Researchers have compared the tumour immune microenvironments (TIMEs) of primary gastric cancers and found distinct patterns between primary and metastatic lesions.
There are around 6,600 new stomach cancer cases every year in the UK. Palliative system therapy is one of the main treatment options for patients with metastatic gastric cancer (MGC). The therapy aims to alleviate disease-related symptoms and improve overall survival. Nevertheless, the prognosis for MGC patients is still very poor. Individuals with MGC have an overall survival rate of less than 2 years.
Advancements in immune checkpoint inhibitors (ICI), such as anti-programmed cell death 1 (PD-1) and anti-programmed death-ligand 1 (PD-L1), have revolutionised the treatment of solid tumours. Anti-PD-1 antibodies, including nivolumab and pembrolizumab, have provided significant benefits and alternative options for patients with MGC. However, in patients previously treated for MGC, the overall response rate for anti-PD-1 antibodies is low. In fact, most patients do not response to these ICIs. Whilst there are no definite predictive biomarkers, PD-L1 expression, DNA mismatch repair (MMR) and Epstein-Barr virus (EBV) status have been proposed as potential biomarkers for ICI response in MGC patients. In addition, researchers have reported high levels of tumour-infiltrating lymphocytes as a favourable prognostic marker.
Comparing tumour immune microenvironments
For patients with MGC who have previously received cytotoxic or molecularly targeted therapies, oncologists often give anti-PD-1 treatment. Evaluating immune-related biomarkers before starting anti-PD-1 treatment is important to determine therapy response. However, taking a biopsy again from metastatic lesions is not always feasible. Therefore, researchers typically assess immune-related biomarkers for MGC based on TIME of PGC specimens, prior to recurrence or at the time of initial diagnosis. Yet, PGC specimens do not accurately reflect the TIME of MGCs during metastasis, disease progression or after previous therapy. There have been no reports regarding the evaluation of immune-related biomarkers in MGC specimens.
In this study, published in Scientific Reports, the team compared the TIMEs of primary and paired MGCs. This included T-cell density, PD-L1 expression, MMR status, EBV positivity and immune-related gene expression. They also evaluated the prognostic impact of tumour-infiltrating T cells in primary (PGC) and metastatic tumours in gastric cancer patients.
Distinct tumour immune microenvironments
The team enrolled 23 patients who underwent surgical treatment for PGC and MGC. The researchers observed PD-L1 positivity in 52.2% of PGC cases and 4.3% of MGC cases. They detected MMR deficiency more frequently in PGC (8.7%) than in paired MGC (4.3%). The team did not find EBV in 46 PGC and MGC specimens from 23 patients. Researchers also found that CD8+ T-cell, PD-L1+ cell, and PD-L1+CK+ cell densities were significantly lower in MGC than PGC. They then categorised specimens based on CD8+ T-cell density and distribution within the tumour microenvironment. Researchers found that the most frequent TIME types were ‘inflamed’ (34.8%) and ‘adaptive immune resistance’ (34.8%) in PGC, and ‘immune desert’ (65.2%) and ‘immunological ignorance’ (73.9%) in MGC. Transcriptomic analysis also revealed that the T-cell inflamed gene set and co-stimulatory gene module were down-regulated in MGC compared to PGC.
This study is the first to evaluate TIME differences between primary and metastatic gastric cancers. The results suggest that the TIMEs of metastatic gastric tumours are less immunologically active than that of primary tumours. The team suggest that differences may be due to the immune escape mechanism of metastatic tumours and the selection pressure on tumours during disease progression or previous therapy. Therefore, it is important to evaluate immune-related biomarkers in metastatic and primary tumours when assessing TIMEs in MGC patients. Moreover, improving our understanding of TIMEs in PGC and MGC is important for designing immunotherapy strategies to improve outcomes for patients.
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