bluuebunny/crossref_metadata_2025 huggingface dataset:
Figure S7 from Clinically Relevant Humanized Mouse Models of Metastatic Prostate Cancer Facilitate Therapeutic Evaluation
Authors: Kostlan Raymond J. , Phoenix John T. , Budreika Audris , Ferrari Marina G. , Khurana Neetika , Choi Jae E. , Juckette Kristin , Mahapatra Somnath , McCollum Brooke L. , Moskal Russell , Mannan Rahul , Qiao Yuanyuan , Vander Griend Donald J. , Chinnaiyan Arul M. , Kregel Steven
Published: September 2024

Percentage of CD3+ cells showing TNF-α expression via intracellular staining isolated from subcutaneous 22Rv1 tumors huNOG mice.
Supplementary Figure S5 from miR-497 Target Gene Regulatory Network in Angiosarcoma
Authors: Benton Annaleigh , Moriarty Noah M. , Terwilliger Emma , Liu Bozhi , Murphy Ant , Maluvac Hannah , Shu Mae , Gartenhaus Lauren E. , Janson Nimod D. , Pfeffer Claire M. , Utturkar Sagar M. , Parkinson Elizabeth I. , Lanman Nadia A. , Hanna Jason A.
Published: September 2024

miR-497 expression in SVR allografts.
Figure S5 from Clinically Relevant Humanized Mouse Models of Metastatic Prostate Cancer Facilitate Therapeutic Evaluation
Authors: Kostlan Raymond J. , Phoenix John T. , Budreika Audris , Ferrari Marina G. , Khurana Neetika , Choi Jae E. , Juckette Kristin , Mahapatra Somnath , McCollum Brooke L. , Moskal Russell , Mannan Rahul , Qiao Yuanyuan , Vander Griend Donald J. , Chinnaiyan Arul M. , Kregel Steven
Published: September 2024

Metastasis by 22Rv1 to the lung in huNOG and huNOG-EXL mice.
Supplementary Figure S4 from miR-497 Target Gene Regulatory Network in Angiosarcoma
Authors: Benton Annaleigh , Moriarty Noah M. , Terwilliger Emma , Liu Bozhi , Murphy Ant , Maluvac Hannah , Shu Mae , Gartenhaus Lauren E. , Janson Nimod D. , Pfeffer Claire M. , Utturkar Sagar M. , Parkinson Elizabeth I. , Lanman Nadia A. , Hanna Jason A.
Published: September 2024

Genetic depletion of VAT1 inhibits cell migration.
Figure S3 from Clinically Relevant Humanized Mouse Models of Metastatic Prostate Cancer Facilitate Therapeutic Evaluation
Authors: Kostlan Raymond J. , Phoenix John T. , Budreika Audris , Ferrari Marina G. , Khurana Neetika , Choi Jae E. , Juckette Kristin , Mahapatra Somnath , McCollum Brooke L. , Moskal Russell , Mannan Rahul , Qiao Yuanyuan , Vander Griend Donald J. , Chinnaiyan Arul M. , Kregel Steven
Published: September 2024

Metastasis by 22Rv1 to the skull in huNOG and huNOG-EXL mice.
Figure S2 from Clinically Relevant Humanized Mouse Models of Metastatic Prostate Cancer Facilitate Therapeutic Evaluation
Authors: Kostlan Raymond J. , Phoenix John T. , Budreika Audris , Ferrari Marina G. , Khurana Neetika , Choi Jae E. , Juckette Kristin , Mahapatra Somnath , McCollum Brooke L. , Moskal Russell , Mannan Rahul , Qiao Yuanyuan , Vander Griend Donald J. , Chinnaiyan Arul M. , Kregel Steven
Published: September 2024

Metastasis by 22Rv1 to the humerus in huNOG and huNOG-EXL mice.
Figure S12 from Clinically Relevant Humanized Mouse Models of Metastatic Prostate Cancer Facilitate Therapeutic Evaluation
Authors: Kostlan Raymond J. , Phoenix John T. , Budreika Audris , Ferrari Marina G. , Khurana Neetika , Choi Jae E. , Juckette Kristin , Mahapatra Somnath , McCollum Brooke L. , Moskal Russell , Mannan Rahul , Qiao Yuanyuan , Vander Griend Donald J. , Chinnaiyan Arul M. , Kregel Steven
Published: September 2024

Multi-IF for CD3, CD8 and Granzyme B of 22Rv1 tumors in huNOG-EXL mice.
Table S1 from MLLT6/ATF2 Axis Restrains Breast Cancer Progression by Driving DDIT3/4 Expression
Authors: Yu Qing , Zhao Jiayi , Yang Anli , Li Xiangxin
Published: September 2024

Primer sequence for constructs
Figure S2 from MLLT6/ATF2 Axis Restrains Breast Cancer Progression by Driving DDIT3/4 Expression
Authors: Yu Qing , Zhao Jiayi , Yang Anli , Li Xiangxin
Published: September 2024

Supplementary Figure S2, referred to Figure 2
Data from Clinically Relevant Humanized Mouse Models of Metastatic Prostate Cancer Facilitate Therapeutic Evaluation
Authors: Kostlan Raymond J. , Phoenix John T. , Budreika Audris , Ferrari Marina G. , Khurana Neetika , Choi Jae E. , Juckette Kristin , Mahapatra Somnath , McCollum Brooke L. , Moskal Russell , Mannan Rahul , Qiao Yuanyuan , Vander Griend Donald J. , Chinnaiyan Arul M. , Kregel Steven
Published: September 2024

Abstract
There is tremendous need for improved prostate cancer models. Anatomically and developmentally, the mouse prostate differs from the human prostate and does not form tumors spontaneously. Genetically engineered mouse models lack the heterogeneity of human cancer and rarely establish metastatic growth. Human xenografts are an alternative but must rely on an immunocompromised host. Therefore, we generated prostate cancer murine xenograft models with an intact human immune system (huNOG and huNOG-EXL mice) to test whether humanizing tumor-immune interactions would improve modeling of metastatic prostate cancer and the impact of androgen receptor-targeted and immunotherapies. These mice maintain multiple human immune cell lineages, including functional human T-cells and myeloid cells.

Implications: To the best of our knowledge, results illustrate the first model of human prostate cancer that has an intact human immune system, metastasizes to clinically relevant locations, responds appropriately to standard-of-care hormonal therapies, and can model both an immunosuppressive and checkpoint-inhibition responsive immune microenvironment.
Supplementary Table S4 from Effect of Clonal Hematopoiesis Mutations and Canakinumab Treatment on Incidence of Solid Tumors in the CANTOS Randomized Clinical Trial
Authors: Woo Janghee , Zhai Tingting , Yang Fang , Xu Huilei , Healey Margaret L. , Yates Denise P. , Beste Michael T. , Steensma David P.
Published: September 2024

Supplementary Table S4 shows the baseline characteristics between all CANTOS patients and the genomic subgroup patients.
Supplemental Material from Diet Modulates the Gut Microbiome, Metabolism, and Mammary Gland Inflammation to Influence Breast Cancer Risk
Authors: Arnone Alana A. , Wilson Adam S. , Soto-Pantoja David R. , Cook Katherine L.
Published: September 2024

Supplemental Material: Effect of diet on mammary gland and tumor metabolism. Heat map of untargeted metabolomic results from mammary glands and mammary tumors from mice fed a control, HS, lard, CO, lard + flaxseed oil, or lard + safflower oil diet
Supplementary Figure S1 from CHD2 Regulates Neuron–Glioma Interactions in Pediatric Glioma
Authors: Zhang Xu , Duan Shoufu , Apostolou Panagiota E. , Wu Xiaoping , Watanabe Jun , Gallitto Matthew , Barron Tara , Taylor Kathryn R. , Woo Pamelyn J. , Hua Xu , Zhou Hui , Wei Hong-Jian , McQuillan Nicholas , Kang Kyung-Don , Friedman Gregory K. , Canoll Peter D. , Chang Kenneth , Wu Cheng-Chia , Hashizume Rintaro , Vakoc Christopher R. , Monje Michelle , McKhann Guy M. , Gogos Joseph A. , Zhang Zhiguo
Published: September 2024

Validation of hits from CRISPR/Cas9 screens.
Table S1 from MYC Induces Oncogenic Stress through RNA Decay and Ribonucleotide Catabolism in Breast Cancer
Authors: Meena Jitendra K. , Wang Jarey H. , Neill Nicholas J. , Keough Dianne , Putluri Nagireddy , Katsonis Panagiotis , Koire Amanda M. , Lee Hyemin , Bowling Elizabeth A. , Tyagi Siddhartha , Orellana Mayra , Dominguez-Vidaña Rocio , Li Heyuan , Eagle Kenneth , Danan Charles , Chung Hsiang-Ching , Yang Andrew D. , Wu William , Kurley Sarah J. , Ho Brian M. , Zoeller Joseph R. , Olson Calla M. , Meerbrey Kristen L. , Lichtarge Olivier , Sreekumar Arun , Dacso Clifford C. , Guddat Luke W. , Rejman Dominik , Hocková Dana , Janeba Zlatko , Simon Lukas M. , Lin Charles Y. , Pillon Monica C. , Westbrook Thomas F.
Published: September 2024

Table S1 is the list of candidate facilitator genes of MYC-induced cell death. Table lists the candidate facilitators of MYC-induced cell death discovered through the MYC-specific loss of function genetic screen.
Figure S5 from MYC Induces Oncogenic Stress through RNA Decay and Ribonucleotide Catabolism in Breast Cancer
Authors: Meena Jitendra K. , Wang Jarey H. , Neill Nicholas J. , Keough Dianne , Putluri Nagireddy , Katsonis Panagiotis , Koire Amanda M. , Lee Hyemin , Bowling Elizabeth A. , Tyagi Siddhartha , Orellana Mayra , Dominguez-Vidaña Rocio , Li Heyuan , Eagle Kenneth , Danan Charles , Chung Hsiang-Ching , Yang Andrew D. , Wu William , Kurley Sarah J. , Ho Brian M. , Zoeller Joseph R. , Olson Calla M. , Meerbrey Kristen L. , Lichtarge Olivier , Sreekumar Arun , Dacso Clifford C. , Guddat Luke W. , Rejman Dominik , Hocková Dana , Janeba Zlatko , Simon Lukas M. , Lin Charles Y. , Pillon Monica C. , Westbrook Thomas F.
Published: September 2024

Figure S5 shows expression of MCL1 upon DIS3L knockdown, effect of XDH inhibition on MYC-induced cell death, effect of xanthosine on TNBC apoptosis, ROS and MYC-induced cell death, MYC-induced cell death upon HPRT1 knockdown, and expression of HPRT1 upon knockdown, and effect of DIS3L knockdown on TNBC xenografts.
Supplemental Table S5 from D3S-001, a KRAS G12C Inhibitor with Rapid Target Engagement Kinetics, Overcomes Nucleotide Cycling, and Demonstrates Robust Preclinical and Clinical Activities
Authors: Zhang Jing , Lim Sun Min , Yu Mi Ra , Chen Cheng , Wang Jia , Wang Wenqian , Rui Haopeng , Lu Jingtao , Lu Shun , Mok Tony , Chen Zhi Jian , Cho Byoung Chul
Published: September 2024

Supplemental Table S5 summarizing tumor growth inhibition analysis of the AMG510-R-xMIA PaCa-2 (clone 2) xenograft model
Supplemental Figure S9 from D3S-001, a KRAS G12C Inhibitor with Rapid Target Engagement Kinetics, Overcomes Nucleotide Cycling, and Demonstrates Robust Preclinical and Clinical Activities
Authors: Zhang Jing , Lim Sun Min , Yu Mi Ra , Chen Cheng , Wang Jia , Wang Wenqian , Rui Haopeng , Lu Jingtao , Lu Shun , Mok Tony , Chen Zhi Jian , Cho Byoung Chul
Published: September 2024

Supplemental Figure S9 shows the in vitro anti-tumor effect and tolerability of D3S-001 as monotherapy or in combination with D3S-002 on sotorasib-resistant models.
Supplemental Figure S8 from D3S-001, a KRAS G12C Inhibitor with Rapid Target Engagement Kinetics, Overcomes Nucleotide Cycling, and Demonstrates Robust Preclinical and Clinical Activities
Authors: Zhang Jing , Lim Sun Min , Yu Mi Ra , Chen Cheng , Wang Jia , Wang Wenqian , Rui Haopeng , Lu Jingtao , Lu Shun , Mok Tony , Chen Zhi Jian , Cho Byoung Chul
Published: September 2024

Supplemental Figure S8 shows brain penetration profile of adagrasib in beagle dogs and SD rats
Figure S5 from A Next-Generation BRAF Inhibitor Overcomes Resistance to BRAF Inhibition in Patients with BRAF-Mutant Cancers Using Pharmacokinetics-Informed Dose Escalation
Authors: Yaeger Rona , McKean Meredith A. , Haq Rizwan , Beck J. Thaddeus , Taylor Matthew H. , Cohen Jonathan E. , Bowles Daniel W. , Gadgeel Shirish M. , Mihalcioiu Catalin , Papadopoulos Kyriakos P. , Diamond Eli L. , Sturtz Keren B. , Feng Gang , Drescher Stefanie K. , Reddy Micaela B. , Sengupta Bhaswati , Maity Arnab K. , Brown Suzy A. , Singh Anurag , Brown Eric N. , Baer Brian R. , Wong Jim , Mou Tung-Chung , Wu Wen-I , Kahn Dean R. , Gadal Sunyana , Rosen Neal , Gaudino John J. , Lee Patrice A. , Hartley Dylan P. , Rothenberg S. Michael
Published: September 2024

Figure S5. Efficacy for BRAF non-V600/Class II and Class III-mutant cancer patients.
Figure S4 from A Next-Generation BRAF Inhibitor Overcomes Resistance to BRAF Inhibition in Patients with BRAF-Mutant Cancers Using Pharmacokinetics-Informed Dose Escalation
Authors: Yaeger Rona , McKean Meredith A. , Haq Rizwan , Beck J. Thaddeus , Taylor Matthew H. , Cohen Jonathan E. , Bowles Daniel W. , Gadgeel Shirish M. , Mihalcioiu Catalin , Papadopoulos Kyriakos P. , Diamond Eli L. , Sturtz Keren B. , Feng Gang , Drescher Stefanie K. , Reddy Micaela B. , Sengupta Bhaswati , Maity Arnab K. , Brown Suzy A. , Singh Anurag , Brown Eric N. , Baer Brian R. , Wong Jim , Mou Tung-Chung , Wu Wen-I , Kahn Dean R. , Gadal Sunyana , Rosen Neal , Gaudino John J. , Lee Patrice A. , Hartley Dylan P. , Rothenberg S. Michael
Published: September 2024

Figure S4. Patient PK profiles for PF-07799933.
Figure S3 from A Next-Generation BRAF Inhibitor Overcomes Resistance to BRAF Inhibition in Patients with BRAF-Mutant Cancers Using Pharmacokinetics-Informed Dose Escalation
Authors: Yaeger Rona , McKean Meredith A. , Haq Rizwan , Beck J. Thaddeus , Taylor Matthew H. , Cohen Jonathan E. , Bowles Daniel W. , Gadgeel Shirish M. , Mihalcioiu Catalin , Papadopoulos Kyriakos P. , Diamond Eli L. , Sturtz Keren B. , Feng Gang , Drescher Stefanie K. , Reddy Micaela B. , Sengupta Bhaswati , Maity Arnab K. , Brown Suzy A. , Singh Anurag , Brown Eric N. , Baer Brian R. , Wong Jim , Mou Tung-Chung , Wu Wen-I , Kahn Dean R. , Gadal Sunyana , Rosen Neal , Gaudino John J. , Lee Patrice A. , Hartley Dylan P. , Rothenberg S. Michael
Published: September 2024

Figure S3. Mouse plasma PK profiles for exarafenib and plixorafenib.
Supplementary Figure S9 from Molecular Determinants of Sensitivity to Polatuzumab Vedotin in Diffuse Large B-Cell Lymphoma
Authors: Corcoran Sean R. , Phelan James D. , Choi Jaewoo , Shevchenko Galina , Fenner Rachel E. , Yu Xin , Scheich Sebastian , Hsiao Tony , Morris Vivian M. , Papachristou Evangelia K. , Kishore Kamal , D’Santos Clive S. , Ji Yanlong , Pittaluga Stefania , Wright George W. , Urlaub Henning , Pan Kuan-Ting , Oellerich Thomas , Muppidi Jagan , Hodson Daniel J. , Staudt Louis M.
Published: September 2024

Mutation of CD79A and CD79B glycosylated residues does not alter sensitivity to MMAE
Supplementary Figure S8 from Molecular Determinants of Sensitivity to Polatuzumab Vedotin in Diffuse Large B-Cell Lymphoma
Authors: Corcoran Sean R. , Phelan James D. , Choi Jaewoo , Shevchenko Galina , Fenner Rachel E. , Yu Xin , Scheich Sebastian , Hsiao Tony , Morris Vivian M. , Papachristou Evangelia K. , Kishore Kamal , D’Santos Clive S. , Ji Yanlong , Pittaluga Stefania , Wright George W. , Urlaub Henning , Pan Kuan-Ting , Oellerich Thomas , Muppidi Jagan , Hodson Daniel J. , Staudt Louis M.
Published: September 2024

Knock-In mutations to specific N-linked glycosylation sites results in higher CD79B but not immunoglobulin MFI by flow cytometry
Supplementary Figure S10 from Molecular Determinants of Sensitivity to Polatuzumab Vedotin in Diffuse Large B-Cell Lymphoma
Authors: Corcoran Sean R. , Phelan James D. , Choi Jaewoo , Shevchenko Galina , Fenner Rachel E. , Yu Xin , Scheich Sebastian , Hsiao Tony , Morris Vivian M. , Papachristou Evangelia K. , Kishore Kamal , D’Santos Clive S. , Ji Yanlong , Pittaluga Stefania , Wright George W. , Urlaub Henning , Pan Kuan-Ting , Oellerich Thomas , Muppidi Jagan , Hodson Daniel J. , Staudt Louis M.
Published: September 2024

KLHL6 loss does not score as a negative regulator of surface CD79B or Pola-V sensitivity in CRISPR screens of ABC DLBCL cell lines and KLHL6 loss does not sensitize to MMAE
Supplementary Figure S7 from Efficacy of the Allosteric MEK Inhibitor Trametinib in Relapsed and Refractory Juvenile Myelomonocytic Leukemia: a Report from the Children’s Oncology Group
Authors: Stieglitz Elliot , Lee Alex G. , Angus Steven P. , Davis Christopher , Barkauskas Donald A. , Hall David , Kogan Scott C. , Meyer Julia , Rhodes Steven D. , Tasian Sarah K. , Xuei Xiaoling , Shannon Kevin , Loh Mignon L. , Fox Elizabeth , Weigel Brenda J.
Published: September 2024

SRC proto-oncogene, non-receptor tyrosine kinase expression in scRNAseq.
Supplementary Figure S4 from Efficacy of the Allosteric MEK Inhibitor Trametinib in Relapsed and Refractory Juvenile Myelomonocytic Leukemia: a Report from the Children’s Oncology Group
Authors: Stieglitz Elliot , Lee Alex G. , Angus Steven P. , Davis Christopher , Barkauskas Donald A. , Hall David , Kogan Scott C. , Meyer Julia , Rhodes Steven D. , Tasian Sarah K. , Xuei Xiaoling , Shannon Kevin , Loh Mignon L. , Fox Elizabeth , Weigel Brenda J.
Published: September 2024

Responders and non-responders have distinct patterns of kinase/transcript changes after exposure to trametinib.
Supplementary Figure S3 from Efficacy of the Allosteric MEK Inhibitor Trametinib in Relapsed and Refractory Juvenile Myelomonocytic Leukemia: a Report from the Children’s Oncology Group
Authors: Stieglitz Elliot , Lee Alex G. , Angus Steven P. , Davis Christopher , Barkauskas Donald A. , Hall David , Kogan Scott C. , Meyer Julia , Rhodes Steven D. , Tasian Sarah K. , Xuei Xiaoling , Shannon Kevin , Loh Mignon L. , Fox Elizabeth , Weigel Brenda J.
Published: September 2024

Downregulation of MAPK and inflammatory signaling after trametinib treatment.
Supplementary Figure S2 from Efficacy of the Allosteric MEK Inhibitor Trametinib in Relapsed and Refractory Juvenile Myelomonocytic Leukemia: a Report from the Children’s Oncology Group
Authors: Stieglitz Elliot , Lee Alex G. , Angus Steven P. , Davis Christopher , Barkauskas Donald A. , Hall David , Kogan Scott C. , Meyer Julia , Rhodes Steven D. , Tasian Sarah K. , Xuei Xiaoling , Shannon Kevin , Loh Mignon L. , Fox Elizabeth , Weigel Brenda J.
Published: September 2024

Kinome profiling.
Supplementary Table S8 from A Functional Survey of the Regulatory Landscape of Estrogen Receptor–Positive Breast Cancer Evolution
Authors: Barozzi Iros , Slaven Neil , Canale Eleonora , Lopes Rui , Amorim Monteiro Barbosa Inês , Bleu Melusine , Ivanoiu Diana , Pacini Claudia , Mensa’ Emanuela , Chambers Alfie , Bravaccini Sara , Ravaioli Sara , Győrffy Balázs , Dieci Maria Vittoria , Pruneri Giancarlo , Galli Giorgio Giacomo , Magnani Luca
Published: September 2024

Supplementary Table S8: Summary of SIDP results in T47D vs MCF7. S8.1-2: the tables follow the same structure of S8.1-2. S8.3: the table has the same structure of S8.3. S8.4: summary of the edgeR comparison between T47D and MCF7, for each medium (+E2 or -E2) and direction of the change (DF or IF). Results are presented similarly to tables S3.3. S8.5: total number of significant guides, regions with at least of significant guide, or regions with multiple guides, per medium (+E2 or -E2) and direction of the change (DF or IF).
Supplementary Table S7 from A Functional Survey of the Regulatory Landscape of Estrogen Receptor–Positive Breast Cancer Evolution
Authors: Barozzi Iros , Slaven Neil , Canale Eleonora , Lopes Rui , Amorim Monteiro Barbosa Inês , Bleu Melusine , Ivanoiu Diana , Pacini Claudia , Mensa’ Emanuela , Chambers Alfie , Bravaccini Sara , Ravaioli Sara , Győrffy Balázs , Dieci Maria Vittoria , Pruneri Giancarlo , Galli Giorgio Giacomo , Magnani Luca
Published: September 2024

Supplementary Table S7: SIDP results (MCF7 & LTED) summary. S7.1: regions showing at least one overlapping sgRNA scoring in at least one of the different conditions assayed. For each region (hg38 genomic coordinates), the table indicates whether this was selected as a gene promoter, putative enhancer, or putative insulator. It also shows the symbol of the nearest gene, and the distance to its TSS in bp (positive or negative values indicate the region is either downstream or upstream the TSS, respectively). For each condition (MCF7 +E2, MCF7 -E2 or LTED) and direction of the change (DF vs IF), the table indicates whether the region overlaps one or more (columns labeled “single”) vs two or more (columns labeled “multiple”) sgRNAs. S7.2: summary of the overlaps between either scoring sgRNAs (“guides”), regions showing at least one scoring sgRNA (“regions_single”), or regions showing two or more consistently scoring sgRNAs (“regions_multiple”) between pairs of conditions (as indicated by columns assay_1 and assay_2). The nature of the change (either DF or IF), along with the total number of overlapping sgRNAs or regions, and the corresponding fraction, are also indicated. S7.3: results of gene set enrichment analysis using the indicated gene sets and the set of genes close to the regions showing scoring sgRNAs, according to the indicated pattern (SIDP_set). Statistics of the hyper-geometric test are shown, along with the total number of the overlapping genes (count), the observed and expected overlaps, and the odds ratio. S7.4: total number of regions showing multiple, consistent, scoring sgRNAs, and relative split-up based on the distance (bp) to the nearest TSS (0-0.5 kbp, 0.5-2.5 kbp, 2.5-5 kbp, 5-10 kbp, over 10 kbp), per condition (MCF7 +E2, MCF7 -E2 or LTED) and direction of the change (DF vs IF).
Supplementary Table S4 from Identification of Clonal Hematopoiesis Driver Mutations through In Silico Saturation Mutagenesis
Authors: Demajo Santiago , Ramis-Zaldivar Joan E. , Muiños Ferran , Grau Miguel L. , Andrianova Maria , López-Bigas Núria , González-Pérez Abel
Published: September 2024

Artifactual SNVs in UKB
Supplementary Table S1 from Identification of Clonal Hematopoiesis Driver Mutations through In Silico Saturation Mutagenesis
Authors: Demajo Santiago , Ramis-Zaldivar Joan E. , Muiños Ferran , Grau Miguel L. , Andrianova Maria , López-Bigas Núria , González-Pérez Abel
Published: September 2024

Expert curated rules to define CH driver mutations
Supplementary Table S17 from A Functional Survey of the Regulatory Landscape of Estrogen Receptor–Positive Breast Cancer Evolution
Authors: Barozzi Iros , Slaven Neil , Canale Eleonora , Lopes Rui , Amorim Monteiro Barbosa Inês , Bleu Melusine , Ivanoiu Diana , Pacini Claudia , Mensa’ Emanuela , Chambers Alfie , Bravaccini Sara , Ravaioli Sara , Győrffy Balázs , Dieci Maria Vittoria , Pruneri Giancarlo , Galli Giorgio Giacomo , Magnani Luca
Published: September 2024

Supplementary Table S17: Downstream analyses considering only the SIDV inferred genetic alterations with predicted impact on function and stratifying them by cancer-cell fraction (CCF) increase and decrease in metastatic samples. S17.1: summary of the results of the statistical tests performed to identify differences in the predicted impact of mutations stratified by change in CCF in metastatic samples compared to matched primary. The fraction of variants predicted as pathogenic and either showing an increase or a decrease in CCF (+- 0.1) was compared to that of those showing no change. P-values for the indicated features are shown (Chi-squared test). S17.2: similarly, the distribution of the predicted molecular effects of variants in the three groups (increase, decrease or no change in CCF) were compared using the Kruskal-Wallis test. S17.3: like S13.3 but testing for the enrichment of mutations with both computationally predicted pathogenic effects and a certain CCF increase or decrease in metastatic samples, that also show a certain behavior in SIDP.
Supplementary Figure S8 from Identification of Clonal Hematopoiesis Driver Mutations through In Silico Saturation Mutagenesis
Authors: Demajo Santiago , Ramis-Zaldivar Joan E. , Muiños Ferran , Grau Miguel L. , Andrianova Maria , López-Bigas Núria , González-Pérez Abel
Published: September 2024

Blood somatic mutations across UKB donors
Supplementary Figure S6 from Identification of Clonal Hematopoiesis Driver Mutations through In Silico Saturation Mutagenesis
Authors: Demajo Santiago , Ramis-Zaldivar Joan E. , Muiños Ferran , Grau Miguel L. , Andrianova Maria , López-Bigas Núria , González-Pérez Abel
Published: September 2024

Comparison of boostDM-CH models to expert-curated rule sets
Supplementary Table S13 from A Functional Survey of the Regulatory Landscape of Estrogen Receptor–Positive Breast Cancer Evolution
Authors: Barozzi Iros , Slaven Neil , Canale Eleonora , Lopes Rui , Amorim Monteiro Barbosa Inês , Bleu Melusine , Ivanoiu Diana , Pacini Claudia , Mensa’ Emanuela , Chambers Alfie , Bravaccini Sara , Ravaioli Sara , Győrffy Balázs , Dieci Maria Vittoria , Pruneri Giancarlo , Galli Giorgio Giacomo , Magnani Luca
Published: September 2024

Supplementary Table S13: Computational predictions of the functional impact of the SNVs and short INDELs identified through SIDV. S13.1: for each variant, the type (SNV or INDEL_short) and its hg38 coordinates are listed, along with the symbol of the nearest gene, and the distance to its TSS in bp (positive or negative values indicate the region is either downstream or upstream the TSS, respectively). Reference and alternative alleles are also provided, along with whether the variant is computationally predicted to alter the molecular function of the genomic element bearing it (indicated as different “pathogenic” classes; column mutation_class) or not (“benign”). The table is then indicating, for each one of the models considered, whether the variant is predicted to significantly affect the indicated molecular function. S13.2: extract of S12.1, for three regions of interest.
Supplementary Table S11 from A Functional Survey of the Regulatory Landscape of Estrogen Receptor–Positive Breast Cancer Evolution
Authors: Barozzi Iros , Slaven Neil , Canale Eleonora , Lopes Rui , Amorim Monteiro Barbosa Inês , Bleu Melusine , Ivanoiu Diana , Pacini Claudia , Mensa’ Emanuela , Chambers Alfie , Bravaccini Sara , Ravaioli Sara , Győrffy Balázs , Dieci Maria Vittoria , Pruneri Giancarlo , Galli Giorgio Giacomo , Magnani Luca
Published: September 2024

Supplementary Table S11: De novo coding variants. The table lists all the variants (SNVs and short INDELs) identified in the profiled sub-cohort of 58 SIDV metastatic samples. Chromosome and position on the chromosome (hg38 coordinates) are indicated for each variant, along with the reference, detected alternative allele and its frequency, the gene symbol and the ensemble transcripts, the type of alteration and the codon change, and the identifier of the sample in which the variant was identified.
Supplementary Figure S21 from Identification of Clonal Hematopoiesis Driver Mutations through In Silico Saturation Mutagenesis
Authors: Demajo Santiago , Ramis-Zaldivar Joan E. , Muiños Ferran , Grau Miguel L. , Andrianova Maria , López-Bigas Núria , González-Pérez Abel
Published: September 2024

CH driver mutations in CHEK2 and MDM4
Supplementary Table S10 from A Functional Survey of the Regulatory Landscape of Estrogen Receptor–Positive Breast Cancer Evolution
Authors: Barozzi Iros , Slaven Neil , Canale Eleonora , Lopes Rui , Amorim Monteiro Barbosa Inês , Bleu Melusine , Ivanoiu Diana , Pacini Claudia , Mensa’ Emanuela , Chambers Alfie , Bravaccini Sara , Ravaioli Sara , Győrffy Balázs , Dieci Maria Vittoria , Pruneri Giancarlo , Galli Giorgio Giacomo , Magnani Luca
Published: September 2024

Supplementary Table S10: Metadata of the clinical cohort profiled by SIDV. S10.1: for each donor, from which genetic material from matched normal, primary, and metastatic samples were derived, the following information is provided: the identifier for the samples; the center where the samples were collected; the sequencing batch; the age of diagnosis; the clinical features of the primary tumors; the indication of the metastatic sites. Legend: ER = estrogen-receptor alpha; PR = progesterone receptor; pct = percentage; HR = hormone therapy. S10.2: for each triplet of matched normal, primary and metastasis derived material, and separately for each one of the 100 donors, sequencing statistics are provided. Sequencing depth, fraction of the reads mapping to oligo baits, mean coverage on baits and corresponding fold-enrichment, and on-target mean coverage, are shown. The percentages (pct) of targeted bases covered at least 10x, 30x, 50x or 100x are also indicates.
Supplementary Figure S19 from Identification of Clonal Hematopoiesis Driver Mutations through In Silico Saturation Mutagenesis
Authors: Demajo Santiago , Ramis-Zaldivar Joan E. , Muiños Ferran , Grau Miguel L. , Andrianova Maria , López-Bigas Núria , González-Pérez Abel
Published: September 2024

Newly identified CH driver mutations across UKB
Supplementary Figure S7 from A Functional Survey of the Regulatory Landscape of Estrogen Receptor–Positive Breast Cancer Evolution
Authors: Barozzi Iros , Slaven Neil , Canale Eleonora , Lopes Rui , Amorim Monteiro Barbosa Inês , Bleu Melusine , Ivanoiu Diana , Pacini Claudia , Mensa’ Emanuela , Chambers Alfie , Bravaccini Sara , Ravaioli Sara , Győrffy Balázs , Dieci Maria Vittoria , Pruneri Giancarlo , Galli Giorgio Giacomo , Magnani Luca
Published: September 2024

Supplementary Figure 7. SIDP identifies regulatory regions with context-dependent activity in MCF7 cells.
Supplementary Figure S17 from Identification of Clonal Hematopoiesis Driver Mutations through In Silico Saturation Mutagenesis
Authors: Demajo Santiago , Ramis-Zaldivar Joan E. , Muiños Ferran , Grau Miguel L. , Andrianova Maria , López-Bigas Núria , González-Pérez Abel
Published: September 2024

Comparison of boostDM-CH models and expert-curated rules in the identification of CH driver mutations in the UKB
Supplementary Figure S6 from A Functional Survey of the Regulatory Landscape of Estrogen Receptor–Positive Breast Cancer Evolution
Authors: Barozzi Iros , Slaven Neil , Canale Eleonora , Lopes Rui , Amorim Monteiro Barbosa Inês , Bleu Melusine , Ivanoiu Diana , Pacini Claudia , Mensa’ Emanuela , Chambers Alfie , Bravaccini Sara , Ravaioli Sara , Győrffy Balázs , Dieci Maria Vittoria , Pruneri Giancarlo , Galli Giorgio Giacomo , Magnani Luca
Published: September 2024

Supplementary Figure 6. SIDP results are consistent across ER+ BC cell lines.
Supplementary Figure S14 from Identification of Clonal Hematopoiesis Driver Mutations through In Silico Saturation Mutagenesis
Authors: Demajo Santiago , Ramis-Zaldivar Joan E. , Muiños Ferran , Grau Miguel L. , Andrianova Maria , López-Bigas Núria , González-Pérez Abel
Published: September 2024

Association of CH mutations with different cardiovascular events in UKB
Supplementary Figure S3 from A Functional Survey of the Regulatory Landscape of Estrogen Receptor–Positive Breast Cancer Evolution
Authors: Barozzi Iros , Slaven Neil , Canale Eleonora , Lopes Rui , Amorim Monteiro Barbosa Inês , Bleu Melusine , Ivanoiu Diana , Pacini Claudia , Mensa’ Emanuela , Chambers Alfie , Bravaccini Sara , Ravaioli Sara , Győrffy Balázs , Dieci Maria Vittoria , Pruneri Giancarlo , Galli Giorgio Giacomo , Magnani Luca
Published: September 2024

Supplementary Figure 3. Estrogen deprivation in MCF7 cells introduce stochastic selective pressure in long-term CRISPRi screens.
Supplementary Figure S19 from A Functional Survey of the Regulatory Landscape of Estrogen Receptor–Positive Breast Cancer Evolution
Authors: Barozzi Iros , Slaven Neil , Canale Eleonora , Lopes Rui , Amorim Monteiro Barbosa Inês , Bleu Melusine , Ivanoiu Diana , Pacini Claudia , Mensa’ Emanuela , Chambers Alfie , Bravaccini Sara , Ravaioli Sara , Győrffy Balázs , Dieci Maria Vittoria , Pruneri Giancarlo , Galli Giorgio Giacomo , Magnani Luca
Published: September 2024

Supplementary Figure 19. SIDV functional analyses.
Supplementary Figure S10 from Identification of Clonal Hematopoiesis Driver Mutations through In Silico Saturation Mutagenesis
Authors: Demajo Santiago , Ramis-Zaldivar Joan E. , Muiños Ferran , Grau Miguel L. , Andrianova Maria , López-Bigas Núria , González-Pérez Abel
Published: September 2024

UKB driver mutations that are not observed or not recurrent across cancer genomics cohorts, and mutations in donors with different ethnicity
Supplementary Figure S17 from A Functional Survey of the Regulatory Landscape of Estrogen Receptor–Positive Breast Cancer Evolution
Authors: Barozzi Iros , Slaven Neil , Canale Eleonora , Lopes Rui , Amorim Monteiro Barbosa Inês , Bleu Melusine , Ivanoiu Diana , Pacini Claudia , Mensa’ Emanuela , Chambers Alfie , Bravaccini Sara , Ravaioli Sara , Győrffy Balázs , Dieci Maria Vittoria , Pruneri Giancarlo , Galli Giorgio Giacomo , Magnani Luca
Published: September 2024

Supplementary Figure 17. Activation of TLR5 via paracrine signaling.
Supplementary Figure S14 from A Functional Survey of the Regulatory Landscape of Estrogen Receptor–Positive Breast Cancer Evolution
Authors: Barozzi Iros , Slaven Neil , Canale Eleonora , Lopes Rui , Amorim Monteiro Barbosa Inês , Bleu Melusine , Ivanoiu Diana , Pacini Claudia , Mensa’ Emanuela , Chambers Alfie , Bravaccini Sara , Ravaioli Sara , Győrffy Balázs , Dieci Maria Vittoria , Pruneri Giancarlo , Galli Giorgio Giacomo , Magnani Luca
Published: September 2024

Supplementary Figure 14. TLR5 expression in ER+ cells from normal and cancer samples.
Supplementary Table S4 from Poor Prognosis among Radiation-Associated Bladder Cancer Is Defined by Clinicogenomic Features
Authors: Wijetunga N. Ari , Gessner Kathryn H. , Kanchi Krishna , Moore Jay A. , Fleischmann Zoe , Jin Dexter X. , Frampton Garrett M. , Sturdivant Michael , Repka Michael , Sud Shivani , Corcoran David L. , Galsky Matthew D. , Milowsky Matthew I. , Wobker Sara E. , Kim William Y. , Rose Tracy L. , Damrauer Jeffrey S.
Published: September 2024

Supplementary Table S4
Supplementary Figure S6 from Poor Prognosis among Radiation-Associated Bladder Cancer Is Defined by Clinicogenomic Features
Authors: Wijetunga N. Ari , Gessner Kathryn H. , Kanchi Krishna , Moore Jay A. , Fleischmann Zoe , Jin Dexter X. , Frampton Garrett M. , Sturdivant Michael , Repka Michael , Sud Shivani , Corcoran David L. , Galsky Matthew D. , Milowsky Matthew I. , Wobker Sara E. , Kim William Y. , Rose Tracy L. , Damrauer Jeffrey S.
Published: September 2024

Supplementary Figure S6
Supplementary Figure S2 from Poor Prognosis among Radiation-Associated Bladder Cancer Is Defined by Clinicogenomic Features
Authors: Wijetunga N. Ari , Gessner Kathryn H. , Kanchi Krishna , Moore Jay A. , Fleischmann Zoe , Jin Dexter X. , Frampton Garrett M. , Sturdivant Michael , Repka Michael , Sud Shivani , Corcoran David L. , Galsky Matthew D. , Milowsky Matthew I. , Wobker Sara E. , Kim William Y. , Rose Tracy L. , Damrauer Jeffrey S.
Published: September 2024

Supplementary Figure S2
Supplementary Figure S1 from Poor Prognosis among Radiation-Associated Bladder Cancer Is Defined by Clinicogenomic Features
Authors: Wijetunga N. Ari , Gessner Kathryn H. , Kanchi Krishna , Moore Jay A. , Fleischmann Zoe , Jin Dexter X. , Frampton Garrett M. , Sturdivant Michael , Repka Michael , Sud Shivani , Corcoran David L. , Galsky Matthew D. , Milowsky Matthew I. , Wobker Sara E. , Kim William Y. , Rose Tracy L. , Damrauer Jeffrey S.
Published: September 2024

Supplementary Figure S1
Figure 3 from Poor Prognosis among Radiation-Associated Bladder Cancer Is Defined by Clinicogenomic Features
Authors: Wijetunga N. Ari , Gessner Kathryn H. , Kanchi Krishna , Moore Jay A. , Fleischmann Zoe , Jin Dexter X. , Frampton Garrett M. , Sturdivant Michael , Repka Michael , Sud Shivani , Corcoran David L. , Galsky Matthew D. , Milowsky Matthew I. , Wobker Sara E. , Kim William Y. , Rose Tracy L. , Damrauer Jeffrey S.
Published: September 2024

Identification of de novo mutational signatures. A, Heatmap of the cosine similarity between the de novo mutational signatures and known Catalogue of Somatic Mutations in Cancer SBS profiles. Boxplots of the signature contribution to the overall SNVs for each sample grouped by (B) signature and latency or (C) smoking status and signature for CTRL and (D) RT tumors. Pairwise comparisons between CTRL (gold), RT–short latency (dark blue), and RT–long latency (light blue) tumors were made using the Wilcoxon rank-sum test, with P values listed above their corresponding comparison. Boxplots are represented by the IQR and midline at the median. Error bars equal the Q1/Q3 ± 1.5 × IQR. E, Samples were grouped by the mutational signature with the greatest signature contribution. KM curves were generated based on this max signature assignment for OS for RT patients. Dashed lines indicate median survival. G, Forest plot visualizing a multivariate Cox proportional model for OS incorporating the max signature group, latency, and smoking status. WT, wild type.
Supplement Figure 2 from Anti-HDGF Antibody Targets EGFR Tyrosine Kinase Inhibitor–Tolerant Cells in NSCLC Patient-Derived Xenografts
Authors: Zhou Cindy Q. , Li Ariel , Ri Kaoru , Sultan Ahmed S. , Ren Hening
Published: September 2024

Supplement Figure 2 shows the Effect of anti-HDGF antibody H3 on treatment naive tumor.
Supplementary Data from The Tumor Microbiome Reacts to Hypoxia and Can Influence Response to Radiation Treatment in Colorectal Cancer
Authors: Benej Martin , Hoyd Rebecca , Kreamer McKenzie , Wheeler Caroline E. , Grencewicz Dennis J. , Choueiry Fouad , Chan Carlos H.F. , Zakharia Yousef , Ma Qin , Dodd Rebecca D. , Ulrich Cornelia M. , Hardikar Sheetal , Churchman Michelle L. , Tarhini Ahmad A. , Robinson Lary A. , Singer Eric A. , Ikeguchi Alexandra P. , McCarter Martin D. , Tinoco Gabriel , Husain Marium , Jin Ning , Tan Aik C. , Osman Afaf E.G. , Eljilany Islam , Riedlinger Gregory , Schneider Bryan P. , Benejova Katarina , Kery Martin , Papandreou Ioanna , Zhu Jiangjiang , Denko Nicholas , Spakowicz Daniel
Published: September 2024

Differences in the immune cell populations, estimated by RNAseq, within high and low hypoxia mouse tumors, separated by mouse strain.
Supplementary Data from The Tumor Microbiome Reacts to Hypoxia and Can Influence Response to Radiation Treatment in Colorectal Cancer
Authors: Benej Martin , Hoyd Rebecca , Kreamer McKenzie , Wheeler Caroline E. , Grencewicz Dennis J. , Choueiry Fouad , Chan Carlos H.F. , Zakharia Yousef , Ma Qin , Dodd Rebecca D. , Ulrich Cornelia M. , Hardikar Sheetal , Churchman Michelle L. , Tarhini Ahmad A. , Robinson Lary A. , Singer Eric A. , Ikeguchi Alexandra P. , McCarter Martin D. , Tinoco Gabriel , Husain Marium , Jin Ning , Tan Aik C. , Osman Afaf E.G. , Eljilany Islam , Riedlinger Gregory , Schneider Bryan P. , Benejova Katarina , Kery Martin , Papandreou Ioanna , Zhu Jiangjiang , Denko Nicholas , Spakowicz Daniel
Published: September 2024

Selected log2 fold change results for microbes found to be significantly enriched in hypoxic tumors in both mice and human subjects.
Supplemental Figure S3 from The Tumor Microbiome Reacts to Hypoxia and Can Influence Response to Radiation Treatment in Colorectal Cancer
Authors: Benej Martin , Hoyd Rebecca , Kreamer McKenzie , Wheeler Caroline E. , Grencewicz Dennis J. , Choueiry Fouad , Chan Carlos H.F. , Zakharia Yousef , Ma Qin , Dodd Rebecca D. , Ulrich Cornelia M. , Hardikar Sheetal , Churchman Michelle L. , Tarhini Ahmad A. , Robinson Lary A. , Singer Eric A. , Ikeguchi Alexandra P. , McCarter Martin D. , Tinoco Gabriel , Husain Marium , Jin Ning , Tan Aik C. , Osman Afaf E.G. , Eljilany Islam , Riedlinger Gregory , Schneider Bryan P. , Benejova Katarina , Kery Martin , Papandreou Ioanna , Zhu Jiangjiang , Denko Nicholas , Spakowicz Daniel
Published: September 2024

Boxplot comparing Fusobacterium counts in low and high hypoxia 16s samples.
Supplemental Figure S1 from The Tumor Microbiome Reacts to Hypoxia and Can Influence Response to Radiation Treatment in Colorectal Cancer
Authors: Benej Martin , Hoyd Rebecca , Kreamer McKenzie , Wheeler Caroline E. , Grencewicz Dennis J. , Choueiry Fouad , Chan Carlos H.F. , Zakharia Yousef , Ma Qin , Dodd Rebecca D. , Ulrich Cornelia M. , Hardikar Sheetal , Churchman Michelle L. , Tarhini Ahmad A. , Robinson Lary A. , Singer Eric A. , Ikeguchi Alexandra P. , McCarter Martin D. , Tinoco Gabriel , Husain Marium , Jin Ning , Tan Aik C. , Osman Afaf E.G. , Eljilany Islam , Riedlinger Gregory , Schneider Bryan P. , Benejova Katarina , Kery Martin , Papandreou Ioanna , Zhu Jiangjiang , Denko Nicholas , Spakowicz Daniel
Published: September 2024

Hypoxia scores by stage (A) or sex (B) for the ORIEN radiation-treated cohort.
Data from Poor Prognosis among Radiation-Associated Bladder Cancer Is Defined by Clinicogenomic Features
Authors: Wijetunga N. Ari , Gessner Kathryn H. , Kanchi Krishna , Moore Jay A. , Fleischmann Zoe , Jin Dexter X. , Frampton Garrett M. , Sturdivant Michael , Repka Michael , Sud Shivani , Corcoran David L. , Galsky Matthew D. , Milowsky Matthew I. , Wobker Sara E. , Kim William Y. , Rose Tracy L. , Damrauer Jeffrey S.
Published: September 2024

Abstract
Radiotherapy (RT) for prostate cancer has been associated with an increased risk for the development of bladder cancer. We aimed to integrate clinical and genomic data to better understand the development of RT-associated bladder cancer. A retrospective analysis was performed to identify control patients (CTRL; n = 41) and patients with RT-associated bladder cancer (n = 41). RT- and CTRL-specific features were then identified through integration and analysis of the genomic sequencing data and clinical variables. RT-associated bladder tumors were significantly enriched for alterations in KDM6A and ATM, whereas CTRL tumors were enriched for CDKN2A mutation. Globally, there were an increased number of variants within RT tumors, albeit at a lower variant allele frequency. Mutational signature analysis revealed three predominate motif patterns, with similarity to SBS2/13 (APOBEC3A), SBS5 (ERCC2/smoking), and SBS6/15 (MMR). Poor prognostic factors in the RT cohort include a short tumor latency, smoking status, the presence of the smoking and X-ray therapy mutational signatures, and CDKN2A copy number loss. Based on the clinical and genomic findings, we suggest at least two potential pathways leading to RT-associated bladder cancer: The first occurs in the setting of field cancerization related to smoking or preexisting genetic alterations and leads to the development of more aggressive bladder tumors, and the second involves RT initiating the oncogenic process in otherwise healthy urothelium, leading to a longer latency and less aggressive disease.
Significance:
Clinicogenomic analysis of radiation-associated bladder cancer uncovered mutational signatures that, in addition to a short tumor latency, smoking, and CDKN2A loss, are associated with a poor outcome. These clinical and genomic features provide a potential method to identify patients with prostate cancer who are at an increased risk for the development of aggressive bladder cancer following prostate RT.
Renal Immune-Related Adverse Event Difficult to Diagnose during Nivolumab Treatment for Hypopharyngeal Carcinoma: Case Report
Authors: Maezumi Sorane , Okada Takuro , Kishida Takuma , Ogawa Yasuo , Tsukahara Kiyoaki
Published: September 2024

Introduction: Immune-related adverse events (irAEs) from nivolumab can affect any organ, but renal impairment is less common than effects on other organs. We encountered a case in which a renal irAE was difficult to diagnose due to mild renal dysfunction. Case Presentation: We report the case of a 65-year-old man with hypopharyngeal carcinoma treated with radiotherapy and cisplatin. Histopathological examination after reconstructive surgery showed extranodal invasion. Two months after completing treatment, computed tomography showed multiple lung metastases. We determined that the tumors were platinum-resistant and initiated treatment with nivolumab. Pyuria, worsening renal function, and elevation of C-reactive protein (CRP) to 16 mg/dL were observed 203 days after the first dose and nivolumab was discontinued. We considered the possibility of renal irAE but did not perform renal biopsy because creatinine was not highly elevated. We administered antibiotics for urinary tract infection, but CRP rose to 20 mg/dL and his general condition gradually worsened. Arthralgia in both knees and elbows appeared around the same time and gallium scintigraphy showed polyarticular accumulations. After diagnosing irAE arthritis, 20 mg of prednisolone was administered. Arthralgia and inflammatory responses improved, along with urinary findings and tubular markers. Retrospectively, pyuria, mild renal dysfunction, and elevated CRP were considered to reflect renal irAE. Conclusion: In some cases of mild renal dysfunction, as in the present case, biopsy may not be performed and the diagnosis may be missed. Renal irAEs should be kept in mind when abnormal urinalysis results and renal dysfunction are observed.
Video Assessment to Detect Amyotrophic Lateral Sclerosis
Authors: Oliveira Guilherme Camargo , Ngo Quoc Cuong , Passos Leandro Aparecido , Oliveira Leonardo Silva , Stylianou Stella , Papa João Paulo , Kumar Dinesh
Published: September 2024

Introduction: Weakened facial movements are early-stage symptoms of amyotrophic lateral sclerosis (ALS). ALS is generally detected based on changes in facial expressions, but large differences between individuals can lead to subjectivity in the diagnosis. We have proposed a computerized analysis of facial expression videos to detect ALS. Methods: This study investigated the action units obtained from facial expression videos to differentiate between ALS patients and healthy individuals, identifying the specific action units and facial expressions that give the best results. We utilized the Toronto NeuroFace Dataset, which includes nine facial expression tasks for healthy individuals and ALS patients. Results: The best classification accuracy was 0.91 obtained for the pretending to smile with tight lips expression. Conclusion: This pilot study shows the potential of using computerized facial expression analysis based on action units to identify facial weakness symptoms in ALS.
Endoluminal Vacuum Therapy for the Management of Boerhaave Syndrome: A Case Series
Authors: Soussi Daniella , Alharahsheh Batool Helmi Ahmad , Boshier Piers Robert , Hoare Jonathan , Direkze Natalie , Thomas Robert , Peters Christopher John , Stevens Sophie
Published: September 2024

Introduction: Boerhaave syndrome is a rare condition associated with high morbidity and mortality. Prompt intervention greatly improves outcomes, with surgery traditionally being the mainstay of management. Recent advances in therapeutic endoscopy have led to increasing interest in endoluminal vacuum therapy (EVT), a minimally invasive technique, allowing wound debridement and drainage, encouraging granulation tissue formation. EVT has been associated with positive clinical outcomes, including lower mortality rates compared to surgery and stenting for the management of anastomotic leaks, and to a lesser extent, oesophageal perforations. EVT has been adopted into practice across Europe; however, only few cases have been reported from the UK. Case Presentations: We report three cases of Boerhaave syndrome, successfully managed with EVT, using the Eso-SPONGE ® (B.Braun Medical Ltd, Sheffield, UK). EVT involves the placement of a polyurethane sponge into the wound cavity. The cavity is initially assessed, then an overtube is introduced through which the sponge is inserted, and then the overtube is removed. Sponge position is confirmed and adjusted if necessary. The sponge is connected via a trans-nasal drain to continuous negative pressure suction and is changed every 3–5 days. Having been deemed surgically unfit, all 3 patients were referred for EVT. All patients made excellent recovery and were discharged home. Conclusion: EVT is an effective management strategy for surgically unfit Boerhaave syndrome patients. Eso-SPONGE use aided drainage of the septic focus and closure of the defect, leading to complete recovery. Our findings support the existing evidence that EVT is a promising solution for Boerhaave syndrome.
Pulmonary Arterial Hypertension as an Unusual Presentation of Angioimmunoblastic T-Cell Lymphoma: A Case Report
Authors: Jung Jiyoon
Published: September 2024

Introduction: Angioimmunoblastic T-cell lymphoma (AITL) is a rare form of non-Hodgkin lymphoma with diverse clinical presentations. This report describes a unique case of AITL presenting with pulmonary arterial hypertension (PAH), a rarely associated complication. Case Presentation: An 84-year-old male with a history of gastric cancer presented with dyspnea. Initial investigations revealed lymphadenopathy, pleural effusion, and severe PAH. Diagnostic workup, including histopathological and immunohistochemical analysis of an excisional lymph node biopsy and advanced imaging techniques, confirmed the diagnosis of AITL. The patient was treated with a mini-CHOP chemotherapy regimen, leading to significant improvement in PAH and other symptoms, and achieving complete remission as confirmed by positron emission tomography-computed tomography scans. Conclusion: This case highlights the diagnostic challenge posed by atypical manifestations of AITL, such as PAH. The effective response to chemotherapy in this patient emphasizes the potential for conventional treatment regimens in managing rare presentations of AITL. This report contributes to the limited literature on AITL with PAH and underscores the importance of considering AITL in differential diagnoses for patients presenting with PAH.