bluuebunny/crossref_metadata_2025 huggingface dataset:
Exonic Deletions and Deep Intronic Variants of the SLC26A4 Gene Contribute to the Genetic Diagnosis of Unsolved Patients With Enlarged Vestibular Aqueduct
Authors: Tian Yongan , Liu Mengli , Lu Yu , Zhao Xiaoyan , Yan Zhiqiang , Sun Yi , Ma Jingyuan , Tang Wenxue , Wang Haili , Xu Hongen
Published: October 2024

Enlarged vestibular aqueduct (EVA) is a frequently occurring inner ear malformation that associates with sensorineural hearing loss (SNHL), with SLC26A4 being the responsible gene. Based on multiplex PCR enrichment and sequencing of the exonic and flanking regions of the SLC26A4 gene, we developed a panel specifically for EVA and found that up to 95% of EVA patients in our Chinese cohorts carried biallelic SLC26A4 pathogenic variants (M2). In this study, we tried to investigate the genetic etiology of 13 previously undiagnosed EVA patients with monoallelic (M1) or none (M0) SLC26A4 variant using a stepwise approach, including copy number variation (CNV) analysis of multiplex PCR enrichment and next‐generation sequencing data, single‐molecule real‐time (SMRT) sequencing of the whole SLC26A4 gene, whole exome sequencing (WES), and whole genome sequencing (WGS). CNV analysis revealed deletions in Exons 1–3, Exons 5–6, and Exons 9–10 of the SLC26A4 gene in seven patients, and SMRT sequencing identified the same heterozygous deep intronic variant (NM_000441.2:c.304+941C>T) in two patients, resulting in a final diagnosis in 9/13 patients. Notably, the variants of Exons 9–10 deletion and c.304+941C>T have not been reported previously. We further showed that the variant c.304+941C>T led to the exonization of partial AluSz6 element (126 bp) where the variant is located through sequencing of the mRNA extracted from the blood of a heterozygous variant carrier. In conclusion, our stepwise approach improved the diagnosis rate of EVA, expanded the mutational spectrum of the SLC26A4 gene, and highlighted the contribution of exonic deletions and deep intronic variants to EVA.
The Impact of Standard Cross‐Linking on the Corneal Optical Density–Age Relationship in Keratoconus After Mechanical Stripping of the Epithelium
Authors: Bohac Maja , Gilevska Fanka , Biscevic Alma , Gabric Ivan , Gabric Kresimir , Patel Sudi
Published: October 2024

Background: To determine if cross‐linking (CXL) treatment modifies any pre‐existing association between corneal optical density (COD) and age in keratoconus free of corneal scarring.

Methods: COD was monitored in two groups (i) before and after standard CXL treatment for keratoconus (de‐epithelization with a crescent blade, n = 69 eyes) and (ii) age/gender‐matched cases without any signs of keratoconus (n = 24 eyes). Seven different markers of COD were quantified using a 0–100 grey scale, supplied with Pentacam™ software.

Results: Mean age (±sd, range) in Group I (19 females and 50 males) was 24.2 years (±7.2, 11–44) and in Group II (9 females and 15 males), it was 24.7 years (±7.6, 17–45). COD over the apex and along the depth of the cornea (y, arbitrary scale units) was associated with age (x, in years) in Group I at preop (y = 0.08x + 13.12, rs = 0.350 and p = 0.003), at 12 months postop (y = 0.08x + 15.15, rs = 0.295 and p = 0.014) and in Group II, at the start (y = 0.16x + 11.28, rs = 0.474 and p = 0.019) and 12 months later (y = 0.24x + 8.63, rs = 0.600 and p = 0.002). The change in COD following CXL was significantly associated with the preop value.

Conclusion: CXL initially breaks down the pre‐existing relationship between COD and age. This is re‐established by 12 months postop. The CXL induced change in COD depends on the preop value but not on the patient’s age.
PI3K Mutation Profiles on Exons 9 (E545K and E542K) and 20 (H1047R) in Mexican Patients With HER‐2 Overexpressed Breast Cancer and Its Relevance on Clinical–Pathological and Survival Biological Effects
Authors: Nieto-Coronel T. , Alette Ortega-Gómez , Yacab R. , Fernández-Figueroa E. A. , Lopez-Camarillo C. , Marchat L. , Astudillo-de la Vega H. , Ruiz-Garcia E.
Published: October 2024

Background: Trastuzumab resistance is associated with overexpressing the human epidermal growth factor receptor 2 (HER‐2), which results from the altered phosphoinositide 3‐kinase (PI3K) pathway in breast cancer patients.

Objective: We quantified the frequency of PI3K enzyme single and double‐point mutations in Mexican patients with HER‐2 overexpressing breast cancer and its association with clinical‐pathological variables.

Methods: We embedded HER‐2 breast samples in paraffin from 60 patients, extracted their DNA, and evaluated PI3K mutations in 49 HER‐2‐positive breast tumors. We focused on mutations for one exon 20 (H1047R) and two exon 9 PI3K (E545K, E542K) hotspots and characterized them as single and double‐point mutations. The mean patient follow‐up was 86 months.

Results: Of 49 patients who tested positive for HER‐2 breast cancer, 14.28% showed mutations in PI3K, 71.42% single‐point, and 28.56% double‐point mutations. We found single‐point mutations in H1047R (42.85%) and E545K (28.57%). Only two patients exhibited double‐point mutations: one in E542K/E545K and another in H1047R/E545K (14.28% each). Although we observed lower survival in patients with mutations in PI3K, we did not find a significant association between these factors (p = 0.191). However, single and double‐point mutations in PI3K were significantly associated with the clinical stages of diagnosis and tumor size (p = 0.027 and p = 0.04, respectively).

Conclusion: Single and double‐point mutations in PI3K are related to tumor size and advanced clinical–pathological traits in Mexican patients with HER‐2 overexpression, and future molecular studies are necessary to understand these findings.
The Association Between Anti‐Neoplastic Effects of Curcumin and Urogenital Cancers: A Systematic Review
Authors: Mazaheri-Tehrani Sadegh , Rouzbahani Shiva , Heidari-Beni Motahar
Published: October 2024

Background: Curcumin is a polyphenol compound with anticancer effects. We aimed to review the anti‐neoplastic effects of curcumin on urogenital cancers, by regulating different microRNA expressions.

Methods: A systematic search was conducted in Medline (PubMed), Embase, Scopus, and Web of Science up to the end of August 2024. All English, in vitro, and observational studies that evaluated the effect of curcumin on preventing or treating urogenital cancers through its impact on microRNA expression were included. In vivo or silico studies were excluded.

Result: A total of 2549 records were found. Finally, 25 studies were included. Twelve studies assessed the effect of curcumin on prostate cancer, six studies on ovarian cancer, three studies on cervical cancer, three studies on bladder cancer, and one study on renal cancer. MicroRNAs are small noncoding RNAs that regulate the post‐transcriptional pathways. They possess pivotal roles in different fundamental mechanisms in cells such as differentiation, migration, apoptosis, and proliferation. Curcumin exerts its anticancer effects on urogenital neoplasms by upregulating tumor suppressor microRNAs (miR‐143, miR‐145, miR‐Let‐7, miR‐101, miR‐3127, miR‐3178, miR‐1275, miR‐3198, miR‐1908, miR‐770, miR‐1247, miR‐411, miR‐34a, miR‐383, miR‐708, miR‐483, miR‐199a, miR‐335, miR‐503, miR‐10b, miR‐551a, miR‐9, miR‐203, miR‐7110, miR‐29b, and miR‐126) and downregulating oncogenic microRNAs (miR‐21, miR‐210, miR‐382, miR‐654, miR‐494, miR‐193b, miR‐671, miR‐222, miR‐23b, miR‐664, miR‐183, miR‐214, miR‐320a, miR‐23a, miR‐30a, miR‐320d, miR‐1285, miR‐32, miR‐181a, miR‐205, miR‐216a, miR‐1246, and miR‐106b).

Conclusion: Cell proliferation is inhibited, and cell apoptosis is induced by curcumin in different urogenital cancers through suppressing oncogenic microRNAs or provoking tumor suppressor microRNAs.
Supplementary Table S3 from Targeting the Sodium–Potassium Pump as a Therapeutic Strategy in Acute Myeloid Leukemia
Authors: Schneider Constanze , Spaink Hermes , Alexe Gabriela , Dharia Neekesh V. , Meyer Ashleigh , Merickel Lucy A. , Khalid Delan , Scheich Sebastian , Häupl Björn , Staudt Louis M. , Oellerich Thomas , Stegmaier Kimberly
Published: October 2024

MV4-11 and NB4 BioID_ATP1B1 and BioID_ATP1B3 results
Supplementary Table S3 from Single-Stranded DNA Gap Accumulation Is a Functional Biomarker for USP1 Inhibitor Sensitivity
Authors: da Costa Alexandre A. , Somuncu Ozge , Ravindranathan Ramya , Mukkavalli Sirisha , Martignetti David B. , Nguyen Huy , Jiao Yuqing , Lamarre Benjamin P. , Sadatrezaei Golbahar , Moreau Lisa , Liu Joyce , Iyer Divya R. , Lazaro Jean-Bernard , Shapiro Geoffrey I. , Parmar Kalindi , D’Andrea Alan D.
Published: October 2024

Clinical characteristics of tumor samples used to generate patient derived organoids
Supplementary Figure S10 from Targeting the Sodium–Potassium Pump as a Therapeutic Strategy in Acute Myeloid Leukemia
Authors: Schneider Constanze , Spaink Hermes , Alexe Gabriela , Dharia Neekesh V. , Meyer Ashleigh , Merickel Lucy A. , Khalid Delan , Scheich Sebastian , Häupl Björn , Staudt Louis M. , Oellerich Thomas , Stegmaier Kimberly
Published: October 2024

Cell viability assay in OCI-AML3 CTRL and TP53-KO cells treated with Nutlin-3.
Supplementary Figure S3 from Single-Stranded DNA Gap Accumulation Is a Functional Biomarker for USP1 Inhibitor Sensitivity
Authors: da Costa Alexandre A. , Somuncu Ozge , Ravindranathan Ramya , Mukkavalli Sirisha , Martignetti David B. , Nguyen Huy , Jiao Yuqing , Lamarre Benjamin P. , Sadatrezaei Golbahar , Moreau Lisa , Liu Joyce , Iyer Divya R. , Lazaro Jean-Bernard , Shapiro Geoffrey I. , Parmar Kalindi , D’Andrea Alan D.
Published: October 2024

Supplementary Figure S3. USP1 inhibitor exhibits synergistic activity with a POLQ inhibitor in BRCA1-deficient preclinical models
Table S1-4 from FANCI Inhibition Induces PARP1 Redistribution to Enhance the Efficacy of PARP Inhibitors in Breast Cancer
Authors: Huang Yu-Zhou , Sang Ming-Yi , Xi Pei-Wen , Xu Ruo-Xi , Cai Meng-Yuan , Wang Zi-Wen , Zhao Jian-Yi , Li Yi-Han , Wei Ji-Fu , Ding Qiang
Published: October 2024

Table S1-4 contain the specific sequences and information of Primers used for Quantitative RT-PCR, shRNA, siRNA, and Flag-tagged plasmids.
Figure S8 from FANCI Inhibition Induces PARP1 Redistribution to Enhance the Efficacy of PARP Inhibitors in Breast Cancer
Authors: Huang Yu-Zhou , Sang Ming-Yi , Xi Pei-Wen , Xu Ruo-Xi , Cai Meng-Yuan , Wang Zi-Wen , Zhao Jian-Yi , Li Yi-Han , Wei Ji-Fu , Ding Qiang
Published: October 2024

Figure S8 showcases the combination effect of talazoparib and palbociclib, as well as the influence of FANCI overexpression on this combination.
Figure S1 from FANCI Inhibition Induces PARP1 Redistribution to Enhance the Efficacy of PARP Inhibitors in Breast Cancer
Authors: Huang Yu-Zhou , Sang Ming-Yi , Xi Pei-Wen , Xu Ruo-Xi , Cai Meng-Yuan , Wang Zi-Wen , Zhao Jian-Yi , Li Yi-Han , Wei Ji-Fu , Ding Qiang
Published: October 2024

Figure S1 illustrates the mRNA expression levels of additional key members of the FA pathway.
Table S5 from Chromosome 7 Gain Compensates for Chromosome 10 Loss in Glioma
Authors: Nair Nishanth Ulhas , Schäffer Alejandro A. , Gertz E. Michael , Cheng Kuoyuan , Zerbib Johanna , Sahu Avinash Das , Leor Gil , Shulman Eldad D. , Aldape Kenneth D. , Ben-David Uri , Ruppin Eytan
Published: October 2024

Table S5
Table S4 from Chromosome 7 Gain Compensates for Chromosome 10 Loss in Glioma
Authors: Nair Nishanth Ulhas , Schäffer Alejandro A. , Gertz E. Michael , Cheng Kuoyuan , Zerbib Johanna , Sahu Avinash Das , Leor Gil , Shulman Eldad D. , Aldape Kenneth D. , Ben-David Uri , Ruppin Eytan
Published: October 2024

Table S4
Table S2 from Chromosome 7 Gain Compensates for Chromosome 10 Loss in Glioma
Authors: Nair Nishanth Ulhas , Schäffer Alejandro A. , Gertz E. Michael , Cheng Kuoyuan , Zerbib Johanna , Sahu Avinash Das , Leor Gil , Shulman Eldad D. , Aldape Kenneth D. , Ben-David Uri , Ruppin Eytan
Published: October 2024

Table S2
Table S1 from Chromosome 7 Gain Compensates for Chromosome 10 Loss in Glioma
Authors: Nair Nishanth Ulhas , Schäffer Alejandro A. , Gertz E. Michael , Cheng Kuoyuan , Zerbib Johanna , Sahu Avinash Das , Leor Gil , Shulman Eldad D. , Aldape Kenneth D. , Ben-David Uri , Ruppin Eytan
Published: October 2024

Table S1
Supplementary Material from Chromosome 7 Gain Compensates for Chromosome 10 Loss in Glioma
Authors: Nair Nishanth Ulhas , Schäffer Alejandro A. , Gertz E. Michael , Cheng Kuoyuan , Zerbib Johanna , Sahu Avinash Das , Leor Gil , Shulman Eldad D. , Aldape Kenneth D. , Ben-David Uri , Ruppin Eytan
Published: October 2024

Supplementary Notes, Supplementary Figures, and Supplementary Table Legends
Supplementary Data, Table S1-3 from Cancer-Associated Fibroblasts Expressing Sulfatase 1 Facilitate VEGFA-Dependent Microenvironmental Remodeling to Support Colorectal Cancer
Authors: Wang Huijuan , Chen Jiaxin , Chen Xiaoyu , Liu Yingqiang , Wang Jiawei , Meng Qing , Wang Huogang , He Ying , Song Yujia , Li Jingyun , Ju Zhenyu , Xiao Peng , Qian Junbin , Song Zhangfa
Published: October 2024

Supplementary Data.
Figure S1 from Cancer-Associated Fibroblasts Expressing Sulfatase 1 Facilitate VEGFA-Dependent Microenvironmental Remodeling to Support Colorectal Cancer
Authors: Wang Huijuan , Chen Jiaxin , Chen Xiaoyu , Liu Yingqiang , Wang Jiawei , Meng Qing , Wang Huogang , He Ying , Song Yujia , Li Jingyun , Ju Zhenyu , Xiao Peng , Qian Junbin , Song Zhangfa
Published: October 2024

Figure S1.
KEY SOURCE TABLE from m6A-Mediated Induction of 7-Dehydrocholesterol Reductase Stimulates Cholesterol Synthesis and cAMP Signaling to Promote Bladder Cancer Metastasis
Authors: Zeng Youmiao , Luo Yongbo , Zhao Keyuan , Liu Sheng , Wu Kaiwen , Wu Yudong , Du Kaixuan , Pan Wenbang , Dai Yiheng , Liu Yuanhao , Ren Mengda , Tian Fengyan , Zhou Lijie , Gu Chaohui
Published: October 2024

Gene sets and corresponding primers mentioned in the study
Figure S2 from The USP1 Inhibitor KSQ-4279 Overcomes PARP Inhibitor Resistance in Homologous Recombination–Deficient Tumors
Authors: Cadzow Louise , Brenneman Jehrod , Tobin Erica , Sullivan Pamela , Nayak Sumeet , Ali Janid A. , Shenker Sol , Griffith Jim , McGuire Michael , Grasberger Paula , Mishina Yuji , Murray Morgan , Dodson Anne E. , Gannon Hugh , Krall Elsa , Hixon Jeff , Chipumuro Edmond , Sinkevicius Kerstin , Gokhale Prafulla C. , Ganapathy Suthakar , Matulonis Ursula A. , Liu Joyce F. , Olaharski Andrew , Sangurdekar Dipen , Liu Hanlan , Wilt Jeremy , Schlabach Michael , Stegmeier Frank , Wylie Andrew A.
Published: October 2024

Enzyme kinetic studies of KSQ-4279
Figure S1 from The USP1 Inhibitor KSQ-4279 Overcomes PARP Inhibitor Resistance in Homologous Recombination–Deficient Tumors
Authors: Cadzow Louise , Brenneman Jehrod , Tobin Erica , Sullivan Pamela , Nayak Sumeet , Ali Janid A. , Shenker Sol , Griffith Jim , McGuire Michael , Grasberger Paula , Mishina Yuji , Murray Morgan , Dodson Anne E. , Gannon Hugh , Krall Elsa , Hixon Jeff , Chipumuro Edmond , Sinkevicius Kerstin , Gokhale Prafulla C. , Ganapathy Suthakar , Matulonis Ursula A. , Liu Joyce F. , Olaharski Andrew , Sangurdekar Dipen , Liu Hanlan , Wilt Jeremy , Schlabach Michael , Stegmeier Frank , Wylie Andrew A.
Published: October 2024

USP1/UAF1 CRISPR dependency profiles
Supplementary Figures from CD47-SIRPα Blockade Sensitizes Head and Neck Squamous Cell Carcinoma to Cetuximab by Enhancing Macrophage Adhesion to Cancer Cells
Authors: Li Bolei , Hao Yu , He Hongzhi , Fan Yu , Ren Biao , Peng Xian , Zhou Xuedong , Cheng Lei
Published: October 2024

Supplementary Figures
Data from An Alternatively Spliced Gain-of-Function NT5C2 Isoform Contributes to Chemoresistance in Acute Lymphoblastic Leukemia
Authors: Torres-Diz Manuel , Reglero Clara , Falkenstein Catherine D. , Castro Annette , Hayer Katharina E. , Radens Caleb M. , Quesnel-Vallières Mathieu , Ang Zhiwei , Sehgal Priyanka , Li Marilyn M. , Barash Yoseph , Tasian Sarah K. , Ferrando Adolfo , Thomas-Tikhonenko Andrei
Published: October 2024

Abstract
Relapsed or refractory B-cell acute lymphoblastic leukemia (B-ALL) is a major cause of pediatric cancer–related deaths. Relapse-specific mutations do not account for all chemotherapy failures in B-ALL patients, suggesting additional mechanisms of resistance. By mining RNA sequencing datasets of paired diagnostic/relapse pediatric B-ALL samples, we discovered pervasive alternative splicing (AS) patterns linked to relapse and affecting drivers of resistance to glucocorticoids, antifolates, and thiopurines. Most splicing variations represented cassette exon skipping, “poison” exon inclusion, and intron retention, phenocopying well-documented loss-of-function mutations. In contrast, relapse-associated AS of NT5C2 mRNA yielded an isoform with the functionally uncharacterized in-frame exon 6a. Incorporation of the 8-amino acid sequence SQVAVQKR into this enzyme created a putative phosphorylation site and resulted in elevated nucleosidase activity, which is a known consequence of gain-of-function mutations in NT5C2 and a common determinant of 6-mercaptopurine resistance. Consistent with this finding, NT5C2ex6a and the R238W hotspot variant conferred comparable levels of resistance to 6-mercaptopurine in B-ALL cells both in vitro and in vivo. Furthermore, both NT5C2ex6a and the R238W variant induced collateral sensitivity to the inosine monophosphate dehydrogenase inhibitor mizoribine. These results ascribe to splicing perturbations an important role in chemotherapy resistance in relapsed B-ALL and suggest that inosine monophosphate dehydrogenase inhibitors, including the commonly used immunosuppressive agent mycophenolate mofetil, could be a valuable therapeutic option for treating thiopurine-resistant leukemias.

Significance: Alternative splicing is a potent mechanism of acquired drug resistance in relapsed/refractory acute lymphoblastic leukemias that has diagnostic and therapeutic implications for patients who lack mutations in known chemoresistance genes.
Data from Natural Killer Cell Regulation of Breast Cancer Stem Cells Mediates Metastatic Dormancy
Authors: Bushnell Grace G. , Sharma Deeksha , Wilmot Henry C. , Zheng Michelle , Fashina Toluwaleke D. , Hutchens Chloe M. , Osipov Samuel , Burness Monika , Wicha Max S.
Published: October 2024

Abstract
Patients with breast cancer with estrogen receptor–positive tumors face a constant risk of disease recurrence for the remainder of their lives. Dormant tumor cells residing in tissues such as the bone marrow may generate clinically significant metastases many years after initial diagnosis. Previous studies suggest that dormant cancer cells display “stem-like” properties (cancer stem cell, CSC), which may be regulated by the immune system. To elucidate the role of the immune system in controlling dormancy and its escape, we studied dormancy in immunocompetent, syngeneic mouse breast cancer models. Three mouse breast cancer cell lines, PyMT, Met1, and D2.0R, contained CSCs that displayed short- and long-term metastatic dormancy in vivo, which was dependent on the host immune system. Each model was regulated by different components of the immune system. Natural killer (NK) cells were key for the metastatic dormancy phenotype in D2.0R cells. Quiescent D2.0R CSCs were resistant to NK cell cytotoxicity, whereas proliferative CSCs were sensitive. Resistance to NK cell cytotoxicity was mediated, in part, by the expression of BACH1 and SOX2 transcription factors. Expression of STING and STING targets was decreased in quiescent CSCs, and the STING agonist MSA-2 enhanced NK cell killing. Collectively, these findings demonstrate the role of immune regulation of breast tumor dormancy and highlight the importance of utilizing immunocompetent models to study this phenomenon.

Significance: The immune system controls disseminated breast cancer cells during disease latency, highlighting the need to utilize immunocompetent models to identify strategies for targeting dormant cancer cells and reducing metastatic recurrence.

See related commentary by Cackowski and Korkaya, p. 3319
Data from m6A-Mediated Induction of 7-Dehydrocholesterol Reductase Stimulates Cholesterol Synthesis and cAMP Signaling to Promote Bladder Cancer Metastasis
Authors: Zeng Youmiao , Luo Yongbo , Zhao Keyuan , Liu Sheng , Wu Kaiwen , Wu Yudong , Du Kaixuan , Pan Wenbang , Dai Yiheng , Liu Yuanhao , Ren Mengda , Tian Fengyan , Zhou Lijie , Gu Chaohui
Published: October 2024

Abstract
Dysregulation of cholesterol homeostasis occurs in multiple types of tumors and promotes cancer progression. Investigating the specific processes that induce abnormal cholesterol metabolism could identify therapeutic targets to improve cancer treatment. In this investigation, we observed upregulation of 7-dehydrocholesterol reductase (DHCR7), a vital enzyme involved in the synthesis of cholesterol, within bladder cancer tissues in comparison to normal tissues, which was correlated with increased bladder cancer metastasis. Increased expression of DHCR7 in bladder cancer was attributed to decreased mRNA degradation mediated by YTHDF2. Loss or inhibition of DHCR7 reduced bladder cancer cell invasion in vitro and metastasis in vivo. Mechanistically, DHCR7 promoted bladder cancer metastasis by activating the cAMP/protein kinase A/FAK pathway. Specifically, DHCR7 increased cAMP levels by elevating cholesterol content in lipid rafts, thereby facilitating the transduction of signaling pathways mediated by cAMP receptors. DHCR7 additionally enhanced the cAMP signaling pathway by reducing the concentration of 7-dehydrocholesterol and promoting the transcription of the G protein–coupled receptor, namely gastric inhibitory polypeptide receptor. Overall, these findings demonstrate that DHCR7 plays an important role in bladder cancer invasion and metastasis by modulating cholesterol synthesis and cAMP signaling. Furthermore, inhibition of DHCR7 shows promise as a viable therapeutic strategy for suppressing bladder cancer invasion and metastasis.

Significance: Inhibiting DHCR7 induces cholesterol metabolism reprogramming and lipid raft remodeling to inactivate the cAMP/protein kinase A/FAK axis and suppress bladder cancer metastasis, indicating the therapeutic potential of targeting DHCR7.
Supplementary Tables and Figures 1 from Effectiveness of PARP Inhibitor Maintenance Therapy in Ovarian Cancer by BRCA1/2 and a Scar-Based HRD Signature in Real-World Practice
Authors: Richardson Debra L. , Quintanilha Julia C. F. , Danziger Natalie , Li Gerald , Sokol Ethan , Schrock Alexa B. , Ebot Ericka , Bhardwaj Neeru , Norris Tanesha , Afghahi Anosheh , Frachioni Anthony , Washington Christina , Dockery Lauren , Elvin Julia , Graf Ryon P. , Moore Kathleen N.
Published: October 2024

Supplementary Tables and Figures
Supplementary Tables S1-S12 from KIR2DL2/DL3+NKs and Helios+Tregs in Peripheral Blood Predict Nivolumab Response in Patients with Metastatic Renal Cell Cancer
Authors: Santagata Sara , Trotta Anna Maria , D’Alterio Crescenzo , Napolitano Maria , Rea Giuseppina , Di Napoli Marilena , Portella Luigi , Ieranò Caterina , Guardascione Giuseppe , Coppola Elisabetta , Caux Christophe , Dubois Bertrand , Boyle Helen J. , Carles Joan , Rossetti Sabrina , Azzaro Rosa , Feroce Florinda , Perdonà Sisto , Fordellone Mario , Bello Anna Maria , Califano Daniela , Chiodini Paolo , Pignata Sandro , Scala Stefania
Published: October 2024

Supplementary Table S1. Antibodies used for flow cytometry Supplementary Table S2. mRCC-REV patients characteristics Supplementary Table S3. HDs characteristics Supplementary Table S4. Representativeness of Study Participants Supplementary Table S5. Univariate analysis of peripheral immune cell subsets between HD and mRCC-REV groups Supplementary Table S6. Longitudinal evaluation of peripheral immune cell subsets in mRCC-REV patients Supplementary Table S7. Differential distribution of peripheral immune cell subsets between R and NR groups (T0) in mRCC-REV patients Supplementary Table S8. Univariate analysis of peripheral immune cell subsets between R and NR groups including early death patients (T0) in mRCC-REV patients Supplementary Table S9. Cut-off value prediction with ROC curve for continuous variable at basal level and response to nivolumab after 3 months as classification variable Supplementary Table S10. Association between the KIR2DL2/DL3+NKs/Helios+Tregs values and response to nivolumab treatment Supplementary Table S11. Differential distribution of peripheral immune cell subsets between R and NR groups (T1) in mRCC-REV patients Supplementary Table S12. Cut-off value prediction with ROC curve for continuous variable at T1 and response to nivolumab after 3 months as classification variable
Supplementary Figure S8 from KIR2DL2/DL3+NKs and Helios+Tregs in Peripheral Blood Predict Nivolumab Response in Patients with Metastatic Renal Cell Cancer
Authors: Santagata Sara , Trotta Anna Maria , D’Alterio Crescenzo , Napolitano Maria , Rea Giuseppina , Di Napoli Marilena , Portella Luigi , Ieranò Caterina , Guardascione Giuseppe , Coppola Elisabetta , Caux Christophe , Dubois Bertrand , Boyle Helen J. , Carles Joan , Rossetti Sabrina , Azzaro Rosa , Feroce Florinda , Perdonà Sisto , Fordellone Mario , Bello Anna Maria , Califano Daniela , Chiodini Paolo , Pignata Sandro , Scala Stefania
Published: October 2024

Supplementary Figure S8. .632+ cross validation bootstrap ROC curves and the optimum pretreatment cut-off values of KIR2DL2/DL3+NKs and Helios+Tregs to determine the outcome of REV patients
Supplementary Figure S7 from KIR2DL2/DL3+NKs and Helios+Tregs in Peripheral Blood Predict Nivolumab Response in Patients with Metastatic Renal Cell Cancer
Authors: Santagata Sara , Trotta Anna Maria , D’Alterio Crescenzo , Napolitano Maria , Rea Giuseppina , Di Napoli Marilena , Portella Luigi , Ieranò Caterina , Guardascione Giuseppe , Coppola Elisabetta , Caux Christophe , Dubois Bertrand , Boyle Helen J. , Carles Joan , Rossetti Sabrina , Azzaro Rosa , Feroce Florinda , Perdonà Sisto , Fordellone Mario , Bello Anna Maria , Califano Daniela , Chiodini Paolo , Pignata Sandro , Scala Stefania
Published: October 2024

Supplementary Figure S7. Pretreatment NKs and Tregs subpopulations in mRCC-REV Long Responder (LR) patients vs Not-Responders (NR).
Supplementary Figure S6 from KIR2DL2/DL3+NKs and Helios+Tregs in Peripheral Blood Predict Nivolumab Response in Patients with Metastatic Renal Cell Cancer
Authors: Santagata Sara , Trotta Anna Maria , D’Alterio Crescenzo , Napolitano Maria , Rea Giuseppina , Di Napoli Marilena , Portella Luigi , Ieranò Caterina , Guardascione Giuseppe , Coppola Elisabetta , Caux Christophe , Dubois Bertrand , Boyle Helen J. , Carles Joan , Rossetti Sabrina , Azzaro Rosa , Feroce Florinda , Perdonà Sisto , Fordellone Mario , Bello Anna Maria , Califano Daniela , Chiodini Paolo , Pignata Sandro , Scala Stefania
Published: October 2024

Supplementary Figure S6. Swimmer’s plot of nivolumab-treated mRCC patients.
Supplementary Figure S5 from KIR2DL2/DL3+NKs and Helios+Tregs in Peripheral Blood Predict Nivolumab Response in Patients with Metastatic Renal Cell Cancer
Authors: Santagata Sara , Trotta Anna Maria , D’Alterio Crescenzo , Napolitano Maria , Rea Giuseppina , Di Napoli Marilena , Portella Luigi , Ieranò Caterina , Guardascione Giuseppe , Coppola Elisabetta , Caux Christophe , Dubois Bertrand , Boyle Helen J. , Carles Joan , Rossetti Sabrina , Azzaro Rosa , Feroce Florinda , Perdonà Sisto , Fordellone Mario , Bello Anna Maria , Califano Daniela , Chiodini Paolo , Pignata Sandro , Scala Stefania
Published: October 2024

Supplementary Figure S5. Nivolumab did not significantly affect peripheral NKs and Tregs
Supplementary Figure S4 from KIR2DL2/DL3+NKs and Helios+Tregs in Peripheral Blood Predict Nivolumab Response in Patients with Metastatic Renal Cell Cancer
Authors: Santagata Sara , Trotta Anna Maria , D’Alterio Crescenzo , Napolitano Maria , Rea Giuseppina , Di Napoli Marilena , Portella Luigi , Ieranò Caterina , Guardascione Giuseppe , Coppola Elisabetta , Caux Christophe , Dubois Bertrand , Boyle Helen J. , Carles Joan , Rossetti Sabrina , Azzaro Rosa , Feroce Florinda , Perdonà Sisto , Fordellone Mario , Bello Anna Maria , Califano Daniela , Chiodini Paolo , Pignata Sandro , Scala Stefania
Published: October 2024

Supplementary Figure S4. Pretreatment NKs co-expression of PD-1 and KIR2DL1or KIR2DL2/DL3 in mRCC-REV patients.
Supplementary Figure S3 from KIR2DL2/DL3+NKs and Helios+Tregs in Peripheral Blood Predict Nivolumab Response in Patients with Metastatic Renal Cell Cancer
Authors: Santagata Sara , Trotta Anna Maria , D’Alterio Crescenzo , Napolitano Maria , Rea Giuseppina , Di Napoli Marilena , Portella Luigi , Ieranò Caterina , Guardascione Giuseppe , Coppola Elisabetta , Caux Christophe , Dubois Bertrand , Boyle Helen J. , Carles Joan , Rossetti Sabrina , Azzaro Rosa , Feroce Florinda , Perdonà Sisto , Fordellone Mario , Bello Anna Maria , Califano Daniela , Chiodini Paolo , Pignata Sandro , Scala Stefania
Published: October 2024

Supplementary Figure S3. Pretreatment NKs and Tregs in mRCC-REV patients
Supplementary Figure S2 from KIR2DL2/DL3+NKs and Helios+Tregs in Peripheral Blood Predict Nivolumab Response in Patients with Metastatic Renal Cell Cancer
Authors: Santagata Sara , Trotta Anna Maria , D’Alterio Crescenzo , Napolitano Maria , Rea Giuseppina , Di Napoli Marilena , Portella Luigi , Ieranò Caterina , Guardascione Giuseppe , Coppola Elisabetta , Caux Christophe , Dubois Bertrand , Boyle Helen J. , Carles Joan , Rossetti Sabrina , Azzaro Rosa , Feroce Florinda , Perdonà Sisto , Fordellone Mario , Bello Anna Maria , Califano Daniela , Chiodini Paolo , Pignata Sandro , Scala Stefania
Published: October 2024

Supplementary Figure S2. Correlation between age and pretreatment NKs and Tregs immune subsets cells in mRCC-REV patients and HDs.
Supplementary Figure S13 from KIR2DL2/DL3+NKs and Helios+Tregs in Peripheral Blood Predict Nivolumab Response in Patients with Metastatic Renal Cell Cancer
Authors: Santagata Sara , Trotta Anna Maria , D’Alterio Crescenzo , Napolitano Maria , Rea Giuseppina , Di Napoli Marilena , Portella Luigi , Ieranò Caterina , Guardascione Giuseppe , Coppola Elisabetta , Caux Christophe , Dubois Bertrand , Boyle Helen J. , Carles Joan , Rossetti Sabrina , Azzaro Rosa , Feroce Florinda , Perdonà Sisto , Fordellone Mario , Bello Anna Maria , Califano Daniela , Chiodini Paolo , Pignata Sandro , Scala Stefania
Published: October 2024

Supplementary Figure S13. T0-T1 values (after one month of nivolumab) between PD-1+ Tregs and Helios+Tregs in Responder and Not Responder patients
Supplementary Figure S12 from KIR2DL2/DL3+NKs and Helios+Tregs in Peripheral Blood Predict Nivolumab Response in Patients with Metastatic Renal Cell Cancer
Authors: Santagata Sara , Trotta Anna Maria , D’Alterio Crescenzo , Napolitano Maria , Rea Giuseppina , Di Napoli Marilena , Portella Luigi , Ieranò Caterina , Guardascione Giuseppe , Coppola Elisabetta , Caux Christophe , Dubois Bertrand , Boyle Helen J. , Carles Joan , Rossetti Sabrina , Azzaro Rosa , Feroce Florinda , Perdonà Sisto , Fordellone Mario , Bello Anna Maria , Califano Daniela , Chiodini Paolo , Pignata Sandro , Scala Stefania
Published: October 2024

Supplementary Figure S12. Correlation between pretreatment of PD-1+Tregs and Helios+Tregs in Responder and Not-Responder patients.
Supplementary Figure S11 from KIR2DL2/DL3+NKs and Helios+Tregs in Peripheral Blood Predict Nivolumab Response in Patients with Metastatic Renal Cell Cancer
Authors: Santagata Sara , Trotta Anna Maria , D’Alterio Crescenzo , Napolitano Maria , Rea Giuseppina , Di Napoli Marilena , Portella Luigi , Ieranò Caterina , Guardascione Giuseppe , Coppola Elisabetta , Caux Christophe , Dubois Bertrand , Boyle Helen J. , Carles Joan , Rossetti Sabrina , Azzaro Rosa , Feroce Florinda , Perdonà Sisto , Fordellone Mario , Bello Anna Maria , Califano Daniela , Chiodini Paolo , Pignata Sandro , Scala Stefania
Published: October 2024

Supplementary Figure S11. HLA class I in primary RCC from REV patients
Supplementary Figure S10 from KIR2DL2/DL3+NKs and Helios+Tregs in Peripheral Blood Predict Nivolumab Response in Patients with Metastatic Renal Cell Cancer
Authors: Santagata Sara , Trotta Anna Maria , D’Alterio Crescenzo , Napolitano Maria , Rea Giuseppina , Di Napoli Marilena , Portella Luigi , Ieranò Caterina , Guardascione Giuseppe , Coppola Elisabetta , Caux Christophe , Dubois Bertrand , Boyle Helen J. , Carles Joan , Rossetti Sabrina , Azzaro Rosa , Feroce Florinda , Perdonà Sisto , Fordellone Mario , Bello Anna Maria , Califano Daniela , Chiodini Paolo , Pignata Sandro , Scala Stefania
Published: October 2024

Supplementary Figure S10. .632+ cross validation bootstrap ROC curves and the optimum T1 cut-off values of CD3+ and KIR2DL2/DL3+NKs to determine the outcome of REV patients
Supplementary Figure S1 from KIR2DL2/DL3+NKs and Helios+Tregs in Peripheral Blood Predict Nivolumab Response in Patients with Metastatic Renal Cell Cancer
Authors: Santagata Sara , Trotta Anna Maria , D’Alterio Crescenzo , Napolitano Maria , Rea Giuseppina , Di Napoli Marilena , Portella Luigi , Ieranò Caterina , Guardascione Giuseppe , Coppola Elisabetta , Caux Christophe , Dubois Bertrand , Boyle Helen J. , Carles Joan , Rossetti Sabrina , Azzaro Rosa , Feroce Florinda , Perdonà Sisto , Fordellone Mario , Bello Anna Maria , Califano Daniela , Chiodini Paolo , Pignata Sandro , Scala Stefania
Published: October 2024

Supplementary Figure S1. Gating strategy for identification of Tregs and NKs in peripheral blood.
Supplementary Table S1 from YAP1 Status Defines Two Intrinsic Subtypes of LCNEC with Distinct Molecular Features and Therapeutic Vulnerabilities
Authors: Stewart C. Allison , Diao Lixia , Xi Yuanxin , Wang Runsheng , Ramkumar Kavya , Serrano Alejandra G. , Tanimoto Azusa , Rodriguez B. Leticia , Morris Benjamin B. , Shen Li , Zhang Bingnan , Yang Yan , Hamad Samera H. , Cardnell Robert J. , Duarte Alberto , Sahu Moushumi , Novegil Veronica Y. , Weissman Bernard E. , Frumovitz Michael , Kalhor Neda , Solis Soto Luisa , da Rocha Pedro , Vokes Natalie , Gibbons Don L. , Wang Jing , Heymach John V. , Glisson Bonnie , Byers Lauren Averett , Gay Carl M.
Published: October 2024

Supplementary Table S1. Patient information for a subset with YAP1 IHC.
Supplementary Table S1 from Pembrolizumab and Cabozantinib in Recurrent and/or Metastatic Head and Neck Squamous Cell Carcinoma: Long-term Survival Update with a Biomarker Analysis
Authors: Saba Nabil F. , Chaudhary Ritu , Kirtane Kedar , Marra Angelo , Ekpenyong Asari , McCook-Veal Ashley , Schmitt Nicole C. , Gross Jennifer H. , Patel Mihir R. , Remick Jill , Bates James E. , McDonald Mark W. , Rudra Soumon F. , Stokes William A. , Biernacki Maria , Song Xiaofei , Slebos Robbert J.C. , Liu Yuan , Steuer Conor E. , Shin Dong M. , Teng Yong , Chung Christine H.
Published: October 2024

Supplementary Table S1. Study representativeness.
Supplementary Figure S6 from YAP1 Status Defines Two Intrinsic Subtypes of LCNEC with Distinct Molecular Features and Therapeutic Vulnerabilities
Authors: Stewart C. Allison , Diao Lixia , Xi Yuanxin , Wang Runsheng , Ramkumar Kavya , Serrano Alejandra G. , Tanimoto Azusa , Rodriguez B. Leticia , Morris Benjamin B. , Shen Li , Zhang Bingnan , Yang Yan , Hamad Samera H. , Cardnell Robert J. , Duarte Alberto , Sahu Moushumi , Novegil Veronica Y. , Weissman Bernard E. , Frumovitz Michael , Kalhor Neda , Solis Soto Luisa , da Rocha Pedro , Vokes Natalie , Gibbons Don L. , Wang Jing , Heymach John V. , Glisson Bonnie , Byers Lauren Averett , Gay Carl M.
Published: October 2024

Supplementary Figure S6. Drug response differences in YAP1-high and -low LCNEC preclinical models.
Table 3 from A Phase Ib/II Randomized Clinical Trial of Oleclumab with or without Durvalumab plus Chemotherapy in Patients with Metastatic Pancreatic Ductal Adenocarcinoma
Authors: Coveler Andrew L. , Reilley Matthew J. , Zalupski Mark , Macarulla Teresa , Fountzilas Christos , Ponz-Sarvisé Mariano , Nagrial Adnan , Uboha Nataliya V. , Frentzas Sophia , Overman Michael , Noonan Anne , Messersmith Wells A. , Pavlakis Nick , Mettu Niharika B. , Bisha Ina , Wang Ying , Smith Paul , Murtomaki Elina , Bielska Agata A. , Bragulat Veronique , Cooper Zachary A. , Kumar Rakesh , Spigel David R.
Published: October 2024

Efficacy in the dose-expansion phase (intent-to-treat population; N = 170).
Supplementary Table S2 from A Phase Ib/II Randomized Clinical Trial of Oleclumab with or without Durvalumab plus Chemotherapy in Patients with Metastatic Pancreatic Ductal Adenocarcinoma
Authors: Coveler Andrew L. , Reilley Matthew J. , Zalupski Mark , Macarulla Teresa , Fountzilas Christos , Ponz-Sarvisé Mariano , Nagrial Adnan , Uboha Nataliya V. , Frentzas Sophia , Overman Michael , Noonan Anne , Messersmith Wells A. , Pavlakis Nick , Mettu Niharika B. , Bisha Ina , Wang Ying , Smith Paul , Murtomaki Elina , Bielska Agata A. , Bragulat Veronique , Cooper Zachary A. , Kumar Rakesh , Spigel David R.
Published: October 2024

Treatment-emergent adverse events occurring at any severity in ≥20% of patients in any arm in the dose-escalation phase (as-treated population; N = 25)
Supplementary Table S1 from A Phase Ib/II Randomized Clinical Trial of Oleclumab with or without Durvalumab plus Chemotherapy in Patients with Metastatic Pancreatic Ductal Adenocarcinoma
Authors: Coveler Andrew L. , Reilley Matthew J. , Zalupski Mark , Macarulla Teresa , Fountzilas Christos , Ponz-Sarvisé Mariano , Nagrial Adnan , Uboha Nataliya V. , Frentzas Sophia , Overman Michael , Noonan Anne , Messersmith Wells A. , Pavlakis Nick , Mettu Niharika B. , Bisha Ina , Wang Ying , Smith Paul , Murtomaki Elina , Bielska Agata A. , Bragulat Veronique , Cooper Zachary A. , Kumar Rakesh , Spigel David R.
Published: October 2024

Patient demographics and disease characteristics (dose-escalation phase, as-treated population; N = 25)
Supplementary Figure S4 from A Phase Ib/II Randomized Clinical Trial of Oleclumab with or without Durvalumab plus Chemotherapy in Patients with Metastatic Pancreatic Ductal Adenocarcinoma
Authors: Coveler Andrew L. , Reilley Matthew J. , Zalupski Mark , Macarulla Teresa , Fountzilas Christos , Ponz-Sarvisé Mariano , Nagrial Adnan , Uboha Nataliya V. , Frentzas Sophia , Overman Michael , Noonan Anne , Messersmith Wells A. , Pavlakis Nick , Mettu Niharika B. , Bisha Ina , Wang Ying , Smith Paul , Murtomaki Elina , Bielska Agata A. , Bragulat Veronique , Cooper Zachary A. , Kumar Rakesh , Spigel David R.
Published: October 2024

CD73 expression by KRAS mutation status (A) and OS and PFS stratified by KRAS mutation status (B)
Supplementary Figure S3 from Integrative Multiomic Profiling of Triple-Negative Breast Cancer for Identifying Suitable Therapies
Authors: Jovanović Bojana , Church Sarah E. , Gorman Kara M. , North Khrystyna , Richardson Edward T. , DiLullo Molly , Attaya Victoria , Kasparian Julie , Mohammed-Abreu Ayesha , Kirkner Gregory , Hughes Melissa E. , Lin Nancy U. , Mittendorf Elizabeth A. , Schnitt Stuart J. , Tolaney Sara M. , Goel Shom
Published: October 2024

Supplementary Figure S3. Biological profiles and clinical outcomes for TNBC based on AR status.
Supplementary Figure S2 from Integrative Multiomic Profiling of Triple-Negative Breast Cancer for Identifying Suitable Therapies
Authors: Jovanović Bojana , Church Sarah E. , Gorman Kara M. , North Khrystyna , Richardson Edward T. , DiLullo Molly , Attaya Victoria , Kasparian Julie , Mohammed-Abreu Ayesha , Kirkner Gregory , Hughes Melissa E. , Lin Nancy U. , Mittendorf Elizabeth A. , Schnitt Stuart J. , Tolaney Sara M. , Goel Shom
Published: October 2024

Supplementary Figure S2. Biological profiles and clinical outcomes for TNBC based on RB status.
Supplementary Figure S1 from Integrative Multiomic Profiling of Triple-Negative Breast Cancer for Identifying Suitable Therapies
Authors: Jovanović Bojana , Church Sarah E. , Gorman Kara M. , North Khrystyna , Richardson Edward T. , DiLullo Molly , Attaya Victoria , Kasparian Julie , Mohammed-Abreu Ayesha , Kirkner Gregory , Hughes Melissa E. , Lin Nancy U. , Mittendorf Elizabeth A. , Schnitt Stuart J. , Tolaney Sara M. , Goel Shom
Published: October 2024

Supplementary Figure S1. REMARK diagram for the study.
Supplementary Table S3 from Integrated Clinical Genotype–Phenotype Characteristics of STAT3-Mutated Myeloid Neoplasms
Authors: Ye Matthew T. , Zuo Zhuang , Calin Steliana , Ye Fengxi , He Hua , Kamata Wataru , Yang Yaling , You M. James
Published: October 2024

Representativeness of Study Participants
Supplementary Table S4 from Second Primary Malignancies after CAR T-Cell Therapy: A Systematic Review and Meta-analysis of 5,517 Lymphoma and Myeloma Patients
Authors: Tix Tobias , Alhomoud Mohammad , Shouval Roni , Cliff Edward R. Scheffer , Perales Miguel-Angel , Cordas dos Santos David M. , Rejeski Kai
Published: October 2024

Sensitivity analysis.
Supplementary Figure S9 from Second Primary Malignancies after CAR T-Cell Therapy: A Systematic Review and Meta-analysis of 5,517 Lymphoma and Myeloma Patients
Authors: Tix Tobias , Alhomoud Mohammad , Shouval Roni , Cliff Edward R. Scheffer , Perales Miguel-Angel , Cordas dos Santos David M. , Rejeski Kai
Published: October 2024

SPM point estimates correlate with study follow-up.
Supplementary Figure S6 from Second Primary Malignancies after CAR T-Cell Therapy: A Systematic Review and Meta-analysis of 5,517 Lymphoma and Myeloma Patients
Authors: Tix Tobias , Alhomoud Mohammad , Shouval Roni , Cliff Edward R. Scheffer , Perales Miguel-Angel , Cordas dos Santos David M. , Rejeski Kai
Published: October 2024

Subgroup analysis of SPM point estimates stratified by prior therapy lines.
Supplementary Figure S5 from Second Primary Malignancies after CAR T-Cell Therapy: A Systematic Review and Meta-analysis of 5,517 Lymphoma and Myeloma Patients
Authors: Tix Tobias , Alhomoud Mohammad , Shouval Roni , Cliff Edward R. Scheffer , Perales Miguel-Angel , Cordas dos Santos David M. , Rejeski Kai
Published: October 2024

Subgroup analysis of SPM point estimates stratified by prior HCT exposure.
Figure 5 from Remote Neuroinflammation in Newly Diagnosed Glioblastoma Correlates with Unfavorable Clinical Outcome
Authors: Bartos Laura M. , Quach Stefanie , Zenatti Valerio , Kirchleitner Sabrina V. , Blobner Jens , Wind-Mark Karin , Kolabas Zeynep Ilgin , Ulukaya Selin , Holzgreve Adrien , Ruf Viktoria C. , Kunze Lea H. , Kunte Sebastian T. , Hoermann Leonie , Härtel Marlies , Park Ha Eun , Groß Mattes , Franzmeier Nicolai , Zatcepin Artem , Zounek Adrian , Kaiser Lena , Riemenschneider Markus J. , Perneczky Robert , Rauchmann Boris-Stephan , Stöcklein Sophia , Ziegler Sibylle , Herms Jochen , Ertürk Ali , Tonn Joerg C. , Thon Niklas , von Baumgarten Louisa , Prestel Matthias , Tahirovic Sabina , Albert Nathalie L. , Brendel Matthias
Published: October 2024

Contralateral hemispheres of SB28 glioblastoma mice indicate signatures of disease-associated myeloid cells and immunosuppression. A, Volcano plot highlights genes with significant upregulation and downregulation in the contralateral hemisphere of SB28 glioblastoma mice (red and blue, respectively) compared to sham. B, qPCR reveals higher expression of genes related to an inflammatory myeloid cell state in contralateral hemispheres of SB28 glioblastoma mice in contrast to sham. C, Illustration of the 50 pathways with highest elevation in immune cells of the contralateral hemisphere of SB28 glioblastoma mice (informed by IPA). Note that 40 out of the 50 pathways with highest activation were related to cell migration (phagocytes, leukocytes), phagocytosis, and immune cell activation (indicated in blue). D, IPA network analysis based on altered gene expression signatures in contralateral hemispheres of SB28 glioblastoma mice in contrast to sham. Depicted is a network plot showing TSPO-mediated associations with poor prognosis (e.g., CCL2) and immunosuppression (e.g., CHI3L1).
Supplementary Figure S2 from Second Primary Malignancies after CAR T-Cell Therapy: A Systematic Review and Meta-analysis of 5,517 Lymphoma and Myeloma Patients
Authors: Tix Tobias , Alhomoud Mohammad , Shouval Roni , Cliff Edward R. Scheffer , Perales Miguel-Angel , Cordas dos Santos David M. , Rejeski Kai
Published: October 2024

Study retrieval and identification for meta-analysis.
Figure 2 from Remote Neuroinflammation in Newly Diagnosed Glioblastoma Correlates with Unfavorable Clinical Outcome
Authors: Bartos Laura M. , Quach Stefanie , Zenatti Valerio , Kirchleitner Sabrina V. , Blobner Jens , Wind-Mark Karin , Kolabas Zeynep Ilgin , Ulukaya Selin , Holzgreve Adrien , Ruf Viktoria C. , Kunze Lea H. , Kunte Sebastian T. , Hoermann Leonie , Härtel Marlies , Park Ha Eun , Groß Mattes , Franzmeier Nicolai , Zatcepin Artem , Zounek Adrian , Kaiser Lena , Riemenschneider Markus J. , Perneczky Robert , Rauchmann Boris-Stephan , Stöcklein Sophia , Ziegler Sibylle , Herms Jochen , Ertürk Ali , Tonn Joerg C. , Thon Niklas , von Baumgarten Louisa , Prestel Matthias , Tahirovic Sabina , Albert Nathalie L. , Brendel Matthias
Published: October 2024

Contralateral TSPO-PET signal elevation is associated with tumor phenotype and localization. A and B, Correlation of contralateral TSPO-PET signals in patients with glioblastoma (n = 38) with the TSPO-PET signal of the tumor (A) and the tumor volume in TSPO-PET, FET-PET (B, left), and MRI (B, right). C, Examples of TSPO-PET images derived from patients with distinct tumor extent and TSPO expression in PET indicate distinct contralateral PET signal elevation. D, Overall correlation between corresponding areas of the tumor and the contralateral hemispheres including all 123 brain sub-regions of each individual patient. E, Correlation of regionally defined tumor seed regions with TSPO-PET signals of the 123 sub-regions in the contralateral hemisphere. Surface projection of tumor seed localization (top rows: seed region, colored in black) and corresponding contralateral coefficients of correlation (bottom rows). IFG, inferior-frontal gyrus; ITG, inferior-temporal gyrus; MesTemp, mesio-temporal; MFG, mid-frontal gyrus; Motor, motor area; MTG, mid-temporal gyrus; OFG, orbitofrontal gyrus; SFG, superior-frontal gyrus; STG, superior-temporal gyrus. F, Correlation of both hemispheres within 15 previously defined anatomically and functionally connected brain regions. Highest coefficients of correlation are colored in red, significant correlations are highlighted by thick boundaries.
Supplementary Data 2 from Metabolomic Prediction of Breast Cancer Treatment–Induced Neurologic and Metabolic Toxicities
Authors: Piffoux Max , Jacquemin Jérémie , Pétéra Mélanie , Durand Stéphanie , Abila Angélique , Centeno Delphine , Joly Charlotte , Lyan Bernard , Martin Anne-Laure , Everhard Sibille , Boyault Sandrine , Pistilli Barbara , Fournier Marion , Rouanet Philippe , Havas Julie , Sauterey Baptiste , Campone Mario , Tarpin Carole , Mouret-Reynier Marie-Ange , Rigal Olivier , Petit Thierry , Lasset Christine , Bertaut Aurélie , Cottu Paul , André Fabrice , Vaz-Luis Ines , Pujos-Guillot Estelle , Drouet Youenn , Trédan Olivier
Published: October 2024

metabolic
Supplementary Data 1 from Metabolomic Prediction of Breast Cancer Treatment–Induced Neurologic and Metabolic Toxicities
Authors: Piffoux Max , Jacquemin Jérémie , Pétéra Mélanie , Durand Stéphanie , Abila Angélique , Centeno Delphine , Joly Charlotte , Lyan Bernard , Martin Anne-Laure , Everhard Sibille , Boyault Sandrine , Pistilli Barbara , Fournier Marion , Rouanet Philippe , Havas Julie , Sauterey Baptiste , Campone Mario , Tarpin Carole , Mouret-Reynier Marie-Ange , Rigal Olivier , Petit Thierry , Lasset Christine , Bertaut Aurélie , Cottu Paul , André Fabrice , Vaz-Luis Ines , Pujos-Guillot Estelle , Drouet Youenn , Trédan Olivier
Published: October 2024

Supplementary Data 1