Helicobacter pylori is recognised as a main risk factor for gastric cancer. However, approximately half of the patients with gastritis are negative for H. pylori infection, and the abundance of H. pylori decreases in patients with cancer. In the current study, we profiled gastric epithelium-associated bacterial species in patients with gastritis, intestinal metaplasia, and gastric cancer to identify additional potential pathogenic bacteria. The overall composition of the microbiota was similar between the patients with gastritis and those with intestinal metaplasia. H. pylori was present in half of the non-cancer group, and the dominant bacterial species in the H. pylori-negative patients were Burkholderia, Enterobacter, and Leclercia. The abundance of those bacteria was similar between the cancer and non-cancer groups, whereas the frequency and abundance of H. pylori were significantly lower in the cancer group. Instead, Clostridium, Fusobacterium, and Lactobacillus species were frequently abundant in patients with gastric cancer, demonstrating a gastric cancer-specific bacterial signature. A receiver operating characteristic curve analysis showed that Clostridium colicanis and Fusobacterium nucleatum exhibited a diagnostic ability for gastric cancer. Our findings indicate that the gastric microenvironment is frequently colonised by Clostridium and Fusobacterium in patients with gastric cancer.

The Petersen-Lincoln estimator has been used to estimate the size of a population in a single mark release experiment. However, the estimator is not valid when the capture sample and recapture sample are not independent. We provide an intuitive interpretation for "independence" between samples based on 2 x 2 categorical data formed by capture/non-capture in each of the two samples. From the interpretation, we review a general measure of "dependence" and quantify the correlation bias of the Petersen-Lincoln estimator when two types of dependences (local list dependence and heterogeneity of capture probability) exist. An important implication in the census undercount problem is that instead of using a post enumeration sample to assess the undercount of a census, one should conduct a prior enumeration sample to avoid correlation bias. We extend the Petersen-Lincoln method to the case of two populations. This new estimator of the size of the shared population is proposed and its variance is derived. We discuss a special case where the correlation bias of the proposed estimator due to dependence between samples vanishes. The proposed method is applied to a study of the relapse rate of illicit drug use in Taiwan.

BackgroundGastric cancer is the eighth most common cancer in Taiwan, with a 40% 5-year survival rate. Approximately 40% of patients are refractory to chemotherapy. Currently, the anti-HER2 therapy is the only clinically employed targeted therapy. However, only 7% patients in Taiwan are HER2-positive. Identifying candidate target genes will facilitate the development of adjuvant targeted therapy to increase the efficacy of gastric cancer treatment.MethodsClinical specimens were analyzed by targeted RNA sequencing to assess the expression levels of target genes. Statistical significance of differential expression and correlation between specimens was evaluated. The correlation with patient survival was analyzed as well. In vitro cell mobility was determined using wound-healing and transwell mobility assays.ResultsExpression of BMP1, COL1A1, STAT3, SOX2, FOXA2, and GATA6 was progressively dysregulated through the stages of gastric oncogenesis. The expression profile of these six genes forms an ubiquitously biomarker signature that is sufficient to differentiate cancer from non-cancerous specimens. High expression status of BMP1 correlates with poor long-term survival of late-stage patients. In vitro, suppression of BMP1 inhibits the mobility of the gastric cancer cell lines, indicating a role of BMP1 in metastasis.ConclusionsBMP1 is upregulated in gastric cancer and is correlated with poor patient survival. Suppression of BMP1 reduced gastric cancer mobility in vitro. Our finding suggests that anti-BMP1 therapy will likely augment the efficacy of standard chemotherapy and improve the treatment outcome.

In biological and ecological statistical inference, it is practically useful to provide a lower bound for species richness in a community. Chao (1984, 1989) derived a nonparametric lower bound for species richness in a single community. However, there have been no lower bounds proposed in the literature for the number of species shared by multiple communities. Based on sample species abundance or replicated incidence records from each of the N communities, we derive in this article a nonparametric approach to constructing a lower bound for the number of species shared by N (N ≥ 2) communities. The approach is valid for all types of species abundance distributions (for abundance data) or species detection probabilities (for replicated incidence data). Variance estimators for the proposed lower bounds are obtained by using typical asymptotic theory. Simulation results are reported to examine the performance of the lower bounds. Replicated incidence data of ciliate species collected in three areas from Namibia, southwest Africa, are used for illustration. We also briefly discuss the application of the proposed method to estimate the size of a shared population (i.e., the number of individuals in the intersection of multiple populations) based on capture-recapture data from each population.

BACKGROUND An increased amount of Fusobacterium nucleatum ( F. nucleatum ) is frequently detected in the gastric cancer-associated microbiota of the Taiwanese population. F. nucleatum is known to exert cytotoxic effects and play a role in the progression of colorectal cancer, though the impact of F. nucleatum colonization on gastric cancer cells and patient prognosis has not yet been examined. AIM To identify F. nucleatum- dependent molecular pathways in gastric cancer cells and to determine the impact of F. nucleatum on survival in gastric cancer. METHODS Coculture of F. nucleatum with a gastric cancer cell line was performed, and changes in gene expression were investigated. Genes with significant changes in expression were identified by RNA sequencing. Pathway analysis was carried out to determine deregulated cellular functions. A cohort of gastric cancer patients undergoing gastrectomy was recruited, and nested polymerase chain reaction was performed to detect the presence of F. nucleatum in resected cancer tissues. Statistical analysis was performed to determine whether F. nucleatum colonization affects patient survival. RESULTS RNA sequencing and subsequent pathway analysis revealed a drastic interferon response induced by a high colonization load. This response peaked within 24 h and subsided after 72 h of incubation. In contrast, deregulation of actin and its regulators was observed during prolonged incubation under a low colonization load, likely altering the mobility of gastric cancer cells. According to the clinical specimen analysis, approximately one-third of the gastric cancer patients were positive for F. nucleatum , and statistical analysis indicated that the risk for colonization increases in late-stage cancer patients. Survival analysis demonstrated that F. nucleatum colonization was associated with poorer outcomes among patients also positive for Helicobacter pylori ( H. pylori ). CONCLUSION F. nucleatum colonization leads to deregulation of actin dynamics and likely changes cancer cell mobility. Cohort analysis demonstrated that F. nucleatum colonization leads to poorer prognosis in H. pylori- positive patients with late-stage gastric cancer. Hence, combined colonization of F. nucleatum and H. pylori is a predictive biomarker for poorer survival in late-stage gastric cancer patients treated with gastrectomy.