bluuebunny/crossref_metadata_2025 huggingface dataset:
Supplementary Figure S6 from Phase I/II Study of the Aurora Kinase A Inhibitor Alisertib and Pembrolizumab in Refractory, Rb-Deficient Head and Neck Squamous Cell Carcinomas
Authors: Johnson Faye M. , O’Hara Madison P. , Yapindi Lacin , Jiang Peixin , Tran Hai T. , Reuben Alexandre , Xiao Weihong , Gillison Maura L. , Sun Xiaowen , Khalaf Alexander , Lee J. Jack , Sastry Jagannadha K. , Ghosh Soma
Published: February 2025

Supplementary Figure S6. Plasma samples collected at the baseline from the participants of the trial were compared between the PD and SD groups of patients by the Luminex analyses to profile various cytokines and chemokines.
Figure 1 from Safety and Tolerability of Letetresgene Autoleucel (GSK3377794): Pilot Studies in Patients with Advanced Non–Small Cell Lung Cancer
Authors: Altan Mehmet , Lopes Gilberto , Hiltermann T. Jeroen N. , Govindan Ramaswamy , Villaruz Liza C. , Calvo Emiliano , Edelman Martin J. , Furqan Muhammad , Neal Joel , Felip Enriqueta , Carlisle Jennifer W. , Heymach John V. , O’Cearbhaill Róisín Eilish , Zauderer Marjorie , Chisamore Michael , Corigliano Ellie , Eleftheriadou Ioanna , Zajic Stefan , Jenkins Ben , Goodison Sophia , Suchindran Sunil , Ramos-Hernandez Natalia , Tarek Nidale , Schoenfeld Adam J.
Published: February 2025

Patient attrition and NY-ESO-1 and LAGE-1a expression profiles in the multiarm study. A, Patient attrition for multiarm study. A total of 1,698 patients in the multiarm study were screened and signed the informed consent form. Out of 13 dosed patients, six withdrew prior to meeting interventional phase completion criteria, per protocol. B, NY-ESO-1 IHC P-score distribution of screened NY-ESO-1–positive patients in the multiarm study. NY-ESO-1–positive protein expression was detected as a continuous variable with distribution between 10% and 100% expression. There were 62 patients whose tumors expressed NY-ESO-1 with a P score of ≥10%, 1+, 2+, and 3+, with each vertical bar representing a unique tumor sample depicted by contributing IHC intensity of 0+ in blue, 1+ in light blue, 2+ in light orange, and 3+ in orange (425 patients whose tumors expressed NY-ESO-1 <10%, 1+, 2+, and 3+ are not displayed). One patient (ID #61 in the figure) had two samples. C, NY-ESO-1 expression profile of dosed NY-ESO-1–positive patients in the multiarm study. The mITT population based on NY-ESO-1 IHC expression is individually represented in the vertical bars with the P-score broken down by contributing IHC intensity of 0+ in blue, 1+ in light blue, 2+ in light orange, and 3+ in orange. The patients are ordered by P score, which is indicated by the red line. NY-ESO-1–negative, LAGE-1a–positive patients in the mITT population not shown. D, LAGE-1a RNA expression distribution of all tested patients in the multiarm study. The plot of patients tested for LAGE-1a RT-PCR RNA expression, in which the red line indicates the cutoff = 4 ΔCT, with positive cases depicted in red and negative cases depicted in blue. Triangles represent all patients screened. The two patients dosed who were LAGE-1a–positive are distinguished in the figure with a red circle. Patients with “no expression” were imputed as having the lowest observable value divided by 3. The vertical axis is reversed (zero is higher); lower LAGE-1a score measured by RT-PCR represents higher expression levels. E, NY-ESO-1 and LAGE-1a prevalence. This is a bar chart displaying NY-ESO-1 and LAGE-1a prevalence. LAGE-1a testing was performed on tissue samples in reflex to NY-ESO-1–negative status for when tissue was available. Prevalence includes unique samples from the same patient. NE, not evaluable.
Supplementary Figure S2 from Phase I/II Study of the Aurora Kinase A Inhibitor Alisertib and Pembrolizumab in Refractory, Rb-Deficient Head and Neck Squamous Cell Carcinomas
Authors: Johnson Faye M. , O’Hara Madison P. , Yapindi Lacin , Jiang Peixin , Tran Hai T. , Reuben Alexandre , Xiao Weihong , Gillison Maura L. , Sun Xiaowen , Khalaf Alexander , Lee J. Jack , Sastry Jagannadha K. , Ghosh Soma
Published: February 2025

Supplementary Figure S2. Baseline and follow-up neck CT scans of a patient with recurrent metastatic squamous cell carcinoma.
Supplementary Table S3 from The Landscape of ctDNA in Appendiceal Adenocarcinoma
Authors: White Michael G. , Zeineddine Mohammad A. , Fallon Eleanor A. , Zeineddine Fadl A. , Dansby Julia , Chowdhury Saikat , Hornstein Nicholas , Yousef Abdelrahman , Yousef Mahmoud , Bhutiani Neal , Gu Yue , Kee Bryan , Dasari Arvind , Overman Michael J. , Raghav Kanwal , Kopetz Scott , Uppal Abhineet , Taggart Melissa , Newhook Timothy , Fournier Keith , Helmink Beth , Drusbosky Leylah M. , Shen John Paul
Published: February 2025

Supplementary Table S3: 70 gene ctDNA panel
Supplementary Figures 1 from The Landscape of ctDNA in Appendiceal Adenocarcinoma
Authors: White Michael G. , Zeineddine Mohammad A. , Fallon Eleanor A. , Zeineddine Fadl A. , Dansby Julia , Chowdhury Saikat , Hornstein Nicholas , Yousef Abdelrahman , Yousef Mahmoud , Bhutiani Neal , Gu Yue , Kee Bryan , Dasari Arvind , Overman Michael J. , Raghav Kanwal , Kopetz Scott , Uppal Abhineet , Taggart Melissa , Newhook Timothy , Fournier Keith , Helmink Beth , Drusbosky Leylah M. , Shen John Paul
Published: February 2025

Supplementary Figures
Supplementary Table S7 from Aberrantly Expressed Mitochondrial Lipid Kinase, AGK, Activates JAK2–Histone H3 Axis and BCR Signal: A Mechanistic Study with Implication in CLL Therapy
Authors: Mamidi Murali K. , Sinha Sutapa , Mendez Mariana T. , Sanyal Tapojyoti , Mahmud Hasan , Kay Neil E. , Gupta Mamta , Xu Chao , Vesely Sara K. , Mukherjee Priyabrata , Holter Chakrabarty Jennifer , Ghosh Asish K.
Published: February 2025

Supplementary Table S7. Target genes of the P-histone H3(Y41)/JAK2 pathway.
Supplementary Table S4 from Aberrantly Expressed Mitochondrial Lipid Kinase, AGK, Activates JAK2–Histone H3 Axis and BCR Signal: A Mechanistic Study with Implication in CLL Therapy
Authors: Mamidi Murali K. , Sinha Sutapa , Mendez Mariana T. , Sanyal Tapojyoti , Mahmud Hasan , Kay Neil E. , Gupta Mamta , Xu Chao , Vesely Sara K. , Mukherjee Priyabrata , Holter Chakrabarty Jennifer , Ghosh Asish K.
Published: February 2025

Supplementary Table S4. Target genes of the Erk1/2 MAPK pathway.
Supplementary Information 1 from Framework for the Pathology Workup of Metastatic Castration-Resistant Prostate Cancer Biopsies
Authors: Haffner Michael C. , Morris Michael J. , Ding Chien-Kuang C. , Sayar Erolcan , Mehra Rohit , Robinson Brian , True Lawrence D. , Gleave Martin , Lotan Tamara L. , Aggarwal Rahul , Huang Jiaoti , Loda Massimo , Nelson Peter S. , Rubin Mark A. , Beltran Himisha
Published: February 2025

Supplementary Information 1. Post-workshop survey questions.
Supplementary Table S1 from Aberrantly Expressed Mitochondrial Lipid Kinase, AGK, Activates JAK2–Histone H3 Axis and BCR Signal: A Mechanistic Study with Implication in CLL Therapy
Authors: Mamidi Murali K. , Sinha Sutapa , Mendez Mariana T. , Sanyal Tapojyoti , Mahmud Hasan , Kay Neil E. , Gupta Mamta , Xu Chao , Vesely Sara K. , Mukherjee Priyabrata , Holter Chakrabarty Jennifer , Ghosh Asish K.
Published: February 2025

Supplementary Table S1. CLL Patients’ Prognostic Characteristics.
Supplementary Figure S9 from Aberrantly Expressed Mitochondrial Lipid Kinase, AGK, Activates JAK2–Histone H3 Axis and BCR Signal: A Mechanistic Study with Implication in CLL Therapy
Authors: Mamidi Murali K. , Sinha Sutapa , Mendez Mariana T. , Sanyal Tapojyoti , Mahmud Hasan , Kay Neil E. , Gupta Mamta , Xu Chao , Vesely Sara K. , Mukherjee Priyabrata , Holter Chakrabarty Jennifer , Ghosh Asish K.
Published: February 2025

Supplementary Figure S9. JAK2 inhibition prevents CXCL12-induced migration of primary CLL cells.
Supplementary Figure 3 from Framework for the Pathology Workup of Metastatic Castration-Resistant Prostate Cancer Biopsies
Authors: Haffner Michael C. , Morris Michael J. , Ding Chien-Kuang C. , Sayar Erolcan , Mehra Rohit , Robinson Brian , True Lawrence D. , Gleave Martin , Lotan Tamara L. , Aggarwal Rahul , Huang Jiaoti , Loda Massimo , Nelson Peter S. , Rubin Mark A. , Beltran Himisha
Published: February 2025

Supplementary Figure 3. Example case 3.
Supplementary Figure 2 from Framework for the Pathology Workup of Metastatic Castration-Resistant Prostate Cancer Biopsies
Authors: Haffner Michael C. , Morris Michael J. , Ding Chien-Kuang C. , Sayar Erolcan , Mehra Rohit , Robinson Brian , True Lawrence D. , Gleave Martin , Lotan Tamara L. , Aggarwal Rahul , Huang Jiaoti , Loda Massimo , Nelson Peter S. , Rubin Mark A. , Beltran Himisha
Published: February 2025

Supplementary Figure 2. Example case 2.
Supplementary Figure S7 from Aberrantly Expressed Mitochondrial Lipid Kinase, AGK, Activates JAK2–Histone H3 Axis and BCR Signal: A Mechanistic Study with Implication in CLL Therapy
Authors: Mamidi Murali K. , Sinha Sutapa , Mendez Mariana T. , Sanyal Tapojyoti , Mahmud Hasan , Kay Neil E. , Gupta Mamta , Xu Chao , Vesely Sara K. , Mukherjee Priyabrata , Holter Chakrabarty Jennifer , Ghosh Asish K.
Published: February 2025

Supplementary Figure S7. JAK2-knockdown modulates transcript levels of specific gene-sets in CLL cells.
Supplementary Figure 1 from Framework for the Pathology Workup of Metastatic Castration-Resistant Prostate Cancer Biopsies
Authors: Haffner Michael C. , Morris Michael J. , Ding Chien-Kuang C. , Sayar Erolcan , Mehra Rohit , Robinson Brian , True Lawrence D. , Gleave Martin , Lotan Tamara L. , Aggarwal Rahul , Huang Jiaoti , Loda Massimo , Nelson Peter S. , Rubin Mark A. , Beltran Himisha
Published: February 2025

Supplementary Figure 1. Example case 1.
Supplementary Figure S6 from Aberrantly Expressed Mitochondrial Lipid Kinase, AGK, Activates JAK2–Histone H3 Axis and BCR Signal: A Mechanistic Study with Implication in CLL Therapy
Authors: Mamidi Murali K. , Sinha Sutapa , Mendez Mariana T. , Sanyal Tapojyoti , Mahmud Hasan , Kay Neil E. , Gupta Mamta , Xu Chao , Vesely Sara K. , Mukherjee Priyabrata , Holter Chakrabarty Jennifer , Ghosh Asish K.
Published: February 2025

Supplementary Figure S6. Cytokine treatment activates JAK2/STAT3 pathway.
Supplementary Figure S4 from Aberrantly Expressed Mitochondrial Lipid Kinase, AGK, Activates JAK2–Histone H3 Axis and BCR Signal: A Mechanistic Study with Implication in CLL Therapy
Authors: Mamidi Murali K. , Sinha Sutapa , Mendez Mariana T. , Sanyal Tapojyoti , Mahmud Hasan , Kay Neil E. , Gupta Mamta , Xu Chao , Vesely Sara K. , Mukherjee Priyabrata , Holter Chakrabarty Jennifer , Ghosh Asish K.
Published: February 2025

Supplementary Figure S4. Depletion of AGK reduces P-JAK2 level in CLL cells.
Supplementary Figure S3 from Aberrantly Expressed Mitochondrial Lipid Kinase, AGK, Activates JAK2–Histone H3 Axis and BCR Signal: A Mechanistic Study with Implication in CLL Therapy
Authors: Mamidi Murali K. , Sinha Sutapa , Mendez Mariana T. , Sanyal Tapojyoti , Mahmud Hasan , Kay Neil E. , Gupta Mamta , Xu Chao , Vesely Sara K. , Mukherjee Priyabrata , Holter Chakrabarty Jennifer , Ghosh Asish K.
Published: February 2025

Supplementary Figure S3. HSP90 regulates AGK protein level in CLL cells.
Data from Clinical Characteristics and Outcomes of Central Nervous System Tumors Harboring NTRK Gene Fusions
Authors: Lamoureux Audrey-Anne , Fisher Michael J. , Lemelle Lauriane , Pfaff Elke , Amir-Yazdani Pouneh , Kramm Christof , De Wilde Bram , Kazanowska Bernarda , Hutter Caroline , Pfister Stefan M. , Sturm Dominik , Jones David T.W. , Orbach Daniel , Pierron Gaëlle , Raskin Scott , Drilon Alexander , Diamond Eli L. , Harada Guilherme , Zapotocky Michal , Zamecnik Josef , Krskova Lenka , Ellezam Benjamin , Weil Alexander G. , Venne Dominic , Barritault Marc , Leblond Pierre , Coltin Hallie , Hammad Rawan , Tabori Uri , Hawkins Cynthia , Hansford Jordan R. , Meyran Deborah , Erker Craig , McFadden Kathryn , Sato Mariko , Gottardo Nicholas G. , Dholaria Hetal , Nørøxe Dorte Schou , Goto Hiroaki , Ziegler David S. , Lin Frank Y. , Parsons Donald Williams , Lindsay Holly , Wong Tai-Tong , Liu Yen-Lin , Wu Kuo-Sheng , Franson Andrea T. , Hwang Eugene , Aguilar-Bonilla Ana , Cheng Sylvia , Cacciotti Chantel , Massimino Maura , Schiavello Elisabetta , Wood Paul , Hoffman Lindsey M. , Cappellano Andréa , Lassaletta Alvaro , Van Damme An , Llort Anna , Gerber Nicolas U. , Spalato Ceruso Mariella , Bendel Anne E. , Skrypek Maggie , Hamideh Dima , Mushtaq Naureen , Walter Andrew , Jabado Nada , Alsahlawi Aysha , Farmer Jean-Pierre , Coleman Christina , Mueller Sabine , Mazewski Claire , Aguilera Dolly , Robison Nathan J. , O’Halloran Katrina , Abbou Samuel , Berlanga Pablo , Geoerger Birgit , Øra Ingrid , Moertel Christopher L. , Razis Evangelia D. , Vernadou Anastasia , Ducray François , Bronnimann Charlotte , Seizeur Romuald , Clarke Matthew , Resnick Adam C. , Alves Mélanie , Jones Chris , Doz François , Laetsch Theodore W. , Perreault Sébastien
Published: February 2025

AbstractPurpose:
Tropomyosin receptor kinase (TRK) fusions are detected in less than 2% of central nervous system tumors. There are limited data on the clinical course of affected patients.
Experimental Design:
We conducted an international retrospective cohort study of patients with TRK fusion–driven central nervous system tumors.
Results:
A total of 119 patients were identified. The median age at the time of diagnosis was 4.5 years. The majority were reported to have a histology consistent with a diagnosis of high-grade glioma (HGG; 57.1%) followed by low-grade glioma (LGG; 27.7%). Pediatric patients had a better prognosis, with a median overall survival of 185.5 months compared with 24.8 months in adults (P < 0.0001). Patients with LGG also had a better outcome when compared with HGG (P = 0.0012). The objective response was 68.8% with larotrectinib compared with 38.1% for nontargeted treatment.
Conclusions:
Children with LGG had a favorable outcome compared with adult glioma and HGG. TRK inhibitors seem to improve tumor control.
Data from Phase I Study of ROR1-Specific CAR-T Cells in Advanced Hematopoietic and Epithelial Malignancies
Authors: Jaeger-Ruckstuhl Carla A. , Specht Jennifer M. , Voutsinas Jenna M. , MacMillan Hugh R. , Wu Qian (Vicky) , Muhunthan Vishaka , Berger Carolina , Pullarkat Shalini , Wright Jocelyn H. , Yeung Cecilia C.S. , Hyun Teresa S. , Seaton Brandon , Aicher Lauri D. , Song Xiaoling , Pierce Robert H. , Lo Yun , Cole Gabriel O. , Lee Sylvia M. , Newell Evan W. , Maloney David G. , Riddell Stanley R.
Published: February 2025

AbstractPurpose:
The receptor tyrosine kinase–like orphan receptor 1 (ROR1) is expressed in hematopoietic and epithelial cancers but has limited expression on normal adult tissues. This phase I study evaluated the safety of targeting ROR1 with autologous T lymphocytes engineered to express a ROR1 chimeric antigen receptor (CAR). Secondary objectives evaluated the persistence, trafficking, and antitumor activity of CAR-T cells.
Patients and Methods:
Twenty-one patients with ROR1+ tumors received CAR-T cells at one of four dose levels: 3.3 × 105, 1 × 106, 3.3 × 106, and 1 × 107 cells/kg body weight, administered after lymphodepletion with cyclophosphamide/fludarabine or oxaliplatin/cyclophosphamide. Cohort A included patients with chronic lymphocytic leukemia (CLL, n = 3); cohort B included patients with triple-negative breast cancer (TNBC, n = 10) or non–small cell lung cancer (NSCLC, n = 8). A second infusion was administered to one patient in cohort A with residual CLL in the marrow and three patients in cohort B with stable disease after first infusion.
Results:
Treatment was well tolerated, apart from one dose-limiting toxicity at dose level 4 in a patient with advanced NSCLC. Two of the three (67%) patients with CLL showed robust CAR-T–cell expansion and a rapid antitumor response. In patients with NSCLC and TNBC, CAR-T cells expanded to variable levels and infiltrated tumors poorly and 1 of 18 patients (5.5%) achieved partial response by RECIST 1.1.
Conclusions:
ROR1 CAR-T cells were well tolerated in most patients. Antitumor activity was observed in CLL but was limited in TNBC and NSCLC. Immunogenicity of the CAR and lack of sustained tumor infiltration were identified as limitations.

See related commentary by Kobold, p. 437
Data from The Landscape of ctDNA in Appendiceal Adenocarcinoma
Authors: White Michael G. , Zeineddine Mohammad A. , Fallon Eleanor A. , Zeineddine Fadl A. , Dansby Julia , Chowdhury Saikat , Hornstein Nicholas , Yousef Abdelrahman , Yousef Mahmoud , Bhutiani Neal , Gu Yue , Kee Bryan , Dasari Arvind , Overman Michael J. , Raghav Kanwal , Kopetz Scott , Uppal Abhineet , Taggart Melissa , Newhook Timothy , Fournier Keith , Helmink Beth , Drusbosky Leylah M. , Shen John Paul
Published: February 2025

AbstractPurpose:
Appendiceal adenocarcinoma is a rare malignancy with distinct histopathologic subtypes and a natural history with metastasis primarily limited to the peritoneum. Little is known about the molecular pathogenesis of appendiceal adenocarcinoma relative to common tumors.
Experimental Design:
We analyzed molecular data for patients within the Guardant Health database with appendix cancer (n = 718). We then identified patients with appendiceal adenocarcinoma at our institution (from October 2004–September 2022) for whom ctDNA mutation profiling (liquid biopsy) was performed (n = 168) and extracted clinicopathologic and outcomes data. Of these 168 patients, 57 also had tissue-based tumor mutational profiling, allowing for evaluation of concordance between liquid and tissue assays.
Results:
The mutational landscape of ctDNA in appendiceal adenocarcinoma is distinct from tissue-based sequencing, with TP53 being the most frequently mutated (46%). Relative to other tumors, appendiceal adenocarcinoma seems less likely to shed ctDNA, with only 38% of patients with metastatic appendiceal adenocarcinoma having detectable ctDNA (OR = 0.26; P < 0.0001 relative to colorectal cancer). When detectable, the median variant allele frequency was significantly lower in appendiceal adenocarcinoma (0.4% vs. 1.3% for colorectal cancer; P ≤ 0.001). High-grade, signet ring, or colonic-type histology, metastatic spread beyond the peritoneum, and TP53 mutation were associated with detectable ctDNA. With respect to clinical translation, patients with detectable ctDNA had worse overall survival (HR = 2.32; P = 0.048). In the Guardant Health cohort, actionable mutations were found in 93 patients (13.0%).
Conclusions:
Although metastatic appendiceal adenocarcinoma tumors are less likely to shed tumor DNA into the blood relative to colorectal cancer, ctDNA profiling in appendiceal adenocarcinoma has clinical utility.
Supplementary Table S5 from Alcohol Consumption Does not Modify the Polygenic Risk Score–Based Genetic Risk of Breast Cancer in Postmenopausal Women: Atherosclerosis Risk in Communities Study
Authors: Zhang Minghui , Ru Meng , Zhang Jingning , Wang Ziqiao , Lu Jiayun , Butler Kenneth R. , Chatterjee Nilanjan , Couper David J. , Prizment Anna E. , Soori Mehrnoosh M. , Visvanathan Kala , Zahnow Cynthia A. , Joshu Corinne E. , Platz Elizabeth A.
Published: February 2025

Supplementary Table S5: The association between current ethanol intake and breast cancer incidence stratified by routine examinations frequency and by race in ARIC (1990-2015)
Supplementary Methods S1 from Roles of Necroptosis, Apoptosis, and Inflammation in Colorectal Carcinogenesis: A Longitudinal Human Study
Authors: Su Timothy , Zhu Xiangzhu , Li Yong , Yu Chang , Deng Xinqing , Shubin Eugene , Hou Lifang , Zhao Jing , Fan Lei , Zhang Heping , Murff Harvey J. , Ness Reid M. , Shrubsole Martha J. , Dai Qi
Published: February 2025

Supplementary Methods S1: FFPE protocol for cultured cell lines
Supplementary Figure S4 from Roles of Necroptosis, Apoptosis, and Inflammation in Colorectal Carcinogenesis: A Longitudinal Human Study
Authors: Su Timothy , Zhu Xiangzhu , Li Yong , Yu Chang , Deng Xinqing , Shubin Eugene , Hou Lifang , Zhao Jing , Fan Lei , Zhang Heping , Murff Harvey J. , Ness Reid M. , Shrubsole Martha J. , Dai Qi
Published: February 2025

Supplementary Figure S4: The potential mechanisms for the interaction of necroptosis, apoptosis, and inflammation in colorectal carcinogenesis
Supplementary Figure S1 from Roles of Necroptosis, Apoptosis, and Inflammation in Colorectal Carcinogenesis: A Longitudinal Human Study
Authors: Su Timothy , Zhu Xiangzhu , Li Yong , Yu Chang , Deng Xinqing , Shubin Eugene , Hou Lifang , Zhao Jing , Fan Lei , Zhang Heping , Murff Harvey J. , Ness Reid M. , Shrubsole Martha J. , Dai Qi
Published: February 2025

FFPE protocol for cultured cell lines
Supplementary Figure S6 from Alcohol Consumption Does not Modify the Polygenic Risk Score–Based Genetic Risk of Breast Cancer in Postmenopausal Women: Atherosclerosis Risk in Communities Study
Authors: Zhang Minghui , Ru Meng , Zhang Jingning , Wang Ziqiao , Lu Jiayun , Butler Kenneth R. , Chatterjee Nilanjan , Couper David J. , Prizment Anna E. , Soori Mehrnoosh M. , Visvanathan Kala , Zahnow Cynthia A. , Joshu Corinne E. , Platz Elizabeth A.
Published: February 2025

Supplementary Figure S6: Natural logarithm hazard ratios of breast cancer for P-spline term scaled 313-SNP PRS with 4 degrees of freedom estimated by fully-adjusted Cox proportional hazards model stratified by alcohol consumption category among Black women in ARIC (1990-2015)
Supplementary Figure S5 from Alcohol Consumption Does not Modify the Polygenic Risk Score–Based Genetic Risk of Breast Cancer in Postmenopausal Women: Atherosclerosis Risk in Communities Study
Authors: Zhang Minghui , Ru Meng , Zhang Jingning , Wang Ziqiao , Lu Jiayun , Butler Kenneth R. , Chatterjee Nilanjan , Couper David J. , Prizment Anna E. , Soori Mehrnoosh M. , Visvanathan Kala , Zahnow Cynthia A. , Joshu Corinne E. , Platz Elizabeth A.
Published: February 2025

Supplementary Figure S5: Natural logarithm hazard ratios of breast cancer for P-spline term scaled 313-SNP PRS with 4 degrees of freedom estimated by fully-adjusted Cox proportional hazards model stratified by alcohol consumption category among White women in ARIC (1990-2015)
Supplemental Table 8 from Metabolic Phenotype and Risk of Obesity-Related Cancers in the Women’s Health Initiative
Authors: Karra Prasoona , Hardikar Sheetal , Winn Maci , Anderson Garnet L. , Haaland Benjamin , Shadyab Aladdin H. , Neuhouser Marian L. , Seguin-Fowler Rebecca A. , Thomson Cynthia A. , Coday Mace , Wactawski-Wende Jean , Stefanick Marcia L. , Zhang Xiaochen , Cheng Ting-Yuan David , Karanth Shama , Sun Yangbo , Saquib Nazmus , Pichardo Margaret S. , Jung Su Yon , Tabung Fred K. , Summers Scott A. , Holland William L. , Jalili Thunder , Gunter Marc J. , Playdon Mary C.
Published: February 2025

Supplemental Table 8. Association between individual metabolic dysfunction components with obesity-related cancer risk in the Women’s Health Initiative cohort (N= 20,593).
Supplementary Figure S3 from Alcohol Consumption Does not Modify the Polygenic Risk Score–Based Genetic Risk of Breast Cancer in Postmenopausal Women: Atherosclerosis Risk in Communities Study
Authors: Zhang Minghui , Ru Meng , Zhang Jingning , Wang Ziqiao , Lu Jiayun , Butler Kenneth R. , Chatterjee Nilanjan , Couper David J. , Prizment Anna E. , Soori Mehrnoosh M. , Visvanathan Kala , Zahnow Cynthia A. , Joshu Corinne E. , Platz Elizabeth A.
Published: February 2025

Supplementary Figure S3: Natural logarithm hazard ratios of breast cancer for P-spline term scaled 313-SNP PRS with 4 degrees of freedom estimated by fully-adjusted Cox proportional hazards model in ARIC (1990-2015)
Supplementary Figure S2 from Alcohol Consumption Does not Modify the Polygenic Risk Score–Based Genetic Risk of Breast Cancer in Postmenopausal Women: Atherosclerosis Risk in Communities Study
Authors: Zhang Minghui , Ru Meng , Zhang Jingning , Wang Ziqiao , Lu Jiayun , Butler Kenneth R. , Chatterjee Nilanjan , Couper David J. , Prizment Anna E. , Soori Mehrnoosh M. , Visvanathan Kala , Zahnow Cynthia A. , Joshu Corinne E. , Platz Elizabeth A.
Published: February 2025

Supplementary Figure S2: Time-dependent coefficients of current ethanol intake for breast cancer incidence estimated by fully adjusted Cox proportional hazards model in ARIC (1990-2015)
Supplementary Figure S1 from Alcohol Consumption Does not Modify the Polygenic Risk Score–Based Genetic Risk of Breast Cancer in Postmenopausal Women: Atherosclerosis Risk in Communities Study
Authors: Zhang Minghui , Ru Meng , Zhang Jingning , Wang Ziqiao , Lu Jiayun , Butler Kenneth R. , Chatterjee Nilanjan , Couper David J. , Prizment Anna E. , Soori Mehrnoosh M. , Visvanathan Kala , Zahnow Cynthia A. , Joshu Corinne E. , Platz Elizabeth A.
Published: February 2025

Supplementary Figure S1: Time-dependent coefficients of scaled 313-SNP PRS for breast cancer incidence estimated by fully adjusted Cox proportional hazards model in ARIC (1990-2015)
Supplemental Table 2 from Metabolic Phenotype and Risk of Obesity-Related Cancers in the Women’s Health Initiative
Authors: Karra Prasoona , Hardikar Sheetal , Winn Maci , Anderson Garnet L. , Haaland Benjamin , Shadyab Aladdin H. , Neuhouser Marian L. , Seguin-Fowler Rebecca A. , Thomson Cynthia A. , Coday Mace , Wactawski-Wende Jean , Stefanick Marcia L. , Zhang Xiaochen , Cheng Ting-Yuan David , Karanth Shama , Sun Yangbo , Saquib Nazmus , Pichardo Margaret S. , Jung Su Yon , Tabung Fred K. , Summers Scott A. , Holland William L. , Jalili Thunder , Gunter Marc J. , Playdon Mary C.
Published: February 2025

Supplemental Table 2. Association between metabolic phenotypes defined by Wildman criteria with obesity-related cancer risk in the Women’s Health Initiative cohort (N= 20,593).
Supplemental Table 1 from Metabolic Phenotype and Risk of Obesity-Related Cancers in the Women’s Health Initiative
Authors: Karra Prasoona , Hardikar Sheetal , Winn Maci , Anderson Garnet L. , Haaland Benjamin , Shadyab Aladdin H. , Neuhouser Marian L. , Seguin-Fowler Rebecca A. , Thomson Cynthia A. , Coday Mace , Wactawski-Wende Jean , Stefanick Marcia L. , Zhang Xiaochen , Cheng Ting-Yuan David , Karanth Shama , Sun Yangbo , Saquib Nazmus , Pichardo Margaret S. , Jung Su Yon , Tabung Fred K. , Summers Scott A. , Holland William L. , Jalili Thunder , Gunter Marc J. , Playdon Mary C.
Published: February 2025

Supplemental Table 1. Criteria for metabolic phenotype classification. HDL high density lipoprotein cholesterol; HOMA-IR Homeostatic Model Assessment for Insulin Resistance ; hs-CRP high sensitive C-reactive protein
Supplemental Figure 7 from Metabolic Phenotype and Risk of Obesity-Related Cancers in the Women’s Health Initiative
Authors: Karra Prasoona , Hardikar Sheetal , Winn Maci , Anderson Garnet L. , Haaland Benjamin , Shadyab Aladdin H. , Neuhouser Marian L. , Seguin-Fowler Rebecca A. , Thomson Cynthia A. , Coday Mace , Wactawski-Wende Jean , Stefanick Marcia L. , Zhang Xiaochen , Cheng Ting-Yuan David , Karanth Shama , Sun Yangbo , Saquib Nazmus , Pichardo Margaret S. , Jung Su Yon , Tabung Fred K. , Summers Scott A. , Holland William L. , Jalili Thunder , Gunter Marc J. , Playdon Mary C.
Published: February 2025

Supplemental Figure 7. Hazard ratios and 95% confidence intervals for the association of metabolic phenotype defined by Homeostatic Model Assessment for Insulin Resistance (HOMA-IR) with obesity-related cancer risk, stratified by cancer type among postmenopausal women in the Women’s Health Initiative. Model adjusted for demographics (age, education, race/ethnicity, marital status), lifestyle (smoking status, physical activity, alcohol use, fruits and vegetable intake, fiber intake, read meat intake), hormonal factors for female cancers (parity, hormone therapy use), family history of ORC and study ID. MUNW=metabolically unhealthy normal weight; MHO=metabolically healthy overweight/obese; MUO= metabolically unhealthy overweight/obese. Metabolically healthy normal weight (MHNW) is the comparison group.
Supplemental Figure 6 from Metabolic Phenotype and Risk of Obesity-Related Cancers in the Women’s Health Initiative
Authors: Karra Prasoona , Hardikar Sheetal , Winn Maci , Anderson Garnet L. , Haaland Benjamin , Shadyab Aladdin H. , Neuhouser Marian L. , Seguin-Fowler Rebecca A. , Thomson Cynthia A. , Coday Mace , Wactawski-Wende Jean , Stefanick Marcia L. , Zhang Xiaochen , Cheng Ting-Yuan David , Karanth Shama , Sun Yangbo , Saquib Nazmus , Pichardo Margaret S. , Jung Su Yon , Tabung Fred K. , Summers Scott A. , Holland William L. , Jalili Thunder , Gunter Marc J. , Playdon Mary C.
Published: February 2025

Supplemental Figure 6. Hazard ratios and 95% confidence intervals for the association of metabolic phenotype defined by C-Reactive Protein (hs-CRP) (A) ≥ 3 mg/L, (B) ≥ 10 mg/L with obesity-related cancer risk, stratified by cancer type among postmenopausal women in the Women’s Health Initiative. Model adjusted for demographics (age, education, race/ethnicity, marital status), lifestyle (smoking status, physical activity, alcohol use, fruits and vegetable intake, fiber intake, read meat intake), hormonal factors for female cancers (parity, hormone therapy use), family history of ORC and study ID. MUNW=metabolically unhealthy normal weight; MHO=metabolically healthy overweight/obese; MUO= metabolically unhealthy overweight/obese. Metabolically healthy normal weight (MHNW) is the comparison group.
Supplemental Figure 4 from Metabolic Phenotype and Risk of Obesity-Related Cancers in the Women’s Health Initiative
Authors: Karra Prasoona , Hardikar Sheetal , Winn Maci , Anderson Garnet L. , Haaland Benjamin , Shadyab Aladdin H. , Neuhouser Marian L. , Seguin-Fowler Rebecca A. , Thomson Cynthia A. , Coday Mace , Wactawski-Wende Jean , Stefanick Marcia L. , Zhang Xiaochen , Cheng Ting-Yuan David , Karanth Shama , Sun Yangbo , Saquib Nazmus , Pichardo Margaret S. , Jung Su Yon , Tabung Fred K. , Summers Scott A. , Holland William L. , Jalili Thunder , Gunter Marc J. , Playdon Mary C.
Published: February 2025

Supplemental Figure 4. Hazard ratios and 95% confidence intervals for the association of metabolic phenotype defined by the Wildman criteria with obesity-related cancer risk, stratified by cancer type among postmenopausal women in the Women’s Health Initiative. Model adjusted for demographics (age, education, race/ethnicity, marital status), lifestyle (smoking status, physical activity, alcohol use, fruits and vegetable intake, fiber intake, read meat intake), hormonal factors for female cancers (parity, hormone therapy use), family history of ORC and study ID. MUNW=metabolically unhealthy normal weight; MHO=metabolically healthy overweight/obese; MUO= metabolically unhealthy overweight/obese. Metabolically healthy normal weight (MHNW) is the comparison group.
Data from Roles of Necroptosis, Apoptosis, and Inflammation in Colorectal Carcinogenesis: A Longitudinal Human Study
Authors: Su Timothy , Zhu Xiangzhu , Li Yong , Yu Chang , Deng Xinqing , Shubin Eugene , Hou Lifang , Zhao Jing , Fan Lei , Zhang Heping , Murff Harvey J. , Ness Reid M. , Shrubsole Martha J. , Dai Qi
Published: February 2025

Abstract
Necroptosis triggers an inflammatory cascade associated with antimicrobial defense. No prospective human study has yet explored the role of necroptosis in colorectal cancer development. We conducted quantitative analysis of biomarkers for necroptosis [transient receptor potential cation channel subfamily M member 7 (TRPM7) and phosphorylated mixed lineage kinase domain-like protein], inflammation [cyclooxygenase-2 (COX-2)], apoptosis [BCL2-associated X (BAX) and terminal deoxynucleotidyl transferase dUTP nick end labeling], and cell proliferation (Ki67). This was done using tissue microarray biospecimens from the Cooperative Human Tissue Network and rectal biopsies from a longitudinal study within the Personalized Prevention of Colorectal Cancer Trial. In the human colorectal adenoma–carcinoma sequence, we observed an inverse expression trend between BAX and TRPM7; TRPM7 decreased from normal mucosa to small and large adenomas but significantly increased in early colorectal cancer stages (Ptrend = 0.004). It maintained high levels through all cancer stages. An increased COX-2 intensity in the epithelium was noted during tumorigenesis (Ptrend = 0.02) and was significantly associated with an elevated risk of metachronous polyps (odds ratio = 3.04; 95% confidence interval, 1.07–8.61; Ptrend = 0.02). The combined composite index scores of TRPM7 and COX-2 were strongly linked to 6- to 47-fold increased risks for metachronous adenoma/serrated polyps, whereas combined scores of phosphorylated mixed lineage kinase domain-like protein or TRPM7 with BAX were associated with an 11.5- or 13.3-fold elevated risk for metachronous serrated polyps. In conclusion, our findings suggest that COX-2 expression within normal-looking colorectal mucosa is significantly associated with an increased risk of metachronous colorectal polyp. Furthermore, our results propose the hypothesis that synergistic interactions among necroptosis, inflammation, and apoptosis could play a pivotal role in human colorectal tumorigenesis.

Prevention Relevance: Our findings suggest that COX-2 expression and combined scores of COX-2, TRPM7, and BAX hold promise for predicting the risk of metachronous polyps and could potentially serve as a tool for assessing the effectiveness of chemopreventive agents in preventing colorectal cancer during intervention trials.
Data from Metabolic Phenotype and Risk of Obesity-Related Cancers in the Women’s Health Initiative
Authors: Karra Prasoona , Hardikar Sheetal , Winn Maci , Anderson Garnet L. , Haaland Benjamin , Shadyab Aladdin H. , Neuhouser Marian L. , Seguin-Fowler Rebecca A. , Thomson Cynthia A. , Coday Mace , Wactawski-Wende Jean , Stefanick Marcia L. , Zhang Xiaochen , Cheng Ting-Yuan David , Karanth Shama , Sun Yangbo , Saquib Nazmus , Pichardo Margaret S. , Jung Su Yon , Tabung Fred K. , Summers Scott A. , Holland William L. , Jalili Thunder , Gunter Marc J. , Playdon Mary C.
Published: February 2025

Abstract
Body mass index (BMI) may misclassify obesity-related cancer (ORC) risk, as metabolic dysfunction can occur across BMI levels. We hypothesized that metabolic dysfunction at any BMI increases ORC risk compared with normal BMI without metabolic dysfunction. Postmenopausal women (n = 20,593) in the Women’s Health Initiative with baseline metabolic dysfunction biomarkers [blood pressure, fasting triglycerides, high-density lipoprotein cholesterol, fasting glucose, homeostatic model assessment for insulin resistance (HOMA-IR), and high-sensitive C-reactive protein (hs-CRP)] were included. Metabolic phenotype (metabolically healthy normal weight, metabolically unhealthy normal weight, metabolically healthy overweight/obese, and metabolically unhealthy overweight/obese) was classified using four definitions of metabolic dysfunction: (i) Wildman criteria, (ii) National Cholesterol Education Program Adult Treatment Panel III, (iii) HOMA-IR, and (iv) hs-CRP. Multivariable Cox proportional hazards regression, with death as a competing risk, was used to assess the association between metabolic phenotype and ORC risk. After a median (IQR) follow-up duration of 21 (IQR, 15–22) years, 2,367 women developed an ORC. The risk of any ORC was elevated among metabolically unhealthy normal weight (HR = 1.12, 95% CI, 0.90–1.39), metabolically healthy overweight/obese (HR = 1.15, 95% CI, 1.00–1.32), and metabolically unhealthy overweight/obese (HR = 1.35, 95% CI, 1.18–1.54) individuals compared with metabolically healthy normal weight individuals using Wildman criteria. The results were similar using Adult Treatment Panel III criteria, hs-CRP alone, or HOMA-IR alone to define metabolic phenotype. Individuals with overweight or obesity with or without metabolic dysfunction were at higher risk of ORCs compared with metabolically healthy normal weight individuals. The magnitude of risk was greater among those with metabolic dysfunction, although the CIs of each category overlapped.

Prevention Relevance: Recognizing metabolic dysfunction as a significant risk factor for ORCs underscores the importance of preventive measures targeting metabolic health improvement across all BMI categories.
Table S2 from A PSMA-Targeted Tri-Specific Killer Engager Enhances NK Cell Cytotoxicity against Prostate Cancer
Authors: Phung Shee Kwan , Zorko Nicholas A. , Soignier Yvette , Waller Rhett L. , Shackelford Madison , Walker Joshua T. , Nelson Trygve D. , Selleck Carly , Bendzick Laura E. , Kotz Laura E. , Kile Quinlan M. , Bozicevich Asha J. , Miller Sarah E. , Khaw Melissa , Shetty Mihir , Hinderlie Peter , Ehrhardt Michael , Li Yingming , Luo Xianghua , Dehm Scott M. , Antonarakis Emmanuel S. , Kennedy Philippa R. , Miller Jeffrey S. , Felices Martin
Published: February 2025

Patient characteristics.
Figure S8 from A PSMA-Targeted Tri-Specific Killer Engager Enhances NK Cell Cytotoxicity against Prostate Cancer
Authors: Phung Shee Kwan , Zorko Nicholas A. , Soignier Yvette , Waller Rhett L. , Shackelford Madison , Walker Joshua T. , Nelson Trygve D. , Selleck Carly , Bendzick Laura E. , Kotz Laura E. , Kile Quinlan M. , Bozicevich Asha J. , Miller Sarah E. , Khaw Melissa , Shetty Mihir , Hinderlie Peter , Ehrhardt Michael , Li Yingming , Luo Xianghua , Dehm Scott M. , Antonarakis Emmanuel S. , Kennedy Philippa R. , Miller Jeffrey S. , Felices Martin
Published: February 2025

Healthy donors and prostate cancer patient-derived NK cell killing capacity.
Figure S7 from A PSMA-Targeted Tri-Specific Killer Engager Enhances NK Cell Cytotoxicity against Prostate Cancer
Authors: Phung Shee Kwan , Zorko Nicholas A. , Soignier Yvette , Waller Rhett L. , Shackelford Madison , Walker Joshua T. , Nelson Trygve D. , Selleck Carly , Bendzick Laura E. , Kotz Laura E. , Kile Quinlan M. , Bozicevich Asha J. , Miller Sarah E. , Khaw Melissa , Shetty Mihir , Hinderlie Peter , Ehrhardt Michael , Li Yingming , Luo Xianghua , Dehm Scott M. , Antonarakis Emmanuel S. , Kennedy Philippa R. , Miller Jeffrey S. , Felices Martin
Published: February 2025

Secretome analysis of supernatant from co-culture of NK cells with monocytes or MDSCs.
Figure S5 from A PSMA-Targeted Tri-Specific Killer Engager Enhances NK Cell Cytotoxicity against Prostate Cancer
Authors: Phung Shee Kwan , Zorko Nicholas A. , Soignier Yvette , Waller Rhett L. , Shackelford Madison , Walker Joshua T. , Nelson Trygve D. , Selleck Carly , Bendzick Laura E. , Kotz Laura E. , Kile Quinlan M. , Bozicevich Asha J. , Miller Sarah E. , Khaw Melissa , Shetty Mihir , Hinderlie Peter , Ehrhardt Michael , Li Yingming , Luo Xianghua , Dehm Scott M. , Antonarakis Emmanuel S. , Kennedy Philippa R. , Miller Jeffrey S. , Felices Martin
Published: February 2025

CyTOF analysis of NK cell surface expression.
Figure S4 from A PSMA-Targeted Tri-Specific Killer Engager Enhances NK Cell Cytotoxicity against Prostate Cancer
Authors: Phung Shee Kwan , Zorko Nicholas A. , Soignier Yvette , Waller Rhett L. , Shackelford Madison , Walker Joshua T. , Nelson Trygve D. , Selleck Carly , Bendzick Laura E. , Kotz Laura E. , Kile Quinlan M. , Bozicevich Asha J. , Miller Sarah E. , Khaw Melissa , Shetty Mihir , Hinderlie Peter , Ehrhardt Michael , Li Yingming , Luo Xianghua , Dehm Scott M. , Antonarakis Emmanuel S. , Kennedy Philippa R. , Miller Jeffrey S. , Felices Martin
Published: February 2025

Representative images (10X magnification) from the IncuCyte live cell imaging assay.
Figure S3 from A PSMA-Targeted Tri-Specific Killer Engager Enhances NK Cell Cytotoxicity against Prostate Cancer
Authors: Phung Shee Kwan , Zorko Nicholas A. , Soignier Yvette , Waller Rhett L. , Shackelford Madison , Walker Joshua T. , Nelson Trygve D. , Selleck Carly , Bendzick Laura E. , Kotz Laura E. , Kile Quinlan M. , Bozicevich Asha J. , Miller Sarah E. , Khaw Melissa , Shetty Mihir , Hinderlie Peter , Ehrhardt Michael , Li Yingming , Luo Xianghua , Dehm Scott M. , Antonarakis Emmanuel S. , Kennedy Philippa R. , Miller Jeffrey S. , Felices Martin
Published: February 2025

Antigen specificity test of PSMA TriKE.
Figure S6 from Setdb1 Loss Induces Type I Interferons and Immune Clearance of Melanoma
Authors: McGeary Meaghan K. , Damsky William , Daniels Andrew J. , Lang Sabine M. , Xu Qingji , Song Eric , Huet-Calderwood Clotilde , Lou Hua Jane , Paradkar Sateja , Micevic Goran , Kaech Susan M. , Calderwood David A. , Turk Benjamin E. , Yan Qin , Iwasaki Akiko , Bosenberg Marcus W.
Published: February 2025

Figure S6: Characterization of possible SKO tumor antigens, related to Figure 4.
Figure S3 from Setdb1 Loss Induces Type I Interferons and Immune Clearance of Melanoma
Authors: McGeary Meaghan K. , Damsky William , Daniels Andrew J. , Lang Sabine M. , Xu Qingji , Song Eric , Huet-Calderwood Clotilde , Lou Hua Jane , Paradkar Sateja , Micevic Goran , Kaech Susan M. , Calderwood David A. , Turk Benjamin E. , Yan Qin , Iwasaki Akiko , Bosenberg Marcus W.
Published: February 2025

Figure S3: Validation and characterization of Setdb1-/- cell lines, tumors, and microenvironments, related to Figure 2.
Figure S2 from Setdb1 Loss Induces Type I Interferons and Immune Clearance of Melanoma
Authors: McGeary Meaghan K. , Damsky William , Daniels Andrew J. , Lang Sabine M. , Xu Qingji , Song Eric , Huet-Calderwood Clotilde , Lou Hua Jane , Paradkar Sateja , Micevic Goran , Kaech Susan M. , Calderwood David A. , Turk Benjamin E. , Yan Qin , Iwasaki Akiko , Bosenberg Marcus W.
Published: February 2025

Figure S2: CRISPR screen guide distributions, related to Figure 1
Supplementary Data from Combination CXCR4 and PD-1 Blockade Enhances Intratumoral Dendritic Cell Activation and Immune Responses Against Hepatocellular Carcinoma
Authors: Morita Satoru , Lei Pin-Ji , Shigeta Kohei , Ando Tomofumi , Kobayashi Tatsuya , Kikuchi Hiroto , Matsui Aya , Huang Peigen , Pittet Mikael J. , Duda Dan G.
Published: February 2025

Supplementary Methods
Figure S6 from Combination CXCR4 and PD-1 Blockade Enhances Intratumoral Dendritic Cell Activation and Immune Responses Against Hepatocellular Carcinoma
Authors: Morita Satoru , Lei Pin-Ji , Shigeta Kohei , Ando Tomofumi , Kobayashi Tatsuya , Kikuchi Hiroto , Matsui Aya , Huang Peigen , Pittet Mikael J. , Duda Dan G.
Published: February 2025

Supplementary Figure S6
Table S1 from TBK1 Targeting Is Identified as a Therapeutic Strategy to Enhance CAR T-Cell Efficacy Using Patient-Derived Organotypic Tumor Spheroids
Authors: Sun Yi , Maggs Luke , Panda Apekshya , Wright Samuel J. , Cicerchia Angelina M. , Jenney Anne , Perricone Matthew D. , Mills Caitlin E. , Cattaneo Giulia , Ventin Marco , Chen Feng , Rasmussen Martin Q. , Miranda Alex , Revach Or-Yam , Fang Jacy , Fu Amina , Bowling Peter J. , Sharova Tatyana , Lawless Aleigha , Sorger Peter K. , Bardeesy Nabeel , Wang Xinhui , Flaherty Keith T. , Boland Genevieve M. , Mehta Arnav , Sade-Feldman Moshe , Ferrone Cristina R. , Jenkins Russell W.
Published: February 2025

PDOTS patient data (accompanying Fig. 1)
Figure S7 from TBK1 Targeting Is Identified as a Therapeutic Strategy to Enhance CAR T-Cell Efficacy Using Patient-Derived Organotypic Tumor Spheroids
Authors: Sun Yi , Maggs Luke , Panda Apekshya , Wright Samuel J. , Cicerchia Angelina M. , Jenney Anne , Perricone Matthew D. , Mills Caitlin E. , Cattaneo Giulia , Ventin Marco , Chen Feng , Rasmussen Martin Q. , Miranda Alex , Revach Or-Yam , Fang Jacy , Fu Amina , Bowling Peter J. , Sharova Tatyana , Lawless Aleigha , Sorger Peter K. , Bardeesy Nabeel , Wang Xinhui , Flaherty Keith T. , Boland Genevieve M. , Mehta Arnav , Sade-Feldman Moshe , Ferrone Cristina R. , Jenkins Russell W.
Published: February 2025

Supplemental Figure S7 | Supporting data that targeting TBK1 prevents CAR-T cell dysfunction.
Table S5 from Identification and Phenotypic Characterization of Neoantigen-Specific Cytotoxic CD4+ T Cells in Endometrial Cancer
Authors: Fusagawa Minami , Tokita Serina , Murata Kenji , Mariya Tasuku , Umemoto Mina , Sugita Shintaro , Matsuo Kazuhiko , Hirohashi Yoshihiko , Saito Tsuyoshi , Kanaseki Takayuki , Torigoe Toshihiko
Published: February 2025

Table S5
Figure S5 from TBK1 Targeting Is Identified as a Therapeutic Strategy to Enhance CAR T-Cell Efficacy Using Patient-Derived Organotypic Tumor Spheroids
Authors: Sun Yi , Maggs Luke , Panda Apekshya , Wright Samuel J. , Cicerchia Angelina M. , Jenney Anne , Perricone Matthew D. , Mills Caitlin E. , Cattaneo Giulia , Ventin Marco , Chen Feng , Rasmussen Martin Q. , Miranda Alex , Revach Or-Yam , Fang Jacy , Fu Amina , Bowling Peter J. , Sharova Tatyana , Lawless Aleigha , Sorger Peter K. , Bardeesy Nabeel , Wang Xinhui , Flaherty Keith T. , Boland Genevieve M. , Mehta Arnav , Sade-Feldman Moshe , Ferrone Cristina R. , Jenkins Russell W.
Published: February 2025

Supplemental Figure S5 | Supporting data that targeting TBK1 prevents CAR-T cell dysfunction.
Figure S11 from TBK1 Targeting Is Identified as a Therapeutic Strategy to Enhance CAR T-Cell Efficacy Using Patient-Derived Organotypic Tumor Spheroids
Authors: Sun Yi , Maggs Luke , Panda Apekshya , Wright Samuel J. , Cicerchia Angelina M. , Jenney Anne , Perricone Matthew D. , Mills Caitlin E. , Cattaneo Giulia , Ventin Marco , Chen Feng , Rasmussen Martin Q. , Miranda Alex , Revach Or-Yam , Fang Jacy , Fu Amina , Bowling Peter J. , Sharova Tatyana , Lawless Aleigha , Sorger Peter K. , Bardeesy Nabeel , Wang Xinhui , Flaherty Keith T. , Boland Genevieve M. , Mehta Arnav , Sade-Feldman Moshe , Ferrone Cristina R. , Jenkins Russell W.
Published: February 2025

Supplemental Figure S11 | Supporting data that targeting TBK1 sensitizes cancer cells to CAR-T cell-derived TNFα/IFNγ.
Figure S10 from TBK1 Targeting Is Identified as a Therapeutic Strategy to Enhance CAR T-Cell Efficacy Using Patient-Derived Organotypic Tumor Spheroids
Authors: Sun Yi , Maggs Luke , Panda Apekshya , Wright Samuel J. , Cicerchia Angelina M. , Jenney Anne , Perricone Matthew D. , Mills Caitlin E. , Cattaneo Giulia , Ventin Marco , Chen Feng , Rasmussen Martin Q. , Miranda Alex , Revach Or-Yam , Fang Jacy , Fu Amina , Bowling Peter J. , Sharova Tatyana , Lawless Aleigha , Sorger Peter K. , Bardeesy Nabeel , Wang Xinhui , Flaherty Keith T. , Boland Genevieve M. , Mehta Arnav , Sade-Feldman Moshe , Ferrone Cristina R. , Jenkins Russell W.
Published: February 2025

Supplemental Figure S10 | Supporting data for single cell RNA sequencing of native tumor-infiltrating lymphocytes following CAR-T challenge in 3D co-cultures with PDOTS.
Fig. S8 from Identification and Phenotypic Characterization of Neoantigen-Specific Cytotoxic CD4+ T Cells in Endometrial Cancer
Authors: Fusagawa Minami , Tokita Serina , Murata Kenji , Mariya Tasuku , Umemoto Mina , Sugita Shintaro , Matsuo Kazuhiko , Hirohashi Yoshihiko , Saito Tsuyoshi , Kanaseki Takayuki , Torigoe Toshihiko
Published: February 2025

Fig. S8 | Cytokine production by neoantigen-specific CD4+ TIL clones.
Fig. S7 from Identification and Phenotypic Characterization of Neoantigen-Specific Cytotoxic CD4+ T Cells in Endometrial Cancer
Authors: Fusagawa Minami , Tokita Serina , Murata Kenji , Mariya Tasuku , Umemoto Mina , Sugita Shintaro , Matsuo Kazuhiko , Hirohashi Yoshihiko , Saito Tsuyoshi , Kanaseki Takayuki , Torigoe Toshihiko
Published: February 2025

Fig.S7|Phenotypiccharacterizationofneoantigen-specificCD4+TILclones.
Table S3 from The HSP90 Inhibitor Pimitespib Targets Regulatory T Cells in the Tumor Microenvironment
Authors: Tsuge Ayaka , Watanabe Sho , Kawazoe Akihito , Togashi Yosuke , Itahashi Kota , Masuda Mari , Sai Atsuo , Takei Shogo , Muraoka Hiromi , Ohkubo Shuichi , Sugiyama Daisuke , Yan Yue , Fukuoka Shota , Doi Toshihiko , Shitara Kohei , Koyama Shohei , Nishikawa Hiroyoshi
Published: February 2025

MHC/peptide multimers used for antigen-specific T-cell induction and detection.
Table S2 from The HSP90 Inhibitor Pimitespib Targets Regulatory T Cells in the Tumor Microenvironment
Authors: Tsuge Ayaka , Watanabe Sho , Kawazoe Akihito , Togashi Yosuke , Itahashi Kota , Masuda Mari , Sai Atsuo , Takei Shogo , Muraoka Hiromi , Ohkubo Shuichi , Sugiyama Daisuke , Yan Yue , Fukuoka Shota , Doi Toshihiko , Shitara Kohei , Koyama Shohei , Nishikawa Hiroyoshi
Published: February 2025

Primary antibodies and associated Opal fluorophore applications used for multiplex immunohistochemistry.