bluuebunny/crossref_metadata_2025_split huggingface dataset:
Abstract 2137: Differential gene expression identifies a transcriptional regulatory network involving ESR1and PITX1 in invasive epithelial ovarian cancer
Authors: Li Yichao , Jaiswal Sushil Kumar , Kaur Rupleen , Alsaadi Dana , Liang Xiaoyu , Drews Frank , DeLoia Julie A. , Krivak Thomas , Petrykowska Hanna M. , Gotea Valer , Welch Lonnie , Laura Elnitski 
Published: July 2021

Abstract
The heterogeneous subtypes and stages of epithelial ovarian cancer (EOC) differ in invasive processes, but the molecular factors that drive aggressive behavior remain nebulous. In this study, we analyzed two types of EOC at opposite ends of the invasiveness spectrum, high-grade serous ovarian cancers (HGSOCs) and serous borderline tumors (SBTs). We identified differentially expressed genes to guide follow on studies of regulatory networks. Initially, in a discovery sample set, we generated transcriptome sequences to identify 11 differentially expressed genes in SBTs and HGSOCs, and a nonoverlapping set of 17 differentially expressed genes stage II and stage III HGSOCs. We validated the classification performance of these gene expression signatures on a validation set of SBT and HGSOC with classification rates of 94 and 98% using the 11-gene and 17-gene sets, respectively. Transcription factor binding sites enriched in the differentially expressed gene promoter regions were examined by Chip-seq analysis in ovarian cancer and other cell lines. We identified a suite of transcription factors implicated in the differential regulation associated with invasiveness, including ERα, RARA, PITX1, FOXA1/FOXF1, and BHLHE41/E40. These data implicate estrogen responsive gene regulatory networks in ovarian cancers and suggest that dynamic regulatory interactions determine malignant EOC outcomes.
Citation Format: Yichao Li, Sushil Kumar Jaiswal, Rupleen Kaur, Dana Alsaadi, Xiaoyu Liang, Frank Drews, Julie A. DeLoia, Thomas Krivak, Hanna M. Petrykowska, Valer Gotea, Lonnie Welch, Elnitski Laura. Differential gene expression identifies a transcriptional regulatory network involving ESR1and PITX1 in invasive epithelial ovarian cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 2137.
Abstract 2140: Delineating a functional link between a phosphoserine aminotransferase (PSAT1)-associated gene signature and EGFR-mutant NSCLC
Authors: Biyik-Sit Rumeysa , Clem Brian F. 
Published: July 2021

Abstract
Phosphoserine aminotransferase 1 (PSAT1) catalyzes the second enzymatic step within the serine synthetic pathway and its expression is elevated in numerous human cancers, such as NSCLC. While PSAT1 suppression decreases SSP activity and cell proliferation, non-canonical activities have recently been suggested that may contribute to its pro-tumorigenic function, as is seen with other metabolic enzymes such as pyruvate kinase. Thus, we conducted a genome wide expression screen to uncover potential unknown cellular processes impacted by PSAT1 and to identify a PSAT1-associated gene signature that might inform patient outcomes in NSCLC. Loss of PSAT1 in EGFR-mutant PC9 lung cancer cells led to 491 differentially expressed genes (279-down; 212-up). KEGG and gene ontology analysis identified biological pathways such as metabolic processes, cell cycle regulation, cell adhesion, and cell motility. Transcript analysis confirmed inhibitory effects on the Rb/E2F1 and β-catenin pathways as well as expression of effectors on the actin cytoskeleton upon loss of PSAT1. Importantly, these could be rescued by PSAT1 restoration, including the loss of F-actin stress fibers as observed with phalloidin staining. Lastly, a bioinformatics approach utilizing transcriptomic data from human lung cancer patients was used to define genes altered between EGFR-mutant lung cancers and normal lung and that were differentially expressed in our PSAT1 depletion RNA-seq study. From this, we identified a PSAT1-associated gene signature that was then used to assign risk survival scores to these NSCLC patients. Subsequent, Kaplan Meier analysis demonstrated the prognostic ability of this gene signature for both relapse free and overall survival in EGFR-mutant NSCLC but was unable to predict risk groups in other NSCLC subtypes. Together, transcriptomic analysis under PSAT1 silencing identified its impact on various biological processes, including actin cytoskeleton rearrangement, and led to identification of a gene signature that has predictive ability towards survival outcomes in EGFR-mutant lung cancer.
Citation Format: Rumeysa Biyik-Sit, Brian F. Clem. Delineating a functional link between a phosphoserine aminotransferase (PSAT1)-associated gene signature and EGFR-mutant NSCLC [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 2140.
Abstract 2142: Retrospective analysis of 13160 clinically sequenced tumor samples reveals potential cancer drivers
Authors: Yan Cheng , Wu Hongwei , Yang Junhui , Guo Weihua , Yang Yufei 
Published: July 2021

Abstract
Background: High Throughput Sequencing (HTS) has generated tones of sequencing data that is almost unbearable to interpret. Adequate data mining strategy is in need to take huge volume of sequencing data and be able to derive clinically meaningful information. The positional distribution of somatic mutation on corresponding gene has strong implication of oncogenic involvement. We purpose a framework of cancer gene prioritization. Our aim is to derive candidate cancer genes by leveraging large volume of cancer samples.
Methods: We retrospectively analyzed 13160 clinically derived tumor samples consisting of five cancer types. These samples were previously subjected to captured sequencing covering either entire exome or major cancer related genes. To predict genes with oncogenic property, a modified version of 20/20 rule adapted from Bert's study was applied. After pan-cancer analysis, samples of each cancer type were analyzed separately to obtain cancer type specific candidate genes. Candidate genes uniquely predicted by our study were annotated in terms of molecular function and thoroughly assessed through literature curation.
Results: Using the modified 20/20 rule, pan-cancer analysis reported a total number of 186 candidate genes. 29 of them were uniquely reported by our analysis (absence in Bert's list, CGC list and our internal curation list) including 1 oncogene and 28 tumor suppressors. Their oncogenic involvements were further confirmed using random forest classifier 20/20+. 29 novel cancer candidate genes were significantly enriched in well-established cancer pathways described in Sanchez-Vega, et's study (pval&lt;0.01). For instance, Ras GTPase-activating protein 1 (RASA1) is an inhibitory regulator of the Ras-cyclic AMP pathway. Our data revealed that RASA1 is enriched with inactivating mutations across its coding region: a typical mutational pattern of tumor suppressor.
However, literature mining showed limited understanding regarding the its oncogenic rule.
In cancer type specific analysis, 14 additional candidate cancer genes were uniquely reported by our analysis including known driver genes such as HDAC4 in gastric cancer and KLF5 in intestinal cancer. However, some reported candidate genes were less studied, such as oncogene WNT10A in liver cancer, probably due to low mutation frequency in western population (&lt;0.5% according to TCGA). However, it mutated in 5.29% (59/1115) of our liver cancer cohort and highly recurrent mutations were identified at R171C and G213S.
Citation Format: Cheng Yan, Hongwei Wu, Junhui Yang, Weihua Guo, Yufei Yang. Retrospective analysis of 13160 clinically sequenced tumor samples reveals potential cancer drivers [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 2142.
Abstract 2144: STAT3 regulates the expression of XRCC1 in triple negative breast cancer
Authors: Wright Griffin M. , Gassman Natalie R. 
Published: July 2021

Abstract
Background: Base excision repair (BER) addresses base lesions and abasic sites induced by endogenous and exogenous environmental stresses. XRCC1 is a scaffold protein that facilitates and coordinates the BER repair machinery. Alterations in the protein and gene expression of XRCC1 have been observed in a multitude of cancers, including triple negative breast cancers (TNBC). Increased expression of XRCC1 is associated with aggressiveness and resistance to DNA damaging chemotherapeutics. However, only two transcription factors, E2F1 and Sp1 have been implicated in the transcriptional regulation of XRCC1 to date.
Methods: Utilizing promoter luciferase, transcription factor promoter binding ELISA, and chromatin immunoprecipitation (CHiP), STAT3 binding was identified and mapped in the XRCC1 promoter.
Results: In the current study, we identify a STAT3 binding site within the XRCC1 promoter. Importantly, STAT3 regulation of XRCC1 appears to be constitutive in TNBC cell line models where STAT3 is highly activated. In HEK293T cells, the STAT3 binding site shows low occupancy under basal growth condition, but STAT3 regulation of XRCC1 can be stimulated by cytokine or mitogenic signaling by IL-6 and epidermal growth factor (EGF).
Summary: STAT3 conditionally regulates XRCC1 under specific stress conditions to promote BER. In TNBC, the overexpression of XRCC1 by activated STAT3 likely contributes to increased resistance to DNA damaging chemotherapeutics.
Citation Format: Griffin M. Wright, Natalie R. Gassman. STAT3 regulates the expression of XRCC1 in triple negative breast cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 2144.
Abstract 2147: Discovering novel targets for adenoid cystic carcinoma of the lacrimal gland
Authors: Moeyersoms Acadia H. , Stathias Vasileios , Zhang Michelle , Gallo Ryan A. , Tse David T. , Pelaez Daniel 
Published: July 2021

Abstract
Lacrimal gland adenoid cystic carcinoma is a rare but highly lethal indolent cancer originating in the cells of secretory glands, primarily of the head and neck. With the 10-year survival rate of 20%, the only life extending technique is to remove the eye and surrounding socket contents entirely. Despite radical treatment, ACC is a very slow growing tumor and most patients will present with metastatic disease to the brain, lung, liver, or bones several years out from initial diagnosis and before symptoms are noticeable. Due to the rarity of LGACC, it is not well understood, but extensive genome analysis of ACC of the head and neck has previously uncovered a high mutation rate of MYB and NOTCH in patient samples, though unfortunately neither can be directly targeted by drugs. We have RNA sequencing data for 7 primary LGACC tumors, mass spectrometry data for 12 primary tumors and RNA sequencing for 15 cell lines derived from tumors to discover possible targetable biomarkers in LGACC and to further understand the biology of these tumors. Our analysis has revealed the signatures and drivers of LGACC, most significantly involving extracellular matrix mechanisms including HAPLN1, FABP7, and VCAN. We compared the genes of proteins differentially expressed in the mass spectrometry and RNA sequencing data and discovered 194 genes that were differentially expressed in both analysis types. With this extensive understanding of the molecular signatures, we used iLINCS integrated web-based platform to determine compounds that would target the differentially expressed genes. We have selected compounds based on a rubric we generated and will test them individually and in combination on LGACC cell lines to determine the best specific treatment for primary tumors and metastatic disease.
Citation Format: Acadia H. Moeyersoms, Vasileios Stathias, Michelle Zhang, Ryan A. Gallo, David T. Tse, Daniel Pelaez. Discovering novel targets for adenoid cystic carcinoma of the lacrimal gland [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 2147.
Abstract 2149: Subgroups of early-stage microsatellite stability endometrial, colorectal and stomach tumors based on transcriptomics have distinct disease-free survival
Authors: Zhang Shi , Liu Xinyi , Zhang Lan , Huang Mengli 
Published: July 2021

Abstract
Background: Microsatellite stability (MSS) is a biomarker for worse prognosis than microsatellite instability (MSI) in non-metastatic tumors. Tumors with MSS status are more probable to occur postoperative recurrence and metastasis. Some studies had revealed that endometrial and gastrointestinal tumors have distinct MSI-related features compared with other types of cancers, indicating there are potential similarities in these cancer types. The proportion of MSS population in non-metastatic endometrial and gastrointestinal tumors were about 90% and 75%. There are high heterogeneity in such wide range of patient population. The status of immune microenvironment based on immunohistochemistry or RNA-Seq profiling had been proved effective prognostic biomarker in some previous investigation. Therefore, we assume a subtype model of immune microenvironment based on transcriptomics features in endometrial and gastrointestinal tumors.
Method: 128 patients with I-III stage MSS endometrial and gastrointestinal tumors from TCGA project were included as training cohort and a meta cohort of 603 patients of colorectal and stomach cancers from GEO datasets (GSE39582,GSE62254) were included as validation cohort in our study. The RNA-Seq profiling data and disease-free survival (DFS) of patients were collected. CIBERSORT tool was conducted to evaluate the immune-related cells' enrichment. A lasso-cox model of DFS was developed based on the CIBERSORT features. Patients in training cohort were scored the recurrence risk by the model. We further investigate the differentially expressed genes between high-risk and low-risk patients. Log-rank test was used to evaluate the difference of DFS.
Result: 76 immune-related genes were identified to be differentially expressed significantly. The patients in training cohort were divided into two groups (group1 n=81, group2 n=41) based on non-negative matrix factorization (NMF) method. The DFS of group1 and group2 were significantly different (log-rank p=0.005). In validation cohort, patients were divided into group1 and group2 (group1 n=401, group2 n=202) using clustering method above. A significant difference between subgroups was also tested (log-rank p&lt;0.0001).
Conclusion: We identified 76 immune-related genes using CIBERSORT tool. Based on this gene set, early stage MSS endometrial and gastrointestinal tumors could be divided into two subgroups with distinct disease-free survival.
Citation Format: Shi Zhang, Xinyi Liu, Lan Zhang, Mengli Huang. Subgroups of early-stage microsatellite stability endometrial, colorectal and stomach tumors based on transcriptomics have distinct disease-free survival [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 2149.
Abstract 2150: High RRM1 expression as a potential poor prognosis factorin bladder cancer patients
Authors: Xu Ziqiao , Bei Ting , Xie Wenzhuan , Huang Mengli 
Published: July 2021

Abstract
Background: RRM1 encodes the M1 subunit of Ribonucleotide Reductase (RNR), a complex participating in DNA replication and repairment. RRM1 expression level has been reported to be associated with prognosis in various cancers, such as non-small-cell lung cancer, pancreatic cancer, breast cancer, and biliary tract cancer. However, the prognosis value of RRM1 expression in bladder cancer (BLCA) has not been revealed.
Method: Three bladder cancer cohorts with RNA-seq data including 2 cohorts from the GEO database and 1 from the TCGA database were used for investigating the overall survival (OS) of BLCA patients with differentiated RRM1 RNA expression. GSEA and CIBERSORT analyses were performed to study the potential mechanisms. The value of RRM1 RNA expression in predicting the clinical benefits of immune checkpoint inhibitors (ICIs) treated BLCA patients was also investigated using data from an ICI cohort (IMvigor210 cohort, n=348).
Result: We found significant differences in OS between BLCA patients with high (top 25% RRM1 RNA expression patients) and low (lowest 25% RRM1 RNA expression patients) RRM1 RNA expression in all the three bladder cancer cohorts from the TCGA and the GEO database. The multiple-variables Cox regression analysis revealed that higher RRM1 expression was associated with worse survival outcomes (HR=1.65, 95% CI = 1.05 - 2.6, P = 0.03).GSEA analysis revealed that 20 out of 50 Hallmark gene sets were enriched in the RRM1 high expression group. Among these enriched gene sets, the interferon-gamma is a well-established immune-related pathway. Furthermore, CIBERSORT analysis showed that the RRM1 high expression group had higher scores in IFN-gamma response, intra-tumor heterogeneity, and leukocyte fraction than the RRM1 low expression group. Combining results from both CIBERSORT and GSEA analysis, we hypothesized that RRM1 expression may be an efficacious predictor for ICI treatment in BLCA patients. Overall survival analysis of another external ICI cohort revealed that ICI treated BLCA patients with high RRM1 expression tended to have better OS than those with low RRM1 expression (HR = 0.77, CI95 0.54 - 1.1), but this difference was not statistically significant (P = 0.152).
Conclusion: Our study demonstrated that high RRM1 expression may serve as a poor prognostic biomarker in BLCA patients. Moreover, our study suggested that BLCA patients with high RRM1 expression may benefit more from ICIs therapies than those with low RRM1 expression.
Citation Format: Ziqiao Xu, Ting Bei, Wenzhuan Xie, Mengli Huang. High RRM1 expression as a potential poor prognosis factorin bladder cancer patients [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 2150.
Abstract 2158: Arsenic hexoxide has differential effects on cell proliferation and genome-wide gene expression in human primary mammary epithelial and mcf7 cells
Authors: Bunch Heeyoun , Kim Donguk , Park Na Yeon , Jeong Jaehyeon , Kang Keunsoo , Calderwood Stuart K. , Cho Dong-Hyung , Bae Ill Ju 
Published: July 2021

Abstract
Arsenic is reportedly a biphasic inorganic compound for its toxicity and anticancer effects in humans. Recent studies have shown that certain arsenic compounds including arsenic hexoxide (AS4O6; hereafter, AS6) induce programmed cell death and cell cycle arrest in human cancer cells and murine cancer models. However, the mechanisms by which AS6 suppresses cancer cells are incompletely understood. In this study, we report the mechanisms of AS6 through transcriptome analyses. In particular, the cytotoxicity and global gene expression regulation by AS6 were compared in human normal and cancer breast epithelial cells. Using RNA-sequencing and bioinformatics analyses, differentially expressed genes in significantly affected biological pathways in these cell types were validated by real-time quantitative polymerase chain reaction and immunoblotting assays. Our data show markedly differential effects of AS6 on cytotoxicity and gene expression in human mammary epithelial normal cells (HUMEC) and Michigan Cancer Foundation 7 (MCF7), a human mammary epithelial cancer cell line. AS6 selectively arrests cell growth and induces cell death in MCF7 cells without affecting the growth of HUMEC in a dose-dependent manner. AS6 alters the transcription of a large number of genes in MCF7 cells, but much fewer genes in HUMEC. Importantly, we found that the cell proliferation, cell cycle, and DNA repair pathways are significantly suppressed whereas cellular stress response and apoptotic pathways increase in AS6-treated MCF7 cells. Together, we provide the first evidence of differential effects of AS6 on normal and cancerous breast epithelial cells, suggesting that AS6 at moderate concentrations induces cell cycle arrest and apoptosis through modulating genome-wide gene expression, leading to compromised DNA repair and increased genome instability selectively in human breast cancer cells.
Citation Format: Heeyoun Bunch, Donguk Kim, Na Yeon Park, Jaehyeon Jeong, Keunsoo Kang, Stuart K. Calderwood, Dong-Hyung Cho, Ill Ju Bae. Arsenic hexoxide has differential effects on cell proliferation and genome-wide gene expression in human primary mammary epithelial and mcf7 cells [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 2158.
Abstract 2171: Brain cancer map: A neural network-based clustering of brain cancer samples based on genome-wide CNV and LOH patterns
Authors: Roytman Megan , Shams Soheil 
Published: July 2021

Abstract
Genomic based classification of cancers has been performed using gene expression and methylation patterns (e.g. well-established gene expression profiles used to sub-classify breast cancer). However, there has been very limited progress on classifying cancers based on their global CNV and/or LOH patterns. In this study, we present a novel neural network algorithm based on Self-Organizing Maps (SOMs) that creates a 2-dimensional map of cancer based on global CNV and LOH patterns. We applied this algorithm to 636 brain tumor samples from the TCGA project as part of the Glioblastoma (GBM) and Low-Grade Glioma (LGG) TCGA data sets. The CNV and LOH profiles for the samples was generated and manually curated to adjust for sample ploidy and call fragmentation due to normal cell contamination. Our algorithm generated a 25-node map of brain tumors, where different nodes represent a unique genome-wide profile and neighboring nodes are more similar to each other than more distant nodes. The generated map included nodes representing already known and prognostically important profiles such as 1p/19q co-deletion and combination of trisomy 7, monosomy 10, and homozygous deletion of p16. This is a significant validation of the approach since these profiles were generated completely automatically. In addition to these, new profiles were generated that were further investigated for prognostic value. We then projected all 636 samples back onto the learned map and were able to detect clusters of samples that generally fell within one cancer type, but also discovered some nodes shared by GBM and LGG samples indicating similarity in the CNV profile between these cancer types. We generated Kaplan-Meier survival plot for samples mapped to each node and were able to show statistically significant differences in survival based on the clustering. This approach has the possibility to create a unique CNV based classification of brain tumors for both prognostic and therapeutic applications.
Citation Format: Megan Roytman, Soheil Shams. Brain cancer map: A neural network-based clustering of brain cancer samples based on genome-wide CNV and LOH patterns [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 2171.