoh Yurie , Takahashi Kazuya , Kimura Yuki , Tojo Mineyuki , Kawashima Rie , Miyato Hideyo , Sata Naohiro , Kitayama Joji 
Published: June 2022

Abstract
Background: Type2 diabetes mellitus(T2DM) is a risk factor for cancer. Recent studies have shown that DPP-4 inhibitor(DPP-4i) can either promote or suppress cancer progression. However, the detailed mechanisms remain unknown. Here, in this study, we investigated the effect of DPP-4i on tumor microenvironment and its effect on the prognosis of cancer patients.
Method: We retrospectively examined the outcome of colorectal cancer (CRC) patients with T2DM who received curative surgery in Jichi Medical University Hospital and asked the impact of DPP-4i intake on their outcome. In addition, we performed immunohistochemistry to examine the phenotypes of TIL, TAM and epithelial-mesenchymal transition (EMT) of cancer cells in surgically removed CRC tissues in 40 CRC patients who had taken DPP-4i and propensity score-matched 40 patients who had not.
Results: A total of 1696 patients underwent curative colectomy from April 2010 to March 2020. Among them, 260 patients had T2DM at the time of surgery, and 135 patients had been treated with drugs including DPP-4i. The postoperative disease-free survival rate (DFS) was significantly worse in the DPP-4i intake group compared with non-intake group (5 year DFS 18.5% vs 5.4%, HR=2.0, p&lt;0.05). The number of Zeb1-positive tumor cells significantly increased in DPP-4i intake group. (Median(M)=29.0 (0-189)/mm2 vs 9.0 (0-71)/mm2, p&lt;0.01). The number of CD3 (+) TIL in DPP-4i intake group was Median(M)=277.4(min 121.6-max 523.2)/mm2 which was significantly lower than those in non-intake group (M= 319.6, min 493.0-max 823.6/mm2). CD8(+) TIL in DPP-4i intake was reduced more significantly than in non-intake group (M=187.6, min 67.8-max 347.4/mm2 vs M=336.8, min 200.2-max 588.4/mm2, p&lt;0.05) with less CD8/CD3 ratio (61.2% vs 67.1%, p&lt;0.05). On the other hand, the density of CD68(+)CD163(+) TAM was significantly higher(M=202.6, min 122.8-max 257.0/mm2 vs M=126.6, min 94.8-max 247.6/mm2, p&lt;0.05) in DPP-4i intake group.
Conclusion: DPP-4i increases the number of M2-type TAM while decreases the number of effector TIL and promote EMT of cancer cells in tumor microenvironment, which might lead to the poor outcome of the patients with CRC.
Citation Format: Akira Saito, Hideyuki Ohzawa, Yuki Kaneko, Kohei Tamura, Yurie Futoh, Kazuya Takahashi, Yuki Kimura, Mineyuki Tojo, Rie Kawashima, Hideyo Miyato, Naohiro Sata, Joji Kitayama. Dipeptidyl peptidase-4 inhibitor impairs the outcomes of patients with type 2 diabetes mellitus after curative resection for colorectal cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 6379.
Abstract 6394: The SB Image Processing Toolkit: Machine learning for cancer research on the CGC
Authors: Koc Soner , Babic Jovana , Nikolic Nevena , Stankovic Ana , Ventre Daniel , Ray Manisha , Worman Zelia F. , Subramanian Sai Lakshmi , Dean Dennis A. , DiGiovanna Jack , Dusenbery Brandi Davis 
Published: June 2022

Abstract
Applying machine learning algorithms to analysis of multi-omics datasets has provided a wealth of analysis and interpretations of data not easily achievable by conventional methods. The Cancer Genomics Cloud (CGC), powered by Seven Bridges, offers many helpful features to simplify and streamline the performance of machine learning (ML) tasks on the platform. The CGC platform contains features and tools for all of the steps of a ML project, from data exploration, to model generation, to production, so that all key steps occur on the platform. The Data Cruncher interactive analysis tool enables users to perform data exploration, modeling, training, and visualization using familiar frameworks like Jupyterlab and RStudio. We applied this ML methodology to imaging tools, to create The SB Image Processing Toolkit. Here we demonstrate the use of this toolkit with specific cancer datasets, including training and analysis, with all steps taking place on the cloud.
The SB Image Processing Toolkit is a collection of various deep-learning, preprocessing, and utility tools and workflows created with the purpose of performing image class prediction on any type of image data. The toolkit supports a variety of images used in cancer research, such as histopathology and radiology images, and common formats like JPG or PNG. There are nine distinct tools within the toolkit, including methods for quality control, normalization, preprocessing for histopathology or radiology images, classification, and deep learning. Together, these tools create an easy-to-use infrastructure to enable various stages of ML and Image Processing. Most importantly, it was designed to enable users to create and use ML image classifiers on the CGC without any coding experience. All workflows can be searched for and implemented via the Public Apps Gallery on the CGC. Users can import image data, run analysis, and compare results all in one environment.
By harnessing the scale and flexibility of cloud computing, the SB Image Processing Toolkit brings massive speed and price improvements compared to manual writing and running model training scripts. In conjunction with the access to data and ease of use, the CGC makes complex machine learning methods accessible to any researcher.
Citation Format: Soner Koc, Jovana Babic, Nevena Nikolic, Ana Stankovic, Daniel Ventre, Manisha Ray, Zelia F. Worman, Sai Lakshmi Subramanian, Dennis A. Dean, Jack DiGiovanna, Brandi Davis Dusenbery. The SB Image Processing Toolkit: Machine learning for cancer research on the CGC [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 6394.
Abstract 642: Spatial analysis of tumor infiltrating lymphocytes in histological images using deep learning predicts progression-free survival in colorectal cancer
Authors: Xu Hongming , Cha Yoon Jin , Clemenceau Jean , Choi Jinhwan , Lee Sung Hak , Kang Jeonghyun , Hwang Tae Hyun 
Published: June 2022

Abstract
Histological distribution and density of tumor infiltrating lymphocytes (TILs) are known to be informative to cancer patients’ outcome. However, due to the heterogeneity and huge size of digitized pathology slides, it has been a challenging problem to quantify TILs-related features in whole slide images (WSI). This study aimed to explore the impact of spatial distribution of TILs quantified by deep learning (DL) approaches based on digitalized WSI stained with hematoxylin and eosin in patients with colorectal cancer (CRC). The cancer and TILs regions are first separately identified by deep learning models in the WSI. The TILs densities at tumor invasive margins are then quantified by image analysis algorithms and used for prognosis of progression-free survival (PFS) in CRC patients. The prognostic impact of spatial distributions of TILs in CRC patients was explored in the Yonsei cohort (n=180) and validated in the TCGA cohort (n=268). Two experienced pathologists manually measured TILs at the most invasive margin as 0-3 by the Klintrup-Mäkinen (KM) grading method and compared to DL approaches. On multivariate analysis, TILs densities within 200µm of the invasive margin (f_im200) was remained as the most significant prognostic factor for PFS (HR 0.004 [95% CI, 0.0001-0.1502], p=.002) in the Yonsei cohort. On multivariate analysis using the TCGA dataset, f_im200 retained prognostic significance for PFS (HR 0.031, [95% CI 0.001-0.645], p=.024). Inter-observer agreement of manual KM grading was insignificant in both cohorts. The survival analysis by pathologists’ manual KM grading showed statistically significant different PFS from the TCGA cohort, but not the Yonsei cohort. In summary, automated quantification of TILs at the invasive margin showed a prognostic utility to predict PFS, and could provide reproducible TILs density measurement in CRC patients.
Citation Format: Hongming Xu, Yoon Jin Cha, Jean Clemenceau, Jinhwan Choi, Sung Hak Lee, Jeonghyun Kang, Tae Hyun Hwang. Spatial analysis of tumor infiltrating lymphocytes in histological images using deep learning predicts progression-free survival in colorectal cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 642.
Abstract 655: Macrophage mediated resistance to TKI therapy in ALK fusion positive non-small cell lung cancer
Authors: Mandell Melanie , Priest Katherine , Le Anh , Heasley Lynn , Nemenoff Raphael , Schenk Erin L. 
Published: June 2022

Abstract
Patients with lung cancer bearing driver oncogenes such as epidermal growth factor receptor (EGFR) mutations or anaplastic lymphoma kinase (ALK) fusions, often experience long term disease control on targeted therapy. Despite excellent initial responses, ultimately these tumors develop resistance to targeted therapy. While several cancer cell intrinsic mechanisms of targeted therapy resistance are well known, they do not account for all cases of resistance. Based on our previous observations, we hypothesized components of the tumor microenvironment, specifically monocytes and macrophages, also contribute to the development of targeted therapy resistance. We generated bone marrow derived macrophages from C57BL/6 mice and polarized them to an M0, M1, or M2 phenotype over the course of 6 days. At day 7, cells were plated in fresh media and after 2 days, the conditioned media (CM) was collected. Macrophage polarization was verified via qPCR. Murine cell lines, EA-1, EA-2, and EA-3 are unique, murine lung adenocarcinomas bearing an oncogenic ALK fusion derived from C57BL/6 mice. These murine cell lines were then cultured in the macrophage CM prior to exposure to ALK fusion specific tyrosine kinase inhibitors (TKI), alectinib or crizotinib. We observed that culture in M2-CM resulted in at least a 10-fold increase in alectinib resistance across all 3 murine cell lines when compared to the same cell lines cultured in M1 or M0-CM. We next tested for the activity of known, clinically relevant bypass signaling pathways as mediator of M2-CM protection. Aftatinib, an inhibitor of EGFR and human epidermal growth factor receptor 2 (HER2) family of proteins, did not alter M2-CM protection in the presence of alectinib. M2-CM did not impart TKI resistance to the murine cell lines in the presence of crizotinib, a TKI which inhibits ALK fusion activity and MET receptor tyrosine kinase activity, suggesting bypass signaling through MET drives the M2-CM resistance. Ongoing animal model studies demonstrate a clear role for innate immune cells in decreasing tumor responsiveness to TKI. In summary, our work demonstrates TKI therapy may be modulated by the presence of and interaction with specific immune cells within the tumor microenvironment. These data support exploring macrophage targeting therapies to improve TKI responsiveness.
Citation Format: Melanie Mandell, Katherine Priest, Anh Le, Lynn Heasley, Raphael Nemenoff, Erin L. Schenk. Macrophage mediated resistance to TKI therapy in ALK fusion positive non-small cell lung cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 655.
Abstract 780: Transcriptional profile of human pancreatic acinar ductal metaplasia
Authors: Perkins Corey Melissa , Jiang Jinmai , Hakimjavadi Hesamedin , Bray Julie K. , Gosling Alyssa , da Silva Lais , Bulut Gamze , Ali Jamel , Setiawan Wendy , Campbell-Thompson Martha , Chamala Srikar , Schmittgen Thomas D. 
Published: June 2022

Abstract
Aberrant acinar to ductal metaplasia (ADM), one of the earliest events involved in exocrine pancreatic cancer development, is typically studied using pancreata from transgenic mouse models. We used primary, human pancreatic acinar cells to evaluate the transcriptional profile during the course of ADM. Following six days of culture on Matrigel, acinar cells underwent morphological and molecular changes reminiscent of ADM. RNA was sequenced from 14 donor’s paired pancreata (day 0 and 6 of culture). Unsupervised hierarchical clustering demonstrated complete separation of the gene expression profile between culture day 0 (acinar phenotype) and day 6 (ductal phenotype). By and large, acinar-specific genes were downregulated in the samples from day 6 ADM while ductal-specific genes were upregulated. Using a gene set enrichment approach, we identified regulons that are involved in regulating ADM including downregulated, acinar-associated transcription factors (including PTF1A, RBPJL, and XBP1) and upregulated, ductal- and progenitor-associated transcription factors (SOX11, SOX4, and YAP1). The expression of pancreatic cancer associated genes significantly correlated with the gene expression/regulon activity observed in normal pancreas undergoing ADM. We reported a detail analysis of the transcriptional profile during human ADM. Our findings confirm that many ADM-related transcription factors and signaling pathways discovered in transgenic mouse models are applicable to human ADM and highlights the relevancy of in vitro models of pancreas plasticity using human tissue.
Citation Format: Corey Melissa Perkins, Jinmai Jiang, Hesamedin Hakimjavadi, Julie K. Bray, Alyssa Gosling, Lais da Silva, Gamze Bulut, Jamel Ali, Wendy Setiawan, Martha Campbell-Thompson, Srikar Chamala, Thomas D. Schmittgen. Transcriptional profile of human pancreatic acinar ductal metaplasia [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 780.
Abstract 803: Identifying a RAD18/UBC13-dependent mechanism of replication fork recovery to modulate chemoresponse in BRCA1-deficient cancers
Authors: Cybulla Emily , Jackson Jessica , Tirman Stephanie , Quinet Annabel , Lemacon Delphine , Vindigni Alessandro 
Published: June 2022

Abstract
Mutations in the breast cancer susceptibility genes BRCA1 and BRCA2 are associated with an increased lifetime risk of breast and ovarian cancers. While the BRCA proteins play a well-established role in double-stranded DNA break repair, recent studies have revealed an emerging role of BRCA1/2 in replication stress response. While replication forks are extensively degraded by nucleases in BRCA-deficient cancer cells, activation of specialized fork recovery mechanisms enables resumption of DNA synthesis and promotes cell survival. My project aims to determine this fork recovery mechanism in BRCA1-deficient cells and to identify potential recovery factors that can be targeted to improve chemotherapeutic response in BRCA1-mutated breast and ovarian cancers. To monitor perturbations in replication fork dynamics on a genome-wide scale, we utilize a DNA fiber assay technique measuring rates of fork recovery and replication fork degradation. In parallel, electron microscopy analysis allows direct visualization of replication fork intermediates. Cell survival assays are employed to test how loss of fork recovery factors impacts cell proliferation and chemotherapeutic response in BRCA1-deficient cells. Our results reveal that RAD18 and UBC13, which catalyze ubiquitination of Proliferating Cellular Nuclear Antigen (PCNA), promote fork recovery in BRCA1-deficient, but not BRCA2-deficient, cancer cells. Previous work has also shown that PCNA polyubiquitination by UBC13 is important for reversed fork formation in BRCA-proficient cells. However, our findings show that extensive degradation of reversed fork substrates still occurs in BRCA1-deficient cells lacking RAD18 or UBC13, indicating that PCNA polyubiquitination is not essential for fork reversal in this genetic background. In addition, loss of RAD18 in BRCA1-deficient cells significantly slows cell proliferation, and UBC13 inhibition further sensitizes cells lacking BRCA1 to the replication stress inducer Hydroxyurea (HU). Based on our findings, we hypothesize that RAD18, UBC13, and PCNA ubiquitination may represent novel targets to improve chemoresponse in BRCA1-deficient cancers that rely on fork recovery mechanisms for survival.
Citation Format: Emily Cybulla, Jessica Jackson, Stephanie Tirman, Annabel Quinet, Delphine Lemacon, Alessandro Vindigni. Identifying a RAD18/UBC13-dependent mechanism of replication fork recovery to modulate chemoresponse in BRCA1-deficient cancers [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 803.
Abstract 817: microRNA-26a-5p is a prognostic factor that regulates cancer stemness
Authors: Kang Daeun , Park Chang Ryul , Lee Minhyeok , Lee Su Yel , Park Se Jin , Hwang Wan Jin , Ku Gwan Woo , Yu Seong Lan , Jeong In Beom , Kwon Sun Jung , Kang Jaeku , Lee Eung Bae , Son Ji Woong 
Published: June 2022

Abstract
Background: Cancer stem cells (CSCs) identified in lung cancer exhibit resistance to chemotherapy, radiotherapy, and targeted therapy. Therefore, a technology to control of CSCs is needed to overcome such resistance to cancer therapy. Various evidences about the association between epithelial-mesenchymal transition related transcriptomic alteration and acquisition of CSC phenotype have been proposed recently. In our previous research, down-regulated miR-26a-5p is closely related to mesenchymal-like lung cancer cell lines. These findings suggest that miR-26a-5p might be involved in lung cancer stemness.
Methods: RNA polymerase III subunit G (POLR3G) was selected as a candidate target of miR-26a-5p related to cancer stemness. its quantitative relationship was investigated by polymerase chain reaction, western blot after transfection of miR-26a-5p. luciferase assay were done for investigating the direct regulation of miR-26a-5p on POLR3G expression. After transfection of miR-26a-5p, colony formation assay and sphere formation assay were performed to evaluate the effect on cancer stemness. By treating cancer cell by miR-26a-5p and paclitaxel, cell viability was checked by 3-(4,5-dimethylthiazol-2-yl)-5-(3-carboxymethoxyphenyl)-2-(4-sulfophenyl)-2H-tetrazolium (MTS) assay and Muse cell analyzer. Expression level of each gene and its impact on survival were revealed by the cancer genome atlas pancancer database.
Results: miR-26a-5p regulated the expression of POLR3G directly. Overexpression of miR-26a-5p induced down regulation of POLR3G and a marked reduction of colony formation and sphere formation. Co-treatment of miR-26a-5p with paclitaxel decreased cell growth, suggesting that miR-26a-5p might play a role as a chemotherapy sensitizer. In the cancer genome atlas data, down-regulated miR-26a-5p and up-regulated POLR3G were shown compared to adjacent normal tissue. High miR-26a-5p and low POLR3G expression were also related to higher survival rate of patients with lung adenocarcinoma.
Conclusions: Overexpression of miR-26a-5p can suppress lung cancer stemness and make cancer cell become sensitive to chemotherapy. This finding provides a novel insight into a potential lung cancer treatment by regulating stemness.
Citation Format: Daeun Kang, Chang Ryul Park, Minhyeok Lee, Su Yel Lee, Se Jin Park, Wan Jin Hwang, Gwan Woo Ku, Seong Lan Yu, In Beom Jeong, Sun Jung Kwon, Jaeku Kang, Eung Bae Lee, Ji Woong Son. microRNA-26a-5p is a prognostic factor that regulates cancer stemness [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 817.
Abstract 830: ZFP14, a p53 target, suppresses tumor formation by regulating HOXA gene cluster expression
Authors: Mohibi Shakur , Zhang Jin , Chen Mingyi , Chen Xinbin 
Published: June 2022

Abstract
KRAB containing zinc finger proteins form the largest class of mammalian transcription factors. However, the physiological or pathological functions of the majority of them are unknown. Here, we established ZFP14 as a p53 target gene that is induced upon genotoxic stress in a p53-dependent manner. To determine the function of ZFP14 in mouse and human cancer cell lines, we generated ZFP14-KO cells that showed increased senescence as well as reduced cell growth and migration. Moreover, we showed that ZFP14 negatively regulates p53, which was the cause of reduced oncogenic properties in ZFP14-KO cancer cells. Mechanistically, we found that ZFP14 modulates p53 protein stability by associating with and possibly enhancing MDM2/p53 complex integrity through its zinc finger domains. Interestingly, we found that lower expression of ZFP14 correlates with poor patient survival in multiple human cancers. Notably, in a similar fashion, mice deficient in ZFP14 were susceptible to spontaneous tumor formation, developed other abnormalities such as systemic inflammation and liver steatosis, which led to their shorter lifespan. Finally, we showed that ZFP14 regulates the expression of the HOXA gene cluster in mouse and humans, which we propose as a possible mechanism by which ZFP14 regulates tumorigenesis. Our findings suggest that ZFP14 is an important regulator of p53 and HOXA genes during inflammation and tumorigenesis.
Citation Format: Shakur Mohibi, Jin Zhang, Mingyi Chen, Xinbin Chen. ZFP14, a p53 target, suppresses tumor formation by regulating HOXA gene cluster expression [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 830.