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. 2020 Apr 1;6(2):a004945.
doi: 10.1101/mcs.a004945. Print 2020 Apr.

RNA Sequencing Profiles and Diagnostic Signatures Linked With Response to Ramucirumab in Gastric Cancer

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Free PMC article

RNA Sequencing Profiles and Diagnostic Signatures Linked With Response to Ramucirumab in Gastric Cancer

Maxim Sorokin et al. Cold Spring Harb Mol Case Stud. .
Free PMC article

Abstract

Gastric cancer (GC) is the fifth-ranked cancer type by associated mortality. The proportion of early diagnosis is low, and most patients are diagnosed at the advanced stages. First-line therapy standardly includes fluoropyrimidines and platinum compounds with trastuzumab for HER2-positive cases. For recurrent disease, there are several alternative options including ramucirumab, a monoclonal therapeutic antibody that inhibits VEGF-mediated tumor angiogenesis by binding with VEGFR2, alone or in combination with other cancer drugs. However, overall response rate following ramucirumab or its combinations is 30%-80% of the patients, suggesting that personalization of drug prescription is needed to increase efficacy of treatment. We report here original tumor RNA sequencing profiles for 15 advanced GC patients linked with data on clinical response to ramucirumab or its combinations. Three genes showed differential expression in the tumors for responders versus nonresponders: CHRM3, LRFN1, and TEX15 Of them, CHRM3 was up-regulated in the responders. Using the bioinformatic platform Oncobox we simulated ramucirumab efficiency and compared output model results with actual tumor response data. An agreement was observed between predicted and real clinical outcomes (AUC ≥ 0.7). These results suggest that RNA sequencing may be used to personalize the prescription of ramucirumab for GC and indicate potential molecular mechanisms underlying ramucirumab resistance. The RNA sequencing profiles obtained here are fully compatible with the previously published Oncobox Atlas of Normal Tissue Expression (ANTE) data.

Keywords: stomach cancer.

Figures

Figure 1.
Figure 1.
Histological subtypes of gastric cancer (GC) samples and principal component analysis (PCA). (A) Tubular adenocarcinoma; (B) poorly cohesive adenocarcinoma, signet-ring cell type; (C) poorly cohesive adenocarcinoma, NOS; (D) omental metastasis of mucinous gastric adenocarcinoma; and (E) PCA of stomach cancer samples, normal stomach samples from the ANTE database, and normal brain samples (outgroup) from the ANTE database (Suntsova et al. 2019).
Figure 2.
Figure 2.
The nectin adhesion pathway (positive regulation of JNK cascade) was more active in the nonresponder tumors (upper panel) than in the responder tumors (lower panel). The pathway is shown as an interacting network in which green arrows indicate activation. Gene expression values were geometrically averaged for responders and nonresponders. The depth of color of each node of the network corresponds to the logarithms of the case-to-normal (CNR) expression rate for each node, in which “normal” is a geometric average between normal tissue samples. The normal tissue gene expression profiles for healthy donors were taken from the ANTE database (Suntsova et al. 2019). The scale represents the extent of up/down-regulation of the pathway nodes. PAL (pathway activation level) was calculated using the Oncobox software (described in Methods).
Figure 3.
Figure 3.
The receiver operating characteristic (ROC) area under the curve (AUC) and histograms for predicting response to ramucirumab in gastric cancer (GC) patients using Oncobox balanced efficiency score (BES) values. (A) ROC AUC for the complete set of patients (n = 15). (B) ROC AUC for the patients who received ramucirumab monotherapy (n = 7). (C) Histogram and threshold value for the complete set of patients (n = 15). (D) Histogram and threshold value for the patients who received ramucirumab monotherapy (n = 7). The Oncobox BES of ramucirumab was used as a predictor of response. Patients were divided into two classes: “nonresponders,” for progressive disease, and “responders,” for stable disease and partial response (RECIST). Threshold values were assigned based on an assumption of the equality of type I and type II error rates.
Figure 4.
Figure 4.
The Oncobox BES for ramucirumab predictive power for progression-free survival in GC patients receiving chemotherapy regimens with ramucirumab (N = 15). Cohorts of patients with BES values lower or higher than 0.1 are shown separately. The risk table is shown below the plot. Hazard ratio = 0.16 (95% CI, 0.034–0.74, P = 0.019). Log-rank test P = 0.013.

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