Elevated X-linked inhibitor of apoptosis protein (XIAP) expression uncovers detrimental prognosis in subgroups of neoadjuvant treated and T-cell rich esophageal adenocarcinoma

Lars M. Schiffmann†Email author View ORCID ID profile,
Heike Göbel†,
Heike Löser,
Fabian Schorn,
Jan Paul Werthenbach,
Hans F. Fuchs,
Patrick S. Plum,
Marc Bludau,
Thomas Zander,
Wolfgang Schröder,
Christiane J. Bruns,
Hamid Kashkar,
Alexander Quaas† and
Florian Gebauer†

†Contributed equally

BMC Cancer201919:531

https://doi.org/10.1186/s12885-019-5722-1

Received: 19 February 2019
Accepted: 16 May 2019
Published: 31 May 2019

Open Peer Review reports

Abstract

Background

Molecular markers predicting survival in esophageal adenocarcinoma (EAC) are rare. Specifically, in favorable oncologic situations, e.g. nodal negativity or major neoadjuvant therapy response, there is a lack of additional risk factors that serve to predict patients’ outcome more precisely. This study evaluated X-linked inhibitor of apoptosis protein (XIAP) as a potential marker improving outcome prediction.

Methods

Tissue microarrays from 362 patients that were diagnosed with resectable EAC were included in the study. XIAP was stained by immunohistochemistry and correlated to clinical outcome, molecular markers and markers of the cellular tumor microenvironment.

Results

XIAP did not impact on overall survival (OS) in the whole study collective. Subgroup analyses stratifying for common genetic markers (TP53, ERBB2, ARID1A/SWI/SNF) did not disclose any impact of XIAP expression on survival. Detailed subgroup analyses of [1] nodal negative patients, [2] highly T-cell infiltrated tumors and [3] therapy responders to neoadjuvant treatment revealed a significant inverse role of high XIAP expression in these specific oncologic situations; elevated XIAP expression detrimentally affected patients’ outcome in these subgroups. [1]: OS XIAP low: 202 months (m) vs. XIAP high: 38 m; [2]: OS 116 m vs. 28.2 m; [3]: OS 31 m vs. 4 m).

Conclusions

Our data suggest XIAP expression in EAC as a worthy tool to improve outcome prediction in specific oncologic settings that might directly impact on clinical diagnosis and treatment of EAC in the future.