scholarly journals The expression of long-chain non-coding RNA DMTF1v4 in colorectal cancer tissue and its relationship with clinicopathological features

2019 ◽  
Vol 17 ◽  
pp. 205873921984554
Author(s):  
Yanjuan Cai ◽  
Shutong Zhuang ◽  
Hongpeng Liu ◽  
Jianfu Qiu ◽  
Li Zeng
Keyword(s):  
Colorectal Cancer ◽  
Regression Analysis ◽  
Distant Metastasis ◽  
Cox Regression ◽  
Cancer Tissue ◽  
Depth Of Invasion ◽  
Cox Regression Analysis ◽  
Node Metastasis ◽  
Non Coding Rna ◽  
Long Chain

Emerging studies have showed that long-chain non-coding RNA DMTF1v4 might participate in the process of multidrug resistance phenotype of gastric cancer. However, its expression and function in colorectal cancer (CRC) is still unknown. In this study, we discovered that DMTF1v4 was generally 5.15 ± 1.67 times upregulated in CRC tissues compared to the adjacent normal tissues. Moreover, the expression level of DMTF1v4 was closely related to the distant metastasis of tumor, but it was not related to age, sex, tumor location, tumor staging, depth of invasion, lymph node metastasis, and differentiation level. Survival analysis showed that the overall survival rate of patients with high expression of DMTF1v4 was 45.0% in cancer tissues, which was significantly lower than 82.5% of DMTF1v4 low expression patients (χ2 = 11.562, P < 0.01). The results of univariate COX regression analysis showed that DMTF1v4, TNM (tumor, node, metastasis) staging, distant metastasis, and tumor differentiation were closely related to the prognosis of patients ( P < 0.05). Multivariate COX regression analysis showed that DMTF1v4 and distant metastasis could be independent prognostic factors for CRC patients. In conclusion, this study revealed that DMTF1v4 might promote the development of CRC, which can be used as an independent factor to judge the prognosis of CRC.

scholarly journals Influence of Old Age on Risk of Lymph Node Metastasis and Survival in Patients With T1 Colorectal Cancer: A Population-Based Analysis

2021 ◽  
Author(s):  
Hua Ye ◽  
Bin Zheng ◽  
Qi Zheng ◽  
Ping Chen
Keyword(s):  
Colorectal Cancer ◽  
Logistic Regression ◽  
Regression Analysis ◽  
Lymph Node ◽  
Old Age ◽  
Competing Risks ◽  
Cox Regression ◽  
Cox Regression Analysis ◽  
Node Metastasis ◽  
T1 Colorectal Cancer

Abstract Background We aimed at determining the influence of old age on lymph node metastasis (LNM) and prognosis in T1 colorectal cancer (CRC). Methods We collected data from eligible patients in Surveillance, Epidemiology, and End Results database between 2004 and 2015. Independent predictors of LNM were identified by the logistic regression analysis. Cox regression analysis, propensity score-matched analysis and competing risks analysis were used to analyze the associations between old age and lymph node (LN) status, and to validate the prognostic value of old age on cancer-specific survival (CSS).Results In total, 10092 patients were identified. Among them, 6423 patients (63.6%) had greater than or equal to 12 examined lymph nodes (LNs) (LNE ³12), and 5777 patients (57.7%) were of 65 years or older. The observed rate of LNM was 14.9 % (960 out of 6423). Logistic regression models demonstrated that tumor size ³3cm (odds ratio, OR = 1.316, P = 0.038), poorly differentiated (OR = 3.716, P <0.001), older age (OR = 0.633 for age 65–79 years, OR= 0.477 for age over 80 years, both P < 0.001), and negative CEA level (OR = 0.71, P =0.007) were independent prognostic factors. Cox regression analysis demonstrated CSS was not significantly different between elderly patients undergoing radical resection with LNE³12 and those with LNE <12 (HR= 0.865, P = 0.153), which were firmly validated after propensity score-matched analysis by a competing risks model.Conclusions We found that tumor size<3cm, well/moderately differentiated, negative CEA level and adenocarcinoma in elderly patients with T1 colorectal cancer who were suitable for Local excision.

scholarly journals Prediction of Prognostic Biomarkers and Construction of an Autophagy Prognostic Model for Colorectal Cancer Using Bioinformatics

2020 ◽  
Vol 19 ◽  
pp. 153303382098417
Author(s):  
Ting-ting Liu ◽  
Shu-min Liu
Keyword(s):  
Colorectal Cancer ◽  
Regression Analysis ◽  
Prognostic Model ◽  
Cox Regression ◽  
Small Gtpase ◽  
Functional Enrichment ◽  
Clinical Correlation ◽  
Cox Regression Analysis ◽  
Prognostic Analysis ◽  
Key Genes

Objective: The incidence of colorectal cancer is increasing every year, and autophagy may be related closely to the pathogenesis of colorectal cancer. Autophagy is a natural catabolic mechanism that allows the degradation of cellular components in eukaryotic cells. However, autophagy plays a dual role in tumorigenesis. It not only promotes normal cell survival and tumor growth but also induces cell death and suppresses tumors survival. In addition, the pathogenesis of various conditions, including inflammation, neurodegenerative diseases, or tumors, is associated with abnormal autophagy. The present work aimed to examine the significance of autophagy-related genes (ARGs) in prognosis prediction, to construct an autophagy prognostic model, and to identify independent prognostic factors for colorectal cancer (CRC). Methods: This study discovered a total of 36 ARGs in CRC cases using The Cancer Genome Atlas (TCGA) and Human Autophagy-dedicated (HADd) databases along with functional enrichment analysis. Then, an autophagy prognostic model was constructed using univariate Cox regression analysis, and the key prognostic genes were screened. Finally, independent prognostic markers were determined through independent prognostic analysis and clinical correlation analysis of key genes. Results: Of the 36 differentially expressed ARGs, 13 were related to prognosis, as determined by univariate Cox regression analysis. A total of 6 key genes were obtained by a multivariate Cox regression analysis. Independent prognostic values were shown by 3 genes, namely, microtubule-associated protein 1 light chain 3 (MAP1LC3C), small GTPase superfamily and Rab family (RAB7A), and WD-repeat domain phosphoinositide-interacting protein 2 (WIPI2) by independent prognostic analysis and clinical correlation. Conclusions: In this study, molecular bioinformatics technology was employed to determine and construct a prognostic model of autophagy for colon cancer patients, which revealed 3 autophagy-related features, namely, MAP1LC3C, WIPI2, and RAB7A.

Factors Predictive of Distant Metastases in Patients With Breast Cancer Who Have a Pathologic Complete Response After Neoadjuvant Chemotherapy

2005 ◽  
Vol 23 (28) ◽  
pp. 7098-7104 ◽  
Author(s):  
Ana M. Gonzalez-Angulo ◽  
Sean E. McGuire ◽  
Thomas A. Buchholz ◽  
Susan L. Tucker ◽  
Henry M. Kuerer ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Regression Analysis ◽  
Neoadjuvant Chemotherapy ◽  
Distant Metastasis ◽  
Cox Regression ◽  
Clinical Stage ◽  
Pathologic Complete Response ◽  
Distant Metastases ◽  
Complete Response ◽  
Cox Regression Analysis

Purpose To identify clinicopathological factors predictive of distant metastasis in patients who had a pathologic complete response (pCR) after neoadjuvant chemotherapy (NC). Methods Retrospective review of 226 patients at our institution identified as having a pCR was performed. Clinical stage at diagnosis was I (2%), II (36%), IIIA (27%), IIIB (23%), and IIIC (12%). Eleven percent of all patients were inflammatory breast cancers (IBC). Ninety-five percent received anthracycline-based chemotherapy; 42% also received taxane-based therapy. The relationship of distant metastasis with clinicopathologic factors was evaluated, and Cox regression analysis was performed to identify independent predictors of development of distant metastasis. Results Median follow-up was 63 months. There were 31 distant metastases. Ten-year distant metastasis-free rate was 82%. Multivariate Cox regression analysis using combined stage revealed that clinical stages IIIB, IIIC, and IBC (hazard ratio [HR], 4.24; 95% CI, 1.96 to 9.18; P < .0001), identification of ≤ 10 lymph nodes (HR, 2.94; 95% CI, 1.40 to 6.15; P = .004), and premenopausal status (HR, 3.08; 95% CI, 1.25 to 7.59; P = .015) predicted for distant metastasis. Freedom from distant metastasis at 10 years was 97% for no factors, 88% for one factor, 77% for two factors, and 31% for three factors (P < .0001). Conclusion A small percentage of breast cancer patients with pCR experience recurrence. We identified factors that independently predicted for distant metastasis development. Our data suggest that premenopausal patients with advanced local disease and suboptimal axillary node evaluation may be candidates for clinical trials to determine whether more aggressive or investigational adjuvant therapy will be of benefit.

scholarly journals Serum exosomal miR-4787-3p as potential lymph node metastasis and prognostic marker in esophageal squamous cell carcinoma.

2021 ◽  
Author(s):  
Shuang Liu ◽  
Zheng Lin ◽  
Jianwen Wang ◽  
Zerong Zheng ◽  
Wenqing Rao ◽  
...  
Keyword(s):  
Regression Analysis ◽  
Lymph Node ◽  
Lymph Node Metastasis ◽  
Cox Regression ◽  
High Serum ◽  
Migration And Invasion ◽  
Cox Regression Analysis ◽  
Mirna Array ◽  
Node Metastasis

Abstract Background: To explore the miR-4787-3p expression levels in the serum exosome and tissue and its role in lymph node metastasis and prognosis in ESCC. Methods: The miRNA array was conducted to detect the ESCC serum exosomal miRNAs expression. A receiver operating characteristic (ROC) curve was constructed to determine the predictive ESCC with lymph node metastasis efficacy of serum exosomal miR-4784-3p. The Cox regression analysis was preformed to explore prognostic factors for ESCC. Transwell assay and CCK-8 assays were utilized to evaluate cell migration, invasion, and proliferation, respectively. Results: High serum exosomal miR-4787-3p expression was demonstrated in lymph node metastasis group (P =0.011). The serum exosomal miR-4787-3p expression was significantly associated with histologic grade (P = 0.010), and TNM stage (P = 0.033). However, there was no significant relationship between tissue miR-4787-3p expression and clinical characteristics (P >0.05). ROC analyses revealed that the AUCs of serum exosomal miR-4787-3p for lymph node metastasis prediction was 0.787. The Cox regression analysis found that high expression serum exosomal miR-4787-3p were correlated with poor prognoses (for OS, HR=2.68, 95% CI: 1.02~7.04; for DFS, HR = 2.65, 95% CI: 1.05~6.68). Nevertheless, no association between tissue miR-4787-3p expression and ESCC prognosis. In addition, upregulated expression of miR-4787-3p could promote migration and invasion in vitro. Conclusions: Serum exosomal miR-4787-3p can be promising biomarkers for ESCC metastasis and prognosis

scholarly journals KIF20A Predicts Poor Survival of Patients and Promotes Colorectal Cancer Tumor Progression through the JAK/STAT3 Signaling Pathway

2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Qi Zhang ◽  
Jun Di ◽  
Zhiyu Ji ◽  
Aoning Mi ◽  
Quanying Li ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Tumor Progression ◽  
Cox Regression ◽  
Critical Role ◽  
Depth Of Invasion ◽  
Cox Regression Analysis ◽  
Normal Tissues ◽  
Reduce Cell Proliferation ◽  
Cancer Tumor ◽  
And Migration

Kinesin family member 20A (KIF20A) has been recently reported to be upregulated and associated with increased invasiveness and metastasis in several malignancies. However, the role of KIF20A in colorectal cancer (CRC) is still unclear. This study is aimed at investigating the potential roles of KIF20A in the development of CRC. The results of bioinformatics analysis, immunohistochemical staining, and Western blot analysis showed that KIF20A was overexpressed in CRC tissues compared with adjacent normal tissues. High expression of KIF20A in CRC tissues was associated with depth of invasion, lymphatic node metastasis, distant metastasis, and TNM stage. Moreover, the Kaplan-Meier survival analysis showed that CRC patients with high KIF20A expression had poor prognoses. Cox regression analysis revealed that KIF20A was an independent prognostic factor in patients with CRC. Further studies suggested that knockdown of KIF20A was able to reduce cell proliferation and migration by inhibiting the JAK/STAT3 pathway. Taken together, we propose that KIF20A plays a critical role in the tumorigenesis and tumor progression of colorectal cancer and could represent a potential therapeutic target for CRC.

Long Noncoding RNAZEB1-AS1 Expression Predicts Progression and Poor Prognosis of Colorectal Cancer

2017 ◽  
Vol 32 (4) ◽  
pp. 428-433 ◽  
Author(s):  
Jining Fu ◽  
Yongyuan Cui
Keyword(s):  
Colorectal Cancer ◽  
Poor Prognosis ◽  
Cox Regression ◽  
Area Under The Curve ◽  
Diagnostic Value ◽  
Depth Of Invasion ◽  
Cox Regression Analysis ◽  
Lower Survival Rate ◽  
Differentiation Degree ◽  
Diagnostic Sensitivity And Specificity

Background ZEB1-AS1 acts as an oncogene in hepatocellular carcinoma, accelerating tumor growth and promoting metastasis. However, its roles in colorectal cancer (CRC) remain unclear. Methods In this study, we determined the expression of ZEB1-AS1 in CRC tissues by quantitative real-time polymerase chain reaction (qRT-PCR). Additionally, we investigated the relationship between various clinicopathological features of CRC patients and ZEB1-AS1 expression, and evaluated the diagnostic and prognostic value of ZEB1-AS1 in CRC. Results We found that ZEB1-AS1 expression was significantly higher in CRC tissues than in adjacent normal colorectal tissues. Moreover, its expression was significantly correlated with tumor size, differentiation degree, TNM grade, metastasis, depth of invasion and Dukes' classification, but not with sex, age, location and organization. In addition, at the optimal cutoff value of 2.340, the values of diagnostic sensitivity and specificity amounted to 63.0% and 90.7%, respectively, with an area under the curve (AUC) of 0.846 (95% CI, 0.797-0.895). Finally, CRC patients of the high ZEB1-AS1 expression group had a poorer prognosis and a significantly lower survival rate than those of the low expression group, and Cox regression analysis indicated that ZEB1-AS1 expression and metastasis were independent predictors of poor prognosis. Conclusions Our data suggest that ZEB1-AS1 has no obvious early diagnostic value, but it may be utilized as a new prognostic biomarker for CRC.

scholarly journals Influence of Old Age on Risk of Lymph Node Metastasis and Survival in Patients With T1 Colorectal Cancer: A Population-Based Analysis

2021 ◽  
Vol 11 ◽  
Author(s):  
Hua Ye ◽  
Bin Zheng ◽  
Qi Zheng ◽  
Ping Chen
Keyword(s):  
Colorectal Cancer ◽  
Regression Analysis ◽  
Lymph Node ◽  
Elderly Patients ◽  
Old Age ◽  
Tumor Size ◽  
Cox Regression ◽  
Cox Regression Analysis ◽  
T1 Colorectal Cancer ◽  
Well Differentiated

BackgroundWe aimed at determining the influence of old age on lymph node metastasis (LNM) and prognosis in T1 colorectal cancer (CRC).MethodsWe collected data from eligible patients in Surveillance, Epidemiology, and End Results database between 2004 and 2015. Independent predictors of LNM were identified by logistic regression analysis. Cox regression analysis, propensity score-matched analysis, and competing risks analysis were used to analyze the associations between old age and lymph node (LN) status and to validate the prognostic value of old age on cancer-specific survival (CSS).ResultsIn total, 10,092 patients were identified. Among them, 6,423 patients (63.6%) had greater than or equal to 12 examined lymph nodes (LNE ≥12), and 5,777 patients (57.7%) were 65 years or older. The observed rate of LNM was 4.6% (15 out of 325) in T1 CRC elderly patients, with tumor size &lt;3 cm, well differentiated, with negative carcinoembryonic antigen (CEA) level, and adenocarcinoma. Logistic regression models demonstrated that tumor size ≥3 cm (odds ratio, OR = 1.316, P = 0.038), poorly differentiated (OR = 3.716, P &lt; 0.001), older age (OR = 0.633 for ages 65–79 years, OR = 0.477 for age over 80 years, both P &lt;0.001), and negative CEA level (OR = 0.71, P = 0.007) were independent prognostic factors. Cox regression analysis demonstrated that CSS was not significantly different between elderly patients undergoing radical resection with LNE ≥12 and those with LNE &lt;12 (hazard ratio = 0.865, P = 0.153), which was firmly validated after a propensity score-matched analysis by a competing risks model.ConclusionsThe predictive value of tumor size, grading, primary site, histology, CEA level, and age for LNM should be considered in medical decision making about local resection. We found that tumor size was &lt;3 cm, well differentiated, negative CEA level, and adenocarcinoma in elderly patients with T1 colorectal cancer which was suitable for local excision.

scholarly journals High Expression of PABPC1 Predicts Worse Survival of Gastric Cancer Patients

2020 ◽  
Author(s):  
Tailai An ◽  
Lingna Deng ◽  
Zheng Yang ◽  
Cuicui Chai ◽  
Yan Wang ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Regression Analysis ◽  
Molecular Mechanisms ◽  
Bioinformatics Analysis ◽  
Cox Regression ◽  
Disease Free Survival ◽  
Mrna Translation ◽  
High Expression ◽  
Depth Of Invasion ◽  
Cox Regression Analysis

Abstract Background: Gastric cancer (GC) is one of the most common cancers with one of the highest mortality rates. Unfortunately, underlying molecular mechanisms contributing to GC have not been fully illuminated. PABPC1 is involved in a series of processes, such as mRNA translation, and mRNA deadenylation and decay. We performed this study to clarify the role of PABPC1 in GC. Methods: To evaluate PABPC1 expressions in GC and normal tissues, we performed bioinformatics analysis of data from TCGA. PABPC1 expressions were evaluated by immunohistochemical (IHC) staining of 170 GC specimens. Associations between PABPC1 expression and clinicopathological variables were analyzed. Independent predictive factors for survival of GC patients were determined by Cox regression analysis. Results: It was revealed by bioinformatics analysis that compared with normal gastric tissues, PABPC1 expressions in GC tissues were significantly higher (P=0.002, paired) (P=3.605e^-9, unpaired). It was revealed that PABPC1 expression was significantly associated with tumor size (P=0.008), Borrmann classification (P=0.003), vessel invasion (P=0.017), depth of invasion (P=0.032), lymph node metastasis (P=0.001), and TNM stage (P=0.019). It was demonstrated through Cox regression analysis that PABPC1 expression was a predictive factor for both overall survival (OS) (P<0.001) and disease-free survival (DFS) (P<0.001) of GC patients. Conclusions: Compared with that of normal gastric tissue, expression level of PABPC1 in GC tissue was significantly higher and PABPC1,s high expression was significantly associated with poorer survival, suggesting its potential as a therapeutic biomarker for GC.

scholarly journals Prognostic Nomogram for Postoperative Patients With Gastroesophageal Junction Cancer of No Distant Metastasis

2021 ◽  
Vol 11 ◽  
Author(s):  
Qiang Guo ◽  
YuanYuan Peng ◽  
Heng Yang ◽  
JiaLong Guo
Keyword(s):  
Regression Analysis ◽  
Surgical Resection ◽  
Distant Metastasis ◽  
Calibration Curve ◽  
Cox Regression ◽  
Validation Cohort ◽  
Predictive Accuracy ◽  
Gastroesophageal Junction ◽  
Training Cohort ◽  
Cox Regression Analysis

BackgroundGastroesophageal junction (GEJ) was one of the most common malignant tumors. However, the value of clinicopathological features in predicting the prognosis of postoperative patients with GEJ cancer and without distant metastasis was still unclear.MethodsThe 3425 GEJ patients diagnosed and underwent surgical resection without distant metastasis in the Surveillance, Epidemiology and End Results (SEER) database from 2010 to 2015 were enrolled,and they were randomly divided into training and validation cohorts with 7:3 ratio. Univariate and multivariate Cox regression analysis were used to determine the predictive factors that constituted the nomogram. The predictive accuracy and discriminability of Nomogram were determined by the area under the curve (AUC), C index, and calibration curve, and the influence of various factors on prognosis was explored.Results2,400 patients were designed as training cohort and 1025 patients were designed as validation cohort. The percentages of the distribution of demographic and clinicopathological characteristics in the training and validation cohorts tended to be the same. In the training cohort, multivariate Cox regression analysis revealed that the age, tumor grade, T stage and N stage were independent prognostic risk factors for patients with GEJ cancer without distant metastasis. The C index of nomogram model was 0.667. The AUC of the receiver operating characteristic (ROC) analysis for 3- and 5-year overall survival (OS) were 0.704 and 0.71, respectively. The calibration curve of 3- and 5-year OS after operation showed that there was the best consistency between nomogram prediction and actual observation. In the validation cohort, the C index of nomogram model, the AUC of 3- and 5-year OS, and the calibration curve were similar to the training cohort.ConclusionsNomogram could evaluate the prognosis of patients with GEJ cancer who underwent surgical resection without distant metastasis.

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