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65 citation(s) found for "Wu, Jingjing".

Design of a 3D patient‐specific collision avoidance virtual framework for half‐gantry proton therapy system
Dougherty, Jingjing M. , Whitaker, Thomas J. , Mundy, Daniel W. , Tryggestad, E., Beltran, Chris , Tryggestad, Erik J, Beltran, Chris J., Beltran, Chris J

Journal of Applied Clinical Medical Physics | December 10, 2021 | Volume: 23 | Issue: 2 | Pages: No page available

10.1002/acm2.13496 | PMID 34890094 Get It

AbstractIntroductionThis study presents a comprehensive collision avoidance framework based on three‐dimension (3D) computer‐aided design (CAD) modeling, a graphical user interface (GUI) as peripheral to the radiation treatment planning (RTP) environment, and patient‐specific plan parameters for intensity‐modulated proton therapy (IMPT).MethodsA stand‐alone software application was developed leveraging the Varian scripting application programming interface (API) for RTP database object accessibility. The Collision Avoider software models the Hitachi ProBeat‐V half gantry design and the Kuka robotic couch with triangle mesh structures. Patient‐specific plan parameters are displayed in the collision avoidance software for potential proximity evaluation. The external surfaces of the patients and the immobilization devices are contoured based on computed tomography (CT) images. A “table junction‐to‐CT‐origin” (JCT) measurement is made for every patient at the time of CT simulation to accurately provide reference location of the patient contours to the treatment couch. Collision evaluations were performed virtually with the program during treatment planning to prevent four major types of collisional events: collisions between the gantry head and the treatment couch, gantry head and the patient's body, gantry head and the robotic arm, and collisions between the gantry head and the immobilization devices.ResultsThe Collision Avoider software was able to accurately model the proton treatment delivery system and the robotic couch position. Commonly employed clinical beam configuration and JCT values were investigated. Brain and head and neck patients require more complex gantry and patient positioning system configurations. Physical measurements were performed to validate 3D CAD model geometry. Twelve clinical proton treatment plans were used to validate the accuracy of the software. The software can predict all four types of collisional events in our clinic since its full implementation in 2020.ConclusionA highly efficient patient‐specific collision prevention program for scanning proton therapy has been successfully implemented. The graphical program has provided accurate collision detection since its inception at our institution.
Integrating Genome and Methylome Data to Identify Candidate DNA Methylation Biomarkers for Pancreatic Cancer Risk
Zhu, Jingjing , Yang, Yaohua , Kisiel, John B. , Michaud, Dominique S. , Shu, Xiao-Ou , Liu, Duo , Li, Bingshan , Tao, Ran , Wu, Lang , Mahoney, Douglas W. , Shu, Xiao-Ou , Cai, Qiuyin , Zheng, Wei , Kisiel, John B , Michaud, Dominique S , Guo, Xingyi , Taylor, William R. , Shu, Xiao‐Ou , Cai, Qiuyin , Zheng, Wei , Long, Jirong , Yang, Yaohua

Cancer Epidemiology, Biomarkers & Prevention | September 9, 2021 | Volume: 30 | Issue: 11 | Pages: 2079-2087

10.1158/1055-9965.epi-21-0400 | PMID 34497089 Get It

AbstractBackground:The role of methylation in pancreatic cancer risk remains unclear. We integrated genome and methylome data to identify CpG sites (CpG) with the genetically predicted methylation to be associated with pancreatic cancer risk. We also studied gene expression to understand the identified associations.Methods:Using genetic data and white blood cell methylation data from 1,595 subjects of European descent, we built genetic models to predict DNA methylation levels. After internal and external validation, we applied prediction models with satisfactory performance to the genetic data of 8,280 pancreatic cancer cases and 6,728 controls of European ancestry to investigate the associations of predicted methylation with pancreatic cancer risk. For associated CpGs, we compared their measured levels in pancreatic tumor versus benign tissue.Results:We identified 45 CpGs at nine loci showing an association with pancreatic cancer risk, including 15 CpGs showing an association independent from identified risk variants. We observed significant correlations between predicted methylation of 16 of the 45 CpGs and predicted expression of eight adjacent genes, of which six genes showed associations with pancreatic cancer risk. Of the 45 CpGs, we were able to compare measured methylation of 16 in pancreatic tumor versus benign pancreatic tissue. Of them, six showed differentiated methylation.Conclusions:We identified methylation biomarker candidates associated with pancreatic cancer using genetic instruments and added additional insights into the role of methylation in regulating gene expression in pancreatic cancer development.Impact:A comprehensive study using genetic instruments identifies 45 CpG sites at nine genomic loci for pancreatic cancer risk.
Best Practices for Spatial Profiling for Breast Cancer Research with the GeoMx® Digital Spatial Profiler
Bergholtz, Helga , Carter, Jodi M. , Cesano, Alessandra, Cheang, Maggie C.U. , Church, S. , Divakar, Prajan , Fuhrman, Christopher A. , Goel, Shom , Gong, Jingjing , Guerriero, Jennifer L. , Hoang, Margaret L. , Hwang, E. Shelley , Kuasne, Hellen, Lee, Jinho , Liang, Yan , Perez, Jessica, Prat, Aleix , Pusztai, Lajos , Reeves, Jason , Riazalhosseini, Yasser , Richer, Jennifer K. , Şahin, Özgür , Sato, Hiromi , Sørlie, Thérese , Swarbrick, Alexander , Thompson, E. Aubrey , Tolaney, Sara M. , Warren, Sarah H. , Cheang, Maggie Chon U , Church, Sarah E , Prat, Aleix , Pusztai, Lajos , Sahin, Özgür , Sørlie, Therese , Liang, Yan , Carter, Jodi , Mittendorf, EA , Schlam, Ilana Miriam , Stover, Daniel G. , Swain, Sandra M. , Warren, Sarah

Cancers | September 6, 2021 | Volume: 13 | Issue: 17 | Pages: 4456

10.3390/cancers13174456 | PMID 34503266 Get It

Breast cancer is a heterogenous disease with variability in tumor cells and in the surrounding tumor microenvironment (TME). Understanding the molecular diversity in breast cancer is critical for improving prediction of therapeutic response and prognostication. High-plex spatial profiling of tumors enables characterization of heterogeneity in the breast TME, which can holistically illuminate the biology of tumor growth, dissemination and, ultimately, response to therapy. The GeoMx Digital Spatial Profiler (DSP) enables researchers to spatially resolve and quantify proteins and RNA transcripts from tissue sections. The platform is compatible with both formalin-fixed paraffin-embedded and frozen tissues. RNA profiling was developed at the whole transcriptome level for human and mouse samples and protein profiling of 100-plex for human samples. Tissue can be optically segmented for analysis of regions of interest or cell populations to study biology-directed tissue characterization. The GeoMx Breast Cancer Consortium (GBCC) is composed of breast cancer researchers who are developing innovative approaches for spatial profiling to accelerate biomarker discovery. Here, the GBCC presents best practices for GeoMx profiling to promote the collection of high-quality data, optimization of data analysis and integration of datasets to advance collaboration and meta-analyses. Although the capabilities of the platform are presented in the context of breast cancer research, they can be generalized to a variety of other tumor types that are characterized by high heterogeneity.
Abstract P108: Association of Forced Expiratory Volume (1 Second) with Incidence of Atrial Fibrillation: The Atherosclerosis Risk in Communities (ARIC) Study
Agarwal, Sunil , Enright, Paul, Loehr, Laura R, McNeill, Anne Marie, Poole, Charles, Heiss, Gerardo , Li, Jingjing , Alonso, Álvaro , Blecker, Saul , Chamberlain, Alanna M. , Loehr, Laura R, Soliman, Elsayed Z.

Circulation | July 3, 2021 | Volume: 125 | Issue: suppl_10 | Pages: No page available

10.1161/circ.125.suppl_10.ap108 Get It

Objective: To investigate the association between low forced expiratory volume in 1 second (FEV 1 ) and incident atrial fibrillation (AF) in a population-based cohort. Background: Impaired FEV 1 , a complex measure indicating genetic, developmental, obstructive and restrictive airway disease, musculoskeletal function, and motivation, has been inconsistently associated with an increased risk of cardiovascular disease mortality. Also, extant reports do not provide separate estimates for African Americans, who surprisingly have lower AF incidence than Caucasians. Methods: We examined 15,282 middle-aged African Americans (26%) and Caucasians, men (45%) and women from four U.S. communities enrolled in the Atherosclerosis Risk in Communities (ARIC) cohort study. Lung volumes by standardized spirometry and information on covariates were collected on these participants at the baseline visit (1987-1989). Prevalent AF cases were excluded by 12-lead ECG at baseline. Incident AF was defined as the first event identified from the following: ICD codes for AF from hospital discharge records or death certificates, or ECGs performed during three triennial follow-up visits. Results: Over an average follow-up of 17.5 years, a total of 1,733 (11%) participants developed new-onset AF. The rate of incident AF increased monotonically and inversely by tertiles of FEV 1 in each of the 4 gender-race strata. The unadjusted average incidence rates of AF per 100 person years of follow up by tertiles of FEV 1 (from lowest to highest tertile) were 13.6, 8.3, and 5.7 for white men; 8.7, 4.5, and 3.4 for white women; 8.2, 5.5, and 3.8 for black men; 6.9, 4.1, and 2.4 for black women. After multivariable adjustment for traditional cardiovascular disease risk factors and height, hazard ratios (95% CI) of AF comparing the lowest with the highest tertile of FEV 1 were 1.44 (1.16,1.78) among white men, 1.45 (1.12, 1.87) among white women, 1.81 (1.09, 3.02) among black men, and 1.84(1.20, 2.82) among black women. The trend estimate for per 1 Standard-Deviation lower FEV 1 for the corresponding race and gender groups were 1.21 (1.12, 1.32), 1.38 (1.25, 1.54), 1.45 (1.18, 1.76), and 1.35 (1.12, 1.63), respectively. The above associations were observed across all smoking status categories (current, former, and never). The association between low lung function and incidence of AF was similarly unchanged after exclusion of participants with heart failure (n = 689) or CHD (n = 558) at baseline. The hazard of AF was about 50% higher among those with FEV1/FVC ratio below 0.7. Conclusions: In this large population-based cohort study with a long term follow-up, reduced FEV 1 is strongly associated with a higher AF risk, independent of race, gender, smoking, and several other CVD risk factors. These findings suggest the need for research on mechanisms underlying the observed association to seek broader opportunities for prevention of AF.
Abstract LB058: Performance of a cell-free DNA-based multi-cancer detection test as a tool for diagnostic resolution of symptomatic cancers
Liu, Minetta C. , Seiden, Michael V., Thiel, David D. , Richards, Donald, Becerra, Carlos , Chen, Xiaoji , Wu, Tony, Zhang, Quan , Gao, Jingjing , Jamshidi, Arash , Fung, Eric T. , Bryce, Alan H. , Kurtzman, Kathryn N. , Wu, Tony T., Zhang, Nan , Hubbell, Earl , Klein, Eric A.

Cancer Research | July 1, 2021 | Volume: 81 | Issue: 13_Supplement | Pages: LB058-LB058

10.1158/1538-7445.am2021-lb058 Get It

Abstract Introduction: A test that detects cancer signal across multiple cancer types and predicts signal (tissue) origin (SO) could aid in more efficient diagnostic workup and shorten time to cancer diagnosis in individuals with signs and symptoms.Methods: The Circulating Cell-free Genome Atlas (CCGA; NCT02889978) study is a prospective, longitudinal, multicenter, case-control study to develop and validate a multi-cancer detection test. The 2nd CCGA substudy utilized a targeted methylation-based cell-free DNA assay and machine learning algorithm and included assessment of test performance (sensitivity and SO prediction accuracy) in a subgroup of participants with clinically presenting cancers (CPCs) that were undiagnosed prior to blood draw. Specificity was assessed in the noncancer group and subgroups with confounding (nonmalignant) conditions (CCs; eg, cirrhosis) and noncancer participants enrolled in hematology clinics (HCs).Results: Specificity was 99.5% (95% confidence interval: 98.2-99.9%; 396/398), 93.8% (71.7-99.7%; 15/16), and 99.3% (96.0-100.0%; 136/137) for the noncancer group, CCs subgroup, and HCs subgroup, respectively. Overall sensitivity among those with CPCs was 66.4% (62.2-70.3%; 344/518). Sensitivity of cancer signal detection increased with increasing clinical stage (Table). SO prediction accuracy was 91.7% (88.3-94.3%; 300/327) among CPC participants with cancers detected, excluding those with multiple or unknown primaries. The test demonstrated prognostic value as detected cancer participants had worse survival probability than those not detected. Conclusions: This multi-cancer detection test detected cancer signals and predicted SO in individuals with CPCs with high specificity. These findings support further clinical development of this multi-cancer detection test that could accelerate the diagnostic resolution of symptomatic cancers. Table. Sensitivity by Clinical Stage Across Cancer Type in Clinically Presenting CancersClinical StagePositive Test/Total Cancer; Sensitivity (95% CI)All*344/518; 66.4% (62.2-70.3%)I33/122; 27.0% (20.0-35.5%)II60/102; 58.8% (49.1-67.9%)III103/121; 85.1% (77.7-90.4%)IV136/147; 92.5% (87.1-95.8%)Not expected to be staged9/21; 42.9% (24.5-63.5%)Non-informative2/4; 50.0% (15.0-85.0%)CI, confidence interval.*One participant who had a positive test result had multiple primaries with clinical stage I and not-expected-to-be-staged. Citation Format: Alan H. Bryce, Minetta C. Liu, Michael V. Seiden, David D. Thiel, Donald Richards, Carlos Becerra, Kathryn N. Kurtzman, Xiaoji Chen, Tony Wu, Quan Zhang, Jingjing Gao, Nan Zhang, Earl Hubbell, Arash Jamshidi, Eric T. Fung, Eric A. Klein. Performance of a cell-free DNA-based multi-cancer detection test as a tool for diagnostic resolution of symptomatic cancers [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr LB058.
Abstract LB013: Clinical validation of a targeted methylation-based multi-cancer early detection test
Richards, Donald , Cohn, Allen Lee, Tummala, Mohan K., Lapham, Rosanna L., Cosgrove, David , Chung, Gina G., Clement, Jessica, Gao, Jingjing , Hunkapiller, Nathan, Jamshidi, Arash , Seiden, Michael V., Liu, Minetta C. , Klein, Eric A. , Kurtzman, Kathryn N. , Swanton, Charles

Cancer Research | July 1, 2021 | Volume: 81 | Issue: 13_Supplement | Pages: LB013-LB013

10.1158/1538-7445.am2021-lb013 Get It

Abstract Introduction: A multi-cancer early detection (MCED) test as a complement to existing screening tests could increase the number of cancer cases detected in a population, potentially improving patient outcomes and survival as well as decreasing harmful and aggressive treatments. The Circulating Cell-free Genome Atlas study (CCGA; NCT02889978) was designed to develop and validate a blood-based MCED test analyzing plasma cell-free DNA (cfDNA) to detect cancer signals across multiple cancer types and simultaneously predict their signal origin. Here, the results of the third and final pre-specified CCGA validation sub-study for a refined MCED test in a large cohort in preparation for clinical use are reported. Methods: CCGA is a prospective, multicenter, case-control, observational study with longitudinal follow-up (overall population N=15,254). In this sub-study (n=5309), key primary objectives were to evaluate test performance for cancer signal detection (specificity, overall sensitivity, sensitivity by clinical stage) and signal origin prediction (accuracy). cfDNA from evaluable samples was analyzed using a targeted methylation bisulfite sequencing assay and a machine learning algorithm. The classifier was trained to target a specificity of 99.4% and locked before analysis of the independent validation set. Overall, 4077 participants comprised the independent validation set with confirmed status (cancer: n=2823; non-cancer: n=1254 with non-cancer status confirmed at year-one follow-up). MCED test results are reported for this confirmed status set. Results: Mean (SD) age in the cancer and non-cancer groups was 62.6 (11.76) and 56.2 (12.63) years, respectively. Specificity for cancer signal detection was 99.5% (1248/1254; 95% confidence interval: 99.0-99.8%). Overall sensitivity for cancer signal detection was 51.5% (1453/2823; 49.6-53.3%); sensitivity increased with stage (Stage I: 16.8% [14.5-19.5%], Stage II: 40.4% [36.8-44.1%], Stage III: 77.0% [73.4-80.3%], Stage IV: 90.1% [87.5-92.2%]). Stage I-III sensitivity was 67.6% (593/877; 64.4-70.6%) in a pre-specified set of 12 high-signal cancers accounting for ~63% of annual US cancer deaths [1] and was 40.7% (863/2118; 38.7-42.9%) in all cancers. Cancer signals were detected across >50 cancer types [2]. Overall accuracy of signal origin prediction in true positives was 88.7% (87.0-90.2%). Conclusions: In this pre-specified, large-scale, clinical validation sub-study of CCGA, the MCED test detected cancer signals across >50 cancer types, which is critical to maximize the number of cancer cases detected in a population. This MCED test performed with high specificity and high accuracy of signal origin prediction. These data lay the foundation for population-scale clinical implementation of this test. 1.US Mortality Data 1969-2016 (www.seer.cancer.gov); based on 2015-2016. 2.Amin et al. CA Cancer J Clin. 2017;67:93e99. Citation Format: Eric A. Klein, Donald Richards, Allen Cohn, Mohan Tummala, Rosanna Lapham, David Cosgrove, Gina Chung, Jessica Clement, Jingjing Gao, Nathan Hunkapiller, Arash Jamshidi, Kathryn Kurtzman, Michael V. Seiden, Charles Swanton, Minetta C. Liu. Clinical validation of a targeted methylation-based multi-cancer early detection test [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr LB013.
Functional avoidance‐based intensity modulated proton therapy with 4DCT derived ventilation imaging for lung cancer
Dougherty, Jingjing M. , Castillo, Edward , Faught, Austin M. , Pepin, M. , Beltran, Chris , Guerrero, Thomas , Grills, Inga S., Vinogradskiy, Yevgeniy , Pepin, Mark, Beltran, Chris J., Beltran, Chris J , Pepin, Mark D , Castillo, Richard , Park, Sean S.

Journal of Applied Clinical Medical Physics | June 23, 2021 | Volume: 22 | Issue: 7 | Pages: 276-285

10.1002/acm2.13323 | PMID 34159715 Get It

Abstract The primary objective is to evaluate the potential dosimetric gains of performing functional avoidance‐based proton treatment planning using 4DCT derived ventilation imaging. 4DCT data of 31 patients from a prospective functional avoidance clinical trial were evaluated with intensity modulated proton therapy (IMPT) plans and compared with clinical volumetric modulated arc therapy (VMAT) plans. Dosimetric parameters were compared between standard and functional plans with IMPT and VMAT with one‐way analysis of variance and post hoc paired student t‐test. Normal Tissue Complication Probability (NTCP) models were employed to estimate the risk of two toxicity endpoints for healthy lung tissues. Dose degradation due to proton motion interplay effect was evaluated. Functional IMPT plans led to significant dose reduction to functional lung structures when compared with functional VMAT without significant dose increase to Organ at Risk (OAR) structures. When interplay effect is considered, no significant dose degradation was observed for the OARs or the clinical target volume (CTV) volumes for functional IMPT. Using fV20 as the dose metric and Grade 2+ pneumonitis as toxicity endpoint, there is a mean 5.7% reduction in Grade 2+ RP with the functional IMPT and as high as 26% in reduction for individual patient when compared to the standard IMPT planning. Functional IMPT was able to spare healthy lung tissue to avoid excess dose to normal structures while maintaining satisfying target coverage. NTCP calculation also shows that the risk of pulmonary complications can be further reduced with functional based IMPT.
Detection of cancer signal for over 50 AJCC cancer types with a multi-cancer early-detection test.
Yimer, Habte, Tummala, Mohan K., Shao, Spencer H. , Chung, Gina G., Gao, Jingjing , Venn, Oliver, Clement, Jessica, Tang, W.H. Wilson , Couch, Fergus J. , Kurtzman, Kathryn N. , Swanton, Charles

Journal of Clinical Oncology | June 2, 2021 | Volume: 39 | Issue: 15_suppl | Pages: 3072-3072

10.1200/jco.2021.39.15_suppl.3072 Get It

3072 Background: The Circulating Cell-free Genome Atlas study (CCGA; NCT02889978) previously demonstrated that a blood-based multi-cancer early detection (MCED) test utilizing cell-free DNA (cfDNA) sequencing in combination with machine learning could detect cancer signals across multiple cancer types and predict cancer signal origin. Cancer classes were defined within the CCGA study for sensitivity reporting. Separately, cancer types defined by the American Joint Committee on Cancer (AJCC) criteria, which outline unique staging requirements and reflect a distinct combination of anatomic site, histology and other biologic features, were assigned to each cancer participant using the same source data for primary site of origin and histologic type. Here, we report CCGA ‘cancer class’ designation and AJCC ‘cancer type’ assignment within the third and final CCGA3 validation substudy to better characterize the diversity of tumors across which a cancer signal could be detected with the MCED test that is nearing clinical availability. Methods: CCGA is a prospective, multicenter, case-control, observational study with longitudinal follow-up (overall population N = 15,254). Plasma cfDNA from evaluable samples was analyzed using a targeted methylation bisulfite sequencing assay and a machine learning approach, and test performance, including sensitivity, was assessed. For sensitivity reporting, CCGA cancer classes were assigned to cancer participants using a combination of the type of primary cancer reported by the site and tumor characteristics abstracted from the site pathology reports by GRAIL pathologists. Each cancer participant also was separately assigned an AJCC cancer type based on the same source data using AJCC staging manual (8th edition) classifications. Results: A total of 4077 participants comprised the independent validation set with confirmed status (cancer: n = 2823; non-cancer: n = 1254 with non-cancer status confirmed at year-one follow-up). Sensitivity was reported for 24 cancer classes (sample sizes ranged from 10 to 524 participants), as well as an “other” cancer class (59 participants). According to AJCC classification, the MCED test was found to detect cancer signals across 50+ AJCC cancer types, including some types not present in the training set; some cancer types had limited representation. Conclusions: This MCED test that is nearing clinical availability and was evaluated in the third CCGA substudy detected cancer signals across 50+ AJCC cancer types. Reporting CCGA cancer classes and AJCC cancer types demonstrates the ability of the MCED test to detect cancer signals across a set of diverse cancer types representing a wide range of biologic characteristics, including cancer types that the classifier has not been trained on, and supports its use on a population-wide scale. Clinical trial information: NCT02889978.
Performance of a targeted methylation-based multi-cancer early detection test by race/ethnicity.
Yimer, Habte, Tummala, Mohan K., Shao, Spencer H. , Chung, Gina G., Clement, Jessica, Gao, Jingjing , Roberts, Lewis R. , Roberts, Lewis R , Tang, W.H. Wilson , Hubbell, Earl , Kurtzman, Kathryn N. , Swanton, Charles

Journal of Clinical Oncology | June 2, 2021 | Volume: 39 | Issue: 15_suppl | Pages: 3071-3071

10.1200/jco.2021.39.15_suppl.3071 Get It

3071 Background: Disparities in cancer screening and outcomes based on factors such as gender, socioeconomic status, and race/ethnicity are well documented.1 The Circulating Cell-free Genome Atlas study (CCGA; NCT02889978) was designed to develop and validate a blood-based multi-cancer early detection (MCED) test analyzing plasma cell-free DNA (cfDNA) to detect cancer signals across multiple cancer types and simultaneously predict cancer signal origin. Findings stratified by race/ethnicity from the third and final CCGA validation sub-study are reported. Methods: CCGA is a prospective, multicenter, case-control, observational study with longitudinal follow-up (overall N = 15,254). In this pre-specified exploratory analysis from the third substudy, key objectives were to evaluate test performance for cancer signal detection (specificity, overall sensitivity, and sensitivity by clinical stage) among racial/ethnic groups. Plasma cfDNA from evaluable samples was analyzed using a targeted methylation bisulfite sequencing assay and a machine learning approach. Overall, 4077 participants comprised the independent validation set with confirmed status (cancer: n = 2823; non-cancer: n = 1254). The groups stratified by race/ethnicity were White Non-Hispanic, Black Non-Hispanic, Other Non-Hispanic (including but not limited to Asian, Native Hawaiian, Pacific Islander, American Indian, Alaska Native), Hispanic (all races), and Other/unknown. The study was not powered to detect statistical differences between groups. Results: Cancer and non-cancer groups were predominantly White (2316/2823, 82.0% and 996/1254, 79.4%, respectively). Across racial/ethnic groups, specificity for cancer signal detection was 99.6% (White Non-Hispanic: 992/996, 95% confidence interval [99.0-99.8%]), 100.0% (Black Non-Hispanic: 85/85 [95.7-100.0%]), 100.0% (Other Non-Hispanic: 33/33 [89.6-100.0%]), 98.1% (Hispanic: 101/103 [93.2-99.5%]), and 100% (Other/unknown: 37/37 [90.6-100.0%]). Despite slight differences in cancer type and staging across racial/ethnic groups, overall sensitivity for cancer signal detection among groups ranged from 43.9% to 63.0% (White Non-Hispanic: 50.5%, 1169/2316 [48.4-52.5%], Black Non-Hispanic: 53.9%, 104/193 [46.8-60.8%], Other Non-Hispanic: 43.9%, 25/57 [31.8-56.7%], Hispanic: 63.0%, 121/192 [56.0-69.5%], and Other/unknown: 52.3%, 34/65 [40.4-64.0%]). For all racial/ethnic groups, sensitivity generally increased with clinical stage (with limited exceptions at Stage IV in some groups with small sample sizes). Conclusions: The MCED test demonstrated consistent specificity and sensitivity across racial/ethnic groups, though results are limited by sample size for some groups. These findings indicate broad applicability and support clinical implementation of this MCED test on a population scale. 1. Zavela et al. Brit J Cancer 2021. Clinical trial information: NCT02889978.
Guidelines for the use and interpretation of assays for monitoring autophagy (4th edition) 1
Klionsky, Daniel J., Abdel‐Aziz, Amal Kamal , Abdellatif, Mahmoud , Abdoli, Asghar , Abel, Steffen , Abeliovich, Hagai , Abildgaard, Marie H. , Abudu, Yakubu Princely , Acevedo‐Arozena, Abraham , Adamopoulos, Iannis E. , Adeli, Khosrow , Adolph, Timon E. , Adornetto, Annagrazia , Aflaki, Elma, Agam, Galila , Aggarwal, Bharat B. , Agnello, Maria, Agostinis, Patrizia , Agrewala, Javed N. , Agrotis, Alexander , Aguilar, Patricia V., Ahmad, S. Tariq, Ahumada-Castro, Ulises , Aits, Sonja , Aizawa, Shu, Akkoç, Yunus , Akoumianaki, Tonia, Akpinar, Hafize Aysin , Al‐Abd, Ahmed M. , Al-Akra, Lina, Gharaibeh, Abeer , Alaoui‐Jamali, Moulay A. , Alberti, Simon , Alessandri, Cristiano , Alonso, Alicia , Altan‐Bonnet, Nihal , Álvarez, Élida, Alves, Sara , Costa, Cristine Alvès da , Alzaharna, Mazen M. , Amadio, Marialaura , Amantini, Consuelo , Amaral, Cristina , Ambrosio, Susanna , Amer, Amal O. , Ammanathan, Veena , An, Zhenyi, Andrabi, Shaida A. , Andres, Allen M. , Ann, David K. , Anozie, Uche C. , Ansari, Mohammad Y. , Antas, Pedro , Antebi, Adam , Antón, Zuriñe , Anwar, Tahira , Apétoh, Lionel , Araki, Toshiyuki , Araki, Yasuhiro , Araya, Jun , Arévalo, María‐Ángeles , Argüelles, Sandro , Arias, Esperanza , Arikkath, Jyothi , Ariosa, Aileen, Aroca, Ángeles , Arroyo, Daniela S., Arsov, Ivica, Artero, Rubén , Asaro, Dalia Maria Lucia, Ashur‐Fabian, Osnat , Atanasov, Atanas G. , Au, Alicia K. , Auberger, Patrick , Auner, Holger W. , Aurelian, Laure , Avagliano, Laura , Ávalos, Yenniffer , Aveleira, Célia A. , Aydın, Yücel , Ayyadevara, Srinivas , Azzopardi, Maria , Baba, Misuzu, Backer, Jonathan , Bae, Soo Han , Baehrecke, Eric H. , Bagetta, Giacinto , Bagniewska‐Zadworna, Agnieszka , Bai, Hua , Bai, Xiyuan , Bairagi, Nandadulal , Baksi, Shounak , Balbi, Teresa , Ballester, María , Balazadeh, Salma , Balzan, Rena , Bandopadhyay, Rina , Banerjee, Sulagna , Bánréti, Ágnes , Baracca, Alessandra , Barbati, Cristiana , Bargiela, Ariadna , Barilà, Daniela , Barlow, Peter G. , Barmada, Sami J. , Barreiro, Esther , Bártek, Jiří , Bartel, Bonnie , Bartolomé, Alberto , Barve, Gaurav , Bassham, Diane C. , Baulieu, E.E. , Baumgarner, Bradley L. , Bayry, Jagadeesh , Beale, Rupert , Beau, Isabelle , Beaumatin, Florian , Bechara, Luiz Roberto Grassmann , Beck, George R. , Beers, Michael F. , Begun, Jakob , Behrends, Christian , Bejarano, Eloy , Bel, Shai , Belaïd, Amine , Belgareh‐Touzé, Naïma, Bellarosa, Cristina , Belleudi, Francesca , Belló-Pérez, Melissa , Beltran, Jackeline Soares de Oliveira , Beltran, Sebastián, Benbrook, Doris M. , Bendorius, Mykolas , Benítez, Bruno A. , Benito‐Cuesta, Irene , Bensalem, Julien , Berchtold, Martin W. , Berezowska, Sabina , Bergamaschi, Daniele , Berliocchi, Laura , Berlioz‐Torrent, Clarisse , Bernard, Amélie , Besirli, Cagri G. , Besteiro, Sébastien , Betin, Virginie M.S., Beyaert, Rudi , Bezbradica, Jelena S. , Bhaskar, Kiran , Bhatia‐Kiššová, Ingrid, Bhattacharya, Sujoy , Bhuiyan, Md. Shenuarin , Bi, Xiaolin , Biden, Trevor J. , Bijian, Krikor , Billes, Viktor , Binart, Nadine , Bincoletto, Cláudia , Blanco, Gonzalo , Blas‐García, Ana , Błasiak, Janusz , Blomgran, Robert , Blum, Janice S. , Boada-Romero, Emilio, Boban, Mirta , Boeuf, Philippe , Boland, Barry , Bomont, Pascale , Bonaldo, Paolo , Bonam, Srinivasa Reddy , Bonfili, Laura , Bootman, Martin D. , Bordi, Matteo , Borner, Christoph , Bornhäuser, Beat , Bose, Santanu , Botas, Juan , Boulanger, Chantal M. , Bourgeois, Benjamin , Bourke, Nollaig M. , Bousquet, Guilhem , Boya, Patricia , Bozhkov, Peter V. , Bozi, Luiz H. M. , Bozkurt, Tolga O. , Pedro, José Manuel Bravo‐San , Brest, Patrick , Bringer, Marie-Agnès , Briones‐Herrera, Alfredo , Broaddus, V. Courtney, Brodersen, Peter , Brodsky, Jeffrey L. , Bronson, Paola G. , Bronstein, Jeff M. , Brown, Rhoderick E. , Brum, Patrı́cia C. , Bruno, Daniele , Bryson‐Richardson, Robert J. , Bucci, Cecilia , Buchrieser, Carmen , Bueno, Marta , Buchan, J. Ross , Buckingham, Erin M., Budak, Hikmet , Budini, Mauricio , Bultynck, Geert , Burada, Florin , Burgoyne, Joseph R. , Burón, María I. , Bustos, Victor , Büttner, Sabrina , Byrd, Aaron , Cabas, Isabel , Cabrera, Sandra , Cadwell, Ken , Cai, Jingjing , Cai, Lu , Cai, Qian , Calbet, José A. L. , Caldwell, Guy A. , Call, Jarrod A. , Calvani, Riccardo , Calvo, Ana Cristina , Calvo‐Rubio, Miguel , Câmara, Niels Olsen Saraiva , Camonis, Jacques , Camougrand, Nadine , Campanella, Michelangelo , Campbell, Edward M. , Campos, Juliane C. , Camuzard, Olivier , Cancino, Jorge , Caniggia, Isabella , Canonico, Barbara , Cantı́, Carles , Cao, Bin , Caramés, B. , Cardenal‐Muñoz, Elena , Cárdenas, César , Cárdenas, Luis , Cardoso, Sandra M. , Carew, Jennifer S. , Carle, Georges F. , Carleton, Gillian , Carloni, Silvia , Carneiro, Letícia A. M. , Carosi, Julian M. , Carra, Serena , Carrier, Alice , Carter, A. 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W., Chan, Ho Yin Edwin , Chan, Helen H., Chan, Hung , Chan, Matthew T.V. , Chan, Yau Sang , Chang, Hao‐Chun , Chang, Kai , Chao, Jie , Charlet‐Berguerand, Nicolas , Chatterjee, Samrat , Chaube, Shail K. , Chaudhary, Anu , Chauhan, Santosh , Chaum, Edward , Checler, Frédéric , Cheetham, Michael E. , Chen, Chang‐Shi , Chen, Jian‐Fu , Chen, Liam L., Chen, Mingliang , Chen, Mu‐Kuan , Chen, Ning , Chen, Wei , Chen, Xinming , Chen, Xiongwen , Chen, Yan , Chen, Ye‐Guang , Chen, Yingyu , Chen, Yongqiang , Chen, Zhefan Stephen , Chen, Zhihua , Cheng, Xiu‐Tang , Cheng, Yiyun , Cheng, Zhiyong , Cheong, Jit Kong , Cherry, Sara , Cheung, Chi F., Cheung, Chun Hei Antonio , Cheung, King‐Ho , Chevet, Éric , Chi, Richard J., Chiaradonna, Ferdinando , Chiariello, M , Chica, Nathalia , Chiocca, Susanna , Chiong, Mario , Chiou, Shih‐Hwa , Chiramel, Abhilash I., Chiurchiù, Valerio , Cho, Dong-Hyung, Choe, Seong‐Kyu , Choi, Augustine M.K. , Choi, Mary E. , Choudhury, Kamalika Roy , Chow, Norman , Chua, Jason P. , Chua, John Jia En , Chung, Hyewon , Chung, Kin Pan , Chung, So‐Hyang , Chung, Yuen-Li, Ciechomska, Iwona A. , Cinque, Laura , Çırak, Sebahattin , Clarke, Robert , Clementi, Emilio , Coccia, Eliana M. , Codogno, Patrice , Colasanti, Tania , Colasuonno, Fiorella , Colbert, Robert A. , Colell, Anna , Coll, Núria S. , Collins, Mark O. , Colombo, Marı́a I. , Colón‐Ramos, Daniel A. , Cominetti, Márcia R. , Consiglio, Antonella , Conte, A. , Contu, Viorica Raluca , Cookson, Mark , Coombs, Kevin M. , Costa, Maria do Carmo , Costantino, Sarah , Costelli, Paola , Criollo, Alfredo , Crippa, V. , Cristofani, Riccardo , Csizmadia, Tamás , Cui, Bing , Cui, Yixian , Culetto, Emmanuel , Cumino, Andrea C. , Cybulsky, Andrey V. , Czaja, Mark J. , Czuczwar, Stanisław J. , D’Adamo, Stefania , D’Amelio, Marcello , D’Orazi, Gabriella , Silva, James Almada da , Dafsari, Hormos Salimi , Daglia, Maria , Dai, Xiaoxia , Dai, Yun , Dai, Yuyuan , Col, Jessica Dal , Dalhaimer, Paul , Valle, Luisa Dalla , Dallenga, Tobias , Dalmasso, Guillaume , Dando, Ilaria , Das, Hiranmoy , Dasari, Santosh K. , Dash, Srikanta, Dauphinee, Adrian N. , Davies, Jeffrey S. , Dávila, Valeria A. , Davis, Roger J. , Naidu, Sharadha Dayalan , Bosscher, Karolien De , Leonibus, Chiara De , Barbosa, Mayara Garcia de Mattos , Meyer, Guido R.Y. De , Palma, Clara De , Virgilio, Claudio De , Zio, Daniela De , Decuypere, Jean-Paul , Deehan, Mark , Deflorian, Gianluca , Dehay, Benjamin , Delaney, Joe R. , Delorme‐Axford, Elizabeth , Demers, Nicholas D. , Deng, Hongbin , Dengjel, Jörn , Dent, Paul, DePamphilis, Melvin L., Descoteaux, Albert , Devis, Laura , Devkota, Sushil , Devuyst, Olivier , Dewson, Grant , Dharmasivam, Mahendiran , Domenico, Fabio Di , Fazio, Pietro Di , Fonzo, Alessio Di , Guardo, Giovanni Di , Guglielmo, Gianni M. Di , Leo, Luca Di , Malta, Chiara Di , Nardo, Alessia Di, Rienzo, Martina Di , Diao, Jiajie , Diaz-Araya, Guillermo, Díaz‐Laviada, Inés , Dickinson, Jared M. , Diederich, Marc , Dieudé, Mélanie , Ding, Shiping , Ding, Wen-Xing, Dinić, Jelena , Dinić, Miroslav , Dinkova‐Kostova, Albena T. , Distler, Jörg H. 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Fielding , Henkel, Vanessa, Herb, Marc , Herman-Antosiewicz, Anna , Hernández, Agustín , Hernández, Carlos , Hernández-Díaz, Sergio , Hernández–Gea, Virginia , Herpin, Amaury , Herreros, Judit , Hervás, Javier H. , Hesselson, Daniel , Hetz, Claudio , Higuchi, Yujiro , Hilfiker, Sabine , Hill, Joseph A., Ho, Emmanuel A. , Ho, Idy H. T. , Ho, Philip Wing‐Lok , Ho, Shu‐Leong , Ho, Wan Yun, Hoet, Peter , Hofius, Daniel , Höhn, Annika , Hong, Yi-Ren Hong Chang-Won, Hooper, Lora V. , Hsin, I‐Lun , Hu, Bing , Hu, Dong , Hu, Wei , Hu, Zhuowei , Hua, Jinlian, Huan, Chongmin , Huang, Chuanshu , Huang, Chunling , Huang, Haishan , Huang, Michael , Huang, Shan , Huang, Tianzhi , Huang, Xing , Huang, Yuxiang , Hubert, Virginie , Hübner, Christian A. , Hughes, Stephanie M. , Hughes, William E. , Hummer, Gerhard , Hurley, James H. , Hussain, Sabah N. A. , Hussain, Salik , Hutabarat, Martina , Hwang, Hui-Yun, Ieni, Antonio , Ikeda, Fumiyo , Imagawa, Yusuke , Imbriano, Carol , Imoto, Masaya , Inman, Denise M. , Inoki, Ken , Iozzo, Renato V. , Iribarren, Pablo , Ishaq, Mohd , Ishimwe, Nestor , Ismail, Nahed , Issazadeh‐Navikas, Shohreh , Itakura, Eisuke , Ito, Daisuke , Ivankovic, Davor , Ivanova, Saška , Iyer, Anand Krishnan V. , Izquierdo, José M. , Jacobo‐Herrera, Nadia , Jacquin, Élise , Jadiya, Pooja , Jaeschke, Hartmut , Jagannath, Chinnaswamy, Jakobsson, Johan , Janji, Bassam , Jansen‐Dürr, Pidder , Jansson, Patric J. , Januszewski, Sławomir, Jeltsch‐David, Hélène , Jenny, Andreas , Jensen, Thomas E. , Jessen, Niels , Jia, Lijun , Jia, Rui , Jiang, Qing , Jiang, Richeng , Jiang, Teng , Jiang, Xuejun , Jiang, Yu , Jiménez-Sánchez, María , Jin, Fengyan , Jin, Li , Jin, Luqi, Jin, Si , Joffre, Carine , Johnston, Simon A. , Jokitalo, Eija , Juárez, Esmeralda , Juhász, Gábor , Jun, Youngsoo , Jung, Chang Hwa , Jung, Sung‐Chul , Jungbluth, Heinz , Jungverdorben, Johannes , Just, Steffen , Kaasik, Allen , Kaganovich, Daniel , Kain, Renate , Kajimura, Shingo , Kalamvoki, Maria , Kalia, Manjula , Kalinowski, Danuta S. , Kaludercic, Nina , Kalvari, Ioanna , Kamińska, Joanna , Kanamori, Hiromitsu , Kang, Chanhee , Kang, Rui , Kang, Sang Sun , Kaniyappan, Senthilvelrajan , Kanki, Tomotake , Kanneganti, Thirumala‐Devi , Kanthasamy, Arthi , Kantorow, Marc , Kapuy, Orsolya , Karim, Md. 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Andrew, Lizcano, José M. , Ljubojević-Holzer, Senka , Lleonart, Matilde E. , Llobet‐Navàs, David , Llorente, Alicia, Lo, Chih Hung , Lobato‐Márquez, Damián , Long, Yun , Loos, Ben , Loos, Julia A. , López-Doménech, Guillermo, López‐Guerrero, José Antonio , López-Jiménez, Ana T. , López-Pérez, Óscar , López-Valero, Israel, Lorenowicz, Magdalena J. , Lorente, Mar , Lossi, Laura , Lotersztajn, Sophie , Lovell, Jonathan F., Lovy, Alenka , Lőw, Péter, Lu, Guang , Lu, Haocheng , Lu, Jiahong , Lu, Mengji, Lu, Shuyan, Luciani, Alessandro , Lucocq, John M., Ludovico, Paula , Luftig, Micah A. , Luhr, Morten, Luis-Ravelo, Diego , Lum, Julian J., Luna-Dulcey, Liany, Lund, Anders H. , Lund, Viktor K. , Lüningschrör, Patrick , Luo, Honglin, Luo, Rongcan , Luo, Zhi , Luparello, Claudio , Lüscher, Bernhard , Luu, Luan , Lyakhovich, Alex , Lyamzaev, Konstantin G. , Lystad, Alf Håkon , Lytvynchuk, Lyubomyr , Alvin, C. H. , Ma, Ning-Fang, Ma, Quanhong , Ma, Xinliang , Ma, Yueyun , Ma, Zhenyi , MacDougald, Ormond A. , MacIntosh, Gustavo C. , Macleod, Kay F. , Maday, Sandra , Madeo, Frank , Madesh, Muniswamy , Madl, Tobias , Madrigal‐Matute, Julio , Maeda, Akiko, Maejima, Yasuhiro , Magariños, Marta , Mahavadi, Poornima , Maiani, Emiliano , Maiese, Kenneth , Maiti, Panchanan , Maiuri, Maria Chiara , Major, Michael Ben, Makareeva, Elena , Malik, Fayaz , Mallilankaraman, Karthik , Maloyan, Alina , Mammadova, Najiba, Man, Gene Chi Wai , Manai, Federico , Mancias, Joseph D. , Mandelkow, Eva‐Maria , Manfredi, Angelo A. , Manshian, Bella B. , Manzano, Raquel , Marchese, Chiara , Marchetti, Sandrine , Marcucci, F, Mardente, Stefania , Mareninova, Olga A. , Mari, Muriel , Marinelli, Sara , Mariño, Guillermo , Mariotto, Sofia , Martin, Alexandre , Martin, Katie R. , Martin, Sara L. , Martín‐Segura, Adrián , Martin-Burriel, Inmaculada, Martín-Rincón, Marcos , Martín‐Sanz, Paloma , Martinez, Aitor , Martı́nez, Ana , Martinez-Lopez, Nuria, Martínez‐Vicente, Marta , Martins, Daniel Oliveira , Martins, Joilson O. , Martins, Waleska K. , Martins-Marques, Tania, Marzetti, Emanuele , Masaldan, Shashank , Masclaux-Daubresse, Celine, Mashek, Douglas G. , Massa, Valentina , Massieu, Lourdes , Masyuk, Anatoliy I. , Masyuk, Tetyana V., Matheu, Ander , Matoba, Satoaki , Matsuzaki, Sachiko , Mattar, Pamela , Mattè, Alessandro , Mauriz, José L., Mauthe, Mario , Maycotte, Paola , Mayer, Johanna , Mazzoni, Cristina , Mazzulli, Joseph R. , McCarty, Nami , McGill, Mitchell R. , McKenna, Sharon L. , McLoughlin, Fionn , McNiven, Mark A., McWilliams, Thomas G. , Medeiros, Tania , Medina, Diego L., Megeney, Lynn A. , Megyeri, Klára , Mehrpour, Maryam , Mehta, Jawahar L. , Meijer, Alfred J., Mejlvang, Jakob , Meléndez, Alicia , Melk, Annette, Memişoğlu, Gönen , Mendes, A.F. , Meng, Delong , Meng, Fei, Mercier, A., Mergny, Jean‐Louis , Merkley, Seth D. , Meske, Volker, Mestre, Ana Cecilia, Metur, Shree Padma, Meyer, C., Meyer, Hemmo , Mi, Wenyi , Mialet‐Perez, Jeanne , Miao, Jun‐Ying, Micale, Lucia , Miki, Yasuo, Milan, Enrico , Milczarek, Małgorzata , Miller, Samuel I. , Millward, Steven W. , Mirzaei, Hamed, Mirzaei, Hamid Reza , Mirzaei, Mehdi , Mishra, Amit , Mishra, Nandita , Mishra, Paras Kumar, Misirkić, Maja , Misasi, Roberta, Misra, Amit , Misso, Gabriella , Mitchell, Claire H. , Mitou, Géraldine, Miura, Tetsuji , Miyazaki, Makoto, Miyazaki, Mitsunori , Miyazaki, Taiga , Miyazawa, Keisuke, Mizushima, Noboru , Mogensen, Trine H. , Mohammadinejad, Reza , Mohamud, Yasir , Mohanty, Abhishek , Möhlmann, Torsten , Moley, Kelle H. , Möller, Andreas, Mollereau, Bertrand , Mollinedo, Faustino, Montagna, Costanza , Monteiro, Mervyn J. , Montella, Andrea , Montes, L. 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David , Sze, Stephen Cho Wing , Szewczyk, Nathaniel J. , Tabęcka-Łonczynska, Anna, Tabolacci, Claudio , Taegtmeyer, Heinrich, Tagaya, Mitsuo , Tai, Haoran , Tait, Stephen W. G., Takahashi, Yoshinori , Tam, Chit , Tam, Shing Yau , Tampellini, Davide , Tamura, Atsushi , Tan, Eng-King, Tan, Ya‐Qin , Tanaka, Masaki , Tang, Daolin , Tang, Jingfeng , Tang, Tie-Shan , Tao, Zhipeng , Taouis, Mohammed , Tavernarakis, Nektarios, Taylor, Allen, Teixeira, Natércia , Tekirdağ, Kumsal Ayşe, Tencomnao, Tewin , Tenreiro, Sandra , Tharaux, Pierre‐Louis , Thedieck, Kathrin , Thekkinghat, Arvind A. , Thinwa, Josephine , Thirumalaikumar, Venkatesh P. , Thomes, Paul G. , Thorburn, Andrew , Thum, Thomas, Thumm, Michael , Tian, Ling, Tichý, Aleš , Timmerman, Vincent , Titorenko, Vladimir I. , Toivonen, Janne M. , Tomaipitinca, Luana , Tomar, Dhanendra , Tomás‐Zapico, Cristina , Tomić, Sergej , Tong, Chao, Tong, Xin , Torgersen, Maria L., Torii, Satoru , Torres-López, Liliana , Torriglia, Alicia , Towers, Christina G. , Towns, Roberto, Tran, Quynh‐Giao , Travassos, Leonardo H. , Tremel, Shirley , Trougakos, Ioannis P., Tsao, Betty P. , Tse, Tak Fu, Tsvetkov, Andrey S. , Tumbarello, David A. , Tyler, Jessica K., Tyutereva, Elena V. , Uchiyama, Yasuo , Ugun‐Klusek, Aslihan , Uhlig, Holm H. , Ułamek-Kozioł, Marzena, Ulasov, Ilya V. , Umekawa, Midori, Ungermann, Christian , Urbe, Sylvie, Uribe-Carretero, Elisabet , Uversky, Vladimir N. , Vaccaro, María I. , Vahsen, Björn F. , Vakifahmetoglu-Norberg, Helin, Valdor, Rut , Valente, Maria João , Valko, Ayelén , Vallée, Richard, Valverde, Ángela M. , Berghe, Greet Van den, Veen, Stijn van der , Kaer, Luc Van , Loosdregt, Jorg van , Wijk, Sjoerd J. L. van , Vandenberghe, Wim , Vanhorebeek, Ilse , Vannier-Santos, Marcos A., Vannini, Nicola , Vanrell, M. Cristina, Vantaggiato, Chiara , Varela‐Nieto, Isabel , Varga, Máté , Vasconcelos, M. Helena , Vats, Somya , Vega-Rubín-de-Celis, Silvia , Velasco, Guillermo , Velázquez, Ariadna P., Vellai, Tibor , Vellenga, Edo , Verdier, Mireille , Verginis, Panayotis , Vergne, Isabelle , Verkade, Paul , Verma, Manish , Verstreken, Patrik , Vervliet, Tim , Vervoorts, Jörg , Víctor, Víctor M., Vidoni, Chiara , Vieira, Otília V. , Vierstra, Richard D., Viganò, Sonia , Vihinen, Helena , Vijayan, Vinoy, Vila, Miquel , Villalba, José M., Villalobo, Antonio , Villarejo‐Zori, Beatriz , Vincent, Olivier , Vindis, Cécile , Viret, Christophe , Vocadlo, David J. , Voitsekhovskaja, Olga V. , Volonté, Cinzia , Volta, Mattia , Vomero, Marta , Haefen, Clarissa von, Vooijs, Marc , Voos, Wolfgang , Vučićević, Ljubica , Waguri, Satoshi , Waite, Kenrick A., Wakatsuki, Shuji , Walker, David W., Walker, Mark J. , Walter, Jochen, Wandosell, Francisco , Wang, Bo , Wang, Chao-Yung, Wang, Chen , Wang, Chenran, Wang, Chenwei , Wang, Cun-Yu, Wang, Fengming, Wang, Han, Wang, Hexiang , Wang, Hong‐Gang , Wang, Jianrong, Wang, Jigang , Wang, Jun-Dong , Wang, Kui , Wang, Lianrong, Wang, Liming , Wang, Maggie Haitian, Wang, Meiqing , Wang, Nanbu , Wang, Pengwei , Wang, Ping , Wang, Ping, Wang, Q., Wang, Qiong , Wang, Wentao , Wang, Xinnan, Wang, Xuejun , Wang, Yan, Wang, Yanchang , Wang, Yanzhuang , Wang, Yihua , Wang, Yu , Wang, Yuqi , Wang, Zhe, Wang, Zhenyu , Wang, Zhouguang , Watanabe, Eizo, Watchon, Maxinne , Wawrzyńska, Anna , Weaver, Timothy E., Węgrzyn, Grzegorz, Wehman, Ann M. , Wei, Huafeng , Wei, Taotao , Wei, Yongjie, Weiergräber, Oliver H. , Weihl, Conrad C., Weindl, Günther , Weiskirchen, Ralf , Wen, Runxia H. , Werner, Antonia, Weykopf, Beatrice , Whitton, J. Lindsay , Wiktorska, Katarzyna , Wildenberg, Manon E. , Wileman, Tom, Wilkinson, Simon , Williams, Brett, Williams, Robin S. B. , Williamson, Peter R. , Wilson, Richard A. , Winsor, Nathaniel J. , Wodrich, Harald , Woehlbier, Ute , Wollert, Thomas , Wong, Richard W., Wong, Vincent Kam Wai , Wong, W. Wei-Lynn, Wu, Anguo , Wu, Kenneth K., Wu, Shan‐Ying , Wu, William Ka Kei , Wu, Shufang, Wu, Xiaoqing , Wu, Yao‐Wen , Wu, Yihua , Xavier, Ramnik J. , Xia, Hongguang , Xia, Lixin , Xia, Zhengyuan , Ge, Xiang , Xiang, Jin , Xiang, Mingliang , Xiang, Wei , Xiao, Guozhi , Xiao, Hengyi , Xiao, Hongtao , Xiao, Jian, Xiao, Lan , Xiao, Shi , Xiao, Yin , Xie, Baoming, Xie, Zhiping , Xie, Min , Xie, Yuxiang , Xie, Zhonglin, Xilouri, Maria , Xu, En , Xu, Jin‐Rong , Xu, Liang , Xu, Xiulong , Xue, Yu , Yakhine-Diop, Sokhna M. S. , Yamaguchi, Masamitsu , Yamamoto, Ai , Yamashina, Shunhei, Yan, Shengmin , Yan, Shian-Jang, Yan, Zhen , Yang, Chuanbin , Yang, Dun-Sheng, Yang, Huan , Yang, Huang-Tian, Yang, Hui , Yang, Jing , Yang, Jingyu , Yang, Ling , Liu, Yang , Yang, Ming , Yang, Seungwon, Yang, Shu , Yang, Shun-Fa , Yang, Wannian, Yang, Wei , Yang, Xiaoyong , Yang, Yi , Yao, Xiaoqiang , Yao, Yong-Gang , Yao, Yong-ming, Yasui, Takahiro , Yazdankhah, Meysam, Yi, Cong , Yin, Xiao-Ming , Yin, Yanhai , Yin, Zhangyuan , Yin, Ziyi , Ying, Meidan , Ying, Zheng, Yip, Calvin K. , Yiu, Stephanie Pei Tung , Yoo, Young Hyun , Yoshimori, Tamotsu, Yousefi, Bahman, Yu, Boxuan , Yu, Haiyang , Yu, Jun, Li, Yu , Yu, Ming‐Lung , Yu, Seong-Woon, Yu, Victor C. , Yu, Zhengping, Yuan, Junying , Yuan, Ling‐Qing , Yuan, Shilin , Yuan, Yanggang , Yuan, Zengqiang , Yue, Jianbo , Yue, Zhenyu , Yung, Raymond , Zacks, David, Zaffagnini, Gabriele , Zambelli, Vanessa O. , Zanella, Isabella , Zang, Qun S. , Zanivan, Sara , Zappavigna, Silvia , Zaragoza, P. , Zarbalis, Konstantinos S., Zarebkohan, Amir , Zarrouk, Amira , Zeitlin, Scott, Zeng, Jialiu , Zeng, Judeng , Žerovnik, Eva , Zhan, Lixuan , Zhang, Donna D., Zhang, Hong , Zhang, Honghe , Zhang, Huafeng , Zhang, Huaye, Zhang, Huiling , Zhang, Jianbin , Zhang, Jingpu , Zhang, Kalin Yanbo , Zhang, Leshuai W. , Zhang, Lu , Zhang, Luoying , Zhang, Menghuan, Zhang, Peng , Zhang, Sheng , Zhang, Xiangnan, Zhang, Xiao-Wei, Zhang, Xiaolei , Zhang, Xiaoyan , Zhang, Xin , Zhang, Xinxin , Zhang, Yang, Zhang, Yi , Zhang, Yingdong , Zhang, Yuanyuan , Zhang, Yuchen , Zhang, Zhe , Zhang, Zhibing , Zhang, Zili , Zhao, Haobin, Zhao, Lei , Zhao, Shuang , Zhao, Tongbiao , Zhao, Ying, Zhao, Yongchao , Zhao, Yongliang , Zhao, Yuting , Zheng, Guoping , Zheng, Kai, Zheng, Ling , Zheng, Shizhong , Zheng, Xi‐Long , Zheng, Zu‐Guo , Zhivotovsky, Boris, Zhong, Qing , Zhou, Ao, Zhou, Ben , Zhou, Cefan , Zhou, Gang , Zhou, Hongbo , Zhou, Kailiang, Zhou, Rongjia , Zhou, Yanshuang, Zhou, Yinghong , Zhou, Yubin , Zhou, Zhengyu, Zhou, Zhou , Zhu, Binglin , Zhu, Changlian , Zhu, Guo‐Qing , Zhu, Haining , Zhu, Hongxin, Zhu, Yanping , Zhu, Yushan , Zhuang, Haixia , Zhuang, Xiaohong , Zimmermann, Christine , Żołądek, Teresa , Zong, Wei‐Xing, Zorov, Dmitry B. , Zorzano, Antonio, Zou, Weiping, Zou, Zhen , Zou, Zhengzhi, Zuryn, Steven , Kenchappa, Chandra Shekar, Li, Zuguo , Lin, Yong , Sluimer, Judith C. , Stallings, Christina L. , Tong, Chun-Kit, Wang, Ping , Hu, Bo , Lee, Edward B. , Tse, Hung‐Fat , Suszták, Katalin , Lei, Yu Leo , Yu, M-L , Dai, Yun , Bartolome, Alberto , Brown, Rhoderick E , Passos, João F , Paneni, Francesco , Sahin, Özgür , Pereira de Almeida, Luis , Ren, Jun , Bornhauser, Beat , Kumar, Sharad , Sampaio-Marques, Belém , Ludovico, Paula , Luftig, Micah , Begun, Jakob , Krasnodembskaya, Anna D , Dafsari, Hormos Salimi , Chevet, Eric , Tse, Hung-Fat , Barmada, Sami , Ebrahimi-Fakhari, Darius , Cavadas, Claudia , Sue, Carolyn M , Cardenal-Muñoz, Elena , Lee, Edward B , Golebiewska, Anna , Calbet, Jose A L , Boya, Patricia , Maday, Sandra , Klionsky, Daniel J. , Abdelfatah, Sara , Abdoli, Asghar , Agarwal, Anupam , Ahmed, Zubair M. , Alcocer‐Gómez, Elísabet , Ali, Muhammad , Al‐Bari, Md. Abdul Alim , Aliwaini, Saeb H. , Alizadeh, Javad , Almacellas, Eugènia , Almasan, Alexandru , Alonso, G. , Altieri, Dario C. , Andersen, Stig Uggerhøj , Andrade-Silva, Magaiver , Angelini, Sabrina , Apostolova, Nadezda , Arasaki, Kohei , Araújo, Wagner L. , Arden, Catherine , Arimoto, Hirokazu , Armstrong-James, Darius P. H. , Pelloquin, Laetitia , Aschner, Michael , Ashrafizadeh, Milad , Autelli, Riccardo , Aveic, Sanja , Avin‐Wittenberg, Tamar , Ayton, Scott , Backues, Steven K. , Bae, Dong-Hun , Bae, Ok‐Nam , Baek, Ahruem , Baek, Seung‐Hoon , Baek, Sung Hee , Bai, Jie , Bai, Yidong , Baldari, Cosima T. , Balduini, Walter , Ballabio, Andrea , Banerjee, Sreeparna , Bao, Yan , Baptista, Maurı́cio S. , Barreto, George Emilio , Basagoudanavar, Suresh H. , Bast, Robert C. , Basu, Alakananda , Batoko, Henri , Batten, Isabella , Behrens, Georg M. N. , Bei, Roberto , Behl, Christian , Bello‐Morales, Raquel , Beltrán, Sebastián , Bergami, Matteo , Bergmann, Andreas , Berthoux, Lionel , Bhattacharya, Resham , Bhattacharyya, Shalmoli , Bhutia, Sujit Kumar , Bi, Lanrong , Birgisdottir, Åsa Birna , Bjørkøy, Geir , Blomgren, Klas , Boada-Romero, Emilio , Boesze‐Battaglia, Kathleen , Bonifacino, Juan S. , Boone, Brian A. , Borthakur, Gautam , Bosch, Jürgen , Bose, Santanu , Botana, Luis Miguel , Boulton, Michael E. , Bourdenx, Mathieu , Brackney, Doug E. , Brandts, Christian , Braun, Ralf J. , Braus, Gerhard H. , Bravo, Roberto , Brody, Steven L. , Brown, Carolyn Nicole , Brumell, John Hunter , Brunetti‐Pierri, Nicola , Buitrago‐Molina, Laura Elisa , Buraschi, Simone , Buch, Shilpa J. , Butturini, Elena , Cairó, Montserrat , Caldwell, Kim A. , Campbell‐Valois, François‐Xavier , Campello, Silvia , Campesi, Ilaria , Almeida, Danilo Cândido de , Canesi, Laura , Caraglia, Michele , Carchman, Evie H. , Carmona‐Gutiérrez, Didac , Carnevali, Oliana , Carrier, Lucie , Carroll, Bernadette , Carter, A. Brent , Casas, Caty , Castillo, Eliseo F. , Castro‐Caldas, Margarida , Castro‐Obregón, Susana , Catz, Sergio , Cayuela, María Luisa , Cecarini, Valentina , Cecconi, Francesco , Cenci, Simone , Ceperuelo‐Mallafré, Victòria , Cervia, Davide , Chae, Han–Jung , Chakrabarti, Oishee , Chan, Edmond Y. W., Chan, Edward D. , Chandra, Partha Kumar , Chang, Chih‐Peng , Chang, Chunmei , Chapman, Tracey , Chen, Guang‐Chao , Chen, Leilei , Chen, Lin , Chen, Quan , Chen, Ruey‐Hwa , Chen, Shi , Chen, Wei‐Qiang , Chen, Xu , Chen, Yu-Jen , Chen, Yujie , Chen, Zhi , Chen, Zhijian J. , Chen, Zhixiang , Cheng, Hanhua , Cheng, Jun , Cheng, Shi‐Yuan , Cheng, Wei Nee , Cheng, Xiaodong , Chen, Zhong , Cheong, Heesun , Chernyak, Boris V. , Chi, Richard J., Chiang, Aks , Chiarelli, Roberto , Chu, Charleen T. , Chung, Seockhoon , Cianfanelli, Valentina , Cifuentes, Mariana , Cirone, Mara , Clague, Michael J. , Cohen, Ehud , Cohen, Mickaël M. , Čolić, Miodrag J , Combaret, Lydie , Comincini, Sergio , Conte, Andrea, Conti, Fabrizio , Coppens, Isabelle , Corasaniti, Maria Tiziana , Corkery, Dale , Cordes, Nils , Cortese, Katia , Coto‐Montes, Ana M. , Crack, Peter John , Crespo, José L. , Cuadrado, Antonio , Cui, Jun , Cui, Yong , D’Arcangelo, Daniela , D’Lugos, Andrew C. , Dagda, Ruben Karim , Dagdas, Yasin , Daμμe, Markus , Dantuma, Nico P. , Darling, April L. , Dasarathy, Srinivasan , Daumke, Oliver , Davis, Tanja , Amicis, Francesca De , Felice, Francesca De , Franceschi, Lucia De , Milito, Angelo De , Nunzio, Cosimo De , Santi, Mauro De , Debnath, Jayanta , DeBosch, Brian J. , DeGregori, James V. , Rio, Gabriel del , Delbridge, Lea M.D. , Delpino, M. Victoria , Demarchi, Francesca , Dembitz, Vilma , Deng, Zhiqiang , Denton, Donna , Der, Channing J , Deretić, Vojo , Dhiman, Rohan , Bernardo, Diego di , Cristina, Manlio Di , Nardo, Alessia Di, Sano, Federica Di , Diallinas, George , Diaz-Araya, Guillermo, Đikić, Ivan , Ding, Wen‐Xing , Dini, Luciana , Dionne, Marc , Diwan, Abhinav , Dixon, Ian , Djavaheri‐Mergny, Mojgan , Dobrinski, Ina , Dobrovinskaya, Oxana R. , Dobrowolski, Radek , Dobson, Renwick C. J. , Donadelli, Massimo , Dong, Bo, Dötsch, Volker , Dou, Huan , Dridi, Sami , Du, Caigan , Du, Li‐Lin , Dubrovska, Anna , Dunlop, Elaine A. , Dwarakanath, Bilikere Srinivasa Rao , Eftekharpour, Eftekhar , Eichinger, Ludwig , Eissa, N. Tony , Eissa, Sanaa , El‐Naggar, Shahenda , Eliopoulos, Aristides G. , Elks, Philip M. , Emerling, Brooke M. , Engelbrecht, Anna‐Mart , Escobar‐Henriques, Mafalda , Fabriàs, Gemma , Fabrizi, Cinzia , Falkenburger, Björn H. , Fan, Yanbo , Fanto, Manolis , Feng, Du , Feng, Yibin , Feng, Yuchen , Fernández-Checa, José Carlos , Filippi‐Chiela, Eduardo Cremonese , Filomeni, Giuseppe , Fineschi, Vittorio , Flamigni, Flavio , Follo, Carlo , Fon, Edward A , Fornai, Francesco , Fraldi, Alessandro , Franco, Brunella , Franco, Rodrigo , Friedman, Scott L. , Frühbeck, Gema , Fujita, Naonobu , Fujiwara, Yuuki , Fukuda, Mitsunori , Furic, Luc , Fusco, Carmela , Galluzzi, Lorenzo, Gan, Boyi , Gao, Hui , Gao, Shou‐Jiang , Gargini, Ricardo , Garry, Robert F. , Ge, Liang , Ge, Wanzhong , Gelfi, Cecilia , Gentle, Ian Edward , Gewirtz, David A , Ghigo, Alessandra , Giampietri, Claudia , Gibson, Spencer B. , Giniger, Edward , Giorgi, Carlotta , Girão, Henrique , Goldstone, David C. , Gomez‐Puerto, Maria Catalina , Goñi, Félix M. , González‐Hernández, Tomás , Gorbatyuk, Marina S. , Goruppi, Sandro , Gottlieb, Roberta A. , Gozes, Illana , Green, Douglas R. , Grinstaff, Mark W. , Grune, Tilman , Guntur, Anyonya R. , Guo, Lian‐Wang , Gupta, Shashi Kumar , Gustafsson, Åsa B. , Haapasalo, Annakaisa , Hadano, Shinji , Hafrén, Anders , Hall, Belinda S. , Hamann, Andréa , Han, Weidong , Hanson, Phyllis I. , Haroon, Nigil , Harris, James , Hasegawa, Takafumi , Nagoor, Noor Hasima , Hay, Bruce A. , Hayrabedyan, Soren , He, Yu‐Ying , Helgason, G. Vignir , Hergovich, Alexander , Hernández–Gea, Virginia , Heussler, Volker Theo , Hlavacek, William S. , Hobbs, G. Aaron , Hochstrasser, Mark , Hofman, Paul , Holmberg, Carina I. , Hombrebueno, José R. , Hoppe, Thorsten , Horos, Rastislav , Hoshida, Yujin , Hsu, Hsin‐Yun , Hu, Li‐Fang , Hu, Ming Chang , Hu, Ronggui , Hu, Yu‐Chen , Hua, Fang , Hua, Jinlian, Hua, Yingqi , Huang, Canhua , Huang, Chuanxin , Huang, Kun , Huang, Rui , Huber, Tobias Bruno , Humbert, Magali , Hussey, Patrick J. , Hwang, Hui‐Yun , Hwang, Seungmin , Imai, Yuzuru , Iovanna, Juan , Ippolito, Giuseppe , Irazoqui, Javier E. , Ishaq, Mohd, Ishikawa, Makoto , Isidoro, Ciro , Izumi, Masanori , Jäättelä, Marja , Jabir, Majid Sakhi , Jackson, William T. , Jacomin, Anne‐Claire , Jakobi, Arjen J. , Jantsch, Jonathan , Jassey, Alagie , Jean, Steve , Jendelová, Pavla , Jewell, Jenna L. , Ji, Jing , Jiang, Liwen , Jin, Eun‐Jung , Jin, Hongchuan , Jin, Meiyan , Jo, Eun‐Kyeong , Johansen, Terje , Johnson, Gail V.W. , Jolly, Mohit Kumar , Joosten, Leo A. B. , Jordán, Joaquı́n , Joseph, Bertrand , Ju, Dianwen , Ju, Jeong-Sun , Ju, Jingfang , Judith, Delphine , Jung, Yong‐Keun , Kaarniranta, Kai , Kabuta, Tomohiro , Kahana, Alon , Kaminskyy, Vitaliy O. , Kanasaki, Keizo , Kanthasamy, Anumantha G. , Karamouzis, Michalis V. , Karmakar, Parimal , Katare, Rajesh , Kaufmann, Stefan H. E. , Kaushik, Susmita , Kawasaki, Kiyoshi, Ke, Po‐Yuan , Keating, Damien J. , Kehrl, John H. , Keller, Christian W. , Kemper, Jongsook Kim , Kermorgant, Stéphanie , Ketteler, Robin , Khambu, Bilon , Kim, Deok Ryong, Kim, Eun Young , Kim, Jin Kyung , Kim, Jin‐Hoi , Kim, Ju Hwan , Kim, Keun Il , Kim, Peter Kijun , Kinghorn, Kerri J. , Kirkin, Vladimir , Киселев, С. Л. , Kittler, Josef T. , Knorr, Roland L. , Ko, Ben C.B. , Ko, Jiunn‐Liang , Kobayashi, Hotaka , Koenig, Ulrich , Koike, Masato , Kohlwein, Sepp Dieter , Komatsu, Masaaki , Kopp, Benjamin T. , Korcsmaros, Tamas Douglas , Korolchuk, Viktor I. , Kotler, Mónica L. , Koukourakis, Michael Ioannis , Kovács, Tibor, Koya, Daisuke , Kozako, Tomohiro , Krämer, Helmut , Kroemer, Guido , Ktistakis, Nicholas T. , Kuchitsu, Kazuyuki , Kumar, Ashok , Kumar, Deepak, Kundu, Mondira , Kurgan, Lukasz , Kutateladze, Tatiana G. , Kwon, Ho Jeong , Kwon, Taeg Kyu , Kyrmizi, Irene , Spada, Albert R. La , Lai, Zhibing, Lamark, Trond , Lane, Jon D. , Lang, Charles H. , Lange, Carsten, Langel, Ülo , Lapaquette, Pierre , LaRusso, Nicholas F. , Lastres‐Becker, Isabel , Lavandero, Sergio , Law, Hkw , Layfield, Robert , Leduc‐Gaudet, Jean‐Philippe , Lee, He-Jin, Lee, Jae Man , Lee, Jun Hee , Lee, Seung‐Jae , Lee, Ying‐Ray , Lefebvre, Christophe , Legouis, Renaud , Leitinger, Gerd , Lenz, Heinz Josef, León, Yolanda, Leopoldino, Andréia Machado , Leung, Chi-Ting, Levine, Beth , Li, Jing , Li, Ke, Li, Min , Li, Min , Li, Pin‐Lan , Li, Tiangang , Li, Zhiqiang, Lian, Jiqin , Liang, Chengyu, Liang, Qiangrong , Liao, Mingzhi , Lilly, Mary A. , Lin, Liang , Lin, Pei‐Hui , Lin, Xueying , Linden, Rafael , Ling, Shuo‐Chien , Lingor, Paul , Linnemann, Amelia K , Liou, Yih‐Cherng , Lira, Vitor Agnew , Liu, Chunfeng , Liu, Cui Hua , Liu, Hao , Liu, Hsiao‐Sheng , Liu, Julia C. , Liu, Longhua , Liu, Meilian , Liu, Qin , Liu, Xiao-Hong, Liu, Xiaodong , Liu, Xingguo , Liu, Xuedong , Liu, Yang, Liu, Yang, Lizard, Gérard , Llorente, Alicia , Long, Qi , Long, Yun Chau, López, Manuela G. , Lőrincz, Péter , Lovat, Penny E. , Lu, Jin‐Jian , Lum, Julian J., Lünemann, Jan D. , Luo, Shouqing , Ma, Changle , Ma, Mengxiao , Ma, Ning‐Fang , Macián, Fernando , MacKeigan, Jeffrey P. , Majello, Barbara , Malorni, Walter , Mandell, Michael A. , Manjili, Masoud H. , Manjithaya, Ravi R. , Manque, Patrício , Manzoni, Claudia , Mao, Kai, Marconi, Anna Maria , Margeta, Marta , Marinelli, Oliviero , Marshall, Richard Scott , Marten, Mark R. , Martens, Sascha , Martin, Sara, Martín-Acebes, Miguel A. , Martín‐Burriel, Inmaculada , Martina, José A. , Martinet, Wim , Martinez, Jennifer , Martínez‐Velázquez, Moisés , Martinez-Lopez, Nuria, Martins‐Marques, Tânia , Masclaux‐Daubresse, Céline , Masson, Glenn Robert , Masuelli, Laura , Masyuk, Tetyana V., Matarrese, Paola , Mattoscio, Domenico , Mauriz, Jose Luis , Mauvezin, Caroline , Maverakis, Emanual Michael , Mazzoccoli, Gianluigi , McDonald, Christine , McLaughlin, BethAnn , Mechta‐Grigoriou, Fatima , Meijer, Annemarie H. , Meng, Tian, Menna‐Barreto, Rubem F. 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Autophagy | March 24, 2021 | Volume: 17 | Issue: 1 | Pages: 1-382

10.1080/15548627.2020.1797280 | PMID 33634751 Get It