bluuebunny/crossref_metadata_2025_split huggingface dataset:
Abstract 2057: Delivering on the Vision of Bench to Bedside: A Rare Disease Funding Community Collaboration to Develop Effective Therapies for Neurofibromatosis Type 1 Tumors
Authors: La Rosa Salvatore , Bakker Annette C. , Browder Vidya , Blakeley Jaishri O. , Verma Sharad K. , Wong Ling M. , Morris Jill , Bora Naba 
Published: September 2020

Abstract
The time from identifying a drug target to a new drug approval is often measured in decades and can take even longer for therapies to treat rare diseases. In fact, 95% of rare diseases do not have a specific therapy approved at all. Coordinated efforts to augment the drug development pipeline along with long-term and comprehensive support that enable scientific breakthroughs for rare diseases is possible, but it requires integration across multiple stakeholders. With the recently announced granted acceptance from the FDA to file status of the AstraZeneca and MSD (Merck) application for the MEK inhibitor selumetinib to treat plexiform neurofibromas in children, a major milestone towards the first-ever approved treatment for people with Neurofibromatosis Type 1 (NF1) associated tumors is closer than ever. This study analyzes the coordinated funding efforts of four federal and philanthropic organizations to advance drug development for NF1 associated tumors and discusses how these organizations collaborated and evolved practices to optimize funding and research support. This model could be replicated for other rare diseases if funders are able to take an active, coordinated approach to identify gaps, tools, and infrastructures most needed for that specific disease area.
Citation Format: Salvatore La Rosa, Annette C. Bakker, Vidya Browder, Jaishri O. Blakeley, Sharad K. Verma, Ling M. Wong, Jill Morris, Naba Bora. Delivering on the Vision of Bench to Bedside: A Rare Disease Funding Community Collaboration to Develop Effective Therapies for Neurofibromatosis Type 1 Tumors [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 2057.
Abstract 2059: Exploiting machine learning in local treatment strategies in cancer patients with bone metastases: A real world clinical trial
Authors: Zhao Hui , wang zhiyu , Sun jing , Gu yifeng , Yang mengdi , Yao guangyu 
Published: September 2020

Abstract
With rising life expectancy in cancer patients with bone metastases, the need for local treatment (LT) is expanding. Machine learning (ML) could create reasonable generalizations, the purpose of this article was to evaluate the use of ML model in LT strategies. Patients were treated by an interdisciplinary team in Shanghai Sixth People's Hospital. Visual analog scale (VAS) and Quality of Life (QoL) Questionnaire Bone Metastases Module scores were analyzed before, 1 week, 1, 3, and 6 months after treatments. ML models were used to calculate LT probability, and confusion matrix was used to calculate the accuracy, precision, recall and F1 score of models. ML models were further used to calculate pathological fracture (PF) probability in lung cancer patients. Of 386 patients enrolled between 2016 and 2017, 101 patients underwent LT. Significant improved VAS and pain domains scores were observed in 27 surgery patients at 1, 3 and 6m, while functional domains scores at 3 and 6m. All five scores improved significantly in 46 percutaneous osteoplasty patients at 1w, 1 and 3m. Significant improved VAS and pain domains scores were observed in 28 radiation patients at 1 and 3m, while functional domains scores at 3m. Compared with team decision-making, decision tree was superior to support vector machine and Bayesian neural networks in model building. The VAS scale, primary cancer, Frankel classification, Mirels score, C-terminal telopeptide of type I collagen (CTx), age, mid-fragment of osteocalcin (MID), character of bone metastases, CA153, and visceral metastases were included in the DT model. In 386 patients, the values of decision tree for the accuracy, precision, recall and F1 score were 86.53%, 78.44%, and 64.90% and 0.69 respectively. 124 lung cancer patients were used to calculate PF probability by decision tree. We also put driving gene mutation and five differentially expressed proteins into the model. The VAS scale, character of bone metastases, age, driving gene mutation, C-terminal telopeptide of type I collagen (CTx), mid-fragment of osteocalcin (MID) and enolase 1 (ENO1) were included in the DT model. The sensitivity, specificity and accuracy of DT model was 90.52%, 87.19% and 77.72%. Appropriate LT provided significant pain relief and improvement in QoL. The ML model is effective in helping physicians determine which patient may be the candidate for LT.
Citation Format: Hui Zhao, zhiyu wang, jing Sun, yifeng Gu, mengdi Yang, guangyu Yao. Exploiting machine learning in local treatment strategies in cancer patients with bone metastases: A real world clinical trial [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 2059.
Abstract 2094: Improving cancer cytogenetic case review with a new machine learning system
Authors: Roytman Megan , Wasnikar Viren , An Paul , Kashevan Raja , Verma Shalini , Shams Soheil 
Published: September 2020

Abstract
A novel machine learning system trained on The Cancer Genome Atlas (TCGA) data has been designed to help with classification, prognostic measures, and monitoring treatment responses in cancer management. The utility of this system will be demonstrated using a set of retrospective samples.
Cytogenetic analysis has long been utilized in clinical cancer care with conventional cytogenetic methods such as chromosomal banding and FISH still standard protocols for hematologic malignancies. With the advent of microarrays, smaller and more complex variants have been discovered in cancer samples but identifying the potential impact of many alterations such as copy number variation (CNV) and loss of heterozygosity (LOH) has not been fully exploited. A typical cancer cytogenetic report can list many tens of variants with unclear clinical implications.
To bridge this gap and assist with determining the clinical implications of such alterations, we have developed a novel machine learning system that has been trained using data from The Cancer Genome Atlas (TCGA). The TCGA data has been processed using the SNP-FASST2 segmentation algorithm followed by manual review for ploidy adjustment yielding high quality regions of CNV and LOH for over 6000 cases across 29 cancer types. Our novel neural network used this processed data to arrange samples based on their CNV and LOH profile across a two-dimensional map. The proximity of one sample to another on this map corresponds to its similarity in terms of CNV and LOH profile. To apply this system in a clinical setting, we have designed a case review system that aligns a new case with the learned cancer map to provide information on the similarity of the case with ones in TCGA. This enables rapid verification of tumor type or detection of a different origin for the sample than the one reported. In addition, the system can create a prognostic score using clinical survival data for the samples in TCGA.
Here we will demonstrate the utility of the system in classifying new cases against the learned cancer map and estimating prognostic measures.
Citation Format: Megan Roytman, Viren Wasnikar, Paul An, Raja Kashevan, Shalini Verma, Soheil Shams. Improving cancer cytogenetic case review with a new machine learning system [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 2094.
Abstract 2116: Strength of immune selection in tumors varies with sex and age
Authors: Castro Andrea , Pyke Rachel M. , Zanetti Maurizio , Carter Hannah 
Published: September 2020

Abstract
Individual MHC genotype constrains the mutational landscape during tumorigenesis. Immune checkpoint inhibition reactivates immunity against tumors that escaped immune surveillance in approximately 30% of cases. Recent studies demonstrated poorer response rates in female and younger melanoma patients. Although immune responses differ with sex and age, the role of MHC-based immune selection in this context is unknown. We found that tumors in younger and female individuals accumulated more poorly presented driver mutations than those in older and male patients, despite no differences in MHC genotype. Younger patients showed strongest effects of MHC-based driver mutation selection, with younger females showing compounded effects and nearly twice as much MHC-II based selection. This study presents the first evidence that strength of immune selection during tumor development varies with sex and age, and may influence the availability of mutant peptides capable of driving effective response to immune checkpoint inhibitor therapy.
Citation Format: Andrea Castro, Rachel M. Pyke, Maurizio Zanetti, Hannah Carter. Strength of immune selection in tumors varies with sex and age [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 2116.
Abstract 2148: Screening of cancer-reactive T cells in lymph nodes in colorectal cancer patients
Authors: Kiyotani Kazuma , Okamura Kazumi , Nagayama Satoshi , Nakamura Yusuke 
Published: September 2020

Abstract
Tumor draining lymph nodes (TDLNs) are located in the routes of lymphatic drainage from a primary tumor and have the highest metastasis in various types of solid tumors. TDLNs are considered as a tissue to activate the antitumor immunity, where antigen-specific effector T cells are generated and released to the blood stream. These effector T cells then infiltrate into the tumor site and attack cancer cells. However, it has not been investigated whether cancer-reactive T cells are present in lymph nodes. Through T cell receptor (TCR) repertoire analysis of cancer tissues and total 203 regional lymph nodes from 23 colorectal cancer patients, we previously found that regional lymph nodes, especially metastasis-positive lymph nodes, contain T cells with TCR shared with primary cancer tissues. In this study, we collected surgically-resected fresh cancer tissues and total 12 regional lymph nodes from 4 colorectal cancer patients. From these freshly-obtained cancer tissues and lymph nodes, we isolated single cells and then cultured T cells and patient-derived cancer cells. We co-cultured each of T cells from the 12 lymph nodes with autologous cancer cells, and examined their cancer-reactivity using IFN-γ ELISPOT assay. Six among the 7 metastasis-positive lymph nodes, shows significant production of INF-γ, suggesting the presence of cancer-reactive T cells in the lymph nodes. We also detected cancer-reactive T cells in 3 out of 5 metastasis-negative lymph nodes. In FACS analysis, we found the proportion of TIM3+ cells in CD8+PD1+ T cells were lower in T cells in lymph nodes compared to T cells in primary tumor. These data suggest that lymph nodes may be a good source of T cells for cancer immunotherapy.
Citation Format: Kazuma Kiyotani, Kazumi Okamura, Satoshi Nagayama, Yusuke Nakamura. Screening of cancer-reactive T cells in lymph nodes in colorectal cancer patients [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 2148.
Abstract 219: A high throughput single-cell workflow for paired genomic and phenotypic analysis
Authors: Dhingra Dalia , Mendez Pedro , Ooi Aik , Wang Shu , Gulati Saurabh , Sciambi Adam , Ruff Dave 
Published: September 2020

Abstract
Fusion gene detection has long been a focus of cancer research, when combined with mutations found in gDNA, can lead to a better understanding of disease progression. One example, BCR-ABL, a marker for CML and AML stem cells, is a target for tyrosine kinase inhibitor (TKI) treatments; however, there are mutations within BCR-ABL that evade TKIs and are selectively resistant to drug therapy. Single-cell technologies are now able to provide information into genomic DNA content, RNA expression, and protein surface markers, unmasked by the heterogeneity found in bulk data. However, multimodal analysis from the same single cell has not been straightforward to implement in a high throughput single-cell workflow. Here, we report the development of chemistries that enable analyses of both targeted genomic DNA and RNA sequencing from the same cell.
This workflow relies on the Tapestri platform, which uses a two-step microfluidic droplet system for the analysis of thousands of cells per run. The first droplet encapsulates each cell and releases the DNA while the second droplet introduces additional reagents for enzymatic manipulations on the cellular analytes. Novel primer designs are leveraged to capture both DNA and RNA and provide for independent barcoded sequence information. We first establish the utility of the Tapestri platform for accurate gene expression assessment with a targeted panel for breast cancer. For fusion gene transcript detection, panels were designed for AML and CML including primers targeting multiple potential variants of BCR-ABL transcripts. Cell lines were used to show high sensitivity and specificity of fusion sequence calls from RNA in cells where the expected SNVs, indels, and CNVs were also detected from gDNA. More complex targeted RNA and DNA panels, such as one for breast cancer with 35 gene expression amplicons and 88 genotyping amplicons, were also tested where we show agreement between cells clustered based on RNA expression and the cell assignment based on SNVs from gDNA.
This single-cell multimodal workflow on the Tapestri platform currently has the power to quantitatively link genotypic and phenotypic data from the same cell with future potential in biomarker identification and ultimately, to link to best-fit therapeutics.
Citation Format: Dalia Dhingra, Pedro Mendez, Aik Ooi, Shu Wang, Saurabh Gulati, Adam Sciambi, Dave Ruff. A high throughput single-cell workflow for paired genomic and phenotypic analysis [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 219.
Abstract 2278: CTLA-4 targeted engineered toxin bodies designed to deplete regulatory T cells (Tregs)
Authors: Iberg Aimee , Acquaye-Seedah Edith , Rabia Lilia A. , Robinson Garrett L. , Ramos Hilario J. , Dekker Joseph D. , Zhao Jay , Willert Erin K. 
Published: September 2020

Abstract
Tumor resident regulatory T cells (Tregs) are important mediators of an immunosuppressive tumor microenvironment (TME) promoting tumor immune evasion. The presence of Tregs, and a higher ratio of Tregs to effector T cells in the TME, are associated with poor prognosis. The depletion of Tregs in the TME is expected to re-expose the tumor to the immune system to allow for tumor control. CLTA-4 is expressed on the cell surface of Tregs and is a clinically validated target. Better responses to CTLA-4 monoclonal antibody (mAb) treatment are correlated with stronger ADCC-mediated Treg depletion in preclinical models, and patient FcγR polymorphism has been reported to correlate with response to CTLA-4 mAb therapy. Towards improving on current therapies, many efforts to increase effective depletion of Tregs (such as by Fc effector modification) are being pursued. Engineered toxin bodies (ETBs) are comprised of a proprietarily engineered form of Shiga-like Toxin A subunit (SLT-A) genetically fused to antibody-like binding domains. ETBs work through novel mechanisms of action and are capable of forcing internalization, self-routing through intracellular compartments to the cytosol, and inducing potent cell-kill via the enzymatic and permanent inactivation of ribosomes. Targeted ETBs are being developed to specifically target and destroy CTLA-4 expressing cells. In vitro, cells expressing CTLA-4 are effectively and specifically killed by targeted ETBs. This direct cell kill activity of the ETB has the potential to deplete Tregs in the TME without a requirement for ADCC mechanisms. ETBs have been designed to bind various CTLA-4 epitopes, and to comprise of different targeting domains formats, including monomeric and diabody single chain variable fragments (scFvs) as well as single domain and biparatopic antibody fragments. The development of a CTLA-4 targeted ETB is ongoing. The entry of a protein with direct cell kill properties into the therapeutic space represents a differentiated mechanism of action to deplete Tregs for ultimate re-invigoration of the anti-tumor immune response, and has the potential to provide benefit to patients, including in the relapsed or refractory setting.
Citation Format: Aimee Iberg, Edith Acquaye-Seedah, Lilia A. Rabia, Garrett L. Robinson, Hilario J. Ramos, Joseph D. Dekker, Jay Zhao, Erin K. Willert. CTLA-4 targeted engineered toxin bodies designed to deplete regulatory T cells (Tregs) [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 2278.
Abstract 2352: Sexual morbidity and gender disparities among young-onset colorectal cancer patients and survivors
Authors: Springer Tamara , Newcomer Kimberly , Peterson Danielle , Yarden Ronit 
Published: September 2020

Abstract
Rectal cancer incidence is rising dramatically among people younger than 50 years old. The risk has doubled four times for individuals born in the 1990s relative to those born in the 1970s. Previously, we and others showed that young-onset patients are more likely to be diagnosed at an advanced stage of colorectal cancer when compared to patients of all ages, which would render aggressive treatments. There is limited data and public discussion on the long-term effects of colorectal cancer treatments on intimacy and sexual morbidity and their long-term impact on the quality of life especially among young cancer survivors who were developing their own social and financial responsibilities and establishing their life-long goals. To explore the unique challenges and unmet needs of the young-adult patient population, a cross-sectional study was conducted. Colorectal cancer patients and survivors (N=885) diagnosed between the ages of 20 to 50 years old (median age 42 ± 7.0) completed an online questionnaire that was based on established instruments including EORTC-QOL-30, EORTC-CR-29, and EORTC-SHC-22. Patients and survivors diagnosed at stage III reported worse outcomes. Patients' comprehension of radiation sexual-side effects was assessed based on self-reported discussions with their physicians. Prior to radiation, providers were significantly less likely to discuss the many sexual side-effects and long-term consequences of radiation and surgery with women than with men. Providers were also less likely to discuss fertility preservation, a notable issue with a strong impact on young cancer patients, with women than men prior to and during treatments, regardless of their parental status. While the majority of patients reported having sexual-dysfunction after treatment, women more frequently classified different aspects of their sexual dysfunction as being 'severe.' and expressed worse body image than men. Women were more likely to experience pain while more men reported reduction in sex drive. Additionally, a strong correlation was noted between sexual dysfunction and emotional exhaustion in all young-onset patients and survivors. Together, our survey demonstrates inadequate communications between patients and providers about the irreversible sexual side-effects of colorectal cancer treatments. Younger patients and survivors are facing unique long-term challenges and require further information about fertility preservation options and emotional support regarding their sexuality post-treatment.
Citation Format: Tamara Springer, Kimberly Newcomer, Danielle Peterson, Ronit Yarden. Sexual morbidity and gender disparities among young-onset colorectal cancer patients and survivors [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 2352.
Abstract 238: Targeting glutaminolysis potentiates the efficacy of chemotherapy in RAS-driven pancreatic cancers
Authors: Mukhopadhyay Suman , Goswami Debanjan , Nissley Dwight V. , McCormick Frank 
Published: September 2020

Abstract
Pancreatic cancer is an extremely aggressive and deadly malignancy. Despite a detailed understanding of pancreatic ductal adenocarcinoma (PDAC)'s biology, the outcome of the current therapeutic regimen remains grim. Chemotherapeutic treatment is one of the first-line systemic treatments for PDAC. However, creating resistance against chemotherapy remains a major challenge. Oncogenic K-Ras mutation is one of the most common events responsible for the initiation and progression of PDAC. K-Ras mutation also promotes the activation of a transcription factor called NRF2 that is crucial for tumor development and pancreatic cancer proliferation. Our study detects differential basal levels of NRF2 in a panel of PDAC cell lines. We hypothesized that this phenomenon might reflect a greater intrinsic capacity of PDAC cells to become resistant to chemotherapy. We then demonstrated that up-regulation of NRF2 creates resistance against chemotherapy in PDAC cells. Consequently, NRF2 activation rewires metabolic pathway networks. Importantly, our metabolomics analysis revealed that, upon NRF2 activation, several metabolic pathways are reprogrammed. Recent advances in tumor metabolism signify the critical role of glutamine as a key regulator of cancer therapy. Moreover, we observed that inhibiting glutamine metabolism enhances the efficacy of chemotherapeutic drugs in PDAC cells. Taken together, our finding holds promise as a novel combination therapy for patients with pancreatic cancer marked by developed resistance against chemotherapy. Finally, this treatment strategy further establishes the potential for exploiting metabolic changes in RAS-driven cancer cells that confer novel therapeutic opportunities.
Citation Format: Suman Mukhopadhyay, Debanjan Goswami, Dwight V. Nissley, Frank McCormick. Targeting glutaminolysis potentiates the efficacy of chemotherapy in RAS-driven pancreatic cancers [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 238.