bluuebunny/crossref_metadata_2025 huggingface dataset:
Supplementary Figure S8 from Oncogenic drivers and therapeutic vulnerabilities in KRAS wild-type pancreatic cancer
Authors: Singh Harshabad , Keller Rachel B. , Kapner Kevin S. , Dilly Julien , Raghavan Srivatsan , Yuan Chen , Cohen Elizabeth F. , Tolstorukov Michael , Andrews Elizabeth , Brais Lauren K. , da Silva Annacarolina , Perez Kimberly , Rubinson Douglas A. , Surana Rishi , Giannakis Marios , Ng Kimmie , Clancy Thomas E. , Yurgelun Matthew B. , Schlechter Benjamin L. , Clark Jeffrey W. , Shapiro Geoffrey I. , Rosenthal Michael H. , Hornick Jason L. , Nardi Valentina , Li Yvonne Y. , Gupta Hersh , Cherniack Andrew D. , Meyerson Matthew , Cleary James M. , Nowak Jonathan A. , Wolpin Brian M. , Aguirre Andrew J.
Published: September 2024

Germline genetic analysis of KRAS WT versus KRAS mutant pancreatic cancer
Supplementary Figure S6 from Oncogenic drivers and therapeutic vulnerabilities in KRAS wild-type pancreatic cancer
Authors: Singh Harshabad , Keller Rachel B. , Kapner Kevin S. , Dilly Julien , Raghavan Srivatsan , Yuan Chen , Cohen Elizabeth F. , Tolstorukov Michael , Andrews Elizabeth , Brais Lauren K. , da Silva Annacarolina , Perez Kimberly , Rubinson Douglas A. , Surana Rishi , Giannakis Marios , Ng Kimmie , Clancy Thomas E. , Yurgelun Matthew B. , Schlechter Benjamin L. , Clark Jeffrey W. , Shapiro Geoffrey I. , Rosenthal Michael H. , Hornick Jason L. , Nardi Valentina , Li Yvonne Y. , Gupta Hersh , Cherniack Andrew D. , Meyerson Matthew , Cleary James M. , Nowak Jonathan A. , Wolpin Brian M. , Aguirre Andrew J.
Published: September 2024

MAPK amplifications are alternative drivers in KRAS WT pancreatic cancer
Supplementary Figure S10 from Oncogenic drivers and therapeutic vulnerabilities in KRAS wild-type pancreatic cancer
Authors: Singh Harshabad , Keller Rachel B. , Kapner Kevin S. , Dilly Julien , Raghavan Srivatsan , Yuan Chen , Cohen Elizabeth F. , Tolstorukov Michael , Andrews Elizabeth , Brais Lauren K. , da Silva Annacarolina , Perez Kimberly , Rubinson Douglas A. , Surana Rishi , Giannakis Marios , Ng Kimmie , Clancy Thomas E. , Yurgelun Matthew B. , Schlechter Benjamin L. , Clark Jeffrey W. , Shapiro Geoffrey I. , Rosenthal Michael H. , Hornick Jason L. , Nardi Valentina , Li Yvonne Y. , Gupta Hersh , Cherniack Andrew D. , Meyerson Matthew , Cleary James M. , Nowak Jonathan A. , Wolpin Brian M. , Aguirre Andrew J.
Published: September 2024

Additional clinicopathologic/genomic data for KRAS WT patient with SLC4A4-ROS1 fusion
Figure S1 from Randomized Trial of a Personalized Dendritic Cell Vaccine after Autologous Stem Cell Transplant for Multiple Myeloma
Authors: Chung David J. , Shah Nina , Wu Juan , Logan Brent , Bisharat Lina , Callander Natalie , Cheloni Giulia , Anderson Kenneth , Chodon Thinle , Dhakal Binod , Devine Steven , Somaiya Dutt Poorvi , Efebera Yvonne , Geller Nancy , Ghiasuddin Haider , Hematti Peiman , Holmberg Leona , Howard Alan , Johnson Bryon , Karagkouni Dimitra , Lazarus Hillard M. , Malek Ehsan , McCarthy Philip , McKenna David , Mendizabal Adam , Nooka Ajay , Munshi Nikhil , O'Donnell Lynn , Rapoport Aaron P. , Reese Jane , Rosenblatt Jacalyn , Soiffer Robert , Stroopinsky Dina , Uhl Lynne , Vlachos Ioannis S. , Waller Edmund K. , Young James W. , Pasquini Marcelo C. , Avigan David
Published: September 2024

Supplemental Figure 1: (A) Progression Free Survival Kaplan Meier Curve. (B) Overall Survival Kaplan Meier Curve.
Supplementary Data 1 from A Phase II Study of Optimized Individualized Adaptive Radiation Therapy for Hepatocellular Carcinoma
Authors: Herr Daniel J. , Wang Chang , Mendiratta-Lala Mishal , Matuszak Martha , Mayo Charles S. , Cao Yue , Parikh Neehar D. , Ten Haken Randy , Owen Dawn , Evans Joseph R. , Stanescu Teodor , Yan Michael , Dawson Laura A. , Schipper Matthew , Lawrence Theodore S. , Cuneo Kyle C.
Published: September 2024

Supplemental Tables
Supplementary Table 7 from Cancer-associated fibroblast-like tumor cells remodel the Ewing sarcoma tumor microenvironment
Authors: Wrenn Emma D. , Apfelbaum April A. , Rudzinski Erin R. , Deng Xuemei , Jiang Wei , Sud Sudha , Van Noord Raelene A. , Newman Erika A. , Garcia Nicolas M. , Miyaki Aya , Hoglund Virginia J. , Bhise Shruti S. , Kanaan Sami B. , Waltner Olivia G. , Furlan Scott N. , Lawlor Elizabeth R.
Published: September 2024

Supplemental Table 7. Clinical information and CD73 IHC score for patient tumor tissue microarray.
Supplementary Table S3 from Safety and Efficacy of Anlotinib Hydrochloride Plus Temozolomide in Patients with Recurrent Glioblastoma
Authors: Xu Qingsheng , Huang Kaiyuan , Meng Xiangqi , Weng Yuxiang , Zhang Luyuan , Bu Linghao , Zheng Xiujue , Cai Jinquan , Zhan Renya , Chen Qun
Published: September 2024

Supplementary Table S3. Summary of other trial results for recurrent glioblastoma.
Supplementary Figure S2 from Safety and Efficacy of Anlotinib Hydrochloride Plus Temozolomide in Patients with Recurrent Glioblastoma
Authors: Xu Qingsheng , Huang Kaiyuan , Meng Xiangqi , Weng Yuxiang , Zhang Luyuan , Bu Linghao , Zheng Xiujue , Cai Jinquan , Zhan Renya , Chen Qun
Published: September 2024

Axial, sagittal and coronal gadolinium-enhanced and FLAIR MRI at pre-baseline (A-D). Three months later, MRI demonstrated progressive disease after anlotinib plus temozolomide (E-H).
Figure S2 from Liquid biopsies with circulating plasma HPV–DNA measurements – a clinically applicable surveillance tool for HPV-positive oropharyngeal cancer patients
Authors: Jakobsen Kathrine K. , Bendtsen Simone K. , Pallisgaard Niels , Friborg Jeppe , Lelkaitis Giedrius , Grønhøj Christian , von Buchwald Christian
Published: September 2024

Figure S2: Copies of HPV DNA per ml plasma in the pretreatment sample in follow-up serial samples in patients with an HPV+ follow-up sample but with no clinical or radiological evidence of recurrence or residual disease. Red dots denote an HPV+ sample, black dots denote an HPV- sample measured by ddPCR. Size of yellow RT rectangle indicates time (days) of radiotherapy with curative intent.
Supplementary Tables S1-S5 from Novel Genomic Risk Stratification Model for Primary Gastrointestinal Stromal Tumors (GIST) in the Imatinib and Adjuvant Therapy Era
Authors: Dermawan Josephine K. , Kelly Ciara , Gao Zhidong , Smith Shaleigh , Jadeja Bhumika , Singer Samuel , Tap William D. , Chi Ping , Antonescu Cristina R.
Published: September 2024

Supplementary Table S1. Metastasis Frequencies by Traditional vs. Genomic Risk Stratification
Supplementary Table S2. List of gene level and chromosomal arm level genomic variables used in OncoCast.
Supplementary Table S3-S4. Frequencies of genomic alterations by OncoCast risk groups in primary gastric and small bowel GISTs.
Supplementary Table S5. Number and frequencies of specific KIT/PDGFRA mutations in primary localized gastric and small bowel GISTs.
Supplementary Figure S1 from Novel Genomic Risk Stratification Model for Primary Gastrointestinal Stromal Tumors (GIST) in the Imatinib and Adjuvant Therapy Era
Authors: Dermawan Josephine K. , Kelly Ciara , Gao Zhidong , Smith Shaleigh , Jadeja Bhumika , Singer Samuel , Tap William D. , Chi Ping , Antonescu Cristina R.
Published: September 2024

Supplementary Figure 1. Traditional risk stratification in primary gastric and small bowel GIST.
Primary gastric (A-C) and small bowel (D-F) GISTs localized at diagnosis without prior neoadjuvant treatment are risk stratified into low, moderate, and high risk groups based on site, tumor size and mitotic rate using the Miettinen (also includes very low risk) (A, D), Fletcher (B, E) and Joensuu (C, F) risk stratification schemes (Miettinen 2006, Fletcher 2002, Joensuu 2008). Recurrence-free survival for patients in each of these risk groups is represented by Kaplan-Meier curves (global log-rank P) for all primary localized cases.
Supplementary Data 1 from Unique spectrum of activating BRAF alterations in prostate cancer
Authors: Chehrazi-Raffle Alex , Tukachinsky Hanna , Toye Eamon , Sivakumar Smruthy , Schrock Alexa B. , Bergom Hannah E. , Ebrahimi Hedyeh , Pal Sumanta , Dorff Tanya , Agarwal Neeraj , Mahal Brandon A. , Oxnard Geoffrey R. , Hwang Justin , Antonarakis Emmanuel S.
Published: September 2024

Supplementary Data
Supplementary Table S8 from Baseline mutations and ctDNA dynamics as prognostic and predictive factors in ER-positive/HER2-negative metastatic breast cancer patients
Authors: Pascual Javier , Gil-Gil Miguel , Proszek Paula , Zielinski Christoph , Reay Alistair , Ruiz-Borrego Manuel , Cutts Rosalind , Ciruelos Gil Eva M. , Feber Andrew , Muñoz-Mateu Montserrat , Swift Claire , Bermejo Begoña , Herranz Jesus , Margeli Vila Mireia , Antón Antonio , Kahan Zsuzsanna , Csöszi Tibor , Liu Yuan , Fernandez Garcia Daniel , Garcia-Murillas Isaac , Hubank Michael , Turner Nicholas C. , Martín Miguel
Published: September 2024

Supplementary Table 8. Summary of baseline ESR1 and PIK3CA mutations, with number of affected patients and mean VAF.
Supplementary Table S1 from Baseline mutations and ctDNA dynamics as prognostic and predictive factors in ER-positive/HER2-negative metastatic breast cancer patients
Authors: Pascual Javier , Gil-Gil Miguel , Proszek Paula , Zielinski Christoph , Reay Alistair , Ruiz-Borrego Manuel , Cutts Rosalind , Ciruelos Gil Eva M. , Feber Andrew , Muñoz-Mateu Montserrat , Swift Claire , Bermejo Begoña , Herranz Jesus , Margeli Vila Mireia , Antón Antonio , Kahan Zsuzsanna , Csöszi Tibor , Liu Yuan , Fernandez Garcia Daniel , Garcia-Murillas Isaac , Hubank Michael , Turner Nicholas C. , Martín Miguel
Published: September 2024

Supplementary Table 1. List of the 21 genes included in the breast cancer panel used for sequencing, and the targeted coding regions in each case.
Supplementary Figure S1 from Baseline mutations and ctDNA dynamics as prognostic and predictive factors in ER-positive/HER2-negative metastatic breast cancer patients
Authors: Pascual Javier , Gil-Gil Miguel , Proszek Paula , Zielinski Christoph , Reay Alistair , Ruiz-Borrego Manuel , Cutts Rosalind , Ciruelos Gil Eva M. , Feber Andrew , Muñoz-Mateu Montserrat , Swift Claire , Bermejo Begoña , Herranz Jesus , Margeli Vila Mireia , Antón Antonio , Kahan Zsuzsanna , Csöszi Tibor , Liu Yuan , Fernandez Garcia Daniel , Garcia-Murillas Isaac , Hubank Michael , Turner Nicholas C. , Martín Miguel
Published: September 2024

Supplementary Figure 1. Survival analysis in baseline population (C1D1).
Supplementary Figure S2 from Prognostic markers of DNA methylation and NGS sequencing in progressive glioblastoma from the EORTC-26101 trial
Authors: Kessler Tobias , Schrimpf Daniel , Doerner Laura , Hai Ling , Kaulen Leon D. , Ito Jakob , van den Bent Martin , Taphoorn Martin , Brandes Alba A. , Idbaih Ahmed , Dômont Julien , Clement Paul M. , Campone Mario , Bendszus Martin , von Deimling Andreas , Sahm Felix , Platten Michael , Wick Wolfgang , Wick Antje
Published: September 2024

Supplementary Figure 2: Overall (A) and progression-free (B) survival in the EORTC-26101 clinical study (n = 596) and EORTC-26101 biomarker cohort (n = 380).
Supplementary Figure S1 from Prognostic markers of DNA methylation and NGS sequencing in progressive glioblastoma from the EORTC-26101 trial
Authors: Kessler Tobias , Schrimpf Daniel , Doerner Laura , Hai Ling , Kaulen Leon D. , Ito Jakob , van den Bent Martin , Taphoorn Martin , Brandes Alba A. , Idbaih Ahmed , Dômont Julien , Clement Paul M. , Campone Mario , Bendszus Martin , von Deimling Andreas , Sahm Felix , Platten Michael , Wick Wolfgang , Wick Antje
Published: September 2024

Supplementary Figure 1: Overview of the clinical trial and biomarker analysis. Out of 596 patients in the EORTC-26101 trial, patient tumor tissue to perform DNA methylation (Meth) and NGS sequencing analysis was available from 380 patients (63.8%). Of these, 99 patients treated with lomustine and 189 patients treated with lomustine and bevacizumab were eligible to detect biomarkers for bevacizumab response.
Supplementary Table S1 from A pilot study omitting radiation in the treatment of children with newly diagnosed Wnt-activated medulloblastoma
Authors: Cohen Kenneth J. , Munjapara Vasu , Aguilera Dolly , Castellino Robert C. , Stapleton Stacie L. , Landi Daniel , Ashley David M. , Rodriguez Fausto J. , Hawkins Cynthia , Yang Edward , London Wendy , Chi Susan , Bandopadhayay Pratiti
Published: September 2024

Detailed mutations
Supplementary Table S4 from Integrated genomic and transcriptomic analysis improves disease classification and risk stratification of MDS with ring sideroblasts.
Authors: Todisco Gabriele , Creignou Maria , Bernard Elsa , Björklund Ann-Charlotte , Moura Pedro Luis. , Tesi Bianca , Mortera Blanco Teresa , Sander Birgitta , Jansson Monika , Walldin Gunilla , Barbosa Indira , Reinsbach Susanne E. , Hofman Isabel Juliana. , Nilsson Christer , Yoshizato Tetsuichi , Dimitriou Marios , Chang David , Olafsdottir Svanhildur , Venckute Larsson Sigita , Tobiasson Magnus , Malcovati Luca , Woll Petter , Jacobsen Sten-Eirik W. , Papaemmanuil Elli , Hellström-Lindberg Eva
Published: September 2024

Variables significant for survival analysis in univariate analysis
Supplementary Results S1 from Integrated genomic and transcriptomic analysis improves disease classification and risk stratification of MDS with ring sideroblasts.
Authors: Todisco Gabriele , Creignou Maria , Bernard Elsa , Björklund Ann-Charlotte , Moura Pedro Luis. , Tesi Bianca , Mortera Blanco Teresa , Sander Birgitta , Jansson Monika , Walldin Gunilla , Barbosa Indira , Reinsbach Susanne E. , Hofman Isabel Juliana. , Nilsson Christer , Yoshizato Tetsuichi , Dimitriou Marios , Chang David , Olafsdottir Svanhildur , Venckute Larsson Sigita , Tobiasson Magnus , Malcovati Luca , Woll Petter , Jacobsen Sten-Eirik W. , Papaemmanuil Elli , Hellström-Lindberg Eva
Published: September 2024

Supplementary Results
Supplementary Figure S8 from Integrated genomic and transcriptomic analysis improves disease classification and risk stratification of MDS with ring sideroblasts.
Authors: Todisco Gabriele , Creignou Maria , Bernard Elsa , Björklund Ann-Charlotte , Moura Pedro Luis. , Tesi Bianca , Mortera Blanco Teresa , Sander Birgitta , Jansson Monika , Walldin Gunilla , Barbosa Indira , Reinsbach Susanne E. , Hofman Isabel Juliana. , Nilsson Christer , Yoshizato Tetsuichi , Dimitriou Marios , Chang David , Olafsdottir Svanhildur , Venckute Larsson Sigita , Tobiasson Magnus , Malcovati Luca , Woll Petter , Jacobsen Sten-Eirik W. , Papaemmanuil Elli , Hellström-Lindberg Eva
Published: September 2024

Unsupervised consensus clustering analysis on gene expression data. Consensus clustering applied to the MDSRS+ cohort revealed 3 transcriptomic profiles, named EMK, INT and IMP according to the results from gene set enrichment analysis.
Supplementary Figure S19 from Integrated genomic and transcriptomic analysis improves disease classification and risk stratification of MDS with ring sideroblasts.
Authors: Todisco Gabriele , Creignou Maria , Bernard Elsa , Björklund Ann-Charlotte , Moura Pedro Luis. , Tesi Bianca , Mortera Blanco Teresa , Sander Birgitta , Jansson Monika , Walldin Gunilla , Barbosa Indira , Reinsbach Susanne E. , Hofman Isabel Juliana. , Nilsson Christer , Yoshizato Tetsuichi , Dimitriou Marios , Chang David , Olafsdottir Svanhildur , Venckute Larsson Sigita , Tobiasson Magnus , Malcovati Luca , Woll Petter , Jacobsen Sten-Eirik W. , Papaemmanuil Elli , Hellström-Lindberg Eva
Published: September 2024

Prognostic effect of genomic and transcriptomic analyses on MDSRS+ outcome. Overall survival (OS) stratified by genomic (A), transcriptomic classification (B) and estimated MEP percentage (C) in all MDSRS+ (A-C) and MDS-RS-SLD/MLD only (D-F). Multivariable Cox proportional hazard model for OS in all MDSRS+ including age, IPSS-mol score and estimated MEP percentage as continuous variables (G). OS stratified by estimated MEP percentage and IPSS-mol risk category (full representation of the 6 IPSS-mol categories shown in Supplemental Figure 21B).
Supplementary Figure S7 from Single-cell RNA analysis reveals cell-intrinsic functions of CAR-T cells correlating with response in a phase II study of lymphoma patients
Authors: Sarén Tina , Ramachandran Mohanraj , Gammelgård Gustav , Lövgren Tanja , Mirabello Claudio , Björklund Åsa K. , Wikström Kristina , Hashemi Jamileh , Freyhult Eva , Ahlström Håkan , Amini Rose-Marie , Hagberg Hans , Loskog Angelica , Enblad Gunilla , Essand Magnus
Published: September 2024

Supplementary Figure S7. Cluster specifications of single-cell RNA sequenced CAR-T infusion
products
Supplementary Figure S1 from Single-cell RNA analysis reveals cell-intrinsic functions of CAR-T cells correlating with response in a phase II study of lymphoma patients
Authors: Sarén Tina , Ramachandran Mohanraj , Gammelgård Gustav , Lövgren Tanja , Mirabello Claudio , Björklund Åsa K. , Wikström Kristina , Hashemi Jamileh , Freyhult Eva , Ahlström Håkan , Amini Rose-Marie , Hagberg Hans , Loskog Angelica , Enblad Gunilla , Essand Magnus
Published: September 2024

Supplementary Figure S1. CRP level before CAR-T infusion influence response
Supplementary Data 1 from Depth of radiographic response (DpR) and time to tumor regrowth (TTG) predicts overall survival following anti-VEGF therapy in recurrent glioblastoma
Authors: Ellingson Benjamin M. , Hagiwara Akifumi , Morris Connor J. , Cho Nicholas S. , Oshima Sonoko , Sanvito Francesco , Oughourlian Talia C. , Telesca Donatello , Raymond Catalina , Abrey Lauren E. , Garcia Josep , Aftab Dana T. , Hessel Colin , Rachmilewitz Minei Tamar , Harats Dror , Nathanson David A. , Wen Patrick Y. , Cloughesy Timothy F.
Published: September 2024

Supplemental Tables S1-S5
Supplementary Figure 1 from Efficacy and safety of stereotactic body radiotherapy combined with Camrelizumab and Apatinib in hepatocellular carcinoma patients with portal vein tumor thrombus
Authors: Hu Yue , Zhou Min , Tang Jing , Li Shuang , Liu Hongli , Hu Jianli , Ma Hong , Liu Junli , Qin Tingting , Yu Xiongjie , Chen Yongshun , Peng Jin , Zou Yanmei , Zhang Tao , Xue Jun
Published: September 2024

Supplementary Figure 1. Study time frame.
Supplementary Figure S7 from Memory-like differentiation, tumor targeting monoclonal antibodies, and chimeric antigen receptors enhance natural killer cell responses to head and neck cancer
Authors: Jacobs Miriam T. , Wong Pamela , Zhou Alice Y. , Becker-Hapak Michelle , Marin Nancy D. , Marsala Lynne , Foster Mark , Foltz Jennifer A. , Cubitt Celia C. , Tran Jennifer , Russler-Germain David A. , Neal Carly , Kersting-Schadek Samantha , Chang Lily , Schappe Timothy , Pence Patrick , McClain Ethan , Zevallos Jose P. , Rich Jason T. , Paniello Randal C. , Jackson Ryan S. , Pipkorn Patrik , Adkins Douglas R. , DeSelm Carl J. , Berrien-Elliott Melissa M. , Puram Sidharth V. , Fehniger Todd A.
Published: September 2024

Supplementary Figure 7. EphA2-CAR-ML NK cells require intracellular CAR signaling and have antigen specific enhanced response to HNSCC.
Supplementary Figure S5 from Memory-like differentiation, tumor targeting monoclonal antibodies, and chimeric antigen receptors enhance natural killer cell responses to head and neck cancer
Authors: Jacobs Miriam T. , Wong Pamela , Zhou Alice Y. , Becker-Hapak Michelle , Marin Nancy D. , Marsala Lynne , Foster Mark , Foltz Jennifer A. , Cubitt Celia C. , Tran Jennifer , Russler-Germain David A. , Neal Carly , Kersting-Schadek Samantha , Chang Lily , Schappe Timothy , Pence Patrick , McClain Ethan , Zevallos Jose P. , Rich Jason T. , Paniello Randal C. , Jackson Ryan S. , Pipkorn Patrik , Adkins Douglas R. , DeSelm Carl J. , Berrien-Elliott Melissa M. , Puram Sidharth V. , Fehniger Todd A.
Published: September 2024

Supplementary Figure 5. Expression of EphA2 on target cells and gating strategy for CAR-expressing NK cells
Supplementary Figure S3 from Memory-like differentiation, tumor targeting monoclonal antibodies, and chimeric antigen receptors enhance natural killer cell responses to head and neck cancer
Authors: Jacobs Miriam T. , Wong Pamela , Zhou Alice Y. , Becker-Hapak Michelle , Marin Nancy D. , Marsala Lynne , Foster Mark , Foltz Jennifer A. , Cubitt Celia C. , Tran Jennifer , Russler-Germain David A. , Neal Carly , Kersting-Schadek Samantha , Chang Lily , Schappe Timothy , Pence Patrick , McClain Ethan , Zevallos Jose P. , Rich Jason T. , Paniello Randal C. , Jackson Ryan S. , Pipkorn Patrik , Adkins Douglas R. , DeSelm Carl J. , Berrien-Elliott Melissa M. , Puram Sidharth V. , Fehniger Todd A.
Published: September 2024

Supplementary Figure 3. Individual blockade of DNAM-1, NKG2D and CD2 modestly impairs NK cell activity against HNSCC.
Supplementary Figure S2 from Memory-like differentiation, tumor targeting monoclonal antibodies, and chimeric antigen receptors enhance natural killer cell responses to head and neck cancer
Authors: Jacobs Miriam T. , Wong Pamela , Zhou Alice Y. , Becker-Hapak Michelle , Marin Nancy D. , Marsala Lynne , Foster Mark , Foltz Jennifer A. , Cubitt Celia C. , Tran Jennifer , Russler-Germain David A. , Neal Carly , Kersting-Schadek Samantha , Chang Lily , Schappe Timothy , Pence Patrick , McClain Ethan , Zevallos Jose P. , Rich Jason T. , Paniello Randal C. , Jackson Ryan S. , Pipkorn Patrik , Adkins Douglas R. , DeSelm Carl J. , Berrien-Elliott Melissa M. , Puram Sidharth V. , Fehniger Todd A.
Published: September 2024

Supplementary Figure 2. HNSCC cell lines and patient samples express multiple inhibitory and activating surface ligands.
Table S2 from HDACi-dependent microenvironmental normalization overcomes tumor burden-induced T-cell exhaustion
Authors: Nguyen Andrew , Brown Dominique , Krishnan Ramya , Bastin Donald , Deng Li , Chen Lan , Salem Omar , Walsh Scott R. , Bramson Jonathan L. , Wan Yonghong
Published: September 2024

Table S2: Overrepresented GO terms associated with Module 2 (M2)
Table S1 from HDACi-dependent microenvironmental normalization overcomes tumor burden-induced T-cell exhaustion
Authors: Nguyen Andrew , Brown Dominique , Krishnan Ramya , Bastin Donald , Deng Li , Chen Lan , Salem Omar , Walsh Scott R. , Bramson Jonathan L. , Wan Yonghong
Published: September 2024

Table S1: Gene lists of T cell signatures
Supplementary Figure S1 from Immune marker spatial distribution and clinical outcome after PD-1 blockade in mismatch repair-deficient, advanced colorectal carcinomas
Authors: Saberzadeh-Ardestani Bahar , Graham Rondell P. , McMahon Sara , Ahanonu Eze , Shi Qian , Williams Crystal , Hubbard Antony , Zhang Wenjun , Muranyi Andrea , Yan Dongyao , Jin Zhaohui , Shanmugam Kandavel , Sinicrope Frank A.
Published: September 2024

Supplementary Figure S1. PD-L1 (green) was expressed in (A) CD3+ T lymphocytes (magenta/pink), (B) CD68+ macrophages (red), panCK+ (cyan/light blue) tumor cells, and (C) tumor cells (red). PD-1 expression on CD8+ T lymphocytes was also observed.
Supplementary Figure S1 from Negative Predictive Value of Circulating Tumor Tissue Modified Viral (TTMV)-HPV DNA for HPV-driven Oropharyngeal Cancer Surveillance
Authors: Hanna Glenn J. , Roof Scott A. , Jabalee James , Rettig Eleni M. , Ferrandino Rocco , Chen Sida , Posner Marshall R. , Misiukiewicz Krzysztof J. , Genden Eric M. , Chai Raymond L. , Sims John , Thrash Elaine , Stern Scott J. , Kalman Noah S. , Yarlagadda Sreenija , Raben Adam , Clements Lydia , Mendelsohn Abie , Kaczmar John M. , Pandey Yadav , Bhayani Mihir K. , Gupta Piyush , Kuperwasser Charlotte , Del Vecchio Fitz Catherine , Berger Barry M.
Published: September 2024

Supplementary Figure S1: Case examples of false negative TTMV-HPV DNA results identified during surveillance
Supplementary Table S3 from SPOP mutations target STING1 signaling in prostate cancer and create therapeutic vulnerabilities to PARP inhibitor–induced growth suppression
Authors: Geng Chuandong , Zhang Man-Chao , Manyam Ganiraju C. , Vykoukal Jody V. , Fahrmann Johannes F. , Peng Shan , Wu Cheng , Park Sanghee , Kondraganti Shakuntala , Wang Daoqi , Robinson Brian D. , Loda Massimo , Barbieri Christopher E. , Yap Timothy A. , Corn Paul G. , Hanash Samir , Broom Bradley M. , Pilie Patrick G. , Thompson Timothy C.
Published: September 2024

Supplementary Table S3. Complete listing of antibodies used for immunoblotting (IB) and immunostaining analysis (Fig. 6C, 6D and Extended Data Fig. 5, 6). Vendor and catalog numbers are included in the list.
Supplementary Table S2 from SPOP mutations target STING1 signaling in prostate cancer and create therapeutic vulnerabilities to PARP inhibitor–induced growth suppression
Authors: Geng Chuandong , Zhang Man-Chao , Manyam Ganiraju C. , Vykoukal Jody V. , Fahrmann Johannes F. , Peng Shan , Wu Cheng , Park Sanghee , Kondraganti Shakuntala , Wang Daoqi , Robinson Brian D. , Loda Massimo , Barbieri Christopher E. , Yap Timothy A. , Corn Paul G. , Hanash Samir , Broom Bradley M. , Pilie Patrick G. , Thompson Timothy C.
Published: September 2024

Supplementary Table S2. Listing of protein features differentially expressed in Dox-inducible SPOPmut (F102C and F133V) C4-2b prostate cancer cells compared to C4-2b vector control shown in Fig. 2A upper panel
Supplementary Table S13 from SPOP mutations target STING1 signaling in prostate cancer and create therapeutic vulnerabilities to PARP inhibitor–induced growth suppression
Authors: Geng Chuandong , Zhang Man-Chao , Manyam Ganiraju C. , Vykoukal Jody V. , Fahrmann Johannes F. , Peng Shan , Wu Cheng , Park Sanghee , Kondraganti Shakuntala , Wang Daoqi , Robinson Brian D. , Loda Massimo , Barbieri Christopher E. , Yap Timothy A. , Corn Paul G. , Hanash Samir , Broom Bradley M. , Pilie Patrick G. , Thompson Timothy C.
Published: September 2024

Supplementary Table S13. Quantification of each protein-specific band normalized to vinculin (macrophage cells (RAW264.7) mono- or cocultured with RM-1-BM EV or SPOPmut models under treatment with OLA, Fig. 5E).
Supplementary Table S11 from SPOP mutations target STING1 signaling in prostate cancer and create therapeutic vulnerabilities to PARP inhibitor–induced growth suppression
Authors: Geng Chuandong , Zhang Man-Chao , Manyam Ganiraju C. , Vykoukal Jody V. , Fahrmann Johannes F. , Peng Shan , Wu Cheng , Park Sanghee , Kondraganti Shakuntala , Wang Daoqi , Robinson Brian D. , Loda Massimo , Barbieri Christopher E. , Yap Timothy A. , Corn Paul G. , Hanash Samir , Broom Bradley M. , Pilie Patrick G. , Thompson Timothy C.
Published: September 2024

Supplemental Table S11. Quantification of each protein-specific band normalized to vinculin (C4-2b–derived models, Fig. 4E).
Supplementary Figure S7 from SPOP mutations target STING1 signaling in prostate cancer and create therapeutic vulnerabilities to PARP inhibitor–induced growth suppression
Authors: Geng Chuandong , Zhang Man-Chao , Manyam Ganiraju C. , Vykoukal Jody V. , Fahrmann Johannes F. , Peng Shan , Wu Cheng , Park Sanghee , Kondraganti Shakuntala , Wang Daoqi , Robinson Brian D. , Loda Massimo , Barbieri Christopher E. , Yap Timothy A. , Corn Paul G. , Hanash Samir , Broom Bradley M. , Pilie Patrick G. , Thompson Timothy C.
Published: September 2024

Supplementary Fig. S7. Original unedited IB images for representative Western blots experiments (n-2) used in Supplementary Figure S6.
Supplementary Figure S3 from SPOP mutations target STING1 signaling in prostate cancer and create therapeutic vulnerabilities to PARP inhibitor–induced growth suppression
Authors: Geng Chuandong , Zhang Man-Chao , Manyam Ganiraju C. , Vykoukal Jody V. , Fahrmann Johannes F. , Peng Shan , Wu Cheng , Park Sanghee , Kondraganti Shakuntala , Wang Daoqi , Robinson Brian D. , Loda Massimo , Barbieri Christopher E. , Yap Timothy A. , Corn Paul G. , Hanash Samir , Broom Bradley M. , Pilie Patrick G. , Thompson Timothy C.
Published: September 2024

Supplementary Fig. S3. Original unedited IB images for representative Western blots experiments (n-3) used in Figure 3A.
Supplementary Figure S20 from SPOP mutations target STING1 signaling in prostate cancer and create therapeutic vulnerabilities to PARP inhibitor–induced growth suppression
Authors: Geng Chuandong , Zhang Man-Chao , Manyam Ganiraju C. , Vykoukal Jody V. , Fahrmann Johannes F. , Peng Shan , Wu Cheng , Park Sanghee , Kondraganti Shakuntala , Wang Daoqi , Robinson Brian D. , Loda Massimo , Barbieri Christopher E. , Yap Timothy A. , Corn Paul G. , Hanash Samir , Broom Bradley M. , Pilie Patrick G. , Thompson Timothy C.
Published: September 2024

Supplementary Fig. S20. Immunofluorescence staining analysis of PARP1 in C4-2b-empty vector and C4-2b-SPOPF133V xenograft tumors treated with talazoparib (TALA) or control vehicle
Supplementary Figure S19 from SPOP mutations target STING1 signaling in prostate cancer and create therapeutic vulnerabilities to PARP inhibitor–induced growth suppression
Authors: Geng Chuandong , Zhang Man-Chao , Manyam Ganiraju C. , Vykoukal Jody V. , Fahrmann Johannes F. , Peng Shan , Wu Cheng , Park Sanghee , Kondraganti Shakuntala , Wang Daoqi , Robinson Brian D. , Loda Massimo , Barbieri Christopher E. , Yap Timothy A. , Corn Paul G. , Hanash Samir , Broom Bradley M. , Pilie Patrick G. , Thompson Timothy C.
Published: September 2024

Supplementary Fig. S19. Heatmaps of common differentially expressed genes in co-cultured and mono-cultured prostate cancer model tumor cells demonstrating significant (FDR < 0.05) interaction between treatment [OLA or vehicle control (DMSO)] and SPOP phenotype (RM-1-BM-SPOPF133V mutant–expressing prostate cancer cells w/ or w/o RAW264.7 macrophage cocultured).
Supplementary Figure S11 from SPOP mutations target STING1 signaling in prostate cancer and create therapeutic vulnerabilities to PARP inhibitor–induced growth suppression
Authors: Geng Chuandong , Zhang Man-Chao , Manyam Ganiraju C. , Vykoukal Jody V. , Fahrmann Johannes F. , Peng Shan , Wu Cheng , Park Sanghee , Kondraganti Shakuntala , Wang Daoqi , Robinson Brian D. , Loda Massimo , Barbieri Christopher E. , Yap Timothy A. , Corn Paul G. , Hanash Samir , Broom Bradley M. , Pilie Patrick G. , Thompson Timothy C.
Published: September 2024

Supplementary Fig. S11. Original unedited IB images for representative Western blots experiments (n-2) used in Figure 3F.
Supplementary Table S7 from Integrating Multisector Molecular Characterization into Personalized Peptide Vaccine Design for Patients with Newly Diagnosed Glioblastoma
Authors: Johanns Tanner M. , Garfinkle Elizabeth A.R. , Miller Katherine E. , Livingstone Alexandra J. , Roberts Kaleigh F. , Rao Venkata Lakshmi P. , Dowling Joshua L. , Chicoine Michael R. , Dacey Ralph G. , Zipfel Gregory J. , Kim Albert H. , Mardis Elaine R. , Dunn Gavin P.
Published: September 2024

RNA-sequencing pseudo counts generated via Salmon algorithm
Supplementary Table S3 from Integrating Multisector Molecular Characterization into Personalized Peptide Vaccine Design for Patients with Newly Diagnosed Glioblastoma
Authors: Johanns Tanner M. , Garfinkle Elizabeth A.R. , Miller Katherine E. , Livingstone Alexandra J. , Roberts Kaleigh F. , Rao Venkata Lakshmi P. , Dowling Joshua L. , Chicoine Michael R. , Dacey Ralph G. , Zipfel Gregory J. , Kim Albert H. , Mardis Elaine R. , Dunn Gavin P.
Published: September 2024

pVAC-Seq predicted neoantigens for each subject and each tumor region from whole exome sequencing data
Supplementary Table S4 from Phase I Study of GS-3583, an FMS-like Tyrosine Kinase 3 Agonist Fc Fusion Protein, in Patients with Advanced Solid Tumors
Authors: Tolcher Anthony W. , Brody Joshua D. , Rajakumaraswamy Nishanthan , Kuhne Michelle , Trowe Torsten , Dauki Anees M. , Pai Shantheri , Han Ling , Lin Kai-Wen , Petrarca Michael , Kummar Shivaani
Published: September 2024

ADA prevalence and incidence rate.
Supplementary Table S3 from Phase I Study of GS-3583, an FMS-like Tyrosine Kinase 3 Agonist Fc Fusion Protein, in Patients with Advanced Solid Tumors
Authors: Tolcher Anthony W. , Brody Joshua D. , Rajakumaraswamy Nishanthan , Kuhne Michelle , Trowe Torsten , Dauki Anees M. , Pai Shantheri , Han Ling , Lin Kai-Wen , Petrarca Michael , Kummar Shivaani
Published: September 2024

CHIP mutations detected using QBDA.
Supplementary Table S1 from Phase I Study of GS-3583, an FMS-like Tyrosine Kinase 3 Agonist Fc Fusion Protein, in Patients with Advanced Solid Tumors
Authors: Tolcher Anthony W. , Brody Joshua D. , Rajakumaraswamy Nishanthan , Kuhne Michelle , Trowe Torsten , Dauki Anees M. , Pai Shantheri , Han Ling , Lin Kai-Wen , Petrarca Michael , Kummar Shivaani
Published: September 2024

Gene panel used in NGS.
Data from Efficacy of osimertinib in patients with lung cancer positive for uncommon EGFR exon 19 deletion mutations
Authors: Grant Michael J. , Aredo Jacqueline V. , Starrett Jacqueline H. , Stockhammer Paul , van Alderwerelt van Rosenburgh Iris K. , Wurtz Anna , Piper-Valillo Andrew J. , Piotrowska Zofia , Falcon Christina , Yu Helena A. , Aggarwal Charu , Scholes Dylan , Patil Tejas , Nguyen Christina , Phadke Manali , Li Fang-yong , Neal Joel , Lemmon Mark A. , Walther Zenta , Politi Katerina , Goldberg Sarah B.
Published: September 2024

Abstract
Purpose: The uncommon EGFR exon 19 deletion (ex19del), L747_A750>P, demonstrates reduced sensitivity to osimertinib compared to the common ex19del, E746_A750del in preclinical models. The clinical efficacy of osimertinib in patients with non-small cell lung cancer (NSCLC) harboring L747_A750>P and other uncommon ex19dels is not known. Design: The AACR GENIE database was interrogated to characterize the frequency of individual ex19dels relative to other variants, and a multi-center retrospective cohort was used to compare clinical outcomes for patients with tumors harboring E746_A750del, L747_A750>P, and other uncommon ex19dels who received osimertinib in the first line (1L) or in second or later lines of therapy and were T790M+ (≥2L). Results: Ex19dels comprised 45% of EGFR mutations, with 72 distinct variants ranging in frequency from 28.1% (E746_A750del) to 0.03%, with L747_A750>P representing 1.8% of the EGFR mutant cohort. In our multi-institution cohort (N=200), E746_A750del was associated with significantly prolonged progression free survival (PFS) with 1L osimertinib vs. L747_A750>P (median 21.3 months [95% CI 17.0-31.7] vs. 11.7 months [10.8-29.4], adjusted hazard ratio [HR] 0.52 [0.28-0.98] p=0.043). Osimertinib efficacy in patients with other uncommon ex19dels varied based on the specific mutation present. Conclusions: The ex19del L747_A750>P is associated with inferior PFS compared to the common E746_A750del mutation in patients treated with 1L osimertinib. Understanding differences in osimertinib efficacy among EGFR ex19del
Data from FDA Oncology Center of Excellence crowdsourcing initiative: outreach to the scientific community to identify research questions for pooled analyses of oncology clinical trial data
Authors: Schneider Julie A. , Eckstein Julia , Goldberg Kirsten B. , Ascione Mark C. , Bailey Thamar , Taylor Kimberly , Coffey Aisha M. , Satchi Darshini , Philips Howard , Sridhara Rajeshwari , Nair Abhilasha , Pazdur Richard , Theoret Marc R.
Published: September 2024

Abstract
The FDA Oncology Center of Excellence recently launched a crowdsourcing pilot to request ideas from the scientific community for research questions that FDA could address with pooled analyses of clinical trial data submitted to the agency for regulatory purposes. This effort builds on FDA’s track record of publishing pooled analyses to explore scientific questions that cannot be addressed in a single trial due to limited sample size. The research crowdsourcing pilot tested a new approach for obtaining external input on regulatory science activities, because FDA is generally unable to share patient-level data outside of the agency due to federal disclosure laws and regulations protecting different types of data submitted in regulatory applications. We received 29 submissions over the 28-day crowdsourcing campaign, including one research idea that we are exploring for possible follow up. Based on our experience with this pilot, we learned that crowdsourcing is a promising new approach to gather external input and feedback. We identified opportunities to build understanding in the external oncology community about the types of data typically included in regulatory applications and expand dissemination of published FDA pooled analyses to help inform future drug development and clinical practice.
Data from SALVO: Single Arm Trial of Ipilimumab and Nivolumab as Adjuvant Therapy for Resected Mucosal Melanoma
Authors: Kottschade Lisa A. , Pond Gregory Russell. , Olszanski Anthony J. , Zakharia Yousef , Domingo-Musibay Evidio , Hauke Ralph J. , Curti Brendan D. , Schober Sarah , Milhem Mohammed M. , Block Matthew S. , Hieken Tina , McWilliams Robert R.
Published: September 2024

Abstract
Background: Mucosal melanoma is a rare, aggressive form of melanoma with extremely high recurrence rates despite definitive surgical resection with curative intent. Currently there is no consensus on adjuvant therapy. Data on checkpoint inhibitors (CPI) for adjuvant therapy is lacking. Methods: We performed a single arm, multicenter clinical trial using “flip dose” ipilimumab (1mg/kg q3w x4 cycles), and nivolumab (3 mg/kg q3w x4 cycles), then Nivolumab 480 mg q4w x 11 cycles to complete a year of adjuvant therapy. Participants must have had R0/R1 resection <90 days prior to registration, no prior systemic therapy (adjuvant radiation allowed), ECOG 0/1, no uncontrolled autoimmune disease or other invasive cancer. Patients were recruited through the Midwest Melanoma Partnership/Hoosier Oncology Network. Results: From Sept 2017 to August 2021 35 patients enrolled. Of these, 29 (83%) had R0 resections, and 7 (20%) received adjuvant radiation. Median age was 67 years, 21 (60.0%) female. Relapse-free survival rates at 1 and 2 years were 50% (95% CI 31-66%) and 37% (95% CI 19-55%), respectively. Overall survival rates at 1 and 2 years were 87% (95% CI 68-95%) and 68% (95% CI 46-83%), respectively. Median RFS was 14.3 m (95% CI 5.7-25.8). Most common grade 3 toxicities were diarrhea (14%), hypertension (14%), and hyponatremia (11%), with no grade 4/5 toxicities. Conclusions: Flip dose ipilimumab and nivolumab after resection of mucosal melanoma is associated with outcomes improved over that of surgical resection alone. Long term follow up, subgroup analyses and correlative studies are ongoing.
Data from Antitumor efficacy of dual blockade with encorafenib plus cetuximab in combination with chemotherapy in human BRAFV600E mutant colorectal cancer.
Authors: Napolitano Stefania , Woods Melanie , Lee Hey Min , De Falco Vincenzo , Martini Giulia , Della Corte Carminia M. , Martinelli Erika , Famiglietti Vincenzo , Ciardiello Davide , Anderson Amanda , Wall Fowlkes Natalie , Villarreal Oscar Eduardo. , Sorokin Alexey , Kanikarla Preeti , Coker Olu , Morris Van , Altucci Lucia , Tabernero Josep , Troiani Teresa , Ciardiello Fortunato , Kopetz Scott
Published: September 2024

Abstract
Purpose: Encorafenib plus cetuximab is an effective therapeutic option in chemorefractory BRAFV600E mCRC. However, there is a need to improve the efficacy of this molecular targeted therapy and evaluate regimens suitable for untreated BRAFV600E mCRC patients. Experimental Design: We performed a series of in vivo studies using BRAFV600EmCRC tumor xenografts. Mice were randomized to receive: 5-fluoruracil, irinotecan or oxaliplatin regimens (FOLFIRI or FOLFOX), encorafenib plus cetuximab (E+C) or the combination. Treatments included long term treatment until progression, with de-escalation strategies replicating maintenance treatments. Transcriptomic changes after progression on cytotoxic chemotherapy or targeted therapy were assessed. Results: Antitumor activity of either FOLFIRI or E+C was better in first-line as compared to second-line, with partial cross-resistance seen between cytotoxic regimen and targeted therapy with average 62% loss of efficacy for FOLFIRI after E+C and 45% loss of efficacy of E+C after FOLFIRI (p<0.001 for both). FOLFIRI treated models had upregulation of EMT and MAPK pathway activation, where E+C treated models had suppressed MAPK signaling. In contrast, with chemotherapy with E+C, EMT and MAPK signaling remained suppressed. FOLFOX or FOLFIRI, each in combination with E+C, were the most active first-line treatments as compared to E+C or to chemotherapy alone. Further, FOLFOX in combination with E+C as first-line induction therapy, followed by E+C +/- 5-FU as maintenance therapy, was the most effective strategy for long term disease control. Conclusions: These results support the combination of cytotoxic chemotherapy and molecular targeted therapy as a promising therapeutic approach in the first-line treatment of BRAFV600E mCRC.
Data from Proteostasis modulation in germline missense von Hippel Lindau disease
Authors: Chittiboina Prashant , Mandal Debjani , Bugarini Alejandro , Asuzu David T. , Mullaney Dustin , Mastorakos Panagiotis , Stoica Stefan , Alvarez Reinier , Scott Gretchen , Maric Dragan , Elkahloun Abdel , Zhuang Zhengping , Chew Emily Y. , Yang Chunzhang , Linehan Marston , Lonser Russell R.
Published: September 2024

Abstract
Purpose: Missense mutated von Hippel Lindau (VHL) protein (pVHL) maintains intrinsic function but undergoes proteasomal degradation and tumor initiation/progression in VHL disease. Vorinostat can rescue missense mutated pVHL and arrest tumor growth in pre-clinical models. We asked if short-term oral vorinostat could rescue pVHL in central nervous system hemangioblastomas in germline missense VHL patients. Experimental Design: We administered oral vorinostat to seven subjects (aged 46.0±14.5 years) and then removed symptomatic hemangioblastomas surgically (clinicaltrials.gov identifier NCT02108002). Results: Vorinostat was tolerated without serious adverse events by all patients. pVHL expression was elevated in neoplastic stromal cells compared to untreated hemangioblastomas from same patients. We found transcriptional suppression of downstream HIF effectors. Mechanistically, vorinostat prevented Hsp90 recruitment to mutated pVHL in-vitro. The effects of vorinostat on the Hsp90-pVHL interaction, pVHL rescue, and transcriptional repression of downstream HIF effectors was independent of the location of the missense mutation on the VHL locus. We confirmed a neoplastic stromal cell-specific effect in suppression of pro-tumorigenic pathways with single nucleus transcriptomic profiling. Conclusions: We found that oral vorinostat treatment in VHL patients with germline missense mutations has a potent biologic effect that warrants further clinical study. These results provide biologic evidence to support the use of proteostasis modulation for the treatment of syndromic solid tumors involving protein misfolding.
Data from Proinflammatory macrophage activation by the polysialic acid-Siglec-16 axis is linked to increased survival of glioblastoma patients
Authors: Thiesler Hauke , Gretenkort Lina , Hoffmeister Leonie , Albers Iris , Ohlmeier Luisa , Röckle Iris , Verhagen Andrea , Banan Rouzbeh , Köpcke Nora , Krönke Nicole , Feuerhake Friedrich , Behling Felix , Barrantes-Freer Alonso , Mielke Dorothee , Rohde Veit , Hong Bujung , Varki Ajit , Schwabe Kerstin , Krauss Joachim K. , Stadelmann Christine , Hartmann Christian , Hildebrandt Herbert
Published: September 2024

Abstract
Purpose: Interactions with tumor-associated microglia and macrophages (TAM) are critical for glioblastoma progression. Polysialic acid (polySia) is a tumor-associated glycan, but its frequency of occurrence and its prognostic value in glioblastoma are disputed. Through interactions with the opposing immune receptors Siglec-11 and Siglec-16, polySia is implicated in the regulation of microglia and macrophage activity. However, due to a nonfunctional SIGLEC16P allele, SIGLEC16 penetrance is less than 40%. Here, we explored possible consequences of SIGLEC16 status and tumor cell-associated polySia on glioblastoma outcome. Experimental Design: FFPE specimens of two independent cohorts with 70 and 100 newly diagnosed glioblastoma patients were retrospectively analyzed for SIGLEC16 and polySia status in relation to overall survival. Inflammatory TAM activation was assessed in tumors, in heterotypic tumor spheroids consisting of polySia-positive glioblastoma cells and Siglec-16-positive or –negative macrophages, and by exposing Siglec-16-positive or –negative macrophages to glioblastoma cell-derived membrane fractions. Results: Overall survival of SIGLEC16 carriers with polySia-positive tumors was increased. Consistent with proinflammatory Siglec-16 signaling, levels of TAM positive for the M2 marker CD163 were reduced, whereas the M1 marker CD74 and TNF expression were increased, and CD8+ T cells enhanced in SIGLEC16 polySia double-positive tumors. Correspondingly, TNF production was elevated in heterotypic spheroid cultures with Siglec-16-expressing macrophages. Furthermore, a higher, mainly M1-like cytokine release and activating immune signaling was observed in SIGLEC16-positive as compared to SIGLEC16-negative macrophages confronted with glioblastoma cell-derived membranes. Conclusions: Collectively, these results strongly suggest that proinflammatory TAM activation causes the better outcome in glioblastoma patients with a functional polySia-Siglec-16 axis.
Data from Devimistat in combination with gemcitabine and cisplatin in biliary tract cancer: Pre-clinical evaluation and phase 1b multicenter clinical trial (BilT-04)
Authors: Mohan Arathi , Griffith Kent A. , Wuchu Fulei , Zhen David B. , Kumar-Sinha Chandan , Crysler Oxana , Hsiehchen David , Enzler Thomas , Dippman Dominique , Gunchick Valerie , Achreja Abhinav , Animasahun Olamide , Choppara Srinadh , Nenwani Minal , Chinnaiyan Arul M. , Nagrath Deepak , Zalupski Mark M. , Sahai Vaibhav
Published: September 2024

Abstract
Purpose: Devimistat (CPI-613®) is a novel inhibitor of tumoral mitochondrial metabolism. We investigated effect of devimistat in vitro and in a phase 1b clinical trial in patients with advanced biliary tract cancer (BTC). Patients and Methods: Cell viability assays of devimistat +/- GC were performed and effect of devimistat on mitochondrial respiration via oxygen consumption rate (OCR) was evaluated. A phase 1b/2 trial was initiated in patients with untreated advanced BTC. In phase 1b, devimistat was infused over 2 hours in combination with GC on days 1 and 8 every 21 days with a primary objective to determine recommended phase 2 dose (RP2D). Secondary objectives included safety, overall response rate (ORR), progression-free survival (PFS) and overall survival (OS). Results: In vitro, devimistat with GC had synergistic effect on two cell lines. Devimistat significantly decreased OCR at higher doses and in arms with divided dosing. In the phase 1b trial, 20 patients received a median of 9 cycles (range 3-19). One DLT was observed and the RP2D of devimistat was determined to be 2000 mg/m2 in combination with GC. Most common grade 3 toxicities included neutropenia (n=11, 55%), anemia (n=4, 20%), and infection (n=3, 15%); with no grade 4 toxicities. After a median follow-up of 15.6 months, ORR is 45% and median PFS is 10 months (95% CI, 7.1 – 14.9). Median OS is not yet estimable. Conclusion: Devimistat in combination with GC is well tolerated and has an acceptable safety profile in patients with untreated advanced BTC.