Project description:Colorectal cancer (CRC) is the third most common lethal malignancy in Korea and worldwide. Rectal cancer patients occupy about 30% of CRC patients, and the majority of rectal cancer patients had locally advanced disease at diagnosis. The standard treatment of locally advanced rectal cancer (LARC) is neoadjuvant radiation therapy with concurrent chemotherapy (CCRT) followed by total mesorectal excision (TME). This multidisciplinary team approach improved local tumor control and overall survival of rectal cancer patients. High throughput proteomic analysis and machine learning algorithm identify DUOX2 (dual oxidase 2) as a novel biomarker for prediction of non-complete response after concurrent chemoradiation therapy for rectal cancer.High throughput proteomic analysis and machine learning algorithm identify DUOX2 (dual oxidase 2) as a novel biomarker for prediction of non-complete response after concurrent chemoradiation therapy for rectal cancer.
Project description:The treatment strategy of rectal cancer has substantially changed in recent decades. Historically postoperative chemoradiotherapy (CRT) was considered to be the first-line therapy for stage II and III rectal cancers. However, the preoperative CRT is now considered to be the optimal therapy regimen for locally advanced rectal ancer due to its improved local control, reduced toxicity, and increased rate of sphincter preservation. Our study established a clinically practical multi-class prediction model by adopting a novel strategy that applies two separate prediction models (MI and TO predictor) sequentially to a patient to predict the response. For promising clinical practice, we validated our model in a published dataset, which is completely independent dataset from ours. This study suggests a clinically plausible prediction model that correctly infers the preoperative CRT response of patients with high accuracy based on 163 gene signatures we identified. Total RNAs were isolated from primary rectal tumor tissues of 69 patients who underwent chemoradiation therapy (CRT). These patients are classified into four different CRT responses: minimal response (MI), moderate response (MO), near total response (NT) and total response (TO). All the RNAs were subjected to microarray analysis using Affymetrix GenChip arrays.
Project description:The treatment strategy of rectal cancer has substantially changed in recent decades. Historically postoperative chemoradiotherapy (CRT) was considered to be the first-line therapy for stage II and III rectal cancers. However, the preoperative CRT is now considered to be the optimal therapy regimen for locally advanced rectal ancer due to its improved local control, reduced toxicity, and increased rate of sphincter preservation. Our study established a clinically practical multi-class prediction model by adopting a novel strategy that applies two separate prediction models (MI and TO predictor) sequentially to a patient to predict the response. For promising clinical practice, we validated our model in a published dataset, which is completely independent dataset from ours. This study suggests a clinically plausible prediction model that correctly infers the preoperative CRT response of patients with high accuracy based on 163 gene signatures we identified.
Project description:Cancer-associated fibroblasts (CAFs) are an important component of the desmoplastic stroma in rectal cancer. Preoperative chemoradiotherapy plays a pivotal role in the management of locally advanced rectal cancer. Patient-derived CAFs were used to evaluate the response to radiotherapy and its consequent impact on colorectal cancer cells (COLO320DM). COLO320DM cells were seeded and 24 hours later 1.8Gy irradiated. Subsequently, 24h later COLO320DM cells were treated with the secretome of 10x 1.8Gy irradiated CAFs or sham treated CAFs in 0.5% of serum. RNA was isolated 6 hours or 48 hours later.
Project description:To measure global gene expression in primary locally advanced rectal cancer patients who have undergone CRT and screen valuable biomarkers to predict the effects of CRT.Samples fromprimary locally advanced rectal cancer patients were collected. The effects of chemoradiotherapy were evaluated.
Project description:Understanding transcriptional changes in locally advanced rectal cancer which are therapy-related and dependent upon tumour regression will drive stratified medicine in the rectal cancer paradigm
Project description:Neoadjuvant chemoradiotherapy (CRT) is used in locally advanced rectal cancer when tumours threaten the circumferential resection margin. A variable response to treatment remains, notwithstanding potentially significant morbidity, and no clinically routinely used predictive biomarkers guide decision making. This experimental study aimed to identify significantly differentially expressed proteins between patients responding or not to CRT, using novel temporal proteomic profiling, and to validate any proteins of interest.
Project description:Purpose: Preoperative 5-fluorouracil (5-FU) based radiochemotherapy (RCT) represents the standard treatment for locally advanced rectal cancer. Both, tumor response and progression vary considerably. MicroRNAs represent master regulators of gene expression, and may therefore contribute to this heterogeneity. Results: Thirty-six miRNAs were identified to significantly correlate with sensitivity of CRC cell lines to RCT (q < 0.05). This list included miR320a as most significantly correlated as well as other miRNAs involved in the MAPK-, TGF- and Wnt-pathway. Importantly, transfection of selected miRNAs (let7g, miR-132, miR-224, miR-320a and miR-429) each induced a shift of sensitivity (p<0.00001). Moreover, high expression of miR-224 was associated with a poor prognosis in rectal cancer patients (p=0.043). Experimental design: Genome-wide microRNA (miRNA) profiling was performed from 12 colorectal cancer (CRC) cell lines. To establish an in vitro signature of radiochemosensitivity, these profiles were correlated to the individual sensitivities of each cell line to 5-FU and radiation. The functional relevance of selected miRNAs was validated by transfecting miRNA-mimics into SW480 cells, followed by treatment with 5-FU and radiation. 12 Samples with 3 replicates each.
