bluuebunny/crossref_metadata_2025_split huggingface dataset:
Abstract P3-08-11: The application of machine learning techniques to standardize breast cancer grading and develop multivariate risk outcome models
Authors: Prastawa Marcel , Madduri Abishek Sainath , Veremis Brandon , Shtabsky Alexander , Marami Bahram , Zeineh Jack , Donovan Michael Joseph , Fernandez Gerardo 
Published: March 2020

Abstract
Background: The 2019 NCCN guidelines and the College of American Pathology (CAP) endorse consistent, unambiguous comprehensive pathology reporting for invasive breast cancer. Challenges surrounding inter-pathologist variability and the lack of quantitative, standardized approaches to histologic grade are significant and critical to patient management. We developed an automated multi-network machine learning platform for histologic grading and examined performance with clinical outcome. Methods: Using the Cancer Genome Atlas (TCGA) breast cancer (BCA) image dataset and clinical data as a training cohort, we evaluated 420 conventional H&E images (one slide per patient). An artificial intelligent (AI) / deep-learning based workflow is used to normalize staining differences, identify regions of tumor vs. normal and characterize individual cellular attributes of breast cancer grading systems including overall gland structure, nuclear morphology, and mitotic figures. Individual features were correlated with overall survival using the concordance index (c-index). Support vector models and Kaplan-Meier incidence curves were used to further understand feature importance. Results: Using the AI platform, 88 image features representing BCA gland morphology and cellular-nuclear attributes were generated from 420 patients with 36 events including metastasis and or death with a median overall survival (OS) of 5-years. Three clinical variables were available including AJCC stage, grade and age at diagnosis. Image features were prioritized on C-index &lt;0.5 or &gt;0.5 which reflects increased or reduced risk of poor outcome, respectively. A training model consisting of image features + clinical data produced a C-index of 0.85, Hazards ratio 11, p&lt;0.001. Only 1 clinical feature (stage) and 9 imaging features (all with individual c-indices &lt;0.5) representing nuclear shape, size, number and mitotic figure activity were selected.
Conclusions: Our innovative lab-based AI / deep-learning platform produced accurate BCA risk models to predict metastasis and OS through automated H&E BCA grading. Future analyses include a multi-site validation study to confirm these initial training results.
Citation Format: Marcel Prastawa, Abishek Sainath Madduri, Brandon Veremis, Alexander Shtabsky, Bahram Marami, Jack Zeineh, Michael Joseph Donovan, Gerardo Fernandez. The application of machine learning techniques to standardize breast cancer grading and develop multivariate risk outcome models [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr P3-08-11.
Abstract P3-10-16: Identification of molecules that enhance the efficacy of eribulin in TNBC and IBC cell lines
Authors: Lee Jangsoon , Fuson Jon A , Liu Huey , Pearson Troy , Tripathy Debu , Lim Bora , Ueno Naoto T 
Published: March 2020

Abstract
BACKGROUND: Eribulin mesylate, a non-taxane microtubule-dynamics inhibitor, is an effective chemotherapy drug for patients with metastatic breast cancer who have previously received at least two chemotherapeutic regimens. We are seeking to enhance the anti-tumor activity of eribulin in metastatic breast cancer cell lines. The purpose of this study was to identify kinase targets that markedly enhance the efficacy of eribulin using high-throughput nonbiased synthetic lethal RNA interference (RNAi) screening and to validate these targets in combination with eribulin using triple-negative breast cancer (TNBC) and inflammatory breast cancer (IBC) cell lines which are heterogeneous diseases and characterized by their high metastatic potential and poor prognosis.
METHODS: High-throughput RNAi screening (709-human-kinome library) was performed to identify target kinases. The Bliss scoring method was used to identify potential targets from the screening (using a Bliss score cut-off of 0.15), and protein-protein interactome analysis (STRING V.11) and Ingenuity Pathway Analysis (IPA) were used to identify therapeutic target pathways. To validate the in vitro efficacy of selected targets, we performed CellTiter-Blue or sulforhodamine B cell proliferation and anchorage-independent colony-formation assays in 18 TNBC and 6 IBC cell lines treated with eribulin with or without inhibitors of the discovered targets.
RESULTS: In vitro proliferation data demonstrated that single-agent eribulin had a nanomolar range of half-maximal inhibitory concentrations (0.2 - 4.0 nM) in most of the tested cell lines. RNAi screening identified 130 relevant kinase targets. IPA and STRING analysis revealed PI3K/AKT/mTOR, MAPK, JNK, and PAK1 as major canonical pathways that could be targeted to enhance the cytotoxic effect of eribulin. In in vitro cell line validation, PAK1 inhibitor NVS-PAK1-1 and mTOR inhibitor everolimus showed strong combinational anti-tumor effect (combination index values = 0.1 - 0.9), and JNK inhibitor JNK-In-8 showed moderate combinational anti-tumor effect (combination index values = 0.5 - 0.9) in combination with eribulin. Inhibitors of PI3K (copanlisib) and MEK (trametinib) showed combinational anti-tumor effect in some cell lines.
CONCLUSION: We identified that PAK1, mTOR, and JNK inhibitors enhanced the anti-proliferation effects of eribulin in TNBC and IBC cell lines. Our data inform new treatment strategies with eribulin for TNBC and IBC that could lead to clinical trials of innovative combination therapy based on eribulin.
Citation Format: Jangsoon Lee, Jon A Fuson, Huey Liu, Troy Pearson, Debu Tripathy, Bora Lim, Naoto T Ueno. Identification of molecules that enhance the efficacy of eribulin in TNBC and IBC cell lines [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr P3-10-16.
Abstract P3-11-26: Investigating the synergistic anti-cancer effects on mitochondrial function in breast cancer cells using arctigenin, cinnamaldehyde, and chlorogenic acid individually and in combination
Authors: Schuster Caroline , Gollahon Lauren S 
Published: March 2020

Abstract
One of the major obstacles in current breast cancer treatment efficacy is the ability of breast cancer cells to develop resistance to chemotherapeutic drugs. In addition, a second major obstacle is the off-target cytotoxicity of these drugs on normal cells, leading to debilitating side effects. Many of these current chemotherapeutics target DNA (repair, replication, division). As a result, the bystander effect to normal cells and tissues is significant. However, one major difference between cancer and normal cells is their metabolism. The Warburg Effect suggests that cancer cells prefer a glycolytic, hypoxic environment. Emerging studies have begun to delineate differences in mitochondrial function between cancer and normal cells. In this study, we sought to exploit this metabolic difference by investigating alternative breast cancer treatment options based on application of natural product components. Previous studies from our lab demonstrated the efficacy of a mixture of plant extracts in killing cancer cells. Proteomics studies showed significant mitochondrial disruption in the cancer cells compared to normal cells. Here, we investigate three of the main components, identified by Mass Spectometry, to determine their anticancer properties compared to the whole extracts’ mixture. Arctigenin, chlorogenic acid, and cinnamaldehyde all demonstrate anti-cancer activity. We hypothesize that each component of the whole extract causes breast cancer cell death by disruption of mitochondrial activity and metabolic shifts, and lead to an increase in oxidative stress that is further amplified by combination treatment. These small molecules were administered to MDA-MB-231 and MCF-7 breast cancer or normal MCF-10A and MCF-12F breast cells, either alone or in combination. To evaluate differences in cell response, mitochondrial integrity and metabolic shifts were evaluated by flow cytometry, fluorescence microscopy and the Agilent Seahorse XF Cell Mito Stress Test. The ladder measures the mitochondria’s oxygen consumption rate, basal respiration, ATP production, proton leak, maximal respiration, spare respiratory capacity, and non-mitochondrial respiration. This study provides evidence that targeting the mitochondria may be a more effective anticancer treatment and that either components of natural products or combinations thereof offer new approaches in treating breast cancer that significantly reduce off-target effects to normal cells.
Citation Format: Caroline Schuster, Lauren S Gollahon. Investigating the synergistic anti-cancer effects on mitochondrial function in breast cancer cells using arctigenin, cinnamaldehyde, and chlorogenic acid individually and in combination [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr P3-11-26.
Abstract P4-05-23: Validation of proteome based molecular stratification of breast cancer using 1,229 patient samples from four independent datasets
Authors: Gyorffy Balazs 
Published: March 2020

Abstract
Introduction. In routine diagnostics, four genes are used to determine the molecular subtype and the optimal systemic therapy for breast cancer patients, ESR1, PGR, HER2, and in some cases MKI67. While these can be measured by different molecular genetic methods, immunohistochemistry is still the most widely used technique. The aim of present study was to determine how effective recent proteomic technologies are in measuring the expression of these genes.
Methods. A literature search was performed to identify available proteome-level datasets. Differential expression was compared using Mann-Whitney test. Receiver operating characteristics (ROC) was computed to validate discriminative power and to determine the optimal cutoff values. Each dataset was processed separately.
Results. All together four datasets with a total of 1,229 specimens with proteome level-data were identified. One dataset was generated using RPPA (reverse phase protein lysate microarray, n=874) and three using LC-MS (liquid chromatography-mass spectrometry, n=355). In all four datasets combined, a total of 7,419 proteins were measured. It was not possible to analyze all combinations because of limited data availability - HER2 data was available in the RPPA study only, and ESR1/PGR in the LC-MS studies only. The determination of HER2 status by IHC and HER2 protein expression by RPPA show very high correlation (p=2.9E-18). ESR1 protein expression determined by LC-MS show a significant correlation to IHC results (p=0.04). The ROC analysis for HER2 delivered an area under the ROC curve (AUC) of 0.74 (p=1.9e-20). For ESR1, the AUC was 0.61 (p=0.03). ESR1 and PGR show a moderate correlation in LC-MS data (correlation coefficient=0.17, p=0.04). Finally, when comparing MKI-67 expression between normal (n=53) and tumor samples (n=65) within one dataset, tumor samples had significantly higher expression (fold change=2.22, p=3.9E-05).
Conclusions. The RPPA method achieved high correlation with IHC results. Our results suggest that proteomic technologies will be capable to deliver molecular stratification enabling the discrimination of breast cancer subtypes in the future.
Citation Format: Balazs Gyorffy. Validation of proteome based molecular stratification of breast cancer using 1,229 patient samples from four independent datasets [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr P4-05-23.
Abstract P4-05-24: A stroma-adjusted ZEB1 expression signature is associated with decreased immune cell infiltration and poor overall survival in breast cancer
Authors: Block C James , Wu Guojun 
Published: March 2020

Abstract
The epithelial-to-mesenchymal transition (EMT) is a critical physiologic process which can be activated by cancer cells to enhance metastatic and chemoresistant properties in experimental models. Recent studies have identified positive associations between the expression of EMT-associated gene signatures with both the immune response and survival in multiple cancer types. Although these studies relied upon whole-tumor RNA sequencing data, which can be confounded by infiltrating immune and stromal cells, they failed to investigate this potential confounding effect. In this study, we comprehensively dissected the associations between the expression of multiple EMT transcription factors with stromal and immune cell tumor infiltration in breast cancer. We demonstrated that previously-reported associations between the expression of EMT marker genes and immune activity were confounded by stromal cell infiltration. Adjusting for this confounding effect eliminated these reported associations. Interestingly, we discovered that stroma-adjusted ZEB1 expression has a unique, inverse association with immune cell activity in multiple cancer types, most significantly in breast cancer. Further analysis revealed that ZEB1 is significantly correlated with reduced tumor infiltration of multiple immune cell types. By deriving a high-confidence stroma-adjusted ZEB1-activated gene signature, we confirmed that ZEB1 transcriptional activity has similar associations with both tumor immune activity and stromal content as ZEB1, thus identifying potential mechanisms underlying decreased immune cell infiltration. Finally, multivariate survival analysis reveals that the ZEB1 gene signature has significant associations with reduced overall survival in breast cancer patients. In conclusion, this study identifies a novel association between stroma-adjusted ZEB1 expression and tumor immune activity and addresses the critical issue of confounding between EMT-associated genes and tumor stromal content.
Citation Format: C James Block, Guojun Wu. A stroma-adjusted ZEB1 expression signature is associated with decreased immune cell infiltration and poor overall survival in breast cancer [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr P4-05-24.
Abstract P4-09-09: Characteristics of stage 1 to 3 breast cancer patients with amplification of centromere of chromosome 17
Authors: Voutsadakis Ioannis , Davies Vanessa 
Published: March 2020

Abstract
Background: Amplification of the centromeric region of chromosome 17 (CEP17) as measured by In Situ Hybridization (ISH) of the CEP17 probe is used clinically as part of the ISH assay for HER2 status determination in breast cancer. The value of amplification of CEP17 beyond its use in the HER2 ISH test and characteristics of cases bearing CEP17 amplification, have not been fully explored.
Methods: A retrospective review of charts of patients with stage 1 to 3 breast cancer that had a dual probe HER2/ CEP17 FISH test in our cancer center during an eight-year period was performed. Data on demographic, and cancer-specific characteristics of the included patients were extracted. The group of patients with an amplified CEP17 defined as mean copy number ≥3 per nucleus was compared with the group without amplification.
Results: Two hundred and two patients were included in the analysis. Amplification of CEP17 was observed in 36 patients (17.8%). All patients in the amplified group had a concomitant amplification of HER2 (mean copy number ≥3 per nucleus). In the CEP17 non-amplified group 78 of 166 patients (47%) had an amplified HER2 status. More patients in the amplified group had a clinical HER2+ status according to the 3-protein classifier (33.3% versus 11.5% in the non-amplified group) and less patients in the amplified group had a clinical ER+/ HER2- status (63.9% versus 81.8% in the non-amplified group, x2 p=0.0003). Other significant differences between the amplified and CEP17 non-amplified groups were observed in their lymph node (LN) status (55.6% of patients in the amplified group versus 36.8% in the non-amplified group were lymph node positive, p= 0.04) and in the nuclear heterogeneity component of grade (90.9% of patients in the amplified group were nuclear grade 3 versus 66.9% in the non-amplified group, p= 0.02). There were no statistically significant differences between the groups in overall stage, grade, menopause status or histology.
Conclusion: Patients with amplification of CEP17 had a co-amplified HER2 and were more commonly HER2+, LN positive and grade 3 in the nuclear component of grade.
Citation Format: Ioannis Voutsadakis, Vanessa Davies. Characteristics of stage 1 to 3 breast cancer patients with amplification of centromere of chromosome 17 [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr P4-09-09.
Abstract P4-09-11: PIK3CA somatic alterations in 412 chinese invasive breast cancers: Higher frequency of mutant H1047R detected by next generation sequencing compared to breast cancer in caucasians
Authors: Jia Minghan , Liao Ning , Chen Bo , Zhang Guochun , Wang Yulei , Chen Xiaoqing , Guo Liping , Cao Li , Mok Hsiaopei , Ren Chongyang , Li Kai , Li Cheukfai , Wen Lingzhu , Lin Jiali , Wei Guangnan , Zhang Zhou , Balch Charles M 
Published: March 2020

Abstract
Purpose: Somatic alterations of PIK3CA gene is an important therapeutic target in breast cancer (BC). The PI3Kα-specific inhibitor alpelisib was remarkably active against PIK3CA-mutated, HR-positive/HER2-negative BC in the SOLAR-1 trial. We hypothesized that PIK3CA alterations in Chinese BC patients across different molecular subtypes might differ from other ethnic groups and this information would be useful for selecting anti-PI3K therapy. Methods: The molecular profile of the PIK3CA gene was analyzed in 412 Chinese untreated invasive BC patients with ER/HER2 molecular subtypes, using a 540 gene next-generation sequencing panel. The results were compared to the molecular profile of Caucasian breast cancer patients in The Cancer Genome Atlas(TCGA-white). Results: Compared to wild type, PIK3CA alterations were more frequent in the ER+ subtype (49.3%, p=0.024), and tumors with low ki67 proliferation (58.3%, p=0.007) and low histological grade (grade I/II/III 80%, 53.4%, 35.9%, p&lt;0.001). Compared to TCGA Caucasian race (TCGA-white), Chinese BC patients had a higher alteration frequency (45.6% vs. 34.7%, p&lt;0.001). The p.H1047R mutation predominantly occurred among three hot spots (p.E545K, p.E542K and p.H1047R) for Chinese BC compared to that of the TCGA-white cohort (66.1% vs 43.7%, p=0.01). Nine novel mutation sites of PIK3CA were observed in the Chinese cohort that was absent among Caucasian BC patients. Among the four ER/HER2 molecular subtypes, ER+/HER2+ tumors harbored the most PIK3CA alterations (51.6%), while ER-/HER2- harbored the least (30.0%). However the latter presented the highest frequency of copy number amplification (19.05%). Conclusion: PIK3CA alterations prevail in nearly half of Chinese BC patients and has some different molecular features compared to that of Caucasian BC patients. The PIK3CA distribution patterns differed among four ER/HER2 subtypes. The results provide more insights for evaluating the results of PIK3CA inhibitors.
Citation Format: Minghan Jia, Ning Liao, Bo Chen, Guochun Zhang, Yulei Wang, Xiaoqing Chen, Liping Guo, Li Cao, Hsiaopei Mok, Chongyang Ren, Kai Li, Cheukfai Li, Lingzhu Wen, Jiali Lin, Guangnan Wei, Zhou Zhang, Charles M Balch. PIK3CA somatic alterations in 412 chinese invasive breast cancers: Higher frequency of mutant H1047R detected by next generation sequencing compared to breast cancer in caucasians [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr P4-09-11.
Abstract P4-12-16: A seven year single institution experience with IntrabeamTM intraoperative radiation therapy:recurrence rates and predictors of recurrence
Authors: Munford Christina , Burak William E , Miller Krista , Davis Jennifer , Neal Nicole , Price Caleb , Bertke Matthew , Hasselle Michael , Pederson Aaron 
Published: March 2020

Abstract
Objectives: Patients undergoing single fraction intraoperative radiation therapy (IORT) for early stage breast cancer were analyzed to determine rates of local recurrence and to identify predictors of local recurrence.
Materials and Methods: Patients who underwent intraoperative radiotherapy (IORT 20 Gray at 50kV using the INTRABEAMTM IORT system) have been analyzed over a 7 year period. The procedures were performed at a single institution by a single surgical and radiation oncology group. Post-operative whole breast radiotherapy (WBRT) was generally recommended in high risk patients with positive sentinel lymph nodes (SLN), lymphovascular invasion (LVI), extensive intraductal component (EIC), or positive margins requiring re-excision. Local recurrence was defined as any same breast recurrence during the follow-up period.
Results: A total of 438 patients were included in the analysis. Median follow-up was 35 months. Median age was 68 years, mean tumor size on preoperative ultrasound was 1.2 cm. Patient characteristics are listed below:
Patient/Tumor CharacteristicnGrade 1-232474.5%Grade 311125.5%Presence of LVI429.9%Presence of EIC4811.6%ER Negative429.7%PR Negative7918.4%DCIS only6514.4%Invasive Lobular only102.2%Positive SLN276.9%Re-excision performed6013.7%
A total of 16 patients (3.7%) had a local or simultaneous local/regional recurrence. Median time to recurrence was 24.5 months. When analyzing associations between predictor variables and local recurrence using logistic regression, it was found that high tumor grade, EIC, LVI, DCIS or DCIS component, and need for re-excision were significant (p&lt;0.05) predictors of local recurrence. Furthermore, there was a strong association with local recurrence and time to local recurrence when adjuvant endocrine therapy was recommended but the patient was either non-compliant or discontinued use due to side-effects (odds ratio 0.064, p&lt;0.0005).
Conclusions: INTRABEAMTM IORT can be used in select breast cancer patients with low local recurrence rates. Unfavorable tumor features and non-compliance with adjuvant endocrine therapy result in the highest risk of local recurrence. Better patient selection and pre-treatment education should minimize this risk.
Citation Format: Christina Munford, William E Burak Jr, Krista Miller, Jennifer Davis, Nicole Neal, Caleb Price, Matthew Bertke, Michael Hasselle, Aaron Pederson. A seven year single institution experience with IntrabeamTM intraoperative radiation therapy:recurrence rates and predictors of recurrence [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr P4-12-16.