bluuebunny/crossref_metadata_2025 huggingface dataset:
Format-tuning of in vivo-launched bispecific T cell engager enhances efficacy against renal cell carcinoma
Authors: O’Connell Ryan P , Liaw Kevin , Wellhausen Nils , Chuckran Christopher A , Bhojnagarwala Pratik S , Bordoloi Devivasha , Park Daniel , Shupin Nicholas , Kulp Daniel , June Carl H , Weiner David
Published: June 2024

Background

Advanced clear cell renal cell carcinoma (ccRCC) is a prevalent kidney cancer for which long-term survival rates are abysmal, though immunotherapies are showing potential. Not yet clinically vetted are bispecific T cell engagers (BTEs) that activate T cell-mediated cancer killing through intercellular synapsing. Multiple BTE formats exist, however, with limited cross-characterizations to help optimize new drug design. Here, we developed BTEs to treat ccRCC by targeting carbonic anhydrase 9 (CA9) while characterizing the persistent BTE (PBTE) format and comparing it to a new format, the persistent multivalent T cell engager (PMTE). These antibody therapies against ccRCC are developed as both recombinant and synthetic DNA (synDNA) medicines.

Methods

Antibody formatting effects on binding kinetics were assessed by flow cytometry and intercellular synaptic strength assays while potency was tested using T-cell activation and cytotoxicity assays. Mouse models were used to study antibody plasma and tumor pharmacokinetics, as well as antitumor efficacy as both recombinant and synDNA medicines. Specifically, three models using ccRCC cell line xenografts and human donor T cells in immunodeficient mice were used to support this study.

Results

Compared with a first-generation BTE, we show that the PBTE reduced avidity, intercellular synaptic strength, cytotoxic potency by as much as 33-fold, and ultimately efficacy against ccRCC tumors in vivo. However, compared with the PBTE, we demonstrate that the PMTE improved cell avidity, restored intercellular synapses, augmented cytotoxic potency by 40-fold, improved tumor distribution pharmacokinetics by 2-fold, and recovered synDNA efficacy in mouse tumor models by 20-fold. All the while, the PMTE displayed a desirable half-life of 4 days in mice compared with the conventional BTE’s 2 hours.

Conclusions

With impressive efficacy, the CA9-targeted PMTE is a promising new therapy for advanced ccRCC, which can be effectively delivered through synDNA. The highly potent PMTE format itself is a promising new tool for future applications in the multispecific antibody space.
Sudden change of genuine multipartite entanglement in non-Markovian dynamics
Authors: Ali Mazhar
Published: June 2024

We investigate entanglement dynamics of bipartite as well multipartite systems beyond Markov approximation. We study two pairs of cavity–reservoir systems, modeled as four qubits and track the change of entanglement among cavity–cavity qubits, reservoir–reservoir qubits, and also for genuine entanglement of all four qubits. For cavity–cavity qubits, we find that non-Markovianity prolongs the life of entanglement besides collapse/revival phenomenon. For reservoir–reservoir qubits, entanglement sudden birth is delayed accordingly along with oscillations. For all four qubits, with a specific initial state, we find that genuine entanglement develops gradually, reaches to a maximum constant value and then freezes at this value for some time before decaying. This sudden change in dynamics of genuine entanglement occurs for a time window where neither cavities nor reservoirs are entangled. In contrast to Markov process, sudden change phenomenon may be recurrent in non-Markovian regime.
Social media-based community science for turtle nest monitoring and conservation
Authors: Dupuis-Désormeaux Marc , Van Alstyne Grace , Mueller Maureen , Takayesu Ruth , D'Elia Vince , Tan Tisha , MacDonald Suzanne E.
Published: June 2024

In late 2020, a private volunteer group operating through a Facebook group approached Toronto and Region Conservation Authority (TRCA) with an interest in participating in the Citizen Science Nest Protection and Monitoring Volunteer Program. During the 2021 season, TRCA staff virtually trained volunteers in turtle nest detection, protection, and monitoring due to COVID-19 social constraints, and provided necessary supplies and equipment. In 2021 volunteers and staff detected 181 turtle nests and were able to protect 75 nests with simple predator-exclusion devices, while in 2022, 165 nests were detected, and 155 were protected. The volunteers also collected data, including nesting location, date, and species in addition to the number of successful hatchlings (2021 only). In 2021, the 75 protected nests yielded 81 Midland Painted Turtle and 665 Snapping Turtle hatchlings. Five Midland Painted Turtle’s eggs were also recovered from an injured turtle, and 44 Snapping Turtle eggs were recovered from a partially predated nest, transported to the Ontario Turtle Conservation Centre, incubated, hatched, and overwintered, and then released back into the local wetlands. The partnership with a local community group proved effective, and we would recommend this practice to other conservation organizations interested in turtle nest protection.
Intra-Turonian stratigraphic reorganization on the Arabian Plate
Authors: Simmons Michael D. , Bidgood Michael D. , Davies Roger B. , Droste Henk , Levell Bruce , Razin Philippe , van Buchem Frans S. P.
Published: June 2024

Shallow-marine carbonate deposition was widespread across the Arabian Plate during much of the Late Permian–Mesozoic but was significantly interrupted by a major tectonically driven stratigraphic reorganization that took place within the Turonian. Published literature terms this the ‘Wasia–Aruma Break’, the ‘mid-Turonian Unconformity’, or the ‘K150 Sequence Boundary (SB)’. It is widely understood that this event relates to subduction in a closing Neotethys Ocean and obduction onto the continental margin, especially in the southeastern part of the plate. As well as a change in facies, a hiatus of variable duration is present, associated with erosion of the underlying stratigraphy.

Despite the event being known for several decades, precision on its timing has been lacking due to the limitations of biostratigraphic data and because few other chronostratigraphic proxies have been employed. In order to rectify this, all relevant biostratigraphic data from across the Arabian Plate have been synthesized and evaluated in the context of a review of chronostratigraphic calibration of standard biozones from multiple fossil groups. This shows that the youngest preserved rocks beneath the K150 SB can be assigned to the middle Turonian
Helvetoglobotruncana helvetica
planktonic foraminifera zone or
Collignoniceras woollgari
ammonite zone. The oldest rocks above the K150 SB can be assigned to the same biozones, supporting the assertions that it is a very short duration event. Whilst obduction may have initiated earlier (as supported by the recognition of precursor events), crustal loading was sufficient by 91.5 Ma to develop a forebulge in the eastern part of the plate with associated uplift and erosion.

A review of relative sea-level change during the Turonian has been carried out to investigate eustatic signals during this time. In multiple sections around the world, a sea-level fall in the upper part of the
woollgari
Zone of European usage can be detected. This appears to coincide with an episode of climate cooling. However, despite there being correspondence between the K150 SB and a significant eustatic event, this seems mostly coincidental as the tectonic drivers at this time across Arabia were much more dramatic. This is especially true in southeastern Arabia. In northwestern Arabia, tectonic quiescence may have allowed eustasy to dominate. In any case, a eustatic fall would have amplified the effects of tectonics across the entire region.
Supplementary Figure S8 from A Histone Methylation–MAPK Signaling Axis Drives Durable Epithelial–Mesenchymal Transition in Hypoxic Pancreatic Cancer
Authors: Brown Brooke A. , Myers Paul J. , Adair Sara J. , Pitarresi Jason R. , Sah-Teli Shiv K. , Campbell Logan A. , Hart William S. , Barbeau Michelle C. , Leong Kelsey , Seyler Nicholas , Kane William , Lee Kyoung Eun , Stelow Edward , Jones Marieke , Simon M. Celeste , Koivunen Peppi , Bauer Todd W. , Stanger Ben Z. , Lazzara Matthew J.
Published: June 2024

Supplementary Figure S8
Supplementary Figure S5 from A Histone Methylation–MAPK Signaling Axis Drives Durable Epithelial–Mesenchymal Transition in Hypoxic Pancreatic Cancer
Authors: Brown Brooke A. , Myers Paul J. , Adair Sara J. , Pitarresi Jason R. , Sah-Teli Shiv K. , Campbell Logan A. , Hart William S. , Barbeau Michelle C. , Leong Kelsey , Seyler Nicholas , Kane William , Lee Kyoung Eun , Stelow Edward , Jones Marieke , Simon M. Celeste , Koivunen Peppi , Bauer Todd W. , Stanger Ben Z. , Lazzara Matthew J.
Published: June 2024

Supplementary Figure S5
Supplementary Figure S13 from A Histone Methylation–MAPK Signaling Axis Drives Durable Epithelial–Mesenchymal Transition in Hypoxic Pancreatic Cancer
Authors: Brown Brooke A. , Myers Paul J. , Adair Sara J. , Pitarresi Jason R. , Sah-Teli Shiv K. , Campbell Logan A. , Hart William S. , Barbeau Michelle C. , Leong Kelsey , Seyler Nicholas , Kane William , Lee Kyoung Eun , Stelow Edward , Jones Marieke , Simon M. Celeste , Koivunen Peppi , Bauer Todd W. , Stanger Ben Z. , Lazzara Matthew J.
Published: June 2024

Supplementary Figure S13
Supplementary Tables from Whole-Genome DNA Methylation Profiling of Intrahepatic Cholangiocarcinoma Reveals Prognostic Subtypes with Distinct Biological Drivers
Authors: Liao Haotian , Chen Xing , Wang Haichuan , Lin Youpei , Chen Lu , Yuan Kefei , Liao Mingheng , Jiang Hanyu , Peng Jiajie , Wu Zhenru , Huang Jiwei , Li Jiaxin , Zeng Yong
Published: June 2024

Supplementary Table S1-S11
Supplementary Fig. S12 from Whole-Genome DNA Methylation Profiling of Intrahepatic Cholangiocarcinoma Reveals Prognostic Subtypes with Distinct Biological Drivers
Authors: Liao Haotian , Chen Xing , Wang Haichuan , Lin Youpei , Chen Lu , Yuan Kefei , Liao Mingheng , Jiang Hanyu , Peng Jiajie , Wu Zhenru , Huang Jiwei , Li Jiaxin , Zeng Yong
Published: June 2024

Supplementary Fig. S12
Supplementary Fig. S1 from Whole-Genome DNA Methylation Profiling of Intrahepatic Cholangiocarcinoma Reveals Prognostic Subtypes with Distinct Biological Drivers
Authors: Liao Haotian , Chen Xing , Wang Haichuan , Lin Youpei , Chen Lu , Yuan Kefei , Liao Mingheng , Jiang Hanyu , Peng Jiajie , Wu Zhenru , Huang Jiwei , Li Jiaxin , Zeng Yong
Published: June 2024

Supplementary Fig. S1
Supplementary Tables S1-S19 from Obesogenic High-Fat Diet and MYC Cooperate to Promote Lactate Accumulation and Tumor Microenvironment Remodeling in Prostate Cancer
Authors: Boufaied Nadia , Chetta Paolo , Hallal Tarek , Cacciatore Stefano , Lalli Daniela , Luthold Carole , Homsy Kevin , Imada Eddie L. , Syamala Sudeepa , Photopoulos Cornelia , Di Matteo Anna , de Polo Anna , Storaci Alessandra Maria , Huang Ying , Giunchi Francesca , Sheridan Patricia A. , Michelotti Gregory , Nguyen Quang-De , Zhao Xin , Liu Yang , Davicioni Elai , Spratt Daniel E. , Sabbioneda Simone , Maga Giovanni , Mucci Lorelei A. , Ghigna Claudia , Marchionni Luigi , Butler Lisa M. , Ellis Leigh , Bordeleau François , Loda Massimo , Vaira Valentina , Labbé David P. , Zadra Giorgia
Published: June 2024

Excel file containing 19 supplementary tables
Supplementary Information from Obesogenic High-Fat Diet and MYC Cooperate to Promote Lactate Accumulation and Tumor Microenvironment Remodeling in Prostate Cancer
Authors: Boufaied Nadia , Chetta Paolo , Hallal Tarek , Cacciatore Stefano , Lalli Daniela , Luthold Carole , Homsy Kevin , Imada Eddie L. , Syamala Sudeepa , Photopoulos Cornelia , Di Matteo Anna , de Polo Anna , Storaci Alessandra Maria , Huang Ying , Giunchi Francesca , Sheridan Patricia A. , Michelotti Gregory , Nguyen Quang-De , Zhao Xin , Liu Yang , Davicioni Elai , Spratt Daniel E. , Sabbioneda Simone , Maga Giovanni , Mucci Lorelei A. , Ghigna Claudia , Marchionni Luigi , Butler Lisa M. , Ellis Leigh , Bordeleau François , Loda Massimo , Vaira Valentina , Labbé David P. , Zadra Giorgia
Published: June 2024

Supplementary references for Materials and Methods
Supplementary Figure S8 from Obesogenic High-Fat Diet and MYC Cooperate to Promote Lactate Accumulation and Tumor Microenvironment Remodeling in Prostate Cancer
Authors: Boufaied Nadia , Chetta Paolo , Hallal Tarek , Cacciatore Stefano , Lalli Daniela , Luthold Carole , Homsy Kevin , Imada Eddie L. , Syamala Sudeepa , Photopoulos Cornelia , Di Matteo Anna , de Polo Anna , Storaci Alessandra Maria , Huang Ying , Giunchi Francesca , Sheridan Patricia A. , Michelotti Gregory , Nguyen Quang-De , Zhao Xin , Liu Yang , Davicioni Elai , Spratt Daniel E. , Sabbioneda Simone , Maga Giovanni , Mucci Lorelei A. , Ghigna Claudia , Marchionni Luigi , Butler Lisa M. , Ellis Leigh , Bordeleau François , Loda Massimo , Vaira Valentina , Labbé David P. , Zadra Giorgia
Published: June 2024

Supplementary Figure S8 shows migration assays of MYC-CaP cells treated with lactate or LDHA inhibitor FX11.
Supplementary Figure S5 from Obesogenic High-Fat Diet and MYC Cooperate to Promote Lactate Accumulation and Tumor Microenvironment Remodeling in Prostate Cancer
Authors: Boufaied Nadia , Chetta Paolo , Hallal Tarek , Cacciatore Stefano , Lalli Daniela , Luthold Carole , Homsy Kevin , Imada Eddie L. , Syamala Sudeepa , Photopoulos Cornelia , Di Matteo Anna , de Polo Anna , Storaci Alessandra Maria , Huang Ying , Giunchi Francesca , Sheridan Patricia A. , Michelotti Gregory , Nguyen Quang-De , Zhao Xin , Liu Yang , Davicioni Elai , Spratt Daniel E. , Sabbioneda Simone , Maga Giovanni , Mucci Lorelei A. , Ghigna Claudia , Marchionni Luigi , Butler Lisa M. , Ellis Leigh , Bordeleau François , Loda Massimo , Vaira Valentina , Labbé David P. , Zadra Giorgia
Published: June 2024

Supplementary Figure S5 shows the output of ESTIMATE and PUREE methods to assess tumor purity.
Supplementary Figure S4 from Obesogenic High-Fat Diet and MYC Cooperate to Promote Lactate Accumulation and Tumor Microenvironment Remodeling in Prostate Cancer
Authors: Boufaied Nadia , Chetta Paolo , Hallal Tarek , Cacciatore Stefano , Lalli Daniela , Luthold Carole , Homsy Kevin , Imada Eddie L. , Syamala Sudeepa , Photopoulos Cornelia , Di Matteo Anna , de Polo Anna , Storaci Alessandra Maria , Huang Ying , Giunchi Francesca , Sheridan Patricia A. , Michelotti Gregory , Nguyen Quang-De , Zhao Xin , Liu Yang , Davicioni Elai , Spratt Daniel E. , Sabbioneda Simone , Maga Giovanni , Mucci Lorelei A. , Ghigna Claudia , Marchionni Luigi , Butler Lisa M. , Ellis Leigh , Bordeleau François , Loda Massimo , Vaira Valentina , Labbé David P. , Zadra Giorgia
Published: June 2024

Supplementary Figure S4 shows the effect of obesogenic high-fat diet on glycolytic enzymes and HIF-1 alpha in vivo.
Supplementary Data from ACSL4-Mediated Membrane Phospholipid Remodeling Induces Integrin β1 Activation to Facilitate Triple-Negative Breast Cancer Metastasis
Authors: Qiu Yuxiang , Wang Xing , Sun Yan , Jin Ting , Tang Rui , Zhou Xinyue , Xu Ming , Gan Yubi , Wang Rui , Luo Haojun , Liu Manran , Tang Xi
Published: June 2024

Supplementary Figure S1-S7
Supplementary Table S3 from The Deep Learning Framework iCanTCR Enables Early Cancer Detection Using the T-cell Receptor Repertoire in Peripheral Blood
Authors: Cai Yideng , Luo Meng , Yang Wenyi , Xu Chang , Wang Pingping , Xue Guangfu , Jin Xiyun , Cheng Rui , Que Jinhao , Zhou Wenyang , Pang Boran , Xu Shouping , Li Yu , Jiang Qinghua , Xu Zhaochun
Published: June 2024

Sample information of non-cancer cohorts in Emerson's study
Supplementary Table S1 from The Deep Learning Framework iCanTCR Enables Early Cancer Detection Using the T-cell Receptor Repertoire in Peripheral Blood
Authors: Cai Yideng , Luo Meng , Yang Wenyi , Xu Chang , Wang Pingping , Xue Guangfu , Jin Xiyun , Cheng Rui , Que Jinhao , Zhou Wenyang , Pang Boran , Xu Shouping , Li Yu , Jiang Qinghua , Xu Zhaochun
Published: June 2024

Information of cancer samples from TCRdb used in this study
Supplementary Figures S1-S8 from The Deep Learning Framework iCanTCR Enables Early Cancer Detection Using the T-cell Receptor Repertoire in Peripheral Blood
Authors: Cai Yideng , Luo Meng , Yang Wenyi , Xu Chang , Wang Pingping , Xue Guangfu , Jin Xiyun , Cheng Rui , Que Jinhao , Zhou Wenyang , Pang Boran , Xu Shouping , Li Yu , Jiang Qinghua , Xu Zhaochun
Published: June 2024

Supplementary Figure S1-S8
Supplementary Table S1 from Oncogenic Cell Tagging and Single-Cell Transcriptomics Reveal Cell Type–Specific and Time-Resolved Responses to Vhl Inactivation in the Kidney
Authors: Kurlekar Samvid , Lima Joanna D.C.C. , Li Ran , Lombardi Olivia , Masson Norma , Barros Ayslan B. , Pontecorvi Virginia , Mole David R. , Pugh Christopher W. , Adam Julie , Ratcliffe Peter J.
Published: June 2024

scRNA-seq metrics, cell type markers, and lists of differentially expressed genes
Supplementary Figure S3 from Oncogenic Cell Tagging and Single-Cell Transcriptomics Reveal Cell Type–Specific and Time-Resolved Responses to Vhl Inactivation in the Kidney
Authors: Kurlekar Samvid , Lima Joanna D.C.C. , Li Ran , Lombardi Olivia , Masson Norma , Barros Ayslan B. , Pontecorvi Virginia , Mole David R. , Pugh Christopher W. , Adam Julie , Ratcliffe Peter J.
Published: June 2024

Vhl-null cells specifically undergo time-dependent alterations in gene expression
Supplementary Data from Regular Use of Aspirin and Statins Reduces the Risk of Cancer in Individuals with Systemic Inflammatory Diseases
Authors: Lin Jia-Run , Han Duan-Duan , Wei Wei , Zeng Qin , Rong Zi-Xuan , Bai Xue , Zhang Yan-Pei , Wang Jian , Cai Xiao-Ting , Rao Xu-Guang , Ma Si-Cong , Dong Zhong-Yi
Published: June 2024

Supplementary Fig. S1-13，Supplementary Table S1-15
Supplementary Figure S1 from Oncogenic Cell Tagging and Single-Cell Transcriptomics Reveal Cell Type–Specific and Time-Resolved Responses to Vhl Inactivation in the Kidney
Authors: Kurlekar Samvid , Lima Joanna D.C.C. , Li Ran , Lombardi Olivia , Masson Norma , Barros Ayslan B. , Pontecorvi Virginia , Mole David R. , Pugh Christopher W. , Adam Julie , Ratcliffe Peter J.
Published: June 2024

Single-cell RNA sequencing on flow-sorted renal cells
Figure 5 from Oncogenic Cell Tagging and Single-Cell Transcriptomics Reveal Cell Type–Specific and Time-Resolved Responses to Vhl Inactivation in the Kidney
Authors: Kurlekar Samvid , Lima Joanna D.C.C. , Li Ran , Lombardi Olivia , Masson Norma , Barros Ayslan B. , Pontecorvi Virginia , Mole David R. , Pugh Christopher W. , Adam Julie , Ratcliffe Peter J.
Published: June 2024

Vhl-null cells specifically undergo time-dependent alterations in gene expression. A, Density plot depicting UMAP distribution of tdTomato-positive cells from kidneys of Control and KO mice harvested at the early or late time points. B, Left, UMAP plot depicting tdTomato-positive cells from Control and KO mice harvested at the early and late time points colored by UMAP cluster. Right, proportion of cells from each condition belonging to any cluster. C, Scatter plot depicting frequency of expression in tdTomato-positive cells from KO mice at the late time point against log2-fold change (log2FC) between cells from KO mice at the late versus early time points for all genes. Orange, significantly regulated genes. Genes explicitly mentioned in the main text are labeled. D, Gene set enrichment plots depicting upregulation of genes regulated early after Vhl inactivation (left) or genes known to be HIF targets (right) in Vhl-null cells at the late versus early time points. NES, normalized enrichment score. P value adjusted by Bonferroni correction for multiple testing. E, UMAP plot depicting “PT like” cells among tdTomato-positive cells from Control and KO mice harvested at the early and late time points. Black, PT-like cells. F, Proportion of cells inferred to be “PT like” within tdTomato-positive (top) or tdTomato-negative (bottom) cells across conditions. Median and interquartile range plotted. Pairwise comparisons tested by one-way ANOVA with Holm–Šídák correction. G, Representative CD45 IHC on kidneys from Control (n = 1F, 4M) and KO (n = 6M) mice harvested at the late time point. Scale bar, 50 μm. Magnification, ×40. A–F, scRNA-seq data shown for n = 3F, 1M mice for Control early and Control late samples; n = 2F, 2M mice for KO early and KO late samples.
Figure 4 from Oncogenic Cell Tagging and Single-Cell Transcriptomics Reveal Cell Type–Specific and Time-Resolved Responses to Vhl Inactivation in the Kidney
Authors: Kurlekar Samvid , Lima Joanna D.C.C. , Li Ran , Lombardi Olivia , Masson Norma , Barros Ayslan B. , Pontecorvi Virginia , Mole David R. , Pugh Christopher W. , Adam Julie , Ratcliffe Peter J.
Published: June 2024

Renal cortex, but not the papilla, is permissive to long-term survival of Vhl-null cells. A, Representative tdTomato IHC counterstained with hematoxylin in different renal anatomical regions of Control or KO mice harvested at the early or late time points. Scale bar, 100 μm. Magnification, ×20. B, Proportion of cells that are tdTomato-positive in different regions of the kidney as quantified by tdTomato IHC in kidneys from Control or KO mice harvested at different intervals after recombination. n = 7F, 16M for all regions for KO; n = 9F, 15M; 9F, 15M; 9F, 14M; 8F, 14M for cortex, outer medulla, inner medulla, and papilla, respectively, for Control. Line denotes linear regression. Significance testing performed for slope and intercept of linear regression by t test.
Figure 3 from Oncogenic Cell Tagging and Single-Cell Transcriptomics Reveal Cell Type–Specific and Time-Resolved Responses to Vhl Inactivation in the Kidney
Authors: Kurlekar Samvid , Lima Joanna D.C.C. , Li Ran , Lombardi Olivia , Masson Norma , Barros Ayslan B. , Pontecorvi Virginia , Mole David R. , Pugh Christopher W. , Adam Julie , Ratcliffe Peter J.
Published: June 2024

Biallelic Vhl inactivation entrains early cell-specific transcriptomic changes in RTE cells. A, Density plot depicting UMAP distribution of tdTomato-negative and -positive cells from kidneys of Control and KO mice harvested early after recombination. B, Left, UMAP plot depicting cells from Control and KO mice harvested early after recombination colored by UMAP clusters. Right, proportion of cells from each condition belonging to any cluster. C, Scatter plot depicting frequency of expression in tdTomato-negative (top) or tdTomato-positive (bottom) cells from KO mice against log2-fold change (log2FC) between cells from KO versus Control mice for all genes at the early time point. Orange, significantly regulated genes. Genes explicitly mentioned in the main text are labeled. D, Scatter plot depicting log2-fold change between tdTomato-positive cells from KO versus Control for genes significantly regulated in every renal cell identity. Blue, names of HIF target genes. E, PCA of gene expression changes early after Vhl inactivation in different renal cell identities. A–E, scRNA-seq data are shown for n = 3F, 1M for Control negative; n = 3F, 1M mice for Control positive samples; n = 2F, 1M mice for KO negative samples; n = 2F, 2M mice for KO-positive samples.
Supplementary tables from Repolarization of Immunosuppressive Macrophages by Targeting SLAMF7-Regulated CCL2 Signaling Sensitizes Hepatocellular Carcinoma to Immunotherapy
Authors: Weng Jialei , Wang Zheng , Hu Zhiqiu , Xu Wenxin , Sun Jia-Lei , Wang Fu , Zhou Qiang , Liu Shaoqing , Xu Min , Xu Minghao , Gao Dongmei , Shen Ying-Hao , Yi Yong , Shi Yi , Dong Qiongzhu , Zhou Chenhao , Ren Ning
Published: June 2024

The Supplementary Data consist of:
Supplementary Tables S1-7
Supplementary Figure S3 from Repolarization of Immunosuppressive Macrophages by Targeting SLAMF7-Regulated CCL2 Signaling Sensitizes Hepatocellular Carcinoma to Immunotherapy
Authors: Weng Jialei , Wang Zheng , Hu Zhiqiu , Xu Wenxin , Sun Jia-Lei , Wang Fu , Zhou Qiang , Liu Shaoqing , Xu Min , Xu Minghao , Gao Dongmei , Shen Ying-Hao , Yi Yong , Shi Yi , Dong Qiongzhu , Zhou Chenhao , Ren Ning
Published: June 2024

(A-B) Flow cytometry assays of tumor infiltration proportions of CD11b+ F4/80+ MHC-II+ macrophages and CD3+ CD8+ PD-1+ T cells in orthotopic Hepa1-6 tumors with Slamf7 overexpression and control groups. (C) Heatmap showing the immunological activity ssGSEA scores in tumor samples from TCGA-LIHC cohort. The upper horizontal bars represent the expression level of SLAMF7. (D) Correlation matrix showing the relationships between SLAMF7 level and various immune activity scores in tumors from TCGA-LIHC cohort. (E) Violin diagrams showing the percentages of 22 immune cell types calculated using the CIBERSORT method in HCC tumors with SLAMF7 high and low expression groups. (F) The standardized risk score of a T cell exhaustion (TEX) signature between tumors with low and high SLAMF7 expression in the TCGA-LIHC cohort. (G) Correlation of the risk score of a M2-like macrophage-related gene signature with mRNA level of SLAMF7 in GSE14520 cohort. (H) Immunologic signature gene sets enriched in HCC with high SLAMF7 expression from TCGA-LIHC cohort. Student’s t test.
Supplementary Figure S2 from Repolarization of Immunosuppressive Macrophages by Targeting SLAMF7-Regulated CCL2 Signaling Sensitizes Hepatocellular Carcinoma to Immunotherapy
Authors: Weng Jialei , Wang Zheng , Hu Zhiqiu , Xu Wenxin , Sun Jia-Lei , Wang Fu , Zhou Qiang , Liu Shaoqing , Xu Min , Xu Minghao , Gao Dongmei , Shen Ying-Hao , Yi Yong , Shi Yi , Dong Qiongzhu , Zhou Chenhao , Ren Ning
Published: June 2024

Representative IHC staining images of p53 protein in murine liver tumor tissues in the indicated groups. Scale bar: 50 μm.
Table S7 from Cigarette Smoking and E-cigarette Use Induce Shared DNA Methylation Changes Linked to Carcinogenesis
Authors: Herzog Chiara , Jones Allison , Evans Iona , Raut Janhavi R. , Zikan Michal , Cibula David , Wong Andrew , Brenner Hermann , Richmond Rebecca C. , Widschwendter Martin
Published: June 2024

Supplementary Table 7
Table S6 from Cigarette Smoking and E-cigarette Use Induce Shared DNA Methylation Changes Linked to Carcinogenesis
Authors: Herzog Chiara , Jones Allison , Evans Iona , Raut Janhavi R. , Zikan Michal , Cibula David , Wong Andrew , Brenner Hermann , Richmond Rebecca C. , Widschwendter Martin
Published: June 2024

Supplementary Table 6
Table S4 from Cigarette Smoking and E-cigarette Use Induce Shared DNA Methylation Changes Linked to Carcinogenesis
Authors: Herzog Chiara , Jones Allison , Evans Iona , Raut Janhavi R. , Zikan Michal , Cibula David , Wong Andrew , Brenner Hermann , Richmond Rebecca C. , Widschwendter Martin
Published: June 2024

Supplementary Table 4
Table S3 from Cigarette Smoking and E-cigarette Use Induce Shared DNA Methylation Changes Linked to Carcinogenesis
Authors: Herzog Chiara , Jones Allison , Evans Iona , Raut Janhavi R. , Zikan Michal , Cibula David , Wong Andrew , Brenner Hermann , Richmond Rebecca C. , Widschwendter Martin
Published: June 2024

Supplementary Table 3
Table S2 from Cigarette Smoking and E-cigarette Use Induce Shared DNA Methylation Changes Linked to Carcinogenesis
Authors: Herzog Chiara , Jones Allison , Evans Iona , Raut Janhavi R. , Zikan Michal , Cibula David , Wong Andrew , Brenner Hermann , Richmond Rebecca C. , Widschwendter Martin
Published: June 2024

Supplementary Table 2
Table S1 from Cigarette Smoking and E-cigarette Use Induce Shared DNA Methylation Changes Linked to Carcinogenesis
Authors: Herzog Chiara , Jones Allison , Evans Iona , Raut Janhavi R. , Zikan Michal , Cibula David , Wong Andrew , Brenner Hermann , Richmond Rebecca C. , Widschwendter Martin
Published: June 2024

Supplementary Table 1
Figure S8 from Cigarette Smoking and E-cigarette Use Induce Shared DNA Methylation Changes Linked to Carcinogenesis
Authors: Herzog Chiara , Jones Allison , Evans Iona , Raut Janhavi R. , Zikan Michal , Cibula David , Wong Andrew , Brenner Hermann , Richmond Rebecca C. , Widschwendter Martin
Published: June 2024

Supplementary Figure 8
Figure S7 from Cigarette Smoking and E-cigarette Use Induce Shared DNA Methylation Changes Linked to Carcinogenesis
Authors: Herzog Chiara , Jones Allison , Evans Iona , Raut Janhavi R. , Zikan Michal , Cibula David , Wong Andrew , Brenner Hermann , Richmond Rebecca C. , Widschwendter Martin
Published: June 2024

Supplementary Figure 7
Figure S3 from Cigarette Smoking and E-cigarette Use Induce Shared DNA Methylation Changes Linked to Carcinogenesis
Authors: Herzog Chiara , Jones Allison , Evans Iona , Raut Janhavi R. , Zikan Michal , Cibula David , Wong Andrew , Brenner Hermann , Richmond Rebecca C. , Widschwendter Martin
Published: June 2024

Supplementary Figure 3
Figure S2 from Cigarette Smoking and E-cigarette Use Induce Shared DNA Methylation Changes Linked to Carcinogenesis
Authors: Herzog Chiara , Jones Allison , Evans Iona , Raut Janhavi R. , Zikan Michal , Cibula David , Wong Andrew , Brenner Hermann , Richmond Rebecca C. , Widschwendter Martin
Published: June 2024

Supplementary Figure 2
Figure S11 from Cigarette Smoking and E-cigarette Use Induce Shared DNA Methylation Changes Linked to Carcinogenesis
Authors: Herzog Chiara , Jones Allison , Evans Iona , Raut Janhavi R. , Zikan Michal , Cibula David , Wong Andrew , Brenner Hermann , Richmond Rebecca C. , Widschwendter Martin
Published: June 2024

Supplementary Figure 11
Figure S1 from Cigarette Smoking and E-cigarette Use Induce Shared DNA Methylation Changes Linked to Carcinogenesis
Authors: Herzog Chiara , Jones Allison , Evans Iona , Raut Janhavi R. , Zikan Michal , Cibula David , Wong Andrew , Brenner Hermann , Richmond Rebecca C. , Widschwendter Martin
Published: June 2024

Supplementary Figure 1
Figure 3 from Cigarette Smoking and E-cigarette Use Induce Shared DNA Methylation Changes Linked to Carcinogenesis
Authors: Herzog Chiara , Jones Allison , Evans Iona , Raut Janhavi R. , Zikan Michal , Cibula David , Wong Andrew , Brenner Hermann , Richmond Rebecca C. , Widschwendter Martin
Published: June 2024

Evaluation of scores in independent validation sets. Independent dataset comprising 304 matched blood and buccal samples (n = 152 each) and 442 cervical samples was used to validate the findings. A–C, Mean beta values (uncorrected) in each of the four sets of CpGs in buccal (A), blood (B), and cervical (C) samples of never smokers, ex-smokers, and current smokers versus immune cell proportion (A and C) or lymphoid proportion (B). D–F, AUC of corrected values in each of the four sets of CpG comparing never smokers with current or former smokers in buccal (D), blood (E), and cervical (F) samples. Mean methylation scores in this figure only include sites present on the 450K array for comparability between datasets.
Figure 1 from Cigarette Smoking and E-cigarette Use Induce Shared DNA Methylation Changes Linked to Carcinogenesis
Authors: Herzog Chiara , Jones Allison , Evans Iona , Raut Janhavi R. , Zikan Michal , Cibula David , Wong Andrew , Brenner Hermann , Richmond Rebecca C. , Widschwendter Martin
Published: June 2024

General overview of the study and identification of cell type–specific smoking-dependent epigenetic changes. A, Overview of the study. We aimed to identify cell- and tissue-specific epigenetic alterations and used a discovery set of buccal, cervical, and immune cells (all female). Findings were then validated in several independent sets to confirm the association with current and former smoking and explore association of cell-specific effects across smoking alternatives (e-cigarette use, moist tobacco use), lung cancer tissue and progression, and possibility to predict lung cancers in smokers using noninvasive samples. A detailed workflow of the analysis is shown in Supplementary Fig. S1. B, Scatterplots of methylation beta values in three CpGs located in the AHRR gene or intergenic region versus immune cell proportion (buccal and cervical samples) or lymphoid proportion (blood) indicate methylation differences may be derived from distinct cell types. C, Visualization of delta-beta values across four groups of CpGs identified in Supplementary Fig. S5A. A matrix of inferred delta-beta values across all tissues for all significant CpGs (i.e., significant in at least one tissue in the EWAS) was clustered using UMAP and the following clusters identified: epithelial hypomethylation (epithelial hypoM), immune hypomethylation (immune hypoM), distal epithelial hypermethylation (distal epithelial hyperM; effects in distal epithelium but not directly exposed epithelium), and proximal epithelial hypermethylation (proximal epithelial hypoM; effects in buccal/directly exposed samples only). (A, Created with BioRender.com.)
Data from A Histone Methylation–MAPK Signaling Axis Drives Durable Epithelial–Mesenchymal Transition in Hypoxic Pancreatic Cancer
Authors: Brown Brooke A. , Myers Paul J. , Adair Sara J. , Pitarresi Jason R. , Sah-Teli Shiv K. , Campbell Logan A. , Hart William S. , Barbeau Michelle C. , Leong Kelsey , Seyler Nicholas , Kane William , Lee Kyoung Eun , Stelow Edward , Jones Marieke , Simon M. Celeste , Koivunen Peppi , Bauer Todd W. , Stanger Ben Z. , Lazzara Matthew J.
Published: June 2024

Abstract
The tumor microenvironment in pancreatic ductal adenocarcinoma (PDAC) plays a key role in tumor progression and response to therapy. The dense PDAC stroma causes hypovascularity, which leads to hypoxia. Here, we showed that hypoxia drives long-lasting epithelial–mesenchymal transition (EMT) in PDAC primarily through a positive-feedback histone methylation–MAPK signaling axis. Transformed cells preferentially underwent EMT in hypoxic tumor regions in multiple model systems. Hypoxia drove a cell autonomous EMT in PDAC cells, which, unlike EMT in response to growth factors, could last for weeks. Furthermore, hypoxia reduced histone demethylase KDM2A activity, suppressed PP2 family phosphatase expression, and activated MAPKs to post-translationally stabilize histone methyltransferase NSD2, leading to an H3K36me2-dependent EMT in which hypoxia-inducible factors played only a supporting role. Hypoxia-driven EMT could be antagonized in vivo by combinations of MAPK inhibitors. Collectively, these results suggest that hypoxia promotes durable EMT in PDAC by inducing a histone methylation–MAPK axis that can be effectively targeted with multidrug therapies, providing a potential strategy for overcoming chemoresistance.
Significance:
Integrated regulation of histone methylation and MAPK signaling by the low-oxygen environment of pancreatic cancer drives long-lasting EMT that promotes chemoresistance and shortens patient survival and that can be pharmacologically inhibited.

See related commentary by Wirth and Schneider, p. 1739
Data from Obesogenic High-Fat Diet and MYC Cooperate to Promote Lactate Accumulation and Tumor Microenvironment Remodeling in Prostate Cancer
Authors: Boufaied Nadia , Chetta Paolo , Hallal Tarek , Cacciatore Stefano , Lalli Daniela , Luthold Carole , Homsy Kevin , Imada Eddie L. , Syamala Sudeepa , Photopoulos Cornelia , Di Matteo Anna , de Polo Anna , Storaci Alessandra Maria , Huang Ying , Giunchi Francesca , Sheridan Patricia A. , Michelotti Gregory , Nguyen Quang-De , Zhao Xin , Liu Yang , Davicioni Elai , Spratt Daniel E. , Sabbioneda Simone , Maga Giovanni , Mucci Lorelei A. , Ghigna Claudia , Marchionni Luigi , Butler Lisa M. , Ellis Leigh , Bordeleau François , Loda Massimo , Vaira Valentina , Labbé David P. , Zadra Giorgia
Published: June 2024

Abstract
Cancer cells exhibit metabolic plasticity to meet oncogene-driven dependencies while coping with nutrient availability. A better understanding of how systemic metabolism impacts the accumulation of metabolites that reprogram the tumor microenvironment (TME) and drive cancer could facilitate development of precision nutrition approaches. Using the Hi-MYC prostate cancer mouse model, we demonstrated that an obesogenic high-fat diet (HFD) rich in saturated fats accelerates the development of c-MYC–driven invasive prostate cancer through metabolic rewiring. Although c-MYC modulated key metabolic pathways, interaction with an obesogenic HFD was necessary to induce glycolysis and lactate accumulation in tumors. These metabolic changes were associated with augmented infiltration of CD206+ and PD-L1+ tumor-associated macrophages (TAM) and FOXP3+ regulatory T cells, as well as with the activation of transcriptional programs linked to disease progression and therapy resistance. Lactate itself also stimulated neoangiogenesis and prostate cancer cell migration, which were significantly reduced following treatment with the lactate dehydrogenase inhibitor FX11. In patients with prostate cancer, high saturated fat intake and increased body mass index were associated with tumor glycolytic features that promote the infiltration of M2-like TAMs. Finally, upregulation of lactate dehydrogenase, indicative of a lactagenic phenotype, was associated with a shorter time to biochemical recurrence in independent clinical cohorts. This work identifies cooperation between genetic drivers and systemic metabolism to hijack the TME and promote prostate cancer progression through oncometabolite accumulation. This sets the stage for the assessment of lactate as a prognostic biomarker and supports strategies of dietary intervention and direct lactagenesis blockade in treating advanced prostate cancer.
Significance:
Lactate accumulation driven by high-fat diet and MYC reprograms the tumor microenvironment and promotes prostate cancer progression, supporting the potential of lactate as a biomarker and therapeutic target in prostate cancer.

See related commentary by Frigo, p. 1742
Data from SPARC Stabilizes ApoE to Induce Cholesterol-Dependent Invasion and Sorafenib Resistance in Hepatocellular Carcinoma
Authors: Wan Shan , He Quan-Yao , Yang Yun , Liu Feng , Zhang Xue , Guo Xin , Niu Hui , Wang Yi , Liu Yi-Xuan , Ye Wen-Long , Li Xiu-Ming , ZhuanSun Xue-Mei , Sun Pu , He Xiao-Shun , Hu Guang , Breuhahn Kai , Zhao Hua , Wu Guo-Qiang , Wu Hua
Published: June 2024

Abstract
Dysregulation of cholesterol homeostasis is implicated in the development and progression of hepatocellular carcinoma (HCC) that is characterized by intrahepatic and early extrahepatic metastases. A better understanding of the underlying mechanisms regulating cholesterol metabolism in HCC could help identify strategies to circumvent the aggressive phenotype. Here, we found that high expression of intracellular SPARC (secreted protein acidic and rich in cysteine) was significantly associated with elevated cholesterol levels and an enhanced invasive phenotype in HCC. SPARC potentiated cholesterol accumulation in HCC cells during tumor progression by stabilizing the ApoE protein. Mechanistically, SPARC competitively bound to ApoE, impairing its interaction with the E3 ligase tripartite motif containing 21 (TRIM21) and preventing its ubiquitylation and subsequent degradation. ApoE accumulation led to cholesterol enrichment in HCC cells, stimulating PI3K–AKT signaling and inducing epithelial–mesenchymal transition (EMT). Importantly, sorafenib-resistant HCC cells were characterized by increased expression of intracellular SPARC, elevated cholesterol levels, and enhanced invasive capacity. Inhibiting SPARC expression or reducing cholesterol levels enhanced the sensitivity of HCC cells to sorafenib treatment. Together, these findings unveil interplay between SPARC and cholesterol homeostasis. Targeting SPARC-triggered cholesterol-dependent oncogenic signaling is a potential therapeutic strategy for advanced HCC.
Significance:
Intracellular SPARC boosts cholesterol availability to fuel invasion and drug resistance in hepatocellular carcinoma, providing a rational approach to improve the treatment of advanced liver cancer.
Data from Oncogenic Cell Tagging and Single-Cell Transcriptomics Reveal Cell Type–Specific and Time-Resolved Responses to Vhl Inactivation in the Kidney
Authors: Kurlekar Samvid , Lima Joanna D.C.C. , Li Ran , Lombardi Olivia , Masson Norma , Barros Ayslan B. , Pontecorvi Virginia , Mole David R. , Pugh Christopher W. , Adam Julie , Ratcliffe Peter J.
Published: June 2024

Abstract
Defining the initial events in oncogenesis and the cellular responses they entrain, even in advance of morphologic abnormality, is a fundamental challenge in understanding cancer initiation. As a paradigm to address this, we longitudinally studied the changes induced by loss of the tumor suppressor gene von Hippel Lindau (VHL), which ultimately drives clear cell renal cell carcinoma. Vhl inactivation was directly coupled to expression of a tdTomato reporter within a single allele, allowing accurate visualization of affected cells in their native context and retrieval from the kidney for single-cell RNA sequencing. This strategy uncovered cell type–specific responses to Vhl inactivation, defined a proximal tubular cell class with oncogenic potential, and revealed longer term adaptive changes in the renal epithelium and the interstitium. Oncogenic cell tagging also revealed markedly heterogeneous cellular effects including time-limited proliferation and elimination of specific cell types. Overall, this study reports an experimental strategy for understanding oncogenic processes in which cells bearing genetic alterations can be generated in their native context, marked, and analyzed over time. The observed effects of loss of Vhl in kidney cells provide insights into VHL tumor suppressor action and development of renal cell carcinoma.
Significance:
Single-cell analysis of heterogeneous and dynamic responses to Vhl inactivation in the kidney suggests that early events shape the cell type specificity of oncogenesis, providing a focus for mechanistic understanding and therapeutic targeting.
Data from Cigarette Smoking and E-cigarette Use Induce Shared DNA Methylation Changes Linked to Carcinogenesis
Authors: Herzog Chiara , Jones Allison , Evans Iona , Raut Janhavi R. , Zikan Michal , Cibula David , Wong Andrew , Brenner Hermann , Richmond Rebecca C. , Widschwendter Martin
Published: June 2024

Abstract
Tobacco use is a major modifiable risk factor for adverse health outcomes, including cancer, and elicits profound epigenetic changes thought to be associated with long-term cancer risk. While electronic cigarettes (e-cigarettes) have been advocated as harm reduction alternatives to tobacco products, recent studies have revealed potential detrimental effects, highlighting the urgent need for further research into the molecular and health impacts of e-cigarettes. Here, we applied computational deconvolution methods to dissect the cell- and tissue-specific epigenetic effects of tobacco or e-cigarette use on DNA methylation (DNAme) in over 3,500 buccal/saliva, cervical, or blood samples, spanning epithelial and immune cells at directly and indirectly exposed sites. The 535 identified smoking-related DNAme loci [cytosine-phosphate-guanine sites (CpG)] clustered into four functional groups, including detoxification or growth signaling, based on cell type and anatomic site. Loci hypermethylated in buccal epithelial cells of smokers associated with NOTCH1/RUNX3/growth factor receptor signaling also exhibited elevated methylation in cancer tissue and progressing lung carcinoma in situ lesions, and hypermethylation of these sites predicted lung cancer development in buccal samples collected from smokers up to 22 years prior to diagnosis, suggesting a potential role in driving carcinogenesis. Alarmingly, these CpGs were also hypermethylated in e-cigarette users with a limited smoking history. This study sheds light on the cell type–specific changes to the epigenetic landscape induced by smoking-related products.
Significance:
The use of both cigarettes and e-cigarettes elicits cell- and exposure-specific epigenetic effects that are predictive of carcinogenesis, suggesting caution when broadly recommending e-cigarettes as aids for smoking cessation.
Comprehensive Target Engagement by the EZH2 Inhibitor Tulmimetostat Allows for Targeting of ARID1A Mutant Cancers
Authors: Keller Patricia J. , Adams Elizabeth J. , Wu Rentian , Côté Alexandre , Arora Shilpi , Cantone Nico , Meyer Rosana , Mertz Jennifer A. , Gehling Victor , Cui Jike , Stuckey Jacob I. , Khanna Avinash , Zhao Feng , Chen Zehua , Yu Ziyang , Cummings Richard T. , Taimi Mohammed , Lakhani Nehal J. , Rasco Drew , Gutierrez Martin , Duska Linda , Devitt Michael , Rippley Ronda , Levell Julian , Truong Jennifer , Wang Jing , Sun Kaiming , Trojer Patrick
Published: June 2024

Recurrent somatic mutations in the BRG1/BRM-associated factor (BAF) chromatin remodeling complex subunit ARID1A occur frequently in advanced urothelial, endometrial, and ovarian clear cell carcinomas, creating an alternative chromatin state that may be exploited therapeutically. The histone methyltransferase EZH2 has been previously identified as targetable vulnerability in the context of ARID1A mutations. In this study, we describe the discovery of tulmimetostat, an orally available, clinical stage EZH2 inhibitor, and it elucidates the aspects of its application potential in ARID1A mutant tumors. Tulmimetostat administration achieved efficacy in multiple ARID1A mutant bladder, ovarian, and endometrial tumor models and improved cisplatin response in chemotherapy-resistant models. Consistent with its comprehensive and durable level of target coverage, tulmimetostat demonstrated greater efficacy than other PRC2-targeted inhibitors at comparable or lower exposures in a bladder cancer xenograft mouse model. Tulmimetostat mediated extensive changes in gene expression, in addition to a profound reduction in global H3K27me3 levels in tumors. Phase I clinical pharmacokinetic and pharmacodynamic data indicated that tulmimetostat exhibits durable exposure and profound target engagement. Importantly, a tulmimetostat controlled gene expression signature identified in whole blood from a cohort of 32 patients with cancer correlated with tulmimetostat exposure, representing a pharmacodynamic marker for the assessment of target coverage for PRC2-targeted agents in the clinic. Collectively, these data suggest that tulmimetostat has the potential to achieve clinical benefit in solid tumors as a monotherapy but also in combination with chemotherapeutic agents, and may be beneficial in various indications with recurrent ARID1A mutations.

Significance: The EZH2 inhibitor tulmimetostat achieves comprehensive target inhibition in ARID1A mutant solid tumor models and cancer patients that can be assessed with a pharmacodynamic gene signature in peripheral blood.
Supplementary Figure 6 from Patient-Derived Tumor Xenograft Study with CDK4/6 Inhibitor Plus AKT Inhibitor for the Management of Metastatic Castration-Resistant Prostate Cancer
Authors: Kase Adam M. , Gleba Justyna , Miller James L. , Miller Erin , Petit Joachim , Barrett Michael T. , Zhou Yumei , Parent Ephraim E. , Cai Hancheng , Knight Joshua A. , Orme Jacob , Reynolds Jordan , Durham William F. , Metz Thomas M. , Meurice Nathalie , Edenfield Brandy , Alasonyalilar Demirer Aylin , Bilgili Ahmet , Hickman Peyton G. , Pawlush Matthew L. , Marlow Laura , Wickland Daniel P. , Tan Winston , Copland John A.
Published: June 2024

Supplementary Figure 6
Supplementary Figure S7 from Discovery of a Long Half-Life AURKA Inhibitor to Treat MYC-Amplified Solid Tumors as a Monotherapy and in Combination with Everolimus
Authors: Chang Chun-Ping , Yeh Teng-Kuang , Chen Chiung-Tong , Wang Wan-Ping , Chen Yen-Ting , Tsai Chia-Hua , Chen Yan-Fu , Ke Yi-Yu , Wang Jing-Ya , Chen Ching-Ping , Hsieh Tsung-Chih , Wu Mine-Hsine , Huang Chen-Lung , Chen Ya-Ping , Zhuang Hong , Chi Ya-Hui
Published: June 2024

Supplementary Figure S7. Kinase profiling of 6K465 and alisertib. Analyzing kinase profiles of 6K465 (tested at 0.1 uM) and alisertib (tested at 1.0 uM) reveals notable distinctions. The kinase profiling data for alisertib was sourced from the publication by Manfredi et al. (47); top 50 hit kinases for each of the compound are presented. Percent (%) inhibition values represent the mean from two replicate experiments, with color-coding indicating the efficacy of inhibition. NA, not available.