bluuebunny/crossref_metadata_2025 huggingface dataset:
Supplementary Table 5 from ANO1 Reprograms Cholesterol Metabolism and the Tumor Microenvironment to Promote Cancer Metastasis
Authors: Deng Chun-Miao , Zhang Guo-Geng , Liu Qin-Wen , Xu Jiao-Jiao , Liu Zhi-Chao , Yang Jing , Xu Tao-Yang , Li Zhi-Gang , Zhang Fan , Li Bin
Published: June 2023

Supplementary Table 5 shows Correlation between ANO1 expression levels and clinicopathological parameters in 100 cases of esophageal cancer
Supplementary Table 4 from ANO1 Reprograms Cholesterol Metabolism and the Tumor Microenvironment to Promote Cancer Metastasis
Authors: Deng Chun-Miao , Zhang Guo-Geng , Liu Qin-Wen , Xu Jiao-Jiao , Liu Zhi-Chao , Yang Jing , Xu Tao-Yang , Li Zhi-Gang , Zhang Fan , Li Bin
Published: June 2023

Supplementary Table 4 shows DEGs between highly metastasis ESCC sub cell line KYSE150-Luc-LM3 and the parental cell line
Supplementary Table 3 from ANO1 Reprograms Cholesterol Metabolism and the Tumor Microenvironment to Promote Cancer Metastasis
Authors: Deng Chun-Miao , Zhang Guo-Geng , Liu Qin-Wen , Xu Jiao-Jiao , Liu Zhi-Chao , Yang Jing , Xu Tao-Yang , Li Zhi-Gang , Zhang Fan , Li Bin
Published: June 2023

Supplementary Table 3 shows DEGs between ESCC primary tumors and matched lymph node metastatic tumors
Supplementary Table 2 from ANO1 Reprograms Cholesterol Metabolism and the Tumor Microenvironment to Promote Cancer Metastasis
Authors: Deng Chun-Miao , Zhang Guo-Geng , Liu Qin-Wen , Xu Jiao-Jiao , Liu Zhi-Chao , Yang Jing , Xu Tao-Yang , Li Zhi-Gang , Zhang Fan , Li Bin
Published: June 2023

Supplementary Table 2 shows qRT-PCR primers
Supplementary Table 1 from ANO1 Reprograms Cholesterol Metabolism and the Tumor Microenvironment to Promote Cancer Metastasis
Authors: Deng Chun-Miao , Zhang Guo-Geng , Liu Qin-Wen , Xu Jiao-Jiao , Liu Zhi-Chao , Yang Jing , Xu Tao-Yang , Li Zhi-Gang , Zhang Fan , Li Bin
Published: June 2023

Supplementary Table 1 shows primary antibody list
Supplementary Methods from ANO1 Reprograms Cholesterol Metabolism and the Tumor Microenvironment to Promote Cancer Metastasis
Authors: Deng Chun-Miao , Zhang Guo-Geng , Liu Qin-Wen , Xu Jiao-Jiao , Liu Zhi-Chao , Yang Jing , Xu Tao-Yang , Li Zhi-Gang , Zhang Fan , Li Bin
Published: June 2023

Supplementary Methods shows supplementary Materials and Methods
Supplementary Tables from Large B-cell Lymphomas of Immune-Privileged Sites Relapse via Parallel Clonal Evolution from a Common Progenitor B Cell
Authors: Los-de Vries G. Tjitske , Stathi Phylicia , Rutkens Ryanne , Hijmering Nathalie J. , Luijks Jeroen A.C.W. , Groenen Patricia J.T.A. , de Jong Daphne , Ylstra Bauke , Roemer Margaretha G.M.
Published: June 2023

Supplementary Tables
Figure S1 from DAB2IP Is a Bifunctional Tumor Suppressor That Regulates Wild-Type RAS and Inflammatory Cascades in KRAS Mutant Colon Cancer
Authors: Miller Abigail L. , Perurena Naiara , Gardner Alycia , Hinoue Toshinori , Loi Patrick , Laird Peter W. , Cichowski Karen
Published: June 2023

An immunoblot showing anti-apoptotic NF-kB target genes in shCNT and shDAB2IP HCT116 cells.
Supplementary Information from Dual Impact of IGF2 on Alveolar Stem Cell Function during Tobacco-Induced Injury Repair and Development of Pulmonary Emphysema and Cancer
Authors: Boo Hye-Jin , Min Hye-Young , Park Choon-Sik , Park Jong-Sook , Jeong Ji Yun , Lee Shin Yup , Kim Woo-Young , Lee Jae-Won , Oh Sei-Ryang , Park Rang-Woon , Lee Ho-Young
Published: June 2023

Supplementary Methods, Tables, and Figures
Data from DAB2IP Is a Bifunctional Tumor Suppressor That Regulates Wild-Type RAS and Inflammatory Cascades in KRAS Mutant Colon Cancer
Authors: Miller Abigail L. , Perurena Naiara , Gardner Alycia , Hinoue Toshinori , Loi Patrick , Laird Peter W. , Cichowski Karen
Published: June 2023

Abstract
The DAB2IP tumor suppressor encodes a RAS GTPase-activating protein. Accordingly, DAB2IP has been shown to be mutated or suppressed in tumor types that typically lack RAS mutations. However, here we report that DAB2IP is mutated or selectively silenced in the vast majority of KRAS and BRAF mutant colorectal cancers. In this setting, DAB2IP loss promoted tumor development by activating wild-type H- and N-RAS proteins, which was surprisingly required to achieve robust activation of RAS effector pathways in KRAS-mutant tumors. DAB2IP loss also triggered production of inflammatory mediators and the recruitment of protumorigenic macrophages in vivo. Importantly, tumor growth was suppressed by depleting macrophages or inhibiting cytokine/inflammatory mediator expression with a JAK/TBK1 inhibitor. In human tumors, DAB2IP was lost at early stages of tumor development, and its depletion was associated with an enrichment of macrophage and inflammatory signatures. Together, these findings demonstrate that DAB2IP restrains the activation of the RAS pathway and inflammatory cascades in the colon and that its loss represents a common and unappreciated mechanism for amplifying these two critical oncogenic signals in colorectal cancer.
Significance:
DAB2IP is lost in early-stage tumors, which amplifies RAS signaling, triggers inflammatory mediators, and recruits macrophages in KRAS-mutant colon cancers.
Data from Dual Impact of IGF2 on Alveolar Stem Cell Function during Tobacco-Induced Injury Repair and Development of Pulmonary Emphysema and Cancer
Authors: Boo Hye-Jin , Min Hye-Young , Park Choon-Sik , Park Jong-Sook , Jeong Ji Yun , Lee Shin Yup , Kim Woo-Young , Lee Jae-Won , Oh Sei-Ryang , Park Rang-Woon , Lee Ho-Young
Published: June 2023

Abstract
Pulmonary emphysema is a destructive inflammatory disease primarily caused by cigarette smoking (CS). Recovery from CS-induced injury requires proper stem cell (SC) activities with a tightly controlled balance of proliferation and differentiation. Here we show that acute alveolar injury induced by two representative tobacco carcinogens, 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone and benzo[a]pyrene (N/B), increased IGF2 expression in alveolar type 2 (AT2) cells to promote their SC function and facilitate alveolar regeneration. Autocrine IGF2 signaling upregulated Wnt genes, particularly Wnt3, to stimulate AT2 proliferation and alveolar barrier regeneration after N/B-induced acute injury. In contrast, repetitive N/B exposure provoked sustained IGF2-Wnt signaling through DNMT3A-mediated epigenetic control of IGF2 expression, causing a proliferation/differentiation imbalance in AT2s and development of emphysema and cancer. Hypermethylation of the IGF2 promoter and overexpression of DNMT3A, IGF2, and the Wnt target gene AXIN2 were seen in the lungs of patients with CS-associated emphysema and cancer. Pharmacologic or genetic approaches targeting IGF2-Wnt signaling or DNMT prevented the development of N/B-induced pulmonary diseases. These findings support dual roles of AT2 cells, which can either stimulate alveolar repair or promote emphysema and cancer depending on IGF2 expression levels.
Significance:
IGF2-Wnt signaling plays a key role in AT2-mediated alveolar repair after cigarette smoking–induced injury but also drives pathogenesis of pulmonary emphysema and cancer when hyperactivated.
Data from Chi3l1 is a modulator of glioma stem cell states and a therapeutic target in glioblastoma
Authors: Guetta-Terrier Charlotte , Karambizi David , Akosman Bedia , Zepecki John P. , Chen Jia-Shu , Kamle Suchitra , Fajardo J. Eduardo , Fiser Andras , Singh Ritambhara , Toms Steven A. , Lee Chun Geun , Elias Jack A. , Tapinos Nikos
Published: June 2023

Abstract
Chi3l1 (chitinase 3-like 1) is a secreted protein that is highly expressed in glioblastoma. Here, we show that Chi3l1 alters the state of glioma stem cells (GSCs) to support tumor growth. Exposure of patient-derived GSCs to Chi3l1 reduced the frequency of CD133+SOX2+ cells and increased the CD44+Chi3l1+ cells. Chi3l1 bound to CD44 and induced phosphorylation and nuclear translocation of β-catenin, Akt and STAT3. Single cell RNA-seq and RNA velocity following incubation of GSCs with Chi3l1 showed significant changes in GSC state dynamics driving GSCs towards a mesenchymal expression profile and reducing transition probabilities towards terminal cellular states. ATAC-seq revealed that Chi3l1 increases accessibility of promoters containing a MAZ transcription factor footprint. Inhibition of MAZ downregulated a set of genes with high expression in cellular clusters that exhibit significant cell state transitions after treatment with Chi3l1, and MAZ deficiency rescued the Chi3l-induced increase of GSC self-renewal. Finally, targeting Chi3l1 in vivo with a blocking antibody inhibited tumor growth and increased the probability of survival. Overall, this work suggests that Chi3l1 interacts with CD44 on the surface of glioma stem cells to induce Akt/β-catenin signaling and MAZ transcriptional activity, which in turn upregulates CD44 expression in a pro-mesenchymal feed-forward loop. The role of Chi3l1 in regulating cellular plasticity confers a targetable vulnerability to glioblastoma.
Data from Proteomic profiling of extracellular matrix components from patient metastases identifies consistently elevated proteins for developing nanobodies that target primary tumors and metastases
Authors: Jailkhani Noor , Clauser Karl R. , Mak Howard H. , Rickelt Steffen , Tian Chenxi , Whittaker Charles A. , Tanabe Kenneth K. , Purdy Stephen R. , Carr Steven A. , Hynes Richard O.
Published: June 2023

Abstract
Metastases are hard to detect and treat, and they cause most cancer-related deaths. The relative lack of therapies targeting metastases represents a major unmet clinical need. The extracellular matrix (ECM) forms a major component of the tumor microenvironment in both primary and metastatic tumors, and certain ECM proteins can be selectively and abundantly expressed in tumors. Nanobodies against ECM proteins that show selective abundance in metastases have the potential to be used as vehicles for delivery of imaging and therapeutic cargoes. Here, we describe a strategy to develop phage-display libraries of nanobodies against ECM proteins expressed in human metastases, using as immunogens entire ECM-enriched preparations from triple-negative breast cancer (TNBC) and colorectal carcinoma (CRC) metastases to different organs as immunogens. In parallel, LC-MS/MS-based proteomics were used to define a metastasis-associated ECM signature shared by metastases from TNBC and CRC, and this conserved set of ECM proteins was selectively elevated in other tumors. As proof of concept, selective and high-affinity nanobodies were isolated against an example protein from this signature, Tenascin-C (TNC), known to be abundant in many tumor types and to play a role in metastasis. TNC was abundantly expressed in patient metastases and widely expressed across diverse metastatic sites originating from several primary tumor types. Immuno-PET/CT showed that anti-TNC nanobodies bind TNBC tumors and metastases with excellent specificity. We propose that such generic nanobodies against tumors and metastases are promising cancer-agnostic tools for delivery of therapeutics to tumor and metastatic ECM.
Data from Ubiquitin ligases Siah1a/2 control alveolar macrophage functions to limit carcinogen-induced lung adenocarcinoma
Authors: Scortegagna Marzia , Du Yuanning , Bradley Linda M. , Wang Kun , Molinolo Alfredo , Ruppin Eytan , Murad Rabi , Ronai Ze'ev A.
Published: June 2023

Abstract
Cellular components of the tumor microenvironment, including myeloid cells, play important roles in the progression of lung adenocarcinoma (LUAD) and its response to therapy. Here, we characterize the function of the ubiquitin ligases Siah1a/2 in regulating the differentiation and activity of alveolar macrophages (AMs) and assess the implication of Siah1a/2 control of AMs for carcinogen-induced LUAD. Macrophage-specific genetic ablation of Siah1a/2 promoted accumulation of AMs with an immature phenotype and increased expression of pro-tumorigenic and pro-inflammatory Stat3 and β-catenin gene signatures. Administration of urethane to wild-type mice promoted enrichment of immature-like AMs and lung tumor development, which was enhanced by macrophage-specific Siah1a/2 ablation. The pro-fibrotic gene signature seen in Siah1a/2-ablated immature-like macrophages was associated with increased tumor infiltration of CD14+ myeloid cells and poorer survival of LUAD patients. Single-cell RNA-seq confirmed the presence of a cluster of immature-like AMs expressing a pro-fibrotic signature in lungs of LUAD patients, a signature enhanced in smokers. These findings identify Siah1a/2 in alveolar macrophages as gatekeepers of lung cancer development.
Supplementary Fig. 2 from Monitoring Sarcoma Response to Immune Checkpoint Inhibition and Local Cryotherapy with Circulating Tumor DNA Analysis
Authors: Bui Nam Q. , Nemat-Gorgani Neda , Subramanian Ajay , Torres Ileana A. , Lohman Marta , Sears Timothy J. , van de Rijn Matt , Charville Gregory W. , Becker Hans-Christoph , Wang David S. , Hwang Gloria L. , Ganjoo Kristen N. , Moding Everett J.
Published: June 2023

Supplementary Fig. 2
Supplementary Fig. 1 from Monitoring Sarcoma Response to Immune Checkpoint Inhibition and Local Cryotherapy with Circulating Tumor DNA Analysis
Authors: Bui Nam Q. , Nemat-Gorgani Neda , Subramanian Ajay , Torres Ileana A. , Lohman Marta , Sears Timothy J. , van de Rijn Matt , Charville Gregory W. , Becker Hans-Christoph , Wang David S. , Hwang Gloria L. , Ganjoo Kristen N. , Moding Everett J.
Published: June 2023

Supplementary Fig. 1
Suppl Table S2 from Efficacy of Nivolumab in Pediatric Cancers with High Mutation Burden and Mismatch Repair Deficiency
Authors: Das Anirban , Tabori Uri , Sambira Nahum Lauren C. , Collins Natalie B. , Deyell Rebecca , Dvir Rina , Faure-Conter Cecile , Hassall Timothy E. , Minturn Jane E. , Edwards Melissa , Brookes Elissa , Bianchi Vanessa , Levine Adrian , Stone Simone C. , Sudhaman Sumedha , Sanchez Ramirez Santiago , Ercan Ayse B. , Stengs Lucie , Chung Jill , Negm Logine , Getz Gad , Maruvka Yosef E. , Ertl-Wagner Birgit , Ohashi Pamela S. , Pugh Trevor , Hawkins Cynthia , Bouffet Eric , Morgenstern Daniel A.
Published: June 2023

Results of time-dependent co-variate and landmark analyses at time-points 3 and 6 months of the trial
Data from Efficacy of nivolumab in pediatric cancers with high mutation burden and mismatch-repair deficiency
Authors: Das Anirban , Tabori Uri , Sambira Nahum Lauren C. , Collins Natalie B. , Deyell Rebecca , Dvir Rina , Faure-Conter Cecile , Hassall Timothy E. , Minturn Jane E. , Edwards Melissa , Brookes Elissa , Bianchi Vanessa , Levine Adrian , Stone Simone C. , Sudhaman Sumedha , Sanchez-Ramirez Santiago , Ercan Ayse B. , Stengs Lucie , Chung Jiil , Negm Logine , Getz Gad , Maruvka Yosef E. , Ertl-Wagner Birgit , Ohashi Pamela S. , Pugh Trevor , Hawkins Cynthia , Bouffet Eric , Morgenstern Daniel A.
Published: June 2023

Abstract
Purpose: Checkpoint-inhibitors have limited efficacy for children with unselected solid and brain tumors. We report the first prospective pediatric trial (NCT02992964) using nivolumab exclusively for refractory non-hematological cancers harboring tumor mutation burden (TMB) ≥5 mutations/megabase (mut/Mb) and/or mismatch-repair deficiency (MMRD). Patients and methods: Twenty patients were screened, and ten ultimately included in the response cohort of whom nine had TMB >10mut/Mb (three initially eligible based on MMRD) and one patient had TMB between 5-10 mut/Mb. Results: Delayed immune responses contributed to best overall response of 50%, improving on initial objective responses (20%) and leading to 2-year overall survival (OS) of 50% (95% CI; 27, 93). Four children, including three with refractory malignant gliomas are in complete remission at a median follow-up of 37-months (range: 32.4-60), culminating in 2-year OS of 43% (95% CI; 18.2, 100). Biomarker analyses confirmed benefit in children with germline MMRD, microsatellite instability, higher activated and lower regulatory circulating T-cells. Stochastic mutation accumulation driven by underlying germline MMRD impacted the tumor microenvironment, contributing to delayed responses. No benefit was observed in the single patient with a MMR-proficient tumour and TMB 7.4 mut/Mb. Conclusions: Nivolumab resulted in durable responses and prolonged survival for the first time in a pediatric trial of refractory hypermutated cancers including malignant gliomas. Novel biomarkers identified here need to be translated rapidly to clinical care to identify children who can benefit from checkpoint-inhibitors, including for upfront management of their cancers.
Data from Monitoring sarcoma response to immune checkpoint inhibition and local cryotherapy with circulating tumor DNA analysis
Authors: Bui Nam Q. , Nemat-Gorgani Neda , Subramanian Ajay , Torres Ileana A. , Lohman Marta , Sears Timothy J. , van de Rijn Matt , Charville Gregory W. , Becker Hans-Christoph , Wang David S. , Hwang Gloria L. , Ganjoo Kristen N. , Moding Everett J.
Published: June 2023

Abstract
Purpose: Immune checkpoint inhibition has led to promising responses in soft tissue sarcomas (STSs), but the majority of patients do not respond and biomarkers of response will be crucial. Local ablative therapies may augment systemic responses to immunotherapy. We evaluated circulating tumor DNA (ctDNA) as a biomarker of response in patients treated on a trial combining immunotherapy with local cryotherapy for advanced STSs. Experimental Design: We enrolled 30 patients with unresectable or metastatic STS to a phase 2 clinical trial. Patients received ipilimumab and nivolumab for 4 doses followed by nivolumab alone with cryoablation performed between cycles 1 and 2. The primary endpoint was objective response rate (ORR) by 14 weeks. Personalized ctDNA analysis using bespoke panels was performed on blood samples collected prior to each immunotherapy cycle. Results: ctDNA was detected in at least one sample for 96% of patients. Pre-treatment ctDNA allele fraction was negatively associated with treatment response, progression-free survival (PFS), and overall survival (OS). ctDNA increased in 90% of patients from pre-treatment to post-cryotherapy, and patients with a subsequent decrease in ctDNA or undetectable ctDNA after cryotherapy had significantly better PFS. Of the 27 evaluable patients, the ORR was 4% by RECIST and 11% by irRECIST. Median PFS and OS were 2.7 and 12.0 months, respectively. No new safety signals were observed. Conclusions: ctDNA represents a promising biomarker for monitoring response to treatment in advanced STS, warranting future prospective studies. Combining cryotherapy and immune checkpoint inhibitors did not increase the response rate of STSs to immunotherapy.
Table S7 from A Transcriptome-Based Precision Oncology Platform for Patient–Therapy Alignment in a Diverse Set of Treatment-Resistant Malignancies
Authors: Mundi Prabhjot S. , Dela Cruz Filemon S. , Grunn Adina , Diolaiti Daniel , Mauguen Audrey , Rainey Allison R. , Guillan Kristina , Siddiquee Armaan , You Daoqi , Realubit Ronald , Karan Charles , Ortiz Michael V. , Douglass Eugene F. , Accordino Melissa , Mistretta Suzanne , Brogan Frances , Bruce Jeffrey N. , Caescu Cristina I. , Carvajal Richard D. , Crew Katherine D. , Decastro Guarionex , Heaney Mark , Henick Brian S. , Hershman Dawn L. , Hou June Y. , Iwamoto Fabio M. , Jurcic Joseph G. , Kiran Ravi P. , Kluger Michael D. , Kreisl Teri , Lamanna Nicole , Lassman Andrew B. , Lim Emerson A. , Manji Gulam A. , McKhann Guy M. , McKiernan James M. , Neugut Alfred I. , Olive Kenneth P. , Rosenblat Todd , Schwartz Gary K. , Shu Catherine A. , Sisti Michael B. , Tergas Ana , Vattakalam Reena M. , Welch Mary , Wenske Sven , Wright Jason D. , Canoll Peter , Hibshoosh Hanina , Kalinsky Kevin , Aburi Mahalaxmi , Sims Peter A. , Alvarez Mariano J. , Kung Andrew L. , Califano Andrea
Published: June 2023

Current list of cancer cell lines with available drug perturbation RNASeq profiles, which together comprise the PanACEA resource.
Table S6 from A Transcriptome-Based Precision Oncology Platform for Patient–Therapy Alignment in a Diverse Set of Treatment-Resistant Malignancies
Authors: Mundi Prabhjot S. , Dela Cruz Filemon S. , Grunn Adina , Diolaiti Daniel , Mauguen Audrey , Rainey Allison R. , Guillan Kristina , Siddiquee Armaan , You Daoqi , Realubit Ronald , Karan Charles , Ortiz Michael V. , Douglass Eugene F. , Accordino Melissa , Mistretta Suzanne , Brogan Frances , Bruce Jeffrey N. , Caescu Cristina I. , Carvajal Richard D. , Crew Katherine D. , Decastro Guarionex , Heaney Mark , Henick Brian S. , Hershman Dawn L. , Hou June Y. , Iwamoto Fabio M. , Jurcic Joseph G. , Kiran Ravi P. , Kluger Michael D. , Kreisl Teri , Lamanna Nicole , Lassman Andrew B. , Lim Emerson A. , Manji Gulam A. , McKhann Guy M. , McKiernan James M. , Neugut Alfred I. , Olive Kenneth P. , Rosenblat Todd , Schwartz Gary K. , Shu Catherine A. , Sisti Michael B. , Tergas Ana , Vattakalam Reena M. , Welch Mary , Wenske Sven , Wright Jason D. , Canoll Peter , Hibshoosh Hanina , Kalinsky Kevin , Aburi Mahalaxmi , Sims Peter A. , Alvarez Mariano J. , Kung Andrew L. , Califano Andrea
Published: June 2023

Detailed summary of therapeutic response at end-of-study time point, organized by study group—OncoTreat, OncoTarget, or Negative control—and then stratified by each individual drug arm. The study was underpowered for statistical analyses of therapeutic response in individual drug arms.
Table S5 from A Transcriptome-Based Precision Oncology Platform for Patient–Therapy Alignment in a Diverse Set of Treatment-Resistant Malignancies
Authors: Mundi Prabhjot S. , Dela Cruz Filemon S. , Grunn Adina , Diolaiti Daniel , Mauguen Audrey , Rainey Allison R. , Guillan Kristina , Siddiquee Armaan , You Daoqi , Realubit Ronald , Karan Charles , Ortiz Michael V. , Douglass Eugene F. , Accordino Melissa , Mistretta Suzanne , Brogan Frances , Bruce Jeffrey N. , Caescu Cristina I. , Carvajal Richard D. , Crew Katherine D. , Decastro Guarionex , Heaney Mark , Henick Brian S. , Hershman Dawn L. , Hou June Y. , Iwamoto Fabio M. , Jurcic Joseph G. , Kiran Ravi P. , Kluger Michael D. , Kreisl Teri , Lamanna Nicole , Lassman Andrew B. , Lim Emerson A. , Manji Gulam A. , McKhann Guy M. , McKiernan James M. , Neugut Alfred I. , Olive Kenneth P. , Rosenblat Todd , Schwartz Gary K. , Shu Catherine A. , Sisti Michael B. , Tergas Ana , Vattakalam Reena M. , Welch Mary , Wenske Sven , Wright Jason D. , Canoll Peter , Hibshoosh Hanina , Kalinsky Kevin , Aburi Mahalaxmi , Sims Peter A. , Alvarez Mariano J. , Kung Andrew L. , Califano Andrea
Published: June 2023

Comprehensive list of clinically relevant drugs screened in cell lines (not all were available at time of study). The list is divided into three sections, including one with FDA approved antineoplastics, one with experimental antineoplastics in clinical trials, and one with non-antineoplastics and tool compounds selectively screened when demonstrating an EC50 < 2μM.
Table S4 from A Transcriptome-Based Precision Oncology Platform for Patient–Therapy Alignment in a Diverse Set of Treatment-Resistant Malignancies
Authors: Mundi Prabhjot S. , Dela Cruz Filemon S. , Grunn Adina , Diolaiti Daniel , Mauguen Audrey , Rainey Allison R. , Guillan Kristina , Siddiquee Armaan , You Daoqi , Realubit Ronald , Karan Charles , Ortiz Michael V. , Douglass Eugene F. , Accordino Melissa , Mistretta Suzanne , Brogan Frances , Bruce Jeffrey N. , Caescu Cristina I. , Carvajal Richard D. , Crew Katherine D. , Decastro Guarionex , Heaney Mark , Henick Brian S. , Hershman Dawn L. , Hou June Y. , Iwamoto Fabio M. , Jurcic Joseph G. , Kiran Ravi P. , Kluger Michael D. , Kreisl Teri , Lamanna Nicole , Lassman Andrew B. , Lim Emerson A. , Manji Gulam A. , McKhann Guy M. , McKiernan James M. , Neugut Alfred I. , Olive Kenneth P. , Rosenblat Todd , Schwartz Gary K. , Shu Catherine A. , Sisti Michael B. , Tergas Ana , Vattakalam Reena M. , Welch Mary , Wenske Sven , Wright Jason D. , Canoll Peter , Hibshoosh Hanina , Kalinsky Kevin , Aburi Mahalaxmi , Sims Peter A. , Alvarez Mariano J. , Kung Andrew L. , Califano Andrea
Published: June 2023

Curated list of proteins with high-affinity inhibitor drugs for OncoTarget analysis.
Table S2 from A Transcriptome-Based Precision Oncology Platform for Patient–Therapy Alignment in a Diverse Set of Treatment-Resistant Malignancies
Authors: Mundi Prabhjot S. , Dela Cruz Filemon S. , Grunn Adina , Diolaiti Daniel , Mauguen Audrey , Rainey Allison R. , Guillan Kristina , Siddiquee Armaan , You Daoqi , Realubit Ronald , Karan Charles , Ortiz Michael V. , Douglass Eugene F. , Accordino Melissa , Mistretta Suzanne , Brogan Frances , Bruce Jeffrey N. , Caescu Cristina I. , Carvajal Richard D. , Crew Katherine D. , Decastro Guarionex , Heaney Mark , Henick Brian S. , Hershman Dawn L. , Hou June Y. , Iwamoto Fabio M. , Jurcic Joseph G. , Kiran Ravi P. , Kluger Michael D. , Kreisl Teri , Lamanna Nicole , Lassman Andrew B. , Lim Emerson A. , Manji Gulam A. , McKhann Guy M. , McKiernan James M. , Neugut Alfred I. , Olive Kenneth P. , Rosenblat Todd , Schwartz Gary K. , Shu Catherine A. , Sisti Michael B. , Tergas Ana , Vattakalam Reena M. , Welch Mary , Wenske Sven , Wright Jason D. , Canoll Peter , Hibshoosh Hanina , Kalinsky Kevin , Aburi Mahalaxmi , Sims Peter A. , Alvarez Mariano J. , Kung Andrew L. , Califano Andrea
Published: June 2023

Prioritized drugs, prediction basis, and dosing schedule for PDX therapeutic study.
Supplementary Figures Part 2 from Analysis of Donor Pancreata Defines the Transcriptomic Signature and Microenvironment of Early Neoplastic Lesions
Authors: Carpenter Eileen S. , Elhossiny Ahmed M. , Kadiyala Padma , Li Jay , McGue Jake , Griffith Brian D. , Zhang Yaqing , Edwards Jacob , Nelson Sarah , Lima Fatima , Donahue Katelyn L. , Du Wenting , Bischoff Allison C. , Alomari Danyah , Watkoske Hannah R. , Mattea Michael , The Stephanie , Espinoza Carlos E. , Barrett Meredith , Sonnenday Christopher J. , Olden Nicholas , Chen Chin-Tung , Peterson Nicole , Gunchick Valerie , Sahai Vaibhav , Rao Arvind , Bednar Filip , Shi Jiaqi , Frankel Timothy L. , Pasca di Magliano Marina
Published: June 2023

Supplementary Figures 11-14 and associated legends.
Supplementary Figures S1-S6 from A Transcriptome-Based Precision Oncology Platform for Patient–Therapy Alignment in a Diverse Set of Treatment-Resistant Malignancies
Authors: Mundi Prabhjot S. , Dela Cruz Filemon S. , Grunn Adina , Diolaiti Daniel , Mauguen Audrey , Rainey Allison R. , Guillan Kristina , Siddiquee Armaan , You Daoqi , Realubit Ronald , Karan Charles , Ortiz Michael V. , Douglass Eugene F. , Accordino Melissa , Mistretta Suzanne , Brogan Frances , Bruce Jeffrey N. , Caescu Cristina I. , Carvajal Richard D. , Crew Katherine D. , Decastro Guarionex , Heaney Mark , Henick Brian S. , Hershman Dawn L. , Hou June Y. , Iwamoto Fabio M. , Jurcic Joseph G. , Kiran Ravi P. , Kluger Michael D. , Kreisl Teri , Lamanna Nicole , Lassman Andrew B. , Lim Emerson A. , Manji Gulam A. , McKhann Guy M. , McKiernan James M. , Neugut Alfred I. , Olive Kenneth P. , Rosenblat Todd , Schwartz Gary K. , Shu Catherine A. , Sisti Michael B. , Tergas Ana , Vattakalam Reena M. , Welch Mary , Wenske Sven , Wright Jason D. , Canoll Peter , Hibshoosh Hanina , Kalinsky Kevin , Aburi Mahalaxmi , Sims Peter A. , Alvarez Mariano J. , Kung Andrew L. , Califano Andrea
Published: June 2023

Supplementary Figures S1-S6 and figure legends.
Key Resources Table from A Transcriptome-Based Precision Oncology Platform for Patient–Therapy Alignment in a Diverse Set of Treatment-Resistant Malignancies
Authors: Mundi Prabhjot S. , Dela Cruz Filemon S. , Grunn Adina , Diolaiti Daniel , Mauguen Audrey , Rainey Allison R. , Guillan Kristina , Siddiquee Armaan , You Daoqi , Realubit Ronald , Karan Charles , Ortiz Michael V. , Douglass Eugene F. , Accordino Melissa , Mistretta Suzanne , Brogan Frances , Bruce Jeffrey N. , Caescu Cristina I. , Carvajal Richard D. , Crew Katherine D. , Decastro Guarionex , Heaney Mark , Henick Brian S. , Hershman Dawn L. , Hou June Y. , Iwamoto Fabio M. , Jurcic Joseph G. , Kiran Ravi P. , Kluger Michael D. , Kreisl Teri , Lamanna Nicole , Lassman Andrew B. , Lim Emerson A. , Manji Gulam A. , McKhann Guy M. , McKiernan James M. , Neugut Alfred I. , Olive Kenneth P. , Rosenblat Todd , Schwartz Gary K. , Shu Catherine A. , Sisti Michael B. , Tergas Ana , Vattakalam Reena M. , Welch Mary , Wenske Sven , Wright Jason D. , Canoll Peter , Hibshoosh Hanina , Kalinsky Kevin , Aburi Mahalaxmi , Sims Peter A. , Alvarez Mariano J. , Kung Andrew L. , Califano Andrea
Published: June 2023

Key Resources Table
Supplementary Table S1 from p38MAPKα Stromal Reprogramming Sensitizes Metastatic Breast Cancer to Immunotherapy
Authors: Faget Douglas V. , Luo Xianmin , Inkman Matthew J. , Ren Qihao , Su Xinming , Ding Kai , Waters Michael R. , Raut Ganesh Kumar , Pandey Gaurav , Dodhiawala Paarth B. , Ramalho-Oliveira Renata , Ye Jiayu , Cole Thomas , Murali Bhavna , Zheleznyak Alexander , Shokeen Monica , Weiss Kurt R. , Monahan Joseph B. , DeSelm Carl J. , Lee Adrian V. , Oesterreich Steffi , Weilbaecher Katherine N. , Zhang Jin , DeNardo David G. , Stewart Sheila A.
Published: June 2023

Table containing all of our reagents
Supplementary Table S4 from Single-Cell RNA Sequencing Unifies Developmental Programs of Esophageal and Gastric Intestinal Metaplasia
Authors: Nowicki-Osuch Karol , Zhuang Lizhe , Cheung Tik Shing , Black Emily L. , Masqué-Soler Neus , Devonshire Ginny , Redmond Aisling M. , Freeman Adam , di Pietro Massimilliano , Pilonis Nastazja , Januszewicz Wladyslaw , O'Donovan Maria , Tavaré Simon , Shields Jacqueline D. , Fitzgerald Rebecca C.
Published: June 2023

This table contains results of pairwise differential expression analysis between E-GM and gastric tissues and Atrophic gastritis and gastric tissue.
Supplementary Figures S1-S10 from p38MAPKα Stromal Reprogramming Sensitizes Metastatic Breast Cancer to Immunotherapy
Authors: Faget Douglas V. , Luo Xianmin , Inkman Matthew J. , Ren Qihao , Su Xinming , Ding Kai , Waters Michael R. , Raut Ganesh Kumar , Pandey Gaurav , Dodhiawala Paarth B. , Ramalho-Oliveira Renata , Ye Jiayu , Cole Thomas , Murali Bhavna , Zheleznyak Alexander , Shokeen Monica , Weiss Kurt R. , Monahan Joseph B. , DeSelm Carl J. , Lee Adrian V. , Oesterreich Steffi , Weilbaecher Katherine N. , Zhang Jin , DeNardo David G. , Stewart Sheila A.
Published: June 2023

Contains supplemental figures and legends
Supplementary Table S2 from Single-Cell RNA Sequencing Unifies Developmental Programs of Esophageal and Gastric Intestinal Metaplasia
Authors: Nowicki-Osuch Karol , Zhuang Lizhe , Cheung Tik Shing , Black Emily L. , Masqué-Soler Neus , Devonshire Ginny , Redmond Aisling M. , Freeman Adam , di Pietro Massimilliano , Pilonis Nastazja , Januszewicz Wladyslaw , O'Donovan Maria , Tavaré Simon , Shields Jacqueline D. , Fitzgerald Rebecca C.
Published: June 2023

This table contains marker genes identified in each cluster of cells.
Supplementary Figures from Single-Cell RNA Sequencing Unifies Developmental Programs of Esophageal and Gastric Intestinal Metaplasia
Authors: Nowicki-Osuch Karol , Zhuang Lizhe , Cheung Tik Shing , Black Emily L. , Masqué-Soler Neus , Devonshire Ginny , Redmond Aisling M. , Freeman Adam , di Pietro Massimilliano , Pilonis Nastazja , Januszewicz Wladyslaw , O'Donovan Maria , Tavaré Simon , Shields Jacqueline D. , Fitzgerald Rebecca C.
Published: June 2023

This file captions for supplementary tables and supplementary figures S1-S28 together with their legends
Figure 5 from Single-Cell RNA Sequencing Unifies Developmental Programs of Esophageal and Gastric Intestinal Metaplasia
Authors: Nowicki-Osuch Karol , Zhuang Lizhe , Cheung Tik Shing , Black Emily L. , Masqué-Soler Neus , Devonshire Ginny , Redmond Aisling M. , Freeman Adam , di Pietro Massimilliano , Pilonis Nastazja , Januszewicz Wladyslaw , O'Donovan Maria , Tavaré Simon , Shields Jacqueline D. , Fitzgerald Rebecca C.
Published: June 2023

Gastric and esophageal IM are enriched for extracellular matrix–depositing subtypes of fibroblasts. A, UMAP of fibroblast-like cells (cluster 13 in Supplementary Fig. S1) with fibroblast-specific clusters highlighted. B, UMAP of fibroblast-like cells (cluster 13 in Supplementary Fig. S1) with manually annotated cell types derived from Davidson et al. (38). C, UMAP of fibroblast-like cells (cluster 13 in Supplementary Fig. S1) with the contribution of individual tissue type highlighted. D, Bubble plot of top five genes identified in the differential analysis between the fibroblast-specific cell clusters. E, Bubble plot of genes identified as markers of early fibroblast development by Davidson et al. (38). F, Contribution of cell types derived from Davidson et al. (38) to cell counts from individual tissue types. The tissues originate from three studies: (i) Nowicki-Osuch and Zhuang et al. (4) and this study, (ii) Sathe et al. (62), and (iii) Zhang et al. (61). For tissue for which patient status could be identified, the tissue was split into healthy and disease states. NGB samples are adjacent to gastric cancer samples. G, Proportion of each subtype in total S1/S2/S3 fibroblasts derived from IF staining of E-GM, BE-IM, and GIM. H, Representative IF staining of E-GM, BE-IM, and GIM of S1 (CD34+CD31−), S2 (POSTN+aSMA−), and S3 (aSMA+) fibroblasts. I, Schematic summary of unified developmental trajectories between BE-IM and GIM.
Figure 4 from Single-Cell RNA Sequencing Unifies Developmental Programs of Esophageal and Gastric Intestinal Metaplasia
Authors: Nowicki-Osuch Karol , Zhuang Lizhe , Cheung Tik Shing , Black Emily L. , Masqué-Soler Neus , Devonshire Ginny , Redmond Aisling M. , Freeman Adam , di Pietro Massimilliano , Pilonis Nastazja , Januszewicz Wladyslaw , O'Donovan Maria , Tavaré Simon , Shields Jacqueline D. , Fitzgerald Rebecca C.
Published: June 2023

E-GM and atrophic gastritis share early features of developing IM. A, UMAP of columnar cells of gastric cell types (NGC and NGB, top left), E-GM (top right), and atrophic gastritis (NAG and CAG, bottom left) with cell-type annotation highlighted. Bottom right, UMAP with clusters 6 and 16 (identified during reclustering of columnar cells and overlapping gastric neck cells) highlighted. EE, enteroendocrine. B, Stacked bar chart of tissue contribution to the cells assigned to clusters 6 and 16. C, Gene set enrichment analysis (GSEA) using the C3 gene set database of differentially expressed genes between neck-like cells from E-GM and NGC samples. HNF4A- and MYC-related pathways are highlighted. The differential analysis was done between E-GM cells and NGC + NSCJ neck-like cells with each patient treated as an individual replicate. NES, normalized enrichment score. D, GSEA using the C3 gene set database of differentially expressed genes between NAG/CAG and NGC/NGB/NSCJ sample neck-like cells. AP-1–related pathways are highlighted. The differential analysis was done between cluster 16 cells (including NAG, CAG, and E-GM cells) and cluster 6 (including NGC + NGB + NSCJ neck-like cells) with each patient treated as an individual replicate. E, Venn diagram demonstrating the overlap between genes enriched in the comparison of atrophic gastritis (NAG and CAG) and normal gastric samples or E-GM and normal gastric samples. Bottom left: bubble plot of top 25 expressed genes shared between the comparison. Bottom right, violin plots of selected genes. F, WGS-based analysis of E-GM and BE-IM. Top, mutational burden [single-nucleotide variants/megabase (SNV/Mb)] of NGC, E-GM, and BE-IM samples. Bottom, distribution of COSMIC SNV signatures in the E-GM and BE-IM samples.
Figure 2 from Single-Cell RNA Sequencing Unifies Developmental Programs of Esophageal and Gastric Intestinal Metaplasia
Authors: Nowicki-Osuch Karol , Zhuang Lizhe , Cheung Tik Shing , Black Emily L. , Masqué-Soler Neus , Devonshire Ginny , Redmond Aisling M. , Freeman Adam , di Pietro Massimilliano , Pilonis Nastazja , Januszewicz Wladyslaw , O'Donovan Maria , Tavaré Simon , Shields Jacqueline D. , Fitzgerald Rebecca C.
Published: June 2023

Cell-type distribution across the tissues of the GI tract. A, UMAP of all high-quality cells (point order is randomized) used in the study, with the cell types assigned to the epithelial compartment in color. The line indicates a TSCAN-derived trajectory between the clusters of epithelial cells. Nonepithelial cells are in gray. B, Stacked bar chart of the proportion of cell types assigned to individual tissue types. The color scale is the same as in A. BSCJ, squamocolumnar junction between NE and BE-IM.
Figure 6 from Late-Stage Metastatic Melanoma Emerges through a Diversity of Evolutionary Pathways
Authors: Spain Lavinia , Coulton Alexander , Lobon Irene , Rowan Andrew , Schnidrig Desiree , Shepherd Scott T.C. , Shum Benjamin , Byrne Fiona , Goicoechea Maria , Piperni Elisa , Au Lewis , Edmonds Kim , Carlyle Eleanor , Hunter Nikki , Renn Alexandra , Messiou Christina , Hughes Peta , Nobbs Jaime , Foijer Floris , van den Bos Hilda , Wardenaar Rene , Spierings Diana C.J. , Spencer Charlotte , Schmitt Andreas M. , Tippu Zayd , Lingard Karla , Grostate Lauren , Peat Kema , Kelly Kayleigh , Sarker Sarah , Vaughan Sarah , Mangwende Mary , Terry Lauren , Kelly Denise , Biano Jennifer , Murra Aida , Korteweg Justine , Lewis Charlotte , O'Flaherty Molly , Cattin Anne-Laure , Emmerich Max , Gerard Camille L. , Pallikonda Husayn Ahmed , Lynch Joanna , Mason Robert , Rogiers Aljosja , Xu Hang , Huebner Ariana , McGranahan Nicholas , Al Bakir Maise , Murai Jun , Naceur-Lombardelli Cristina , Borg Elaine , Mitchison Miriam , Moore David A. , Falzon Mary , Proctor Ian , Stamp Gordon W.H. , Nye Emma L. , Young Kate , Furness Andrew J.S. , Pickering Lisa , Stewart Ruby , Mahadeva Ula , Green Anna , Larkin James , Litchfield Kevin , Swanton Charles , Jamal-Hanjani Mariam , Turajlic Samra
Published: June 2023

Identification of a likely non–whole-genome–doubled clone that was not identifiable from bulk sequencing data in CRUKP2567. Clonal phylogeny of CRUKP2567 (A), with anatomic diagram (B) based on bulk SNVs mapping samples to clones on the tree. The scale indicates the number of mutations. C, MEDICC2 copy-number tree for bulk exome samples from CRUKP2567. The cluster highlighted in blue has undergone one WGD event, while the other nonhighlighted cluster, containing brain metastasis and primary tumor samples, has not. Diamonds indicate the samples for which bulk copy-number profiles are displayed in Supplementary Fig. S23. D, Hierarchical clustering tree containing all single cells (SS) from FACs-high-ploidy sorting (FH) and FACs-low-ploidy sorting (FL), as well as WGD bulk samples and non-WGD bulk samples. E, Radiologic images of the patient indicating thorax upon initiation of stage IV disease and complete extracranial response to BRAF inhibitor, followed by rapid recolonization of the thorax with resistant clones (left to right). BR, brain; BRAFi, BRAF inhibitor; CR, complete response; DI, diaphragm; LN, lymph node; LU, lung; MEKi, MEK inhibitor; PC, pericardium, PLFa, pleural fluid (archival); PR, primary.
Figure 1 from Single-Cell RNA Sequencing Unifies Developmental Programs of Esophageal and Gastric Intestinal Metaplasia
Authors: Nowicki-Osuch Karol , Zhuang Lizhe , Cheung Tik Shing , Black Emily L. , Masqué-Soler Neus , Devonshire Ginny , Redmond Aisling M. , Freeman Adam , di Pietro Massimilliano , Pilonis Nastazja , Januszewicz Wladyslaw , O'Donovan Maria , Tavaré Simon , Shields Jacqueline D. , Fitzgerald Rebecca C.
Published: June 2023

Overview of the scRNA-seq atlas of the GI tract. A, Overview of the samples analyzed in the study. For each sample, the approximate location of tissue is indicated. Where indicated, text in brackets denotes the study from which samples originate [Wang et al. (37), Zhang et al. (61), and Sathe et al. (62)]. The remaining samples were collected in the current study or originate from Nowicki-Osuch and Zhuang et al. (4). B, UMAP of all high-quality cells used in the study. The main plot shows all tissue types overlay (point order is randomized). The insets show selected tissue types grouped according to their anatomic location and disease state. BSCJ, squamocolumnar junction between NE and BE-IM.
Figure 3 from Late-Stage Metastatic Melanoma Emerges through a Diversity of Evolutionary Pathways
Authors: Spain Lavinia , Coulton Alexander , Lobon Irene , Rowan Andrew , Schnidrig Desiree , Shepherd Scott T.C. , Shum Benjamin , Byrne Fiona , Goicoechea Maria , Piperni Elisa , Au Lewis , Edmonds Kim , Carlyle Eleanor , Hunter Nikki , Renn Alexandra , Messiou Christina , Hughes Peta , Nobbs Jaime , Foijer Floris , van den Bos Hilda , Wardenaar Rene , Spierings Diana C.J. , Spencer Charlotte , Schmitt Andreas M. , Tippu Zayd , Lingard Karla , Grostate Lauren , Peat Kema , Kelly Kayleigh , Sarker Sarah , Vaughan Sarah , Mangwende Mary , Terry Lauren , Kelly Denise , Biano Jennifer , Murra Aida , Korteweg Justine , Lewis Charlotte , O'Flaherty Molly , Cattin Anne-Laure , Emmerich Max , Gerard Camille L. , Pallikonda Husayn Ahmed , Lynch Joanna , Mason Robert , Rogiers Aljosja , Xu Hang , Huebner Ariana , McGranahan Nicholas , Al Bakir Maise , Murai Jun , Naceur-Lombardelli Cristina , Borg Elaine , Mitchison Miriam , Moore David A. , Falzon Mary , Proctor Ian , Stamp Gordon W.H. , Nye Emma L. , Young Kate , Furness Andrew J.S. , Pickering Lisa , Stewart Ruby , Mahadeva Ula , Green Anna , Larkin James , Litchfield Kevin , Swanton Charles , Jamal-Hanjani Mariam , Turajlic Samra
Published: June 2023

Late-emerging brain metastases have a lower copy-number burden. A, wGII per metastatic site. Site-specific null distributions of mean wGII were generated by randomizing sample sets (from any metastatic site) while keeping patient contributions constant (see Methods). **, P ≤ 0.01. Leptomen., leptomeninges. B, Correlation between brain copy-number (CN) distance to other sites and time of emergence of brain metastases after stage IV diagnosis in days. C, Growth dynamics of tumors in patient CRUKP5107. The brain lesion (in orange) was detected in only the last two scans after the targeted therapy [BRAF inhibitor (i) + MEKi], ICI (PD-1i + CTLA4i), and chemotherapy courses. PD, progressive disease; PR, partial response; SD, stable disease. D, SNV and indel phylogenetic tree of tumor clones in patient CRUKP5107. E, The mutational signature contributions to each clone in the phylogeny in D are shown. MMR, mismatch repair. F, The anatomic distribution of clones. Each pie chart represents a sample with its clonal composition indicated by the colors. A multiregional sampling of the same tumor is indicated by the gray dashed lines. BR, brain; LI, liver; LU, lung; PC, pericardium; ST, soft tissue.
Supplementary Table S3 from Cell-Autonomous Cxcl1 Sustains Tolerogenic Circuitries and Stromal Inflammation via Neutrophil-Derived TNF in Pancreatic Cancer
Authors: Bianchi Anna , De Castro Silva Iago , Deshpande Nilesh U. , Singh Samara , Mehra Siddharth , Garrido Vanessa T. , Guo Xinyu , Nivelo Luis A. , Kolonias Despina S. , Saigh Shannon J. , Wieder Eric , Rafie Christine I. , Dosch Austin R. , Zhou Zhiqun , Umland Oliver , Amirian Haleh , Ogobuiro Ifeanyichukwu C. , Zhang Jian , Ban Yuguang , Shiau Carina , Nagathihalli Nagaraj S. , Montgomery Elizabeth A. , Hwang William L. , Brambilla Roberta , Komanduri Krishna , Villarino Alejandro V. , Toska Eneda , Stanger Ben Z. , Gabrilovich Dmitry I. , Merchant Nipun B. , Datta Jashodeep
Published: June 2023

Co-occupied and unique target genes shared between Creb and RNApol-II in chromatin immunoprecipitation and sequencing (ChIP-seq) experiments performed in murine Kras-Trp53 cooperative KPC pancreatic cancer cells
Supplementary Methods & Figures S1-S5 from Tracing Founder Mutations in Circulating and Tissue-Resident Follicular Lymphoma Precursors
Authors: Schroers-Martin Joseph G. , Soo Joanne , Brisou Gabriel , Scherer Florian , Kurtz David M. , Sworder Brian J. , Khodadoust Michael S. , Jin Michael C. , Bru Agnès , Liu Chih Long , Stehr Henning , Vineis Paolo , Natkunam Yasodha , Teras Lauren R. , Song Joo Y. , Nadel Bertrand , Diehn Maximilian , Roulland Sandrine , Alizadeh Ash A.
Published: June 2023

Supplementary Methods and Figures S1-S5
Supplementary Table S9 from (R)-2-Hydroxyglutarate Inhibits KDM5 Histone Lysine Demethylases to Drive Transformation in IDH-Mutant Cancers
Authors: Gunn Kathryn , Myllykoski Matti , Cao John Z. , Ahmed Manna , Huang Bofu , Rouaisnel Betty , Diplas Bill H. , Levitt Michael M. , Looper Ryan , Doench John G. , Ligon Keith L. , Kornblum Harley I. , McBrayer Samuel K. , Yan Hai , Duy Cihangir , Godley Lucy A. , Koivunen Peppi , Losman Julie-Aurore
Published: June 2023

Supplementary Table S9 shows the gene set enrichment analysis gene set that corresponds to Figure S6A.
Supplementary Table S8 from (R)-2-Hydroxyglutarate Inhibits KDM5 Histone Lysine Demethylases to Drive Transformation in IDH-Mutant Cancers
Authors: Gunn Kathryn , Myllykoski Matti , Cao John Z. , Ahmed Manna , Huang Bofu , Rouaisnel Betty , Diplas Bill H. , Levitt Michael M. , Looper Ryan , Doench John G. , Ligon Keith L. , Kornblum Harley I. , McBrayer Samuel K. , Yan Hai , Duy Cihangir , Godley Lucy A. , Koivunen Peppi , Losman Julie-Aurore
Published: June 2023

Supplementary Table S8 shows the pathway analysis of the expression data from Supplementary Table S7.
Supplementary Table S7 from (R)-2-Hydroxyglutarate Inhibits KDM5 Histone Lysine Demethylases to Drive Transformation in IDH-Mutant Cancers
Authors: Gunn Kathryn , Myllykoski Matti , Cao John Z. , Ahmed Manna , Huang Bofu , Rouaisnel Betty , Diplas Bill H. , Levitt Michael M. , Looper Ryan , Doench John G. , Ligon Keith L. , Kornblum Harley I. , McBrayer Samuel K. , Yan Hai , Duy Cihangir , Godley Lucy A. , Koivunen Peppi , Losman Julie-Aurore
Published: June 2023

Supplementary Table S7 shows the gene set enrichment analysis gene set that corresponds to Figure 4E.
Supplementary Table S5 from (R)-2-Hydroxyglutarate Inhibits KDM5 Histone Lysine Demethylases to Drive Transformation in IDH-Mutant Cancers
Authors: Gunn Kathryn , Myllykoski Matti , Cao John Z. , Ahmed Manna , Huang Bofu , Rouaisnel Betty , Diplas Bill H. , Levitt Michael M. , Looper Ryan , Doench John G. , Ligon Keith L. , Kornblum Harley I. , McBrayer Samuel K. , Yan Hai , Duy Cihangir , Godley Lucy A. , Koivunen Peppi , Losman Julie-Aurore
Published: June 2023

Supplementary Table S5 shows the rank order list of genes targeted by sgRNAs enriched in the custom minipool CRISPR/Cas9 knockout screens.
Supplementary Table S11 from (R)-2-Hydroxyglutarate Inhibits KDM5 Histone Lysine Demethylases to Drive Transformation in IDH-Mutant Cancers
Authors: Gunn Kathryn , Myllykoski Matti , Cao John Z. , Ahmed Manna , Huang Bofu , Rouaisnel Betty , Diplas Bill H. , Levitt Michael M. , Looper Ryan , Doench John G. , Ligon Keith L. , Kornblum Harley I. , McBrayer Samuel K. , Yan Hai , Duy Cihangir , Godley Lucy A. , Koivunen Peppi , Losman Julie-Aurore
Published: June 2023

Supplementary Table S11 shows the characteristics of the primary glioma patient samples.
Supplementary Table S10 from (R)-2-Hydroxyglutarate Inhibits KDM5 Histone Lysine Demethylases to Drive Transformation in IDH-Mutant Cancers
Authors: Gunn Kathryn , Myllykoski Matti , Cao John Z. , Ahmed Manna , Huang Bofu , Rouaisnel Betty , Diplas Bill H. , Levitt Michael M. , Looper Ryan , Doench John G. , Ligon Keith L. , Kornblum Harley I. , McBrayer Samuel K. , Yan Hai , Duy Cihangir , Godley Lucy A. , Koivunen Peppi , Losman Julie-Aurore
Published: June 2023

Supplementary Table S10 shows the gene set enrichment analysis gene set that corresponds to Figure S6B.
Supplementary Figure S7 from (R)-2-Hydroxyglutarate Inhibits KDM5 Histone Lysine Demethylases to Drive Transformation in IDH-Mutant Cancers
Authors: Gunn Kathryn , Myllykoski Matti , Cao John Z. , Ahmed Manna , Huang Bofu , Rouaisnel Betty , Diplas Bill H. , Levitt Michael M. , Looper Ryan , Doench John G. , Ligon Keith L. , Kornblum Harley I. , McBrayer Samuel K. , Yan Hai , Duy Cihangir , Godley Lucy A. , Koivunen Peppi , Losman Julie-Aurore
Published: June 2023

5mC levels in primary AML and primary glioma samples and in MCTS lines.