bluuebunny/crossref_metadata_2025_split huggingface dataset:
Abstract 2213: Vaping, smoking and lung cancer: A case-control study
Authors: Bittoni Marisa A. , Carbone David , Harris Randall 
Published: March 2024

Abstract
Introduction: Nicotine exposure through the use of electronic delivery systems (vaping) has been found to elevate the risk of certain conditions of the lungs, e.g., vaping associated lung injury. However, the potential impact of vaping on lung cancer risk remains largely unexplored. We, therefore, examined the association of vaping and cigarette smoking with lung cancer risk in a case-control study conducted at The Ohio State University in Columbus, Ohio.
Methods: Medical records examined from the James Cancer Hospital and Solove Research Institute revealed 4,975 cases with newly diagnosed, pathologically confirmed lung cancer during 2013-2021. These cases were compared to 27,294 controls without cancer that were group-matched on a 5:1 ratio to cases by age, gender, race and year of ascertainment. Descriptive statistics were calculated, and logistic regression analyses were performed to assess the associations between vaping, smoking and lung cancer.
Results: The lung cancer cases in this study were 55% male, 88% white, with mean age at diagnosis of 62 years. The adjusted odds ratio (OR) for individuals who reported vaping and smoking was OR=21.1 (95% CI=17.1, 26.1) versus OR=6.3 (95% CI=5.8, 6.8) for smoking only. Estimates for gender and histologic cell type of lung cancer, e.g., pulmonary adenocarcinoma, squamous cell carcinoma and small cell carcinoma, were consistently over threefold higher for vaping and smoking compared to smoking only (p&lt;0.001), and the vaping effect persisted even after adjustment for comorbidities, COPD and cardiovascular disease.
Conclusion: Adjusted estimates of odds ratios (OR) revealed over threefold higher risk of lung cancer among individuals who had vaped and smoked compared to individuals who only smoked. Our results suggest that the addition of vaping to smoking greatly accelerates the risk of developing lung cancer. Future studies are needed to further confirm these results.
Citation Format: Marisa A. Bittoni, David Carbone, Randall Harris. Vaping, smoking and lung cancer: A case-control study [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 2213.
Abstract 2260: Transcriptomic immuno-oncology investigation of B-cell lymphomas using a novel comparative workflow
Authors: Rapier-Sharman Naomi , Told Michael T. , Kim Sehi , O'Neill Kim L. , Pickett Brett E. 
Published: March 2024

Abstract
Patients with B-cell lymphoma currently have limited treatment options, often with serious side effects; for example, B-cell lymphoma patients undergoing chemo- and radiation therapies experience poor health from off-target toxicity. Similarly, though CD19 CAR T-cell therapy is very effective, patients suffer lifelong B-cell aplasia as a side effect. Comparing a cancer to an autoimmune disease in the same tissue type may grant us additional insights on the immune dysregulation of the cancer, leading to development of more immune-aware cancer treatments. We introduce a new data-driven comparative workflow for the analysis of immuno-oncology attributes by comparing a cancer and an autoimmune disease in the same tissue type. As an example use case, we compare primary B-cell lymphomas to primary B-cells from systemic lupus erythematosus with the goal of delineating new mechanisms that can be leveraged to treat B-cell lymphomas. Our analysis will utilize bulk RNA-sequencing (RNA-seq) of B-cells for initial discovery, followed by single-cell RNA-sequencing (scRNA-seq) of Peripheral Blood Mononuclear Cells (PBMCs) for validation. Our analytical framework incorporates differential gene analysis, GO Terms, known protein-protein interactions, principal component analysis, and machine learning for biomarker detection. Here, we describe our novel tool in detail and share the results of our lymphoma use case to gain a better understanding of the targetable immune-related attributes of B-cell lymphoma. We expect that this novel tool, along with the results of our B-cell lymphoma use case, will contribute to the continued development of immune-focused treatment options for B-cell lymphoma and other cancers.
Citation Format: Naomi Rapier-Sharman, Michael T. Told, Sehi Kim, Kim L. O'Neill, Brett E. Pickett. Transcriptomic immuno-oncology investigation of B-cell lymphomas using a novel comparative workflow [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 2260.
Abstract 2280: HPV integration identifies emerging oncogenes and carcinogenic mechanisms, potentially indicating tumor recurrences
Authors: Li Shiting , Xia Shaomiao , Lawas Maria , Qin Tingting , Grab Bailey , D'Silva Nisha , Rozek Laura , Sartor Maureen 
Published: March 2024

Abstract
HPV integration events in Head and neck squamous cell carcinomas (HNSCC) are strongly associated with carcinogenesis and tumor progression. Previous studies have elucidated the mechanisms and structures of HPV-human fusion events, pinpointing potential integration “hotspots” (i.e. genes with nearby HPV integration in recurrent patients). However, none has comprehensively investigated the effects of HPV integration on both HPV and human gene expression, nor assessed the clinical implications of these bidirectional expression changes.
In this study, we conducted bulk RNA sequencing on 67 Formalin-Fixed Paraffin-Embedded Oropharyngeal Squamous Cell Carcinoma (OPSCC) tumor samples from the University of Michigan hospital, and analyzed them in conjunction with bulk and single cell RNA-seq from another &gt;200 HPV(+) HNSCC patients from four previous studies. Among the 117 samples confidently identified as HPV integration positive, we recaptured all previously known integration “hotspot” genes as well as several novel ones that have altered expression in the integrated samples.
Exploring the impact of HPV integration on the expression of human and HPV genes, we found that HPV integration in HNSCC is strongly associated with keratinization, immune response, and the development of HPV(+) HNSCC subtypes. Upon HPV integration, expression of non-oncogenic HPV genes is often lost. We hypothesized that the expression ratio of these potentially HPV immunogenic genes (E1-E5, L1,L2) to the HPV oncogenic genes E6 and E7 (termed the ImmunOnco Score) would predict clinical outcomes. Survival analysis of 70 University of Michigan patients showed low ImmunOnco Score is associated with tumor recurrence.
Citation Format: Shiting Li, Shaomiao Xia, Maria Lawas, Tingting Qin, Bailey Grab, Nisha D'Silva, Laura Rozek, Maureen Sartor. HPV integration identifies emerging oncogenes and carcinogenic mechanisms, potentially indicating tumor recurrences [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 2280.
Abstract 2282: Predictive association of tumor cells hijacked NFATC2 activities with resistance to immune checkpoint inhibition in melanoma patients
Authors: Lawal Bashir , Wang Yue , Lotfinejad Parisa , Wang Xiaosong 
Published: March 2024

Abstract
Background: Immune checkpoint blockade (ICB) has emerged as an effective cancer therapy. However, only a small fraction of patients receives benefits whereas a significant subset of patients experienced severe or even lethal autoimmune diseases. Stratifying patients that would benefit from immunotherapy remain a highly unmet clinical need. Dysregulations of transcriptional programs have been implicated in cancer initiation and progression. To date, there is a paucity of studies on the predictive values of transcriptional factors on ICB response based on the most recently emerged ICB clinical trial datasets. We reasoned that cancer cells may hijack key transcriptional programs in hematological cells to evade the attack from immune cells and acquired tolerance to immunotherapy.
Method: Herein, we used an R package singscore/1.14.0 to compute the TFs activity scores based on their validated gene targets (TGs). Leveraging melanoma clinical trial datasets, we analyzed the predictive association of the TF scores with resistance to anti-PD1 ICB. The R package, iGenSig was used to evaluate the potential confounding variables.
Results: Our landscape correlation analysis revealed NFATC2 (Nuclear Factor Of Activated T Cells 2)-TGs as the most significant predictor of anti-PD-1 ICB resistance in melanoma. NFATCT-TGS as a predictor of anti-PD1 resistance is confounded by liver metastasis and achieved AUC range between 0.71 to 0.74 in three datasets (PRJEB23709, GSE160638, and Phs000452). In addition, prior anti-CTLA4 exposure (AUC=0.87 and 0.89) is associated with higher predictive efficacy of NFATC2-TGS than anti-CTLA4 naïve tumor (AUC=0.61 and 0.69) in phs000452 and GSE91061 datasets. Survival analysis revealed that NFATC2 is a better predictor of progressive-free survival (PFS; HR=5.95), and overall survival (OS; HR= 3.28-3.38) in anti-CTLA4 exposed tumor than anti-CTLA4 naïve tumor (PFS: HR=1.92, and OS; HR=1.64-2.17). Finally, NFATC2-TGS show strong inhibitory correlation with B cells and T cells infiltration, but strongly correlated with tumor purity.
Conclusion: We demonstrate that NFATC2 TGS predicts ICB benefits in melanoma patients, and thus may guide the recruitment of melanoma patients for anti-PD1 ICB. Our data provide support to the hypothesis that melanoma acquired NFATC2 transcriptional program to avoid immune cells evasion and acquired tolerance to ICB immunotherapy
Citation Format: Bashir Lawal, Yue Wang, Parisa Lotfinejad, Xiaosong Wang. Predictive association of tumor cells hijacked NFATC2 activities with resistance to immune checkpoint inhibition in melanoma patients [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 2282.
Abstract 2326: Integrating single nucleotide variants (SNVs), copy number alterations (CNAs), and structural variants (SVs) into single-cell clonal lineage inference
Authors: Bristy Nishat , Fu Xuecong , Schwartz Russell 
Published: March 2024

Abstract
Background: We extend algorithms for clonal lineage inference (``tumor phylogenetics'') from single-cell DNA sequence (scDNA-seq) data to accommodate broader classes of genetic variants, including single nucleotide variants (SNVs), copy number alterations (CNAs), and structural variants (SVs).
Methods: We develop a computational method based on constrained optimization, posing a problem of inferring cellular lineage trees consistent with a given scDNA-seq data set constrained to follow a Dollo parsimony model for SNVs and SVs. We then seek an optimal tree consistent with these constraints so as to optimize for a CNA minimum evolution model balanced against measure of consistency of the different data types with one another relative to the reconstructed set of clones. We pose this problem as an integer linear program (ILP) that we solve heuristically via a coordinate descent algorithm. We tested the resulting method on a combination of synthetic scDNA-seq data and publicly available real data.
Results: Results on synthetic data show the method to be effective at constructing lineage trees under a variety of parameter domains, including variations in noise levels, clone numbers, single cells, and mutation rates. We further show it to yield improved accuracy over widely used prior models that operate on only subsets of these variant types. Application to previously published scDNA-seq data demonstrate the method to be effective at inferring clonal lineage trees incorporating all three variant types. The results further show how the different kinds of variants can contribute in tandem to progression along single cell lineages or to the emergence of clones exhibiting hallmarks of distinct mechanisms of progression.
Conclusion: The results support the effectiveness of our method in resolving accurate trees from scDNA-seq data including diverse variant types, as well as the value of considering these mutation types collectively in developing a comprehensive understanding of how various forms of somatic mutability together shape clonal evolution in cancers.
Citation Format: Nishat Bristy, Xuecong Fu, Russell Schwartz. Integrating single nucleotide variants (SNVs), copy number alterations (CNAs), and structural variants (SVs) into single-cell clonal lineage inference [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 2326.
Abstract 2329: Cancer region definition using spatial gene expression patterns by super resolution reconstruction algorithm for spatial transcriptomics data
Authors: Park Jeongbin , Cook Seungho , Lee Dongjoo , Choi Jinyeong , Yoo Seongjin , Im Hyung-Jun , Lee Daeseung , Choi Hongyoon 
Published: March 2024

Abstract
Background: Spatially resolved transcriptomics (ST) has enabled a variety of cancer research on the heterogeneity of tumor microenvironment. However, when identifying cancer boundaries based on ST, the limited resolution of ST such as Visium hinders the accurate identification of cancerous regions. To address these issues, we have developed a novel approach for accurately classifying regions of the tumor by using deep image prior (DIP) algorithm to convert Visium data into high-resolution images.
Methods: We proposed SuperST, which utilizes deep image prior to transform low-resolution ST data into high-resolution images, providing more accurate spatial marker expression patterns. This method was used to define cancer regions by combining with a pre-trained deep learning algorithm that recognizes spatial patterns. ST data of hepatocellular carcinoma (HCC) patients were used to apply SuperST. Firstly, 400 spatially variable genes were identified. SuperST leverages the deep image prior (DIP) algorithm and a U-Net neural network to transform ST data into high-resolution ones without needing ground-truth high-resolution data. The final high-resolution images of gene expression data were used to extract 512-dimensional feature vectors for each gene via a pre-trained convolutional neural network model (VGG16). Subsequently, we apply K-means clustering to these features to identify transcriptionally distinct tissue regions considering spatial information and compared with the human-labeled cancer regions.
Results: The cancer region detection using spatial gene expression data and our algorithm yielded results that substantially align with the human annotations on the H&E images. Furthermore, compared to the cancer definition obtained using the CopyKat and SPACET algorithms, our results were more spatially consistent for cancerous regions as well as providing high-resolution image-level definition of cancer region margin. This indicates that our algorithm better utilizes spatial information and more effectively overcomes the low resolution of ST data.
Conclusion: This research demonstrates the effective application of our SuperST algorithm to the challenging problem of cancer region detection only using spatial gene expression data. It suggests that our algorithm could be utilized for a variety of problems in spatial biology in cancer research.
Citation Format: Jeongbin Park, Seungho Cook, Dongjoo Lee, Jinyeong Choi, Seongjin Yoo, Hyung-Jun Im, Daeseung Lee, Hongyoon Choi. Cancer region definition using spatial gene expression patterns by super resolution reconstruction algorithm for spatial transcriptomics data [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 2329.
Abstract 24: Utilizing T cell receptor-based therapy to treat anaplastic thyroid cancer
Authors: Hung Shao-Hsi , Henderson Ying C. , Ke Pan , Chiu Yulun , Singh Shailbala , Chen Yunyun , Lai Stephen Y. , Yee Cassian 
Published: March 2024

Abstract
Anaplastic thyroid cancer (ATC) is one of the most aggressive solid tumor in thyroid tissue, with a 6-month medium overall survival. The effectiveness of conventional treatments in extending the survival of patients is limited. Therefore, there is an urgent need to develop novel systemic therapeutic interventions. Adoptive cell therapy has revolutionized cancer immunotherapy by successfully treating B-cell malignancies through chimeric antigen receptor-based approaches. For solid tumors, there is a need to identify a broader spectrum of tumor target antigens, and the field has now shifted towards leveraging T cell receptors (TCRs) which can recognize both intracellular and extracellular antigen-derived epitopes. Our team has established an immunogenic epitope discovery pipeline, followed by a specialized protocol for empiric validation of candidate epitopes. We characterized immunogenic epitopes by coupling tandem mass spectrometry of MHC-eluted peptides with tumor proteome and MHC-peptide binding prediction databases. By integrating multi-omics data (genomics, transcriptomics, and immunopeptidomics) from both in-house and publicly available ATC databases, we find that ATC exhibits significant upregulation of pathways associated with microtubule-based movement, chromosome segregation, and kinetochore complex components. We have identified several HLA-A2- and A24-restricted immunogenic peptides representing these pathway-associated proteins that covered more than 60% of the patient population. These immunogenic peptides were subsequently utilized to isolate antigen-specific T cells from peripheral blood and identify cognate TCR. These peptide-specific T lymphocytes elicit cytotoxicity toward multiple HLA-matched ATC cell lines and tumor samples in vitro and in vivo. In conclusion, our studies contribute to the development of a new treatment paradigm for treating ATC.
Citation Format: Shao-Hsi Hung, Ying C. Henderson, Pan Ke, Yulun Chiu, Shailbala Singh, Yunyun Chen, Stephen Y. Lai, Cassian Yee. Utilizing T cell receptor-based therapy to treat anaplastic thyroid cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 24.
Abstract 2401: Changes in skeletal muscle mass after gastrointestinal cancer surgery by body composition
Authors: Maeda Yuto , Miyamoto Yuji , Ohuchi Mayuko , Hiyoshi Yukiharu , Yoshida Naoya , Baba Hideo 
Published: March 2024

Abstract
Background: Previous studies have extensively explored the correlation between preoperative skeletal muscle mass and long-term survival in gastrointestinal cancers. However, investigations into postoperative skeletal muscle mass alterations are limited. In gastrointestinal cancers, factors such as the tumor and surgical interventions can significantly impact dietary intake, nutritional status, and skeletal muscle mass, affecting postoperative body composition. This study aimed to examine these postoperative changes in skeletal muscle mass across different gastrointestinal cancers, including esophageal, gastric, and colorectum.
Methods: This study encompassed 969 patients with Stage I-III esophageal (307 cases), gastric (278 cases), and colorectal (384 cases) cancers who underwent radical resection between 2005 and 2019. Skeletal muscle mass was quantified as the total psoas volume (TPV), measured using Ziostation2® imaging software from preoperative and postoperative CT scans at 1, 2, and 3 years. The study compared postoperative TPV trends across the different cancer types.
Results: The study cohort comprised patients with esophageal (median age 66 years, 85% male), gastric (65 years, 60%), and colorectal cancers (67 years, 55%). Median BMIs were 21.5, 19.4, and 22.6 kg/m2, and median TPVs were 352.0, 305.8, and 309.5 cm3 for esophageal, gastric, and colorectal cancers, respectively. Esophageal cancer patients had significantly higher TPV and male predominance, while gastric cancer patients had notably lower BMI. Relative to preoperative TPV, the postoperative TPV at three years was 0.92, 0.91, and 0.96 for esophageal, gastric, and colorectal cancers, respectively. A year-by-year decrease in TPV was observed for each cancer type, with colorectal cancer demonstrating a less pronounced decrease compared to esophageal and gastric cancers (p&lt;0.01). Stage-wise analysis revealed no significant differences among the cancer types. Regarding gender, no significant differences were noted between gastric and colorectal cancers, but esophageal cancer showed a more marked decrease in TPV in males compared to females. In recurrent cases, no significant TPV differences were observed in esophageal cancer, while recurrent gastric and colorectal cancers exhibited significant TPV decreases.
Conclusions: The study indicates a general decline in TPV following gastrointestinal cancer surgery, with the extent of reduction varying according to the type of tumor and treatment.
Citation Format: Yuto Maeda, Yuji Miyamoto, Mayuko Ohuchi, Yukiharu Hiyoshi, Naoya Yoshida, Hideo Baba. Changes in skeletal muscle mass after gastrointestinal cancer surgery by body composition [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 2401.