Background/Aims: MicroRNA-142-3p (miR-142-3p) is dysregulated in many malignancies and may function as a tumor suppressor or oncogene in tumorigenesis and tumor development. However, few studies have investigated the clinical significance and biological function of miR-142-3p in hepatocellular carcinoma (HCC). Methods: The expression levels of taurine upregulated gene 1 (TUG1), miR-142-3p, and zinc finger E-box-binding homeobox 1 (ZEB1) were evaluated in HCC tissues and cell lines by quantitative real-time PCR. MTT and colony formation assays were used to detect cell proliferation ability, transwell assays were used to assess cell migration and invasion, and luciferase reporter assays were used to examine the interaction between the long noncoding RNA TUG1 and miR-142-3p. Tumor formation was evaluated through in vivo experiments. Results: miR-142-3p was significantly downregulated in HCC tissues, but TUG1 was upregulated in HCC tissues. Knockdown of TUG1 and upregulation of miR-142-3p inhibited cell proliferation, cell migration, cell invasion, and the epithelial-mesenchymal transition (EMT). miR-142-3p was found to be a prognostic factor of HCC, and the mechanism by which TUG1 upregulated ZEB1 was via direct binding to miR-142-3p. In vivo assays showed that TUG1 knockdown suppressed cell proliferation and the EMT in nude mice. Conclusion: The results of this study suggest that the TUG1/miR-142-3p/ ZEB1 axis contributes to the formation of malignant behaviors in HCC.

Defects in DNA damage repair may cause genome instability and cancer development. The tumor suppressor gene p53 regulates cell cycle arrest to allow time for DNA repair. The oncoprotein mouse double minute 2 (MDM2) promotes cell survival, proliferation, invasion, and therapeutic resistance in many types of cancer. The major role of MDM2 is to inhibit p53 activity and promote its degradation. In this review, we describe the influence of MDM2 on genomic instability, the role of MDM2 on releasing p53 and binding DNA repair proteins to inhibit repair, and the regulation network of MDM2 including its transcriptional modifications, protein stability, and localization following DNA damage in genome integrity maintenance and in MDM2-p53 axis control. We also discuss p53-dependent and p53 independent oncogenic function of MDM2 and the outcomes of clinical trials that have been used with clinical inhibitors targeting p53-MDM2 to treat certain cancers.

IntroductionLung cancer is the most common cancer and the leading cause of cancer death in China, as well as in the world. Late diagnosis is the main obstacle to improving survival. Currently, early detection methods for lung cancer have many limitations, for example, low specificity, risk of radiation exposure and overdiagnosis. Exhaled breath analysis is one of the most promising non-invasive techniques for early detection of lung cancer. The aim of this study is to identify volatile organic compound (VOC) biomarkers in lung cancer and to construct a predictive model for lung cancer based on exhaled breath analysis.Methods and analysisThe study will recruit 389 lung cancer patients in one cancer centre and 389 healthy subjects in two lung cancer screening centres. Bio-VOC breath sampler and Tedlar bag will be used to collect breath samples. Gas chromatography-mass spectrometry coupled with solid phase microextraction technique will be used to analyse VOCs in exhaled breath. VOC biomarkers with statistical significance and showing abilities to discriminate lung cancer patients from healthy subjects will be selected for the construction of predictive model for lung cancer.Ethics and disseminationThe study was approved by the Ethics Committee of Sichuan Cancer Hospital on 6 April 2017 (No. SCCHEC-02-2017-011). The results of this study will be disseminated in presentations at academic conferences, publications in peer-reviewed journals and the news media.Trial registration numberChiCTR-DOD-17011134; Pre-results.

Non-small cell lung cancer (NSCLC) patients with Kirsten rat sarcoma viral oncogene homolog (KRAS) mutation are associated with significant clinical heterogeneity and a poor prognosis to standard NSCLC therapies such as surgical resection, radiotherapy, chemotherapies, and targeted medicines. However, the application of immune checkpoints inhibitors (ICIs) has dramatically altered the therapeutic pattern of NSCLC management. Clinical studies have indicated that some KRAS-mutant NSCLC patients could benefit from ICIs; however, the responses in some patients are still poor. This review intends to elucidate the mechanisms of resistance to immunotherapy in KRAS-driven NSCLC and highlight the TME functions altered by immunoinhibitors, immunostimulators, and cancer metabolism. These metabolic pathways could potentially be promising approaches to overcome immunotherapy resistance.

Background Cervical cancer (CC) represents the fourth most frequently diagnosed malignancy affecting women all over the world. However, effective prognostic biomarkers are still limited for accurately identifying high-risk patients. Here, we provided a combination machine learning algorithm-based signature to predict the prognosis of cervical squamous cell carcinoma (CSCC). Methods and materials After utilizing RNA sequencing (RNA-seq) data from 36 formalin-fixed and paraffin-embedded (FFPE) samples, the most significant modules were highlighted by the weighted gene co-expression network analysis (WGCNA). A candidate genes-based prognostic classifier was constructed by the least absolute shrinkage and selection operator (LASSO) and then validated in an independent validation set. Finally, based on the multivariate analysis, a nomogram including the FIGO stage, therapy outcome, and risk score level was built to predict progression-free survival (PFS) probability. Results A mRNA-based signature was developed to classify patients into high- and low-risk groups with significantly different PFS and overall survival (OS) rate (training set: p < 0.001 for PFS, p = 0.016 for OS; validation set: p = 0.002 for PFS, p = 0.028 for OS). The prognostic classifier was an independent and powerful prognostic biomarker for PFS in both cohorts (training set: hazard ratio [HR] = 0.13, 95% CI 0.05–0.33, p < 0.001; validation set: HR = 0.02, 95% CI 0.01–0.04, p < 0.001). A nomogram that integrated the independent prognostic factors was constructed for clinical application. The calibration curve showed that the nomogram was able to predict 1-, 3-, and 5-year PFS accurately, and it performed well in the external validation cohorts (concordance index: 0.828 and 0.864, respectively). Conclusion The mRNA-based biomarker is a powerful and independent prognostic factor. Furthermore, the nomogram comprising our prognostic classifier is a promising predictor in identifying the progression risk of CSCC patients.

Background The main limitation of current immune checkpoint inhibitors (ICIs) in the treatment of cervical cancer comes from the fact that it benefits only a minority of patients. The study aims to develop a classification system to identify immune subtypes of cervical squamous cell carcinoma (SCC), thereby helping to screen candidates who may respond to ICIs. Methods A real-world cervical SCC cohort of 36 samples were analyzed. We used a nonnegative matrix factorization (NMF) algorithm to separate different expression patterns of immune-related genes (IRGs). The immune characteristics, potential immune biomarkers, and somatic mutations were compared. Two independent data sets containing 555 samples were used for validation. Results Two subtypes with different immunophenotypes were identified. Patients in sub1 showed favorable progression-free survival (PFS) and overall survival (OS) in the training and validation cohorts. The sub1 was remarkably related to increased immune cell abundance, more enriched immune activation pathways, and higher somatic mutation burden. Also, the sub1 group was more sensitive to ICIs, while patients in the sub2 group were more likely to fail to respond to ICIs but exhibited GPCR pathway activity. Finally, an 83-gene classifier was constructed for cervical SCC classification. Conclusion This study establishes a new classification to further understand the immunological diversity of cervical SCC, to assist in the selection of candidates for immunotherapy.

BackgroundColorectal cancer (CRC) is estimated to be one of the most common cancers and the leading cause of cancer-related death worldwide. SOX9 is commonly overexpressed in CRC and participates in drug resistance. In addition, DNA damage repair confers resistance to anticancer drugs. However, the correlation between DNA damage repair and high SOX9 expression is still unclear. In this study, we aimed to investigate the function and the specific underlying mechanism of the SOX9-dependent DNA damage repair pathway in CRC.MethodsThe expression levels of SOX9 and MMS22L in CRC were examined by immunohistochemistry (IHC) and TCGA analysis. RNA sequencing was conducted in RKO SOX9-deficient cells and RKO shControl cells. Mechanistic studies were performed in CRC cells by modulating SOX9 and MMS22L expression, and we evaluated drug sensitivity and DNA damage repair signaling events. In addition, we investigated the effect of oxaliplatin in tumors with SOX9 overexpression and low expression of MMS22L in vivo.ResultsOur study showed that SOX9 has a higher expression level in CRC tissues than in normal tissues and predicts poor prognosis in CRC patients. Overexpression and knockdown of SOX9 were associated with the efficacy of oxaliplatin. In addition, SOX9 activity was enriched in the DNA damage repair pathway via regulation of MMS22L expression and participation in DNA double-strand break repair. SOX9 was upregulated and formed a complex with MMS22L, which promoted the nuclear translocation of MMS22L upon oxaliplatin treatment. Moreover, the xenograft assay results showed that oxaliplatin abrogated tumor growth from cells with MMS22L downregulation in mice.ConclusionsIn CRC, activation of the SOX9-MMS22L-dependent DNA damage pathway is a core pathway regulating oxaliplatin sensitivity. Targeting this pathway in oxaliplatin-resistant CRC cells is a promising therapeutic option.

Exhaled breath analysis has emerged as a promising non-invasive method for diagnosing lung cancer (LC), whereas reliable biomarkers are lacking. Herein, a standardized and systematic study was presented for LC diagnosis, classification and metabolism exploration. To improve the reliability of biomarkers, a validation group was included, and quality control for breath sampling and analysis, comprehensive pollutants analysis, and strict biomarker screening were performed. The performance of exhaled breath biomarkers was shown to be excellent in diagnosing LC even in early stages (stage I and II) with surpassing 0.930 area under the receiver operating characteristic (ROC) curve (AUC), 90% of sensitivity and 88% of specificity both in the discovery and validation analyses. Meanwhile, in these two groups, diagnosing subtypes of LC attained AUCs over 0.930 and reached 1.00 in the two subtypes of adenocarcinomas. It is demonstrated that the metabolism changes in LC are possibly related to lipid oxidation, gut microbial, cytochrome P450 and glutathione S-transferase, and glutathione pathways change in LC progression. Overall, the reliable biomarkers contribute to the clinical application of breath analysis in screening LC patients as well as those in early stages.