bluuebunny/crossref_metadata_2025 huggingface dataset:
Data from The Tumor Immune Microenvironment Drives Survival Outcomes and Therapeutic Response in an Integrated Molecular Analysis of Gastric Adenocarcinoma
Authors: Skubleny Daniel , Purich Kieran , McLean David R. , Martins-Filho Sebastiao N. , Buttenschoen Klaus , Haase Erika , McCall Michael , Ghosh Sunita , Spratlin Jennifer L. , Schiller Dan E. , Rayat Gina R.
Published: December 2024

AbstractPurpose:
We performed an integrated analysis of molecular classification systems proposed by The Cancer Genome Atlas (TCGA), the Asian Cancer Research Group (ACRG), and the tumor microenvironment (TME) score to identify which classification scheme(s) are most promising to pursue in subsequent translational investigations.
Experimental Design:
Supervised machine learning classifiers were created using 10-fold nested cross-validation for TCGA, ACRG, and TME subtypes and applied to 2,202 patients with gastric cancer from 11 separate publicly available datasets. Overall survival was assessed with a multivariable Cox proportional hazards model. A propensity score–matched analysis was performed to evaluate the subgroup effect of adjuvant chemotherapy on molecular subtypes. A public external cohort comprised of metastatic gastric cancer treated with immunotherapy was used to externally validate the molecular subtypes.
Results:
Classification models for TCGA, ACRG, and TME achieved an accuracy ± SD of 89.5% ± 0.04, 84.7% ± 0.04, and 89.3% ± 0.02, respectively. We identified the TME score as the only significantly prognostic classification system [HR, 0.54 (95% confidence interval [CI], 0.39–0.74); global Wald test P < 0.001]. In our subgroup analysis, patients who received adjuvant chemotherapy achieved greater survival with increasing TME score (HR, 0.47; 95% CI, 0.29–0.74; interaction P < 0.05). The combination of TME-high and microsatellite instability scores significantly outperformed microsatellite instability as a univariable predictor of immunotherapy response.
Conclusions:
We conclude that the TME score is a predominate driver of prognosis as well as chemotherapy- and immunotherapy-related outcomes in gastric cancer. This article provides a foundation for additional analyses and translational work.
Supplementary Table 4 from Increased RNA and Protein Degradation Is Required for Counteracting Transcriptional Burden and Proteotoxic Stress in Human Aneuploid Cells
Authors: Ippolito Marica Rosaria , Zerbib Johanna , Eliezer Yonatan , Reuveni Eli , Viganò Sonia , De Feudis Giuseppina , Shulman Eldad D. , Savir Kadmon Anouk , Slutsky Rachel , Chang Tiangen , Campagnolo Emma M. , Taglietti Silvia , Scorzoni Simone , Gianotti Sara , Martin Sara , Muenzner Julia , Mülleder Michael , Rozenblum Nir , Rubolino Carmela , Ben-Yishay Tal , Laue Kathrin , Cohen-Sharir Yael , Vigorito Ilaria , Nicassio Francesco , Ruppin Eytan , Ralser Markus , Vazquez Francisca , Santaguida Stefano , Ben-David Uri
Published: December 2024

PRISM screen results of human cancer cell lines treated with bortezomib, in the absence or presence of reversine
Supplementary Table 2 from Increased RNA and Protein Degradation Is Required for Counteracting Transcriptional Burden and Proteotoxic Stress in Human Aneuploid Cells
Authors: Ippolito Marica Rosaria , Zerbib Johanna , Eliezer Yonatan , Reuveni Eli , Viganò Sonia , De Feudis Giuseppina , Shulman Eldad D. , Savir Kadmon Anouk , Slutsky Rachel , Chang Tiangen , Campagnolo Emma M. , Taglietti Silvia , Scorzoni Simone , Gianotti Sara , Martin Sara , Muenzner Julia , Mülleder Michael , Rozenblum Nir , Rubolino Carmela , Ben-Yishay Tal , Laue Kathrin , Cohen-Sharir Yael , Vigorito Ilaria , Nicassio Francesco , Ruppin Eytan , Ralser Markus , Vazquez Francisca , Santaguida Stefano , Ben-David Uri
Published: December 2024

Gene set enrichment analysis of differential protein expression between the highly-aneuploid clones (SS51, SS111) and pseudo-diploid clones (SS48, SS31)
Supplementary Table 1 from Increased RNA and Protein Degradation Is Required for Counteracting Transcriptional Burden and Proteotoxic Stress in Human Aneuploid Cells
Authors: Ippolito Marica Rosaria , Zerbib Johanna , Eliezer Yonatan , Reuveni Eli , Viganò Sonia , De Feudis Giuseppina , Shulman Eldad D. , Savir Kadmon Anouk , Slutsky Rachel , Chang Tiangen , Campagnolo Emma M. , Taglietti Silvia , Scorzoni Simone , Gianotti Sara , Martin Sara , Muenzner Julia , Mülleder Michael , Rozenblum Nir , Rubolino Carmela , Ben-Yishay Tal , Laue Kathrin , Cohen-Sharir Yael , Vigorito Ilaria , Nicassio Francesco , Ruppin Eytan , Ralser Markus , Vazquez Francisca , Santaguida Stefano , Ben-David Uri
Published: December 2024

Pre-ranked gene set enrichment analysis of differential mRNA expression between the highly-aneuploid clones (SS51, SS111) and the pseudo-diploid clone (SS48).
Supplementary Table S5 from Botensilimab, an Fc-Enhanced Anti–CTLA-4 Antibody, Is Effective against Tumors Poorly Responsive to Conventional Immunotherapy
Authors: Chand Dhan , Savitsky David A. , Krishnan Shanmugarajan , Mednick Gabriel , Delepine Chloe , Garcia-Broncano Pilar , Soh Kah Teong , Wu Wei , Wilkens Margaret K. , Udartseva Olga , Vincent Sylvia , Joshi Bishnu , Keith Justin G. , Manrique Mariana , Marques Marilyn , Tanne Antoine , Levey Daniel L. , Han Haiyong , Ng Serina , Ridpath Jackson , Huber Olivia , Morin Benjamin , Galand Claire , Bourdelais Sean , Gombos Randi B. , Ward Rebecca , Qin Yu , Waight Jeremy D. , Costa Matthew R. , Sebastian-Yague Alvaro , Rudqvist Nils-Petter , Pupecka-Swider Malgorzata , Venkatraman Vignesh , Slee Andrew , Patel Jaymin M. , Grossman Joseph E. , Wilson Nicholas S. , Von Hoff Daniel D. , Stebbing Justin , Curiel Tyler J. , Buell Jennifer S. , O’Day Steven J. , Stein Robert B.
Published: December 2024

This dataset presents the serum pharmacokinetic parameters of botensilimab in cynomolgus monkeys. The study includes both male and female monkeys, allowing for sex-based comparisons. These data are crucial for understanding botensilimab's behavior in the body and inform dose selection for clinical trials. The dataset provides insights into potential differences in drug metabolism between sexes and across different dose levels. Importantly, it also helps contextualize the toxicology findings, allowing for a more comprehensive assessment of the drug's safety and efficacy profile.
Supplementary Table S3 from Botensilimab, an Fc-Enhanced Anti–CTLA-4 Antibody, Is Effective against Tumors Poorly Responsive to Conventional Immunotherapy
Authors: Chand Dhan , Savitsky David A. , Krishnan Shanmugarajan , Mednick Gabriel , Delepine Chloe , Garcia-Broncano Pilar , Soh Kah Teong , Wu Wei , Wilkens Margaret K. , Udartseva Olga , Vincent Sylvia , Joshi Bishnu , Keith Justin G. , Manrique Mariana , Marques Marilyn , Tanne Antoine , Levey Daniel L. , Han Haiyong , Ng Serina , Ridpath Jackson , Huber Olivia , Morin Benjamin , Galand Claire , Bourdelais Sean , Gombos Randi B. , Ward Rebecca , Qin Yu , Waight Jeremy D. , Costa Matthew R. , Sebastian-Yague Alvaro , Rudqvist Nils-Petter , Pupecka-Swider Malgorzata , Venkatraman Vignesh , Slee Andrew , Patel Jaymin M. , Grossman Joseph E. , Wilson Nicholas S. , Von Hoff Daniel D. , Stebbing Justin , Curiel Tyler J. , Buell Jennifer S. , O’Day Steven J. , Stein Robert B.
Published: December 2024

This table presents a comparison of the binding epitopes of botensilimab, ipilimumab, and tremelimumab on human CTLA-4. It highlights the specific amino acid residues on CTLA-4 that are involved in the binding interface for each antibody. This comparison provides insight into binding characteristics of botensilimab relative to established anti-CTLA-4 therapies.
Figure S6 from RNA Shielding of p65 Is Required to Potentiate Oncogenic Inflammation in TET2-Mutated Clonal Hematopoiesis
Authors: Ben-Crentsil Nana Adjoa , Mohammed Ismail Wazim , Balasis Maria E. , Newman Hannah , Quintana Ariel , Binder Moritz , Kruer Traci , Neupane Surendra , Ferrall-Fairbanks Meghan C. , Fernandez Jenna , Lasho Terra L. , Finke Christy M. , Ibrahim Mohammed L. , McGraw Kathy L. , Wysota Michael , Aldrich Amy L. , Ryder Christopher B. , Letson Christopher T. , Traina Joshua , McLemore Amy F. , Droin Nathalie , Shastri Aditi , Yun Seongseok , Solary Eric , Sallman David A. , Beg Amer A. , Ma Li , Gaspar-Maia Alexandre , Patnaik Mrinal M. , Padron Eric
Published: December 2024

Contains data related to Figure 5 but which were not included in the main figure
Supplementary Figure S4 from Botensilimab, an Fc-Enhanced Anti–CTLA-4 Antibody, Is Effective against Tumors Poorly Responsive to Conventional Immunotherapy
Authors: Chand Dhan , Savitsky David A. , Krishnan Shanmugarajan , Mednick Gabriel , Delepine Chloe , Garcia-Broncano Pilar , Soh Kah Teong , Wu Wei , Wilkens Margaret K. , Udartseva Olga , Vincent Sylvia , Joshi Bishnu , Keith Justin G. , Manrique Mariana , Marques Marilyn , Tanne Antoine , Levey Daniel L. , Han Haiyong , Ng Serina , Ridpath Jackson , Huber Olivia , Morin Benjamin , Galand Claire , Bourdelais Sean , Gombos Randi B. , Ward Rebecca , Qin Yu , Waight Jeremy D. , Costa Matthew R. , Sebastian-Yague Alvaro , Rudqvist Nils-Petter , Pupecka-Swider Malgorzata , Venkatraman Vignesh , Slee Andrew , Patel Jaymin M. , Grossman Joseph E. , Wilson Nicholas S. , Von Hoff Daniel D. , Stebbing Justin , Curiel Tyler J. , Buell Jennifer S. , O’Day Steven J. , Stein Robert B.
Published: December 2024

This dataset presents comparative results demonstrating the superior ability of Fc-enhanced anti-CTLA-4 to potentiate antigen-specific T cell responses in vivo versus the parental anti-CTLA-4 antibody. The use of the Staphylococcal Enterotoxin B-challenged model in non-tumor bearing mice highlights the broader immunological effects of Fc-enhanced anti-CTLA-4 beyond the tumor microenvironment.
Supplementary Figure S3 from Botensilimab, an Fc-Enhanced Anti–CTLA-4 Antibody, Is Effective against Tumors Poorly Responsive to Conventional Immunotherapy
Authors: Chand Dhan , Savitsky David A. , Krishnan Shanmugarajan , Mednick Gabriel , Delepine Chloe , Garcia-Broncano Pilar , Soh Kah Teong , Wu Wei , Wilkens Margaret K. , Udartseva Olga , Vincent Sylvia , Joshi Bishnu , Keith Justin G. , Manrique Mariana , Marques Marilyn , Tanne Antoine , Levey Daniel L. , Han Haiyong , Ng Serina , Ridpath Jackson , Huber Olivia , Morin Benjamin , Galand Claire , Bourdelais Sean , Gombos Randi B. , Ward Rebecca , Qin Yu , Waight Jeremy D. , Costa Matthew R. , Sebastian-Yague Alvaro , Rudqvist Nils-Petter , Pupecka-Swider Malgorzata , Venkatraman Vignesh , Slee Andrew , Patel Jaymin M. , Grossman Joseph E. , Wilson Nicholas S. , Von Hoff Daniel D. , Stebbing Justin , Curiel Tyler J. , Buell Jennifer S. , O’Day Steven J. , Stein Robert B.
Published: December 2024

This dataset presents comparative results demonstrating the enhanced T cell modulation in the tumor microenvironment promoted by Fc-enhanced anti-CTLA-4 versus the parental anti-CTLA-4 antibody in two specific tumor-bearing mouse models: MC38 and CT26. These data demonstrate the superior ability of Fc-enhanced anti-CTLA-4 to promote T cell infiltration and Treg depletion in the tumor microenvironment. This information is crucial for understanding the mechanistic basis for the improved anti-tumor efficacy of Fc-enhanced anti-CTLA-4 antibodies.
Supplementary Table S9 from MARK2/MARK3 Kinases Are Catalytic Codependencies of YAP/TAZ in Human Cancer
Authors: Klingbeil Olaf , Skopelitis Damianos , Tonelli Claudia , Yoshimoto Toyoki , Alpsoy Aktan , Panepinto Maria C. , Minicozzi Francesca , Merrill Joseph R. , Cafiero Amanda M. , Aggarwal Disha , Russo Suzanne , Ha Taehoon , Demerdash Osama E. , Wee Tse-Luen , Spector David L. , Lyons Scott K. , Tuveson David A. , Cifani Paolo , Vakoc Christopher R.
Published: December 2024

sgRNA sequences. Table of all sgRNA-sequences used in this study.
Supplementary Figure S11 from Botensilimab, an Fc-Enhanced Anti–CTLA-4 Antibody, Is Effective against Tumors Poorly Responsive to Conventional Immunotherapy
Authors: Chand Dhan , Savitsky David A. , Krishnan Shanmugarajan , Mednick Gabriel , Delepine Chloe , Garcia-Broncano Pilar , Soh Kah Teong , Wu Wei , Wilkens Margaret K. , Udartseva Olga , Vincent Sylvia , Joshi Bishnu , Keith Justin G. , Manrique Mariana , Marques Marilyn , Tanne Antoine , Levey Daniel L. , Han Haiyong , Ng Serina , Ridpath Jackson , Huber Olivia , Morin Benjamin , Galand Claire , Bourdelais Sean , Gombos Randi B. , Ward Rebecca , Qin Yu , Waight Jeremy D. , Costa Matthew R. , Sebastian-Yague Alvaro , Rudqvist Nils-Petter , Pupecka-Swider Malgorzata , Venkatraman Vignesh , Slee Andrew , Patel Jaymin M. , Grossman Joseph E. , Wilson Nicholas S. , Von Hoff Daniel D. , Stebbing Justin , Curiel Tyler J. , Buell Jennifer S. , O’Day Steven J. , Stein Robert B.
Published: December 2024

This CONSORT flow diagram for the expanded phase I clinical trial of botensilimab is essential for assessing the validity and generalizability of the trial results. It allows readers to understand how many patients were initially considered, how many were actually treated, and how many contributed to the biomarker analyses. This transparency is essential for interpreting the strength of the evidence supporting botensilimab's efficacy and safety in advanced solid cancers.
Supplementary Table S7 from MARK2/MARK3 Kinases Are Catalytic Codependencies of YAP/TAZ in Human Cancer
Authors: Klingbeil Olaf , Skopelitis Damianos , Tonelli Claudia , Yoshimoto Toyoki , Alpsoy Aktan , Panepinto Maria C. , Minicozzi Francesca , Merrill Joseph R. , Cafiero Amanda M. , Aggarwal Disha , Russo Suzanne , Ha Taehoon , Demerdash Osama E. , Wee Tse-Luen , Spector David L. , Lyons Scott K. , Tuveson David A. , Cifani Paolo , Vakoc Christopher R.
Published: December 2024

YAP/TAZ signature. Table of genes used as YAP/TAZ signature.
Supplementary Table S6 from MARK2/MARK3 Kinases Are Catalytic Codependencies of YAP/TAZ in Human Cancer
Authors: Klingbeil Olaf , Skopelitis Damianos , Tonelli Claudia , Yoshimoto Toyoki , Alpsoy Aktan , Panepinto Maria C. , Minicozzi Francesca , Merrill Joseph R. , Cafiero Amanda M. , Aggarwal Disha , Russo Suzanne , Ha Taehoon , Demerdash Osama E. , Wee Tse-Luen , Spector David L. , Lyons Scott K. , Tuveson David A. , Cifani Paolo , Vakoc Christopher R.
Published: December 2024

FDR for synergy score paralog combinations. Table of FDR corresponding to synergy scores calculated using GEMINI.
Supplementary Figure S1 from Botensilimab, an Fc-Enhanced Anti–CTLA-4 Antibody, Is Effective against Tumors Poorly Responsive to Conventional Immunotherapy
Authors: Chand Dhan , Savitsky David A. , Krishnan Shanmugarajan , Mednick Gabriel , Delepine Chloe , Garcia-Broncano Pilar , Soh Kah Teong , Wu Wei , Wilkens Margaret K. , Udartseva Olga , Vincent Sylvia , Joshi Bishnu , Keith Justin G. , Manrique Mariana , Marques Marilyn , Tanne Antoine , Levey Daniel L. , Han Haiyong , Ng Serina , Ridpath Jackson , Huber Olivia , Morin Benjamin , Galand Claire , Bourdelais Sean , Gombos Randi B. , Ward Rebecca , Qin Yu , Waight Jeremy D. , Costa Matthew R. , Sebastian-Yague Alvaro , Rudqvist Nils-Petter , Pupecka-Swider Malgorzata , Venkatraman Vignesh , Slee Andrew , Patel Jaymin M. , Grossman Joseph E. , Wilson Nicholas S. , Von Hoff Daniel D. , Stebbing Justin , Curiel Tyler J. , Buell Jennifer S. , O’Day Steven J. , Stein Robert B.
Published: December 2024

This dataset presents the binding characteristics of the mouse anti-CTLA-4 (αCTLA-4) antibodies to various mouse Fc gamma receptors (FcγRs). This information is crucial for understanding the Fc-mediated effector functions of the αCTLA-4 antibodies used in the study. The binding data help explain the mechanisms of action and potential efficacy differences between the various αCTLA-4 antibodies in mouse models.
Supplementary Table S11 from MARK2/MARK3 Kinases Are Catalytic Codependencies of YAP/TAZ in Human Cancer
Authors: Klingbeil Olaf , Skopelitis Damianos , Tonelli Claudia , Yoshimoto Toyoki , Alpsoy Aktan , Panepinto Maria C. , Minicozzi Francesca , Merrill Joseph R. , Cafiero Amanda M. , Aggarwal Disha , Russo Suzanne , Ha Taehoon , Demerdash Osama E. , Wee Tse-Luen , Spector David L. , Lyons Scott K. , Tuveson David A. , Cifani Paolo , Vakoc Christopher R.
Published: December 2024

YAP:TEAD4 bound YAP/TAZ dependent enhancers. Peak location file for enhancers with YAP,TEAD4 binding, and reduction of signal upon YAP/TAZ knockout.
Supplementary Table S1 from MARK2/MARK3 Kinases Are Catalytic Codependencies of YAP/TAZ in Human Cancer
Authors: Klingbeil Olaf , Skopelitis Damianos , Tonelli Claudia , Yoshimoto Toyoki , Alpsoy Aktan , Panepinto Maria C. , Minicozzi Francesca , Merrill Joseph R. , Cafiero Amanda M. , Aggarwal Disha , Russo Suzanne , Ha Taehoon , Demerdash Osama E. , Wee Tse-Luen , Spector David L. , Lyons Scott K. , Tuveson David A. , Cifani Paolo , Vakoc Christopher R.
Published: December 2024

Paralog CRISPR screening data. Table for sgRNA sequences and raw sequencing counts of paralog CRISPR screens in 22 cancer cell lines.
Supplementary Figure S7 from MARK2/MARK3 Kinases Are Catalytic Codependencies of YAP/TAZ in Human Cancer
Authors: Klingbeil Olaf , Skopelitis Damianos , Tonelli Claudia , Yoshimoto Toyoki , Alpsoy Aktan , Panepinto Maria C. , Minicozzi Francesca , Merrill Joseph R. , Cafiero Amanda M. , Aggarwal Disha , Russo Suzanne , Ha Taehoon , Demerdash Osama E. , Wee Tse-Luen , Spector David L. , Lyons Scott K. , Tuveson David A. , Cifani Paolo , Vakoc Christopher R.
Published: December 2024

A, IP–western blot analysis evaluating the interaction between 14-3-3e and YAPWT and YAP5D mutants or TAZWT and TAZ4D mutants in HEK-293T cells. Aspartate mutant reversion to wild-type S/T is indicated. Data are representative of two independent experiments. B, mRNA expression log2 fold-change of YAP/TAZ target genes (n=78 genes significantly downregulated upon YAP/TAZdKO and upregulated upon YAPWT expression) following YAP mutant overexpression compared to Ctrl in RH-30 cells. n=2 C, Rescue experiment of MARK2+3dKO following lentiviral YAP mutant overexpression in RH-30 cells. Data shown are the mean ± SD of %GFP+ (normalized to day 3 after infection). n=3. P values are calculated using a mixed effects model (considering the interaction of experimental groups over time) compared to Ctrl group and corrected with Bonferroni-Holm (BH). Data are an extension of Figure 4E. D, Western blot analysis in RH-30 cells following cDNA overexpression of YAP mutants. E,F, Representative immunofluorescence (IF) images of HA-YAP or HA-TAZ mutants, DAPI, and alpha-tubulin following lentiviral overexpression of indicated mutants in HEK-293T cells. scale bar: 30µm.
Supplementary Figure S5 from MARK2/MARK3 Kinases Are Catalytic Codependencies of YAP/TAZ in Human Cancer
Authors: Klingbeil Olaf , Skopelitis Damianos , Tonelli Claudia , Yoshimoto Toyoki , Alpsoy Aktan , Panepinto Maria C. , Minicozzi Francesca , Merrill Joseph R. , Cafiero Amanda M. , Aggarwal Disha , Russo Suzanne , Ha Taehoon , Demerdash Osama E. , Wee Tse-Luen , Spector David L. , Lyons Scott K. , Tuveson David A. , Cifani Paolo , Vakoc Christopher R.
Published: December 2024

A-K, Fragmentation spectrum supporting peptide identity and phosphosites on YAP, TAZ, and NF2. Precursor ion chromatogram (XIC) and corresponding ions are provided in supplementary materials.
Supplementary Figure S2 from MARK2/MARK3 Kinases Are Catalytic Codependencies of YAP/TAZ in Human Cancer
Authors: Klingbeil Olaf , Skopelitis Damianos , Tonelli Claudia , Yoshimoto Toyoki , Alpsoy Aktan , Panepinto Maria C. , Minicozzi Francesca , Merrill Joseph R. , Cafiero Amanda M. , Aggarwal Disha , Russo Suzanne , Ha Taehoon , Demerdash Osama E. , Wee Tse-Luen , Spector David L. , Lyons Scott K. , Tuveson David A. , Cifani Paolo , Vakoc Christopher R.
Published: December 2024

A, Growth kinetics of subcutaneous YAPC xenografts implanted in immunodeficient mice. Indicated genes were knocked out just before injection. Data are shown as mean ± SEM n=5 per group. P values are calculated using a mixed effects model (considering the interaction of experimental groups over time) compared to Ctrl group and corrected with Bonferroni-Holm (BH). B, Tumor imaging at the end-point of the xenograft experiments shown in A. C, mRNA expression of MARK1-4 in different tissues. Data from Genotype-Tissue Expression (GTEx) database. D, Competition-based fitness assays for Ctrl (dgRNA targeting hROSA26 locus) and knockout of essential gene CDK1 corresponding to experiments shown in Fig. 1H and J. Data shown are the mean ± SD of %GFP+ (normalized to day 3 after infection). n=3. E, Western blot analysis of MARK1-4 overexpression in YAPC cells. F, Rescue experiment in YAPC cells using lentiviral expression of MARK1, MARK4 cDNAs or empty vector control (Ctrl). Data shown are the mean ± SD of %GFP+ (normalized to day 3 after infection). n=3. P values are calculated using a mixed effects model (considering the interaction of experimental groups over time) compared to Ctrl group and corrected with Bonferroni-Holm (BH). G¬¬, Rescue experiment in Cas9+ YAPC cells using lentiviral overexpression cDNA of CRISPR resistant (CR) analog sensitive mutant MARK2M129G, kinase-dead mutant MARK2K82H or empty vector control (Ctrl). Data shown are the mean ± SD of %GFP+ (normalized to day 3 after infection). n=3. P values are calculated using a mixed effects model (considering the interaction of experimental groups over time) compared to Ctrl group and corrected with Bonferroni-Holm (BH).
Supplementary Videos Legends from TREM2-Expressing Multinucleated Giant Macrophages Are a Biomarker of Good Prognosis in Head and Neck Squamous Cell Carcinoma
Authors: Gessain Grégoire , Anzali Ahmed-Amine , Lerousseau Marvin , Mulder Kevin , Bied Mathilde , Auperin Anne , Stockholm Daniel , Signolle Nicolas , Sassi Farah , Marques Da Costa Maria Eugenia , Marchais Antonin , Sayadi Alexandre , Weidner Daniela , Uderhardt Stefan , Blampey Quentin , Nakkireddy Sumanth Reddy , Broutin Sophie , Dutertre Charles-Antoine , Busson Pierre , Walter Thomas , Marhic Alix , Moya-Plana Antoine , Guerlain Johanne , Breuskin Ingrid , Casiraghi Odile , Gorphe Philippe , Classe Marion , Scoazec Jean-Yves , Blériot Camille , Ginhoux Florent
Published: December 2024

Legends of the two videos S1 and S2
Supplementary Table S8 from TREM2-Expressing Multinucleated Giant Macrophages Are a Biomarker of Good Prognosis in Head and Neck Squamous Cell Carcinoma
Authors: Gessain Grégoire , Anzali Ahmed-Amine , Lerousseau Marvin , Mulder Kevin , Bied Mathilde , Auperin Anne , Stockholm Daniel , Signolle Nicolas , Sassi Farah , Marques Da Costa Maria Eugenia , Marchais Antonin , Sayadi Alexandre , Weidner Daniela , Uderhardt Stefan , Blampey Quentin , Nakkireddy Sumanth Reddy , Broutin Sophie , Dutertre Charles-Antoine , Busson Pierre , Walter Thomas , Marhic Alix , Moya-Plana Antoine , Guerlain Johanne , Breuskin Ingrid , Casiraghi Odile , Gorphe Philippe , Classe Marion , Scoazec Jean-Yves , Blériot Camille , Ginhoux Florent
Published: December 2024

This table provides the DEG for the seven main clusters of the Visium experiment
Figure S7 from TREM2-Expressing Multinucleated Giant Macrophages Are a Biomarker of Good Prognosis in Head and Neck Squamous Cell Carcinoma
Authors: Gessain Grégoire , Anzali Ahmed-Amine , Lerousseau Marvin , Mulder Kevin , Bied Mathilde , Auperin Anne , Stockholm Daniel , Signolle Nicolas , Sassi Farah , Marques Da Costa Maria Eugenia , Marchais Antonin , Sayadi Alexandre , Weidner Daniela , Uderhardt Stefan , Blampey Quentin , Nakkireddy Sumanth Reddy , Broutin Sophie , Dutertre Charles-Antoine , Busson Pierre , Walter Thomas , Marhic Alix , Moya-Plana Antoine , Guerlain Johanne , Breuskin Ingrid , Casiraghi Odile , Gorphe Philippe , Classe Marion , Scoazec Jean-Yves , Blériot Camille , Ginhoux Florent
Published: December 2024

CosMx 64-plex human immuno-oncology protein panel
Figure S2 from TREM2-Expressing Multinucleated Giant Macrophages Are a Biomarker of Good Prognosis in Head and Neck Squamous Cell Carcinoma
Authors: Gessain Grégoire , Anzali Ahmed-Amine , Lerousseau Marvin , Mulder Kevin , Bied Mathilde , Auperin Anne , Stockholm Daniel , Signolle Nicolas , Sassi Farah , Marques Da Costa Maria Eugenia , Marchais Antonin , Sayadi Alexandre , Weidner Daniela , Uderhardt Stefan , Blampey Quentin , Nakkireddy Sumanth Reddy , Broutin Sophie , Dutertre Charles-Antoine , Busson Pierre , Walter Thomas , Marhic Alix , Moya-Plana Antoine , Guerlain Johanne , Breuskin Ingrid , Casiraghi Odile , Gorphe Philippe , Classe Marion , Scoazec Jean-Yves , Blériot Camille , Ginhoux Florent
Published: December 2024

Quantification of TILs, CD68-positive mononuclear macrophages and tumor grade
Supplementary Figure 7 from TCR-Engineered T Cells Directed against Ropporin-1 Constitute a Safe and Effective Treatment for Triple-Negative Breast Cancer
Authors: Kortleve Dian , Hammerl Dora , van Brakel Mandy , Wijers Rebecca , Roelofs Daphne , Kroese Kim , Timmermans Mieke M. , Liao Chen-Yi , Huang Shaozhuo , Trapman-Jansen Anita , Foekens Renée , Michaux Justine , de Beijer Monique T.A. , Buschow Sonja I. , Demmers Jeroen A.A. , Kok Marleen , Danen Erik H.J. , Bassani-Sternberg Michal , Martens John W.M. , Abbott Rachel J.M. , Debets Reno
Published: December 2024

The extent of recognition of the ROPN1 target by FLY-1A TCR T cells correlates with level of expression.
Supplementary Figure 4 from TCR-Engineered T Cells Directed against Ropporin-1 Constitute a Safe and Effective Treatment for Triple-Negative Breast Cancer
Authors: Kortleve Dian , Hammerl Dora , van Brakel Mandy , Wijers Rebecca , Roelofs Daphne , Kroese Kim , Timmermans Mieke M. , Liao Chen-Yi , Huang Shaozhuo , Trapman-Jansen Anita , Foekens Renée , Michaux Justine , de Beijer Monique T.A. , Buschow Sonja I. , Demmers Jeroen A.A. , Kok Marleen , Danen Erik H.J. , Bassani-Sternberg Michal , Martens John W.M. , Abbott Rachel J.M. , Debets Reno
Published: December 2024

FLY-1A TCR T-cells do not recognize ROPN1-negative and/or HLA-A2-negative tumor cells.
Supplementary Figure 3 from TCR-Engineered T Cells Directed against Ropporin-1 Constitute a Safe and Effective Treatment for Triple-Negative Breast Cancer
Authors: Kortleve Dian , Hammerl Dora , van Brakel Mandy , Wijers Rebecca , Roelofs Daphne , Kroese Kim , Timmermans Mieke M. , Liao Chen-Yi , Huang Shaozhuo , Trapman-Jansen Anita , Foekens Renée , Michaux Justine , de Beijer Monique T.A. , Buschow Sonja I. , Demmers Jeroen A.A. , Kok Marleen , Danen Erik H.J. , Bassani-Sternberg Michal , Martens John W.M. , Abbott Rachel J.M. , Debets Reno
Published: December 2024

FLY-1A TCR T-cells recognize melanoma tumoroids.
Supplementary Figure 2 from TCR-Engineered T Cells Directed against Ropporin-1 Constitute a Safe and Effective Treatment for Triple-Negative Breast Cancer
Authors: Kortleve Dian , Hammerl Dora , van Brakel Mandy , Wijers Rebecca , Roelofs Daphne , Kroese Kim , Timmermans Mieke M. , Liao Chen-Yi , Huang Shaozhuo , Trapman-Jansen Anita , Foekens Renée , Michaux Justine , de Beijer Monique T.A. , Buschow Sonja I. , Demmers Jeroen A.A. , Kok Marleen , Danen Erik H.J. , Bassani-Sternberg Michal , Martens John W.M. , Abbott Rachel J.M. , Debets Reno
Published: December 2024

Retrieval of ROPN1/B-specific T-cells and TCR genes.
Supplementary Table S2 from Identification and Characterization of Chemotherapy-Resistant High-Risk Neuroblastoma Persister Cells
Authors: Grossmann Liron D. , Chen Chia-Hui , Uzun Yasin , Thadi Anusha , Wolpaw Adam J. , Louault Kevin , Goldstein Yael , Surrey Lea F. , Martinez Daniel , Calafatti Matteo , Gerelus Mark , Gao Peng , Lee Lobin , Patel Khushbu , Kaufman Rebecca S. , Shani Guy , Farrel Alvin , Moshitch-Moshkovitz Sharon , Grimaldi Paris , Shapiro Matthew , Kendsersky Nathan M. , Lindsay Jarrett M. , Casey Colleen E. , Krytska Kateryna , Scolaro Laura , Tsang Matthew , Groff David , Matkar Smita , Kalna Josh R. , Mycek Emily , McDevitt Jayne , Runbeck Erin , Patel Tasleema , Bernt Kathrin M. , Asgharzadeh Shahab , DeClerck Yves A. , Mossé Yael P. , Tan Kai , Maris John M.
Published: December 2024

Supplementary Table S2 links the CN number to the HTAN biospecimen numbers
Figure S5 from Identification and Characterization of Chemotherapy-Resistant High-Risk Neuroblastoma Persister Cells
Authors: Grossmann Liron D. , Chen Chia-Hui , Uzun Yasin , Thadi Anusha , Wolpaw Adam J. , Louault Kevin , Goldstein Yael , Surrey Lea F. , Martinez Daniel , Calafatti Matteo , Gerelus Mark , Gao Peng , Lee Lobin , Patel Khushbu , Kaufman Rebecca S. , Shani Guy , Farrel Alvin , Moshitch-Moshkovitz Sharon , Grimaldi Paris , Shapiro Matthew , Kendsersky Nathan M. , Lindsay Jarrett M. , Casey Colleen E. , Krytska Kateryna , Scolaro Laura , Tsang Matthew , Groff David , Matkar Smita , Kalna Josh R. , Mycek Emily , McDevitt Jayne , Runbeck Erin , Patel Tasleema , Bernt Kathrin M. , Asgharzadeh Shahab , DeClerck Yves A. , Mossé Yael P. , Tan Kai , Maris John M.
Published: December 2024

Supplementary Figure S5 shows the connection between NF-kB/stemness subtype and mesenchymal transcriptional state.
Figure S3 from Identification and Characterization of Chemotherapy-Resistant High-Risk Neuroblastoma Persister Cells
Authors: Grossmann Liron D. , Chen Chia-Hui , Uzun Yasin , Thadi Anusha , Wolpaw Adam J. , Louault Kevin , Goldstein Yael , Surrey Lea F. , Martinez Daniel , Calafatti Matteo , Gerelus Mark , Gao Peng , Lee Lobin , Patel Khushbu , Kaufman Rebecca S. , Shani Guy , Farrel Alvin , Moshitch-Moshkovitz Sharon , Grimaldi Paris , Shapiro Matthew , Kendsersky Nathan M. , Lindsay Jarrett M. , Casey Colleen E. , Krytska Kateryna , Scolaro Laura , Tsang Matthew , Groff David , Matkar Smita , Kalna Josh R. , Mycek Emily , McDevitt Jayne , Runbeck Erin , Patel Tasleema , Bernt Kathrin M. , Asgharzadeh Shahab , DeClerck Yves A. , Mossé Yael P. , Tan Kai , Maris John M.
Published: December 2024

Supplementary Figure S3 shows the WGS analysis of the diagnostic and definitive surgery including clonal evolution of ALK mutation from diagnosis to definitive surgery in one tumor.
Data from A Targetable Secreted Neural Protein Drives Pancreatic Cancer Metastatic Colonization and HIF1α Nuclear Retention
Authors: Yamaguchi Norihiro , Wu Y. Gloria , Ravetch Ethan , Takahashi Mai , Khan Abdul G. , Hayashi Akimasa , Mei Wenbin , Hsu Dennis , Umeda Shigeaki , de Stanchina Elisa , Lorenz Ivo C. , Iacobuzio-Donahue Christine A. , Tavazoie Sohail F.
Published: December 2024

Abstract
Pancreatic ductal adenocarcinoma (PDAC) is an increasingly diagnosed cancer that kills 90% of afflicted patients, with most patients receiving palliative chemotherapy. We identified neuronal pentraxin 1 (NPTX1) as a cancer-secreted protein that becomes overexpressed in human and murine PDAC cells during metastatic progression and identified adhesion molecule with Ig-like domain 2 (AMIGO2) as its receptor. Molecular, genetic, biochemical, and pharmacologic experiments revealed that secreted NPTX1 acts cell-autonomously on the AMIGO2 receptor to drive PDAC metastatic colonization of the liver—the primary site of PDAC metastasis. NPTX1–AMIGO2 signaling enhanced hypoxic growth and was critically required for hypoxia-inducible factor-1α (HIF1α) nuclear retention and function. NPTX1 is overexpressed in human PDAC tumors and upregulated in liver metastases. Therapeutic targeting of NPTX1 with a high-affinity monoclonal antibody substantially reduced PDAC liver metastatic colonization. We thus identify NPTX1–AMIGO2 as druggable critical upstream regulators of the HIF1α hypoxic response in PDAC.

Significance: We identified the NPTX1–AMIGO2 axis as a regulatory mechanism upstream of HIF1α-driven hypoxia response that promotes PDAC liver metastasis. Therapeutic NPTX1 targeting outperformed a common chemotherapy regimen in inhibiting liver metastasis and suppressed primary tumor growth in preclinical models, revealing a novel therapeutic strategy targeting hypoxic response in PDAC.
Data from TREM2-Expressing Multinucleated Giant Macrophages Are a Biomarker of Good Prognosis in Head and Neck Squamous Cell Carcinoma
Authors: Gessain Grégoire , Anzali Ahmed-Amine , Lerousseau Marvin , Mulder Kevin , Bied Mathilde , Auperin Anne , Stockholm Daniel , Signolle Nicolas , Sassi Farah , Marques Da Costa Maria Eugenia , Marchais Antonin , Sayadi Alexandre , Weidner Daniela , Uderhardt Stefan , Blampey Quentin , Nakkireddy Sumanth Reddy , Broutin Sophie , Dutertre Charles-Antoine , Busson Pierre , Walter Thomas , Marhic Alix , Moya-Plana Antoine , Guerlain Johanne , Breuskin Ingrid , Casiraghi Odile , Gorphe Philippe , Classe Marion , Scoazec Jean-Yves , Blériot Camille , Ginhoux Florent
Published: December 2024

Abstract
Patients with head and neck squamous cell carcinomas (HNSCC) often have poor outcomes due to suboptimal risk management and treatment strategies; yet integrating novel prognostic biomarkers into clinical practice is challenging. Here, we report the presence of multinucleated giant cells (MGC)—a type of macrophages—in tumors from patients with HNSCC, which are associated with a favorable prognosis in treatment-naive and preoperative chemotherapy–treated patients. Importantly, MGC density increased in tumors following preoperative therapy, suggesting a role of these cells in the antitumoral response. To enable clinical translation of MGC density as a prognostic marker, we developed a deep-learning model to automate its quantification on routinely stained pathological whole slide images. Finally, we used spatial transcriptomic and proteomic approaches to describe the MGC-related tumor microenvironment and observed an increase in central memory CD4 T cells. We defined an MGC-specific signature resembling to TREM2-expressing mononuclear tumor-associated macrophages, which colocalized in keratin tumor niches.
Significance:
Novel individual biomarkers are needed to guide therapeutic decisions for patients with head and neck cancer. We report for the first time, granulomas of TREM2-expressing multinucleated giant macrophages in keratin-rich tumor niches, as a biomarker of favorable prognosis and developed a deep-learning model to automate its quantification on routinely stained pathological slides.
Cancer in 2024
Authors:   AACR Cancer Disparities Progress Report 2024 Steering Committee,   AACR Cancer Progress Report 2024 Steering Committee
Published: December 2024

Excerpts from the 14th edition of the annual American Association for Cancer Research Cancer Progress Report (https://cancerprogressreport.aacr.org/progress/) and the third edition of the American Association for Cancer Research Cancer Disparities Progress Report (https://cancerprogressreport.aacr.org/disparities/) to US Congress and the public, both released in 2024, highlight significant strides made possible through medical research, much of which is supported by federal investments in the NIH, NCI, FDA, and Centers for Disease Control and Prevention, as well as recent progress in understanding the overlapping and intersecting causes of cancer disparities and in addressing health inequities through evidence-based public policies.
Supplementary Table 2 from Dynamic Evolution of Fibroblasts Revealed by Single-Cell RNA Sequencing of Human Pancreatic Cancer
Authors: Dimitrieva Slavica , Harrison Jon M. , Chang Jonathan , Piquet Michelle , Mino-Kenudson Mari , Gabriel Millicent , Sagar Vivek , Horn Heiko , Lage Kasper , Kim Julie , Li Gang , Weng Shaobu , Harris Cynthia , Kulkarni Anupriya S. , Ting David T. , Qadan Motaz , Fagenholz Peter J. , Ferrone Cristina R. , Grauel Angelo L. , Laszewski Tyler , Raza Alina , Riester Markus , Somerville Tim , Wagner Joel P. , Dranoff Glenn , Engelman Jeffrey A. , Kauffmann Audrey , Leary Rebecca , Warshaw Andrew L. , Lillemoe Keith D. , Fernández-del Castillo Carlos , Ruddy David A. , Liss Andrew S. , Cremasco Viviana
Published: December 2024

Supplementary Table 2
Figure 4 from Dynamic Evolution of Fibroblasts Revealed by Single-Cell RNA Sequencing of Human Pancreatic Cancer
Authors: Dimitrieva Slavica , Harrison Jon M. , Chang Jonathan , Piquet Michelle , Mino-Kenudson Mari , Gabriel Millicent , Sagar Vivek , Horn Heiko , Lage Kasper , Kim Julie , Li Gang , Weng Shaobu , Harris Cynthia , Kulkarni Anupriya S. , Ting David T. , Qadan Motaz , Fagenholz Peter J. , Ferrone Cristina R. , Grauel Angelo L. , Laszewski Tyler , Raza Alina , Riester Markus , Somerville Tim , Wagner Joel P. , Dranoff Glenn , Engelman Jeffrey A. , Kauffmann Audrey , Leary Rebecca , Warshaw Andrew L. , Lillemoe Keith D. , Fernández-del Castillo Carlos , Ruddy David A. , Liss Andrew S. , Cremasco Viviana
Published: December 2024

Differentiation of fibroblasts is coupled with a loss of transcriptional regulatory programs. A, Trajectory analysis of fibroblast subclusters inferred by Slingshot. B, Gene expression of CAF marker genes plotted along the pseudotime trajectory leading to CAFs. Expression values in natural-log scale. C, RNA velocity analysis of fibroblast cells. D, Volcano plots of DE genes between fibroblast populations. Transcription factors that are DE between populations, with an adjusted P value <0.01 and average log2FC > 0.5 in absolute value, are indicated. E, Gene expression of selected transcription factors plotted along the pseudotime trajectory leading to CAFs. Expression values in natural-log scale. F, Top 20 candidate master regulators of transcriptional program altered between fibroblast populations identified by the master regulator analysis algorithm (MARINa). The targets of each transcription factor are shown in vertical bars (repressed genes are in blue, and activated genes in red) and are rank-sorted (x-axis) from the one most downregulated to the one most upregulated in the selected conditions: normal fibroblasts compared with transitional fibroblasts and transitional compared with CAFs. The heatmaps on the right side of each panel indicate inferred differential activity (Act) and differential expression (Exp) of the transcription factor. MARINa, MAster Regulator INference algorithm.
Figure 3 from Dynamic Evolution of Fibroblasts Revealed by Single-Cell RNA Sequencing of Human Pancreatic Cancer
Authors: Dimitrieva Slavica , Harrison Jon M. , Chang Jonathan , Piquet Michelle , Mino-Kenudson Mari , Gabriel Millicent , Sagar Vivek , Horn Heiko , Lage Kasper , Kim Julie , Li Gang , Weng Shaobu , Harris Cynthia , Kulkarni Anupriya S. , Ting David T. , Qadan Motaz , Fagenholz Peter J. , Ferrone Cristina R. , Grauel Angelo L. , Laszewski Tyler , Raza Alina , Riester Markus , Somerville Tim , Wagner Joel P. , Dranoff Glenn , Engelman Jeffrey A. , Kauffmann Audrey , Leary Rebecca , Warshaw Andrew L. , Lillemoe Keith D. , Fernández-del Castillo Carlos , Ruddy David A. , Liss Andrew S. , Cremasco Viviana
Published: December 2024

Distinct fibroblast populations are associated with tissue types. A, UMAP projection based on the top five PCs of fibroblast single-cell transcriptomes. B, UMAP projections of single cells from each tissue type (colored) contributing to the fibroblast UMAP (gray). C, UMAP projections of single cells from autoimmune (left) and idiopathic (right) chronic pancreatitis samples (colored) contributing to the fibroblast UMAP (gray). D, Quantification of each fibroblast cluster within tissue types. E, Bubble plot demonstrating relative expression of marker genes across clusters. The intensity of the color is proportional to the average expression of the marker within a cluster, and the bubble size is proportional to the number of cells expressing the marker. F, Violin plots of the expression of genes with defined roles in fibroblast biology. G, Visualization of selected KEGG and Reactome pathways significantly enriched in fibroblast clusters. The bubble size is proportional to the number of genes enriched, and the intensity of the color is proportional to significance of the enrichment. Normal fibroblasts (F1); inflammatory fibroblasts (F2); injury-reactive fibroblasts (F3); transitional fibroblasts (F4); CAFs (F5). UMAP, UMAP, Uniform Manifold Approximation and Projection for Dimension Reduction.
Figure 1 from Dynamic Evolution of Fibroblasts Revealed by Single-Cell RNA Sequencing of Human Pancreatic Cancer
Authors: Dimitrieva Slavica , Harrison Jon M. , Chang Jonathan , Piquet Michelle , Mino-Kenudson Mari , Gabriel Millicent , Sagar Vivek , Horn Heiko , Lage Kasper , Kim Julie , Li Gang , Weng Shaobu , Harris Cynthia , Kulkarni Anupriya S. , Ting David T. , Qadan Motaz , Fagenholz Peter J. , Ferrone Cristina R. , Grauel Angelo L. , Laszewski Tyler , Raza Alina , Riester Markus , Somerville Tim , Wagner Joel P. , Dranoff Glenn , Engelman Jeffrey A. , Kauffmann Audrey , Leary Rebecca , Warshaw Andrew L. , Lillemoe Keith D. , Fernández-del Castillo Carlos , Ruddy David A. , Liss Andrew S. , Cremasco Viviana
Published: December 2024

scRNA-seq of human pancreatic tissues. A, Schematic representation of the types of tissues employed in this study and the experimental pipeline for their analysis by scRNA-seq. B, UMAP visualization of single cells from all samples colored by cell type. C, UMAP projections of single cells from each tissue type (colored) contributing to the global UMAP (gray). D, Representative images of H&E-stained sections of each tissue type. Scale bar, 100 μm. E, Quantification of cell types within each tissue type. F, Quantification of cell populations (% from the total) along with the number of DE genes in each cell population between tissue types. UMAP, Uniform Manifold Approximation and Projection for Dimension Reduction; H&E, hematoxylin and eosin.
Data from Dynamic Evolution of Fibroblasts Revealed by Single-Cell RNA Sequencing of Human Pancreatic Cancer
Authors: Dimitrieva Slavica , Harrison Jon M. , Chang Jonathan , Piquet Michelle , Mino-Kenudson Mari , Gabriel Millicent , Sagar Vivek , Horn Heiko , Lage Kasper , Kim Julie , Li Gang , Weng Shaobu , Harris Cynthia , Kulkarni Anupriya S. , Ting David T. , Qadan Motaz , Fagenholz Peter J. , Ferrone Cristina R. , Grauel Angelo L. , Laszewski Tyler , Raza Alina , Riester Markus , Somerville Tim , Wagner Joel P. , Dranoff Glenn , Engelman Jeffrey A. , Kauffmann Audrey , Leary Rebecca , Warshaw Andrew L. , Lillemoe Keith D. , Fernández-del Castillo Carlos , Ruddy David A. , Liss Andrew S. , Cremasco Viviana
Published: December 2024

Abstract
Cancer progression and response to therapy are inextricably reliant on the coevolution of a supportive tissue microenvironment. This is particularly evident in pancreatic ductal adenocarcinoma, a tumor type characterized by expansive and heterogeneous stroma. Herein, we employed single-cell RNA sequencing and spatial transcriptomics of normal, inflamed, and malignant pancreatic tissues to contextualize stromal dynamics associated with disease and treatment status, identifying temporal and spatial trajectories of fibroblast differentiation. Using analytical tools to infer cellular communication, together with a newly developed assay to annotate genomic alterations in cancer cells, we additionally explored the complex intercellular networks underlying tissue circuitry, highlighting a fibroblast-centric interactome that grows in strength and complexity in the context of malignant transformation. Our study yields new insights on the stromal remodeling events favoring the development of a tumor-supportive microenvironment and provides a powerful resource for the exploration of novel points of therapeutic intervention in pancreatic ductal adenocarcinoma.
Significance:
Pancreatic cancer remains a high unmet medical need. Understanding the interactions between stroma and cancer cells in this disease may unveil new opportunities for therapeutic intervention.
Zooming In on Agreement-Making: Tracing the BBNJ Negotiations with the MARIPOLDATAbase
Authors: Vadrot Alice B. M. , Langlet Arne , Dunshirn Paul , Fellinger Simon , Ruiz-Rodríguez Silvia C. , Tessnow-von Wysocki Ina
Published: December 2024

Starting in 2018, the MARIPOLDATAbase has systematically cataloged observations covering the entire Biodiversity Beyond National Jurisdiction (BBNJ) negotiations until their conclusion in June 2023. By providing primary data on the whole negotiation process, the MARIPOLDATAbase supports empirical, scholarly work on diverse aspects of international marine biodiversity politics. This research note presents the database, its key features, and how it can be used to trace and map the BBNJ process. Drawing on examples from our own research, we show how we used these data—on actors and alliances, statement length, agreement text, positions, networks, statements, concepts, and meeting formats—to analyze various aspects of agreement-making. We note that our database has specific value for researchers who, in the past, struggled to access the BBNJ negotiations as well as for scholars who wish to follow marine biodiversity negotiations in the future. By facilitating the use of primary negotiation data, the MARIPOLDATAbase structure and content support both broad research areas and specific research questions. We conclude by proposing a methodological shift in the study of global environmental negotiations echoing recent attempts to elevate the ethical standards, data quality, political stakes, and critical reflection on the future of global environmental meetings and their role in global environmental politics (GEP) research.
Neural Basis of Perceptual Surface Qualities and Materials: Evidence from Electroencephalogram Decoding
Authors: Orima Taiki , Wakita Suguru , Motoyoshi Isamu
Published: December 2024

The human visual system can easily recognize object material categories and estimate surface properties such as glossiness and smoothness. Recent psychophysical and computational studies suggest that the material perception depends on global feature statistics. To elucidate dynamic neural representations underlying surface property and material perception in humans, we measured visual evoked potentials (VEPs) for 191 natural images consisting of 20 categories of materials and then classified material categories and surface properties from the VEPs. As a result, we found that material categories were correctly classified by the VEPs even at latencies of 150 msec or less. The apparent surface properties were also significantly classified within 175 msec (lightness, colorfulness, and smoothness) and after 200 msec (glossiness, hardness, and heaviness). The subsequent reverse-correlation analysis revealed that the VEPs at these latencies are highly correlated with low- and high-level global feature statistics of the surface images, indicating that neural activities about such global features are reflected in the VEPs. Moreover, by using deep generative models (multimodal variational autoencoder models) to reconstruct surface images from the VEPs via style information, we demonstrated that the reconstructed surface images are judged by observers to have very similar material categories and surface properties as the original natural surfaces. These results support the notion that neural representations of statistical features in the early cortical response play a crucial role in the perception and recognition of surface materials in humans.