Tetsuya Tsukamoto

Abstract Approximately 660,000 women are diagnosed with cervical cancer annually. Current screening options such as cytology or human papillomavirus testing have limitations, creating a need to identify more effective ancillary biomarkers for triage. Here, we evaluated whether metabolomic analysis of cervical mucus metabolism could be used to identify biomarkers of cervical intraepithelial neoplasia (CIN) and cervical cancer. The case–control group consisted of 181 CIN, 69 squamous cell carcinoma (SCC) patients, and 48 healthy controls in the primary cohort. We undertook metabolomic analyses using ultra‐HPLC–tandem mass spectrometry. Univariate and multivariate analyses were carried out to profile metabolite characteristics, and receiver operating characteristic (ROC) analysis identified biomarker candidates. Five metabolites conferred the highest discriminatory power for SCC: oxidized glutathione (GSSG) (area under the ROC curve, 0.924; 95% confidence interval, 0.877–0.971), malic acid (0.914, 0.859–0.968), kynurenine (0.884, 0.823–0.945), GSSG/glutathione (GSH) (0.936, 0.892–0.979), and kynurenine/tryptophan (0.909, 0.856–0.961). Malic acid was the best marker for detection of CIN2 or worse (0.858, 0.793–0.922) and was a clinically useful metabolite. We confirmed the reproducibility of the results by validation cohort. Additionally, metabolomic analyses revealed eight pathways strongly associated with cervical neoplasia. Of these, only the tricarboxylic acid cycle was strongly associated with all CINs and cancer, indicating active energy production. Aberrant arginine metabolism by decreasing arginine and increasing citrulline might reduce tumor immunity. Changes in cysteine‐methionine and GSH pathways might drive the initiation and progression of cervical cancer. These results suggest that metabolic analysis can identify ancillary biomarkers and could improve our understanding of the pathophysiological mechanisms underlying cervical neoplasia.

Abstract Currently, human papillomavirus tests and cytology are used to screen for cervical cancer. However, more accurate ancillary screening tests are needed. MicroRNAs (miRNAs) and cytokines are promising biomarkers that are aberrantly expressed in cervical cancer. Therefore, the potential of developing new screening markers based on the levels of miRNAs and cytokines in serum and local mucus samples from the same patients with cervical neoplasia was investigated. miRNA screening was performed by microarray and measurement using real‐time reverse‐transcriptase PCR. Cytokine were measured using multiplex bead assay, and changes in expressions were analyzed based on disease severity. As lesions progressed, miR‐20b‐5p, −155‐5p, −144‐3p, −451a, and −126‐3p expression levels were increased in mucus, and miR‐16‐5p, −223‐3p, and ‐451a expression levels were decreased in serum. Regarding cytokines, IL‐6, IL‐8, monocyte chemoattractant protein‐1, Eotaxin, interferon‐γ, and RANTES were increased, whereas granulocyte–colony‐stimulating factor (G‐CSF) was significantly decreased in mucus. miRNAs and cytokines in serum did not have high diagnostic accuracy. However, a combination of miR‐20b‐5p, ‐451a, ‐126‐3p, Eotaxin, as well as G‐CSF in mucus samples, had high diagnostic accuracy with an area under the receiver operating characteristic curve of 0.989 (0.979–0.999). Our results suggest that using mucus for this ancillary test is more beneficial than serum.

Helicobacter pylori induces DNA methylation in gastric mucosa, which links to gastric cancer (GC) risk. In contrast, CpG island methylator phenotype (CIMP) is defined as high levels of cancer-specific methylation and provides distinct molecular and clinicopathological features of GC. The association between those two types of methylation in GC remains unclear. We examined DNA methylation of well-validated H. pylori infection associated genes in GC and its adjacent mucosa and investigated its association with CIMP, various molecular subtypes and clinical features. We studied 50 candidate loci in 24 gastric samples to identify H. pylori infection associated genes. Identified loci were further examined in 624 gastric tissue from 217 primary GC, 217 adjacent mucosa, and 190 mucosae from cancer-free subjects. We identified five genes (IGF2, SLC16A2, SOX11, P2RX7, and MYOD1) as hypermethylated in H. pylori infected gastric mucosa. In non-neoplastic mucosa, methylation of H. pylori infection associated genes was higher in patients with GC than those without. In primary GC tissues, higher methylation of H. pylori infection associated genes correlated with CIMP-positive and its related features, such as MLH1 methylated cases. On the other hand, GC with lower methylation of these genes presented aggressive clinicopathological features including undifferentiated histopathology, advanced stage at diagnosis. H. pylori infection associated DNA methylation is correlated with CIMP, specific molecular and clinicopathological features in GC, supporting its utility as promising biomarker in this tumor type.