RESUMEN
This study investigates the association of PD-L1 expression and immune cell infiltrates and their impact on clinical outcome, in addition to their overlap with microsatellite instability (MSI), HER2 and ATM molecular subgroups of gastric cancer (GC). PD-L1 membrane expression on tumour cells (TC) and infiltrating immune cells (IC), CD3 + T-lymphocytes, CD8+ cytotoxic T-cells, ATM and HER2 were assessed by immunohistochemistry (IHC) in the ACRG (Asian Cancer Research Group) GC cohort (N = 380). EBV status was determined using in situ hybridization and MSI status was performed using PCR and MLH1 IHC. The PD-L1 segment was associated with increased T-cell infiltrates, while the MSI-high segment was enriched for PD-L1, CD3, and CD8. Multivariate analysis confirmed PD-L1 positivity, high CD3 and high CD8 as independent prognostic factors for both disease-free survival and overall survival (all p < 0.05). Patients with MSI-high tumours had better overall survival by both univariate and multivariate analysis. The ATM-low and HER2-high subgroups differed markedly in their immune profile; the ATM-low subgroups enriched for MSI, PD-L1 positivity and CD8 + T-cells, while the HER2 segment was enriched for MSS, with no enrichment for immune markers. Hence, we demonstrate a molecular profiling approach that can divide GC into four molecular subgroups, namely ATM-low, HER2-high, PD-L1 positive and MSI-high with differing levels of immune infiltrates and prognostic significance which may help to stratify patients for response to targeted therapies.
RESUMEN
BACKGROUND: Several studies in colorectal cancer (CRC) indicate a relationship between tumour immune infiltrates and clinical outcome. We tested the utility of a digital pattern recognition-based image analysis (DPRIA) system to segregate tissue regions and facilitate automated quantification of immune infiltrates in CRC. METHODS: Primary CRC with matched hepatic metastatic (n=7), primary CRC alone (n=18) and primary CRC with matched normal (n=40) tissue were analysed immunohistochemically. Genie pattern recognition software was used to segregate distinct tissue regions in combination with image analysis algorithms to quantify immune cells. RESULTS: Immune infiltrates were observed predominately at the invasive margin. Quantitative image analysis revealed a significant increase in the prevalence of Foxp3 (P<0.0001), CD8 (P<0.0001), CD68 (<0.0001) and CD31 (<0.0001) positive cells in the stroma of primary and metastatic CRC, compared with tumour cell mass. A direct comparison between non-metastatic primary CRC (MET-) and primary CRC that resulted in metastasis (MET+) showed an immunosuppressive phenotype, with elevated Foxp3 (P<0.05) and reduced numbers of CD8 (P<0.05) cells in the stroma of MET+ compared with MET- samples. CONCLUSION: By combining immunohistochemistry with DPRIA, we demonstrate a potential metastatic phenotype in CRC. Our study accelerates wider acceptance and use of automated systems as an adjunct to traditional histopathological techniques.
