bluuebunny/crossref_metadata_2025 huggingface dataset:
Supplementary Table S6 from C/EBPα Confers Dependence to Fatty Acid Anabolic Pathways and Vulnerability to Lipid Oxidative Stress–Induced Ferroptosis in FLT3-Mutant Leukemia
Authors: Sabatier Marie , Birsen Rudy , Lauture Laura , Mouche Sarah , Angelino Paolo , Dehairs Jonas , Goupille Léa , Boussaid Ismael , Heiblig Maël , Boet Emeline , Sahal Ambrine , Saland Estelle , Santos Juliana C. , Armengol Marc , Fernández-Serrano Miranda , Farge Thomas , Cognet Guillaume , Simonetta Federico , Pignon Corentin , Graffeuil Antoine , Mazzotti Céline , Avet-Loiseau Hervé , Delos Océane , Bertrand-Michel Justine , Chedru Amélie , Dembitz Vilma , Gallipoli Paolo , Anstee Natasha S. , Loo Sun , Wei Andrew H. , Carroll Martin , Goubard Armelle , Castellano Rémy , Collette Yves , Vergez François , Mansat-De Mas Véronique , Bertoli Sarah , Tavitian Suzanne , Picard Muriel , Récher Christian , Bourges-Abella Nathalie , Granat Fanny , Kosmider Olivier , Sujobert Pierre , Colsch Benoit , Joffre Carine , Stuani Lucille , Swinnen Johannes V. , Guillou Hervé , Roué Gael , Hakim Nawad , Dejean Anne S. , Tsantoulis Petros , Larrue Clément , Bouscary Didier , Tamburini Jerome , Sarry Jean-Emmanuel
Published: July 2023

Table S6: Proteomic analysis of FLT3-ITD AML cell lines treated with vehicle or QUIZ
Supplementary Table S3 from C/EBPα Confers Dependence to Fatty Acid Anabolic Pathways and Vulnerability to Lipid Oxidative Stress–Induced Ferroptosis in FLT3-Mutant Leukemia
Authors: Sabatier Marie , Birsen Rudy , Lauture Laura , Mouche Sarah , Angelino Paolo , Dehairs Jonas , Goupille Léa , Boussaid Ismael , Heiblig Maël , Boet Emeline , Sahal Ambrine , Saland Estelle , Santos Juliana C. , Armengol Marc , Fernández-Serrano Miranda , Farge Thomas , Cognet Guillaume , Simonetta Federico , Pignon Corentin , Graffeuil Antoine , Mazzotti Céline , Avet-Loiseau Hervé , Delos Océane , Bertrand-Michel Justine , Chedru Amélie , Dembitz Vilma , Gallipoli Paolo , Anstee Natasha S. , Loo Sun , Wei Andrew H. , Carroll Martin , Goubard Armelle , Castellano Rémy , Collette Yves , Vergez François , Mansat-De Mas Véronique , Bertoli Sarah , Tavitian Suzanne , Picard Muriel , Récher Christian , Bourges-Abella Nathalie , Granat Fanny , Kosmider Olivier , Sujobert Pierre , Colsch Benoit , Joffre Carine , Stuani Lucille , Swinnen Johannes V. , Guillou Hervé , Roué Gael , Hakim Nawad , Dejean Anne S. , Tsantoulis Petros , Larrue Clément , Bouscary Didier , Tamburini Jerome , Sarry Jean-Emmanuel
Published: July 2023

Table S3: Clinical characteristics of samples from patients with AML used in PDX assays
Supplementary Figure S2 from Early Infiltration of Innate Immune Cells to the Liver Depletes HNF4α and Promotes Extrahepatic Carcinogenesis
Authors: Goldman Omer , Adler Lital N. , Hajaj Emma , Croese Tommaso , Darzi Naama , Galai Sivan , Tishler Hila , Ariav Yarden , Lavie Dor , Fellus-Alyagor Liat , Oren Roni , Kuznetsov Yuri , David Eyal , Jaschek Rami , Stossel Chani , Singer Oded , Malitsky Sergey , Barak Renana , Seger Rony , Erez Neta , Amit Ido , Tanay Amos , Saada Ann , Golan Talia , Rubinek Tamar , Sang Lee Joo , Ben-Shachar Shay , Wolf Ido , Erez Ayelet
Published: July 2023

Supplementary Figure S2 demonstrates the infiltration of mature innate immune cells to the liver during breast carcinogenesis
Supplementary Table S15 from C/EBPα Confers Dependence to Fatty Acid Anabolic Pathways and Vulnerability to Lipid Oxidative Stress–Induced Ferroptosis in FLT3-Mutant Leukemia
Authors: Sabatier Marie , Birsen Rudy , Lauture Laura , Mouche Sarah , Angelino Paolo , Dehairs Jonas , Goupille Léa , Boussaid Ismael , Heiblig Maël , Boet Emeline , Sahal Ambrine , Saland Estelle , Santos Juliana C. , Armengol Marc , Fernández-Serrano Miranda , Farge Thomas , Cognet Guillaume , Simonetta Federico , Pignon Corentin , Graffeuil Antoine , Mazzotti Céline , Avet-Loiseau Hervé , Delos Océane , Bertrand-Michel Justine , Chedru Amélie , Dembitz Vilma , Gallipoli Paolo , Anstee Natasha S. , Loo Sun , Wei Andrew H. , Carroll Martin , Goubard Armelle , Castellano Rémy , Collette Yves , Vergez François , Mansat-De Mas Véronique , Bertoli Sarah , Tavitian Suzanne , Picard Muriel , Récher Christian , Bourges-Abella Nathalie , Granat Fanny , Kosmider Olivier , Sujobert Pierre , Colsch Benoit , Joffre Carine , Stuani Lucille , Swinnen Johannes V. , Guillou Hervé , Roué Gael , Hakim Nawad , Dejean Anne S. , Tsantoulis Petros , Larrue Clément , Bouscary Didier , Tamburini Jerome , Sarry Jean-Emmanuel
Published: July 2023

Table S15: Relative quantification by lipid class
Supplementary Extended Data 1 from Early Infiltration of Innate Immune Cells to the Liver Depletes HNF4α and Promotes Extrahepatic Carcinogenesis
Authors: Goldman Omer , Adler Lital N. , Hajaj Emma , Croese Tommaso , Darzi Naama , Galai Sivan , Tishler Hila , Ariav Yarden , Lavie Dor , Fellus-Alyagor Liat , Oren Roni , Kuznetsov Yuri , David Eyal , Jaschek Rami , Stossel Chani , Singer Oded , Malitsky Sergey , Barak Renana , Seger Rony , Erez Neta , Amit Ido , Tanay Amos , Saada Ann , Golan Talia , Rubinek Tamar , Sang Lee Joo , Ben-Shachar Shay , Wolf Ido , Erez Ayelet
Published: July 2023

Supplementary Extended Data 1 describes the FACS gating startegy
Supplementary Table S13 from C/EBPα Confers Dependence to Fatty Acid Anabolic Pathways and Vulnerability to Lipid Oxidative Stress–Induced Ferroptosis in FLT3-Mutant Leukemia
Authors: Sabatier Marie , Birsen Rudy , Lauture Laura , Mouche Sarah , Angelino Paolo , Dehairs Jonas , Goupille Léa , Boussaid Ismael , Heiblig Maël , Boet Emeline , Sahal Ambrine , Saland Estelle , Santos Juliana C. , Armengol Marc , Fernández-Serrano Miranda , Farge Thomas , Cognet Guillaume , Simonetta Federico , Pignon Corentin , Graffeuil Antoine , Mazzotti Céline , Avet-Loiseau Hervé , Delos Océane , Bertrand-Michel Justine , Chedru Amélie , Dembitz Vilma , Gallipoli Paolo , Anstee Natasha S. , Loo Sun , Wei Andrew H. , Carroll Martin , Goubard Armelle , Castellano Rémy , Collette Yves , Vergez François , Mansat-De Mas Véronique , Bertoli Sarah , Tavitian Suzanne , Picard Muriel , Récher Christian , Bourges-Abella Nathalie , Granat Fanny , Kosmider Olivier , Sujobert Pierre , Colsch Benoit , Joffre Carine , Stuani Lucille , Swinnen Johannes V. , Guillou Hervé , Roué Gael , Hakim Nawad , Dejean Anne S. , Tsantoulis Petros , Larrue Clément , Bouscary Didier , Tamburini Jerome , Sarry Jean-Emmanuel
Published: July 2023

Table S13: lipidomic results by lipid species in dox-inducible and constitutives shRNAs and siRNA CTL/CEBPA, empty vector/CEBPA-OE and vehicle/QUIZ conditions in MOLM-14 cells
Supplementary Table S12 from C/EBPα Confers Dependence to Fatty Acid Anabolic Pathways and Vulnerability to Lipid Oxidative Stress–Induced Ferroptosis in FLT3-Mutant Leukemia
Authors: Sabatier Marie , Birsen Rudy , Lauture Laura , Mouche Sarah , Angelino Paolo , Dehairs Jonas , Goupille Léa , Boussaid Ismael , Heiblig Maël , Boet Emeline , Sahal Ambrine , Saland Estelle , Santos Juliana C. , Armengol Marc , Fernández-Serrano Miranda , Farge Thomas , Cognet Guillaume , Simonetta Federico , Pignon Corentin , Graffeuil Antoine , Mazzotti Céline , Avet-Loiseau Hervé , Delos Océane , Bertrand-Michel Justine , Chedru Amélie , Dembitz Vilma , Gallipoli Paolo , Anstee Natasha S. , Loo Sun , Wei Andrew H. , Carroll Martin , Goubard Armelle , Castellano Rémy , Collette Yves , Vergez François , Mansat-De Mas Véronique , Bertoli Sarah , Tavitian Suzanne , Picard Muriel , Récher Christian , Bourges-Abella Nathalie , Granat Fanny , Kosmider Olivier , Sujobert Pierre , Colsch Benoit , Joffre Carine , Stuani Lucille , Swinnen Johannes V. , Guillou Hervé , Roué Gael , Hakim Nawad , Dejean Anne S. , Tsantoulis Petros , Larrue Clément , Bouscary Didier , Tamburini Jerome , Sarry Jean-Emmanuel
Published: July 2023

Table S12: gene signatures used to analyze RNA-seq data from patients with AML before/after GILT
Supplementary Figure S1-S11 and Table S1 from Splicing Factor SRSF1 Promotes Pancreatitis and KRASG12D-Mediated Pancreatic Cancer
Authors: Wan Ledong , Lin Kuan-Ting , Rahman Mohammad Alinoor , Ishigami Yuma , Wang Zhikai , Jensen Mads A. , Wilkinson John E. , Park Youngkyu , Tuveson David A. , Krainer Adrian R.
Published: July 2023

Figure S1. Elevated SRSF1 induces pancreatitis and is associated with its duration. Figure S2. Elevated SRSF1 predicts poor PDAC clinical prognosis and is associated with PDAC progression. Figure S3. SRSF1 accelerates KRASG12D-mediated PDAC tumorigenesis. Figure S4. SRSF1 loss delays KRASG12D-mediated PDAC initiation. Figure S5. Opposite patterns of pathway enrichment by KRASG12D mutation versus SRSF1 upregulation. Figure S6. Recombination and activation of KrasG12D allele in pancreas cells from KC mice. Figure S7. KSC and KPSC mice exhibit a hyper-activated MAPK pathway, suppression of which diminished SRSF1-induced pancreatitis. Figure S8. Decreased SRSF1 expression perturbs MAPK signaling. Figure S9. MYC promotes SRSF1 expression in PDAC. Figure S10. SRSF1 regulates IL1R1 alternative splicing and expression. Figure S11. Knockout of Il1r1 rescues SRSF1-induced pancreatitis. Table S1. Oligonucleotides for PCR and short hairpin RNAs.
Supplementary Figures S1-S22 from Integrative Analysis of a Large Real-World Cohort of Small Cell Lung Cancer Identifies Distinct Genetic Subtypes and Insights into Histologic Transformation
Authors: Sivakumar Smruthy , Moore Jay A. , Montesion Meagan , Sharaf Radwa , Lin Douglas I. , Colón Caterina I. , Fleishmann Zoe , Ebot Ericka M. , Newberg Justin Y. , Mills Jennifer M. , Hegde Priti S. , Pan Quintin , Dowlati Afshin , Frampton Garrett M. , Sage Julien , Lovly Christine M.
Published: July 2023

Figure S1: Patterns of tumor mutational burden across different ancestry groups.
Figure S2: Spectrum of TP53 and RB1 mutations in SCLC.
Figure S3: Gene alteration landscape detected from targeted sequencing of liquid biopsies.
Figure S4: Chromosomal loss events are frequent in SCLC and are preferentially enriched for tumor suppressor genes.
Figure S5: Hematoxylin & Eosin (H&E) staining for some representative SCLC tumors with rare genomic alterations.
Figure S6: Gene alterations detected in SMARCA4-altered SCLC.
Figure S7: SCLC tumors exhibit recurrent gene rearrangements with therapeutic potential.
Figure S8: Trends of overall survival across different ancestry groups and stage in the clinical cohort.
Figure S9: Examination of tumor purity and tumor mutational burden (TMB).
Figure S10: Liver and Brain SCLC metastases are enriched for chromosomal arm-level gains compared to lung-biopsied SCLC tumors.
Figure S11: SCLC tumors present with unique co-occurring and mutual exclusive patterns of gene alterations.
Figure S12: SCLC tumors with wild-type TP53 and/or RB1 have a low tumor mutational burden.
Figure S13: SCLC tumors with wild-type TP53 and/or RB1 present with specific gene alterations.
Figure S14: A smoking-associated mutational signature is rare in TP53/RB1 WT SCLC tumors.
Figure S15: TP53 and RB1 alterations are less frequent in never smokers.
Figure S16: Patterns of overall survival based on TP53 and RB1 alteration status.
Figure S17: TP53 and RB1 mutations are more frequent in older patients with SCLC.
Figure S18: Gene alterations detected in HPV-positive SCLC.
Figure S19: Examination of HPV subtypes and prevalence in TP53/RB1 mutant and wild-type SCLC tumors.
Figure S20: EGFR-mutant SCLC tumors exhibit unique mutational signature profiles.
Figure S21: No overall survival differences based on EGFR mutation status in SCLC.
Figure S22: Putative transformed SCLC tumors from EGFR-mutant NSCLC are enriched for EGFR exon 19 deletions.
Supplementary Table S5 from Comutations and KRASG12C Inhibitor Efficacy in Advanced NSCLC
Authors: Negrao Marcelo V. , Araujo Haniel A. , Lamberti Giuseppe , Cooper Alissa J. , Akhave Neal S. , Zhou Teng , Delasos Lukas , Hicks J. Kevin , Aldea Mihaela , Minuti Gabriele , Hines Jacobi , Aredo Jacqueline V. , Dennis Michael J. , Chakrabarti Turja , Scott Susan C. , Bironzo Paolo , Scheffler Matthias , Christopoulos Petros , Stenzinger Albrecht , Riess Jonathan W. , Kim So Yeon , Goldberg Sarah B. , Li Mingjia , Wang Qi , Qing Yun , Ni Ying , Do Minh Truong , Lee Richard , Ricciuti Biagio , Alessi Joao Victor , Wang Jing , Resuli Blerina , Landi Lorenza , Tseng Shu-Chi , Nishino Mizuki , Digumarthy Subba R. , Rinsurongkawong Waree , Rinsurongkawong Vadeerat , Vaporciyan Ara A. , Blumenschein George R. , Zhang Jianjun , Owen Dwight H. , Blakely Collin M. , Mountzios Giannis , Shu Catherine A. , Bestvina Christine M. , Garassino Marina Chiara , Marrone Kristen A. , Gray Jhanelle E. , Patel Sandip Pravin , Cummings Amy L. , Wakelee Heather A. , Wolf Juergen , Scagliotti Giorgio Vittorio , Cappuzzo Federico , Barlesi Fabrice , Patil Pradnya D. , Drusbosky Leylah , Gibbons Don L. , Meric-Bernstam Funda , Lee J. Jack , Heymach John V. , Hong David S. , Heist Rebecca S. , Awad Mark M. , Skoulidis Ferdinandos
Published: July 2023

Multivariable analysis - overall survival
Supplementary Table S4 from Comutations and KRASG12C Inhibitor Efficacy in Advanced NSCLC
Authors: Negrao Marcelo V. , Araujo Haniel A. , Lamberti Giuseppe , Cooper Alissa J. , Akhave Neal S. , Zhou Teng , Delasos Lukas , Hicks J. Kevin , Aldea Mihaela , Minuti Gabriele , Hines Jacobi , Aredo Jacqueline V. , Dennis Michael J. , Chakrabarti Turja , Scott Susan C. , Bironzo Paolo , Scheffler Matthias , Christopoulos Petros , Stenzinger Albrecht , Riess Jonathan W. , Kim So Yeon , Goldberg Sarah B. , Li Mingjia , Wang Qi , Qing Yun , Ni Ying , Do Minh Truong , Lee Richard , Ricciuti Biagio , Alessi Joao Victor , Wang Jing , Resuli Blerina , Landi Lorenza , Tseng Shu-Chi , Nishino Mizuki , Digumarthy Subba R. , Rinsurongkawong Waree , Rinsurongkawong Vadeerat , Vaporciyan Ara A. , Blumenschein George R. , Zhang Jianjun , Owen Dwight H. , Blakely Collin M. , Mountzios Giannis , Shu Catherine A. , Bestvina Christine M. , Garassino Marina Chiara , Marrone Kristen A. , Gray Jhanelle E. , Patel Sandip Pravin , Cummings Amy L. , Wakelee Heather A. , Wolf Juergen , Scagliotti Giorgio Vittorio , Cappuzzo Federico , Barlesi Fabrice , Patil Pradnya D. , Drusbosky Leylah , Gibbons Don L. , Meric-Bernstam Funda , Lee J. Jack , Heymach John V. , Hong David S. , Heist Rebecca S. , Awad Mark M. , Skoulidis Ferdinandos
Published: July 2023

Multivariable analysis - progression-free survival
Table S3 from Type I Interferon Signaling via the EGR2 Transcriptional Regulator Potentiates CAR T Cell–Intrinsic Dysfunction
Authors: Jung In-Young , Bartoszek Robert L. , Rech Andrew J. , Collins Sierra M. , Ooi Soon-Keat , Williams Erik F. , Hopkins Caitlin R. , Narayan Vivek , Haas Naomi B. , Frey Noelle V. , Hexner Elizabeth O. , Siegel Donald L. , Plesa Gabriela , Porter David L. , Cantu Adrian , Everett John K. , Guedan Sonia , Berger Shelley L. , Bushman Frederic D. , Herbst Friederike , Fraietta Joseph A.
Published: July 2023

Chromatin accessibility profiles for EGR2 knockout (KO) and AAVS1 knockout (AAVS1) CD8+ CAR T-cells. The table provides information on the locus mapping, p-value, average log2 fold change, percentage of cells, adjusted p-value, transcript ID, gene name, gene ID, gene biotype, region type, closest region, query region, and distance.
Table S1 from Type I Interferon Signaling via the EGR2 Transcriptional Regulator Potentiates CAR T Cell–Intrinsic Dysfunction
Authors: Jung In-Young , Bartoszek Robert L. , Rech Andrew J. , Collins Sierra M. , Ooi Soon-Keat , Williams Erik F. , Hopkins Caitlin R. , Narayan Vivek , Haas Naomi B. , Frey Noelle V. , Hexner Elizabeth O. , Siegel Donald L. , Plesa Gabriela , Porter David L. , Cantu Adrian , Everett John K. , Guedan Sonia , Berger Shelley L. , Bushman Frederic D. , Herbst Friederike , Fraietta Joseph A.
Published: July 2023

Genes comprising the TCF7 regulon, the type I IFN signature, and the EGR2 Co-expression signatures. Gene names and symbols are listed.
Supplementary Figure S7 from Comutations and KRASG12C Inhibitor Efficacy in Advanced NSCLC
Authors: Negrao Marcelo V. , Araujo Haniel A. , Lamberti Giuseppe , Cooper Alissa J. , Akhave Neal S. , Zhou Teng , Delasos Lukas , Hicks J. Kevin , Aldea Mihaela , Minuti Gabriele , Hines Jacobi , Aredo Jacqueline V. , Dennis Michael J. , Chakrabarti Turja , Scott Susan C. , Bironzo Paolo , Scheffler Matthias , Christopoulos Petros , Stenzinger Albrecht , Riess Jonathan W. , Kim So Yeon , Goldberg Sarah B. , Li Mingjia , Wang Qi , Qing Yun , Ni Ying , Do Minh Truong , Lee Richard , Ricciuti Biagio , Alessi Joao Victor , Wang Jing , Resuli Blerina , Landi Lorenza , Tseng Shu-Chi , Nishino Mizuki , Digumarthy Subba R. , Rinsurongkawong Waree , Rinsurongkawong Vadeerat , Vaporciyan Ara A. , Blumenschein George R. , Zhang Jianjun , Owen Dwight H. , Blakely Collin M. , Mountzios Giannis , Shu Catherine A. , Bestvina Christine M. , Garassino Marina Chiara , Marrone Kristen A. , Gray Jhanelle E. , Patel Sandip Pravin , Cummings Amy L. , Wakelee Heather A. , Wolf Juergen , Scagliotti Giorgio Vittorio , Cappuzzo Federico , Barlesi Fabrice , Patil Pradnya D. , Drusbosky Leylah , Gibbons Don L. , Meric-Bernstam Funda , Lee J. Jack , Heymach John V. , Hong David S. , Heist Rebecca S. , Awad Mark M. , Skoulidis Ferdinandos
Published: July 2023

Progression-free survival (left) and overall survival (right) according to co-mutation status for (A) CHEK2 and (B) ATRX in the overall mutation-evaluable population.
Supplementary Figure S6 from Comutations and KRASG12C Inhibitor Efficacy in Advanced NSCLC
Authors: Negrao Marcelo V. , Araujo Haniel A. , Lamberti Giuseppe , Cooper Alissa J. , Akhave Neal S. , Zhou Teng , Delasos Lukas , Hicks J. Kevin , Aldea Mihaela , Minuti Gabriele , Hines Jacobi , Aredo Jacqueline V. , Dennis Michael J. , Chakrabarti Turja , Scott Susan C. , Bironzo Paolo , Scheffler Matthias , Christopoulos Petros , Stenzinger Albrecht , Riess Jonathan W. , Kim So Yeon , Goldberg Sarah B. , Li Mingjia , Wang Qi , Qing Yun , Ni Ying , Do Minh Truong , Lee Richard , Ricciuti Biagio , Alessi Joao Victor , Wang Jing , Resuli Blerina , Landi Lorenza , Tseng Shu-Chi , Nishino Mizuki , Digumarthy Subba R. , Rinsurongkawong Waree , Rinsurongkawong Vadeerat , Vaporciyan Ara A. , Blumenschein George R. , Zhang Jianjun , Owen Dwight H. , Blakely Collin M. , Mountzios Giannis , Shu Catherine A. , Bestvina Christine M. , Garassino Marina Chiara , Marrone Kristen A. , Gray Jhanelle E. , Patel Sandip Pravin , Cummings Amy L. , Wakelee Heather A. , Wolf Juergen , Scagliotti Giorgio Vittorio , Cappuzzo Federico , Barlesi Fabrice , Patil Pradnya D. , Drusbosky Leylah , Gibbons Don L. , Meric-Bernstam Funda , Lee J. Jack , Heymach John V. , Hong David S. , Heist Rebecca S. , Awad Mark M. , Skoulidis Ferdinandos
Published: July 2023

Progression-free survival (left) and overall survival (right) according to TP53 co-mutation status in A) overall cohort, B) cohort A, and C) cohort B.
Supplementary Figure S5 from Comutations and KRASG12C Inhibitor Efficacy in Advanced NSCLC
Authors: Negrao Marcelo V. , Araujo Haniel A. , Lamberti Giuseppe , Cooper Alissa J. , Akhave Neal S. , Zhou Teng , Delasos Lukas , Hicks J. Kevin , Aldea Mihaela , Minuti Gabriele , Hines Jacobi , Aredo Jacqueline V. , Dennis Michael J. , Chakrabarti Turja , Scott Susan C. , Bironzo Paolo , Scheffler Matthias , Christopoulos Petros , Stenzinger Albrecht , Riess Jonathan W. , Kim So Yeon , Goldberg Sarah B. , Li Mingjia , Wang Qi , Qing Yun , Ni Ying , Do Minh Truong , Lee Richard , Ricciuti Biagio , Alessi Joao Victor , Wang Jing , Resuli Blerina , Landi Lorenza , Tseng Shu-Chi , Nishino Mizuki , Digumarthy Subba R. , Rinsurongkawong Waree , Rinsurongkawong Vadeerat , Vaporciyan Ara A. , Blumenschein George R. , Zhang Jianjun , Owen Dwight H. , Blakely Collin M. , Mountzios Giannis , Shu Catherine A. , Bestvina Christine M. , Garassino Marina Chiara , Marrone Kristen A. , Gray Jhanelle E. , Patel Sandip Pravin , Cummings Amy L. , Wakelee Heather A. , Wolf Juergen , Scagliotti Giorgio Vittorio , Cappuzzo Federico , Barlesi Fabrice , Patil Pradnya D. , Drusbosky Leylah , Gibbons Don L. , Meric-Bernstam Funda , Lee J. Jack , Heymach John V. , Hong David S. , Heist Rebecca S. , Awad Mark M. , Skoulidis Ferdinandos
Published: July 2023

Survival outcomes according to KEAP1 and STK11 co-mutation status: A) Cohort A; B) Cohort B; C) further subclassifying KEAP1MUT tumors according to STK11 mutation status; D) PFS and OS according to STK11 co-mutation status in KSCWT tumors in the overall study cohort.
Supplementary Figure S4 from Comutations and KRASG12C Inhibitor Efficacy in Advanced NSCLC
Authors: Negrao Marcelo V. , Araujo Haniel A. , Lamberti Giuseppe , Cooper Alissa J. , Akhave Neal S. , Zhou Teng , Delasos Lukas , Hicks J. Kevin , Aldea Mihaela , Minuti Gabriele , Hines Jacobi , Aredo Jacqueline V. , Dennis Michael J. , Chakrabarti Turja , Scott Susan C. , Bironzo Paolo , Scheffler Matthias , Christopoulos Petros , Stenzinger Albrecht , Riess Jonathan W. , Kim So Yeon , Goldberg Sarah B. , Li Mingjia , Wang Qi , Qing Yun , Ni Ying , Do Minh Truong , Lee Richard , Ricciuti Biagio , Alessi Joao Victor , Wang Jing , Resuli Blerina , Landi Lorenza , Tseng Shu-Chi , Nishino Mizuki , Digumarthy Subba R. , Rinsurongkawong Waree , Rinsurongkawong Vadeerat , Vaporciyan Ara A. , Blumenschein George R. , Zhang Jianjun , Owen Dwight H. , Blakely Collin M. , Mountzios Giannis , Shu Catherine A. , Bestvina Christine M. , Garassino Marina Chiara , Marrone Kristen A. , Gray Jhanelle E. , Patel Sandip Pravin , Cummings Amy L. , Wakelee Heather A. , Wolf Juergen , Scagliotti Giorgio Vittorio , Cappuzzo Federico , Barlesi Fabrice , Patil Pradnya D. , Drusbosky Leylah , Gibbons Don L. , Meric-Bernstam Funda , Lee J. Jack , Heymach John V. , Hong David S. , Heist Rebecca S. , Awad Mark M. , Skoulidis Ferdinandos
Published: July 2023

Clinical outcomes with KRAS G12Ci therapy according to co-mutation status for A) KEAP1, B) SMARCA4, and C) CDKN2A in patients previously treated with immune checkpoint inhibitors.
Figure S4 from Type I Interferon Signaling via the EGR2 Transcriptional Regulator Potentiates CAR T Cell–Intrinsic Dysfunction
Authors: Jung In-Young , Bartoszek Robert L. , Rech Andrew J. , Collins Sierra M. , Ooi Soon-Keat , Williams Erik F. , Hopkins Caitlin R. , Narayan Vivek , Haas Naomi B. , Frey Noelle V. , Hexner Elizabeth O. , Siegel Donald L. , Plesa Gabriela , Porter David L. , Cantu Adrian , Everett John K. , Guedan Sonia , Berger Shelley L. , Bushman Frederic D. , Herbst Friederike , Fraietta Joseph A.
Published: July 2023

Marker gene expression in CAR T-cell clusters. A, Uniform manifold approximation and projection (UMAP) plot of AAVS1 and EGR2 knockout (KO) CAR T-cell samples is shown. B, UMAP plots showing expression levels of CD4 and CD8. C, Violin plot depicting expression of cluster-defining markers in CD4+ T-cells. D, Differentially expressed genes in IL7R+ versus CTLA4+ CD4+ T-cells. E, Violin plots showing expression levels of cluster-defining markers in CD8+ T-cells. F, Heatmap displaying differentially expressed genes between CD8+ cell clusters. G, Cell cycle scores mapped on UMAP plots.
Figure S3 from Type I Interferon Signaling via the EGR2 Transcriptional Regulator Potentiates CAR T Cell–Intrinsic Dysfunction
Authors: Jung In-Young , Bartoszek Robert L. , Rech Andrew J. , Collins Sierra M. , Ooi Soon-Keat , Williams Erik F. , Hopkins Caitlin R. , Narayan Vivek , Haas Naomi B. , Frey Noelle V. , Hexner Elizabeth O. , Siegel Donald L. , Plesa Gabriela , Porter David L. , Cantu Adrian , Everett John K. , Guedan Sonia , Berger Shelley L. , Bushman Frederic D. , Herbst Friederike , Fraietta Joseph A.
Published: July 2023

Impact of EGR2 knockout on different T-cell subsets and CD28-based CAR T-cells. A, Naive, central memory, effector memory, and effector T-cells were magnetically isolated. PSMA CAR-T cells with AAVS1 and EGR2 knockout (KO) were then generated from the T-cell subsets and restimulation experiments were conducted to examine the development of exhaustion and memory. B, Expression of exhaustion markers (TIM3+LAG3+), C, cytotoxicity and D, expression of early memory markers (CD45RO+CD27+) after chronic CAR stimulation. (E-H) EGR2 was deleted in PSMA-CD28 based CAR T-cells, and the immunophenotype of CAR T-cells was assessed during the restimulation assay. E, Expression of exhaustion markers (TIM3+LAG3+), F, cytotoxicity, G, expression of early memory markers (CD45RO+CD27+) after chronic CAR stimulation and H, CAR T-cell expansion capacity during restimulation. All experiments were conducted using T-cells from two independent healthy donors, and panels (A-H) are representative data from one donor. (Mann-Whitney test, n = 4). *P < 0.05, **P < 0.01, ***P < 0.001, ns.: not significant.
Figure S2 from Type I Interferon Signaling via the EGR2 Transcriptional Regulator Potentiates CAR T Cell–Intrinsic Dysfunction
Authors: Jung In-Young , Bartoszek Robert L. , Rech Andrew J. , Collins Sierra M. , Ooi Soon-Keat , Williams Erik F. , Hopkins Caitlin R. , Narayan Vivek , Haas Naomi B. , Frey Noelle V. , Hexner Elizabeth O. , Siegel Donald L. , Plesa Gabriela , Porter David L. , Cantu Adrian , Everett John K. , Guedan Sonia , Berger Shelley L. , Bushman Frederic D. , Herbst Friederike , Fraietta Joseph A.
Published: July 2023

Impact of EGR2 knockout on CD8+/CD4+ ratio and Th2 cytokine production in the setting of chronic tumor antigen stimulation. A, Comparison of CD8+/CD4+ ratio in control and EGR2 knockout (KO) CAR T-cells after chronic CAR stimulation. B, Th2 cytokine production by control and EGR2 KO CAR T-cells after 24 hours of CAR stimulation (Mann-Whitney test, n = 4). All experiments were performed using T-cells from three independent healthy donors. Panel B is representative data from one donor. *P < 0.05, **P < 0.01, ***P < 0.001, ns: not significant.
Figure S11 from Type I Interferon Signaling via the EGR2 Transcriptional Regulator Potentiates CAR T Cell–Intrinsic Dysfunction
Authors: Jung In-Young , Bartoszek Robert L. , Rech Andrew J. , Collins Sierra M. , Ooi Soon-Keat , Williams Erik F. , Hopkins Caitlin R. , Narayan Vivek , Haas Naomi B. , Frey Noelle V. , Hexner Elizabeth O. , Siegel Donald L. , Plesa Gabriela , Porter David L. , Cantu Adrian , Everett John K. , Guedan Sonia , Berger Shelley L. , Bushman Frederic D. , Herbst Friederike , Fraietta Joseph A.
Published: July 2023

Analysis of survival outcomes and EGR2 gene expression in CD19 CAR T-cell products. The figure presents the P values and hazard ratio of different EGR2 molecular marker stratification points in relation to A, overall survival and B, event-free survival The black arrows indicate the stratification points used in the study. C, EGR2-targeted gene expression scores in CD19 CAR T-cell products from responders and non-responders in pediatric ALL. D, Summary of how EGR2 regulates resistance to CAR T-cell therapy through the type I IFN pathway.
Figure S10 from Type I Interferon Signaling via the EGR2 Transcriptional Regulator Potentiates CAR T Cell–Intrinsic Dysfunction
Authors: Jung In-Young , Bartoszek Robert L. , Rech Andrew J. , Collins Sierra M. , Ooi Soon-Keat , Williams Erik F. , Hopkins Caitlin R. , Narayan Vivek , Haas Naomi B. , Frey Noelle V. , Hexner Elizabeth O. , Siegel Donald L. , Plesa Gabriela , Porter David L. , Cantu Adrian , Everett John K. , Guedan Sonia , Berger Shelley L. , Bushman Frederic D. , Herbst Friederike , Fraietta Joseph A.
Published: July 2023

EGR2 knockout enhances the long-term potency and memory function of CAR T-cells in vivo. A, Schematic of the tumor rechallenge experiments. B, Tumor growth after the first (left) and second (right) NALM6 challenges (Mann-Whitney test, n = 10). C, Mouse survival after high-dose second tumor challenge (Log-rank test). D, Tumor growth inhibition in a prostate cancer model using PSMA-targeting CAR T-cells with EGR2 or AAVS1 knockout (KO) compared to control CD19 CAR T-cells (19BBz). The tumor growth was monitored over time using caliper-based measurements in NSG mice (n = 8).
Supplementary Table S4 from Mitophagy Promotes Resistance to BH3 Mimetics in Acute Myeloid Leukemia
Authors: Glytsou Christina , Chen Xufeng , Zacharioudakis Emmanouil , Al-Santli Wafa , Zhou Hua , Nadorp Bettina , Lee Soobeom , Lasry Audrey , Sun Zhengxi , Papaioannou Dimitrios , Cammer Michael , Wang Kun , Zal Tomasz , Zal Malgorzata Anna , Carter Bing Z. , Ishizawa Jo , Tibes Raoul , Tsirigos Aristotelis , Andreeff Michael , Gavathiotis Evripidis , Aifantis Iannis
Published: July 2023

Supplementary Table S4 shows autophagy related genes and their ranking in NMF analysis of scRNAseq data.
Supplementary Table S3 from Mitophagy Promotes Resistance to BH3 Mimetics in Acute Myeloid Leukemia
Authors: Glytsou Christina , Chen Xufeng , Zacharioudakis Emmanouil , Al-Santli Wafa , Zhou Hua , Nadorp Bettina , Lee Soobeom , Lasry Audrey , Sun Zhengxi , Papaioannou Dimitrios , Cammer Michael , Wang Kun , Zal Tomasz , Zal Malgorzata Anna , Carter Bing Z. , Ishizawa Jo , Tibes Raoul , Tsirigos Aristotelis , Andreeff Michael , Gavathiotis Evripidis , Aifantis Iannis
Published: July 2023

Supplementary Table S3 shows the information of the AML patient samples used in this study.
Supplementary Methods from Mitophagy Promotes Resistance to BH3 Mimetics in Acute Myeloid Leukemia
Authors: Glytsou Christina , Chen Xufeng , Zacharioudakis Emmanouil , Al-Santli Wafa , Zhou Hua , Nadorp Bettina , Lee Soobeom , Lasry Audrey , Sun Zhengxi , Papaioannou Dimitrios , Cammer Michael , Wang Kun , Zal Tomasz , Zal Malgorzata Anna , Carter Bing Z. , Ishizawa Jo , Tibes Raoul , Tsirigos Aristotelis , Andreeff Michael , Gavathiotis Evripidis , Aifantis Iannis
Published: July 2023

Supplementary Methods, Tables, and References
Supplementary Figures 1-7 from Mitophagy Promotes Resistance to BH3 Mimetics in Acute Myeloid Leukemia
Authors: Glytsou Christina , Chen Xufeng , Zacharioudakis Emmanouil , Al-Santli Wafa , Zhou Hua , Nadorp Bettina , Lee Soobeom , Lasry Audrey , Sun Zhengxi , Papaioannou Dimitrios , Cammer Michael , Wang Kun , Zal Tomasz , Zal Malgorzata Anna , Carter Bing Z. , Ishizawa Jo , Tibes Raoul , Tsirigos Aristotelis , Andreeff Michael , Gavathiotis Evripidis , Aifantis Iannis
Published: July 2023

Supplemental Figure S1 shows the integration of CRISPR/Cas9 loss-of-function screens to identify dependencies and liabilities in BH3-mimetics treatments.
Supplemental Figure S2 demonstrates that increased mitochondria-ER interactions contribute to BH3-mimetics resistance.
Supplemental Figure S3 shows that mitophagy affects the responsiveness of AML cells to BH3-mimetics.
Supplemental Figure S4 reveals that enhanced autophagic clearance of mitochondria as a mechanism of resistance to BH3-mimetics in AML.
Supplemental Figure S5 exhibits the synergism between BH3-mimetics and macroautophagy inhibition in human AML.
Supplemental Figure S6 shows that deletion of MFN2 or MARCH5 sensitizes AML cells to BH3-mimetics.
Supplemental Figure S7 displays that targeting of MFN2 or MARCH5 impairs the process of mitophagy.
Table S6 from An African-Specific Variant of TP53 Reveals PADI4 as a Regulator of p53-Mediated Tumor Suppression
Authors: Indeglia Alexandra , Leung Jessica C. , Miller Sven A. , Leu Julia I-Ju , Dougherty James F. , Clarke Nicole L. , Kirven Nicole A. , Shao Chunlei , Ke Lei , Lovell Scott , Barnoud Thibaut , Lu David Y. , Lin Cindy , Kannan Toshitha , Battaile Kevin P. , Yang Tyler Hong Loong , Batista Oliva Isabela , Claiborne Daniel T. , Vogel Peter , Liu Lijun , Liu Qin , Nefedova Yulia , Cassel Joel , Auslander Noam , Kossenkov Andrew V. , Karanicolas John , Murphy Maureen E.
Published: July 2023

Key Reagents List for this study.
Table S5 from An African-Specific Variant of TP53 Reveals PADI4 as a Regulator of p53-Mediated Tumor Suppression
Authors: Indeglia Alexandra , Leung Jessica C. , Miller Sven A. , Leu Julia I-Ju , Dougherty James F. , Clarke Nicole L. , Kirven Nicole A. , Shao Chunlei , Ke Lei , Lovell Scott , Barnoud Thibaut , Lu David Y. , Lin Cindy , Kannan Toshitha , Battaile Kevin P. , Yang Tyler Hong Loong , Batista Oliva Isabela , Claiborne Daniel T. , Vogel Peter , Liu Lijun , Liu Qin , Nefedova Yulia , Cassel Joel , Auslander Noam , Kossenkov Andrew V. , Karanicolas John , Murphy Maureen E.
Published: July 2023

Secondary Validations of top drug hits from HCT116 WT vs Y107H clones.
Table S4 from An African-Specific Variant of TP53 Reveals PADI4 as a Regulator of p53-Mediated Tumor Suppression
Authors: Indeglia Alexandra , Leung Jessica C. , Miller Sven A. , Leu Julia I-Ju , Dougherty James F. , Clarke Nicole L. , Kirven Nicole A. , Shao Chunlei , Ke Lei , Lovell Scott , Barnoud Thibaut , Lu David Y. , Lin Cindy , Kannan Toshitha , Battaile Kevin P. , Yang Tyler Hong Loong , Batista Oliva Isabela , Claiborne Daniel T. , Vogel Peter , Liu Lijun , Liu Qin , Nefedova Yulia , Cassel Joel , Auslander Noam , Kossenkov Andrew V. , Karanicolas John , Murphy Maureen E.
Published: July 2023

Extra crystallographic data for p53Y107H.
Table S3 from An African-Specific Variant of TP53 Reveals PADI4 as a Regulator of p53-Mediated Tumor Suppression
Authors: Indeglia Alexandra , Leung Jessica C. , Miller Sven A. , Leu Julia I-Ju , Dougherty James F. , Clarke Nicole L. , Kirven Nicole A. , Shao Chunlei , Ke Lei , Lovell Scott , Barnoud Thibaut , Lu David Y. , Lin Cindy , Kannan Toshitha , Battaile Kevin P. , Yang Tyler Hong Loong , Batista Oliva Isabela , Claiborne Daniel T. , Vogel Peter , Liu Lijun , Liu Qin , Nefedova Yulia , Cassel Joel , Auslander Noam , Kossenkov Andrew V. , Karanicolas John , Murphy Maureen E.
Published: July 2023

Oligos for ChIP-qPCR and qPCR used in this study
Table S2 from An African-Specific Variant of TP53 Reveals PADI4 as a Regulator of p53-Mediated Tumor Suppression
Authors: Indeglia Alexandra , Leung Jessica C. , Miller Sven A. , Leu Julia I-Ju , Dougherty James F. , Clarke Nicole L. , Kirven Nicole A. , Shao Chunlei , Ke Lei , Lovell Scott , Barnoud Thibaut , Lu David Y. , Lin Cindy , Kannan Toshitha , Battaile Kevin P. , Yang Tyler Hong Loong , Batista Oliva Isabela , Claiborne Daniel T. , Vogel Peter , Liu Lijun , Liu Qin , Nefedova Yulia , Cassel Joel , Auslander Noam , Kossenkov Andrew V. , Karanicolas John , Murphy Maureen E.
Published: July 2023

Evaluating the association between AA, Y107H variant, and cancer risk.
Supplementary Tables 1-3, 7-9 from A Compendium of Syngeneic, Transplantable Pediatric High-Grade Glioma Models Reveals Subtype-Specific Therapeutic Vulnerabilities
Authors: McNicholas Michael , De Cola Antonella , Bashardanesh Zahedeh , Foss Amelia , Lloyd Cameron B. , Hébert Steven , Faury Damien , Andrade Augusto Faria , Jabado Nada , Kleinman Claudia L. , Pathania Manav
Published: July 2023

Tables describing statistical analyses, median survivals, IC50 values calculated from cell viability assays, primer sequences and antibodies.
Suppl. Table 7 from The DNA Damage Response and Inflammation in Cancer
Authors: Klapp Vanessa , Álvarez-Abril Beatriz , Leuzzi Giuseppe , Kroemer Guido , Ciccia Alberto , Galluzzi Lorenzo
Published: July 2023

Other DDR pathways in inflammation and cancer
Supplementary Figures 1-27 from A Compendium of Syngeneic, Transplantable Pediatric High-Grade Glioma Models Reveals Subtype-Specific Therapeutic Vulnerabilities
Authors: McNicholas Michael , De Cola Antonella , Bashardanesh Zahedeh , Foss Amelia , Lloyd Cameron B. , Hébert Steven , Faury Damien , Andrade Augusto Faria , Jabado Nada , Kleinman Claudia L. , Pathania Manav
Published: July 2023

Figures describing hindbrain vs ganglionic eminence targeting strategies, each of the 16 models generated and validation that they expressed the introduced mutations, survival of GE vs CTX-electroporated embryos, and cell viability data shown in bar graph format.
Suppl. Table 6 from The DNA Damage Response and Inflammation in Cancer
Authors: Klapp Vanessa , Álvarez-Abril Beatriz , Leuzzi Giuseppe , Kroemer Guido , Ciccia Alberto , Galluzzi Lorenzo
Published: July 2023

DDR signaling and inflammation in cancer
Figure 7 from A Compendium of Syngeneic, Transplantable Pediatric High-Grade Glioma Models Reveals Subtype-Specific Therapeutic Vulnerabilities
Authors: McNicholas Michael , De Cola Antonella , Bashardanesh Zahedeh , Foss Amelia , Lloyd Cameron B. , Hébert Steven , Faury Damien , Andrade Augusto Faria , Jabado Nada , Kleinman Claudia L. , Pathania Manav
Published: July 2023

A, Dose–response curves for the PI3K inhibitor alpelisib, the PDGFRAmutant inhibitor avapritinib, the LSD1/HDAC inhibitor corin, the KDM6A/B inhibitor GSK-J4, the MDM2 inhibitor idasanutlin, the NAMPT inhibitor FK866, the FGFR inhibitor infigratinib, and the MEK inhibitor trametinib, tested in mouse tumor-derived GS lines. Cells were treated for 3 days (avapritinib, FK-866, idasanutlin, trametinib) or 6 days (alpelisib, corin, GSK-J4, infigratinib) at the indicated concentrations. The most sensitive and the most resistant cell lines are highlighted with different colors and with dashed vs. solid lines. Means ± SD are plotted from at least n = 3 replicates. Statistics are summarized in Supplementary Table 7. B, Kaplan-Meier curves depicting survival of mice orthotopically injected with KPP cells and orally treated for 2 weeks with avapritinib vs. vehicle control. **, P < 0.01 was calculated using the log-rank Mantel-Cox test. Statistical comparisons are described in Supplementary Table 2. C, Dose–response curves for alpelisib and trametinib tested against patient-derived cell lines for 6 days at the indicated concentrations. Means ± SD are plotted from at least n = 3 replicates. Statistics are summarized in Supplementary Table 7. D, Cell viability assays using mouse GS cells and patient-derived cells following treatment with trametinib, alpelisib, and a combination of both drugs for 6 days at the indicated concentrations. Means ± SD are plotted from at least n = 3 replicates. ****, P < 0.0001; **, P < 0.01 were calculated using ordinary one-way ANOVA. Statistics are summarized in Supplementary Table 7. E, Left: representative fluorescence images of disseminating GFP+ tumor cells 12 days following engraftment, and 4 days following initiation of continuous intracranial delivery of alpelisib and trametinib vs. vehicle control. Scale bar, 1 mm. Right: the extent of dissemination and the size of GFP+ tumors following resection at 4 days after treatment. Means ± SD are plotted from at least n = 3 replicates. *, P < 0.05 was calculated using the Welch t test.
Figure 6 from A Compendium of Syngeneic, Transplantable Pediatric High-Grade Glioma Models Reveals Subtype-Specific Therapeutic Vulnerabilities
Authors: McNicholas Michael , De Cola Antonella , Bashardanesh Zahedeh , Foss Amelia , Lloyd Cameron B. , Hébert Steven , Faury Damien , Andrade Augusto Faria , Jabado Nada , Kleinman Claudia L. , Pathania Manav
Published: July 2023

A, Left: acid-extracted histone and protein lysates prepared from ex vivo GS lines derived from the two-hit de novo models (KP, H3.1KP, KF, and KN) were probed for K27M, K27me3, HA, and total H3.3 levels. NSCs derived from the LRL (LRL NSC) were used as controls. Middle: validation of FGFR1 overexpression in ex vivo KF cells; GAPDH was used as a loading control. Right: validation of p53 and NF1 downregulation in ex vivo cells by qRT-PCR. Data are presented as means ± SD from at least n = 3 replicates. ****, P < 0.0001 and ***, P = 0.0003 were calculated using unpaired t test and one-way ANOVA. B, Left: acid-extracted histone and protein lysates prepared from ex vivo GS lines derived from the three- and four-hit de novo models (KPP, KPD, KPAP, KPAD, KPPMPIK, H3.1KACVPIK, KNF, KPF, and KPC) were probed for K27M, K27me3, HA, and total H3.3 levels. LRL NSCs were used as controls. Validation of PDGFRA, PPM1D, PIK3CA, ACVR1, FGFR1, and CCND2 overexpression in ex vivo GS cells; GAPDH and tubulin were used as loading controls. Right: validation of p53, ATRX, and NF1 downregulation in ex vivo GS cells by qRT-PCR. Data are presented as means ± SD from at least n = 3 replicates. ****, P < 0.0001 and ***, P = 0.0003 were calculated using unpaired t test and one-way ANOVA. C, Left: IHC detection of hematoxylin and eosin (H&E), GFP, K27M, and Ki-67 in coronal hindbrain sections from orthotopically engrafted, symptomatic mice. Mice were injected in either the pons (H3K27M) or striatum (H3.3G34R) with 150,000 to 300,000 cells from each cell GS cell line (n = 5 mice per condition). Tumor cells are GFP+. Scale bars, 2 mm. Right: BLI of brainstem tumors in orthotopically engrafted C57BL/6J mice without shaving/depilation using Akaluc imaging. D, Kaplan–Meier curves depicting survival of mice orthotopically injected with GS cells derived from H3.3K27M (left), H3.1K27M (middle), and H3.3G34R (right) models. Note that the following samples are shown twice in A and B: LRL NSC, KF, and KN; these repetitions are indicated with an asterisk. The sole purpose of this repetition is to make it easier for the reader, by collating all the Western blot (WB) data describing the “two-hit” models in A and all the WB data describing the “three-hit or more” models in B.
Figure 5 from A Compendium of Syngeneic, Transplantable Pediatric High-Grade Glioma Models Reveals Subtype-Specific Therapeutic Vulnerabilities
Authors: McNicholas Michael , De Cola Antonella , Bashardanesh Zahedeh , Foss Amelia , Lloyd Cameron B. , Hébert Steven , Faury Damien , Andrade Augusto Faria , Jabado Nada , Kleinman Claudia L. , Pathania Manav
Published: July 2023

A, Top: penetrance of spinal dissemination in tumor-bearing mice harboring H3.3K27M, NF1LOF, and FGFR1N457K mutations compared with all other genotypes. Bottom: representative bright field (BF) and fluorescence (GFP) images of GFP+ tumor cells that have disseminated into the thoracic spinal cord. Scale bars, 1 mm. B, Top: penetrance of exophytic spread in tumor-bearing mice harboring FGFR1N457K, PIK3CAE545K, PPM1DΔC, and NF1LOF. Bottom: representative BF and fluorescence images showing exophytic spread (bottom left) or a lack of exophytic spread (bottom right) of GFP+ tumor cells. Scale bars, 1 mm. C, Top: penetrance of cranial nerve invasion in tumor-bearing KF, KPP, H3.1KACVPIK, and KPPMPIK mice. Bottom: representative BF and fluorescence images showing cranial nerve invasion of GFP+ tumor cells (indicated by white arrows). Scale bars, 1 mm. D, Analysis of the extent of invasion of H3.1/3K27M-driven tumors into different anatomic regions (CB, cerebellum; BS, brainstem). E, Immunofluorescence and quantification of Ki-67+/GFP+ cells in H3.1/3K27M- and H3.3G34R-driven tumors. GFP+ tumor cells have a mitotic index of 10 or higher. Data, mean ± SEM. Representative images showing DAPI, GFP, and Ki-67 immunofluorescence levels in a brainstem tumor are shown on the right. Scale bars, 50 μm. F, Quantification of H3K27me3 immunofluorescence signal intensity in HA+ nuclei in tumors. Data, mean ± SEM; ****, P < 0.0001 was calculated using the one-way ANOVA test. Representative images of H3K27me3 and HA staining in a brainstem tumor are shown on the right. Scale bars, 50 μm. a.u., arbitrary units.
Figure 4 from A Compendium of Syngeneic, Transplantable Pediatric High-Grade Glioma Models Reveals Subtype-Specific Therapeutic Vulnerabilities
Authors: McNicholas Michael , De Cola Antonella , Bashardanesh Zahedeh , Foss Amelia , Lloyd Cameron B. , Hébert Steven , Faury Damien , Andrade Augusto Faria , Jabado Nada , Kleinman Claudia L. , Pathania Manav
Published: July 2023

A, Mutation combinations represented in H3K27M models and the acronyms used to refer to them. B, IHC detection of hematoxylin and eosin (H&E), GFP, K27M, and Ki-67 in coronal hindbrain sections from tumor-bearing, symptomatic mice. Embryos were electroporated with vectors encoding (i) H3.3K27M, p53LOF (KP); (ii) H3.1K27M, p53LOF (H3.1KP); (iii) H3.3K27M, FGFR1N457K (KF); (iv) H3.3K27M, NF1LOF (KN); (v) H3.3K27M, p53LOF, FGFR1N457K (KPF); and (vi) H3.3K27M, p53LOF, CCND2WT (KPC). Tumor cells are GFP+. Higher magnification panels below each low-magnification panel are of the tumor bulk in the brainstem, i.e., pons and medulla, which are directly below the cerebellum and fourth ventricle. Scale bars, 2 mm in the low-magnification panels and 200 μm in the high-magnification panels. C, Kaplan–Meier survival curves of IUE, tumor-bearing mice carrying different combinations of mutations. KP (n = 6), H3.1KP (n = 6), KF (n = 10), KN (n = 7), KPF (n = 16), and KPC (n = 9). Statistical comparisons using the log-rank Mantel–Cox tests are described in Supplementary Table S2.
Figure 3 from A Compendium of Syngeneic, Transplantable Pediatric High-Grade Glioma Models Reveals Subtype-Specific Therapeutic Vulnerabilities
Authors: McNicholas Michael , De Cola Antonella , Bashardanesh Zahedeh , Foss Amelia , Lloyd Cameron B. , Hébert Steven , Faury Damien , Andrade Augusto Faria , Jabado Nada , Kleinman Claudia L. , Pathania Manav
Published: July 2023

A, Uniform manifold approximation and projection (UMAP) of KNF and KPP integration colored by cell type annotation summarized in Supplementary Table S5 (left) and by replicate (right). Cells that did not meet quality control thresholds, as determined from individual sample analysis, and cells with no cell type consensus are not plotted. OL, oligodendrocyte. B, Distribution of ssGSEA scores per cell for human tumor signatures in OPC-projected cells of KNF samples (top) and KPP samples (bottom). Signatures were derived from differential expression of bulk RNA-seq data for tumor subtypes (see Methods). N = 34,326 cells in KNF; N = 3,892 cells in KPP. C, UMAP as in A with cells colored by cluster. D, Predominant cell types per cluster of KNF and KPP integration (left), corresponding proportion of each genotype within the cluster (middle), and number of cells per cluster (right). Only cells passing QC and with a cell type consensus are considered. Cell types comprising at least 30% of the cluster are shown. ASTR, astrocyte. E, Proportion of cells per replicate annotated as OPC (left), microglia (middle), and macrophages (right). F, Proportion of cells with detected Mag (left) and Pdgfra (right). G, UMAPs of each replicate from individual sample analysis with cells colored by normalized expression of Myrf (left) and Cspg4 (right). H, Mean inferred TF activity scores (scaled) and percent of cells with activity of TF shown for clusters 0, 7, 10, and 2, with predominant cell types of OPC, proliferating OPC (P-OPC), newly forming oligodendrocytes (NFOL), and mature oligodendrocytes, respectively; cluster number is indicated in parenthesis. Representative TFs with differing activity patterns between genotypes are shown. I, Proportion of cells with detected Ptprc (left) and Ly86 (right). J, Mean expression of DAM signature genes in immune cluster 5, with cells grouped by genotype. P < 2.2e-16.
Supplementary Tables S1-S12 from Targeting N-linked Glycosylation for the Therapy of Aggressive Lymphomas
Authors: Scheich Sebastian , Chen Jiji , Liu Jiamin , Schnütgen Frank , Enssle Julius C. , Ceribelli Michele , Thomas Craig J. , Choi Jaewoo , Morris Vivian , Hsiao Tony , Nguyen Hang , Wang Boya , Bolomsky Arnold , Phelan James D. , Corcoran Sean , Urlaub Henning , Young Ryan M. , Häupl Björn , Wright George W. , Huang Da Wei , Ji Yanlong , Yu Xin , Xu Weihong , Yang Yandan , Zhao Hong , Muppidi Jagan , Pan Kuan-Ting , Oellerich Thomas , Staudt Louis M.
Published: July 2023

Table S1. Brunello library sgRNA normalized read counts of IRF4 sorted CRISPR screens. Table S2. Segregation score of IRF4 sorted CRISPR screens. Table S3. Glycoproteomics in STT3A or STT3B KO cells. Table S4. Brunello sgRNA Library Normalized Read Counts of CRISPR screens. Table S5. CRISPR screen score of essentiality screens. Table S6. Glycoproteomics after NGI-1 treatment. Table S7.HBL1 and TMD8 Phosphotyrosone Phosphoproteome (pYome). Table S8. TMD8 CD79A-BioID. Table S9. HBL1 CD22 BioID. Table S10. Brunello library sgRNA normalized read counts of NGI-1 drug modified screen (TMD8). Table S11. CRISPR screen score of NGI-1 drug modifier screen. Table S12. TMD8 Drug screen Excess HSA.