HYBRID EVENT: You can participate in person at Baltimore, Maryland, USA or Virtually from your home or work.
Xiangyu Su, Speaker at Cancer Conferences
Southeast University, China

Abstract:

Esophageal cancer(EC) is a common digestive malignancy that ranks sixth in cancer deaths, with a 5-year survival rate of 15-25%. As a result, reliable prognostic biomarkers are required to accurately predict the prognosis of EC. T-cell exhaustion(TEX) is associated with poorer prognosis and immune infiltration in EC. In this study, nine risk genes were finally screened to constitute the prognostic model using LASSO analysis. Patients were divided into two groups based on the expression of the TEX-related genes: high-risk group and low-risk group. The expression of TEX-related genes differed significantly between the two groups. The findings revealed that the risk model developed was highly related to the clinical prognosis and amount of immune cell infiltration in EC patients. It was also significantly correlated with the therapeutic sensitivity of multiple chemotherapeutic agents in EC patients. Subsequently, we successfully constructed drug-resistant cell lines KYSE480/CDDP-R and KYSE180/CDDP-R to verify the correlation between PDCD1 and drug resistance in EC. Then, we examined the mRNA and protein expression levels of PDCD1 in parental and drug-resistant cells using qPCR and WB. It was found that the expression level of PDCD1 was significantly increased in the plasma red of drug-resistant cells. Next, we knocked down PDCD1 in drug-resistant cells and found that the resistance of EC cells to CDDP was significantly reduced. And the proportion of apoptotic cells in cells treated with 6 µM CDDP for 24h was significantly in increase. The TEX-based risk model achieved good prediction results for prognosis prediction in EC patients. And it was also significantly associated with the level of immune cell infiltration and drug therapy sensitivity of EC patients. The high-risk group had lower TIDE scores, indicating that the high-risk group benefits more after receiving immunotherapy. Thus the TEX-based risk model can be used as a novel tumor prognostic biomarker.

Audience Take Away Notes:
The TEX-based risk model can be used as a novel tumor prognostic biomarker for risk stratification and EC patient prognosis prediction
Our study provides a new biomarker for predicting the prognosis of patients with esophageal cancer and could help physicians to more accurately predict patient prognosis and response to treatment
Our study found that PDCD1 plays an important role in drug resistance in esophageal cancer, which provides new ideas for the development of new treatment strategies

Biography:

Dr. Xiangyu Su studied clinical medicine at the Southeast University, China and graduated as Bachelor in 2005. He received his MS degree in 2008 at the same institution. He then joined Department of Oncology, Zhongda Hospital affiliated Southeast University, Nanjing, China. He is a PhD candidate in Oncology at Southeast University. He has published more than 10 research articles in SCI (E) journals.

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