Efforts to address the poor prognosis associated with esophageal adenocarcinoma (EAC) have been hampered by a lack of biomarkers to identify early disease and therapeutic targets. Despite extensive efforts to understand the somatic mutations associated with EAC over the past decade, a gap remains in understanding how the atlas of genomic aberrations in this cancer impacts the proteome and which somatic variants are of importance for the disease phenotype. We performed a quantitative proteomic analysis of 23 EACs and matched adjacent normal esophageal and gastric tissues. We explored the correlation of transcript and protein abundance using tissue-matched RNA-seq and proteomic data from seven patients and further integrated these data with a cohort of EAC RNA-seq data (n = 264 patients), EAC whole-genome sequencing (n = 454 patients), and external published datasets. We quantified protein expression from 5879 genes in EAC and patient-matched normal tissues. Several biomarker candidates with EAC-selective expression were identified, including the transmembrane protein GPA33. We further verified the EAC-enriched expression of GPA33 in an external cohort of 115 patients and confirm this as an attractive diagnostic and therapeutic target. To further extend the insights gained from our proteomic data, an integrated analysis of protein and RNA expression in EAC and normal tissues revealed several genes with poorly correlated protein and RNA abundance, suggesting posttranscriptional regulation of protein expression. These outlier genes, including SLC25A30, TAOK2, and AGMAT, only rarely demonstrated somatic mutation, suggesting post-transcriptional drivers for this EAC-specific phenotype. AGMAT was demonstrated to be overexpressed at the protein level in EAC compared to adjacent normal tissues with an EAC-selective, post-transcriptional mechanism of regulation of protein abundance proposed. Integrated analysis of proteome, transcriptome, and genome in EAC has revealed several genes with tumor-selective, posttranscriptional regulation of protein expression, which may be an exploitable vulnerability.

Cambridge Oesophagogastric Centre Addenbrooke's Hospital Cambridge United Kingdom; Institute of Genetics and Cancer University of Edinburgh Edinburgh Scotland

Clinical Department of Laboratory Medicine Proteomics Core Facility Medical University Vienna Vienna Austria; Bruker Austria Wien Austria

Department of Pathology Royal Infirmary of Edinburgh Edinburgh United Kingdom

Department of Pharmacology and Public Health Faculty of Medicine The Hashemite University Zarqa Jordan

Edinburgh Pathology Institute of Genetics and Cancer University of Edinburgh Edinburgh Scotland

Institute of Genetics and Cancer University of Gdansk Gdansk Poland

International Center for Cancer Vaccine Science University of Gdansk Gdansk Poland

International Center for Cancer Vaccine Science University of Gdansk Gdansk Poland; Institute for Adaptive and Neural Computation School of Informatics University of Edinburgh Edinburgh UK; International Centre for Cancer Vaccine Science University of Gdańsk Gdańsk Poland; Department of Biochemistry and Microbiology University of Victoria Victoria Canada; The Canadian Association for Responsible AI in Medicine Victoria BC Canada

Research Centre for Applied Molecular Oncology Masaryk Memorial Cancer Institute Brno Czech Republic

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Bray F., Ferlay J., Soerjomataram I., Siegel R.L., Torre L.A., Jemal A. Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA. Cancer J. Clin. 2018;68:394–424. PubMed

Then E.O., Lopez M., Saleem S., Gayam V., Sunkara T., Culliford A., et al. Esophageal cancer: an updated surveillance epidemiology and end results database analysis. World J. Oncol. 2020;11:55–64. PubMed PMC

Edgren G., Adami H.-O., Weiderpass E., Nyrén O., Nyrén O. A global assessment of the oesophageal adenocarcinoma epidemic. Gut. 2013;62:1406–1414. PubMed

Killcoyne S., Fitzgerald R.C. Evolution and progression of Barrett’s oesophagus to oesophageal cancer. Nat. Rev. Cancer. 2021;21:731–741. PubMed

Rahman S.A., Walker R.C., Maynard N., Trudgill N., Crosby T., Cromwell D.A., et al. The AUGIS survival predictor: prediction of long-term and conditional survival after esophagectomy using random survival forests. Ann. Surg. 2021;277:267–274. PubMed PMC

Thrift A.P. The epidemic of oesophageal carcinoma: where are we now? Cancer Epidemiol. 2016;41:88–95. PubMed

Pilonis N.D., Killcoyne S., Tan W.K., O'Donovan M., Malhotra S., Tripathi M., et al. Use of a Cytosponge biomarker panel to prioritise endoscopic Barrett’s oesophagus surveillance: a cross-sectional study followed by a real-world prospective pilot. Lancet Oncol. 2022;23:270–278. PubMed PMC

Al-Batran S.-E., Homann N., Pauligk C., Goetze T.O., Meiler J., Kasper S., et al. Perioperative chemotherapy with fluorouracil plus leucovorin, oxaliplatin, and docetaxel versus fluorouracil or capecitabine plus cisplatin and epirubicin for locally advanced, resectable gastric or gastro-oesophageal junction adenocarcinoma (FLOT4): a randomised, phase 2/3 trial. Lancet. 2019;393:1948–1957. PubMed

Coleman H.G., Xie S.-H., Lagergren J. The epidemiology of esophageal adenocarcinoma. Gastroenterology. 2018;154:390–405. PubMed

Chen J., Jiang Y., Chang T.S., Rubenstein J.H., Kwon R.S., Wamsteker E.J., et al. Detection of Barrett’s neoplasia with a near-infrared fluorescent heterodimeric peptide. Endoscopy. 2022;54:1198–1204. PubMed PMC

Frankell A.M., Jammula S., Li X., Contino G., Killcoyne S., Abbas S., et al. The landscape of selection in 551 esophageal adenocarcinomas defines genomic biomarkers for the clinic. Nat. Genet. 2019;51:506–516. PubMed PMC

O’Neill J.R. An overview of mass spectrometry-based methods for functional proteomics. Methods Mol. Biol. 2019;1871:179–196. PubMed

O’Neill J.R., Pak H.S., Pairo-Castineira E., Save V., Paterson-Brown S., Nenutil R., et al. Quantitative shotgun proteomics unveils candidate novel esophageal adenocarcinoma (EAC)-specific proteins. Mol. Cell. Proteomics. 2017;16:1138–1150. PubMed PMC

Kim J. Integrated genomic characterization of oesophageal carcinoma. Nature. 2017;541:169–175. PubMed PMC

Dai J.Y., Wang X., Buas M.F., Zhang C., Ma J., Wei B., et al. Whole-genome sequencing of esophageal adenocarcinoma in Chinese patients reveals distinct mutational signatures and genomic alterations. Commun. Biol. 2018;1:1–9. PubMed PMC

Bratlie S.O., Wallenius V., Edebo A., Fändriks L., Casselbrant A. Proteomic approach to the potential role of angiotensin II in Barrett dysplasia. Proteomics Clin. Appl. 2019;13 PubMed

Weke K., Singh A., Uwugiaren N., Alfaro J.A., Wang T., Hupp T.R., et al. MicroPOTS analysis of Barrett’s esophageal cell line models identifies proteomic changes after physiologic and radiation stress. J. Proteome Res. 2021;20:2195–2205. PubMed PMC

Kessner D., Chambers M., Burke R., Agus D., Mallick P. ProteoWizard: open source software for rapid proteomics tools development. Bioinformatics. 2008;24:2534–2536. PubMed PMC

Kim S., Pevzner P.A. MS-GF+ makes progress towards a universal database search tool for proteomics. Nat. Commun. 2014;5:5277. PubMed PMC

Ivanov M.V., Levitsky L.I., Bubis J.A., Gorshkov M.V. Scavager: a versatile postsearch validation algorithm for shotgun proteomics based on gradient boosting. Proteomics. 2019;19 PubMed

Röst H.L., Schmitt U., Aebersold R., Malmström L. pyOpenMS: a Python-based interface to the OpenMS mass-spectrometry algorithm library. Proteomics. 2014;14:74–77. PubMed

Benjamini Y., Yekutieli D. The control of the false discovery rate in multiple testing under dependency. Ann. Stat. 2001;29:1165–1188.

Wang D., Eraslan B., Wieland T., Hallström B., Hopf T., Zolg D.P., et al. A deep proteome and transcriptome abundance atlas of 29 healthy human tissues. Mol. Syst. Biol. 2019;15 PubMed PMC

Jiang L., Wang M., Lin S., Jian R., Li X., Chan J., et al. A quantitative proteome map of the human body. Cell. 2020;183:269–283.e19. PubMed PMC

Consortium T. Gte. The GTEx Consortium atlas of genetic regulatory effects across human tissues. Science. 2020;369:1318–1330. PubMed PMC

Robinson M.D., Oshlack A. A scaling normalization method for differential expression analysis of RNA-seq data. Genome Biol. 2010;11:R25. PubMed PMC

Auton A., Auton A., Brooks L.D., Durbin R.M., Garrison E.P., Kang H.M., et al. A global reference for human genetic variation. Nature. 2015;526:68–74. PubMed PMC

Kandoth C., Gao J., qwangmsk, Mattioni M., Struck A., Boursin Y., et al. mskcc/vcf2maf: vcf2maf v1.6.16 (v1.6.16) Zenodo. 2018 doi: 10.5281/zenodo.1185418. DOI

Heath J.K., White S.J., Johnstone C.N., Catimel B., Simpson R.J., Moritz R.L., et al. The human A33 antigen is a transmembrane glycoprotein and a novel member of the immunoglobulin superfamily. Proc. Natl. Acad. Sci. U. S. A. 1997;94:469–474. PubMed PMC

van Niel G., Raposo G., Candalh C., Boussac M., Hershberg R., Cerf-Bensussan N., et al. Intestinal epithelial cells secrete exosome-like vesicles. Gastroenterology. 2001;121:337–349. PubMed

Owen R.P., White M.J., Severson D.T., Braden B., Bailey A., Goldin R., et al. Single cell RNA-seq reveals profound transcriptional similarity between Barrett’s oesophagus and oesophageal submucosal glands. Nat. Commun. 2018;9:4261. PubMed PMC

Maunoury R., Robine S., Pringault E., Léonard N., Gaillard J.A., Louvard D. Developmental regulation of villin gene expression in the epithelial cell lineages of mouse digestive and urogenital tracts. Development. 1992;115:717–728. PubMed

Nowicki-Osuch K., Zhuang L., Jammula S., Bleaney C.W., Mahbubani K.T., Devonshire G., et al. Molecular phenotyping reveals the identity of Barrett’s esophagus and its malignant transition. Science. 2021;373:760–767. PubMed

Liu Y.-Q., Chu L.Y., Yang T., Zhang B., Zheng Z.T., Xie J.J., et al. Serum DSG2 as a potential biomarker for diagnosis of esophageal squamous cell carcinoma and esophagogastric junction adenocarcinoma. Biosci. Rep. 2022;42 PubMed PMC

Pavlov K., Honing J., Meijer C., Boersma-van Ek W., Peters F.T.M., van den Berg A., et al. GATA6 expression in Barrett’s oesophagus and oesophageal adenocarcinoma. Dig. Liver Dis. 2015;47:73–80. PubMed

Dai Y., Wang Q., Gonzalez Lopez A., Anders M., Malfertheiner P., Vieth M., et al. Genome-wide analysis of Barrett’s adenocarcinoma. A first step towards identifying patients at risk and developing therapeutic paths. Transl. Oncol. 2018;11:116–124. PubMed PMC

Scanlan M.J., Simpson A.J.G., Old L.J. The cancer/testis genes: review, standardization, and commentary. Cancer Immun. 2004;4:1. PubMed

Tang W.-W., Liu Z.-H., Yang T.-X., Wang H.-J., Cao X.-F. Upregulation of MAGEA4 correlates with poor prognosis in patients with early stage of esophageal squamous cell carcinoma. Oncotargets Ther. 2016;9:4289–4293. PubMed PMC

Zhang Y., Zhang Y., Zhang L. Expression of cancer–testis antigens in esophageal cancer and their progress in immunotherapy. J. Cancer Res. Clin. Oncol. 2019;145:281–291. PubMed PMC

Hong D.S., Jalal S.I., Elimova E., Ajani J.A., Murphy M.A.B., Cervantes A., Evans T.R.J., et al. SURPASS-2 trial design: a phase 2, open-label study of ADP-A2M4CD8 SPEAR T cells in advanced esophageal or esophagogastric junction cancers. J Clin Oncol. 2022;40:TPS363.

Hammer N.A., Hansen T.V.O., Byskov A.G., Rajpert-De Meyts E., Grøndahl M.L., Bredkjaer H.E., et al. Expression of IGF-II mRNA-binding proteins (IMPs) in gonads and testicular cancer. Reproduction. 2005;130:203–212. PubMed

Chen H.-M., Lin C.C., Chen W.S., Jiang J.K., Yang S.H., Chang S.C., et al. Insulin-like growth factor 2 mRNA-binding protein 1 (IGF2BP1) is a prognostic biomarker and associated with chemotherapy responsiveness in colorectal. Cancer Int. J. Mol. Sci. 2021;22:6940. PubMed PMC

Schwanhäusser B., Busse D., Li N., Dittmar G., Schuchhardt J., Wolf J., et al. Global quantification of mammalian gene expression control. Nature. 2011;473:337–342. PubMed

Yang F., Cai S., Ling L., Zhang H., Tao L., Wang Q. Identification of a five-gene prognostic model and its potential drug repurposing in colorectal cancer based on TCGA, GTEx and GEO databases. Front. Genet. 2020;11:622659. PubMed PMC

Thul P.J., Åkesson L., Wiking M., Mahdessian D., Geladaki A., Ait Blal H., et al. A subcellular map of the human proteome. Science. 2017;356 PubMed

Shibata Y., Haruki N., Kuwabara Y., Ishiguro H., Shinoda N., Sato A., et al. Chfr expression is downregulated by CpG island hypermethylation in esophageal cancer. Carcinogenesis. 2002;23:1695–1699. PubMed

Soutto M., Peng D., Razvi M., Ruemmele P., Hartmann A., Roessner A., et al. Epigenetic and genetic silencing of CHFR in esophageal adenocarcinomas. Cancer. 2010;116:4033–4042. PubMed PMC

Shan L., Zhao M., Lu Y., Ning H., Yang S., Song Y., et al. CENPE promotes lung adenocarcinoma proliferation and is directly regulated by FOXM1. Int. J. Oncol. 2019;55:257–266. PubMed

Zhu X., Luo X., Feng G., Huang H., He Y., Ma W., et al. CENPE expression is associated with its DNA methylation status in esophageal adenocarcinoma and independently predicts unfavorable overall survival. PLoS One. 2019;14 PubMed PMC

Wilhelm M., Schlegl J., Hahne H., Gholami A.M., Lieberenz M., Savitski M.M., et al. Mass-spectrometry-based draft of the human proteome. Nature. 2014;509:582–587. PubMed

Eraslan B., Wang D., Gusic M., Prokisch H., Hallström B.M., Uhlén M., et al. Quantification and discovery of sequence determinants of protein-per-mRNA amount in 29 human tissues. Mol. Syst. Biol. 2019;15 PubMed PMC

Edfors F., Danielsson F., Hallström B.M., Käll L., Lundberg E., Pontén F., et al. Gene-specific correlation of RNA and protein levels in human cells and tissues. Mol. Syst. Biol. 2016;12:883. PubMed PMC

Zhu H., Yin J., Chen D., He S., Chen H. Agmatinase promotes the lung adenocarcinoma tumorigenesis by activating the NO-MAPKs-PI3K/Akt pathway. Cell Death Dis. 2019;10:1–15. PubMed PMC

Secrier M., Li X., de Silva N., Eldridge M.D., Contino G., Bornschein J., et al. Mutational signatures in esophageal adenocarcinoma define etiologically distinct subgroups with therapeutic relevance. Nat. Genet. 2016;48:1131–1141. PubMed PMC

Zhou R.-B., Lu X.-L., Zhang C.-Y., Yin D.-C. RNA binding motif protein 3: a potential biomarker in cancer and therapeutic target in neuroprotection. Oncotarget. 2017;8:22235–22250. PubMed PMC

Jonsson L., Hedner C., Gaber A., Korkocic D., Nodin B., Uhlén M., et al. High expression of RNA-binding motif protein 3 in esophageal and gastric adenocarcinoma correlates with intestinal metaplasia-associated tumours and independently predicts a reduced risk of recurrence and death. Biomark. Res. 2014;2:11. PubMed PMC

Garinchesa P., Sakamoto J., Welt S., Real F., Rettig W., Old L. Organ-specific expression of the colon cancer antigen A33, a cell surface target for antibody-based therapy. Int. J. Oncol. 1996;9:465–471. PubMed

Wu Z., Guo H.-F., Xu H., Cheung N.-K.V. Development of a tetravalent anti-GPA33/anti-CD3 bispecific antibody for colorectal cancers. Mol. Cancer Ther. 2018;17:2164–2175. PubMed PMC

Moore P.A., Shah K., Yang Y., Alderson R., Roberts P., Long V., et al. Development of MGD007, a gpA33 x CD3-bispecific DART protein for T-cell immunotherapy of metastatic colorectal cancer. Mol. Cancer Ther. 2018;17:1761–1772. PubMed

Infante J.R., Bendell J.C., Goff L.W., Jones S.F., Chan E., Sudo T., et al. Safety, pharmacokinetics and pharmacodynamics of the anti-A33 fully-human monoclonal antibody, KRN330, in patients with advanced colorectal cancer. Eur. J. Cancer. 2013;49:1169–1175. PubMed

Opstelten R., de Kivit S., Slot M.C., van den Biggelaar M., Iwaszkiewicz-Grześ D., Gliwiński M., et al. GPA33: a marker to identify stable human regulatory T cells. J. Immunol. 2020;204:3139–3148. PubMed

Buccitelli C., Selbach M. mRNAs, proteins and the emerging principles of gene expression control. Nat. Rev. Genet. 2020;21:630–644. PubMed

Kosti I., Jain N., Aran D., Butte A.J., Sirota M. Cross-tissue analysis of gene and protein expression in normal and cancer tissues. Sci. Rep. 2016;6 PubMed PMC

Liu Y., Beyer A., Aebersold R. On the dependency of cellular protein levels on mRNA abundance. Cell. 2016;165:535–550. PubMed

Cheung H.C., Hai T., Zhu W., Baggerly K.A., Tsavachidis S., Krahe R., et al. Splicing factors PTBP1 and PTBP2 promote proliferation and migration of glioma cell lines. Brain. 2009;132:2277–2288. PubMed PMC

Rochette L., Meloux A., Zeller M., Malka G., Cottin Y., Vergely C. Mitochondrial SLC25 carriers: novel targets for cancer therapy. Molecules. 2020;25:2417. PubMed PMC

Maru D.M., Singh R.R., Hannah C., Albarracin C.T., Li Y.X., Abraham R., et al. MicroRNA-196a is a potential marker of progression during Barrett’s metaplasia-dysplasia-invasive adenocarcinoma sequence in esophagus. Am. J. Pathol. 2009;174:1940–1948. PubMed PMC

Zaidi A.H., Gopalakrishnan V., Kasi P.M., Zeng X., Malhotra U., Balasubramanian J., et al. Evaluation of a 4-protein serum biomarker panel-biglycan, annexin-A6, myeloperoxidase, and protein S100-A9 (B-AMP)-for the detection of esophageal adenocarcinoma. Cancer. 2014;120:3902–3913. PubMed PMC

Koul H.K., Pal M., Koul S. Role of p38 MAP kinase signal transduction in solid tumors. Genes Cancer. 2013;4:342–359. PubMed PMC

Zou X., Blank M. Targeting p38 MAP kinase signaling in cancer through post-translational modifications. Cancer Lett. 2017;384:19–26. PubMed

Salazar C., Barros M., Elorza A.A., Ruiz L.M. Dynamic distribution of HIG2A between the mitochondria and the nucleus in response to hypoxia and oxidative stress. Int. J. Mol. Sci. 2021;23:389. PubMed PMC

Schöbinger M., Klein O.-J., Mitulović G. Low-temperature mobile phase for peptide trapping at elevated separation temperature prior to nano RP-HPLC-MS/MS. Separations. 2016;3:6.

Tóth G., Panić-Janković T., Mitulović G. Pillar array columns for peptide separations in nanoscale reversed-phase chromatography. J Chromatogr A. 2019;1603:426–432. PubMed

Rice T.W., Gress D.M., Patil D.T., Hofstetter W.L., Kelsen D.P., Blackstone E.H. Cancer of the esophagus and esophagogastric junction-major changes in the American Joint Committee on Cancer eighth edition cancer staging manual. CA Cancer J Clin. 2017;67:304–317. PubMed