Project description:Identifying the exact molecules associated with CRC metastasis may be crucial to understand the process, which might also be translated to the diagnosis and treatment of CRC. In this study, we investigate the association of microRNA expression patterns with the lymph node metastasis of colorectal cancer. To investigate the association of microRNA expression patterns with the lymph node metastasis of colorectal cancer, eight primary colorectal cancer tissues derived from stage II–III colorectal cancer patients with (n = 4) or without (n = 4) lymph node metastasis were collected and the miRNA expression profiles of them were determined using Agilent miRNA microarray. Different miRNA expression profiles were identified in CRC tissues between lymph node metastasis positive and negative group.
Project description:If we can more accurately predict the likelihood of regional lymph node metastasis (LNM) for endoscopically resected T1-stage colorectal cancers (CRC), the number of unnecessary additional surgeries can be reduced. We aimed of identify miRNA markers that can predict LNM-positive tumors among T1-stage CRCs and we also developed a miRNA classifier set for facilitating the accuracy and applicability.
Project description:Surgical resection of colorectal cancers (CRC) that have not invaded beyond the bowel wall (i.e. Stage I) can achieve 5-year patient survival rates exceeding 90%. In the majority of Stage I cases with T1 (submucosal) or T2 (not beyond the muscularis propria) depth of tumour invasion, surgery alone is curative. However, for approximately 10% of resected T1/2 CRC, even though histopathology inspection of the tumour deems it to be restricted to the bowel wall, malignant cells are identified in draining lymph nodes, signifying local metastasis. These patients are classified with Stage IIIA disease and are at greater risk than Stage I patients whose tumours show similar invasive depth, but lack lymph node involvement. To counter the risk of distant malignant dissemination, Stage IIIA patients require more extensive treatment with adjuvant chemotherapy, while Stage I patients do not. In this study we aim to get a better understanding of the underlying biological pathways linked to lymph node metastasis (LNM) using discovery based MS (DIA) and RNASeq as well as IHC and PRM to verify possible protein marker. All of this was done on archival tissue samples (FFPE).
Project description:Lymph node status is a crucial predictor for the overall survival of invasive breast cancer. However, lymph node involvement is only detected in about half of HER2 positive patients. Currently, there are no biomarkers available for distinguishing small size HER2-positive breast cancers with different lymph node statuses. Thus, in the present study, we applied label-free quantitative proteomic strategy to construct plasma proteomic profiles of ten patients with small size HER2-positive breast cancers (5 patients with lymph node metastasis versus 5 patients with lymph node metastasis).
Project description:Both the univariate analysis and multivariate analysis showed that the status of primary lymph node was the strongest predict factor. The subgroup analysis confirmed that the lymph node metastasis was associated to worse prognosis only in stage T3 and T4, rather than in stage T1 and T2. We firstly proposed the hypothesis that the status of lymph node reflected delayed diagnose of the disease, rather than the biological behavior of “seed”. The mRNA profile showed that there was minimal difference between lymph node positive and negative subgroups. The status of lymph node reflected delayed diagnose of the disease, rather than the biological behavior of “seed”.
Project description:Gene expression profiling of early stage cervical cancer tumours with and without lymph node metastasis, in order to predict lymph node metastasis before treatment. Subsequently, comparing gene expression profiles between healthy cervical tissue and early stage cervical cancer tissue. Keywords: Disease stage analysis
Project description:Samples were taken from colorectal cancers in surgically resected specimens in 36 colorectal cancer patients. The expression profiles were determined using Affymetrix Human Genome U133 Plus 2.0 arrays. Comparison between the sample groups allow to identify a set of discriminating genes that can be used for molecular markers for predicting recurrence. Keywords: repeat Thirty-six colorectal cancer patients who had undergone surgical resection of colorectal cancer were studied. In all patients, curative resection was performed and no patients had any distant metastasis at the time of operation (stage III patients). Among the 36 patients, 23 patients did not develop recurrence. On the other hand, 13 patients developed rucurrence such as liver metastases, lung metastases and distant lymph node metastases. The median follow up period was 4.5 years.
Project description:The presence of lymph node metastasis (LNM) affects treatment strategy decisions in T1NxM0 colorectal cancer (CRC), but the currently used clinicopathological-based risk stratification cannot be used to accurately predict LNM. In this study, we established a model for predicting LNM and explored the mechanism of metastasis in T1 CRC.
Project description:Identifying the exact molecules associated with CRC metastasis may be crucial to understand the process, which might also be translated to the diagnosis and treatment of CRC. In this study, we investigate the association of microRNA expression patterns with the lymph node metastasis of colorectal cancer.
Project description:Microarray was used to find out the differentially expressed in tumor sites of early-stage oral squamous cell carcinoma compared with Normal parts. Furthermore, we compared cases of early-stage oral squamous cell carcinoma with lymph node metastasis with cases without lymph node metastasis. The miRNAs obtained may not only serve as predictive biomarkers for lymph node metastasis, but may also be used further to understand disease.