Upregulation of cervical carcinoma expressed PCNA regulatory long non-coding RNA promotes esophageal squamous cell carcinoma progression

DNA replication: Mechanisms and therapeutic interventions for diseases

Accurate and integral cellular DNA replication is modulated by multiple replication-associated proteins, which is fundamental to preserve genome stability. Furthermore, replication proteins cooperate with multiple DNA damage factors to deal with replication stress through mechanisms beyond their role in replication. Cancer cells with chronic replication stress exhibit aberrant DNA replication and DNA damage response, providing an exploitable therapeutic target in tumors. Numerous evidence has indicated that posttranslational modifications (PTMs) of replication proteins present distinct functions in DNA replication and respond to replication stress. In addition, abundant replication proteins are involved in tumorigenesis and development, which act as diagnostic and prognostic biomarkers in some tumors, implying these proteins act as therapeutic targets in clinical. Replication-target cancer therapy emerges as the times require. In this context, we outline the current investigation of the DNA replication mechanism, and simultaneously enumerate the aberrant expression of replication proteins as hallmark for various diseases, revealing their therapeutic potential for target therapy. Meanwhile, we also discuss current observations that the novel PTM of replication proteins in response to replication stress, which seems to be a promising strategy to eliminate diseases.

DDTC Suppresses Ovarian Cancer Development via the PI3K/AKT/mTOR Signaling Pathway

In prior research, 6,12-diphenyl-3,9-diazatetraasterane-1, 5, 7, 11-tetracarboxylate (DDTC) has been shown to be an effective inhibitor of the growth of the SKOV3 and A2780 ovarian cancer (OC) cell lines. Flow cytometry analyses indicated that DDTC was able to suppress P-CNA expression at the protein level within OC cells, while RNA-seq indicated that DDTC treatment was associated with marked changes in gene expression profiles within A2780 cells. Molecular docking analyses suggested that DDTC has the potential to readily dock with key signaling proteins including PI3K, AKT, and mTOR. In line with these findings, DDTC treatment inhibited the growth of xenograft tumors in a mouse model system. Such treatment was also associated with reduced p-PI3K/PI3K, p-AKT/AKT, p-mTOR/mTOR, and CyclinD1 (CCND1) expressions and with the increased expression of PTEN in vitro and in vivo. Together, these results suggest that DDTC is capable of readily inhibiting OC development at least in part via targeting and modulating signaling via the PI3K/AKT/mTOR axis.

A Nomogram Based on Molecular Biomarkers and Radiomics to Predict Lymph Node Metastasis in Breast Cancer

Background

The aim of this study was to explore the feasibility and efficacy of a non-invasive quantitative imaging evaluation model to assess the lymphatic metastasis of breast cancer based on a radiomics signature constructed using conventional T1-weighted image (T1WI) enhanced MRI and molecular biomarkers.

Methods

Patients with breast cancer diagnosed via lymph biopsies between June 2015 and June 2019 were selected for the study. All patients underwent T1WI contrast-enhancement before treatment; lymph biopsy after surgery; and simultaneous Ki-67, COX-2, PR, Her2 and proliferating cell nuclear antigen detection. All images were imported into ITK-SNAP for whole tumor delineation, and AK software was used for radiomics feature extraction. Next, the radiomics signature Rad-score was constructed after reduction of specific radiomic features. A multiple regression logistic model was built by combining the Rad-score and molecular biomarkers based on the minimum AIC.

Results

In all, 100 patients were enrolled in this study, including 45 with non-lymph node (LN) metastasis and 55 with LN metastasis. A total of 1,051 texture feature parameters were extracted, and LASSO was used to reduce the dimensionality of the radiomics features. The log(λ) was set to 0.002786, and 19 parameters were retained for the construction of the radiomics tag Rad-score. ROC was used to evaluate the diagnostic efficiency of Rad-score: the area under the ROC curve (AUC) of the Rad-score for identifying non-lymphatic and lymphatic metastases was 0.891 in the training cohort and 0.744 in the validation cohort. With the incorporation of tumor molecular markers, the AUCs of the training cohort and validation cohort of the nomogram were 0.936 and 0.793, respectively, which were notably higher than the AUCs of the clinical parameters in the training and validation cohorts (0.719 and 0.588, respectively).

Conclusion

The combined model constructed using the Rad-score and molecular biomarkers can be used as an effective non-invasive method to assess LN metastasis of breast cancer. Furthermore, it can be used to quantitatively evaluate the risk of breast cancer LN metastasis before surgery.