Dataset Information

The adaptive immune and immune checkpoint landscape of neoadjuvant treated esophageal adenocarcinoma using digital pathology quantitation.

ABSTRACT:

Background

Limited studies examine the immune landscape in Esophageal Adenocarcinoma (EAC). We aim to identify novel associations, which may inform immunotherapy treatment stratification.

Methods

Three hundred twenty-nine EAC cases were available in Tissue Microarrays (TMA) format. A discovery cohort of 166 EAC cases were stained immunohistochemically for range of adaptive immune (CD3, CD4, CD8 and CD45RO) and immune checkpoint biomarkers (ICOS, IDO-1, PD-L1, PD-1). A validation cohort of 163 EAC cases was also accessed. A digital pathology analysis approach was used to quantify biomarker density.

Results

CD3, CD4, CD8, CD45RO, ICOS and PD-1 were individually predictive of better overall survival (OS) (Log rank p = < 0.001; p = 0.014; p = 0.001; p = < 0.001; p = 0.008 and p = 0.026 respectively). Correlation and multivariate analysis identified high CD45RO/ICOS patients with significantly improved OS which was independently prognostic (HR = 0.445, (0.223-0.886), p = 0.021). Assessment of CD45RO and ICOS high cases in the validation cohort revealed an associated with improved OS (HR = 0.601 (0.363-0.996), p = 0.048). Multiplex IHC identified cellular co-expression of high CD45RO/ICOS. High CD45RO/ICOS patients have significantly improved OS.

Conclusions

Multiplexing identifies true cellular co-expression. These data demonstrate that co-expression of immune biomarkers are associated with better outcome in EAC and may provide evidence for immunotherapy treatment stratification.

SUBMITTER: Humphries MP

PROVIDER: S-EPMC7268770 | biostudies-literature | 2020 Jun

REPOSITORIES: biostudies-literature

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Publications

The adaptive immune and immune checkpoint landscape of neoadjuvant treated esophageal adenocarcinoma using digital pathology quantitation.

Humphries Matthew P MP Craig Stephanie G SG Kacprzyk Rafal R Fisher Natalie C NC Bingham Victoria V McQuaid Stephen S Murray Graeme I GI McManus Damian D Turkington Richard C RC James Jacqueline J Salto-Tellez Manuel M

BMC cancer 20200601 1

<h4>Background</h4>Limited studies examine the immune landscape in Esophageal Adenocarcinoma (EAC). We aim to identify novel associations, which may inform immunotherapy treatment stratification.<h4>Methods</h4>Three hundred twenty-nine EAC cases were available in Tissue Microarrays (TMA) format. A discovery cohort of 166 EAC cases were stained immunohistochemically for range of adaptive immune (CD3, CD4, CD8 and CD45RO) and immune checkpoint biomarkers (ICOS, IDO-1, PD-L1, PD-1). A validation c ...[more]

PMID: 32487090

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Project description:BackgroundWe aimed to investigate clinical implications of specific soluble immune checkpoint molecules (sICMs) in locally advanced rectal cancer (LARC) patients treated with neoadjuvant chemoradiotherapy (nCRT).MethodsWe prospectively enrolled 30 LARC patients treated with nCRT and collected blood samples from them before, during, and after nCRT for prospective studies. Immune checkpoints often refer to T cell surface molecules influencing the immune response. Immune checkpoints, in the form of a soluble monomeric form, is widely present in blood. In the study, eight immune checkpoint-related plasma proteins, including programmed death-ligand 1 (PD-L1), CD80, CD86, CD28, CD27, glucocorticoid-induced tumor necrosis factor receptor (GITR), GITR ligand (GITRL), and inducible T-cell costimulator (ICOS), were measured using the Luminex platform. Two independent pathologists categorized patients as the good responders and the poor responders according to Dworak tumor regression grade (TRG).ResultsOf the 30 patients, the levels of sPD-L1, sCD80, sCD86, sCD28, sGITR, sGITRL, sCD27, and sICOS decreased during nCRT (Pre-nCRT vs. During-nCRT, all p<0.05) but were restored after nCRT treatment (Pre-nCRT vs. Post-nCRT, all p>0.05). In the 14 good responders, the levels of sICMs, other than sGITR (p=0.081) and sGITRL (p=0.071), decreased significantly during nCRT (Pre-nCRT vs. During-nCRT, p<0.05), but they were all significantly increased after nCRT (During-nCRT vs. Post-nCRT, all p<0.05). In the 16 poor responders, only sCD80 was significantly reduced during nCRT (Pre-nCRT vs. During-nCRT, p<0.05), and none was significantly increased after nCRT (During-nCRT vs. Post-nCRT, all p<0.05). High levels of sICMs before nCRT were associated with poor response (all OR≥1). The Pre-model that incorporated the 8 sICMs before nCRT yielded a good predictive value (AUC, 0.848) and was identified as an independent predictor of treatment response (OR, 2.62; 95% CI, 1.11-6.18; p=0.027).ConclusionOur results suggest chemoradiotherapy could influence the change of sPD-L1, sCD80, sCD86, sCD28, sGITR, sGITRL, sCD27, and sICOS in patients with LARC. The levels of the majority of soluble immune checkpoint molecules were reduced during nCRT and then restored at the end of nCRT, particularly in patients who responded well to nCRT. Combined baseline sICMs can be developed to predict treatment response.

Dataset Information

The adaptive immune and immune checkpoint landscape of neoadjuvant treated esophageal adenocarcinoma using digital pathology quantitation.

Background

Methods

Results

Conclusions

Publications

The adaptive immune and immune checkpoint landscape of neoadjuvant treated esophageal adenocarcinoma using digital pathology quantitation.

Similar Datasets

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