bluuebunny/crossref_metadata_2025_split huggingface dataset:
Abstract 2645: Targeting mRNA processing pathways in ovarian cancer with a small molecule inhibitor
Authors: Tailor Dhanir , Tsai Chia-Feng , Honkala Alexander , Li Wenqi , Liu Tao , Pejovic Tanja , Malhotra Sanjay V. 
Published: June 2022

Abstract
mRNA processing related pathways, including spliceosome and ribosome are over-expressed and unregulated in cancer cells. To investigate the mRNA processing pathways in patient samples, we performed a comprehensive, tandem mass tag (TMT) labeling-based proteome and phosphoproteome profiling of the normal and ovarian cancerous tissues from patients treated with different chemotherapy revealed that malignant cells have overexpression of mRNA processing pathways compared to normal cells. For this analysis, equal amount of tissues were homogenized, and tissue lysates were collected and processed for the quantitative proteomics and phosphoproteomics analysis. KEGG pathway enrichment analysis revealed that spliceosome, basal transcription factors, mRNA surveillance, ribosome and ribosome biogenesis in eukaryotes pathways are upregulated in cancer cells compared to control. On other hand, pathways associated with metabolism and fatty acid biosynthesis were downregulated in malignant cells. Moreover, kinase Enrichment Analysis shows that CDK2, ATM, ATR, and MAPK associated kinases are upregulated in cancer cells compared to normal. Based on proteome analysis of patient samples, we investigated the pharmacological inhibition of Y-box binding protein 1 (YB-1). This is an RNA binding protein and key regulator of pre-mRNA alternative splicing and processing. We recently showed that a natural product-derived small molecule (SU056) inhibits YB-1 activity. We found that SU056 binds to the YB-1 and blocks the RNA binding pocket. Proteomics results suggest that treatment with this drug strongly inhibits the spliceosome pathway. SU056 treatment arrests the ovarian cancer cells in G1 phase and inhibits the CDK2 and Cyclin E. SU056 inhibits the tumor progression and metastasis in the ID8 mice model and sensitizes the OVCAR8 NSG mice model for paclitaxel treatment. Our study provides a compelling case for YB-1 inhibition using SU056 as a potential therapy for ovarian cancer.
Citation Format: Dhanir Tailor, Chia-Feng Tsai, Alexander Honkala, Wenqi Li, Tao Liu, Tanja Pejovic, Sanjay V. Malhotra. Targeting mRNA processing pathways in ovarian cancer with a small molecule inhibitor [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 2645.
Abstract 2651: The tankyrase inhibitor OM-153 demonstrates anti-tumor effect with a therapeutic index above 10
Authors: Brinch Shoshy Alam , Amundsen-Isaksen Enya , Espada Sandra , Aizenshtadt Aleksandra , Holmen Lone , Hammarström Clara , Høyem Merete , Scholz Hanne , Grødeland Gunnveig , Sowa Sven T. , Galera-Prat Albert , Lehtiö Lari , Meerts Ilonka A.T.M. , Leenders Ruben G. G. , Wegert Anita , Krauss Stefan , Waaler Jo 
Published: June 2022

Abstract
The catalytic enzymes tankyrase 1 and 2 (TNKS1/2) poly-ADP-ribosylate target proteins, including AXIN proteins, to earmark them for degradation by the ubiquitin-proteasomal system. Hence, inhibition of TNKS1/2 can stabilize AXIN proteins, and consequently β-catenin degradosomes, resulting in inhibition of WNT/β-catenin signaling. Although several potent small-molecules have been developed to inhibit TNKS1/2 and oncogenic WNT/β-catenin signaling, also showing convincing anti-tumor effects in numerous mouse cancer models, there are currently no TNKS1/2 inhibitors available in the clinic. The development has mainly been disadvantaged by concerns over previous reports unfolding intestinal toxicity, apparently caused by on-target and WNT/β-catenin signaling pathway-specific side effects, and a deficient therapeutic index. Here we show that the novel, highly potent and selective1,2,4-triazole-based TNKS1/2 inhibitor OM-153, displaying improved ADME-properties and mouse pharmacokinetics, reduced WNT/β-catenin signaling and tumor progression in COLO 320DM colon cancer xenografts upon peroral (PO) administration of 0.33-10 mg/kg twice daily (BID). In addition, combined OM-153 and anti-PD-1 treatment conferred a synergistic anti-tumor effect in a B16-F10 mouse melanoma model. In a 28-day repeated dose mouse toxicity study, body weight loss, intestinal damage and tubular damage in the kidney was documented after PO BID administration of 100 mg/kg. In contrast, in mice treated PO BID using 10 mg/kg, the intestinal architecture was intact and no atypical histopathological changes were observed in other organs, while clinical biochemistry and haematological analyses did not identify any changes indicating considerable toxicity. The results provide a scaffold for using OM-153 as a potential anti-cancer treatment and additional preclinical and clinical evaluations.
Citation Format: Shoshy Alam Brinch, Enya Amundsen-Isaksen, Sandra Espada, Aleksandra Aizenshtadt, Lone Holmen, Clara Hammarström, Merete Høyem, Hanne Scholz, Gunnveig Grødeland, Sven T. Sowa, Albert Galera-Prat, Lari Lehtiö, Ilonka A.T.M. Meerts, Ruben G. G. Leenders, Anita Wegert, Stefan Krauss, Jo Waaler. The tankyrase inhibitor OM-153 demonstrates anti-tumor effect with a therapeutic index above 10 [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 2651.
Abstract 2664: Development of covalent KRASG12C inhibitor APG-1842 for the treatment of solid tumors
Authors: Gu Shaoulai , Li Qiang , Li Chao , Wang Qixin , Fang Douglas D. , Wang Shaomeng , Yang Dajun , Zhai Yifan 
Published: June 2022

Abstract
The KRAS gene, which encodes a guanosine triphosphate (GTPase) protein, is frequently mutated in solid cancers. The KRASG12C mutation aberrantly attenuates GTPase activity, leading to accumulation of the GTP-bound activated form of the KRAS protein and activation of downstream signaling pathways. This genotype occurs in approximately 13% of non-small-cell lung cancers (NSCLCs) and 1% to 3% of colorectal cancers and other solid tumors. In this study, investigational agent APG-1842 was characterized as a potent, selective, and covalent KRASG12C inhibitor that irreversibly and specifically blocks KRASG12C in an inactive guanosine diphosphate (GDP)-bound state and downregulates KRAS-dependent signaling.
A RAS-GTP pull-down assay demonstrated that APG-1842 (at a concentration as low as 12 nM) completely blocked GDP-GTP nucleotide exchange, which stabilized an inactive GDP-bound form of KRASG12C and thereby inhibited RAS and RAF binding in KRASG12C-mutant human NSCLC NCI-H358 cells. In these cells, APG-1842 dose dependently inhibited KRAS-dependent signaling target proteins, including phosphorylated extracellular signal-regulated kinase (ERK), S6, and serine/threonine protein kinase Akt (protein kinase B), with a half-maximal inhibitory concentration (IC50) value of 4 nM for ERK1/2 phosphorylation. Using a panel of 18 cancer cell lines representing multiple cancer types in cell viability assays, we found that APG-1842 selectively inhibited cell proliferation in KRASG12C-mutated, but not non-KRASG12C or KRAS wild-type, cell lines.
Oral APG-1842 in mice carrying cell-derived NCI-H358 NSCLC subcutaneous xenografts exerted significant antitumor efficacy at doses ranging from 3 to 100 mg/kg, resulting in tumor regression at 30 mg/kg and above. Consistent with the cellular results, APG-1842 dose dependently inhibited ERK1/2 and S6 phosphorylation in xenografts after 6 and 24 hours of treatment, correlating with systemic and tumor drug exposures. Significant antitumor activity of APG-1842 was also confirmed in a panel of 8 KRASG12C-mutated patient-derived xenograft models derived from patient samples of lung, colorectal, and gastric cancers.
Collectively, these preclinical results suggest that APG-1842 is a potent, bioavailable, and highly selective KRASG12C inhibitor, laying a foundation for clinical development of this agent for patients with KRASG12C-mutant solid tumors.
Citation Format: Shaoulai Gu, Qiang Li, Chao Li, Qixin Wang, Douglas D. Fang, Shaomeng Wang, Dajun Yang, Yifan Zhai. Development of covalent KRASG12C inhibitor APG-1842 for the treatment of solid tumors [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 2664.
Abstract 2720: Unbiased identification of RNA splicing-defined patient populations in lung adenocarcinoma
Authors: Crowther Audrey 
Published: June 2022

Abstract
Aberrant alternative splicing is known to directly contribute to tumor progression in lung adenocarcinoma (LUAD). While the action of individual splicing variants as cancer drivers have been characterized in LUAD, the global splicing landscape and how that corresponds to patient prognosis is poorly understood. Using whole transcriptome RNA-Seq data provided from The Cancer Genome Atlas (TCGA), we applied a new computational pipeline, OncoSplice, to identify potentially novel prognostic disease splicing subtypes and elucidate the biological mechanisms underlying these subtypes. OncoSplice identified over 30 novel splicing-defined subtypes of LUAD, several of which correlate with worse patient survival. Additionally, we identified patient clusters that were significantly enriched in mutations for RNA binding proteins, such as Cap Methyltransferase 2 (CMTR2) and RNA Binding Motif 10 (RBM10). More specifically, mutations in the splicing factor RBM10 were found to be enriched but not requisite for the dominant poor prognosis splicing subtype in LUAD. In non-mutant patients within this subset, RBM10 gene expression downregulation was induced, mimicking the mutation phenotype. Hence, we find alternative non-genetic pathways for impacting splicing in LUAD that leads to poor prognosis through disruption of canonical splicing.
Citation Format: Audrey Crowther. Unbiased identification of RNA splicing-defined patient populations in lung adenocarcinoma [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 2720.
Abstract 2730: Metronomic dose-finding approach of oral chemotherapy by experimentally-driven integrated mathematical modeling
Authors: Kweon Seho , Jeong Yoo-Seong , Ko Yoon Gun , Chung Seung Woo , Lee Ha Kyeong , Chung Suk-Jae , Byun Youngro , Kim Sang Yoon 
Published: June 2022

Abstract
Conventional chemotherapy with maximum tolerated dose (MTD) has shown confident anti-cancer effect and when combined with targeted therapy, immunotherapy. Yet, understanding about how the MTD regimen is optimized has lacked due to its high tumor burdens. In this study, the oral doxorubicin (DOX) formulation was shown to improve oral bioavailability by 12.1% and sustain the metronomic concentration through the flexible protocol. Since the optimizing dose and schedules of DOX in metronomic chemotherapy (MCT) is essential to maximize efficacy and minimize toxicity, which is determined by the exposure of drugs based on pharmacokinetic-pharmacodynamic (PK/PD) correlation, we developed an integrated systemic mathematical model that can evaluate the anti-tumor effect and the toxicity of oral DOX formulation simultaneously. Oral physiologically-based pharmacokinetic (PBPK) models were established with dose dependency, and creatine kinase-MB (CK-MB) and tumor growth profiles were assessed as markers for toxicodynamic (TD) and PD models, respectively. Each model was validated and then integrated into the PK-TD/PD model and the effects of various oral metronomic regimens were predicted. In conclusion, the finalized oral metronomic dosing regimen (10 mg/kg, QD) showed 83.3% tumor growth inhibition without cardiotoxicity. In this study, we defined the MCT regimen using a mathematical model and suggested a dose selection method for developing oral drugs from injections, to efficiently utilize the preclinical results and apply to clinical practice.
Citation Format: Seho Kweon, Yoo-Seong Jeong, Yoon Gun Ko, Seung Woo Chung, Ha Kyeong Lee, Suk-Jae Chung, Youngro Byun, Sang Yoon Kim. Metronomic dose-finding approach of oral chemotherapy by experimentally-driven integrated mathematical modeling [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 2730.
Abstract 2733: A computational model of cellular metabolism with mutation data predicts metabolites associated with somatic mutations in cancers
Authors: Lee Sang Mi , Lee GaRyoung , Lee Sungyoung , Song Hyojin , Yoon Sung Soo , Yun Hongseok , Koh Youngil , Kim Hyun Uk 
Published: June 2022

Abstract
Metabolic reprogramming is considered a hallmark of cancers, which plays an important role in cancer progression and development, partly as a consequence of somatic mutations. A representative product of metabolic reprogramming in cancers is oncometabolites that show abnormal accumulation in a cancer cell, induce malignancy, and are generated upon mutations in a metabolic gene, often IDH1, SDH or FH. Identification of novel mutation-associated metabolites will facilitate developing biomarkers and treatment strategies for cancers, as in the case of ivosidenib, an FDA approved drug for treating acute myeloid leukemia (AML) having the IDH1 mutant. To this end, we develop a computational workflow that predicts so-called metabolite-gene-pathway sets (MGPs) that present metabolites and metabolic pathways significantly associated with gene mutations in cancers. The computational workflow uses cancer patients’ mutation data and a computational model of cellular metabolism called a genome-scale metabolic models (GEM). In this study, the computational workflow was demonstrated using 943 cancer patient-specific GEMs representing 24 different cancer types based on the Pan-Cancer Analysis of Whole Genomes (PCAWG) data [1], which, as a result, predicted 4,135 MGPs for these multiple cancer types. The computational workflow was shown to generate biologically meaningful MGPs on the basis of multi-omics data from 17 AML samples collected in this study as well as previous published studies. For the AML samples, metabolites of the MGPs predicted using the computational workflow showed significantly different intracellular concentrations, depending on mutation of genes involved in the MGP. Moreover, for the 115 MGPs predicted for CNS-GBM/Oligo that are associated with mutation of CIC, EGFR, IDH1 or TP53, 69% of the MGPs were supported by previous studies. This two-level validation indeed showed that it is possible to characterize metabolic pathways and their metabolites that are affected in response to somatic mutations in a cancer cell. Our computational workflow and its prediction outcomes will help better understand the mutation-associated metabolic reprogramming in cancers, and serve as a valuable resource for further extended studies on cancer metabolism. [1] The ICGC/TCGA Pan-Cancer Analysis of Whole Genomes Consortium. Pan-cancer analysis of whole genomes. Nature 578, 82-93
Citation Format: Sang Mi Lee, GaRyoung Lee, Sungyoung Lee, Hyojin Song, Sung Soo Yoon, Hongseok Yun, Youngil Koh, Hyun Uk Kim. A computational model of cellular metabolism with mutation data predicts metabolites associated with somatic mutations in 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 2733.
Abstract 28: New onset of type 2 diabetes after colorectal cancer diagnosis: Results from three prospective US cohort studies, systematic review, and meta-analysis
Authors: Zeng Hongmei , Yuan Chen , Morze Jakub , Fu Ruiying , Wang Kai , Wang Liang , Sun Feng , Ji John S. , Giovannucci Edward L. , Song Mingyang 
Published: June 2022

Abstract
Background: Limited data indicate that patients with colorectal cancer (CRC) are at higher risk of developing type 2 diabetes (T2D). We prospectively examined the risk of T2D between individuals with and without CRC in three large cohorts and conducted a meta-analysis.
Methods: We assessed the diagnosis of CRC and T2D among 111 485 women from the Nurses' Health Study, 112 958 women from the Nurses' Health Study II, and 46 581 men from the Health Professionals Follow-up Study. We used multivariable Cox regression with time-varying covariates to calculate the hazard ratio (HR) of T2D in relation to CRC diagnosis. We further performed a systematic review and meta-analysis of cohort studies.
Findings: Up to 36 years of follow-up (6.9 million person-years), we documented 3402 incident CRC cases and 26 469 T2D cases. Compared to non-CRC individuals, those with CRC were more likely to develop T2D (multivariable-adjusted HR 1.20, 95% CI 1.05-1.38). The association was most evident for individuals with fewer risk factors for T2D. In the meta-analysis of seven cohort studies (1 061 744 participants), CRC was associated with higher T2D risk (meta-analysis HR 1.21, 95% CI 1.11-1.31, I2=57.9%). By CRC duration, a statistically significant association was observed in the first 10 years but not after 10 years of CRC diagnosis (≤5 years, meta-analysis HR 1.32, 95% CI 1.27-1.36; 5.1-10 years, 1.14 [1.04-1.25]; &gt;10 years, 1.14 [0.91-1.37]).
Interpretations: CRC was associated with increased T2D risk, especially in the first ten years after CRC diagnosis. Our findings highlight the importance of T2D prevention for CRC survivorship care.
Citation Format: Hongmei Zeng, Chen Yuan, Jakub Morze, Ruiying Fu, Kai Wang, Liang Wang, Feng Sun, John S. Ji, Edward L. Giovannucci, Mingyang Song. New onset of type 2 diabetes after colorectal cancer diagnosis: Results from three prospective US cohort studies, systematic review, and meta-analysis [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 28.
Abstract 2800: Use of an optimized machine learning algorithm to develop DNA methylation markers for detecting colorectal cancer (CRC)
Authors: Kang Jun-Kyu , Kim Su Yeon , Lim Yoojoo , Kim Hwang-Phill , Kim Tae-You 
Published: June 2022

Abstract
Introduction: Epigenetic changes including methylation occur early in tumorigenesis and are known to be highly pervasive across a tumor type. The DNA methylation pattern can vary between individuals with or without cancer and also in patients with cancer of different origins. In this study, we investigated the discovery of comprehensive markers and validation of the diagnostic and prognostic potential of colorectal cancer.
Methods: Patients with various stage of colorectal cancer were eligible for the current study, mainly stage III. We generated genome-wide methylation data from 379 colorectal cancer (CRC) tissues and 330 available paired adjacent normal mucosa tissues from Korean patients by Illumina EPIC Human Methylation microarray targeting 860,000~ CpG sites. A machine learning algorithm was used to build an optimized prediction model and select the tumor specific markers based on through theses CpG sites. Then, the risk score was devised for prognosis using this marker set. Finally, in order to validate the rule of CpG sites, the genomic location and pathway enrichment analysis was performed by CHROMHMM and Metascape.
Results: 379 colorectal cancer tissues and 330 paired adjacent normal mucosal tissues were included for analysis. Clinical stages of the included patients were, III in N (61.2%), II in N (19.5%), and IV in N (11.9%). A total of 305 methylation markers that showed statistically significant differences between normal and cancer tissues were selected. Our model could accurately identify CRC (areas under the curve for the training and validation cohorts: 0.968 and 0.984, respectively). Using our prediction model, the colorectal cancer patients were predicted as colorectal cancer accurately in the methylation data from TCGA (COREAD; colorectal cancer tissue DNA) and GEO dataset (plasma cfDNA from colorectal cancer patients). The risk score comprising the subset of 305 methylation markers was calculated, and poor prognosis was predicted in the high-risk score group (overall survival P &lt;0.1, progression-free survival P &lt; 0.01). Gene ontology (GO) enrichment analysis showed that the 305 CpG sites were enriched in transcription regulatory regions (160/305, 52.5%) and were associated with developmental process and carcinogenesis (GO: 0032502, P &lt;0.001; C4721208, P &lt;0.001).
Conclusions: In summary, the performance of our prediction model with these 305 CpG sites was highly accurate for CRC diagnosis, and the optimized risk score could predict the prognosis of Korean CRC patients
Citation Format: Jun-Kyu Kang, Su Yeon Kim, Yoojoo Lim, Hwang-Phill Kim, Tae-You Kim. Use of an optimized machine learning algorithm to develop DNA methylation markers for detecting colorectal cancer (CRC) [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 2800.
Abstract 2806: High sensitivity qPCR microsatellite instability detection in FFPE tissue
Authors: Yan Yan Helen , Young Blake , Wang Zhiheng , Yaseen Adam , Pinto Alessandro , Zhang David 
Published: June 2022

Abstract
Microsatellite instability (MSI) refers to genetic instability in short nucleotide repeats (e.g., 1-6bp tandem repeats), where a cell comprises a different number of repeats as compared to what was inherited from a progenitor cell. This genetic instability is often observed in tumor cells with impaired mismatch repair (MMR), especially in colorectal cancer (CRC) and endometrial cancer. MSI-high tumors can help identify patients that would benefit from additional genetic testing to diagnose Lynch Syndrome. Additionally, MSI can potentially be used as a biomarker to predict response to treatment with immunotherapy and CRC patients with MSI have a significantly better prognosis compared to those with intact mismatch repair. Here we present the VarTrace® MSI Research qPCR Assay, which enables high sensitivity detection of microsatellite instability. The assay uses NuProbe’s PCR-based Blocker Displacement Amplification (BDA) technology to enable the selective amplification of MSI unstable alleles with 1% analytical limit of detection. The assay is intended for the qualitative detection of mutations in 5 MSI loci (BAT-25, BAT-26, NR-21, NR-24 and MONO-27) without the need of matched normal, and reports MSI-high (MSI-H), MSI-low (MSI-L) and Microsatellite Stable (MSS). Analytical validation of the assay has been completed on Horizon MSI/MSS formalin-fixed, paraffin-embedded (FFPE) DNA reference standard, SeraCare MSI AF5% reference panel mix, and 50 CRC FFPE samples. One FFPE section with as little as 2ng of input DNA is enough for this assay. The high sensitivity potentially allows for the detection of MSI status in liquid biopsy.
Citation Format: Yan Helen Yan, Blake Young, Zhiheng Wang, Adam Yaseen, Alessandro Pinto, David Zhang. High sensitivity qPCR microsatellite instability detection in FFPE tissue [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 2806.