Zum Hauptinhalt springen

Body composition and lung cancer-associated cachexia in TRACERx.

Al-Sawaf, O ; Weiss, J ; et al.
In: Nature medicine, Jg. 29 (2023-04-01), Heft 4, S. 846
academicJournal

Titel:
Body composition and lung cancer-associated cachexia in TRACERx.
Autor/in / Beteiligte Person: Al-Sawaf, O ; Weiss, J ; Skrzypski, M ; Lam, JM ; Karasaki, T ; Zambrana, F ; Kidd, AC ; Frankell, AM ; Watkins, TBK ; Martínez-Ruiz, C ; Puttick, C ; Black, JRM ; Huebner, A ; Bakir, MA ; Sokač, M ; Collins, S ; Veeriah, S ; Magno, N ; Naceur-Lombardelli, C ; Prymas, P ; Toncheva, A ; Ward, S ; Jayanth, N ; Salgado, R ; Bridge, CP ; Christiani, DC ; Mak, RH ; Bay, C ; Rosenthal, M ; Sattar, N ; Welsh, P ; Liu, Y ; Perrimon, N ; Popuri, K ; Beg, MF ; McGranahan, N ; Hackshaw, A ; Breen, DM ; O'Rahilly, S ; Birkbak, NJ ; Aerts, HJWL ; Jamal-Hanjani, M ; Swanton, C
Zeitschrift: Nature medicine, Jg. 29 (2023-04-01), Heft 4, S. 846
Veröffentlichung: New York Ny : Nature Publishing Company ; <i>Original Publication</i>: New York, NY : Nature Pub. Co., [1995-, 2023
Medientyp: academicJournal
ISSN: 1546-170X (electronic)
DOI: 10.1038/s41591-023-02232-8
Schlagwort:
  • Male
  • Humans
  • Cachexia complications
  • Proteomics
  • Neoplasm Recurrence, Local pathology
  • Body Composition
  • Body Weight
  • Muscle, Skeletal metabolism
  • Antigens, Neoplasm metabolism
  • Neoplasm Proteins
  • Lung Neoplasms pathology
  • Carcinoma, Non-Small-Cell Lung pathology
Sonstiges:
  • Nachgewiesen in: MEDLINE
  • Sprachen: English
  • Corporate Authors: TRACERx Consortium
  • Publication Type: Journal Article; Research Support, N.I.H., Extramural; Research Support, Non-U.S. Gov't
  • Language: English
  • [Nat Med] 2023 Apr; Vol. 29 (4), pp. 846-858. <i>Date of Electronic Publication: </i>2023 Apr 12.
  • MeSH Terms: Lung Neoplasms* / pathology ; Carcinoma, Non-Small-Cell Lung* / pathology ; Male ; Humans ; Cachexia / complications ; Proteomics ; Neoplasm Recurrence, Local / pathology ; Body Composition ; Body Weight ; Muscle, Skeletal / metabolism ; Antigens, Neoplasm / metabolism ; Neoplasm Proteins
  • References: Calle, E. E., Rodriguez, C., Walker-Thurmond, K. & Thun, M. J. Overweight, obesity, and mortality from cancer in a prospectively studied cohort of US adults. N. Engl. J. Med. 348, 1625–1638 (2003). (PMID: 1271173710.1056/NEJMoa021423) ; Guo, Y. et al. Body mass index and mortality in chronic obstructive pulmonary disease: a dose-response meta-analysis. Medicine 95, e4225 (2016). (PMID: 27428228495682210.1097/MD.0000000000004225) ; Lavie, C. J., McAuley, P. A., Church, T. S., Milani, R. V. & Blair, S. N. Obesity and cardiovascular diseases: implications regarding fitness, fatness, and severity in the obesity paradox. J. Am. Coll. Cardiol. 63, 1345–1354 (2014). (PMID: 2453066610.1016/j.jacc.2014.01.022) ; Martin, L. et al. Cancer cachexia in the age of obesity: skeletal muscle depletion is a powerful prognostic factor, independent of body mass index. J. Clin. Oncol. 31, 1539–1547 (2013). (PMID: 2353010110.1200/JCO.2012.45.2722) ; Baracos, V. E., Martin, L., Korc, M., Guttridge, D. C. & Fearon, K. C. H. Cancer-associated cachexia. Nat. Rev. Dis. Primers 4, 17105 (2018). (PMID: 2934525110.1038/nrdp.2017.105) ; Fearon, K. et al. Definition and classification of cancer cachexia: an international consensus. Lancet Oncol. 12, 489–495 (2011). (PMID: 2129661510.1016/S1470-2045(10)70218-7) ; Brown, J. C. et al. The deterioration of muscle mass and radiodensity is prognostic of poor survival in stage I–III colorectal cancer: a population-based cohort study (C-SCANS). J. Cachexia Sarcopenia Muscle 9, 664–672 (2018). (PMID: 29766660610410810.1002/jcsm.12305) ; Caan, B. J. et al. Association of muscle and adiposity measured by computed tomography with survival in patients with nonmetastatic breast cancer. JAMA Oncol. 4, 798–804 (2018). (PMID: 29621380658432210.1001/jamaoncol.2018.0137) ; Lee, J. S. et al. Subcutaneous fat distribution is a prognostic biomarker for men with castration resistant prostate cancer. J. Urol. 200, 114–120 (2018). (PMID: 2936664110.1016/j.juro.2018.01.069) ; Baracos, V. E., Reiman, T., Mourtzakis, M., Gioulbasanis, I. & Antoun, S. Body composition in patients with non-small cell lung cancer: a contemporary view of cancer cachexia with the use of computed tomography image analysis. Am. J. Clin. Nutr. 91, 1133s–1137s (2010). (PMID: 2016432210.3945/ajcn.2010.28608C) ; Yang, M., Shen, Y., Tan, L. & Li, W. Prognostic value of sarcopenia in lung cancer: a systematic review and meta-analysis. Chest 156, 101–111 (2019). (PMID: 3112811510.1016/j.chest.2019.04.115) ; Popinat, G. et al. Subcutaneous fat mass measured on multislice computed tomography of pretreatment PET/CT is a prognostic factor of stage IV non-small cell lung cancer treated by nivolumab. Oncoimmunology 8, e1580128 (2019). (PMID: 31069139649297810.1080/2162402X.2019.1580128) ; Tan, H. et al. Preoperative body composition combined with tumor metabolism analysis by PET/CT is associated with disease-free survival in patients with NSCLC. Contrast Media Mol. Imaging 2022, 7429319 (2022). (PMID: 35935304930027610.1155/2022/7429319) ; Mourtzakis, M. et al. A practical and precise approach to quantification of body composition in cancer patients using computed tomography images acquired during routine care. Appl. Physiol. Nutr. Metab. 33, 997–1006 (2008). (PMID: 1892357610.1139/H08-075) ; Shen, W. et al. Total body skeletal muscle and adipose tissue volumes: estimation from a single abdominal cross-sectional image. J. Appl. Physiol. 97, 2333–2338 (2004). (PMID: 1531074810.1152/japplphysiol.00744.2004) ; Dabiri, S. et al. Deep learning method for localization and segmentation of abdominal CT. Comput. Med. Imaging Graph 85, 101776 (2020). (PMID: 32862015780347110.1016/j.compmedimag.2020.101776) ; Frankell, A. M. et al. The natural history of NSCLC and impact of subclonal selection in TRACERx. Nature (In press) (2023). ; Jamal-Hanjani, M. et al. Tracking the evolution of non-small-cell lung cancer. N. Engl. J. Med. 376, 2109–2121 (2017). (PMID: 2844511210.1056/NEJMoa1616288) ; Christiani, D. B. Lung Cancer Study. https://sites.sph.harvard.edu/blcs/ (2022). ; Anyene, I. et al. Body composition from single versus multi-slice abdominal computed tomography: concordance and associations with colorectal cancer survival. J. Cachexia Sarcopenia Muscle 13, 2974–2984 (2022). (PMID: 36052755974555810.1002/jcsm.13080) ; Speliotes, E. K. et al. Association analyses of 249,796 individuals reveal 18 new loci associated with body mass index. Nat. Genet. 42, 937–948 (2010). (PMID: 20935630301464810.1038/ng.686) ; Locke, A. E. et al. Genetic studies of body mass index yield new insights for obesity biology. Nature 518, 197–206 (2015). (PMID: 25673413438221110.1038/nature14177) ; Wen, W. et al. Meta-analysis of genome-wide association studies in East Asian-ancestry populations identifies four new loci for body mass index. Hum. Mol. Genet 23, 5492–5504 (2014). (PMID: 24861553416882010.1093/hmg/ddu248) ; Akiyama, M. et al. Genome-wide association study identifies 112 new loci for body mass index in the Japanese population. Nat. Genet. 49, 1458–1467 (2017). (PMID: 2889206210.1038/ng.3951) ; Winkler, T. W. et al. The influence of age and sex on genetic associations with adult body size and shape: a large-scale genome-wide interaction study. PLoS Genet 11, e1005378 (2015). (PMID: 26426971459137110.1371/journal.pgen.1005378) ; Johns, N. et al. New genetic signatures associated with cancer cachexia as defined by low skeletal muscle index and weight loss. J. Cachexia Sarcopenia Muscle 8, 122–130 (2017). (PMID: 2789740310.1002/jcsm.12138) ; Solheim, T. S. et al. Is there a genetic cause for cancer cachexia? A clinical validation study in 1,797 patients. Br. J. Cancer 105, 1244–1251 (2011). (PMID: 21934689320848410.1038/bjc.2011.323) ; Baranski, T. J. et al. A high-throughput, functional screen of human body mass index GWAS loci using tissue-specific RNAi Drosophila melanogaster crosses. PLOS Genet. 14, e1007222 (2018). (PMID: 29608557589703510.1371/journal.pgen.1007222) ; Lodge, W. et al. Tumor-derived MMPs regulate cachexia in a Drosophila cancer model. Dev. Cell 56, 2664–2680 (2021). (PMID: 3447394010.1016/j.devcel.2021.08.008) ; Ding, G. et al. Coordination of tumor growth and host wasting by tumor-derived Upd3. Cell Rep. 36, 109553 (2021). (PMID: 34407411841094910.1016/j.celrep.2021.109553) ; Kwon, Y. et al. Systemic organ wasting induced by localized expression of the secreted insulin/IGF antagonist ImpL2. Dev. Cell 33, 36–46 (2015). (PMID: 25850671443724310.1016/j.devcel.2015.02.012) ; Song, W. et al. Tumor-derived ligands trigger tumor growth and host wasting via differential MEK activation. Dev. Cell 48, 277–286 (2019). (PMID: 30639055636835210.1016/j.devcel.2018.12.003) ; Newton, H. et al. Systemic muscle wasting and coordinated tumour response drive tumourigenesis. Nat. Commun. 11, 4653 (2020). (PMID: 32938923749543810.1038/s41467-020-18502-9) ; Figueroa-Clarevega, A. & Bilder, D. Malignant Drosophila tumors interrupt insulin signaling to induce cachexia-like wasting. Dev. Cell 33, 47–55 (2015). (PMID: 25850672439076510.1016/j.devcel.2015.03.001) ; Kim, J. et al. Tumor-induced disruption of the blood–brain barrier promotes host death. Dev. Cell 56, 2712–2721 (2021). (PMID: 34496290851109810.1016/j.devcel.2021.08.010) ; van der Klaauw, A. A. et al. Human semaphorin 3 variants link melanocortin circuit development and energy balance. Cell 176, 729–742 (2019). (PMID: 30661757637091610.1016/j.cell.2018.12.009) ; Trobec, K., von Haehling, S., Anker, S. D. & Lainscak, M. Growth hormone, insulin-like growth factor 1, and insulin signaling—a pharmacological target in body wasting and cachexia. J. Cachexia Sarcopenia Muscle 2, 191–200 (2011). (PMID: 22207907322282210.1007/s13539-011-0043-5) ; Mermel, C.H., Schumacher, S.E., Hill, B. et al. GISTIC2.0 facilitates sensitive and confident localization of the targets of focal somatic copy-number alteration in human cancers. Genome Biol. 12, R41 (2011). ; Achari, A. E. & Jain, S. K. Adiponectin, a therapeutic target for obesity, diabetes and endothelial dysfunction. Int J. Mol. Sci. 18, 1321 (2017). (PMID: 28635626548614210.3390/ijms18061321) ; Bentham, R. et al. Using DNA sequencing data to quantify T cell fraction and therapy response. Nature 597, 555–560 (2021). ; Danaher, P. et al. Gene expression markers of tumor infiltrating leukocytes. J. Immunother. Cancer 5, 18 (2017). (PMID: 28239471531902410.1186/s40425-017-0215-8) ; Newman, A. M. et al. Determining cell type abundance and expression from bulk tissues with digital cytometry. Nat. Biotechnol. 37, 773–782 (2019). (PMID: 31061481661071410.1038/s41587-019-0114-2) ; Assarsson, E. et al. Homogenous 96-Plex PEA immunoassay exhibiting high sensitivity, specificity and excellent scalability. PLoS ONE 9, e95192 (2014). (PMID: 24755770399590610.1371/journal.pone.0095192) ; Lerner, L. et al. MAP3K11/GDF15 axis is a critical driver of cancer cachexia. J. Cachexia Sarcopenia Muscle 7, 467–482 (2016). (PMID: 2723940310.1002/jcsm.12077) ; Lockhart, S. M., Saudek, V. & O’Rahilly, S. GDF15: a hormone conveying somatic distress to the brain. Endocr. Rev. 41, bnaa007 (2020). (PMID: 32310257729942710.1210/endrev/bnaa007) ; Wollert, K. C. et al. An automated assay for growth differentiation factor 15. J. Appl. Lab. Med. 1, 510–521 (2017). (PMID: 3337980210.1373/jalm.2016.022376) ; Cai, D. et al. Extensive serum biomarker analysis in patients with non-small-cell lung carcinoma. Cytokine 126, 154868 (2020). (PMID: 3162911010.1016/j.cyto.2019.154868) ; Roche. Elecsys GDF-15 datasheet. https://diagnostics.roche.com/global/en/products/params/elecsys-gdf-15.html (2020). ; Welsh, P. et al. Reference ranges for GDF-15, and risk factors associated with GDF-15, in a large general population cohort. Clin. Chem. Lab. Med. 60, 1820–1829 (2022). (PMID: 35976089952480410.1515/cclm-2022-0135) ; Ramalingam, S. S. et al. Dacomitinib versus erlotinib in patients with advanced-stage, previously treated non-small-cell lung cancer (ARCHER 1009): a randomised, double-blind, phase 3 trial. Lancet Oncol. 15, 1369–1378 (2014). (PMID: 2543969110.1016/S1470-2045(14)70452-8) ; Kim-Muller, J. Y. et al. GDF15 neutralization restores muscle function and physical performance in a mouse model of cancer cachexia. Cell Rep. 42, 111947 (2023). (PMID: 3664032610.1016/j.celrep.2022.111947) ; He, X. et al. Age- and sex-related differences in body composition in healthy subjects aged 18 to 82 years. Medicine 97, e11152 (2018). (PMID: 29924020602380010.1097/MD.0000000000011152) ; Bamia, C., Trichopoulou, A., Lenas, D. & Trichopoulos, D. Tobacco smoking in relation to body fat mass and distribution in a general population sample. Int. J. Obes. 28, 1091–1096 (2004). (PMID: 10.1038/sj.ijo.0802697) ; Sartori, R., Romanello, V. & Sandri, M. Mechanisms of muscle atrophy and hypertrophy: implications in health and disease. Nat. Commun. 12, 330 (2021). (PMID: 33436614780374810.1038/s41467-020-20123-1) ; Bindels, L. B. et al. Increased gut permeability in cancer cachexia: mechanisms and clinical relevance. Oncotarget 9, 18224–18238 (2018). (PMID: 29719601591506810.18632/oncotarget.24804) ; Cal, S. & López-Otín, C. ADAMTS proteases and cancer. Matrix Biol. 44-46, 77–85 (2015). (PMID: 2563653910.1016/j.matbio.2015.01.013) ; de Matos-Neto, E. M. et al. Systemic inflammation in cachexia—is tumor cytokine expression profile the culprit? Front. Immunol. 6, 629 (2015). (PMID: 267323544689790) ; Webster, J. M., Kempen, L. J. A. P., Hardy, R. S. & Langen, R. C. J. Inflammation and skeletal muscle wasting during cachexia. Front. Physiol. 11, 597675 (2020). (PMID: 33329046771076510.3389/fphys.2020.597675) ; Ying, L. et al. IL-17A contributes to skeletal muscle atrophy in lung cancer-induced cachexia via JAK2/STAT3 pathway. Am. J. Physiol. 322, C814–C824 (2022). (PMID: 10.1152/ajpcell.00463.2021) ; Kir, S. et al. Tumour-derived PTH-related protein triggers adipose tissue browning and cancer cachexia. Nature 513, 100–104 (2014). (PMID: 25043053422496210.1038/nature13528) ; Rochette, L., Zeller, M., Cottin, Y. & Vergely, C. Insights into mechanisms of GDF15 and receptor GFRAL: therapeutic targets. Trends Endocrinol. Metab. 31, 939–951 (2020). (PMID: 3317274910.1016/j.tem.2020.10.004) ; Mulderrig, L. et al. Aldehyde-driven transcriptional stress triggers an anorexic DNA damage response. Nature 600, 158–163 (2021). (PMID: 3481966710.1038/s41586-021-04133-7) ; Tsai, V. W., Lin, S., Brown, D. A., Salis, A. & Breit, S. N. Anorexia-cachexia and obesity treatment may be two sides of the same coin: role of the TGF-β superfamily cytokine MIC-1/GDF15. Int J. Obes. 40, 193–197 (2016). (PMID: 10.1038/ijo.2015.242) ; Johnen, H. et al. Tumor-induced anorexia and weight loss are mediated by the TGF-β superfamily cytokine MIC-1. Nat. Med. 13, 1333–1340 (2007). (PMID: 1798246210.1038/nm1677) ; Lerner, L. et al. Plasma growth differentiation factor 15 is associated with weight loss and mortality in cancer patients. J. Cachexia Sarcopenia Muscle 6, 317–324 (2015). (PMID: 26672741467074010.1002/jcsm.12033) ; Tsai, V. W. et al. Treatment with the TGF-β superfamily cytokine MIC-1/GDF15 reduces the adiposity and corrects the metabolic dysfunction of mice with diet-induced obesity. Int J. Obes. 42, 561–571 (2018). (PMID: 10.1038/ijo.2017.258) ; Emmerson, P. J. et al. The metabolic effects of GDF15 are mediated by the orphan receptor GFRAL. Nat. Med. 23, 1215–1219 (2017). (PMID: 2884609810.1038/nm.4393) ; Patel, S. et al. Endogenous GDF15 and FGF21 additively alleviate hepatic steatosis and insulin resistance in obese mice. Preprint at bioRxiv https://doi.org/10.1101/2022.06.08.495255 (2022). ; Schledzewski, K. et al. Deficiency of liver sinusoidal scavenger receptors stabilin-1 and -2 in mice causes glomerulofibrotic nephropathy via impaired hepatic clearance of noxious blood factors. J. Clin. Invest 121, 703–714 (2011). (PMID: 21293057302673510.1172/JCI44740) ; Dewys, W. D., Costa, G. & Henkin, R. I. Clinical parameters related to anorexia. Cancer Treat. Rep. 65, 49–52 (1981). ; Popuri, K., D. Cobzas, N. Esfandiari, et al. Body Composition Assessment in Axial CT Images Using FEM-Based Automatic Segmentation of Skeletal Muscle. IEEE Trans. Med. Imaging 35, 512–520 (2016). ; Ma, D., V. Chow, K. Popuri, et al. Comprehensive Validation of Automated Whole Body Skeletal Muscle, Adipose Tissue, and Bone Segmentation from 3D CT images for Body Composition Analysis: Towards Extended Body Composition. Preprint at https://arxiv.org/abs/2106.00652 (2021). ; Cespedes Feliciano, E. M., Popuri, K., Cobzas, D. et al. Evaluation of automated computed tomography segmentation to assess body composition and mortality associations in cancer patients. J. Cachexia Sarcopenia Muscle 11, 1258–1269 (2020). ; Arribas, L., Sabaté-Llobera, A., Domingo, M.C. et al. Assessing dynamic change in muscle during treatment of patients with cancer: Precision testing standards. Clin. Nutr. 41, 1059–1065 (2022). ; Bridge, C. P., Rosenthal, M., Wright, B. et al. In OR 2.0 Context-Aware Operating Theaters, Computer Assisted Robotic Endoscopy, Clinical Image-Based Procedures, and Skin Image Analysis. (eds. Stoyanov, D. et al.) Fully-Automated Analysis of Body Composition from CT in Cancer Patients Using Convolutional Neural Networks (Springer International Publishing, 2018). ; Magudia, K., Bridge, C. P., Bay, C. P. et al. Population-Scale CT-based Body Composition Analysis of a Large Outpatient Population Using Deep Learning to Derive Age-, Sex-, and Race-specific Reference Curves. Radiology 298, 319–329 (2021). ; Martin, L., Senesse, P., Gioulbasanis, I. et al. Diagnostic Criteria for the Classification of Cancer-Associated Weight Loss. J. Clin. Oncol. 33, 90–99 (2014). ; Rosenthal, R., Cadieux, E. L., Salgado, R. et al. Neoantigen-directed immune escape in lung cancer evolution. Nature 567, 479–485 (2019).
  • Grant Information: R35 CA197449 United States CA NCI NIH HHS; CTRNBC-2022/100001 United Kingdom CRUK_ Cancer Research UK; MR/V033077/1 United Kingdom MRC_ Medical Research Council; CC2041 United Kingdom MRC_ Medical Research Council; CC2041 United Kingdom CRUK_ Cancer Research UK; 25349 United Kingdom CRUK_ Cancer Research UK; 21999 United Kingdom CRUK_ Cancer Research UK; FC001169 United Kingdom ARC_ Arthritis Research UK; CC2041 United Kingdom WT_ Wellcome Trust; 24956 United Kingdom CRUK_ Cancer Research UK; United Kingdom WT_ Wellcome Trust; 17786 United Kingdom CRUK_ Cancer Research UK; 29569 United Kingdom CRUK_ Cancer Research UK; 30025 United Kingdom CRUK_ Cancer Research UK
  • Contributed Indexing: Investigator: TBK Watkins; NJ Birkbak; HJ Aerts; JF Lester; A Bajaj; A Nakas; A Sodha-Ramdeen; K Ang; M Tufail; MF Chowdhry; M Scotland; R Boyles; S Rathinam; C Wilson; D Marrone; S Dulloo; DA Fennell; G Matharu; JA Shaw; J Riley; L Primrose; E Boleti; H Cheyne; M Khalil; S Richardson; T Cruickshank; G Price; KM Kerr; S Benafif; K Gilbert; B Naidu; AJ Patel; A Osman; C Lacson; G Langman; H Shackleford; M Djearaman; S Kadiri; G Middleton; A Leek; JD Hodgkinson; N Totten; A Montero; E Smith; E Fontaine; F Granato; H Doran; J Novasio; K Rammohan; L Joseph; P Bishop; R Shah; S Moss; V Joshi; P Crosbie; F Gomes; K Brown; M Carter; A Chaturvedi; L Priest; P Oliveira; CR Lindsay; FH Blackhall; MG Krebs; Y Summers; A Clipson; J Tugwood; A Kerr; DG Rothwell; E Kilgour; C Dive; RF Schwarz; TL Kaufmann; GA Wilson; R Rosenthal; P Van Loo; Z Szallasi; J Kisistok; M Sokac; M Diossy; J Demeulemeester; A Bunkum; A Stewart; A Magness; A Rowan; A Karamani; B Chain; BB Campbell; C Castignani; C Bailey; C Abbosh; CE Weeden; C Lee; C Richard; CT Hiley; DA Moore; DR Pearce; D Karagianni; D Biswas; D Levi; E Hoxha; EL Cadieux; EL Lim; E Colliver; E Nye; E Grönroos; F Gálvez-Cancino; F Athanasopoulou; F Gimeno-Valiente; G Kassiotis; G Stavrou; G Mastrokalos; H Zhai; HL Lowe; IG Matos; J Goldman; JL Reading; J Herrero; JK Rane; J Nicod; JA Hartley; KS Peggs; KSS Enfield; K Selvaraju; K Thol; K Litchfield; KW Ng; K Chen; K Dijkstra; K Grigoriadis; K Thakkar; L Ensell; M Shah; MV Duran; M Litovchenko; MW Sunderland; MS Hill; M Dietzen; M Leung; M Escudero; M Angelova; M Tanić; M Sivakumar; N Kanu; O Chervova; O Lucas; O Pich; P Hobson; P Pawlik; RK Stone; R Bentham; RE Hynds; R Vendramin; S Saghafinia; S López; S Gamble; SKA Ung; SA Quezada; S Vanloo; S Zaccaria; S Hessey; S Boeing; S Beck; SK Bola; T Denner; T Marafioti; TP Mourikis; V Spanswick; V Barbè; WT Lu; W Hill; WK Liu; Y Wu; Y Naito; Z Ramsden; C Veiga; G Royle; CA Collins-Fekete; F Fraioli; P Ashford; T Clark; MD Forster; SM Lee; E Borg; M Falzon; D Papadatos-Pastos; J Wilson; T Ahmad; AJ Procter; A Ahmed; MN Taylor; A Nair; D Lawrence; D Patrini; N Navani; RM Thakrar; SM Janes; EM Hoogenboom; F Monk; JW Holding; J Choudhary; K Bhakhri; M Scarci; M Hayward; N Panagiotopoulos; P Gorman; R Khiroya; RC Stephens; YNS Wong; S Bandula; A Sharp; S Smith; N Gower; HK Dhanda; K Chan; C Pilotti; R Leslie; A Grapa; H Zhang; K AbdulJabbar; X Pan; Y Yuan; D Chuter; M MacKenzie; S Chee; A Alzetani; J Cave; L Scarlett; J Richards; P Ingram; S Austin; E Lim; P De Sousa; S Jordan; A Rice; H Raubenheimer; H Bhayani; L Ambrose; A Devaraj; H Chavan; S Begum; SI Buderi; D Kaniu; M Malima; S Booth; AG Nicholson; N Fernandes; P Shah; C Proli; M Hewish; S Danson; MJ Shackcloth; L Robinson; P Russell; KG Blyth; C Dick; J Le Quesne; A Kirk; M Asif; R Bilancia; N Kostoulas; M Thomas
  • Substance Nomenclature: 0 (MAGEA6 protein, human) ; 0 (Antigens, Neoplasm) ; 0 (Neoplasm Proteins)
  • Entry Date(s): Date Created: 20230412 Date Completed: 20230421 Latest Revision: 20240607
  • Update Code: 20240607
  • PubMed Central ID: PMC7614477

Klicken Sie ein Format an und speichern Sie dann die Daten oder geben Sie eine Empfänger-Adresse ein und lassen Sie sich per Email zusenden.

oder
oder

Wählen Sie das für Sie passende Zitationsformat und kopieren Sie es dann in die Zwischenablage, lassen es sich per Mail zusenden oder speichern es als PDF-Datei.

oder
oder

Bitte prüfen Sie, ob die Zitation formal korrekt ist, bevor Sie sie in einer Arbeit verwenden. Benutzen Sie gegebenenfalls den "Exportieren"-Dialog, wenn Sie ein Literaturverwaltungsprogramm verwenden und die Zitat-Angaben selbst formatieren wollen.

xs 0 - 576
sm 576 - 768
md 768 - 992
lg 992 - 1200
xl 1200 - 1366
xxl 1366 -