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1. Deciphering genomic codes using advanced NLP techniques: a scoping review

Author

Cheng, Shuyan, Wei, Yishu, Zhou, Yiliang, Xu, Zihan, Wright, Drew N, Liu, Jinze, and Peng, Yifan

Subjects
Quantitative Biology - Genomics, Computer Science - Artificial Intelligence
Abstract

Objectives: The vast and complex nature of human genomic sequencing data presents challenges for effective analysis. This review aims to investigate the application of Natural Language Processing (NLP) techniques, particularly Large Language Models (LLMs) and transformer architectures, in deciphering genomic codes, focusing on tokenization, transformer models, and regulatory annotation prediction. The goal of this review is to assess data and model accessibility in the most recent literature, gaining a better understanding of the existing capabilities and constraints of these tools in processing genomic sequencing data. Methods: Following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, our scoping review was conducted across PubMed, Medline, Scopus, Web of Science, Embase, and ACM Digital Library. Studies were included if they focused on NLP methodologies applied to genomic sequencing data analysis, without restrictions on publication date or article type. Results: A total of 26 studies published between 2021 and April 2024 were selected for review. The review highlights that tokenization and transformer models enhance the processing and understanding of genomic data, with applications in predicting regulatory annotations like transcription-factor binding sites and chromatin accessibility. Discussion: The application of NLP and LLMs to genomic sequencing data interpretation is a promising field that can help streamline the processing of large-scale genomic data while also providing a better understanding of its complex structures. It has the potential to drive advancements in personalized medicine by offering more efficient and scalable solutions for genomic analysis. Further research is also needed to discuss and overcome current limitations, enhancing model transparency and applicability.

Published
2024
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2. Environment Scan of Generative AI Infrastructure for Clinical and Translational Science

Author

Idnay, Betina, Xu, Zihan, Adams, William G., Adibuzzaman, Mohammad, Anderson, Nicholas R., Bahroos, Neil, Bell, Douglas S., Bumgardner, Cody, Campion, Thomas, Castro, Mario, Cimino, James J., Cohen, I. Glenn, Dorr, David, Elkin, Peter L, Fan, Jungwei W., Ferris, Todd, Foran, David J., Hanauer, David, Hogarth, Mike, Huang, Kun, Kalpathy-Cramer, Jayashree, Kandpal, Manoj, Karnik, Niranjan S., Katoch, Avnish, Lai, Albert M., Lambert, Christophe G., Li, Lang, Lindsell, Christopher, Liu, Jinze, Lu, Zhiyong, Luo, Yuan, McGarvey, Peter, Mendonca, Eneida A., Mirhaji, Parsa, Murphy, Shawn, Osborne, John D., Paschalidis, Ioannis C., Harris, Paul A., Prior, Fred, Shaheen, Nicholas J., Shara, Nawar, Sim, Ida, Tachinardi, Umberto, Waitman, Lemuel R., Wright, Rosalind J., Zai, Adrian H., Zheng, Kai, Lee, Sandra Soo-Jin, Malin, Bradley A., Natarajan, Karthik, Price II, W. Nicholson, Zhang, Rui, Zhang, Yiye, Xu, Hua, Bian, Jiang, Weng, Chunhua, and Peng, Yifan

Subjects
Computer Science - Computers and Society, Computer Science - Artificial Intelligence, Computer Science - Human-Computer Interaction
Abstract

This study reports a comprehensive environmental scan of the generative AI (GenAI) infrastructure in the national network for clinical and translational science across 36 institutions supported by the Clinical and Translational Science Award (CTSA) Program led by the National Center for Advancing Translational Sciences (NCATS) of the National Institutes of Health (NIH) at the United States. With the rapid advancement of GenAI technologies, including large language models (LLMs), healthcare institutions face unprecedented opportunities and challenges. This research explores the current status of GenAI integration, focusing on stakeholder roles, governance structures, and ethical considerations by administering a survey among leaders of health institutions (i.e., representing academic medical centers and health systems) to assess the institutional readiness and approach towards GenAI adoption. Key findings indicate a diverse range of institutional strategies, with most organizations in the experimental phase of GenAI deployment. The study highlights significant variations in governance models, with a strong preference for centralized decision-making but notable gaps in workforce training and ethical oversight. Moreover, the results underscore the need for a more coordinated approach to GenAI governance, emphasizing collaboration among senior leaders, clinicians, information technology staff, and researchers. Our analysis also reveals concerns regarding GenAI bias, data security, and stakeholder trust, which must be addressed to ensure the ethical and effective implementation of GenAI technologies. This study offers valuable insights into the challenges and opportunities of GenAI integration in healthcare, providing a roadmap for institutions aiming to leverage GenAI for improved quality of care and operational efficiency.

Published
2024
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3. Small circular RNAs as vaccines for cancer immunotherapy

Author

Zhang, Yu, Liu, Xiang, Shen, Tingting, Wang, Qiyan, Zhou, Shurong, Yang, Suling, Liao, Shimiao, Su, Ting, Mei, Lei, Zhang, Bei, Huynh, Khoa, Xie, Linying, Guo, Youzhong, Guo, Chunqing, Tyc, Katarzyna M., Qu, Xufeng, Wang, Xiang-Yang, Liu, Jinze, and Zhu, Guizhi

Published
2025
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4. Single-cell and spatially resolved interactomics of tooth-associated keratinocytes in periodontitis

Author

Easter, Quinn T., Fernandes Matuck, Bruno, Beldorati Stark, Germán, Worth, Catherine L., Predeus, Alexander V., Fremin, Brayon, Huynh, Khoa, Ranganathan, Vaishnavi, Ren, Zhi, Pereira, Diana, Rupp, Brittany T., Weaver, Theresa, Miller, Kathryn, Perez, Paola, Hasuike, Akira, Chen, Zhaoxu, Bush, Mandy, Qu, Xufeng, Lee, Janice, Randell, Scott H., Wallet, Shannon M., Sequeira, Inês, Koo, Hyun, Tyc, Katarzyna M., Liu, Jinze, Ko, Kang I., Teichmann, Sarah A., and Byrd, Kevin M.

Published
2024
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7. Realtime Safety Control for Bipedal Robots to Avoid Multiple Obstacles via CLF-CBF Constraints

Author

Liu, Jinze, Li, Minzhe, Huang, Jiunn-Kai, and Grizzle, Jessy W.

Subjects
Computer Science - Robotics
Abstract

This paper presents a reactive planning system that allows a Cassie-series bipedal robot to avoid multiple non-overlapping obstacles via a single, continuously differentiable control barrier function (CBF). The overall system detects an individual obstacle via a height map derived from a LiDAR point cloud and computes an elliptical outer approximation, which is then turned into a CBF. The QP-CLF-CBF formalism developed by Ames et al. is applied to ensure that safe trajectories are generated. Liveness is ensured by an analysis of induced equilibrium points that are distinct from the goal state. Safe planning in environments with multiple obstacles is demonstrated both in simulation and experimentally on the Cassie biped.

Published
2023

12. SPTLC3 Is Essential for Complex I Activity and Contributes to Ischemic Cardiomyopathy

Author

Kovilakath, Anna, Mauro, Adolfo G., Valentine, Yolander, Raucci, Frank, Jamil, Maryam, Carter, Christiane, Thompson, Jeremy, Chen, Qun, Gisela, Beutner, Yue, Yang, Allegood, Jeremy, Wang, Xiaoxin X., Dail, Jordan, Devarakonda, Teja, Myakala, Komuraiah, Windle, Jolene J., Subler, Mark A., Montefusco, David, Willard, Belinda, Javaheri, Ali, Bernas, Tytus, Mahata, Sushil K., Levi, Moshe, Liu, Jinze, Porter, George A., Jr, Lesnefsky, Edward J., Salloum, Fadi N., and Cowart, L. Ashley

Published
2024
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16. A Brief Analysis of Street-Stall Economy

Author

Liu, Jinze, Appolloni, Andrea, Series Editor, Caracciolo, Francesco, Series Editor, Ding, Zhuoqi, Series Editor, Gogas, Periklis, Series Editor, Huang, Gordon, Series Editor, Nartea, Gilbert, Series Editor, Ngo, Thanh, Series Editor, Striełkowski, Wadim, Series Editor, Bhunia, Amalendu, editor, Ahmad, Rubi Binti, editor, and Zhu, Yifeng, editor

Published
2023
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20. Spatial metabolomics reveals glycogen as an actionable target for pulmonary fibrosis

Author

Conroy, Lindsey R., Clarke, Harrison A., Allison, Derek B., Valenca, Samuel Santos, Sun, Qi, Hawkinson, Tara R., Young, Lyndsay E. A., Ferreira, Juanita E., Hammonds, Autumn V., Dunne, Jaclyn B., McDonald, Robert J., Absher, Kimberly J., Dong, Brittany E., Bruntz, Ronald C., Markussen, Kia H., Juras, Jelena A., Alilain, Warren J., Liu, Jinze, Gentry, Matthew S., Angel, Peggi M., Waters, Christopher M., and Sun, Ramon C.

Published
2023
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22. Eating Disorder and Its Causes

Author

Liu, Jinze, Tian, Xirui, Wang, Yibo, Zhong, Hopan, Striełkowski, Wadim, Editor-in-Chief, Black, Jessica M., Series Editor, Butterfield, Stephen A., Series Editor, Chang, Chi-Cheng, Series Editor, Cheng, Jiuqing, Series Editor, Dumanig, Francisco Perlas, Series Editor, Al-Mabuk, Radhi, Series Editor, Scheper-Hughes, Nancy, Series Editor, Urban, Mathias, Series Editor, Webb, Stephen, Series Editor, Holl, Augustin, editor, Chen, Jun, editor, and Guan, Guiyun, editor

Published
2022
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25. Cytoplasmic synthesis of endogenous Alu complementary DNA via reverse transcription and implications in age-related macular degeneration

Author

Fukuda, Shinichi, Varshney, Akhil, Fowler, Benjamin J., Wang, Shao-bin, Narendran, Siddharth, Ambati, Kameshwari, Yasuma, Tetsuhiro, Magagnoli, Joseph, Leung, Hannah, Hirahara, Shuichiro, Nagasaka, Yosuke, Yasuma, Reo, Apicella, Ivana, Pereira, Felipe, Makin, Ryan D., Magner, Eamonn, Liu, Xinan, Sun, Jian, Wang, Mo, Baker, Kirstie, Marion, Kenneth M., Huang, Xiwen, Baghdasaryan, Elmira, Ambati, Meenakshi, Ambati, Vidya L., Pandey, Akshat, Pandya, Lekha, Cummings, Tammy, Banerjee, Daipayan, Huang, Peirong, Yerramothu, Praveen, Tolstonog, Genrich V., Held, Ulrike, Erwin, Jennifer A., Paquola, Apua C. M., Herdy, Joseph R., Ogura, Yuichiro, Terasaki, Hiroko, Oshika, Tetsuro, Darwish, Shaban, Singh, Ramendra K., Mozaffari, Saghar, Bhattarai, Deepak, Kim, Kyung Bo, Hardin, James W., Bennett, Charles L., Hinton, David R., Hanson, Timothy E., Röver, Christian, Parang, Keykavous, Kerur, Nagaraj, Liu, Jinze, Werner, Brian C., Sutton, S.Scott, Sadda, Srinivas R., Schumann, Gerald G., Gelfand, Bradley D., Gage, Fred H., and Ambati, Jayakrishna

Published
2021

31. High-dimensionality reduction clustering of complex carbohydrates to study lung cancer metabolic heterogeneity

Author

Conroy, Lindsey R., primary, Chang, Josephine E., additional, Sun, Qi, additional, Clarke, Harrison A., additional, Buoncristiani, Michael D., additional, Young, Lyndsay E.A., additional, McDonald, Robert J., additional, Liu, Jinze, additional, Gentry, Matthew S., additional, Allison, Derek B., additional, and Sun, Ramon C., additional

Published
2022
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32. Plant-Derived as Alternatives to Animal-Derived Bioactive Peptides: A Review of the Preparation, Bioactivities, Structure–Activity Relationships, and Applications in Chronic Diseases.

Author

Sun, Li, Liu, Jinze, He, Zhongmei, and Du, Rui

Abstract

Background/Objectives: At present, a large number of bioactive peptides have been found from plant sources with potential applications for the prevention of chronic diseases. By promoting plant-derived bioactive peptides (PDBPs), we can reduce dependence on animals, reduce greenhouse gas emissions, and protect the ecological environment. Methods: In this review, we summarize recent advances in sustainably sourced PDBPs in terms of preparation methods, biological activity, structure–activity relationships, and their use in chronic diseases. Results: Firstly, the current preparation methods of PDBPs were summarized, and the advantages and disadvantages of enzymatic method and microbial fermentation method were introduced. Secondly, the biological activities of PDBPs that have been explored are summarized, including antioxidant, antibacterial, anticancer and antihypertensive activities. Finally, based on the biological activity, the structure–activity relationship of PDBPs and its application in chronic diseases were discussed. All these provide the foundation for the development of PDBPs. However, the study of PDBPs still has some limitations. Conclusions: Overall, PDBPs is a good candidate for the prevention and treatment of chronic diseases in humans. This work provides important information for exploring the source of PDBPs, optimizing its biological activity, and accurately designing functional foods or drugs. [ABSTRACT FROM AUTHOR]

Published
2024
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33. MicroRNA Profiles in Hematopoietic Stem Cell Transplant Recipients.

Author

Mohanraj, Lathika, Carter, Christiane, Liu, Jinze, and Swift-Scanlan, Theresa

Subjects
MULTIPLE myeloma treatment, COGNITION disorder risk factors, MULTIPLE myeloma, HEMATOPOIETIC stem cell transplantation, RISK assessment, HEMATOLOGIC malignancies, PATIENTS, TRANSPLANTATION of organs, tissues, etc., AUTOGRAFTS, RESEARCH funding, MICRORNA, PILOT projects, BLOOD collection, FRAIL elderly, FATIGUE (Physiology), QUESTIONNAIRES, CANCER patients, DESCRIPTIVE statistics, TUMOR markers, HEMATOPOIESIS, PRE-tests & post-tests, GENE expression, QUALITY of life, HEMATOPOIETIC stem cells, COMPARATIVE studies, COGNITION
Abstract

Background: Hematopoietic Stem Cell Transplant (HCT) is a potentially curative treatment for hematologic malignancies, including multiple myeloma. Biomarker investigation can guide identification of HCT recipients at-risk for poor outcomes. MicroRNAs (miRNAs) are a class of non-coding RNAs involved in the modulation and regulation of pathological processes and are emerging as prognostic and predictive biomarkers for multiple health conditions. This pilot study aimed to examine miRNA profiles associated with HCT-related risk factors and outcomes in patients undergoing autologous HCT. Methods: Patients eligible for autologous HCT were recruited and blood samples and HCT-related variables were collected. Differential expression analysis of miRNA was conducted on 24 patient samples to compare changes in miRNA profile in HCT eligible patients before and after transplant. Results: Unsupervised clustering of differentially expressed (p <.05) miRNAs pre- and post- HCT identified clusters of up- and down-regulated miRNAs. Four miRNAs (miR-125a-5p, miR-99b-5p, miR-382–5p, miR-145–5p) involved in hematopoiesis (differentiation of progenitor cells, granulocyte function, thrombopoiesis, and tumor suppression) were significantly downregulated post-HCT. Correlation analyses identified select miRNAs associated with risk factors (such as frailty, fatigue, cognitive decline) and quality of life pre- and post-HCT. Select miRNAs were correlated with platelet engraftment. Conclusion: Future studies should examine miRNA signatures in larger cohorts in association with HCT outcomes; and expand investigations in patients receiving allogeneic transplants. This will lead to identification of biomarkers for risk stratification of HCT recipients. [ABSTRACT FROM AUTHOR]

Published
2024
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34. Loss of CLN3, the gene mutated in juvenile neuronal ceroid lipofuscinosis, leads to metabolic impairment and autophagy induction in retinal pigment epithelium

Author

Zhong, Yu, Mohan, Kabhilan, Liu, Jinpeng, Al-Attar, Ahmad, Lin, Penghui, Flight, Robert M., Sun, Qiushi, Warmoes, Marc O., Deshpande, Rahul R., Liu, Huijuan, Jung, Kyung Sik, Mitov, Mihail I., Lin, Nianwei, Butterfield, D. Allan, Lu, Shuyan, Liu, Jinze, Moseley, Hunter N.B., Fan, Teresa W.M., Kleinman, Mark E., and Wang, Qing Jun

Published
2020
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37. Additional Cover

Author

Dubey, Sushil K., primary, Dubey, Rashmi, additional, Prajapati, Subhash C., additional, Jung, Kyungsik, additional, Mohan, Kabhilan, additional, Liu, Xinan, additional, Roney, Jacob, additional, Tian, Wenjian, additional, Abney, Jennifer, additional, Giarmarco, Michelle M., additional, Hernandez, Alvaro G., additional, Liu, Jinze, additional, and Kleinman, Mark E., additional

Published
2024
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39. Comprehensive genomic characterization of head and neck squamous cell carcinomas

Author

Lawrence, Michael S, Sougnez, Carrie, Lichtenstein, Lee, Cibulskis, Kristian, Lander, Eric, Gabriel, Stacey B, Getz, Gad, Ally, Adrian, Balasundaram, Miruna, Birol, Inanc, Bowlby, Reanne, Brooks, Denise, Butterfield, Yaron SN, Carlsen, Rebecca, Cheng, Dean, Chu, Andy, Dhalla, Noreen, Guin, Ranabir, Holt, Robert A, Jones, Steven JM, Lee, Darlene, Li, Haiyan I, Marra, Marco A, Mayo, Michael, Moore, Richard A, Mungall, Andrew J, Gordon Robertson, A, Schein, Jacqueline E, Sipahimalani, Payal, Tam, Angela, Thiessen, Nina, Wong, Tina, Protopopov, Alexei, Santoso, Netty, Lee, Semin, Parfenov, Michael, Zhang, Jianhua, Mahadeshwar, Harshad S, Tang, Jiabin, Ren, Xiaojia, Seth, Sahil, Haseley, Psalm, Zeng, Dong, Yang, Lixing, Xu, Andrew W, Song, Xingzhi, Pantazi, Angeliki, Bristow, Christopher A, Hadjipanayis, Angela, Seidman, Jonathan, Chin, Lynda, Park, Peter J, Kucherlapati, Raju, Akbani, Rehan, Casasent, Tod, Liu, Wenbin, Lu, Yiling, Mills, Gordon, Motter, Thomas, Weinstein, John, Diao, Lixia, Wang, Jing, Hong Fan, You, Liu, Jinze, Wang, Kai, Todd Auman, J, Balu, Saianand, Bodenheimer, Thomas, Buda, Elizabeth, Neil Hayes, D, Hoadley, Katherine A, Hoyle, Alan P, Jefferys, Stuart R, Jones, Corbin D, Kimes, Patrick K, Liu, Yufeng, Marron, JS, Meng, Shaowu, Mieczkowski, Piotr A, Mose, Lisle E, Parker, Joel S, Perou, Charles M, Prins, Jan F, Roach, Jeffrey, Shi, Yan, Simons, Janae V, Singh, Darshan, Soloway, Matthew G, Tan, Donghui, Veluvolu, Umadevi, Walter, Vonn, Waring, Scot, Wilkerson, Matthew D, Wu, Junyuan, Zhao, Ni, Cherniack, Andrew D, Hammerman, Peter S, Tward, Aaron D, Sekhar Pedamallu, Chandra, and Saksena, Gordon

Subjects
Rare Diseases, Cancer Genomics, Biotechnology, Clinical Research, Digestive Diseases, Dental/Oral and Craniofacial Disease, Genetics, Cancer, Human Genome, Good Health and Well Being, Carcinoma, Squamous Cell, DNA Copy Number Variations, DNA, Neoplasm, Female, Gene Expression Regulation, Neoplastic, Genome, Human, Genomics, Head and Neck Neoplasms, Humans, Male, Molecular Targeted Therapy, Mutation, Oncogenes, RNA, Neoplasm, Signal Transduction, Squamous Cell Carcinoma of Head and Neck, Transcription Factors, Cancer Genome Atlas Network, General Science & Technology
Abstract

The Cancer Genome Atlas profiled 279 head and neck squamous cell carcinomas (HNSCCs) to provide a comprehensive landscape of somatic genomic alterations. Here we show that human-papillomavirus-associated tumours are dominated by helical domain mutations of the oncogene PIK3CA, novel alterations involving loss of TRAF3, and amplification of the cell cycle gene E2F1. Smoking-related HNSCCs demonstrate near universal loss-of-function TP53 mutations and CDKN2A inactivation with frequent copy number alterations including amplification of 3q26/28 and 11q13/22. A subgroup of oral cavity tumours with favourable clinical outcomes displayed infrequent copy number alterations in conjunction with activating mutations of HRAS or PIK3CA, coupled with inactivating mutations of CASP8, NOTCH1 and TP53. Other distinct subgroups contained loss-of-function alterations of the chromatin modifier NSD1, WNT pathway genes AJUBA and FAT1, and activation of oxidative stress factor NFE2L2, mainly in laryngeal tumours. Therapeutic candidate alterations were identified in most HNSCCs.

Published
2015

40. Bayes estimators for phylogenetic reconstruction

Author

Huggins, Peter, Li, Wenbin, Haws, David, Friedrich, Thomas, Liu, Jinze, and Yoshida, Ruriko

Subjects
Quantitative Biology - Populations and Evolution, Computer Science - Learning, Quantitative Biology - Quantitative Methods
Abstract

Tree reconstruction methods are often judged by their accuracy, measured by how close they get to the true tree. Yet most reconstruction methods like ML do not explicitly maximize this accuracy. To address this problem, we propose a Bayesian solution. Given tree samples, we propose finding the tree estimate which is closest on average to the samples. This ``median'' tree is known as the Bayes estimator (BE). The BE literally maximizes posterior expected accuracy, measured in terms of closeness (distance) to the true tree. We discuss a unified framework of BE trees, focusing especially on tree distances which are expressible as squared euclidean distances. Notable examples include Robinson--Foulds distance, quartet distance, and squared path difference. Using simulated data, we show Bayes estimators can be efficiently computed in practice by hill climbing. We also show that Bayes estimators achieve higher accuracy, compared to maximum likelihood and neighbor joining., Comment: 31 pages, 4 figures, and 3 tables

Published
2009

44. Supplementary Table 5 from EZH2 Inhibition Promotes Tumor Immunogenicity in Lung Squamous Cell Carcinomas

Author

DuCote, Tanner J., primary, Song, Xiulong, primary, Naughton, Kassandra J., primary, Chen, Fan, primary, Plaugher, Daniel R., primary, Childress, Avery R., primary, Gellert, Abigail R., primary, Skaggs, Erika M., primary, Qu, Xufeng, primary, Liu, Jinze, primary, Liu, Jinpeng, primary, Li, Fei, primary, Wong, Kwok-Kin, primary, and Brainson, Christine F., primary

Published
2024
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45. FIGURE 2 from EZH2 Inhibition Promotes Tumor Immunogenicity in Lung Squamous Cell Carcinomas

Author

DuCote, Tanner J., primary, Song, Xiulong, primary, Naughton, Kassandra J., primary, Chen, Fan, primary, Plaugher, Daniel R., primary, Childress, Avery R., primary, Gellert, Abigail R., primary, Skaggs, Erika M., primary, Qu, Xufeng, primary, Liu, Jinze, primary, Liu, Jinpeng, primary, Li, Fei, primary, Wong, Kwok-Kin, primary, and Brainson, Christine F., primary

Published
2024
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46. Supplementary Figure 4 from EZH2 Inhibition Promotes Tumor Immunogenicity in Lung Squamous Cell Carcinomas

Author

DuCote, Tanner J., primary, Song, Xiulong, primary, Naughton, Kassandra J., primary, Chen, Fan, primary, Plaugher, Daniel R., primary, Childress, Avery R., primary, Gellert, Abigail R., primary, Skaggs, Erika M., primary, Qu, Xufeng, primary, Liu, Jinze, primary, Liu, Jinpeng, primary, Li, Fei, primary, Wong, Kwok-Kin, primary, and Brainson, Christine F., primary

Published
2024
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47. FIGURE 4 from EZH2 Inhibition Promotes Tumor Immunogenicity in Lung Squamous Cell Carcinomas

Author

DuCote, Tanner J., primary, Song, Xiulong, primary, Naughton, Kassandra J., primary, Chen, Fan, primary, Plaugher, Daniel R., primary, Childress, Avery R., primary, Gellert, Abigail R., primary, Skaggs, Erika M., primary, Qu, Xufeng, primary, Liu, Jinze, primary, Liu, Jinpeng, primary, Li, Fei, primary, Wong, Kwok-Kin, primary, and Brainson, Christine F., primary

Published
2024
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48. FIGURE 6 from EZH2 Inhibition Promotes Tumor Immunogenicity in Lung Squamous Cell Carcinomas

Author

DuCote, Tanner J., primary, Song, Xiulong, primary, Naughton, Kassandra J., primary, Chen, Fan, primary, Plaugher, Daniel R., primary, Childress, Avery R., primary, Gellert, Abigail R., primary, Skaggs, Erika M., primary, Qu, Xufeng, primary, Liu, Jinze, primary, Liu, Jinpeng, primary, Li, Fei, primary, Wong, Kwok-Kin, primary, and Brainson, Christine F., primary

Published
2024
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49. Supplementary Figure 6 from EZH2 Inhibition Promotes Tumor Immunogenicity in Lung Squamous Cell Carcinomas

Author

DuCote, Tanner J., primary, Song, Xiulong, primary, Naughton, Kassandra J., primary, Chen, Fan, primary, Plaugher, Daniel R., primary, Childress, Avery R., primary, Gellert, Abigail R., primary, Skaggs, Erika M., primary, Qu, Xufeng, primary, Liu, Jinze, primary, Liu, Jinpeng, primary, Li, Fei, primary, Wong, Kwok-Kin, primary, and Brainson, Christine F., primary

Published
2024
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50. Supplementary Table 1 from EZH2 Inhibition Promotes Tumor Immunogenicity in Lung Squamous Cell Carcinomas

Author

DuCote, Tanner J., primary, Song, Xiulong, primary, Naughton, Kassandra J., primary, Chen, Fan, primary, Plaugher, Daniel R., primary, Childress, Avery R., primary, Gellert, Abigail R., primary, Skaggs, Erika M., primary, Qu, Xufeng, primary, Liu, Jinze, primary, Liu, Jinpeng, primary, Li, Fei, primary, Wong, Kwok-Kin, primary, and Brainson, Christine F., primary

Published
2024
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