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Inactivation of Hippo pathway characterizes a poor-prognosis subtype of esophageal cancer
Zihang Mai, … , Jing Wen, Jianhua Fu
Zihang Mai, … , Jing Wen, Jianhua Fu
Published August 22, 2022
Citation Information: JCI Insight. 2022;7(16):e155218. https://doi.org/10.1172/jci.insight.155218.
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Research Article Gastroenterology Oncology

Inactivation of Hippo pathway characterizes a poor-prognosis subtype of esophageal cancer

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Abstract

Identification of molecular subtypes that reflect different prognoses and treatment responses, especially immune checkpoint inhibitors (ICIs) in esophageal squamous cell carcinoma (ESCC), is essential for treatment decisions. We performed targeted sequencing in 201 patients with ESCC to discover genetic subtypes and validate our findings via multiple data sets. We identified 3 driver genes (FCGBP, GRIN2B, and FRY), and recurrent truncating mutations in FRY impaired its tumor-suppressive function and promoted tumor proliferation. A 3-gene mutation signature (FAT1, FAT3, and FRY) recognized a molecular subtype named “FAT/FRY” with frequent Hippo pathway–related mutations. In multiple ESCC cohorts, the patients with the FAT/FRY subtype had poorer prognosis than did patients in the WT group. Transcriptome analysis indicated that the FAT/FRY subtype was characterized by inactivation of the Hippo pathway, hypoxia, chemoresistance, higher infiltration of CD8+ T cells and activated DCs, and a transcriptome similar to that of cancer responders. Furthermore, the 3-gene signature predicted better survival for patients treated with ICIs, partially explained by its positive correlation with the tumor mutation burden and neoantigen burden. The 3-gene signature is a biomarker to recognize the FAT/FRY molecular subtype, evaluate prognosis, and select potential beneficiaries of ICIs in ESCC.

Authors

Zihang Mai, Jianye Yuan, Hong Yang, Shuogui Fang, Xiuying Xie, Xinye Wang, Jiaxin Xie, Jing Wen, Jianhua Fu

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Figure 3

Molecular characterization of mutational driver FRY.

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Molecular characterization of mutational driver FRY.
(A) FRY mRNA levels...
(A) FRY mRNA levels in ESCC tumor, paratumor, and normal tissues calculated from 3 independent data sets. (B) Proliferation assays of KYSE410 and KYSE30 cells transfected with 2 siRNAs against FRY (si1 and si2) or control siRNA (siNC). (C) Proliferation assays of the FRY-truncating mutant and the corresponding control in KYSE30 and KYSE410 cells. The data in A–C represent mean ± SD; n = 3. P values were calculated by Student’s t test. (D) Survival analysis showed that the mutation status of FRY was significantly associated with a shorter DFS. The P value was calculated by log-rank test. (E) Inference of the relative temporal order of mutations by the Bradley-Terry model. The mountain plot in the left panel displays the distribution over cancer cell fraction of mutations in each gene. The right panel shows the temporal order of mutations, and the error bar represents the quasi-SEs.

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