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Prognostic Molecular Classification of Appendiceal Mucinous Neoplasms Treated with Cytoreductive Surgery and Hyperthermic Intraperitoneal Chemotherapy



Appendiceal mucinous neoplasm (AMN) with peritoneal metastasis is a rare but deadly disease with few prognostic or therapy-predictive biomarkers to guide treatment decisions. Here, we investigated the prognostic and biological attributes of gene expression-based AMN molecular subtypes.


AMN specimens (n = 138) derived from a population-based subseries of patients treated at our institution with cytoreductive surgery and hyperthermic intraperitoneal chemotherapy (CRS/HIPEC) between 05/2000 and 05/2013 were analyzed for gene expression using a custom-designed NanoString 148-gene panel. Signed non-negative matrix factorization (sNMF) was used to define a gene signature capable of delineating robustly-classified AMN molecular subtypes. The sNMF class assignments were evaluated by topology learning, reverse-graph embedding and cross-cohort performance analysis.


Three molecular subtypes of AMN were discerned by the expression patterns of 17 genes with roles in cancer progression or anti-tumor immunity. Tumor subtype assignments were confirmed by topology learning. AMN subtypes were termed immune-enriched (IE), oncogene-enriched (OE) and mixed (M) as evidenced by their gene expression patterns, and exhibited significantly different post-treatment survival outcomes. Genes with specialized immune functions, including markers of T-cells, natural killer cells, B-cells, and cytolytic activity showed increased expression in the low-risk IE subtype, while genes implicated in the promotion of cancer growth and progression were more highly expressed in the high-risk OE subtype. In multivariate analysis, the subtypes demonstrated independent prediction power for post-treatment survival.


Our findings suggest a greater role for the immune system in AMN than previously recognized. AMN subtypes may have clinical utility for predicting CRS/HIPEC treatment outcomes.

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The authors acknowledge the DEMON high performance computing cluster, the Greenplum massively parallel processing database and the Data Lake cloud storage and computing facility at Wake Forest University School of Medicine, the Texas Advanced Computing Center (TACC) at The University of Texas at Austin (, and the Extreme Science and Engineering Discovery Environment (XSEDE, which is supported by National Science Foundation grant number ACI-1548562), for providing high performance computing resources that have contributed to the research results reported within this paper.


This work was supported, in part, by the Orin Smith Family fund (to E.A.L.), pilot funds from the National Organization for Rare Disorders (to E.A.L. and L.D.M.) and the Wake Forest Baptist Compressive Cancer Center’s Shared Resources: Cancer Genomics (CGSR), Tumor Tissue & Pathology (TTPSR) and Bioinformatics (BISR) supported by the National Cancer Institute’s Cancer Center Support Grant award number P30CA012197. The content of this publication is solely the responsibility of the authors and does not necessarily represent the official views of the National Cancer Institute.

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Correspondence to Lance D. Miller PhD or Edward A. Levine MD.

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Su, J., Jin, G., Votanopoulos, K.I. et al. Prognostic Molecular Classification of Appendiceal Mucinous Neoplasms Treated with Cytoreductive Surgery and Hyperthermic Intraperitoneal Chemotherapy. Ann Surg Oncol (2020).

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