Published online Feb 15, 2023. doi: 10.4251/wjgo.v15.i2.303
Peer-review started: October 3, 2022
First decision: October 24, 2022
Revised: November 25, 2022
Accepted: January 12, 2023
Article in press: January 12, 2023
Published online: February 15, 2023
Processing time: 134 Days and 1.1 Hours
Neoadjuvant chemotherapy for gastric cancer is standard of care in western nations. Despite optimal therapy, only 40% of patients achieve complete or near complete treatment response. Treatment response following neoadjuvant chemotherapy is associated with overall survival. Thus, it is of critical importance to identify biomarkers capable of predicting which patients will achieve a favourable response to neoadjuvant chemotherapy in order to optimize survival outcomes.
Personalized medicine is predicated on providing the right treatment for the right patient at the right time. To achieve optimal outcomes treatment regimens now include complex decision-making processes surrounding the timing of chemotherapy and surgery. Recent research has demonstrated that some gastric cancer patients, such as those with tumours harbouring microsatellite instability, may be harmed by neoadjuvant chemotherapy. However, patients that achieve a good treatment response achieve superior clinical outcomes compared to adjuvant chemotherapy. Identifying specific subpopulations using tumour-based biomarkers is of critical importance to maximize outcomes.
We sought to characterize the expression of tumour immunohistochemistry (IHC)-based biomarkers CD4, CD8, Galectin-3 and E-cadherin in our Canadian population. Specifically, we evaluated these markers in comparison to their expression in normal gastric mucosa, as well as their relationship to neoadjuvant chemotherapy tumour response scores and expression in tumour biopsies before and after treatment. We successfully identified a biomarker, namely the CD4/CD8 T-cell ratio, with the potential to predict favourable treatment response. This pilot study serves as a foundation for future study to validate our preliminary findings.
In this study, we evaluated IHC -based biomarkers in human gastric cancer specimens. Informed consent according to an approved ethics protocol was obtained for all patients. Samples were retrieved from endoscopic biopsy prior to treatment with neoadjuvant, adjuvant or palliative chemotherapy, as well as from pathology specimens following surgical resection. Using IHC, we quantified the expression of CD4, CD8, Galectin-3 and E-cadherin in gastric cancer tumours and adjacent normal mucosa. Quantification was performed on digitally scanned images using QuPath, which is an open-source and artificial intelligence-based digital pathology program. Statistical analysis was completed using R. Sample size calculations were performed using the MKpower package in R.
We demonstrate that an elevated CD4/CD8 ratio in gastric cancer tumours is significantly associated with complete or near complete response following FLOT chemotherapy. We identify that neoadjuvant chemotherapy is associated with increased infiltration of CD4 and CD8 T-cells in 15 paired samples assessed before and after exposure to chemotherapy. However, the dynamic increase in these lymphocyte populations does not associate with an increased CD4/CD8 ratio. To expand on the findings of this study, we performed a sample size calculation and identified that CD4, CD8, Galectin-3 and E-cadherin expression may be adequately evaluated with a future study population of 85 patients.
For the first time, we identify that a high CD4/CD8 ratio within gastric cancer tumours is a promising biomarker that predicts favourable tumour response scores following neoadjuvant FLOT chemotherapy. To achieve this result, we use digital pathology technology and artificial intelligence-based quantification of biomarker staining.
This study serves as a foundation for future research in validating the CD4/CD8 ratio as a reliable biomarker that is capable of predicting neoadjuvant treatment response. Our sample size calculations provide a framework for future study design.