Strategies and Advancements for Personalized Medicine in Gastric Cancer
Creators: Skubleny, Daniel
Publisher: name: University of Alberta Library
Year: 2023

<p>Five-year overall survival for gastric cancer in Canada is only 25%. Standard of care treatment using neoadjuvant chemotherapy and surgery achieves partial or complete treatment response in only 40% of patients. Additional strategies and methods to discover novel therapies and optimize existing treatment regimens are required. In this work we use a combination of immunohistochemistry-based biomarkers, 3-dimensional organoid models and omics based molecular classification to investigate and enhance personalized medicine strategies in gastric cancer. <br>
Forty-three patients with gastric adenocarcinoma, of which 18 underwent neoadjuvant chemotherapy, were included in a prospective clinical cohort. Differences in expression of Galectin-3, E-cadherin, CD4+ and CD8+ molecules between tumours with and without treatment response to neoadjuvant chemotherapy were assessed with immunohistochemistry. To enhance procurement of fresh tissue for organoid culture we assessed the feasibility of shipping mouse stomach on ice for 24- or 48-hours using Hank’s Balanced Salts Solution (HBSS), Histidine-tryptophan-ketoglutarate (HTK) or University of Wisconsin solutions as transport media. The effect of transport time and transport media on organoid viability, growth rate and stem cell gene expression of LGR5 and TROY were assessed using cell counting with Trypan Blue and quantitative real-time PCR, respectively. Multivariable generalized additive models (GAM) were used to assess these outcomes over 12 organoid passages. Using publicly available whole-transcriptome data we developed supervised machine learning models to assign molecular subtypes from The Cancer Genome Atlas (TCGA), Asian Cancer Research Group (ACRG) and Tumour Microenvironment score (TME) classification systems to 2,202 patients. Overall survival was assessed using a multivariable Cox proportional hazards model. Using genes informed by these models we developed a custom Nanostring codeset to assign molecular subtypes to our 43-patient cohort and 10 tumour and tumour-organoid pairs. The accuracy of molecular subtype models and our Nanostring test were assessed relative to gold-standard Epstein-Barr encoded early RNAs in-situ hybridization and pentaplex polymerase chain reaction for Epstein-Barr Virus (EBV) and Microsatellite instability (MSI) tumours, respectively. <br>
The ratio between CD4 and CD8 lymphocytes was significantly greater in treatment responsive tumours (Wilcoxon, p=0.03). In univariate models CD4/CD8 ratio was the only biomarker that provided significant predictive value (Accuracy 86%, p&lt;0.001). Mock-shipment of mouse stomach tissue for 24- or 48- hours significantly decreased growth rate relative to freshly prepared organoids but did not affect viability (GAM, p&lt;0.001). Transport media did not affect growth rate or viability. Gene expression of LGR5 and TROY was not affected by transport time or media but significantly decreased upon tissue dissociation and subsequently increased in successive passages to regain endogenous expression levels by passage 6 (Kruskal-Wallis, p&lt;0.001 with post-hoc Dunn’s Test). Two human gastric cancer organoids were developed following 24- or 48- transport in HBSS solution. Classification models for TCGA (57 genes), TME (50 genes) and ACRG (39 genes) had a mean accuracy ± standard deviation of 89.5% ± 0.04, 89.4% ± 0.01 and 84.66% ± 0.04, respectively. Improved prognosis was observed for TME High tumours (Hazard Ratio 0.61, [95% Confidence Interval 0.46, 0.79]) and the TME score was the only statistically significant classification system (Global Wald Test, p&lt;0.001). In a public cohort of 2,202 patients our models demonstrated a 98.7% and 99.3% accuracy for EBV and MSI subtypes with respect to gold-standard tests. In 10 patient and patient-derived organoid samples the Nanostring test was 100% accurate for EBV and MSI subtypes. <br>
In this study, a multimodal approach is applied to investigate personalized medicine strategies for gastric cancer. These results demonstrate that CD4+/CD8+ Ratio is a promising IHC-based biomarker with therapeutic implications for response to neoadjuvant chemotherapy in locally advanced gastric cancer. From a translational perspective we found that cold shipment of fresh gastric tissue for 24- or 48-hours from mouse and human is a feasible and reliable method to increase procurement of primary organoid tissue. To our knowledge, at the time of publication, this study is the largest integrated analysis of TCGA, ACRG and TME molecular classification systems in gastric cancer. Using a custom Nanostring codeset we successful translate these machine learning models to our own population and organoid samples. Together, these findings form a foundation to enhance future investigation of personalized medicine in gastric cancer. </p>