Refining prognosis in early-stage colorectal cancer: one or multiple genes at a time?

LncRNA PTTG3P Sponge Absorbs microRNA-155-5P to Promote Metastasis of Colorectal Cancer

Objective

To study the role of LncRNA PTTG3P in colorectal cancer (CRC) and the underlying mechanism.

Patients and Methods

The expression level of LncRNA PTTG3P was evaluated by quantitative real-time polymerase chain reaction (qRT-PCR) in CRC cell lines and tumor tissues from 43 CRC patients, and the correlations between LncRNA PTTG3P expression and the clinicopathological indicators and prognosis of CRC patients were analyzed. Then, a PTTG3P knockdown model in CRC cell lines HCT-8 and HCT-116 was constructed. Finally, the relationship between LncRNA PTTG3P and microRNA-155-5p was explored through luciferase reporter experiments and recovery experiments.

Results

qRT-PCR results showed that LncRNA PTTG3P was markedly up-regulated in CRC tumor tissues than that in adjacent tissues. Meanwhile, patients with high LncRNA PTTG3P expression had higher rates of lymph node metastasis and distant metastasis. In addition, cell functional experiments suggested that knocking down PTTG3P markedly reduced the migration abilities of CRC cells. Subsequently, bioinformatics analysis and luciferase reporter gene experiments suggested that LncRNA PTTG3P could directly bind to microRNA-155-5P. Analysis of CRC tissue samples showed that microRNA-155-5P expression was markedly reduced in CRC and was negatively correlated with LncRNA PTTG3P. Finally, the recovery experiments also suggested that there was a mutual regulation between LncRNA PTTG3P and microRNA-155-5P, and silencing microRNA-155-5P can reverse the inhibitory effect of knocking down PTTG3P on the malignant progression of CRC.

Conclusion

In summary, LncRNA PTTG3P level was markedly increased in CRC, and was highly correlated to the incidence of lymph node metastasis and distant metastasis in CRC patients. In addition, LncRNA PTTG3P might promote the ability of CRC to invade and migrate by downregulating microRNA-155-5P. Therefore, dissecting the aberrant regulation of LncRNA PTTG3P/microRNA-155-5P may be valuable for early screening, guidance treatment, and recurrence detection of CRC.

COX-2/C-MET/KRAS status-based prognostic nomogram for colorectal cancer: A multicenter cohort study

BACKGROUND/AIM

To construct quantitative prognostic models for colorectal cancer (CRC) based on COX-2/C-MET/KRAS expression status in clinical practice.

PATIENTS AND METHODS

Clinical factors and COX-2/C-MET/KRAS expression status of 578 eligible patients from two Chinese hospitals were included. The patients were randomly allocated into training and validation datasets. We created several models using Cox proportional hazard models: Signature^C contained clinical factors, Signature^G contained COX-2/C-MET/KRAS expression status, and Signature^CG contained both. After comparing their accuracy, nomograms for progression-free survival (PFS) and overall survival (OS) were built for the best signatures, with their concordance index and calibration tested. Further, patients were subgrouped by the median of the best signatures, and survival differences between the subgroups were compared.

RESULTS

For PFS, among the three signatures, Signature^PFS-CG had the best area under the curve (AUC), with the 1-, 2- and 3-year AUCs being 0.70, 0.73 and 0.89 in the training dataset, respectively and 0.67, 0.73 and 0.87 in the validation dataset, respectively. For OS, the AUCs of Signature^OS-CG for 1-, 2- and 3-years were 0.63, 0.71 and 0.81 in the training dataset, respectively and 0.68, 0.71 and 0.76 in validation dataset, respectively. The nomograms based on Signature^PFS-CG and Signature^OS-CG had good calibrations. Subsequent stratification analysis demonstrated that the subgroups were significantly different for both PFS (training:P < 0.001; validation:P< 0.001) and OS (training:P < 0.001; validation:P < 0.001).

CONCLUSIONS

Combining clinical factors and COX-2/C-MET/KRAS expression status, our models provided accurate prognostic information in CRC. They can be used to aid treatment decisions in clinical practice.