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Primary bladder mucosa-associated lymphoid tissue (MALT) lymphoma is an extremely rare bladder tumor. Only scarce reports have been reported. We hereby report a case of an 81-year-old female patient with bladder tumor presenting with frequent urination and dysuria, whose pelvic magnetic resonance imaging (MRI) considered bladder cancer. She underwent transurethral resection of the bladder tumor (TURBT), and histopathology confirmed the mass to be bladder MALT lymphoma. The patient refused further treatment, and no disease recurrence one year after surgery. The current data are insufficient to draw conclusions about the long-term efficacy of treatment for this tumor, regular follow-up is necessary. To further understand the clinical features, pathology, treatment and prognosis of this tumor, we have searched the literature from 1990 to the present, analyzing a total of 64 cases of primary MALT lymphoma.

BackgroundLiver metastases (LM) are the most common tumors encountered in the liver and continue to be a significant cause of morbidity and mortality. Identification of the primary tumor of any LM is crucial for the implementation of effective and tailored treatment approaches, which still represents a difficult problem in clinical practice.MethodsThe resection or biopsy specimens and associated clinicopathologic data were archived from seven independent centers between January 2017 and December 2020. The primary tumor sites of liver tumors were verified through evaluation of available medical records, pathological and imaging information. The performance of a 90-gene expression assay for the determination of the site of tumor origin was assessed.ResultA total of 130 LM covering 15 tumor types and 16 primary liver tumor specimens that met all quality control criteria were analyzed by the 90-gene expression assay. Among 130 LM cases, tumors were most frequently located in the colorectum, ovary and breast. Overall, the analysis of the 90-gene signature showed 93.1% and 100% agreement rates with the reference diagnosis in LM and primary liver tumor, respectively. For the common primary tumor types, the concordance rate was 100%, 95.7%, 100%, 93.8%, 87.5% for classifying the LM from the ovary, colorectum, breast, neuroendocrine, and pancreas, respectively.ConclusionThe overall accuracy of 93.8% demonstrates encouraging performance of the 90-gene expression assay in identifying the primary sites of liver tumors. Future incorporation of the 90-gene expression assay in clinical diagnosis will aid oncologists in applying precise treatments, leading to improved care and outcomes for LM patients.

PurposeThis study aimed to explore the efficacy of the computed tomography (CT) radiomics model for predicting the Ki-67 proliferation index (PI) of pure-solid non-small cell lung cancer (NSCLC).Materials and methodsThis retrospective study included pure-solid NSCLC patients from five centers. The radiomics features were extracted from thin-slice, non-enhanced CT images of the chest. The minimum redundancy maximum relevance (mRMR) and least absolute shrinkage and selection operator (LASSO) were used to reduce and select radiomics features. Logistic regression analysis was employed to build predictive models to determine Ki-67-high and Ki-67-low expression levels. Three prediction models were established: the clinical model, the radiomics model, and the nomogram model combining the radiomics signature and clinical features. The prediction efficiency of different models was evaluated using the area under the curve (AUC).ResultsA total of 211 NSCLC patients with pure-solid nodules or masses were included in the study (N=117 for the training cohort, N=49 for the internal validation cohort, and N=45 for the external validation cohort). The AUC values for the clinical models in the training, internal validation, and external validation cohorts were 0.73 (95% CI: 0.64–0.82), 0.75 (95% CI:0.62–0.89), and 0.72 (95% CI: 0.57–0.86), respectively. The radiomics models showed good predictive ability in diagnosing Ki-67 expression levels in the training cohort (AUC, 0.81 [95% CI: 0.73-0.89]), internal validation cohort (AUC, 0.81 [95% CI: 0.69-0.93]) and external validation cohort (AUC, 0.78 [95% CI: 0.64-0.91]). Compared to the clinical and radiomics models, the nomogram combining both radiomics signatures and clinical features had relatively better diagnostic performance in all three cohorts, with the AUC of 0.83 (95% CI: 0.76–0.90), 0.83 (95% CI: 0.71–0.94), and 0.81 (95% CI: 0.68–0.93), respectively.ConclusionThe nomogram combining the radiomics signature and clinical features may be a potential non-invasive method for predicting Ki-67 expression levels in patients with pure-solid NSCLC.

PurposeThis analysis aimed to investigate the clinical characteristics and changing trajectories of gastric cancer (GC) and esophageal cancer (EC).MethodsWe collected data from a large cancer hospital in Beijing, China, from 2010 to 2019. Joinpoint regression was used to analyze the trends of histological characteristics and comorbidities.ResultsFrom 2010 to 2019, there were a total of 10,083 EC patients and 14,244 GC patients. Patients were mainly men and diagnosed at 55-64 years old. Metabolic comorbidity was the most common comorbidity, with hypertension being predominant. The percentages of stage I showed significant increases for EC [average annual percent change (AAPC): 10.5%] and GC (AAPC: 9.7%) patients. We also observed an increasing trend of EC and GC patients over 65 years old. For EC patients, esophageal squamous cell carcinoma (93.1%) remained as the prioritized subtype, and the middle third of the esophagus was the most common site. EC patients with three or more comorbidities increased from 0.1% to 2.2% (AAPC, 27.7%; 95% CI, 14.7% to 42.2%). For GC patients, adenocarcinoma accounts for 86.9% of the total cases, and cardia was the most common site. The ulcerative comorbidity rate decreased from 2.0% to 1.2% (AAPC, −6.1%; 95% CI, −11.6% to −0.3%).ConclusionESCC remained as the prioritized histological subtype, and the middle third of the esophagus was the most common site of EC. The majority of GC patients had adenocarcinoma, and the cardia was the most common site. There was an increasing trend of patients diagnosed at stage I. These findings provide scientific evidence to guide future treatment.

Due to the characteristics of aggressiveness and high risk of postoperative recurrence, non-small cell lung cancer (NSCLC) is a serious hazard to human health, accounting for 85% of all lung cancer cases. Drug therapies, including chemotherapy, targeted therapy and immunotherapy, are effective treatments for NSCLC in clinics. However, most patients ultimately develop drug resistance, which is also the leading cause of treatment failure in cancer. To date, the mechanisms of drug resistance have yet to be fully elucidated, thus original strategies are developed to overcome this issue. Emerging studies have illustrated that circular RNAs (circRNAs) participate in the generation of therapeutic resistance in NSCLC. CircRNAs mediate the modulations of immune cells, cytokines, autophagy, ferroptosis and metabolism in the tumor microenvironment (TME), which play essential roles in the generation of drug resistance of NSCLC. More importantly, circRNAs function as miRNAs sponges to affect specific signaling pathways, directly leading to the generation of drug resistance. Consequently, this review highlights the mechanisms underlying the relationship between circRNAs and drug resistance in NSCLC. Additionally, several therapeutic drugs associated with circRNAs are summarized, aiming to provide references for circRNAs serving as potential therapeutic targets in overcoming drug resistance in NSCLC.

BackgroundThe survival prognosis is the hallmark of cancer progression. Here, we aimed to develop a recurrence-related gene signature to predict the prognosis of colon adenocarcinoma (COAD).MethodsThe proteomic data from the Clinical Proteomic Tumor Analysis Consortium (CPTAC) and genomic data from the cancer genomic maps [The Cancer Genome Atlas (TCGA)] dataset were analyzed to identify co-differentially expressed genes (cDEGs) between recurrence samples and non-recurrence samples in COAD using limma package. Functional enrichment analysis, including Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway was conducted. Univariate and multivariate Cox regressions were applied to identify the independent prognostic feature cDEGs and establish the signature whose performance was evaluated by Kaplan–Meier curve, receiver operating characteristic (ROC), Harrell’s concordance index (C-index), and calibration curve. The area under the receiver operating characteristic (ROC) curve (AUROC) and a nomogram were calculated to assess the predictive accuracy. GSE17538 and GSE39582 were used for external validation. Quantitative real-time PCR and Western blot analysis were carried out to validate our findings.ResultsWe identified 86 cDEGs in recurrence samples compared with non-recurrence samples. These genes were primarily enriched in the regulation of carbon metabolic process, fructose and mannose metabolism, and extracellular exosome. Then, an eight-gene-based signature (CA12, HBB, NCF1, KBTBD11, MMAA, DMBT1, AHNAK2, and FBLN2) was developed to separate patients into high- and low-risk groups. Patients in the low-risk group had significantly better prognosis than those in the high-risk group. Four prognostic clinical features, including pathological M, N, T, and RS model status, were screened for building the nomogram survival model. The PCR and Western blot analysis results suggested that CA12 and AHNAK2 were significantly upregulated, while MMAA and DMBT1 were downregulated in the tumor sample compared with adjacent tissues, and in non-recurrent samples compared with non-recurrent samples in COAD.ConclusionThese identified recurrence-related gene signatures might provide an effective prognostic predictor and promising therapeutic targets for COAD patients.

In the past several decades, innovative research in cancer biology and immunology has contributed to novel therapeutics, such as targeted therapy and immunotherapy, which have transformed the management of patients with melanoma. Despite the remarkable therapeutic outcomes of targeted treatments targeting MAPK signaling and immunotherapy that suppresses immune checkpoints, some individuals acquire therapeutic resistance and disease recurrence. This review summarizes the current understanding of melanoma genetic variations and discusses individualized melanoma therapy options, particularly for advanced or metastatic melanoma, as well as potential drug resistance mechanisms. A deeper understanding of individualized treatment will assist in improving clinical outcomes for patients with cutaneous melanoma.

Gastric cancer (GC) is the third leading cause of cancer-related death worldwide. Helicobacter pylori infection can induce GC through a serial cascade of events, with emerging evidence suggesting the important role of epigenetic alterations in the development and progression of the disease. Here, we report on mechanisms responsible for Jumonji AT-rich interactive domain1B (JARID1B) upregulation in GC and its role in the malignant transformation induced by H. pylori infection. We found that upregulation of JARID1B was associated with poorer prognosis, greater tumor purity, and less immune cell infiltration into the tumor. Mechanistically, we showed that the upregulation of JARID1B in human GC was attributed to JARID1B amplification and its induction by H. pylori infection. Furthermore, we identified miR-29c as a negative regulator of JARID1B in GC. H. pylori caused downregulation of miR-29c in human GC and thereby contributed to JARID1B upregulation through relieving posttranscriptional regulation. Functionally, we showed that knockdown of JARID1B reduced GC cell proliferation induced by H. pylori infection. Subsequently, cyclinD1 (CCND1), a key molecule in GC, was shown to be a target gene of JARID1B. In conclusion, these results suggest that JARID1B may be an oncogene upregulated in human GC and could represent a novel therapeutic target to prevent malignant transformation induced by H. pylori infection.

BackgroundGastric cancer is a common gastrointestinal malignancy. Since it is often diagnosed in the advanced stage, its mortality rate is high. Traditional therapies (such as continuous chemotherapy) are not satisfactory for advanced gastric cancer, but immunotherapy has shown great therapeutic potential. Gastric cancer has high molecular and phenotypic heterogeneity. New strategies for accurate prognostic evaluation and patient selection for immunotherapy are urgently needed.MethodsWeighted gene coexpression network analysis (WGCNA) was used to identify hub genes related to gastric cancer progression. Based on the hub genes, the samples were divided into two subtypes by consensus clustering analysis. After obtaining the differentially expressed genes between the subtypes, a gastric cancer risk model was constructed through univariate Cox regression, least absolute shrinkage and selection operator (LASSO) regression and multivariate Cox regression analysis. The differences in prognosis, clinical features, tumor microenvironment (TME) components and immune characteristics were compared between subtypes and risk groups, and the connectivity map (CMap) database was applied to identify potential treatments for high-risk patients.ResultsWGCNA and screening revealed nine hub genes closely related to gastric cancer progression. Unsupervised clustering according to hub gene expression grouped gastric cancer patients into two subtypes related to disease progression, and these patients showed significant differences in prognoses, TME immune and stromal scores, and suppressive immune checkpoint expression. Based on the different expression patterns between the subtypes, we constructed a gastric cancer risk model and divided patients into a high-risk group and a low-risk group based on the risk score. High-risk patients had a poorer prognosis, higher TME immune/stromal scores, higher inhibitory immune checkpoint expression, and more immune characteristics suitable for immunotherapy. Multivariate Cox regression analysis including the age, stage and risk score indicated that the risk score can be used as an independent prognostic factor for gastric cancer. On the basis of the risk score, we constructed a nomogram that relatively accurately predicts gastric cancer patient prognoses and screened potential drugs for high-risk patients.ConclusionsOur results suggest that the 7-gene signature related to tumor progression could predict the clinical prognosis and tumor immune characteristics of gastric cancer.

BackgroundEsophageal squamous cell carcinoma (ESCC) has a high incidence rate and poor prognosis. In this study, we aimed to develop a predictive model to estimate the individualized 5-year absolute risk for ESCC in Chinese populations living in the high-risk areas of China.MethodsWe developed a risk-predicting model based on the epidemiologic data from a population-based case-control study including 244 newly diagnosed ESCC patients and 1,220 healthy controls. Initially, we included easy-to-obtain risk factors to construct the model using the multivariable logistic regression analysis. The area under the ROC curves (AUC) with cross-validation methods was used to evaluate the performance of the model. Combined with local age- and sex-specific ESCC incidence and mortality rates, the model was then used to estimate the absolute risk of developing ESCC within 5 years.ResultsA relative risk model was established that included eight factors: age, sex, tobacco smoking, alcohol drinking, education, and dietary habits (intake of hot food, intake of pickled/salted food, and intake of fresh fruit). The relative risk model had good discrimination [AUC, 0.785; 95% confidence interval (CI), 0.749–0.821]. The estimated 5-year absolute risk of ESCC for individuals varied widely, from 0.0003% to 19.72% in the studied population, depending on the exposure to risk factors.ConclusionsOur model based on readily identifiable risk factors showed good discriminative accuracy and strong robustness. And it could be applied to identify individuals with a higher risk of developing ESCC in the Chinese population, who might benefit from further targeted screening to prevent esophageal cancer.

Introduction: Circulating microRNAs (miRNAs) are promising molecular biomarkers for the early detection of esophageal squamous cell carcinoma (ESCC). We investigated the serum miRNA expression profiles from microarray-based technologies and evaluated the diagnostic value of serum miRNAs as potential biomarkers for ESCC by using feature selection algorithms.Methods: Serum miRNA expression profiles were obtained from 52 ESCC patients and 52 age- and sex-matched controls via performing a high-throughput microarray assay. Five representative feature selection algorithms including the false discovery rate procedure, family-wise error rate procedure, Lasso logistic regression, hybrid huberized support vector machine (SVM), and SVM using the squared-error loss with the elastic-net penalty were jointly carried out to select the significantly differentially expressed miRNAs based on the miRNA profiles.Results: Three miRNAs including miR-16-5p, miR-451a, and miR-574-5p were identified as the powerful biomarkers for the diagnosis of ESCC. The diagnostic accuracy of the combination of these three miRNAs was evaluated by using logistic regression and the SVM. The averages of the area under the receiver operating curve and classification accuracies based on different classifiers were more than 0.80 and 0.79, respectively. The cross-validation results suggested that the three-miRNA-based classifiers could clearly distinguish ESCC patients from healthy controls. Moreover, the classifying performance of the miRNA panel persisted in discriminating the healthy group from patients with ESCC stage I-II (AUC > 0.76) and patients with ESCC stage III-IV (AUC > 0.80).Conclusions: These results in this study have moved forward the identification of novel biomarkers for the diagnosis of ESCC.

Background: Gastrointestinal (GI) cancers are the common cause of morbidity and mortality in China which seriously threaten people's health and lives. The aim of this study was to describe the temporal trend in the epidemiology of GI cancers from 1991 to 2015, with an emphasis on the effects of age, period and cohort in Yangzhong City, Jiangsu province, a high-risk area of GI cancers in China.Methods: Our study extracted cases of gastric cancer, esophageal cancer and colorectal cancer diagnosed from 1991 to 2015 from Yangzhong Cancer Registry. Age-standardized rates (ASRs) were calculated and joinpoint regression was used to compute the estimated annual percent changes. Age-period-cohort (APC) model was performed to investigate the independent effects of age, calendar period, and birth cohort.Results: Between 1991 and 2015, 18,006 new cases and 10,262 deaths were registered with GI cancers in Yangzhong. The age-standardized incidence rates (ASIRs) of gastric cancer decreased in both sexes during the study period. And the incidence rates of esophageal cancer stabilized at first then continued to decline, the turning point was in 2005 for men and 2001 for women. Changes in the mortality rates of gastric cancer and esophageal cancer showed significant declined trends around 2000–2010 in both genders. The incidence rates of colorectal cancer increased steadily during the entire study period, and the increase was more pronounced in the mortality rates of men. The results of APC analysis suggest that general decreases in incidence and mortality of esophageal cancer and gastric cancer might be caused by the downward trend of the period and cohort effects, while the increases in colorectal cancer might be caused by the uptrend of the period effects.Conclusions: The incidence and mortality rates of esophageal and gastric cancers showed a downward trend and colorectal cancer was on the rise as a whole in Yangzhong City. The different burden of gastrointestinal cancer indicating heterogeneous risk factors exist and may have contributed to these temporal variations.

Glioma is the most common malignant tumor of the central nervous system with high morbidity and mortality. Circular RNAs (circRNAs) are abundant non-coding RNAs, which contribute to tumor progression by competing with other endogenous RNAs such as microRNA (miRNA). MiRNA are a class of small non-coding RNAs, which interrupt the translation of target mRNAs. CircPCMTD1 (hsa-circ-0001801) is a newly discovered circRNA that was found to be significantly upregulated in glioma. However, its function is unclear. In this study, circPCMTD1 upregulation promoted the cell viability, migration and invasion dramatically, while the inhibition of circPCMTD1 led to a significant reduction of tumor growth in vivo. MiRNAs microarray analyses on circPCMTD1 silencing models in U251 and U118MG cells were performed, and the results suggested that circPCMTD1 knockdown could upregulate the expression of miR-224-5p and downregulate the expression of mTOR, one of miR-224-5p targets, in both cell lines. According to the prediction from circular RNA interactome and Targetscan, there was a complementary sequence in circPCMTD1 for miR-224-5p. Dual-luciferase reporter assay demonstrated that circPCMTD1 were targets of miR-224-5p. RIP assay was also performed to further confirm their directly interaction. Overexpression of miR-224-5p inhibited the viability and proliferation, migration, and invasion of U251 and U118MG glioma cells. In conclusion, circPCMTD1 could contribute to the promotion of glioma progression, and it may serve as the sponge of miR-224-5p to exert its function.