To investigate the global proteomic profiles of vascular endothelial cells (VECs) in the tumor microenvironment and antiangiogenic therapy for colorectal cancer (CRC), matched pairs of normal (NVECs) and tumor-associated VECs (TVECs) were purified from CRC tissues by laser capture microdissection and subjected to iTRAQ based quantitative proteomics analysis. Here, 216 differentially expressed proteins (DEPs) were identified and performed bioinformatics analysis. Interestingly, these proteins were implicated in epithelial mesenchymal transition (EMT), ECM-receptor interaction, focal adhesion, PI3K-Akt signaling pathway, angiogenesis and HIF-1 signaling pathway, which may play important roles in CRC angiogenesis. Among these DEPs, we found that Tenascin-C (TNC) was upregulated in TVECs of CRC and correlated with CRC multistage carcinogenesis and metastasis. Furthermore, the reduction of tumor-derived TNC could attenuate human umbilical vein endothelial cell (HUVEC) proliferation, migration and tube formation through ITGB3/FAK/Akt signaling pathway. Based on the present work, we provided a large-scale proteomic profiling of VECs in CRC with quantitative information, a certain number of potential antiangiogenic targets and a novel vision in the angiogenesis bio-mechanism of CRC.

Nucleotide excision repair (NER) is an important mediator for responsiveness of platinum-based chemotherapy. Our study is aimed at investigating the NER-related genes expression in ascites tumor cells and its application in the prediction of chemoresponse in high-grade serous ovarian cancer (HGSC) patients. The relationship between 16 NER-related genes and the prognosis of ovarian cancer was analyzed in the TCGA database. NER-related genes including HELQ and XAB2 expressions were determined via immunocytochemistry in ascites cell samples from 92 ovarian cancer patients prior to primary cytoreduction surgery. Kaplan-Meier analysis and Cox model were used to investigate the association between NER-related gene expression and prognosis/chemotherapeutic response. Predicting models were constructed using a training cohort of 60 patients and validated in a validation cohort of 32 patients. We found that high expression of HELQ and XAB2 in the training cohort was associated with poor prognosis (for HELQ, , , 95% CI: 1.46-5.49; for XAB2, , , 95% CI: 1.23-4.63) and platinum resistance (for HELQ, ; for XAB2, ). In the validation cohort, the combination of HELQ and XAB2 ( ) showed the highest AUC. The expression levels of HELQ (RR 5.7, 95% CI 1.7-19.2) and XAB2 (RR 3.2, 95% CI 0.9-10.8) in ascites tumor cells were positively correlated to the risk of platinum resistance. In summary, we revealed that the expression levels of HELQ and XAB2 are candidate predictors for primary chemotherapy responsiveness and prognosis in HGSC. Ascites cytology is applicable as a promising method for chemosensitivity prediction in HGSC.

Background: Macrotrabecular hepatocellular carcinoma (MTHCC) has a poor prognosis and is difficult to diagnose preoperatively. The purpose is to build and validate MRI-based models to predict the MTHCC subtype. Methods: Two hundred eight patients with confirmed HCC were enrolled. Three models (model 1: clinicoradiologic model; model 2: fusion radiomics signature; model 3: combined model 1 and model 2) were built based on their clinical data and MR images to predict MTHCC in training and validation cohorts. The performance of the models was assessed using the area under the curve (AUC). The clinical utility of the models was estimated by decision curve analysis (DCA). A nomogram was constructed, and its calibration was evaluated. Results: Model 1 is easier to build than models 2 and 3, with a good AUC of 0.773 (95% CI 0.696–0.838) and 0.801 (95% CI 0.681–0.891) in predicting MTHCC in training and validation cohorts, respectively. It performed slightly superior to model 2 in both training (AUC 0.747; 95% CI 0.689–0.806; p = 0.548) and validation (AUC 0.718; 95% CI 0.618–0.810; p = 0.089) cohorts and was similar to model 3 in the validation (AUC 0.866; 95% CI 0.801–0.928; p = 0.321) but inferior in the training (AUC 0.889; 95% CI 0.851–0.926; p = 0.001) cohorts. The DCA of model 1 had a higher net benefit than the treat-all and treat-none strategy at a threshold probability of 10%. The calibration curves of model 1 closely aligned with the true MTHCC rates in the training (p = 0.355) and validation sets (p = 0.364). Conclusion: The clinicoradiologic model has a good performance in diagnosing MTHCC, and it is simpler and easier to implement, making it a valuable tool for pretherapeutic decision-making in patients.

Cervical cancer is one of the most common types of cancer and the fourth leading cause of cancer‑related deaths in women. The occurrence and development of cervical cancer is a multifactorial and multilevel process, which usually occurs alongside a continuous high‑risk human papillomavirus infection. With further developments in molecular biology and the advancement of sequencing technology, the role of biomarkers in cervical diseases has been gradually recognized. Therefore, it remains a priority to identify key molecular markers that can be used for the screening and triaging of the lesions. In recent years, numerous studies have been conducted in order to identify important markers for cervical diseases. The present review aimed to summarize the molecular alterations and clinical relevance of chromosomal alterations, DNA polymorphisms, the DNA methylation status, histone modifications, and alterations in microRNA and protein expression levels. Accumulating evidence suggests that molecular alterations may reflect the degree and the prognosis of the disease. Although significant progress has been made in the field of cervical cancer research, further samples and experiments are still required to identify crucial molecules.