Dataset Information

Identification of ARGLU1 as a potential therapeutic target for gastric cancer based on genome-wide functional screening data.

ABSTRACT:

Background

Due to the molecular mechanism complexity and heterogeneity of gastric cancer (GC), mechanistically interpretable biomarkers were required for predicting prognosis and discovering therapeutic targets for GC patients.

Methods

Based on a total of 824 GC-specific fitness genes from the Project Score database, LASSOCox regression was performed in TCGA-STAD cohort to construct a GC Prognostic (GCP) model which was then evaluated on 7 independent GC datasets. Targets prioritization was performed in GC organoids. ARGLU1 was selected to further explore the biological function and molecular mechanism. We evaluated the potential of ARGLU1 serving as a promising therapeutic target for GC using patients derived xenograft (PDX) model.

Findings

The 9-gene GCP model showed a statistically significant prognostic performance for GC patients in 7 validation cohorts. Perturbation of SSX4, DDX24, ARGLU1 and TTF2 inhibited GC organoids tumor growth. The results of tissue microarray indicated lower expression of ARGLU1 was correlated with advanced TNM stage and worse overall survival. Over-expression ARGLU1 significantly inhibited GC cells viability in vitro and in vivo. ARGLU1 could enhance the transcriptional level of mismatch repair genes including MLH3, MSH2, MSH3 and MSH6 by potentiating the recruitment of SP1 and YY1 on their promoters. Moreover, inducing ARGLU1 by LNP-formulated saRNA significantly inhibited tumor growth in PDX model.

Interpretation

Based on genome-wide functional screening data, we constructed a 9-gene GCP model with satisfactory predictive accuracy and mechanistic interpretability. Out of nine prognostic genes, ARGLU1 was verified to be a potential therapeutic target for GC.

Funding

National Natural Science Foundation of China.

SUBMITTER: Li F

PROVIDER: S-EPMC8220577 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundPoorly cohesive (PC) is a unique histologic subtype of gastric cancer (GC), with an increasing incidence in recent years. However, the molecular characteristics and therapeutic targets of PC GC are not yet well studied and there are no effective therapies for these patients.MethodsFormalin fixed paraffin embedded (FFPE) samples of 556 GC patients, including 64 PC GC, were collected for next-generation sequencing (NGS). Clinical characteristics and genomic profiling were analyzed. FGFR2 expression was detected by quantitative real time polymerase chain reaction (qRT-PCR) and immunohistochemistry (IHC). FGFR2 inhibitors response was studied in vitro.ResultsAmong 556 GC patients, PC GC patients were younger (P = 0.004), had lower tumor mutation burden (TMB-L) (P = 0.001) than non-PC GC. The top 10 most frequently mutated genes in PC GC were TP53 (48%), CDH1 (31%), ARID1A (14%), FGFR2 (14%), ERBB2 (9%), CDKN2A (9%), FGF3 (8%), LRP1B (9%), FGF19 (8%) and FGF4 (8%). Noticeably, FGFR2 is more frequently mutated than non-PC GC (14% vs. 6%, P = 0.037), including copy number variants (CNVs, 12.5%) and gene rearrangements (3.1%, FGFR2/VTI1A and FGFR2/TACC2). Former studies have confirmed that gain of copy number could increase FGFR2 expression and sensitivity to FGFR2 inhibitors in GC. However, no research has verified the function of FGFR2 rearrangements in GC. Our results showed that cell lines of GC transfected with TACC2-FGFR2 fusion had increased mRNA and protein expression of FGFR2, and were more sensitive to FGFR2 inhibitors. FGFR2 inhibitors might be a new therapeutic target for PC GC. In addition, we found patients of PC GC harboring gene rearrangements (n = 9) had poorer overall survival (OS) in comparison with patients without any gene rearrangement (n = 19) (16.0 months vs 21.0 months, P = 0.043). Gene rearrangement might be an adverse prognostic factor for PC GC patients.ConclusionsFGFR2 alterations were recurrent in PC GC and FGFR2 inhibitors might be a new therapeutic target for PC GC.