Volume 74, Issue 3 pp. 1371-1383
Original Article

A Transcriptomic Signature for Risk-Stratification and Recurrence Prediction in Intrahepatic Cholangiocarcinoma

Yuma Wada

Yuma Wada

Center for Gastrointestinal Research, Baylor Scott & White Research Institute and Charles A. Sammons Cancer Center, Baylor University Medical Center, Dallas, TX

Department of Surgery, Tokushima University, Tokushima, Japan

Department of Molecular Diagnostics and Experimental Therapeutics, Beckman Research Institute of City of Hope Comprehensive Cancer Center, Duarte, CA

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Mitsuo Shimada

Mitsuo Shimada

Department of Surgery, Tokushima University, Tokushima, Japan

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Kensuke Yamamura

Kensuke Yamamura

Center for Gastrointestinal Research, Baylor Scott & White Research Institute and Charles A. Sammons Cancer Center, Baylor University Medical Center, Dallas, TX

Department of Gastroenterological Surgery, Graduate School of Medical Sciences, Kumamoto University, Kumamoto, Japan

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Takeo Toshima

Takeo Toshima

Department of Surgery and Science, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan

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Jasjit K Banwait

Jasjit K Banwait

Center for Gastrointestinal Research, Baylor Scott & White Research Institute and Charles A. Sammons Cancer Center, Baylor University Medical Center, Dallas, TX

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Yuji Morine

Yuji Morine

Department of Surgery, Tokushima University, Tokushima, Japan

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Tetsuya Ikemoto

Tetsuya Ikemoto

Department of Surgery, Tokushima University, Tokushima, Japan

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Yu Saito

Yu Saito

Department of Surgery, Tokushima University, Tokushima, Japan

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Hideo Baba

Hideo Baba

Department of Gastroenterological Surgery, Graduate School of Medical Sciences, Kumamoto University, Kumamoto, Japan

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Masaki Mori

Masaki Mori

Department of Surgery and Science, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan

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Ajay Goel

Corresponding Author

Ajay Goel

Center for Gastrointestinal Research, Baylor Scott & White Research Institute and Charles A. Sammons Cancer Center, Baylor University Medical Center, Dallas, TX

Department of Molecular Diagnostics and Experimental Therapeutics, Beckman Research Institute of City of Hope Comprehensive Cancer Center, Duarte, CA

ADDRESS CORRESPONDENCE AND REPRINT REQUESTS TO:

Ajay Goel, Ph.D.

Department of Molecular Diagnostics and Experimental Therapeutics, Beckman Research Institute of City of Hope

Biomedical Research Center

1218 S. Fifth Avenue, Suite 2226

Monrovia, CA 91016

E-mail: [email protected]

Tel.: +1-626-218-3452

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First published: 16 March 2021
Citations: 3
Supported by the National Cancer Institute/National Institutes of Health (CA72851, CA181572, CA184792, CA202797, and CA187956).
Potential conflict of Interest: Nothing to report.

Abstract

Background and Aims

Tumor recurrence is frequent even in intrahepatic cholangiocarcinoma (ICC), and improved strategies are needed to identify patients at highest risk for such recurrence. We performed genome-wide expression profile analyses to discover and validate a gene signature associated with recurrence in patients with ICC.

Approach and Results

For biomarker discovery, we analyzed genome-wide transcriptomic profiling in ICC tumors from two public data sets: The Cancer Genome Atlas (n = 27) and GSE107943 (n = 28). We identified an eight-gene panel (BIRC5 [baculoviral IAP repeat containing 5], CDC20 [cell division cycle 20], CDH2 [cadherin 2], CENPW [centromere protein W], JPH1 [junctophilin 1], MAD2L1 [mitotic arrest deficient 2 like 1], NEIL3 [Nei like DNA glycosylase 3], and POC1A [POC1 centriolar protein A]) that robustly identified patients with recurrence in the discovery (AUC = 0.92) and in silico validation cohorts (AUC = 0.91). We next analyzed 241 specimens from patients with ICC (training cohort, n = 64; validation cohort, n = 177), followed by Cox proportional hazard regression analysis, to develop an integrated transcriptomic panel and establish a risk-stratification model for recurrence in ICC. We subsequently trained this transcriptomic panel in a clinical cohort (AUC = 0.89; 95% confidence interval [CI] = 0.79-0.95), followed by evaluating its performance in an independent validation cohort (AUC = 0.86; 95% CI = 0.80-0.90). By combining our transcriptomic panel with various clinicopathologic features, we established a risk-stratification model that was significantly superior for the identification of recurrence (AUC = 0.89; univariate HR = 6.08, 95% CI = 3.55-10.41, P < 0.01; and multivariate HR = 3.49, 95% CI = 1.81-6.71, P < 0.01). The risk-stratification model identified potential recurrence in 85% of high-risk patients and nonrecurrence in 76% of low-risk patients, which is dramatically superior to currently used pathological features.

Conclusions

We report a transcriptomic signature for risk-stratification and recurrence prediction that is superior to currently used clinicopathological features in patients with ICC.

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