Classification of esophageal adenocarcinoma into subgroups that are associated with patient survival using RNA-seq and immunohistochemistry.

Journal of Clinical Oncology(2022)

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摘要
e16028 Background: : Prognosis of oesophageal adenocarcinoma (OAC) remains poor globally. Traditional histopathology classifications have minimal impact on clinical management and outcomes. To improve patient outcomes, prognostic and therapeutic stratification is required within this cohort of morphologically homogenous cancers. Identification and validation of candidate prognostic and therapeutic biomarkers may contribute to personalisation of therapy for patients with OAC. Methods: We used RNAseq of OAC tumour tissues to classify OAC into subgroups which were associated with patient survival and the immune infiltrate in the tumour micro-environment. We identified genes that discriminate each group and selected thirteen to perform IHC against the protein products of these genes using the same OAC samples. The IHC markers that best discriminate the immune-clusters were applied to an independent set of OAC in tissue micro-arrays (TMAs) to validate the prognostic significance of the immune-clusters. Results: Using RNA-seq we identified four candidate immune-clusters namely, immune hot, immune cold, immune suppressed and immune moderate, that correlate with progression free and overall patient survival. IHC revealed a correlation of five of thirteen of these IHC markers with the RNAseq data, and the IHC was able to corroborate the classification of OAC immune-clusters. The best markers predictive of these immune-clusters underwent IHC in an independent OAC TMA cohort to confirm the prognostic significance of these markers. The TMAs contain matched primary and nodal disease, so we will also report on the presence of the four subgroups within nodal disease. To date, two of the IHC markers are associated with survival benefit in the TMAs patient group. Conclusions: We anticipate that validating IHC markers to reliably identify the four immune-clusters of OAC will be useful in predicting prognosis, survival and therapeutic classification of OAC in precision oncology of the OAC.
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