bluuebunny/crossref_metadata_2025 huggingface dataset:
Flash-algorithm for helix fit
Authors: Dima Mihai-Octavian , Dima Mihai-Tiberiu , Dima Maria , Mihailescu Madalina
Published: October 2024

We present a novel helix fit, based on an analytical method, on par with FPGA implementations in terms of speed. High-luminosity experiments exhibit event pileup (200 at the upgraded LHC). 1 , 2 To cope with the data load, the concept of Hardware Track Trigger (in the Event Filter pipeline) emerged. The specific solution 3 at ATLAS deploys a Stratix-10 FPGA chip in conjunction with a pre-fitted track database. The throughput is approximately 1.5 M tracks/s. Comparatively we can fit 7.6 M tracks/s (without pattern recognition, no field non-uniformity) on Xeon-Icelake – which puts our solution in a competitive position vis-á-vis the dedicated hardware one when pattern recognition (say Hough transform for stiff tracks, equivalent to resolution relaxation in Ref. 3 ) is included.
Electromagnetic dissociation of nuclei: From LHC to NICA
Authors: Pshenichnov I. A. , Dmitrieva U. A. , Savenkov S. D. , Svetlichnyi A. O.
Published: October 2024

In ultraperipheral collisions (UPC) of relativistic nuclei, the nuclear density distributions do not overlap, and the collision partners interact through Lorentz-contracted Coulomb fields. This leads to electromagnetic dissociation (EMD) of the nuclei induced by equivalent Weizsäcker–Williams photons. The RELDIS model was used to simulate the EMD of [Formula: see text]Bi and [Formula: see text]Xe beam nuclei in the MPD experiment at NICA, focusing on neutron and proton emissions in [Formula: see text]Bi–[Formula: see text]Bi and [Formula: see text]Xe–[Formula: see text]W collisions in collider and fixed target experiments, respectively. These simulations are crucial for understanding the potential contamination of detected hadronic events by EMD events. In addition, EMD of [Formula: see text]Xe in UPC with a CsI target at the BM@N experiment was modeled. A monoenergetic neutron beam resulting from EMD at the BM@N setup can be used for detector calibration and radiobiological research.
Flexible Control Limits for Interval-Valued Data Using Mixture Probability Distributions
Authors: Ravichandran J. , Nandhini G. R.
Published: October 2024

Availability of data in different forms is a boon or bane as it may require different approaches to deal with. In fact, while the construction of control charts is straightforward if the data are real-valued, in many practical situations data are essentially interval-valued with observations often represented by minimum and maximum values. While there are only fewer attempts to develop control charts for interval-valued data, no simple-to-use approaches have been proposed to deal with such type of data. In this paper, considering the idea of the development of control limits for multi-stream processes, we propose to make use of the mixture probability distributions approach to determine control limits for the interval-valued data. The resulting control limits are flexible in nature as they are linked to the control limits of the overall distribution that is based on the average of the means of two upper and lower populations along with their respective standard deviations. We have studied and numerically evaluated the average run length (ARL) properties of the proposed control chart to demonstrate the ways of determining the control chart coefficients. The proposed control chart is then illustrated using a dataset and conclusions are drawn based on the results.
Constructions of optimal cyclic subspace codes via Sidon spaces
Authors: Zhang He , Tang Chunming , Cao Xiwang
Published: October 2024

Let [Formula: see text] be the finite field with cardinality [Formula: see text], and let [Formula: see text] be positive integers, where [Formula: see text] is a factor of [Formula: see text]. Denote by [Formula: see text] the set of all [Formula: see text]-dimensional [Formula: see text]-subspaces of [Formula: see text]. Let [Formula: see text] be a positive integer and [Formula: see text] with [Formula: see text] and [Formula: see text] for any [Formula: see text]. If [Formula: see text], Zhang and Cao [Further constructions of cyclic subspace codes, Cryptogr. Commun. 13 (2021) 245–262] used the set [Formula: see text] to construct several cyclic subspace codes in [Formula: see text] with size [Formula: see text] and optimal minimum distance [Formula: see text]. Under the condition [Formula: see text], Niu, Xiao and Gao [Adv. Math. Commun. 18(4) (2024) 1123–1437] designed a kind of optimal cyclic subspace codes in [Formula: see text] with size [Formula: see text]. This paper further improves their results by using [Formula: see text] and variants of Sidon spaces in [Formula: see text]. In particular, when [Formula: see text] and [Formula: see text] is an odd prime, our code size can attain at [Formula: see text]. With the same parameters, this new code has optimal minimum distance [Formula: see text] and has more codewords than previous works.
A series associated to Rankin–Selberg L-function and modified K-Bessel function
Authors: Maji Bibekananda , Naskar Pritam , Sathyanarayana Sumukha
Published: October 2024

Zagier, in 1981, conjectured that the constant term of an automorphic function associated to the Ramanujan delta function, i.e. [Formula: see text] has a connection with the nontrivial zeros of [Formula: see text]. This conjecture was finally proved by Hafner and Stopple in 2000. Recently, Chakraborty et al. extended this observation for any normalized Hecke eigenform over [Formula: see text] In this paper, we study the infinite series [Formula: see text] for [Formula: see text], where [Formula: see text] denotes the [Formula: see text]th Fourier coefficient of a normalized Hecke eigenform [Formula: see text] and [Formula: see text] represents the modified Bessel function of the second kind of order [Formula: see text]. We generalize a recent identity of Berndt et al. We also observe that the aforementioned series corresponding to [Formula: see text] has a connection with the nontrivial zeros of [Formula: see text].
Japan’s Altered Defence Roadmap in a New Era
Authors: JAIN Purnendra
Published: October 2024

Japan is charting a new path to its defence policy through internal and external balancing in a tense strategic environment defined by uncertainties. While external balancing refers to building wider networks of partners beyond its key security ally, the United States, internal balancing includes establishing new laws and policy reforms and building favourable public opinion. This essay argues that Japan is on the cusp of transformative changes in its defence roadmap, which nations around the Indo-Pacific and beyond will be watching carefully.
India’s Diplomacy in Integrating Regional Infrastructure and Its Implication for China
Authors: WU Lin
Published: October 2024

In recent years, the Modi government has taken an active role in integrating regional infrastructure, participating in the geopolitical game in South Asia and the Indo-Pacific through infrastructure diplomacy and promoting development cooperation in the Global South. This paper examines India’s intentions and actions in integrating regional infrastructure. It also explores the prospects and impacts in the context of Modi 3.0’s shift to a ‘Bharat first’ foreign policy.
Anatomy of a 300 Myr old fjord in Namibia
Authors: Le Heron D. P. , Wohlschlägl R. , Mejías Osorio P. , Kettler C. , Nduutepo A.
Published: October 2024

Namibia is remarkable in terms of its network of
c
. 300 Myr old fjords, cut by Gondwanan glaciers at high palaeolatitudes during the Late Paleozoic Ice Age (LPIA). A classic suite of structures is preserved on Proterozoic bedrock, including striations, roches moutonnées and other subglacial features within many of these palaeovalleys. Some palaeovalleys are plastered with comparatively thin diamictites (a few metres) of presumed subglacial origin, in turn capped by ice marginal delta successions (tens of metres). Close examination of deposits in the outer Orutanda Fjord palaeovalley reveals an architecture that shows departure from this trend. There, boulder-bearing diamictites pass laterally into highly contorted heterolithic successions comprising folded and faulted sandstones, siltstones and shales. Aerial imagery from uncrewed aerial vehicles in tandem with traditional field observations permits mapping of assemblages of soft-sediment deformation structures (tight to recumbent folds, deformation bands, faults, sheath folds) together with spatial mapping of the long axis of boulders in diamictite. Collectively, this assemblage of structures points towards subglacial deformation, and hence an origin as a ‘deforming bed’ beneath a glacier. Although several open questions remain regarding the precise deformation mechanisms, the concept of glacial readvances into a deeply incised palaeovalley is proposed, by direct analogy to similar stratigraphic architectures in the LPIA record of South America.
Co-clustering: A Survey of the Main Methods, Recent Trends, and Open Problems
Authors: Battaglia Elena , Peiretti Federico , Pensa Ruggero Gaetano
Published: October 2024

Since its early formulations, co-clustering has gained popularity and interest both within and outside the machine learning community as a powerful learning paradigm for clustering high-dimensional data with good explainability properties. The simultaneous partitioning of all the modes of the input data tensors (rows and columns in a data matrix) is both a method for improving clustering on one mode while performing dimensionality reduction on the other mode(s), and a tool for providing an actionable interpretation of the clusters in the main mode as summaries of the features in each other mode(s). Hence, it is useful in many complex decision systems and data science applications. In this article, we survey the the co-clustering literature by reviewing the main co-clustering methods, with a special focus on the work done in the past 25 years. We identify, describe, and compare the main algorithmic categories and provide a practical characterization with respect to similar unsupervised techniques. Additionally, we try to explain why it is still a powerful tool despite the apparent recent decreasing interest shown by the machine learning community. To this purpose, we review the most recent trends in co-clustering research and outline the open problems and promising future research perspectives.
Supplementary Table S5 from Combining Genomic Biomarkers to Guide Immunotherapy in Non–Small Cell Lung Cancer
Authors: van de Haar Joris , Mankor Joanne M. , Hummelink Karlijn , Monkhorst Kim , Smit Egbert F. , Wessels Lodewyk F.A. , Cuppen Edwin , Aerts Joachim G.J.V. , Voest Emile E.
Published: October 2024

Baseline characteristics of patients in the validation cohort, stratified by the TMB and STK11/KEAP1/EGFR alteration status.
Supplementary Table S3 from Combining Genomic Biomarkers to Guide Immunotherapy in Non–Small Cell Lung Cancer
Authors: van de Haar Joris , Mankor Joanne M. , Hummelink Karlijn , Monkhorst Kim , Smit Egbert F. , Wessels Lodewyk F.A. , Cuppen Edwin , Aerts Joachim G.J.V. , Voest Emile E.
Published: October 2024

Baseline characteristics of patients in the discovery cohort, stratified by the TMB and STK11/KEAP1/EGFR alteration status.
Supplementary Table S1 from Combining Genomic Biomarkers to Guide Immunotherapy in Non–Small Cell Lung Cancer
Authors: van de Haar Joris , Mankor Joanne M. , Hummelink Karlijn , Monkhorst Kim , Smit Egbert F. , Wessels Lodewyk F.A. , Cuppen Edwin , Aerts Joachim G.J.V. , Voest Emile E.
Published: October 2024

Clinicogenomic dataset of the discovery cohort used for biomarker analyses.
Supplementary Figure S4 from Combining Genomic Biomarkers to Guide Immunotherapy in Non–Small Cell Lung Cancer
Authors: van de Haar Joris , Mankor Joanne M. , Hummelink Karlijn , Monkhorst Kim , Smit Egbert F. , Wessels Lodewyk F.A. , Cuppen Edwin , Aerts Joachim G.J.V. , Voest Emile E.
Published: October 2024

Alterations in STK11, KEAP1, or EGFR and survival of TMB-based subgroups in the validation cohort.
Data from Combining Neratinib with CDK4/6, mTOR, and MEK Inhibitors in Models of HER2-positive Cancer
Authors: Zhao Ming , Scott Stephen , Evans Kurt W. , Yuca Erkan , Saridogan Turcin , Zheng Xiaofeng , Wang Heping , Korkut Anil , Cruz Pico Christian X. , Demirhan Mehmet , Kirby Bryce , Kopetz Scott , Diala Irmina , Lalani Alshad S. , Piha-Paul Sarina , Meric-Bernstam Funda
Published: October 2024

AbstractPurpose:
Neratinib is an irreversible, pan-HER tyrosine kinase inhibitor that is FDA approved for HER2-overexpressing/amplified (HER2+) breast cancer. In this preclinical study, we explored the efficacy of neratinib in combination with inhibitors of downstream signaling in HER2+ cancers in vitro and in vivo.
Experimental Design:
Cell viability, colony formation assays, and Western blotting were used to determine the effect of neratinib in vitro. In vivo efficacy was assessed with patient-derived xenografts (PDX): two breast, two colorectal, and one esophageal cancer (with HER2 mutations). Four PDXs were derived from patients who received previous HER2-targeted therapy. Proteomics were assessed through reverse phase protein arrays and network-level adaptive responses were assessed through Target Score algorithm.
Results:
In HER2+ breast cancer cells, neratinib was synergistic with multiple agents, including mTOR inhibitors everolimus and sapanisertib, MEK inhibitor trametinib, CDK4/6 inhibitor palbociclib, and PI3Kα inhibitor alpelisib. We tested efficacy of neratinib with everolimus, trametinib, or palbociclib in five HER2+ PDXs. Neratinib combined with everolimus or trametinib led to a 100% increase in median event-free survival (EFS; tumor doubling time) in 25% (1/4) and 60% (3/5) of models, respectively, while neratinib with palbociclib increased EFS in all five models. Network analysis of adaptive responses demonstrated upregulation of EGFR and HER2 signaling in response to CDK4/6, mTOR, and MEK inhibition, possibly providing an explanation for the observed synergies with neratinib.
Conclusions:
Taken together, our results provide strong preclinical evidence for combining neratinib with CDK4/6, mTOR, and MEK inhibitors for the treatment of HER2+ cancer.
Supplementary Table S2 from Characterization of Wnt Signaling Pathway Aberrations in Metastatic Prostate Cancer
Authors: Choi Sharon H. , Pan Elizabeth , Elliott Andrew , Beltran Himisha , Panian Justine , Jamieson Christina , Bagrodia Aditya , Rose Brent , Herchenhorn Daniel , Heath Elisabeth , Nabhan Chadi , Antonarakis Emmanuel S. , McKay Rana R.
Published: October 2024

Supplementary Table S2
Supplementary Table S1 from Characterization of Wnt Signaling Pathway Aberrations in Metastatic Prostate Cancer
Authors: Choi Sharon H. , Pan Elizabeth , Elliott Andrew , Beltran Himisha , Panian Justine , Jamieson Christina , Bagrodia Aditya , Rose Brent , Herchenhorn Daniel , Heath Elisabeth , Nabhan Chadi , Antonarakis Emmanuel S. , McKay Rana R.
Published: October 2024

Supplementary Table S1
Supplementary Tables S1-S3 from Targeting Acute Myeloid Leukemia Stem Cells through Perturbation of Mitochondrial Calcium
Authors: Sheth Anagha Inguva , Althoff Mark J. , Tolison Hunter , Engel Krysta , Amaya Maria L. , Krug Anna E. , Young Tracy N. , Minhajuddin Mohammad , Pei Shanshan , Patel Sweta B. , Winters Amanda , Miller Regan , Shelton Ian T. , St-Germain Jonathan , Ling Tianyi , Jones Courtney L. , Raught Brian , Gillen Austin E. , Ransom Monica , Staggs Sarah , Smith Clayton A. , Pollyea Daniel A. , Stevens Brett M. , Jordan Craig T.
Published: October 2024

Supplementary Table 1. List of Bonafide BCL-2 Interactors in HEK293T Cells. Supplementary Table 2. Characteristics of Patient Specimens. Supplementary Table 3. CiteSeq Antibodies Used for Clustering.
Supplementary Figures S1-S6 from Targeting Acute Myeloid Leukemia Stem Cells through Perturbation of Mitochondrial Calcium
Authors: Sheth Anagha Inguva , Althoff Mark J. , Tolison Hunter , Engel Krysta , Amaya Maria L. , Krug Anna E. , Young Tracy N. , Minhajuddin Mohammad , Pei Shanshan , Patel Sweta B. , Winters Amanda , Miller Regan , Shelton Ian T. , St-Germain Jonathan , Ling Tianyi , Jones Courtney L. , Raught Brian , Gillen Austin E. , Ransom Monica , Staggs Sarah , Smith Clayton A. , Pollyea Daniel A. , Stevens Brett M. , Jordan Craig T.
Published: October 2024

Supplementary Figure 1. Comprehensive RNA-Seq and CITE-Seq analysis of venetoclax sensitive versus resistant AML specimens. Supplementary Figure 2. Further Characterization of BCL-2/SERCA3 Relationship and Role of SERCA3 in Primary Human AML Cells. Supplementary Figure 3. BCL-2 Interactors and Characterization of additional MCU Inhibitors in Venetoclax Resistant ROS-low AML cells. Supplementary Figure 4. Effects of Chemotherapeutic agents on AML Function. Supplementary Figure 5. Effects of Mitoxantrone on In Vivo PDX Experiments. Supplementary Figure 6. Effects of Extracellular Calcium Addition on Mitochondrial Calcium Content in Primary Human AML cells.
Supplementary Figures S1-S4 from Clonal Lineage Tracing with Somatic Delivery of Recordable Barcodes Reveals Migration Histories of Metastatic Prostate Cancer
Authors: Serio Ryan N. , Scheben Armin , Lu Billy , Gargiulo Domenic V. , Patruno Lucrezia , Buckholtz Caroline L. , Chaffee Ryan J. , Jibilian Megan C. , Persaud Steven G. , Staklinski Stephen J. , Hassett Rebecca , Brault Lise M. , Ramazzotti Daniele , Barbieri Christopher E. , Siepel Adam C. , Nowak Dawid G.
Published: October 2024

Supplementary Figure S1. Validation of EvoCaP platform in vitro. Supplementary Figure S2. BC10 exhibited robust editing efficiency in vitro. Supplementary Figure S3. Technical markers to identify tumor cells are present in organs. Supplementary Figure S4. Consistent bioluminescence and fluorescence imaging of tissues from EvoCaP mice.
Supplementary Figure S5 from Iron-(Fe3+)-Dependent Reactivation of Telomerase Drives Colorectal Cancers
Authors: Shanmugam Raghuvaran , Majee Prativa , Shi Wei , Ozturk Mert B. , Vaiyapuri Thamil S. , Idzham Khaireen , Raju Anandhkumar , Shin Seung H. , Fidan Kerem , Low Joo-Leng , Chua Joelle Y.H. , Kong Yap C. , Qi Ong Y. , Tan Emile , Chok Aik Y. , Seow-En Isaac , Wee Ian , Macalinao Dominique C. , Chong Dawn Q. , Chang Hong Y. , Lee Fiona , Leow Wei Q. , Murata-Hori Maki , Xiaoqian Zhang , Shumei Chia , Tan Chris S.H. , Dasgupta Ramanuj , Tan Iain B. , Tergaonkar Vinay
Published: October 2024

SP2509 mediated regulation of TERT through Pirin
Supplementary Figure S3 from Iron-(Fe3+)-Dependent Reactivation of Telomerase Drives Colorectal Cancers
Authors: Shanmugam Raghuvaran , Majee Prativa , Shi Wei , Ozturk Mert B. , Vaiyapuri Thamil S. , Idzham Khaireen , Raju Anandhkumar , Shin Seung H. , Fidan Kerem , Low Joo-Leng , Chua Joelle Y.H. , Kong Yap C. , Qi Ong Y. , Tan Emile , Chok Aik Y. , Seow-En Isaac , Wee Ian , Macalinao Dominique C. , Chong Dawn Q. , Chang Hong Y. , Lee Fiona , Leow Wei Q. , Murata-Hori Maki , Xiaoqian Zhang , Shumei Chia , Tan Chris S.H. , Dasgupta Ramanuj , Tan Iain B. , Tergaonkar Vinay
Published: October 2024

ITDRF-CETSA method identifying SP2509’s target.
Supplementary Figure S13 from Iron-(Fe3+)-Dependent Reactivation of Telomerase Drives Colorectal Cancers
Authors: Shanmugam Raghuvaran , Majee Prativa , Shi Wei , Ozturk Mert B. , Vaiyapuri Thamil S. , Idzham Khaireen , Raju Anandhkumar , Shin Seung H. , Fidan Kerem , Low Joo-Leng , Chua Joelle Y.H. , Kong Yap C. , Qi Ong Y. , Tan Emile , Chok Aik Y. , Seow-En Isaac , Wee Ian , Macalinao Dominique C. , Chong Dawn Q. , Chang Hong Y. , Lee Fiona , Leow Wei Q. , Murata-Hori Maki , Xiaoqian Zhang , Shumei Chia , Tan Chris S.H. , Dasgupta Ramanuj , Tan Iain B. , Tergaonkar Vinay
Published: October 2024

Iron-(Fe3+) regulates hTERT via Pirin-mediated control of FBXW7, the Sp1 targeting E3 ligase
Supplementary Table S2 from CD28 Costimulation Augments CAR Signaling in NK Cells via the LCK/CD3ζ/ZAP70 Signaling Axis
Authors: Acharya Sunil , Basar Rafet , Daher May , Rafei Hind , Li Ping , Uprety Nadima , Ensley Emily , Shanley Mayra , Kumar Bijender , Banerjee Pinaki P. , Melo Garcia Luciana , Lin Paul , Mohanty Vakul , Kim Kun H. , Jiang Xianli , Pan Yuchen , Li Ye , Liu Bin , Nunez Cortes Ana K. , Zhang Chenyu , Fathi Mohsen , Rezvan Ali , Montalvo Melisa J. , Cha Sophia L. , Reyes-Silva Francia , Shrestha Rejeena , Guo Xingliang , Kundu Kiran , Biederstädt Alexander , Muniz-Feliciano Luis , Deyter Gary M. , Kaplan Mecit , Jiang Xin R. , Liu Enli , Jain Antrix , Roszik Janos , Fowlkes Natalie W. , Solis Soto Luisa M. , Raso Maria G. , Khoury Joseph D. , Lin Pei , Vega Francisco , Varadarajan Navin , Chen Ken , Marin David , Shpall Elizabeth J. , Rezvani Katayoun
Published: October 2024

(Related to Fig.6G) The list of differentially abundance proteins between CAR27-ζ vs. CAR27-28.
Supplementary Figure S10 from Iron-(Fe3+)-Dependent Reactivation of Telomerase Drives Colorectal Cancers
Authors: Shanmugam Raghuvaran , Majee Prativa , Shi Wei , Ozturk Mert B. , Vaiyapuri Thamil S. , Idzham Khaireen , Raju Anandhkumar , Shin Seung H. , Fidan Kerem , Low Joo-Leng , Chua Joelle Y.H. , Kong Yap C. , Qi Ong Y. , Tan Emile , Chok Aik Y. , Seow-En Isaac , Wee Ian , Macalinao Dominique C. , Chong Dawn Q. , Chang Hong Y. , Lee Fiona , Leow Wei Q. , Murata-Hori Maki , Xiaoqian Zhang , Shumei Chia , Tan Chris S.H. , Dasgupta Ramanuj , Tan Iain B. , Tergaonkar Vinay
Published: October 2024

SP2509 mediated inhibition of CRCs occurs due to loss of iron-(Fe3+) mediated Pirin activity
Supplementary Figure S1 from Iron-(Fe3+)-Dependent Reactivation of Telomerase Drives Colorectal Cancers
Authors: Shanmugam Raghuvaran , Majee Prativa , Shi Wei , Ozturk Mert B. , Vaiyapuri Thamil S. , Idzham Khaireen , Raju Anandhkumar , Shin Seung H. , Fidan Kerem , Low Joo-Leng , Chua Joelle Y.H. , Kong Yap C. , Qi Ong Y. , Tan Emile , Chok Aik Y. , Seow-En Isaac , Wee Ian , Macalinao Dominique C. , Chong Dawn Q. , Chang Hong Y. , Lee Fiona , Leow Wei Q. , Murata-Hori Maki , Xiaoqian Zhang , Shumei Chia , Tan Chris S.H. , Dasgupta Ramanuj , Tan Iain B. , Tergaonkar Vinay
Published: October 2024

Validation of reporter cell lines for small molecule screens.
Supplementary Figure S5 from CD28 Costimulation Augments CAR Signaling in NK Cells via the LCK/CD3ζ/ZAP70 Signaling Axis
Authors: Acharya Sunil , Basar Rafet , Daher May , Rafei Hind , Li Ping , Uprety Nadima , Ensley Emily , Shanley Mayra , Kumar Bijender , Banerjee Pinaki P. , Melo Garcia Luciana , Lin Paul , Mohanty Vakul , Kim Kun H. , Jiang Xianli , Pan Yuchen , Li Ye , Liu Bin , Nunez Cortes Ana K. , Zhang Chenyu , Fathi Mohsen , Rezvan Ali , Montalvo Melisa J. , Cha Sophia L. , Reyes-Silva Francia , Shrestha Rejeena , Guo Xingliang , Kundu Kiran , Biederstädt Alexander , Muniz-Feliciano Luis , Deyter Gary M. , Kaplan Mecit , Jiang Xin R. , Liu Enli , Jain Antrix , Roszik Janos , Fowlkes Natalie W. , Solis Soto Luisa M. , Raso Maria G. , Khoury Joseph D. , Lin Pei , Vega Francisco , Varadarajan Navin , Chen Ken , Marin David , Shpall Elizabeth J. , Rezvani Katayoun
Published: October 2024

In a PDX mouse model of metastatic breast cancer, CAR27-28ζ NK cells lead to a reduction in tumor size and increased NK cell infiltration in the lungs.
Supplementary Table S7 from Biologic and Clinical Analysis of Childhood Gamma Delta T-ALL Identifies LMO2/STAG2 Rearrangements as Extremely High Risk
Authors: Kimura Shunsuke , Park Chun Shik , Montefiori Lindsey E. , Iacobucci Ilaria , Pölönen Petri , Gao Qingsong , Arnold Elizabeth D. , Attarbaschi Andishe , Brown Anthony , Buldini Barbara , Caldwell Kenneth J. , Chang Yunchao , Chen Chelsey , Cheng Cheng , Cheng Zhongshan , Choi John , Conter Valentino , Crews Kristine R. , de Groot-Kruseman Hester A. , Deguchi Takao , Eguchi Mariko , Muhle Hannah E. , Elitzur Sarah , Escherich Gabriele , Freeman Burgess B. , Gu Zhaohui , Han Katie , Horibe Keizo , Imamura Toshihiko , Jeha Sima , Kato Motohiro , Chiew Kean H. , Khan Tanya , Kicinski Michal , Köhrer Stefan , Kornblau Steven M. , Kotecha Rishi S. , Li Chi-Kong , Liu Yen-Chun , Locatelli Franco , Luger Selina M. , Paietta Elisabeth M. , Manabe Atsushi , Marquart Hanne V. , Masetti Riccardo , Maybury Mellissa , Mazilier Pauline , Meijerink Jules P.P. , Mitchell Sharnise , Miyamura Takako , Moore Andrew S. , Oshima Koichi , Pawinska-Wasikowska Katarzyna , Pieters Rob , Prater Mollie S. , Pruett-Miller Shondra M. , Pui Ching-Hon , Qu Chunxu , Reiterova Michaela , Reyes Noemi , Roberts Kathryn G. , Rowe Jacob M. , Sato Atsushi , Schmiegelow Kjeld , Schrappe Martin , Shen Shuhong , Skoczeń Szymon , Spinelli Orietta , Stary Jan , Svaton Michael , Takagi Masatoshi , Takita Junko , Tang Yanjing , Teachey David T. , Thomas Paul G. , Tomizawa Daisuke , Trka Jan , Varotto Elena , Vincent Tiffaney L. , Yang Jun J. , Yeoh Allen E.J. , Zhou Yinmei , Zimmermann Martin , Inaba Hiroto , Mullighan Charles G.
Published: October 2024

Detected structural variants by whole genome sequencing.
Table S5 from Iron Chelation Therapy Elicits Innate Immune Control of Metastatic Ovarian Cancer
Authors: Sandoval Tito A. , Salvagno Camilla , Chae Chang-Suk , Awasthi Deepika , Giovanelli Paolo , Marin Falco Matias , Hwang Sung-Min , Teran-Cabanillas Eli , Suominen Lasse , Yamazaki Takahiro , Kuo Hui-Hsuan , Moyer Jenna E. , Martin M. Laura , Manohar Jyothi , Kim Kihwan , Sierra Maria A. , Ramos Yusibeska , Tan Chen , Emmanuelli Alexander , Song Minkyung , Morales Diana K. , Zamarin Dmitriy , Frey Melissa K. , Cantillo Evelyn , Chapman-Davis Eloise , Holcomb Kevin , Mason Christopher E. , Galluzzi Lorenzo , Ni Zhou Zhen , Vähärautio Anna , Cloonan Suzanne M. , Cubillos-Ruiz Juan R.
Published: October 2024

Table S5 contains all the primers used in this study
Table S2 from Iron Chelation Therapy Elicits Innate Immune Control of Metastatic Ovarian Cancer
Authors: Sandoval Tito A. , Salvagno Camilla , Chae Chang-Suk , Awasthi Deepika , Giovanelli Paolo , Marin Falco Matias , Hwang Sung-Min , Teran-Cabanillas Eli , Suominen Lasse , Yamazaki Takahiro , Kuo Hui-Hsuan , Moyer Jenna E. , Martin M. Laura , Manohar Jyothi , Kim Kihwan , Sierra Maria A. , Ramos Yusibeska , Tan Chen , Emmanuelli Alexander , Song Minkyung , Morales Diana K. , Zamarin Dmitriy , Frey Melissa K. , Cantillo Evelyn , Chapman-Davis Eloise , Holcomb Kevin , Mason Christopher E. , Galluzzi Lorenzo , Ni Zhou Zhen , Vähärautio Anna , Cloonan Suzanne M. , Cubillos-Ruiz Juan R.
Published: October 2024

Table S2 contains all the information related to mass spectrometry
Supplementary Figures from Iron Chelation Therapy Elicits Innate Immune Control of Metastatic Ovarian Cancer
Authors: Sandoval Tito A. , Salvagno Camilla , Chae Chang-Suk , Awasthi Deepika , Giovanelli Paolo , Marin Falco Matias , Hwang Sung-Min , Teran-Cabanillas Eli , Suominen Lasse , Yamazaki Takahiro , Kuo Hui-Hsuan , Moyer Jenna E. , Martin M. Laura , Manohar Jyothi , Kim Kihwan , Sierra Maria A. , Ramos Yusibeska , Tan Chen , Emmanuelli Alexander , Song Minkyung , Morales Diana K. , Zamarin Dmitriy , Frey Melissa K. , Cantillo Evelyn , Chapman-Davis Eloise , Holcomb Kevin , Mason Christopher E. , Galluzzi Lorenzo , Ni Zhou Zhen , Vähärautio Anna , Cloonan Suzanne M. , Cubillos-Ruiz Juan R.
Published: October 2024

Figure S1. (a) Effect of dietary iron levels on ovarian cancer progression. Figure S2. Flow cytometry gating strategy for the analysis of peritoneal cells from mice bearing ID8Defb29/Vegfa tumors that were treated with deferiprone as single agent or in combination with cisplatin. Figure S3. (a-f) Wild-type female mice were implanted with ID8-Defb29/Vegfa tumors and treated as described in Fig 2 d. Figure S4. (a) Representative images of NKp46 staining on the entire omentum. Figure S5. (a) MTT assays for ID8-Defb29/Vegfa, PPNM, and MP cells treated with different concentrations of deferiprone for 12, 24, and 48 hours. Figure S6. (a) Human ovarian cancer cell lines were treated with deferiprone for 48 hours and expression of the indicated genes was analyzed by qRT-PCR. Colors indicate fold change (FC) upon deferiprone treatment compared with vehicle control. Figure S7. (a-b) Mitochondrial iron was traced using mito-ferrogreen in iron-overloaded ID8-Defb29/Vegfa cells that were exposed to deferiprone (100 µM) or vehicle control. Figure S8. (a) Schematic representation of treatment regimens under IFNAR1 blockade related to Fig. 6 a-c.
Supplementary Table S21 from Biologic and Clinical Analysis of Childhood Gamma Delta T-ALL Identifies LMO2/STAG2 Rearrangements as Extremely High Risk
Authors: Kimura Shunsuke , Park Chun Shik , Montefiori Lindsey E. , Iacobucci Ilaria , Pölönen Petri , Gao Qingsong , Arnold Elizabeth D. , Attarbaschi Andishe , Brown Anthony , Buldini Barbara , Caldwell Kenneth J. , Chang Yunchao , Chen Chelsey , Cheng Cheng , Cheng Zhongshan , Choi John , Conter Valentino , Crews Kristine R. , de Groot-Kruseman Hester A. , Deguchi Takao , Eguchi Mariko , Muhle Hannah E. , Elitzur Sarah , Escherich Gabriele , Freeman Burgess B. , Gu Zhaohui , Han Katie , Horibe Keizo , Imamura Toshihiko , Jeha Sima , Kato Motohiro , Chiew Kean H. , Khan Tanya , Kicinski Michal , Köhrer Stefan , Kornblau Steven M. , Kotecha Rishi S. , Li Chi-Kong , Liu Yen-Chun , Locatelli Franco , Luger Selina M. , Paietta Elisabeth M. , Manabe Atsushi , Marquart Hanne V. , Masetti Riccardo , Maybury Mellissa , Mazilier Pauline , Meijerink Jules P.P. , Mitchell Sharnise , Miyamura Takako , Moore Andrew S. , Oshima Koichi , Pawinska-Wasikowska Katarzyna , Pieters Rob , Prater Mollie S. , Pruett-Miller Shondra M. , Pui Ching-Hon , Qu Chunxu , Reiterova Michaela , Reyes Noemi , Roberts Kathryn G. , Rowe Jacob M. , Sato Atsushi , Schmiegelow Kjeld , Schrappe Martin , Shen Shuhong , Skoczeń Szymon , Spinelli Orietta , Stary Jan , Svaton Michael , Takagi Masatoshi , Takita Junko , Tang Yanjing , Teachey David T. , Thomas Paul G. , Tomizawa Daisuke , Trka Jan , Varotto Elena , Vincent Tiffaney L. , Yang Jun J. , Yeoh Allen E.J. , Zhou Yinmei , Zimmermann Martin , Inaba Hiroto , Mullighan Charles G.
Published: October 2024

Compounds used in single-dose (10uM) drug screening.
Supplementary Table S20 from Biologic and Clinical Analysis of Childhood Gamma Delta T-ALL Identifies LMO2/STAG2 Rearrangements as Extremely High Risk
Authors: Kimura Shunsuke , Park Chun Shik , Montefiori Lindsey E. , Iacobucci Ilaria , Pölönen Petri , Gao Qingsong , Arnold Elizabeth D. , Attarbaschi Andishe , Brown Anthony , Buldini Barbara , Caldwell Kenneth J. , Chang Yunchao , Chen Chelsey , Cheng Cheng , Cheng Zhongshan , Choi John , Conter Valentino , Crews Kristine R. , de Groot-Kruseman Hester A. , Deguchi Takao , Eguchi Mariko , Muhle Hannah E. , Elitzur Sarah , Escherich Gabriele , Freeman Burgess B. , Gu Zhaohui , Han Katie , Horibe Keizo , Imamura Toshihiko , Jeha Sima , Kato Motohiro , Chiew Kean H. , Khan Tanya , Kicinski Michal , Köhrer Stefan , Kornblau Steven M. , Kotecha Rishi S. , Li Chi-Kong , Liu Yen-Chun , Locatelli Franco , Luger Selina M. , Paietta Elisabeth M. , Manabe Atsushi , Marquart Hanne V. , Masetti Riccardo , Maybury Mellissa , Mazilier Pauline , Meijerink Jules P.P. , Mitchell Sharnise , Miyamura Takako , Moore Andrew S. , Oshima Koichi , Pawinska-Wasikowska Katarzyna , Pieters Rob , Prater Mollie S. , Pruett-Miller Shondra M. , Pui Ching-Hon , Qu Chunxu , Reiterova Michaela , Reyes Noemi , Roberts Kathryn G. , Rowe Jacob M. , Sato Atsushi , Schmiegelow Kjeld , Schrappe Martin , Shen Shuhong , Skoczeń Szymon , Spinelli Orietta , Stary Jan , Svaton Michael , Takagi Masatoshi , Takita Junko , Tang Yanjing , Teachey David T. , Thomas Paul G. , Tomizawa Daisuke , Trka Jan , Varotto Elena , Vincent Tiffaney L. , Yang Jun J. , Yeoh Allen E.J. , Zhou Yinmei , Zimmermann Martin , Inaba Hiroto , Mullighan Charles G.
Published: October 2024

Differentially accessible peaks in PF382-STAG2KO compared to PF382-WT (each 2 clone duplicate).
Supplementary Table S13 from Biologic and Clinical Analysis of Childhood Gamma Delta T-ALL Identifies LMO2/STAG2 Rearrangements as Extremely High Risk
Authors: Kimura Shunsuke , Park Chun Shik , Montefiori Lindsey E. , Iacobucci Ilaria , Pölönen Petri , Gao Qingsong , Arnold Elizabeth D. , Attarbaschi Andishe , Brown Anthony , Buldini Barbara , Caldwell Kenneth J. , Chang Yunchao , Chen Chelsey , Cheng Cheng , Cheng Zhongshan , Choi John , Conter Valentino , Crews Kristine R. , de Groot-Kruseman Hester A. , Deguchi Takao , Eguchi Mariko , Muhle Hannah E. , Elitzur Sarah , Escherich Gabriele , Freeman Burgess B. , Gu Zhaohui , Han Katie , Horibe Keizo , Imamura Toshihiko , Jeha Sima , Kato Motohiro , Chiew Kean H. , Khan Tanya , Kicinski Michal , Köhrer Stefan , Kornblau Steven M. , Kotecha Rishi S. , Li Chi-Kong , Liu Yen-Chun , Locatelli Franco , Luger Selina M. , Paietta Elisabeth M. , Manabe Atsushi , Marquart Hanne V. , Masetti Riccardo , Maybury Mellissa , Mazilier Pauline , Meijerink Jules P.P. , Mitchell Sharnise , Miyamura Takako , Moore Andrew S. , Oshima Koichi , Pawinska-Wasikowska Katarzyna , Pieters Rob , Prater Mollie S. , Pruett-Miller Shondra M. , Pui Ching-Hon , Qu Chunxu , Reiterova Michaela , Reyes Noemi , Roberts Kathryn G. , Rowe Jacob M. , Sato Atsushi , Schmiegelow Kjeld , Schrappe Martin , Shen Shuhong , Skoczeń Szymon , Spinelli Orietta , Stary Jan , Svaton Michael , Takagi Masatoshi , Takita Junko , Tang Yanjing , Teachey David T. , Thomas Paul G. , Tomizawa Daisuke , Trka Jan , Varotto Elena , Vincent Tiffaney L. , Yang Jun J. , Yeoh Allen E.J. , Zhou Yinmei , Zimmermann Martin , Inaba Hiroto , Mullighan Charles G.
Published: October 2024

Up-regulated pathways in STAG2/LMO2 subtype compared to other T-ALL cases analyzed by gene-set enrichment analysis (GSEA).
Supplementary Fig. S12 from Perivascular NOTCH3+ Stem Cells Drive Meningioma Tumorigenesis and Resistance to Radiotherapy
Authors: Choudhury Abrar , Cady Martha A. , Lucas Calixto-Hope G. , Najem Hinda , Phillips Joanna J. , Palikuqi Brisa , Zakimi Naomi , Joseph Tara , Birrueta Janeth O. , Chen William C. , Oberheim Bush Nancy A. , Hervey-Jumper Shawn L. , Klein Ophir D. , Toedebusch Christine M. , Horbinski Craig M. , Magill Stephen T. , Bhaduri Aparna , Perry Arie , Dickinson Peter J. , Heimberger Amy B. , Ashworth Alan , Crouch Elizabeth E. , Raleigh David R.
Published: October 2024

Supplementary Fig. 12. Single-cell RNA sequencing of human and mouse cells from meningioma xenografts. A, Single-cell counts across experimental conditions, biological replicates (samples), and UMAP clusters from CH-157MN meningioma xenograft human cells analyzed using single-cell RNA sequencing. B, Single-cell counts across experimental conditions, biological replicates, and phases of the cell cycle from meningioma xenograft human cells analyzed using single-cell RNA sequencing. Colors and rows (samples) as in A. C, Single-cell counts across experimental conditions, biological replicates, and UMAP clusters from meningioma xenograft mouse cells analyzed using single-cell RNA sequencing. D, Stacked bar plots showing the distribution of meningioma xenograft human single-cell RNA sequencing clusters across biological replicates. Colors as in A. E, Stacked bar plots showing the distribution of meningioma xenograft mouse single-cell RNA sequencing clusters across biological replicates. Colors as in C.
Supplementary Fig. S11 from Perivascular NOTCH3+ Stem Cells Drive Meningioma Tumorigenesis and Resistance to Radiotherapy
Authors: Choudhury Abrar , Cady Martha A. , Lucas Calixto-Hope G. , Najem Hinda , Phillips Joanna J. , Palikuqi Brisa , Zakimi Naomi , Joseph Tara , Birrueta Janeth O. , Chen William C. , Oberheim Bush Nancy A. , Hervey-Jumper Shawn L. , Klein Ophir D. , Toedebusch Christine M. , Horbinski Craig M. , Magill Stephen T. , Bhaduri Aparna , Perry Arie , Dickinson Peter J. , Heimberger Amy B. , Ashworth Alan , Crouch Elizabeth E. , Raleigh David R.
Published: October 2024

Supplementary Fig. 11. Ptgds is expressed throughout the meninges. Confocal microscopy of whole mount mouse convexity meningeal samples at P7, P30, or P90 after recombination of the ROSAmT/mG allele using Ptgds-Cre shows PTGDS cells are diffusely expressed throughout perivascular and non-perivascular meningeal cells. DAPI marks DNA. Representative of n=3 biological replicates per timepoint. Scale bar, 100µm.
Supplementary Table S1 from Biologic and Clinical Analysis of Childhood Gamma Delta T-ALL Identifies LMO2/STAG2 Rearrangements as Extremely High Risk
Authors: Kimura Shunsuke , Park Chun Shik , Montefiori Lindsey E. , Iacobucci Ilaria , Pölönen Petri , Gao Qingsong , Arnold Elizabeth D. , Attarbaschi Andishe , Brown Anthony , Buldini Barbara , Caldwell Kenneth J. , Chang Yunchao , Chen Chelsey , Cheng Cheng , Cheng Zhongshan , Choi John , Conter Valentino , Crews Kristine R. , de Groot-Kruseman Hester A. , Deguchi Takao , Eguchi Mariko , Muhle Hannah E. , Elitzur Sarah , Escherich Gabriele , Freeman Burgess B. , Gu Zhaohui , Han Katie , Horibe Keizo , Imamura Toshihiko , Jeha Sima , Kato Motohiro , Chiew Kean H. , Khan Tanya , Kicinski Michal , Köhrer Stefan , Kornblau Steven M. , Kotecha Rishi S. , Li Chi-Kong , Liu Yen-Chun , Locatelli Franco , Luger Selina M. , Paietta Elisabeth M. , Manabe Atsushi , Marquart Hanne V. , Masetti Riccardo , Maybury Mellissa , Mazilier Pauline , Meijerink Jules P.P. , Mitchell Sharnise , Miyamura Takako , Moore Andrew S. , Oshima Koichi , Pawinska-Wasikowska Katarzyna , Pieters Rob , Prater Mollie S. , Pruett-Miller Shondra M. , Pui Ching-Hon , Qu Chunxu , Reiterova Michaela , Reyes Noemi , Roberts Kathryn G. , Rowe Jacob M. , Sato Atsushi , Schmiegelow Kjeld , Schrappe Martin , Shen Shuhong , Skoczeń Szymon , Spinelli Orietta , Stary Jan , Svaton Michael , Takagi Masatoshi , Takita Junko , Tang Yanjing , Teachey David T. , Thomas Paul G. , Tomizawa Daisuke , Trka Jan , Varotto Elena , Vincent Tiffaney L. , Yang Jun J. , Yeoh Allen E.J. , Zhou Yinmei , Zimmermann Martin , Inaba Hiroto , Mullighan Charles G.
Published: October 2024

A multi-national consortium of γδ T-ALL study.
Supplementary Table S4 from CRISPR Dependency Screens in Primary Hematopoietic Stem Cells Identify KDM3B as a Genotype-specific Vulnerability in IDH2- and TET2-mutant Cells
Authors: Waarts Michael R. , Mowla Shoron , Boileau Meaghan , Martinez Benitez Anthony R. , Sango Junya , Bagish Maya , Fernández-Maestre Inés , Shan Yufan , Eisman Shira E. , Park Young C. , Wereski Matthew , Csete Isabelle , O’Connor Kavi , Romero-Vega Angelica C. , Miles Linde A. , Xiao Wenbin , Wu Xiaodi , Koche Richard P. , Armstrong Scott A. , Shih Alan H. , Papapetrou Eirini P. , Butler Jason M. , Cai Sheng F. , Bowman Robert L. , Levine Ross L.
Published: October 2024

HSPC RNA-seq results
Supplementary Table S3 from CRISPR Dependency Screens in Primary Hematopoietic Stem Cells Identify KDM3B as a Genotype-specific Vulnerability in IDH2- and TET2-mutant Cells
Authors: Waarts Michael R. , Mowla Shoron , Boileau Meaghan , Martinez Benitez Anthony R. , Sango Junya , Bagish Maya , Fernández-Maestre Inés , Shan Yufan , Eisman Shira E. , Park Young C. , Wereski Matthew , Csete Isabelle , O’Connor Kavi , Romero-Vega Angelica C. , Miles Linde A. , Xiao Wenbin , Wu Xiaodi , Koche Richard P. , Armstrong Scott A. , Shih Alan H. , Papapetrou Eirini P. , Butler Jason M. , Cai Sheng F. , Bowman Robert L. , Levine Ross L.
Published: October 2024

TF-1 RNA-seq results
Supplementary Figure S9 from CRISPR Dependency Screens in Primary Hematopoietic Stem Cells Identify KDM3B as a Genotype-specific Vulnerability in IDH2- and TET2-mutant Cells
Authors: Waarts Michael R. , Mowla Shoron , Boileau Meaghan , Martinez Benitez Anthony R. , Sango Junya , Bagish Maya , Fernández-Maestre Inés , Shan Yufan , Eisman Shira E. , Park Young C. , Wereski Matthew , Csete Isabelle , O’Connor Kavi , Romero-Vega Angelica C. , Miles Linde A. , Xiao Wenbin , Wu Xiaodi , Koche Richard P. , Armstrong Scott A. , Shih Alan H. , Papapetrou Eirini P. , Butler Jason M. , Cai Sheng F. , Bowman Robert L. , Levine Ross L.
Published: October 2024

Effects on TPO, GM-CSF, and ruxolitinib on Idh2R140Q HSPCs
Supplementary Figure S3 from Biologic and Clinical Analysis of Childhood Gamma Delta T-ALL Identifies LMO2/STAG2 Rearrangements as Extremely High Risk
Authors: Kimura Shunsuke , Park Chun Shik , Montefiori Lindsey E. , Iacobucci Ilaria , Pölönen Petri , Gao Qingsong , Arnold Elizabeth D. , Attarbaschi Andishe , Brown Anthony , Buldini Barbara , Caldwell Kenneth J. , Chang Yunchao , Chen Chelsey , Cheng Cheng , Cheng Zhongshan , Choi John , Conter Valentino , Crews Kristine R. , de Groot-Kruseman Hester A. , Deguchi Takao , Eguchi Mariko , Muhle Hannah E. , Elitzur Sarah , Escherich Gabriele , Freeman Burgess B. , Gu Zhaohui , Han Katie , Horibe Keizo , Imamura Toshihiko , Jeha Sima , Kato Motohiro , Chiew Kean H. , Khan Tanya , Kicinski Michal , Köhrer Stefan , Kornblau Steven M. , Kotecha Rishi S. , Li Chi-Kong , Liu Yen-Chun , Locatelli Franco , Luger Selina M. , Paietta Elisabeth M. , Manabe Atsushi , Marquart Hanne V. , Masetti Riccardo , Maybury Mellissa , Mazilier Pauline , Meijerink Jules P.P. , Mitchell Sharnise , Miyamura Takako , Moore Andrew S. , Oshima Koichi , Pawinska-Wasikowska Katarzyna , Pieters Rob , Prater Mollie S. , Pruett-Miller Shondra M. , Pui Ching-Hon , Qu Chunxu , Reiterova Michaela , Reyes Noemi , Roberts Kathryn G. , Rowe Jacob M. , Sato Atsushi , Schmiegelow Kjeld , Schrappe Martin , Shen Shuhong , Skoczeń Szymon , Spinelli Orietta , Stary Jan , Svaton Michael , Takagi Masatoshi , Takita Junko , Tang Yanjing , Teachey David T. , Thomas Paul G. , Tomizawa Daisuke , Trka Jan , Varotto Elena , Vincent Tiffaney L. , Yang Jun J. , Yeoh Allen E.J. , Zhou Yinmei , Zimmermann Martin , Inaba Hiroto , Mullighan Charles G.
Published: October 2024

The genomic feature of LMO2 γδ-like T-ALL.
Supplementary Figure S8 from CRISPR Dependency Screens in Primary Hematopoietic Stem Cells Identify KDM3B as a Genotype-specific Vulnerability in IDH2- and TET2-mutant Cells
Authors: Waarts Michael R. , Mowla Shoron , Boileau Meaghan , Martinez Benitez Anthony R. , Sango Junya , Bagish Maya , Fernández-Maestre Inés , Shan Yufan , Eisman Shira E. , Park Young C. , Wereski Matthew , Csete Isabelle , O’Connor Kavi , Romero-Vega Angelica C. , Miles Linde A. , Xiao Wenbin , Wu Xiaodi , Koche Richard P. , Armstrong Scott A. , Shih Alan H. , Papapetrou Eirini P. , Butler Jason M. , Cai Sheng F. , Bowman Robert L. , Levine Ross L.
Published: October 2024

Chromatin and transcriptional changes mediated by KDM3B
Supplementary Figure S6 from CRISPR Dependency Screens in Primary Hematopoietic Stem Cells Identify KDM3B as a Genotype-specific Vulnerability in IDH2- and TET2-mutant Cells
Authors: Waarts Michael R. , Mowla Shoron , Boileau Meaghan , Martinez Benitez Anthony R. , Sango Junya , Bagish Maya , Fernández-Maestre Inés , Shan Yufan , Eisman Shira E. , Park Young C. , Wereski Matthew , Csete Isabelle , O’Connor Kavi , Romero-Vega Angelica C. , Miles Linde A. , Xiao Wenbin , Wu Xiaodi , Koche Richard P. , Armstrong Scott A. , Shih Alan H. , Papapetrou Eirini P. , Butler Jason M. , Cai Sheng F. , Bowman Robert L. , Levine Ross L.
Published: October 2024

Validation of KDM3B and JMJD1C dependencies in human HSPCs and Tet2-/-Npm1cAFlt3ITD leukemia model
Supplementary Figure S3 from CRISPR Dependency Screens in Primary Hematopoietic Stem Cells Identify KDM3B as a Genotype-specific Vulnerability in IDH2- and TET2-mutant Cells
Authors: Waarts Michael R. , Mowla Shoron , Boileau Meaghan , Martinez Benitez Anthony R. , Sango Junya , Bagish Maya , Fernández-Maestre Inés , Shan Yufan , Eisman Shira E. , Park Young C. , Wereski Matthew , Csete Isabelle , O’Connor Kavi , Romero-Vega Angelica C. , Miles Linde A. , Xiao Wenbin , Wu Xiaodi , Koche Richard P. , Armstrong Scott A. , Shih Alan H. , Papapetrou Eirini P. , Butler Jason M. , Cai Sheng F. , Bowman Robert L. , Levine Ross L.
Published: October 2024

CRISPR screens in Dnmt3a- and Asxl1-mutant HSPCs and Jmjd1c dependency in Idh2- and Tet2-mutant HSPCs
Supplementary Figure S1 from CRISPR Dependency Screens in Primary Hematopoietic Stem Cells Identify KDM3B as a Genotype-specific Vulnerability in IDH2- and TET2-mutant Cells
Authors: Waarts Michael R. , Mowla Shoron , Boileau Meaghan , Martinez Benitez Anthony R. , Sango Junya , Bagish Maya , Fernández-Maestre Inés , Shan Yufan , Eisman Shira E. , Park Young C. , Wereski Matthew , Csete Isabelle , O’Connor Kavi , Romero-Vega Angelica C. , Miles Linde A. , Xiao Wenbin , Wu Xiaodi , Koche Richard P. , Armstrong Scott A. , Shih Alan H. , Papapetrou Eirini P. , Butler Jason M. , Cai Sheng F. , Bowman Robert L. , Levine Ross L.
Published: October 2024

Ex vivo characterization of BMEC/HSPC co-cultures
Data from Clonal Lineage Tracing with Somatic Delivery of Recordable Barcodes Reveals Migration Histories of Metastatic Prostate Cancer
Authors: Serio Ryan N. , Scheben Armin , Lu Billy , Gargiulo Domenic V. , Patruno Lucrezia , Buckholtz Caroline L. , Chaffee Ryan J. , Jibilian Megan C. , Persaud Steven G. , Staklinski Stephen J. , Hassett Rebecca , Brault Lise M. , Ramazzotti Daniele , Barbieri Christopher E. , Siepel Adam C. , Nowak Dawid G.
Published: October 2024

Abstract
The patterns by which primary tumors spread to metastatic sites remain poorly understood. Here, we define patterns of metastatic seeding in prostate cancer using a novel injection-based mouse model—EvoCaP (Evolution in Cancer of the Prostate), featuring aggressive metastatic cancer to bone, liver, lungs, and lymph nodes. To define migration histories between primary and metastatic sites, we used our EvoTraceR pipeline to track distinct tumor clones containing recordable barcodes. We detected widespread intratumoral heterogeneity from the primary tumor in metastatic seeding, with few clonal populations instigating most migration. Metastasis-to-metastasis seeding was uncommon, as most cells remained confined within the tissue. Migration patterns in our model were congruent with human prostate cancer seeding topologies. Our findings support the view of metastatic prostate cancer as a systemic disease driven by waves of aggressive clones expanding their niche, infrequently overcoming constraints that otherwise keep them confined in the primary or metastatic site.

Significance: Defining the kinetics of prostate cancer metastasis is critical for developing novel therapeutic strategies. This study uses CRISPR/Cas9-based barcoding technology to accurately define tumor clonal patterns and routes of migration in a novel somatically engineered mouse model (EvoCaP) that recapitulates human prostate cancer using an in-house developed analytical pipeline (EvoTraceR).
Data from The History of Chromosomal Instability in Genome-Doubled Tumors
Authors: Baker Toby M. , Lai Siqi , Lynch Andrew R. , Lesluyes Tom , Yan Haixi , Ogilvie Huw A. , Verfaillie Annelien , Dentro Stefan , Bowes Amy L. , Pillay Nischalan , Flanagan Adrienne M. , Swanton Charles , Spellman Paul T. , Tarabichi Maxime , Van Loo Peter
Published: October 2024

Abstract
Tumors frequently display high chromosomal instability and contain multiple copies of genomic regions. Here, we describe Gain Route Identification and Timing In Cancer (GRITIC), a generic method for timing genomic gains leading to complex copy number states, using single-sample bulk whole-genome sequencing data. By applying GRITIC to 6,091 tumors, we found that non-parsimonious evolution is frequent in the formation of complex copy number states in genome-doubled tumors. We measured chromosomal instability before and after genome duplication in human tumors and found that late genome doubling was followed by an increase in the rate of copy number gain. Copy number gains often accumulate as punctuated bursts, commonly after genome doubling. We infer that genome duplications typically affect the landscape of copy number losses, while only minimally impacting copy number gains. In summary, GRITIC is a novel copy number gain timing framework that permits the analysis of copy number evolution in chromosomally unstable tumors.

Significance: Complex genomic gains are associated with whole-genome duplications, which are frequent across tumors, span a large fraction of their genomes, and are linked to poorer outcomes. GRITIC infers when these gains occur during tumor development, which will help to identify the genetic events that drive tumor evolution.

See related commentary by Taylor, p. 1766