The high mobility group box (HMGB) protein family consists of four members: HMGB1, 2, 3, and 4. They share similar amino acid sequences and identical functional regions, especially HMGB1, 2, and 3. The homology in structure may lead to similarity in function. In fact, though their targets may be different, they all possess the fundamental function of binding and distorting target DNAs. However, further research confirmed they are distributed differently in tissues and involved in various distinct physiological and pathological cellular processes, including cell proliferation, division, migration, and differentiation. Recently, the roles of HMGB family members in carcinogenesis has been widely investigated; however, systematic discussion on their functions and clinical values in malignant tumors is limited. In this review, we mainly review and summarize recent advances in knowledge of HMGB family members in terms of structure, distribution, biochemical cascades, and specific mechanisms regarding tumor progression. Importantly, the diagnostic, prognostic, and therapeutic value of these proteins in cancers is discussed. Finally, we envisage the orientation and challenges of this field in further studies.

Context Obesity is widely regarded as an established risk factor for colorectal cancer (CRC). However, recent studies have shown that lower mortality and better cancer-specific survival were observed in CRC patients with elevated body mass index (BMI), an example of the obesity paradox, which is the inverse correlation between obesity and mortality in some populations. Objective The aim of this systematic review and meta-analysis was to investigate the association between BMI and CRC outcomes. Data Sources PubMed, Web of Science, MEDLINE, the Cochrane Library, and Embase databases were searched for relevant articles published from inception to December 31, 2020. Study Selection Studies comparing the prognosis of CRC patients with obesity or overweight with that of normal-weight CRC patients were eligible. Data Extraction Data were extracted by 2 reviewers independently; differences were resolved by a third reviewer. BMI was classified according to WHO categories. Data Analysis To assess the prognostic effects of different BMI categories in CRC patients, hazard ratios and 95%CIs of overall survival, disease-free survival, and cancer-specific survival were extracted from included articles. Results Sixteen studies (55 391 patients in total) were included. Higher BMI was significantly associated with more favorable CRC outcomes. Compared with normal-weight patients, underweight patients had worse overall survival (HR = 1.26; 95%CI, 1.15–1.37) and disease-free survival (HR = 1.19; 95%CI, 1.11–1.27, while patients with overweight had better overall survival (HR = 0.92; 95%CI, 0.86–0.99), disease-free survival (HR = 0.96; 95%CI, 0.93–1.00), and cancer-specific survival (HR = 0.86; 95%CI, 0.76–0.98). Patients with morbid obesity had worse overall survival (HR = 1.12; 95%CI, 1.02–1.22) and disease-free survival (HR = 1.15; 95%CI, 1.07–1.24) than normal-weight patients. There was no significant difference in cancer-specific survival between patients with obesity (HR = 0.94; 95%CI, 0.76–1.16) and patients with normal weight, nor between patients with underweight and patients with normal weight (HR = 1.14; 95%CI, 0.82–1.58). Conclusions CRC patients with a higher BMI appear to have reduced mortality compared with normal-weight CRC patients, even though higher BMI/obesity is an established determinant for the development of CRC. Systematic Review Registration PROSPERO registration no. CRD42020202320.

Colorectal cancer (CRC), ranking as the third commonest cancer, leads to extremely high rates of mortality. Metastasis is the major cause of poor outcome in CRC. When metastasis occurs, 5-year survival rates of patients decrease sharply, and strategies to enhance a patient’s lifetime seem limited. MicroRNAs (miRNAs) are evolutionarily conserved small non-coding RNAs that are significantly involved in manipulation of CRC malignant phenotypes, including proliferation, invasion, and metastasis. To date, accumulating studies have revealed the mechanisms and functions of certain miRNAs in CRC metastasis. However, there is no systematic discussion about the biological implications and clinical potential (diagnostic role, prognostic role, and targeted therapy potential) of metastasis-related miRNAs in CRC. This review mainly summarizes the recent advances of miRNA-mediated metastasis in CRC. We also discuss the clinical values of metastasis-related miRNAs as potential biomarkers or therapeutic targets in CRC. Moreover, we envisage the future orientation and challenges in translating these findings into clinical applications.

Systemic chemotherapy is identified as a curative approach to prolong the survival time of patients with colorectal cancer (CRC). Although great progress in therapeutic approaches has been achieved during the last decades, drug resistance still extensively persists and serves as a major hurdle to effective anticancer therapy for CRC. The mechanism of multidrug resistance remains unclear. Recently, mounting evidence suggests that a great number of microRNAs (miRNAs) may contribute to drug resistance in CRC. Certain of these miRNAs may thus be used as promising biomarkers for predicting drug response to chemotherapy or serve as potential targets to develop personalized therapy for patients with CRC. This review mainly summarizes recent advances in miRNAs and the molecular mechanisms underlying miRNA-mediated chemoresistance in CRC. We also discuss the potential role of drug resistance-related miRNAs as potential biomarkers (diagnostic and prognostic value) and envisage the future orientation and challenges in translating the findings on miRNA-mediated chemoresistance of CRC into clinical applications.

Background: Esophageal carcinoma (EC) is the seventh-most prevalent tumor in the world, which is still one of the primary causes of tumor-related death. Identifying noteworthy biomarkers for EC is particularly significant in guiding effective treatment. Recently, circulating tumor cells (CTCs) in peripheral blood (PB) were intensively discussed as prognostic markers in patients with EC. However, an ongoing controversy still exists regarding the prognostic significance of CTCs determined by the CellSearch system in EC sufferers. This meta-analysis was designed to approach this topic. Methods: We systematically conducted searches using PubMed, Medline, Web of Science and the Cochrane Library for relevant studies, which were published through February 20, 2020. Using the random-effects model, our study was performed in Review Manager software, with odds ratios (ORs), risk ratios (RRs), hazard ratios (HRs) and 95% confidence intervals (CIs) as the effect values. Results: Totally 7 articles were finally included in this study. For clinicopathological characteristics, the pooled results on TNM stage indicated that the III/IV group had higher rate of CTCs compared with the I/II group (OR = 1.36, 95% CI: 0.68-2.71, I 2 = 0%). Incidence of CTCs was higher in patients with T3/T4 stage (OR = 2.92, 95% CI: 1.31-6.51, I 2 = 0%) and distant metastasis group (OR = 5.18, 95% CI: 2.38-11.25, I 2 = 0%) compared to patients with T1/T2 stage or nonmetastatic group. The pooled analysis revealed that CTC positivity detected in EC patients was correlated with poor overall survival (OS) (HR = 2.83, 95% CI:1.99-4.03, I 2 = 0%) and relapse-free survival (RFS) (HR = 4.71, 95% CI:2.73-8.13, I 2 = 0%). When pooling the estimated RR, a poor therapeutic response to chemoradiotherapy was discovered in patients with CTC positivity (RR = 1.99, 95% CI:1.73-2.29, I 2 = 60%).

Background: Hepatocellular carcinoma (HCC) is one of the devastating tumors with increasing incidence. Autophagy-associated genes (ARGs) are widely participated in the cellular processes of HCC. This study proposed to identify the novel prognostic gene signature based on ARGs in HCC. Methods: We downloaded the RNA sequencing data and clinical information of HCC and normal tissues from The Cancer Genome Atlas (TCGA) database. The differentially expressed ARGs were screened by the Wilcoxon signed-rank test. Functional enrichment analyses were conducted to explore the biological implications and mechanisms of ARGs in HCC. Cox regression analysis and Lasso regression analysis were performed to screen the ARGs which related to overall survival (OS). The OS-related ARGs were then used to establish a prognostic prediction model. Kaplan-Meier curves and receiver operating characteristic (ROC) curves were both applied to evaluate the accuracy of the model. GSE14520 dataset was downloaded as the testing cohort to validate the prognostic risk model in TCGA. A nomogram based on the clinical features and risk signature was established to predict the 3-year and 5-year survival rate of HCC patients. Results: Totally 27 differentially expressed ARGs were screened in this study. Then, 3 OS-related ARGs (SQSTM1, HSPB8, and BIRC5) were identified via the Cox regression and Lasso regression analyses. Based on these 3 ARGs, a prognostic prediction model was constructed. HCC patients in high-risk group presented poorer prognosis than those with low risk score in TCGA cohort (3-year OS, 53.7% vs 70.2%; 5-year OS, 42.0 % vs 55.2%; P=4.478e-04) and in the testing group (3-year OS, 57.7% vs 73.5%; 5-year OS, 43.2% vs 63.0%; P=1.274e-03). The risk score curve showed a well feasibility in predicting the patients’ survival both in TCGA and GEO cohort with the area under the ROC curve (AUC) of 0.756 and 0.672, respectively. Besides, the calibration curves and C-index indicated that the clinical nomogram performs well to predict the 3-year and 5-year survival rate in HCC patients. Conclusions: The survival model based on the ARGs may be a promising tool to predict the prognosis in HCC patients.

Background Oral squamous cell carcinoma (OSCC) is a malignant cancer, the survival rate of patients is disappointing. Therefore, it is necessary to identify the driven-genes and prognostic biomarkers in OSCC. Methods Four Gene Expression Omnibus (GEO) datasets were integratedly analyzed using bioinformatics approaches, including identification of differentially expressed genes (DEGs), GO and KEGG analysis, construction of protein-protein interaction (PPI) network, selection of hub genes, analysis of prognostic information and genetic alterations of hub genes. ONCOMINE, The Cancer Genome Atlas (TCGA) and Human Protein Atlas databases were used to evaluate the expression and prognostic value of hub genes. Tumor immunity was assessed to investigate the functions of hub genes. Finally, Cox regression model was performed to construct a multiple-gene prognostic signature. Results Totally 261 genes were found to be dysregulated. 10 genes were considered to be the hub genes. The Kaplan-Meier analysis showed that upregulated SPP1, FN1, CXCL8, BIRC5, PLAUR, and AURKA were related to poor outcomes in OSCC patients. FOXM1 and TPX2 were considered as the potential immunotherapeutic targets with future clinical significance. Moreover, we constructed a nine-gene signature (TEX101, DSG2, SCG5, ADA, BOC, SCARA5, FST, SOCS1, and STC2), which can be utilized to predict prognosis of OSCC patients effectively. Conclusion These findings may provide new clues for exploring the molecular mechanisms and targeted therapy in OSCC. The hub genes and risk gene signature are helpful to the personalized treatment and prognostic judgement.

Drug resistance, whether intrinsic or acquired, often leads to treatment failure in esophageal squamous cell carcinoma (ESCC). Clarifying the mechanism of drug resistance in ESCC has great significance for reversing drug resistance, as well as improving the prognosis of patients. Previously, we demonstrated that etoposideinduced 2.4-kb mRNA (EI24) is the target of miR-483-3p, which promoted the growth, migration, and drug resistance in ESCC, suggesting that EI24 participates in repressing the tumorigenesis and progression of ESCC. Here, we observed that EI24 was remarkably decreased in ESCC tissues. Moreover, its expression was directly linked to the prognosis of patients. We then confirmed that the forced overexpression of EI24 repressed cell growth and sensitized ESCC cells to chemotherapeutic agents, whereas EI24 silencing had the opposite effect. Furthermore, gene microarray and ingenuity pathway analysis (IPA) were performed to establish the potential mechanisms and indicated that EI24 exerts a tumor-suppressive role via suppressing the acute phase response signaling pathway or IL-1 signaling pathway in ESCC. Collectively, our data reveal that EI24 overexpression attenuates malignant phenotypes of ESCC and that it is a novel possible ESCC therapeutic target.