bluuebunny/crossref_metadata_2025 huggingface dataset:
Host cells reprogram lipid droplet synthesis through YY1 to resist PRRSV infection
Authors: Zheng Zifang , Ling Xue , Li Yang , Qiao Shuang , Zhang Shuangquan , Wu Jie , Ma Zhiqian , Li Mingyu , Guo Xuyang , Li Zhiwei , Feng Yingtong , Liu Xiao , Goodfellow Ian G. , Zheng Haixue , Xiao Shuqi
Published: July 2024

Metabolism in host cells can be modulated after viral infection, favoring viral survival or clearance. Here, we report that lipid droplet (LD) synthesis in host cells can be modulated by yin yang 1 (YY1) after porcine reproductive and respiratory syndrome virus (PRRSV) infection, resulting in active antiviral activity. As a ubiquitously distributed transcription factor, there was increased expression of YY1 upon PRRSV infection both
in vitro
and
in vivo
. YY1 silencing promoted the replication of PRRSV, whereas YY1 overexpression inhibited PRRSV replication. PRRSV infection led to a marked increase in LDs, while YY1 knockout inhibited LD synthesis, and YY1 overexpression enhanced LD accumulation, indicating that YY1 reprograms PRRSV infection-induced intracellular LD synthesis. We also showed that the viral components do not colocalize with LDs during PRRSV infection, and the effect of exogenously induced LD synthesis on PRRSV replication is nearly lethal. Moreover, we demonstrated that YY1 affects the synthesis of LDs by regulating the expression of lipid metabolism genes. YY1 negatively regulates the expression of fatty acid synthase (FASN) to weaken the fatty acid synthesis pathway and positively regulates the expression of peroxisome proliferator-activated receptor gamma (PPARγ) to promote the synthesis of LDs, thus inhibiting PRRSV replication. These novel findings indicate that YY1 plays a crucial role in regulating PRRSV replication by reprogramming LD synthesis. Therefore, our study provides a novel mechanism of host resistance to PRRSV and suggests potential new antiviral strategies against PRRSV infection.

IMPORTANCE

Porcine reproductive and respiratory virus (PRRSV) has caused incalculable economic damage to the global pig industry since it was first discovered in the 1980s. However, conventional vaccines do not provide satisfactory protection. It is well known that viruses are parasitic pathogens, and the completion of their replication life cycle is highly dependent on host cells. A better understanding of host resistance to PRRSV infection is essential for developing safe and effective strategies to control PRRSV. Here, we report a crucial host antiviral molecule, yin yang 1 (YY1), which is induced to be expressed upon PRRSV infection and subsequently inhibits virus replication by reprogramming lipid droplet (LD) synthesis through transcriptional regulation. Our work provides a novel antiviral mechanism against PRRSV infection and suggests that targeting YY1 could be a new strategy for controlling PRRSV.
Supplemental Material: Is the Mesoarchean Mulgandinnah shear zone, Pilbara Craton, the world’s oldest arc-slicing transform fault?
Authors: Aldoud Abdelmottaleb , al. et
Published: July 2024

 Supporting geophysical data.
Optimizing molecular assays for glyphosate and ALS-inhibitor resistance diagnostics in four weed species
Authors: Sulzback Juliano R.M. , Borgato Ednaldo A. , Cutti Luan , Hill Erin C. , Burns Erin E. , Patterson Eric L.
Published: July 2024

Herbicide-resistant weeds pose a threat to food production in modern agriculture, causing US$32 billion in crop production losses worldwide. In Michigan, highly troublesome and widespread weeds include waterhemp, Palmer amaranth, common ragweed, and horseweed, with accessions that are resistant to glyphosate (Group 9) and ALS-inhibitors (Group 2), major herbicide sites of action utilized in soybean and corn cropping systems. Molecular assays for rapid resistance diagnostics to confirm the in-field status of herbicide resistance can assist with more effective, timely, and proactive management. In this research, we developed and tested PCR-based assays to identify target site resistance mechanisms to both herbicide groups through Sanger sequencing and EPSPS copy number variation. Nine different SNPs were identified in five ALS positions known to confer herbicide resistance among all species surveyed. Pro197Ser was the most frequent in horseweed and common ragweed accessions, whereas Trp574Leu was the predominant mutation in Palmer amaranth and waterhemp. Four horseweed accessions contained the Pro106Ser mutation in the EPSPS gene, which confers resistance to glyphosate. Additionally, waterhemp and Palmer amaranth had 2–7 and 20–160 copies of EPSPS, respectively. The assays were validated by comparing genotyping of several field-collected accessions of unknown resistance status with known resistant and susceptible accessions. The efficacy of genotyping assays was >98% and required only two days, confirming that molecular assays are a robust tool for rapid resistance diagnostics. These assays can help growers evaluate herbicide resistance status in weed populations within the same growing season, allowing them to adopt effective management practices.
A policy scan related to assisted migration as a climate change adaptation tactic in Canada reveals major policy gaps
Authors: Cooke S.J. , Vermey J. , Taylor J.J. , Rytwinski T. , Twardek W.M. , Auld G. , Van Bogaert R. , MacDonald A.L.
Published: July 2024

Assisted migration is increasingly being considered as a potential climate change adaptation tactic even though it also comes with potential risk to ecosystems and society. When implementing conservation actions that involve risk, it is prudent to have policies and guidelines to ensure that such actions are conducted in ways that conform to regional standards and consider risks. Here, we report on a policy scan focused on assisted migration in the context of climate change adaptation originally as a protected areas tactic only, but then broadened to ecosystems in Canada beyond those boundaries. Policy scans are a useful strategy for understanding the evolving policy and regulatory landscape for a given topic and can guide the development of such policies in other jurisdictions. Our scan focused on Canada, where multi-scalar governance systems exist relevant to biodiversity and environmental management. Our comprehensive policy scan (involving scans of legislation, policies, and guidelines found online and through direct inquiries with government bodies) revealed major gaps in the assisted migration policy landscape with very few provincial/territorial or federal policies in Canada. A more rudimentary scan in the United States revealed a similar pattern. There was evidence that some jurisdictions anticipated need for such policies and even a few examples of very specific policies (e.g., seeds) that had already been developed, but there were not comprehensive policies or frameworks. Governments and other relevant bodies/organizations may wish to consider working collaboratively toward the development of robust, evidence-based policies for assisted migration given that we anticipate this conservation intervention becoming more popular as climate change impacts on ecosystems become more evident and dire.
Identification of ECA rules forming MACA in periodic boundary condition
Authors: Banerjee Som , Dalui Mamata
Published: July 2024

Cellular automaton (CA) is a computing model which is emerging rapidly. It is largely used in different types of scientific applications and simulations due to its ability to solve complex problems using simple rule(s). Cellular automata (CAs) are used in different types of applications like cryptography, VLSI systems, fault detection, etc. Typically, most of these applications utilize one-dimensional, 2-state, 3-neighborhood CAs. This paper explores the concept of Next State RMT Transition Diagram (NSRTD) for characterization of all the Elementary Cellular Automata (ECA) rules in periodic boundary condition leading to the identification of all ECA rules forming more than two fixed points (referred to as Single Length Cycle Multi-Attractor CA (MACA)) for an arbitrary CA length (n). For this, the 88 Wolfram classification rules and their equivalent rules have been utilized to reduce the search complexity by avoiding exhaustive searching on all the 256 ECA rules.
Dissipative Dynamics in Open Fermionic Chains
Authors: Karanikas A. I. , Pavlou G. E.
Published: July 2024

By merging the Feynman-Vernon’s approach with the out-of-equilibrium Keldysh-Schwinger formalism, we construct the reduced generating functional through which all the time-dependent correlation functions of an open fermionic system can be directly derived by applying the appropriate functional derivatives. As a concrete example, we investigate the transverse Ising model, we derive the covariance matrix at the steady state of the system and we investigate its critical behaviour.
Social Media, Sentiments and Political Discourse – An Exploratory Study of the 2021 Canadian Federal Election
Authors: Noor Hiba Mohammad , Turetken Ozgur , Akgul Mehmet
Published: July 2024

Social media are widely used for online political discourse. Opinions shared on social media have different sentiments associated with them. Given the very high adoption rates of X (formerly known as Twitter) among adults, those who share their opinions on X not only represent a sizable segment of the society, but also influence (through emotion contagion) an even larger segment who are passive (non-contributing) users of the platform. Furthermore, the discourse that is initiated on X typically spreads to other more traditional media. As a result, X is influential, which makes it useful to understand the factors related to the sentiments expressed in tweets. Such understanding can help policymakers to take actions that align with public needs and priorities. This research focuses on identifying the drivers (keywords) of sentiments associated with political discourse on X. We also explore virality, i.e., how much a message (the tweet) spreads, and the relationship between sentiments and virality. Finally, we explore whether the clustering of tweets among sentiment and virality groups can improve the potential of social media content for predicting election results. Sentiment Analysis of 764,000 tweets related to the 2021 Canadian Federal election was followed by text clustering to identify sentiment-driving topics. We found some keywords predominantly present within a positive or negative sentiment that are suggestive of entities or ideas to invest in or mitigate by political decision makers. We were also able to find partial evidence for “negativity bias” by detecting a negative relationship between sentiment (positivity) and virality (number of retweets). Finally, we demonstrated that high positivity on the political discourse does not reflect election outcomes and examining X content in more neutral groups can improve predictive power. Our findings have implications for political decision makers and social media analytics researchers.
Hardware Acceleration for High-Volume Operations of CRYSTALS-Kyber and CRYSTALS-Dilithium
Authors: Carril Xavier , Kardaris Charalampos , Ribes-GonzáLez Jordi , Farràs Oriol , Hernandez Carles , Kostalabros Vatistas , González-Jiménez Joel Ulises , Moretó Miquel
Published: July 2024

Many high-demand digital services need to perform several cryptographic operations, such as key exchange or security credentialing, in a concise amount of time. In turn, the security of some of these cryptographic schemes is threatened by advances in quantum computing, as quantum computer could break their security in the near future. Post-quantum cryptography (PQC) is an emerging field that studies cryptographic algorithms that resist such attacks. The National Institute of Standards and Technology (NIST) has selected the CRYSTALS-Kyber Key Encapsulation Mechanism and the CRYSTALS-Dilithium Digital Signature algorithm as primary PQC standards. In this article, we present field-programmable gate array (FPGA)-based hardware accelerators for high-volume operations of both schemes. We apply high-level synthesis (HLS) for hardware optimization, leveraging a batch processing approach to maximize the memory throughput and applying custom HLS logic to specific algorithmic components. Using reconfigurable FPGAs, we show that our hardware accelerators achieve speedups between 3

\(\times\)

and 9

\(\times\)

over software baseline implementations, even over ones leveraging CPU vector architectures. Furthermore, the methods used in this study can also be extended to the new CRYSTALS-based NIST FIPS drafts, ML-KEM and ML-DSA, with similar acceleration results.
ChatGPT on ChatGPT: An Exploratory Analysis of its Performance in the Public Sector Workplace
Authors: Wang Jieshu , Kiran Elif , Aurora S.R. , Simeone Michael , Lobo Jose
Published: July 2024

This study explores the impact of Generative Artificial Intelligence (GenAI), in particular, ChatGPT, on the public sector workforce in the United States, focusing on task replacement, assistance potential, and the evolving landscape of skills. Utilizing GPT-4 to evaluate 1,022 core tasks across 51 public sector occupations, we provide an exploratory analysis of the roles susceptible to ChatGPT automation and those in which ChatGPT can augment human efforts. Our findings reveal that while 63% of tasks are resistant to ChatGPT replacement, primarily due to their requirement for physical presence, emotional intelligence, and complex decision-making, tasks that are routine, rule-based, and involving basic content generation show a high potential for automation. The study also identifies key skills that will remain vital, those likely to become obsolete, and new skills that will emerge as essential, highlighting the need for a strategic approach to workforce development in the face of AI advancements. In particular, our findings underscore the growing importance of skills in applying AI technologies and the ability to validate and interpret AI-generated content for humans to remain competitive. We offer insights into public-sector-specific impacts and propose a methodological framework for future research, emphasizing the importance of adapting educational curricula and policies to prepare for an AI-integrated future.
How Diet and Lifestyle Can Fine-Tune Gut Microbiomes for Healthy Aging
Authors: Tamayo M. , Olivares M. , Ruas-Madiedo P. , Margolles A. , Espín J.C. , Medina I. , Moreno-Arribas M.V. , Canals S. , Mirasso C.R. , Ortín S. , Beltrán-Sanchez H. , Palloni A. , Tomás-Barberán F.A. , Sanz Y.
Published: July 2024

Many physical, social, and psychological changes occur during aging that raise the risk of developing chronic diseases, frailty, and dependency. These changes adversely affect the gut microbiota, a phenomenon known as microbe-aging. Those microbiota alterations are, in turn, associated with the development of age-related diseases. The gut microbiota is highly responsive to lifestyle and dietary changes, displaying a flexibility that also provides anactionable tool by which healthy aging can be promoted. This review covers, firstly, the main lifestyle and socioeconomic factors that modify the gut microbiota composition and function during healthy or unhealthy aging and, secondly, the advances being made in defining and promoting healthy aging, including microbiome-informed artificial intelligence tools, personalized dietary patterns, and food probiotic systems.
The Multifaceted Role of Tissue-Resident Memory T Cells
Authors: Christo Susan N. , Park Simone L. , Mueller Scott N. , Mackay Laura K.
Published: July 2024

Regionalized immune surveillance relies on the concerted efforts of diverse memory T cell populations. Of these, tissue-resident memory T (TRM) cells are strategically positioned in barrier tissues, where they enable efficient frontline defense against infections and cancer. However, the long-term persistence of these cells has been implicated in a variety of immune-mediated pathologies. Consequently, modulating TRM cell populations represents an attractive strategy for novel vaccination and therapeutic interventions against tissue-based diseases. Here, we provide an updated overview of TRM cell heterogeneity and function across tissues and disease states. We discuss mechanisms of TRM cell–mediated immune protection and their potential contributions to autoimmune disorders. Finally, we examine how TRM cell responses might be durably boosted or dampened for therapeutic gain.
Dynamical Reweighting for Biased Rare Event Simulations
Authors: Keller Bettina G. , Bolhuis Peter G.
Published: July 2024

Dynamical reweighting techniques aim to recover the correct molecular dynamics from a simulation at a modified potential energy surface. They are important for unbiasing enhanced sampling simulations of molecular rare events. Here, we review the theoretical frameworks of dynamical reweighting for modified potentials. Based on an overview of kinetic models with increasing level of detail, we discuss techniques to reweight two-state dynamics, multistate dynamics, and path integrals. We explore the natural link to transition path sampling and how the effect of nonequilibrium forces can be reweighted. We end by providing an outlook on how dynamical reweighting integrates with techniques for optimizing collective variables and with modern potential energy surfaces.
Modeling for Prediction of Mortality Based on past Medical History in Hospitalized COVID‐19 Patients: A Secondary Analysis
Authors: Ahmadi Seyyed Amir Yasin , Karimi Yeganeh , Abdollahi Arash , Kabir Ali
Published: July 2024

Introduction. Although COVID‐19 is not currently a public health emergency, it will affect susceptible individuals in the post‐COVID‐19 era. Hence, the present study aimed to develop a model for Iranian patients to identify at‐risk groups based on past medical history (PMHx) and some other factors affecting the death of patients hospitalized with COVID‐19. Methods. A secondary study was conducted with the existing data of hospitalized COVID‐19 adult patients in the hospitals covered by Iran University of Medical Sciences. PMHx was extracted from the registered ICD‐10 codes. Stepwise logistic regression was used to predict mortality by PMHx and background covariates such as intensive care unit (ICU) admission. Crude population attributable fraction (PAF) as well as crude and adjusted odds ratio (OR) with 95% confidence interval (CI) were reported. Results. A total of 8879 patients were selected with 19.68% mortality. Infectious and parasitic diseases’ history showed the greatest association (OR = 5.72, 95% CI: 4.20, 7.82), while the greatest PAF was for cardiovascular system diseases (20.46%). According to logistic regression modeling, the largest effect, other than ICU admission and age, was for history of infectious and parasitic diseases (OR = 3.089, 95% CI: 2.13, 4.47). A good performance was achieved (area under curve = 0.875). Conclusion. Considering the prevalence of underlying diseases, many mortality cases of COVID‐19 are attributable to the history of cardiovascular disease. Future studies are needed for policy making regarding reduction of COVID‐19 mortality in susceptible groups in the post‐COVID‐19 era.
Solution of Fractional Kinetic Equations Involving Laguerre Polynomials via Sumudu Transform
Authors: Ahmed Wagdi F. S. , Pawar D. D. , Patil W. D.
Published: July 2024

This study focuses on calculating solutions for fractional kinetic equations involving Laguerre polynomials and their fractional derivatives. By leveraging the Sumudu transform technique, we derive these solutions in the form of the Mittag‐Leffler function. Our investigation includes graphical representations generated using MATLAB to illustrate the behavior of these solutions under varying parametric conditions. It is essential to note that the results obtained in this study are exceptionally versatile and have the potential to yield both established and potentially novel findings in this field of research.
Integrating Implementation Theory to Address Inequities in Cancer Care: Perspectives from an International Working Group
Authors: Whitaker K. L. , Cox A. , McErlean G. , Pal A. , Stansbury K. , Estupiñán Fdez de Mesa M. , Kerrison R. S. , Gil N. , Marcu A. , Armes J. , Yap M. L. , Delaney G. P. , Hoyo C.
Published: July 2024

Background . There are well‐established, persistent inequities in cancer care and cancer outcomes within and between countries. The aim of this article is to explore how implementation theory, specifically the Consolidated Framework for Implementation Research (CFIR), alongside coproduction principles, could be used to maximise the effectiveness of innovations with a vision of reducing inequity in cancer care. Methods. Workshops were conducted with partners from US, Australia, and UK, participating in the University Global Partnership Network (UGPN), which funded the collaboration. From these workshops, three case studies were identified and the framework was applied to identify ways of using CFIR to maximise the effectiveness of innovations. Results. The three case studies focused on human papillomavirus (HPV) testing and vaccination, participation in clinical trials, and use of translation services. We identified opportunities, for each of the case studies, where CFIR could be applied to improve implementation and proposed recommendations to ensure effective implementation of innovations using CFIR domains, including individual constructs (e.g., awareness and cultural competence), inner setting constructs (e.g., technology infrastructure), and outer setting constructs (e.g., how services are monitored, evaluated, and commissioned). Conclusions. Applying CFIR as an implementation framework offers a structured and holistic approach to consider how to maximise the effectiveness of innovations in the context of reducing inequities in cancer care. Working with other countries to apply this framework also provides a uniform approach to understand and reduce inequities across a range of innovations and address the global mission to improve cancer care for all.
TableS1 from CD106 in Tumor-Specific Exhausted CD8+ T Cells Mediates Immunosuppression by Inhibiting TCR Signaling
Authors: Naoi Yuto , Morinaga Takao , Nagasaki Joji , Ariyasu Ryo , Ueda Youki , Yamashita Kazuo , Zhou Wenhao , Kawashima Shusuke , Kawase Katsushige , Honobe-Tabuchi Akiko , Ohnuma Takehiro , Kawamura Tatsuyoshi , Umeda Yoshiyasu , Kawahara Yu , Nakamura Yasuhiro , Kiniwa Yukiko , Yamasaki Osamu , Fukushima Satoshi , Kawazu Masahito , Suzuki Yutaka , Nishikawa Hiroyoshi , Hanazawa Toyoyuki , Ando Mizuo , Inozume Takashi , Togashi Yosuke
Published: July 2024

Patient characteristics for scRNA/TCR-seq or flow cytometry
Figure S6 from A Pan-Cancer Patient-Derived Xenograft Histology Image Repository with Genomic and Pathologic Annotations Enables Deep Learning Analysis
Authors: White Brian S. , Woo Xing Yi , Koc Soner , Sheridan Todd , Neuhauser Steven B. , Wang Shidan , Evrard Yvonne A. , Chen Li , Foroughi pour Ali , Landua John D. , Mashl R. Jay , Davies Sherri R. , Fang Bingliang , Rosa Maria Gabriela , Evans Kurt W. , Bailey Matthew H. , Chen Yeqing , Xiao Min , Rubinstein Jill C. , Sanderson Brian J. , Lloyd Michael W. , Domanskyi Sergii , Dobrolecki Lacey E. , Fujita Maihi , Fujimoto Junya , Xiao Guanghua , Fields Ryan C. , Mudd Jacqueline L. , Xu Xiaowei , Hollingshead Melinda G. , Jiwani Shahanawaz , Acevedo Saul , Davis-Dusenbery Brandi N. , Robinson Peter N. , Moscow Jeffrey A. , Doroshow James H. , Mitsiades Nicholas , Kaochar Salma , Pan Chong-xian , Carvajal-Carmona Luis G. , Welm Alana L. , Welm Bryan E. , Govindan Ramaswamy , Li Shunqiang , Davies Michael A. , Roth Jack A. , Meric-Bernstam Funda , Xie Yang , Herlyn Meenhard , Ding Li , Lewis Michael T. , Bult Carol J. , Dean Dennis A. , Chuang Jeffrey H.
Published: July 2024

Figure S6
Figure S4 from A Pan-Cancer Patient-Derived Xenograft Histology Image Repository with Genomic and Pathologic Annotations Enables Deep Learning Analysis
Authors: White Brian S. , Woo Xing Yi , Koc Soner , Sheridan Todd , Neuhauser Steven B. , Wang Shidan , Evrard Yvonne A. , Chen Li , Foroughi pour Ali , Landua John D. , Mashl R. Jay , Davies Sherri R. , Fang Bingliang , Rosa Maria Gabriela , Evans Kurt W. , Bailey Matthew H. , Chen Yeqing , Xiao Min , Rubinstein Jill C. , Sanderson Brian J. , Lloyd Michael W. , Domanskyi Sergii , Dobrolecki Lacey E. , Fujita Maihi , Fujimoto Junya , Xiao Guanghua , Fields Ryan C. , Mudd Jacqueline L. , Xu Xiaowei , Hollingshead Melinda G. , Jiwani Shahanawaz , Acevedo Saul , Davis-Dusenbery Brandi N. , Robinson Peter N. , Moscow Jeffrey A. , Doroshow James H. , Mitsiades Nicholas , Kaochar Salma , Pan Chong-xian , Carvajal-Carmona Luis G. , Welm Alana L. , Welm Bryan E. , Govindan Ramaswamy , Li Shunqiang , Davies Michael A. , Roth Jack A. , Meric-Bernstam Funda , Xie Yang , Herlyn Meenhard , Ding Li , Lewis Michael T. , Bult Carol J. , Dean Dennis A. , Chuang Jeffrey H.
Published: July 2024

Figure S4
Supplementary Data from CD58 Alterations Govern Antitumor Immune Responses by Inducing PDL1 and IDO in Diffuse Large B-Cell Lymphoma
Authors: Xu Xiyue , Zhang Yidan , Lu Yaxiao , Zhang Xiaoyan , Zhao Cuicui , Wang Jiesong , Guan Qingpei , Feng Yingfang , Gao Meng , Yu Jingwei , Song Zheng , Liu Xia , Golchehre Zahra , Li Lanfang , Ren Weicheng , Pan-Hammarström Qiang , Zhang Huilai , Wang Xianhuo
Published: July 2024

Supplementary Figures and Tables
Figure S15 from A Pan-Cancer Patient-Derived Xenograft Histology Image Repository with Genomic and Pathologic Annotations Enables Deep Learning Analysis
Authors: White Brian S. , Woo Xing Yi , Koc Soner , Sheridan Todd , Neuhauser Steven B. , Wang Shidan , Evrard Yvonne A. , Chen Li , Foroughi pour Ali , Landua John D. , Mashl R. Jay , Davies Sherri R. , Fang Bingliang , Rosa Maria Gabriela , Evans Kurt W. , Bailey Matthew H. , Chen Yeqing , Xiao Min , Rubinstein Jill C. , Sanderson Brian J. , Lloyd Michael W. , Domanskyi Sergii , Dobrolecki Lacey E. , Fujita Maihi , Fujimoto Junya , Xiao Guanghua , Fields Ryan C. , Mudd Jacqueline L. , Xu Xiaowei , Hollingshead Melinda G. , Jiwani Shahanawaz , Acevedo Saul , Davis-Dusenbery Brandi N. , Robinson Peter N. , Moscow Jeffrey A. , Doroshow James H. , Mitsiades Nicholas , Kaochar Salma , Pan Chong-xian , Carvajal-Carmona Luis G. , Welm Alana L. , Welm Bryan E. , Govindan Ramaswamy , Li Shunqiang , Davies Michael A. , Roth Jack A. , Meric-Bernstam Funda , Xie Yang , Herlyn Meenhard , Ding Li , Lewis Michael T. , Bult Carol J. , Dean Dennis A. , Chuang Jeffrey H.
Published: July 2024

Figure S15
Table S6 from Single-Cell and Spatial Transcriptome Profiling Identifies the Transcription Factor BHLHE40 as a Driver of EMT in Metastatic Colorectal Cancer
Authors: Yang Sheng , Zhang Dongsheng , Sun Qingyang , Nie Hongxu , Zhang Yue , Wang Xiaowei , Huang Yuanjian , Sun Yueming
Published: July 2024

Supplementary Table S6: Top 100 scVelo’s rank_velocity_genes of Malignant EPCs_8 sorted by latent time.
Figure S12 from A Pan-Cancer Patient-Derived Xenograft Histology Image Repository with Genomic and Pathologic Annotations Enables Deep Learning Analysis
Authors: White Brian S. , Woo Xing Yi , Koc Soner , Sheridan Todd , Neuhauser Steven B. , Wang Shidan , Evrard Yvonne A. , Chen Li , Foroughi pour Ali , Landua John D. , Mashl R. Jay , Davies Sherri R. , Fang Bingliang , Rosa Maria Gabriela , Evans Kurt W. , Bailey Matthew H. , Chen Yeqing , Xiao Min , Rubinstein Jill C. , Sanderson Brian J. , Lloyd Michael W. , Domanskyi Sergii , Dobrolecki Lacey E. , Fujita Maihi , Fujimoto Junya , Xiao Guanghua , Fields Ryan C. , Mudd Jacqueline L. , Xu Xiaowei , Hollingshead Melinda G. , Jiwani Shahanawaz , Acevedo Saul , Davis-Dusenbery Brandi N. , Robinson Peter N. , Moscow Jeffrey A. , Doroshow James H. , Mitsiades Nicholas , Kaochar Salma , Pan Chong-xian , Carvajal-Carmona Luis G. , Welm Alana L. , Welm Bryan E. , Govindan Ramaswamy , Li Shunqiang , Davies Michael A. , Roth Jack A. , Meric-Bernstam Funda , Xie Yang , Herlyn Meenhard , Ding Li , Lewis Michael T. , Bult Carol J. , Dean Dennis A. , Chuang Jeffrey H.
Published: July 2024

Figure S12
Figure S10 from A Pan-Cancer Patient-Derived Xenograft Histology Image Repository with Genomic and Pathologic Annotations Enables Deep Learning Analysis
Authors: White Brian S. , Woo Xing Yi , Koc Soner , Sheridan Todd , Neuhauser Steven B. , Wang Shidan , Evrard Yvonne A. , Chen Li , Foroughi pour Ali , Landua John D. , Mashl R. Jay , Davies Sherri R. , Fang Bingliang , Rosa Maria Gabriela , Evans Kurt W. , Bailey Matthew H. , Chen Yeqing , Xiao Min , Rubinstein Jill C. , Sanderson Brian J. , Lloyd Michael W. , Domanskyi Sergii , Dobrolecki Lacey E. , Fujita Maihi , Fujimoto Junya , Xiao Guanghua , Fields Ryan C. , Mudd Jacqueline L. , Xu Xiaowei , Hollingshead Melinda G. , Jiwani Shahanawaz , Acevedo Saul , Davis-Dusenbery Brandi N. , Robinson Peter N. , Moscow Jeffrey A. , Doroshow James H. , Mitsiades Nicholas , Kaochar Salma , Pan Chong-xian , Carvajal-Carmona Luis G. , Welm Alana L. , Welm Bryan E. , Govindan Ramaswamy , Li Shunqiang , Davies Michael A. , Roth Jack A. , Meric-Bernstam Funda , Xie Yang , Herlyn Meenhard , Ding Li , Lewis Michael T. , Bult Carol J. , Dean Dennis A. , Chuang Jeffrey H.
Published: July 2024

Figure S10
Supplementary Figure 6 from GPR1 and CMKLR1 Control Lipid Metabolism to Support the Development of Clear Cell Renal Cell Carcinoma
Authors: Wang Dazhi , Mahmud Iqbal , Thakur Vijay S. , Tan Sze Kiat , Isom Daniel G. , Lombard David B. , Gonzalgo Mark L. , Kryvenko Oleksandr N. , Lorenzi Philip L. , Tcheuyap Vanina T. , Brugarolas James , Welford Scott M.
Published: July 2024

Supplementary Figure 6
Supplementary Figure 5 from GPR1 and CMKLR1 Control Lipid Metabolism to Support the Development of Clear Cell Renal Cell Carcinoma
Authors: Wang Dazhi , Mahmud Iqbal , Thakur Vijay S. , Tan Sze Kiat , Isom Daniel G. , Lombard David B. , Gonzalgo Mark L. , Kryvenko Oleksandr N. , Lorenzi Philip L. , Tcheuyap Vanina T. , Brugarolas James , Welford Scott M.
Published: July 2024

Supplementary Figure 5
Supplementary Figure 11 from GPR1 and CMKLR1 Control Lipid Metabolism to Support the Development of Clear Cell Renal Cell Carcinoma
Authors: Wang Dazhi , Mahmud Iqbal , Thakur Vijay S. , Tan Sze Kiat , Isom Daniel G. , Lombard David B. , Gonzalgo Mark L. , Kryvenko Oleksandr N. , Lorenzi Philip L. , Tcheuyap Vanina T. , Brugarolas James , Welford Scott M.
Published: July 2024

Supplementary Figure 11
Differentially regulated genes from GPR1 and CMKLR1 Control Lipid Metabolism to Support the Development of Clear Cell Renal Cell Carcinoma
Authors: Wang Dazhi , Mahmud Iqbal , Thakur Vijay S. , Tan Sze Kiat , Isom Daniel G. , Lombard David B. , Gonzalgo Mark L. , Kryvenko Oleksandr N. , Lorenzi Philip L. , Tcheuyap Vanina T. , Brugarolas James , Welford Scott M.
Published: July 2024

Differentially regulated genes
Supplementary Data from The circMYBL2-Encoded p185 Protein Suppresses Colorectal Cancer Progression by Inhibiting Serine Biosynthesis
Authors: Zhao Ning , Cao Yinghao , Tao Ruikang , Zhu Xiuxian , Li Runze , Chen Yajun , Tao Kaixiong , Li Lei , Chen Hengyu , Ma Xianxiong
Published: July 2024

Supplementary data tables, figures, and legends
Supplementary Fig S5 from A Tetravalent Bispecific Antibody Selectively Inhibits Diverse FGFR3 Oncogenic Variants
Authors: Yang Yan , Suhasini Avvaru N. , Jiang Zaoli , Liu Nina , Rosconi Michael , Zhang Bojie , Li Yinyin , Dudgeon Drew , Seong Changhyun , Kim Steven , Rafique Ashique , Huang Tammy , Bhosle Sangram , Krueger Pamela , Ullman Erica , Olson William , Lin John C. , Shen Yang , Daly Christopher
Published: July 2024

Supplementary Fig S5
Supplementary Fig S2 from A Tetravalent Bispecific Antibody Selectively Inhibits Diverse FGFR3 Oncogenic Variants
Authors: Yang Yan , Suhasini Avvaru N. , Jiang Zaoli , Liu Nina , Rosconi Michael , Zhang Bojie , Li Yinyin , Dudgeon Drew , Seong Changhyun , Kim Steven , Rafique Ashique , Huang Tammy , Bhosle Sangram , Krueger Pamela , Ullman Erica , Olson William , Lin John C. , Shen Yang , Daly Christopher
Published: July 2024

Supplementary Fig S2
Supplementary Fig S12 from A Tetravalent Bispecific Antibody Selectively Inhibits Diverse FGFR3 Oncogenic Variants
Authors: Yang Yan , Suhasini Avvaru N. , Jiang Zaoli , Liu Nina , Rosconi Michael , Zhang Bojie , Li Yinyin , Dudgeon Drew , Seong Changhyun , Kim Steven , Rafique Ashique , Huang Tammy , Bhosle Sangram , Krueger Pamela , Ullman Erica , Olson William , Lin John C. , Shen Yang , Daly Christopher
Published: July 2024

Supplementary Fig S12
Supplementary Fig S11 from A Tetravalent Bispecific Antibody Selectively Inhibits Diverse FGFR3 Oncogenic Variants
Authors: Yang Yan , Suhasini Avvaru N. , Jiang Zaoli , Liu Nina , Rosconi Michael , Zhang Bojie , Li Yinyin , Dudgeon Drew , Seong Changhyun , Kim Steven , Rafique Ashique , Huang Tammy , Bhosle Sangram , Krueger Pamela , Ullman Erica , Olson William , Lin John C. , Shen Yang , Daly Christopher
Published: July 2024

Supplementary Fig S11
Supplementary Fig S10 from A Tetravalent Bispecific Antibody Selectively Inhibits Diverse FGFR3 Oncogenic Variants
Authors: Yang Yan , Suhasini Avvaru N. , Jiang Zaoli , Liu Nina , Rosconi Michael , Zhang Bojie , Li Yinyin , Dudgeon Drew , Seong Changhyun , Kim Steven , Rafique Ashique , Huang Tammy , Bhosle Sangram , Krueger Pamela , Ullman Erica , Olson William , Lin John C. , Shen Yang , Daly Christopher
Published: July 2024

Supplementary Fig S10
Supplementary Data from A Tetravalent Bispecific Antibody Selectively Inhibits Diverse FGFR3 Oncogenic Variants
Authors: Yang Yan , Suhasini Avvaru N. , Jiang Zaoli , Liu Nina , Rosconi Michael , Zhang Bojie , Li Yinyin , Dudgeon Drew , Seong Changhyun , Kim Steven , Rafique Ashique , Huang Tammy , Bhosle Sangram , Krueger Pamela , Ullman Erica , Olson William , Lin John C. , Shen Yang , Daly Christopher
Published: July 2024

Table S1
Figure S10 from Omental Preadipocytes Stimulate Matrix Remodeling and IGF Signaling to Support Ovarian Cancer Metastasis
Authors: Waters Jennifer A. , Robinson Mikella , Lujano-Olazaba Omar , Lucht Cassidy , Gilbert Samuel F. , House Carrie D.
Published: July 2024

Validation of luciferase labeled cells used in ip model
Data from Single-Cell and Spatial Transcriptome Profiling Identifies the Transcription Factor BHLHE40 as a Driver of EMT in Metastatic Colorectal Cancer
Authors: Yang Sheng , Zhang Dongsheng , Sun Qingyang , Nie Hongxu , Zhang Yue , Wang Xiaowei , Huang Yuanjian , Sun Yueming
Published: July 2024

Abstract
Colorectal cancer is one of the most common malignant tumors in humans, with liver metastasis being the primary cause of mortality. The epithelial–mesenchymal transition (EMT) process endows cancer cells with enhanced metastatic potential. To elucidate the cellular mechanisms driving EMT in colorectal cancer, we analyzed single-cell RNA sequencing data from 11 nonmetastatic primary tumors (TnM) and 11 metastatic primary tumors (TM) from colorectal cancer patients. Compared with the TnM group, the TM samples showed elevated numbers of malignant epithelial cell and cancer-associated fibroblast (CAF) subsets that displayed enrichments of EMT, angiogenesis, and TGFβ signaling pathways. One specific TM-enriched subgroup of malignant epithelial cells underwent EMT to transdifferentiate into CXCL1+ CAFs that subsequently differentiated into SFRP2+ CAFs, which was validated by spatial transcriptomic and pseudotime trajectory analyses. Furthermore, cell–cell communication analysis identified BHLHE40 as a probable key transcription factor driving EMT that was associated with poor prognosis. Finally, in vitro and in vivo experiments functionally substantiated that BHLHE40 promoted the proliferation, invasion, migration, EMT, and liver metastasis of colorectal cancer cells. In summary, this study identified BHLHE40 as a key transcription factor regulating EMT that promotes liver metastasis in colorectal cancer.

Significance: Integrated analysis of single-cell RNA sequencing and spatial transcriptomics in metastatic colorectal cancer provides insights into the mechanisms underlying EMT and cancer-associated fibroblast differentiation, which could help improve patient diagnosis and treatment.
Supplementary Table S1 from A Bispecific Antibody That Targets the Membrane-Proximal Region of Mesothelin and Retains High Anticancer Activity in the Presence of Shed Mesothelin
Authors: Chakraborty Anirban , Onda Masanori , O’Shea Tara , Wei Junxia , Liu Xiufen , Bera Tapan K. , Pastan Ira
Published: July 2024

Table S1 shows the amino acid sequences for the BsAbs investigated in the article.
Supplementary Method S1 from A Bispecific Antibody That Targets the Membrane-Proximal Region of Mesothelin and Retains High Anticancer Activity in the Presence of Shed Mesothelin
Authors: Chakraborty Anirban , Onda Masanori , O’Shea Tara , Wei Junxia , Liu Xiufen , Bera Tapan K. , Pastan Ira
Published: July 2024

Supplementary Method 1 explains the preparation of BsAb 5.
Figure S3 from A Bispecific Antibody That Targets the Membrane-Proximal Region of Mesothelin and Retains High Anticancer Activity in the Presence of Shed Mesothelin
Authors: Chakraborty Anirban , Onda Masanori , O’Shea Tara , Wei Junxia , Liu Xiufen , Bera Tapan K. , Pastan Ira
Published: July 2024

Figure S3 shows that PBMCs and bispecific antibodies alone are insufficient to kill OVCAR8-Luc cancer cells.
Figure S2 from A Bispecific Antibody That Targets the Membrane-Proximal Region of Mesothelin and Retains High Anticancer Activity in the Presence of Shed Mesothelin
Authors: Chakraborty Anirban , Onda Masanori , O’Shea Tara , Wei Junxia , Liu Xiufen , Bera Tapan K. , Pastan Ira
Published: July 2024

Figure S2 shows mesothelin expression on A431-Luc cells by flow cytometry.
Figure S1 from A Bispecific Antibody That Targets the Membrane-Proximal Region of Mesothelin and Retains High Anticancer Activity in the Presence of Shed Mesothelin
Authors: Chakraborty Anirban , Onda Masanori , O’Shea Tara , Wei Junxia , Liu Xiufen , Bera Tapan K. , Pastan Ira
Published: July 2024

Figure S1 shows BsAb 4 and BsAb 5 concentration over time in each mouse for half-life determination.
Supplementary Figure S6 from Near-infrared Photoimmunotherapy Targeting Cancer-Associated Fibroblasts in Patient-Derived Xenografts Using a Humanized Anti-Fibroblast Activation Protein Antibody
Authors: Kobayashi Teruki , Noma Kazuhiro , Nishimura Seitaro , Kato Takuya , Nishiwaki Noriyuki , Ohara Toshiaki , Kunitomo Tomoyoshi , Kawasaki Kento , Akai Masaaki , Komoto Satoshi , Kashima Hajime , Kikuchi Satoru , Tazawa Hiroshi , Shirakawa Yasuhiro , Choyke Peter L. , Kobayashi Hisataka , Fujiwara Toshiyoshi
Published: July 2024

Supplementary Figure S6
Supplementary Figure S5 from Near-infrared Photoimmunotherapy Targeting Cancer-Associated Fibroblasts in Patient-Derived Xenografts Using a Humanized Anti-Fibroblast Activation Protein Antibody
Authors: Kobayashi Teruki , Noma Kazuhiro , Nishimura Seitaro , Kato Takuya , Nishiwaki Noriyuki , Ohara Toshiaki , Kunitomo Tomoyoshi , Kawasaki Kento , Akai Masaaki , Komoto Satoshi , Kashima Hajime , Kikuchi Satoru , Tazawa Hiroshi , Shirakawa Yasuhiro , Choyke Peter L. , Kobayashi Hisataka , Fujiwara Toshiyoshi
Published: July 2024

Supplementary Figure S5
Supplementary Figure S1 from Near-infrared Photoimmunotherapy Targeting Cancer-Associated Fibroblasts in Patient-Derived Xenografts Using a Humanized Anti-Fibroblast Activation Protein Antibody
Authors: Kobayashi Teruki , Noma Kazuhiro , Nishimura Seitaro , Kato Takuya , Nishiwaki Noriyuki , Ohara Toshiaki , Kunitomo Tomoyoshi , Kawasaki Kento , Akai Masaaki , Komoto Satoshi , Kashima Hajime , Kikuchi Satoru , Tazawa Hiroshi , Shirakawa Yasuhiro , Choyke Peter L. , Kobayashi Hisataka , Fujiwara Toshiyoshi
Published: July 2024

Supplementary Figure S1
Supplementary Figure 2 from Inhibition of MALT1 and BCL2 Induces Synergistic Antitumor Activity in Models of B-Cell Lymphoma
Authors: Plotnik Joshua P. , Richardson Adam E. , Yang Haopeng , Rojas Estela , Bontcheva Velitchka , Dowell Colleen , Parsons Sydney , Wilson Ashley , Ravanmehr Vida , Will Christine , Jung Paul , Zhu Haizhong , Partha Sarathy Karunan , Panchal Sanjay C. , Mali Raghuveer Singh , Kohlhapp Frederick J. , McClure Ryan A. , Ramathal Cyril Y. , George Mariam D. , Jhala Manisha , Elsen Nathaniel L. , Qiu Wei , Judge Russell A. , Pan Chin , Mastracchio Anthony , Henderson Jared , Meulbroek Jonathan A. , Green Michael R. , Pappano William N.
Published: July 2024

Whole proteomic analysis of ABBV-MALT1 in OCI-LY3
Supplementary Figure 1 from Inhibition of MALT1 and BCL2 Induces Synergistic Antitumor Activity in Models of B-Cell Lymphoma
Authors: Plotnik Joshua P. , Richardson Adam E. , Yang Haopeng , Rojas Estela , Bontcheva Velitchka , Dowell Colleen , Parsons Sydney , Wilson Ashley , Ravanmehr Vida , Will Christine , Jung Paul , Zhu Haizhong , Partha Sarathy Karunan , Panchal Sanjay C. , Mali Raghuveer Singh , Kohlhapp Frederick J. , McClure Ryan A. , Ramathal Cyril Y. , George Mariam D. , Jhala Manisha , Elsen Nathaniel L. , Qiu Wei , Judge Russell A. , Pan Chin , Mastracchio Anthony , Henderson Jared , Meulbroek Jonathan A. , Green Michael R. , Pappano William N.
Published: July 2024

Pan-lineage PRISM analysis of ABBV-MALT1 sensitivity.
Table S1 from The CDK4/6 Inhibitor Palbociclib Synergizes with ATRA to Induce Differentiation in AML
Authors: Hu Linhui , Li Qian , Wang Jiyu , Wang Huiping , Ren Xiyang , Huang Keke , Wang Yangyang , Liang Xue , Pu Lianfang , Xiong Shudao , Zhai Zhimin
Published: July 2024

Table S1
Supplementary Data from The CDK4/6 Inhibitor Palbociclib Synergizes with ATRA to Induce Differentiation in AML
Authors: Hu Linhui , Li Qian , Wang Jiyu , Wang Huiping , Ren Xiyang , Huang Keke , Wang Yangyang , Liang Xue , Pu Lianfang , Xiong Shudao , Zhai Zhimin
Published: July 2024

Supplementary Figure Legends
Figure S4 from The CDK4/6 Inhibitor Palbociclib Synergizes with ATRA to Induce Differentiation in AML
Authors: Hu Linhui , Li Qian , Wang Jiyu , Wang Huiping , Ren Xiyang , Huang Keke , Wang Yangyang , Liang Xue , Pu Lianfang , Xiong Shudao , Zhai Zhimin
Published: July 2024

Figure S4. The effect of Palbociclib and ATRA combination on leukemia burden in vivo (A). Volcano plots of differentially expressed genes in HL-60 cells (B) and molm13 cells (C) from the control and palbociclib and ATRA combination groups.
Figure S1 from The CDK4/6 Inhibitor Palbociclib Synergizes with ATRA to Induce Differentiation in AML
Authors: Hu Linhui , Li Qian , Wang Jiyu , Wang Huiping , Ren Xiyang , Huang Keke , Wang Yangyang , Liang Xue , Pu Lianfang , Xiong Shudao , Zhai Zhimin
Published: July 2024

Figure S1. The mutation frequency of CDK4/6-cyclin D pathway genes, CDKN1A and CDKN2A in 531 AML patients (A). The expression of CDKN1A and CDKN2A was compared between AML and healthy donors in the BeatAML database. * Represent P<0.05.
Supplementary Figure S1 from The Novel ATR Inhibitor M1774 Induces Replication Protein Overexpression and Broad Synergy with DNA-targeted Anticancer Drugs
Authors: Jo Ukhyun , Arakawa Yasuhiro , Zimmermann Astrid , Taniyama Daiki , Mizunuma Makito , Jenkins Lisa M. , Maity Tapan , Kumar Suresh , Zenke Frank T. , Takebe Naoko , Pommier Yves
Published: July 2024

This figure shows Chemical structures of clinically developing ATR inhibitors.
Supplementary Figure 6 from Ultrasensitive Response Explains the Benefit of Combination Chemotherapy Despite Drug Antagonism
Authors: Patterson Sarah C. , Pomeroy Amy E. , Palmer Adam C.
Published: July 2024

Supplemental Figure 6. Experimental population dose responses on log-kill scale. A) Many chemotherapies exhibit exponential dose responses in hematologic cancers (left), which appear linear when plotted on a logarithmic scale (right). The first 90% cytotoxic effect is shown in green (reaching 1 log-kill); the next 90% cytotoxic effect is shown in blue (reaching 2 log-kills); the next 90% cytotoxic effect is shown in red (reaching 3 log-kills). B) Log-kills produced by CHOP and its components at concentrations from 0 to 100% Csustained. n=8 for SU-DHL-1, KHYG-1, and Ki-JK; n=4 for SMZ-1, MOT-N1, and DL-40.
Figure S2 from Optimizing the Design and Geometry of T Cell–Engaging Bispecific Antibodies Targeting CEA in Colorectal Cancer
Authors: Elsayed Abdullah , Plüss Louis , Nideroest Larissa , Rotta Giulia , Thoma Marina , Zangger Nathan , Peissert Frederik , Pfister Stefanie K. , Pellegrino Christian , Dakhel Plaza Sheila , De Luca Roberto , Manz Markus G. , Oxenius Annette , Puca Emanuele , Halin Cornelia , Neri Dario
Published: July 2024

Supplementary Figure S2
Figure S1 from Optimizing the Design and Geometry of T Cell–Engaging Bispecific Antibodies Targeting CEA in Colorectal Cancer
Authors: Elsayed Abdullah , Plüss Louis , Nideroest Larissa , Rotta Giulia , Thoma Marina , Zangger Nathan , Peissert Frederik , Pfister Stefanie K. , Pellegrino Christian , Dakhel Plaza Sheila , De Luca Roberto , Manz Markus G. , Oxenius Annette , Puca Emanuele , Halin Cornelia , Neri Dario
Published: July 2024

Supplementary Figure S1
Supplementary Table S2 from Loss of the DNA Repair Gene RNase H2 Identifies a Unique Subset of DDR-Deficient Leiomyosarcomas
Authors: Nakazawa Michael S. , Silverman Ian M. , Rimkunas Victoria , Veloso Artur , Glodzik Dominik , Johnson Adrienne , Ohsumi Toshiro K. , Patel Shreyaskumar R. , Conley Anthony P. , Roland Christina L. , Soliman Pamela T. , Beird Hannah C. , Wu Chia-Chin , Ingram Davis R. , Lazcano Rossana , Song Dawon , Wani Khalida M. , Lazar Alexander J. , Yap Timothy A. , Wang Wei-Lien , Livingston J. Andrew
Published: July 2024

Biallelic alterations in other DDR genes across all sarcomas in TCGA dataset. Assessment of the number of sarcomas with biallelic alterations in other DDR pathway members.
Supplementary Figure S1 from Loss of the DNA Repair Gene RNase H2 Identifies a Unique Subset of DDR-Deficient Leiomyosarcomas
Authors: Nakazawa Michael S. , Silverman Ian M. , Rimkunas Victoria , Veloso Artur , Glodzik Dominik , Johnson Adrienne , Ohsumi Toshiro K. , Patel Shreyaskumar R. , Conley Anthony P. , Roland Christina L. , Soliman Pamela T. , Beird Hannah C. , Wu Chia-Chin , Ingram Davis R. , Lazcano Rossana , Song Dawon , Wani Khalida M. , Lazar Alexander J. , Yap Timothy A. , Wang Wei-Lien , Livingston J. Andrew
Published: July 2024

Survival data of U-LMS based on RNase H2 status and RNASEH2B/RB1 HomDel status A) Overall survival of U-LMS patients based on loss of RNase H2 (n=23) or intact RNase H2 (n=85) by IHC B) Overall survival of ULMS patients with or without RNASEH2B HomDels, based on the presence or absence of RB1 HomDels.
Data from The CDK4/6 Inhibitor Palbociclib Synergizes with ATRA to Induce Differentiation in AML
Authors: Hu Linhui , Li Qian , Wang Jiyu , Wang Huiping , Ren Xiyang , Huang Keke , Wang Yangyang , Liang Xue , Pu Lianfang , Xiong Shudao , Zhai Zhimin
Published: July 2024

Abstract
Differentiation therapy based on ATRA almost cured acute promyelocytic leukemia (APL). However, it is disappointing that ATRA is not effective against other acute myeloid leukemia (AML) subtypes. Developing new and effective anti-AML therapies that promote leukemia differentiation is necessary. The CDK4/6-cyclin D pathway is a key initiator of the G1–S phase transition, which determines cell fate. Herein, we investigated whether the CDK4/6 inhibitor palbociclib would synergize with ATRA to promote leukemia differentiation in vitro and in vivo. Our findings revealed that CDK4/6-cyclin D pathway genes were aberrantly expressed in AML, and we observed that palbociclib sensitized AML cells to ATRA-induced morphologic, biochemical, and functional changes indicative of myeloid differentiation. The combination of palbociclib and ATRA attenuated AML cell expansion in vivo. These enhanced differentiation effects may be associated with the regulation of transcription factors, including RARα, E2F1, and STAT1. Overall, our findings demonstrate that CDK4/6 inhibition sensitizes AML cells to ATRA and could guide the development of novel therapeutic strategies for patients with AML.