Abstract
Gastric cancer (GC) is a heterogeneous disease, so molecular classification is important for selecting the most appropriate treatment strategies for GC patients. To be applicable in the clinic, there is an urgent need for a platform that will allow screening real-life archival tissue specimens. For this purpose, we performed RNA sequencing of 50 samples from our Asian Cancer Research Group (ACRG) GC cohort to reproduce the molecular subtypes of GC using archival tissues with different platforms. We filtered out genes from the epithelial-to-mesenchymal transition (EMT) and microsatellite instability-high (MSI) signatures (coefficient ≤ 0.4) followed by the ACRG molecular subtype strategy. Overall accuracy of reproduction of ACRG subtype was 66% (33/50). Given the importance of EMT subtype in future clinical trials, we further developed the minimum number of genes (10 genes) for EMT signatures correlating highly with the original EMT signatures (correlation ≥ 0.65). Using our 10-gene model, we could classify EMT subtypes with high sensitivity (0.9576) and specificity (0.811). In conclusion, we reproduced ACRG GC subtypes using different platforms and could predict EMT subtypes with 10 genes and are now planning to use them in our prospective clinical study of precision oncology in GC.
Highlights
Gastric cancer (GC) is a heterogeneous disease with two distinct morphologic subtypes by Lauren’s classification and with variable environmental etiologies, clinical manifestations, and genetic backgrounds
Correlated signature gene lists and signature score cutoffs were adjusted for new expression values originated from RNA sequencing (RNA-Seq)
We further examined the reproducibility between microarray and RNA-Seq with the expression signatures of EMT10, MSI11, and TP53 activity[12], which were used for molecular subtype classification in the previous study[4]
Summary
Gastric cancer (GC) is a heterogeneous disease with two distinct morphologic subtypes by Lauren’s classification (intestinal type and diffuse type) and with variable environmental etiologies, clinical manifestations, and genetic backgrounds. The Asian Cancer Research Group (ACRG) reported four molecular subtypes of GC with clinical significance based on mRNA expression profiles: microsatellite-stable (MSS)/TP53−, MSS/TP53+, MSI, and epithelial-to-mesenchymal transition (EMT) subtypes. In this molecular classification, the MSI subtype was consistently associated with favorable prognosis, while EMT GCs showed a significantly higher recurrence rate, higher probability of peritoneal seeding at recurrence, younger age at presentation, and poorer survival compared to other subtypes[4]. Patients with EMT subtypes showed no remarkable benefit from checkpoint blockade These observations demonstrate the importance of molecular classification of GCs in the clinic and the need for a platform that will allow the screening of real-life biospecimens[7]. We performed RNA sequencing of 50 samples from an ACRG GC cohort to reproduce molecular classification in formalin-fixed paraffin-embedded (FFPE) tissue samples with different platforms that can be used as screening tools in the real world
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
