scholarly journals Identification and Verification of Radiosensitivity Gene Expression Prediction Model in Neoadjuvant Radiotherapy of Locally Advanced Rectal Cancer Patients

Author(s):  
R. Zheng ◽  
B. Xu ◽  
B. Guan ◽  
G. Guan ◽  
P. Chi
2021 ◽  
Vol 67 (2) ◽  
pp. 190-201
Author(s):  
Georgiy Pan`shin ◽  
Nelly Sidibe ◽  
Timur Izmailov

Currently, rectal cancer is one of the leading pathologies in the structure of cancer morbidity and mortality, both in Russia and around the world.                                                                                                      Thus, despite the improvement of existing and development of new methods for surgical treatment and anesthesia, as well as the introduction of the use of radio-and chemotherapy as an adjunct to surgical stage of the treatment, colorectal cancer still has a very high mortality rate among this cohort of cancer patients, and, primarily, due to the fact that approximately 30% of cases it is diagnosed at a very late stages of the disease. And, at the same time, combined and complex therapy to date does not contribute to improving the long-term results of special treatment, which, in the end, range from a complete response, in particular, during radiotherapy treatment, up to absolute resistance to its implementation.                                                                              However, to date, there are already studies confirming the link between radioresistance and gene expression, which induce a response to the DNA damage checkpoint and increase the ability to repair DNA. At the same time, molecular biomarkers have a definite potential to predict the response to, in particular, neoadjuvant chemoradiotherapy for rectal cancer.                                                                                                                                                                        This brief review examines the evolution and current state of neoadjuvant (preoperative) chemoradiotherapy for locally advanced rectal cancer (MRPC). At the same time, it should be emphasized that randomized studies and meta-analyses of recent publications justify the expediency of its use in this category of cancer patients.  Modern strategies for treating patients with locally advanced rectal cancer and radiotherapy regimens used in this clinical situation are also briefly considered, as well as the prospects for using molecular genetic markers of radiosensitivity and their possible impact on the prognosis of this cancer.


2020 ◽  
Vol 150 ◽  
pp. S48-S49
Author(s):  
Aswin George Abraham ◽  
Nawaid Usmani ◽  
Karen Mulder ◽  
JoAnn Thai ◽  
Sunita Ghosh ◽  
...  

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Jiazhou Wang ◽  
Lijun Shen ◽  
Haoyu Zhong ◽  
Zhen Zhou ◽  
Panpan Hu ◽  
...  

Abstract This retrospective study was to investigate whether radiomics feature come from radiotherapy treatment planning CT can predict prognosis in locally advanced rectal cancer patients treated with neoadjuvant chemoradiation followed by surgery. Four-hundred-eleven locally advanced rectal cancer patients which were treated with neoadjuvant chemoradiation enrolled in this study. All patients’ radiotherapy treatment planning CTs were collected. Tumor was delineated on these CTs by physicians. An in-house radiomics software was used to calculate 271 radiomics features. The results of test-retest and contour-recontour studies were used to filter stable radiomics (Spearman correlation coefficient > 0.7). Twenty-one radiomics features were final enrolled. The performance of prediction model with the radiomics or clinical features were calculated. The clinical outcomes include local control, distant control, disease-free survival (DFS) and overall survival (OS). Model performance C-index was evaluated by C-index. Patients are divided into two groups by cluster results. The results of chi-square test revealed that the radiomics feature cluster is independent of clinical features. Patients have significant differences in OS (p = 0.032, log rank test) for these two groups. By supervised modeling, radiomics features can improve the prediction power of OS from 0.672 [0.617 0.728] with clinical features only to 0.730 [0.658 0.801]. In conclusion, the radiomics features from radiotherapy CT can potentially predict OS for locally advanced rectal cancer patients with neoadjuvant chemoradiation treatment.


2019 ◽  
Vol 120 (2) ◽  
pp. 308-315
Author(s):  
Karin M. Hardiman ◽  
Alexis G. Antunez ◽  
Arielle Kanters ◽  
Ari D. Schuman ◽  
Scott E. Regenbogen

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