Adjuvant treatment for resected rectal cancer: Effect of postoperative oxaliplatin added to 5-FU in the neoadjuvant era.

2015 ◽  
Vol 33 (3_suppl) ◽  
pp. 672-672
Author(s):  
Benjamin Garlipp ◽  
Patrick Stuebs ◽  
Hans Lippert ◽  
Karsten Ridwelski ◽  
Henry Ptok ◽  
...  
Keyword(s):  
Rectal Cancer ◽  
Colon Cancer ◽  
Regression Analysis ◽  
Cancer Patients ◽  
Adjuvant Treatment ◽  
Cox Regression ◽  
Disease Free Survival ◽  
Data Set ◽  
Cox Regression Analysis ◽  
The Impact

672 Background: Oxaliplatin (Ox) added to postoperative 5-fluorouracil (5FU) based adjuvant treatment has shown a survival benefit in colon cancer. For rectal cancer, the impact of Ox on survival has almost exclusively been tested in studies using 5FU +/- Ox both as a component of preoperative chemoradiotherapy (CRT) and as adjuvant treatment. Only one study (NCT00807911) investigated adjuvant 5FU +/- Ox in patients undergoing preop 5FU based CRT without Ox. Thus, the evidence for the benefit of adding Ox to adjuvant 5FU in patients treated with preop 5FU based CRT is limited. Methods: Data from the prospective German multicenter Quality Assurance in Rectal Cancer observational trial involving more than 300 hospitals of all levels of care throughout Germany were retrospectively analyzed. Patients undergoing R0 total mesorectal excision (TME) for rectal cancer following neoadjuvant 5FU based treatment without oxaliplatin between 01/01/2008 and 12/31/2010 were included. Disease-free survival (DFS) in patients receiving adjuvant treatment with or without Ox was compared using the Kaplan Meier method. The impact of adjuvant treatment with 5FU with or without Ox on DFS was investigated in a Cox regression analysis including open vs. laparoscopic approach, pT stage, pN stage, tumor grading, TME quality grade, and presence of anastomotic leakage as potential confounding factors. Results: The entire data set included 1,861 patients. Data for all variables investigated were available for 599 patients of whom 512 (85%) and 89 (15%) received 5FU based adjuvant treatment without and with Ox, respectively. Mean DFS was not different in patients receiving 5FU only vs. 5FU with Ox (p=0.103). Cox regression analysis revealed no significant impact of adding Ox to adjuvant 5FU on DFS. Of all factors analyzed, only pN2 (vs. pN0) status had an independent adverse effect on DFS (Hazard ratio 4.22, p<0.001). Conclusions: These data indicate that adjuvant Ox added to 5FU does not provide a DFS benefit in rectal cancer patients treated with preoperative 5FU based CRT under routine care conditions. Rectal cancer patients may be different from patients with colon cancer with respect to benefit from adjuvant Ox.

scholarly journals Development of prognosis model for colon cancer based on autophagy-related genes

2020 ◽  
Vol 18 (1) ◽  
Author(s):  
Xu Wang ◽  
Yuanmin Xu ◽  
Ting Li ◽  
Bo Chen ◽  
Wenqi Yang
Keyword(s):  
Colon Cancer ◽  
Regression Analysis ◽  
High Risk ◽  
Cancer Patients ◽  
Risk Score ◽  
Cox Regression ◽  
Patient Survival ◽  
Expression Profiles ◽  
Cox Regression Analysis ◽  
Risk Patients

Abstract Background Autophagy is an orderly catabolic process for degrading and removing unnecessary or dysfunctional cellular components such as proteins and organelles. Although autophagy is known to play an important role in various types of cancer, the effects of autophagy-related genes (ARGs) on colon cancer have not been well studied. Methods Expression profiles from ARGs in 457 colon cancer patients were retrieved from the TCGA database (https://portal.gdc.cancer.gov). Differentially expressed ARGs and ARGs related to overall patient survival were identified. Cox proportional-hazard models were used to investigate the association between ARG expression profiles and patient prognosis. Results Twenty ARGs were significantly associated with the overall survival of colon cancer patients. Five of these ARGs had a mutation rate ≥ 3%. Patients were divided into high-risk and low-risk groups based on Cox regression analysis of 8 ARGs. Low-risk patients had a significantly longer survival time than high-risk patients (p < 0.001). Univariate and multivariate Cox regression analysis showed that the resulting risk score, which was associated with infiltration depth and metastasis, could be an independent predictor of patient survival. A nomogram was established to predict 1-, 3-, and 5-year survival of colon cancer patients based on 5 independent prognosis factors, including the risk score. The prognostic nomogram with online webserver was more effective and convenient to provide information for researchers and clinicians. Conclusion The 8 ARGs can be used to predict the prognosis of patients and provide information for their individualized treatment.

scholarly journals Development of prognosis model for colon cancer based on autophagy-related genes

2020 ◽  
Author(s):  
Xu Wang ◽  
Yuanmin Xu ◽  
Ting Li ◽  
Bo Chen ◽  
Wenqi Yang
Keyword(s):  
Colon Cancer ◽  
Regression Analysis ◽  
High Risk ◽  
Cancer Patients ◽  
Risk Score ◽  
Cox Regression ◽  
Patient Survival ◽  
Expression Profiles ◽  
Cox Regression Analysis ◽  
Risk Patients

Abstract Background: Autophagy is an orderly catabolic process for degrading and removing unnecessary or dysfunctional cellular components such as proteins and organelles. Although autophagy is known to play an important role in various types of cancer, the effects of autophagy-related genes (ARGs) on colon cancer have not been well studied.Methods: Expression profiles from ARGs in 457 colon cancer patients were retrieved from the TCGA database (https://portal.gdc.cancer.gov). Differentially expressed ARGs and ARGs related to overall patient survival were identified. Cox proportional-hazards models were used to investigate the association between ARG expression profiles and patient prognosis.Results: 20 ARGs were significantly associated with overall survival of colon cancer patients. Five of these ARGs had a mutation rate ≥3%. Patients were divided into high-risk and low-risk groups based on Cox regression analysis of 8 ARGs. Low-risk patients had a significantly longer survival time than high-risk patients (p<0.001). Univariate and multivariate Cox regression analysis showed that the resulting risk score, which was associated with infiltration depth and metastasis, could be an independent predictor of patient survival. A nomogram was established to predict 3- and 5-year survival of colon cancer patients based on 5 independent prognosis factors, including the risk score. The prognostic nomogram with online webserver was more effective and convenient to provide information for researchers and clinicians.Conclusion: The 8 ARGs can be used to predict the prognosis of patients and provide information for their individualized treatment.

Serum Tissue Inhibitor of Metalloproteinase 1 and 2 (TIMP-1 and TIMP-2) Levels in Colorectal Cancer Patients: Associations with Clinicopathological Variables and Patient Survival

2009 ◽  
Vol 24 (4) ◽  
pp. 245-252 ◽  
Author(s):  
Constantinos Giaginis ◽  
Nikolaos Nikiteas ◽  
Alexandra Margeli ◽  
Nikolaos Tzanakis ◽  
Georgios Rallis ◽  
...  
Keyword(s):  
Colon Cancer ◽  
Regression Analysis ◽  
Cancer Patients ◽  
Cancer Biology ◽  
Cox Regression ◽  
Elevated Serum ◽  
Disease Stage ◽  
Tissue Inhibitors Of Metalloproteinases ◽  
Enzyme Linked Immunosorbent Assay ◽  
Cox Regression Analysis

Tissue inhibitors of metalloproteinases (TIMPs) appear to affect many aspects of cancer biology, playing a crucial role in cell signaling by regulating cell growth, apoptosis, invasion, metastasis, angiogenesis, and genomic instability. The aim of the present study was to elucidate the diagnostic and prognostic utility of TIMP-1 and TIMP-2 in patients with colon cancer. Serum TIMP-1 and TIMP-2 concentrations were quantified using an enzyme-linked immunosorbent assay in 97 colon cancer patients. Elevated serum TIMP-1 levels were found in patients with advanced disease stage (p=0.0512) and poorly differentiated histopathological tumor grade (p=0.0059). Patients with increased TIMP-1 levels had shorter overall survival times (log-rank test, p=0.0143). Multivariate analysis also identified TIMP-1 as an independent prognostic factor (Cox regression analysis, p=0.0149). Serum TIMP-2 levels were not significantly associated with disease stage, histopathological grade or survival. In the subgroup of patients with well and moderately differentiated tumors, TIMP-1 and TIMP-2 were identified as independent prognostic factors (Cox regression analysis, p=0.0379 and p=0.0451, respectively). In conclusion, assessment of serum TIMP-1 can be considered a useful biomarker in colon cancer, whereas TIMP-2 appears to be of limited value.

scholarly journals Development of prognosis model for colon cancer based on autophagy-related genes

2020 ◽  
Author(s):  
Xu Wang ◽  
Yuanmin Xu ◽  
Ting Li ◽  
Bo Chen ◽  
Wenqi Yang
Keyword(s):  
Colon Cancer ◽  
Regression Analysis ◽  
High Risk ◽  
Cancer Patients ◽  
Risk Score ◽  
Cox Regression ◽  
Patient Survival ◽  
Expression Profiles ◽  
Cox Regression Analysis ◽  
Risk Patients

Abstract Background: Autophagy is an orderly catabolic process for degrading and removing unnecessary or dysfunctional cellular components such as proteins and organelles. Although autophagy is known to play an important role in various types of cancer, the effects of autophagy-related genes (ARGs) on colon cancer have not been well studied.Methods: Expression profiles from ARGs in 457 colon cancer patients were retrieved from the TCGA database (https://portal.gdc.cancer.gov). Differentially expressed ARGs and ARGs related to overall patient survival were identified. Cox proportional-hazards models were used to investigate the association between ARG expression profiles and patient prognosis.Results: 20 ARGs were significantly associated with overall survival of colon cancer patients. Five of these ARGs had a mutation rate ≥ 3%. Patients were divided into high-risk and low-risk groups based on Cox regression analysis of 8 ARGs. Low-risk patients had a significantly longer survival time than high-risk patients (p < 0.001). Univariate and multivariate Cox regression analysis showed that the resulting risk score, which was associated with infiltration depth and metastasis, could be an independent predictor of patient survival. A nomogram was established to predict 1-, 3- and 5-year survival of colon cancer patients based on 5 independent prognosis factors, including the risk score. The prognostic nomogram with online webserver was more effective and convenient to provide information for researchers and clinicians.Conclusion: The 8 ARGs can be used to predict the prognosis of patients and provide information for their individualized treatment.

scholarly journals Development of prognosis model for colon cancer based on autophagy-related genes

2020 ◽  
Author(s):  
Xu Wang ◽  
Yuanmin Xu ◽  
Ting Li ◽  
Bo Chen ◽  
Wenqi Yang
Keyword(s):  
Colon Cancer ◽  
Regression Analysis ◽  
High Risk ◽  
Cancer Patients ◽  
Risk Score ◽  
Cox Regression ◽  
Patient Survival ◽  
Expression Profiles ◽  
Cox Regression Analysis ◽  
Risk Patients

Abstract Background: Autophagy is an orderly catabolic process for degrading and removing unnecessary or dysfunctional cellular components such as proteins and organelles. Although autophagy is known to play an important role in various types of cancer, the effects of autophagy-related genes (ARGs) on colon cancer have not been well studied.Methods: Expression profiles from ARGs in 457 colon cancer patients were retrieved from the TCGA database (https://portal.gdc.cancer.gov). Differentially expressed ARGs and AGRs related to overall patient survival were identified. Cox proportional-hazards models were used to investigate the association between ARG expression profiles and patient prognosis.Results: 20 ARGs were significantly associated with overall survival of colon cancer patients. Five of these ARGs had a mutation rate ≥3%. Patients were divided into high-risk and low-risk groups based on Cox regression analysis of 8 ARGs. Low-risk patients had a significantly longer survival time than high-risk patients (p<0.001). Univariate and multivariate Cox regression analysis showed that the resulting risk score, which was associated with infiltration depth and metastasis, could be an independent predictor of patient survival. A nomogram was established to predict 3- and 5-year survival of colon cancer patients based on 5 independent prognosis factors, including the risk score. The prognostic nomogram with online webserver was more effective and convenient to provide information for researchers and clinicians.Conclusion: The 8 ARGs can be used to predict the prognosis of patients and provide information for their individualized treatment.

scholarly journals Alternative splicing acts as an independent prognosticator in ovarian carcinoma

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Yan Ouyang ◽  
Kaide Xia ◽  
Xue Yang ◽  
Shichao Zhang ◽  
Li Wang ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
Regression Analysis ◽  
Alternative Splicing ◽  
Ovarian Carcinoma ◽  
Cancer Patients ◽  
Cox Regression ◽  
Excision Repair ◽  
Splicing Factors ◽  
Prognostic Signature ◽  
Cox Regression Analysis

AbstractAlternative splicing (AS) events associated with oncogenic processes present anomalous perturbations in many cancers, including ovarian carcinoma. There are no reliable features to predict survival outcomes for ovarian cancer patients. In this study, comprehensive profiling of AS events was conducted by integrating AS data and clinical information of ovarian serous cystadenocarcinoma (OV). Survival-related AS events were identified by Univariate Cox regression analysis. Then, least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression analysis were used to construct the prognostic signatures within each AS type. Furthermore, we established a splicing-related network to reveal the potential regulatory mechanisms between splicing factors and candidate AS events. A total of 730 AS events were identified as survival-associated splicing events, and the final prognostic signature based on all seven types of AS events could serve as an independent prognostic indicator and had powerful efficiency in distinguishing patient outcomes. In addition, survival-related AS events might be involved in tumor-related pathways including base excision repair and pyrimidine metabolism pathways, and some splicing factors might be correlated with prognosis-related AS events, including SPEN, SF3B5, RNPC3, LUC7L3, SRSF11 and PRPF38B. Our study constructs an independent prognostic signature for predicting ovarian cancer patients’ survival outcome and contributes to elucidating the underlying mechanism of AS in tumor development.

NLRP3 is a Novel Prognostic Biomarker and Correlates With Immune Infiltrates in Lung Adenocarcinoma and Skin Cutaneous Melanoma

2021 ◽  
Author(s):  
Chenxi Yuan ◽  
Qingwei Wang ◽  
Xueting Dai ◽  
Yipeng Song ◽  
Jinming Yu
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Lung Adenocarcinoma ◽  
Immune Cells ◽  
Cutaneous Melanoma ◽  
Cox Regression ◽  
Cox Regression Analysis ◽  
Potential Biomarker ◽  
The Impact ◽  
Nlrp3 Expression

Abstract Background: Lung adenocarcinoma (LUAD) and skin cutaneous melanoma (SKCM) are common tumors around the world. However, the prognosis in advanced patients is poor. Because NLRP3 was not extensively studied in cancers, so that we aimed to identify the impact of NLRP3 on LUAD and SKCM through bioinformatics analyses. Methods: TCGA and TIMER database were utilized in this study. We compared the expression of NLRP3 in different cancers and evaluated its influence on survival of LUAD and SKCM patients. The correlations between clinical information and NLRP3 expression were analyzed using logistic regression. Clinicopathologic characteristics associated with overall survival in were analyzed by Cox regression. In addition, we explored the correlation between NLRP3 and immune infiltrates. GSEA and co-expressed gene with NLRP3 were also done in this study. Results: NLRP3 expressed disparately in tumor tissues and normal tissues. Cox regression analysis indicated that up-regulated NLRP3 was an independent prognostic factor for good prognosis in LUAD and SKCM. Logistic regression analysis showed increased NLRP3 expression was significantly correlated with favorable clinicopathologic parameters such as no lymph node invasion and no distant metastasis. Specifically, a positive correlation between increased NLRP3 expression and immune infiltrating level of various immune cells was observed. Conclusion: Together with all these findings, increased NLRP3 expression correlates with favorable prognosis and increased proportion of immune cells in LUAD and SKCM. These conclusions indicate that NLRP3 can serve as a potential biomarker for evaluating prognosis and immune infiltration level.

Homologous recombination deficiency associated with response to poly (ADP-ribose) polymerase inhibitors in ovarian cancer patients: The first real-word data from China.

2021 ◽  
Vol 39 (15_suppl) ◽  
pp. e17543-e17543
Author(s):  
Xiaoxiang Chen ◽  
Jing Ni ◽  
Xia Xu ◽  
Wenwen Guo ◽  
Xianzhong Cheng ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
Regression Analysis ◽  
Homologous Recombination ◽  
Cancer Patients ◽  
Real World ◽  
Cox Regression ◽  
Wild Type ◽  
Cox Regression Analysis ◽  
Homologous Recombination Deficiency ◽  
Polymerase Inhibitors

e17543 Background: Homologous recombination deficiency (HRD) is the first phenotypically defined predictive biomarker for Poly (ADP-ribose) polymerase inhibitors (PARPi) in ovarian cancer. However, the proportion of HRD positive in real world and the relationship of HRD status with PARPi in Chinese ovarian cancer patients remains unknown. Methods: A total of sixty-four ovarian cancer patients underwent PARPi, both Olaparib and Niraparib, were enrolled from August 2018 to January 2021 in Jiangsu Institute of Cancer Hospital. HRD score which was the sum of loss of heterozygosity (LOH), telomeric allelic imbalance (TAI) and large-scale state transitions (LST) events were calculated using tumor DNA-based next generation sequencing (NGS) assays. HRD-positive was defined by either BRCA1/2 pathogenic or likely pathogenic mutation or HRD score ≥42. Progression-free survival (PFS) was analyzed with a log-rank test using HRD status and summarized using Kaplan-Meier methodology. Univariate and multiple cox-regression analysis were conducted to investigate all possible clinical factors. Results: 71.9% (46/64) patients were HRD positive and the rest 28.1% (18/64) were HRD negative, which was higher than the HRD positive proportion reported in Western countries. The PFS among HRD positive patients was significantly longer than those HRD negative patients (medium PFS 8.9 m vs 3.6 m, hazard ratio [HR]: 0.22, p < 0.001). Among them, 23 patients who were BRCA wild type but HRD positive had longer PFS than those with BRCA wild type and HRD negative (medium PFS 9.2 m vs 3.6 m, HR: 0.20, p < 0.001). Univariate cox-regression analysis found that HRD status, previous treatment lines, secondary cytoreductive surgery (SCS) were significantly associated with PFS after PARPi treatment. After multiple regression correction, HRD status (HR: 0.39, 95% CI: [0.20-0.76], p = 0.006), ECOG score (HR: 2.53, 95% CI: [1.24-5.17], p = 0.011) and SCS (HR: 2.21, 95% CI: [1.09-4.48], p = 0.028) were the independent factors. Subgroup analysis in ECOG = 0 subgroup (N = 36), HRD positive patients had significant longer PFS than HRD negative patients (medium PFS 10.3 m vs 5.8 m, HR: 0.14, p < 0.001). Also in the subgroup of patients without SCS, PFS in patients with HRD was longer than patients without HRD (medium PFS 10.2 m vs 5.7 m, HR: 0.29, p = 0.003). Conclusions: This is the first real-world data of HRD status in ovarian cancer patients from China and demonstrate that HRD is a valid biomarker for PARP inhibitors in Chinese ovarian cancer patients.

Immune-related gene based prognostic signature for the risk stratification analysis of breast cancer

2021 ◽  
Vol 16 ◽  
Author(s):  
Dongqing Su ◽  
Qianzi Lu ◽  
Yi Pan ◽  
Yao Yu ◽  
Shiyuan Wang ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Regression Analysis ◽  
Cancer Patients ◽  
Risk Score ◽  
Cox Regression ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Breast Cancer Patients ◽  
Cox Regression Analysis ◽  
Score Model

Background: Breast cancer has plagued women for many years and caused many deaths around the world. Method: In this study, based on the weighted correlation network analysis, univariate Cox regression analysis and least absolute shrinkage and selection operator, 12 immune-related genes were selected to construct the risk score for breast cancer patients. The multivariable Cox regression analysis, gene set enrichment analysis and nomogram were also conducted in this study. Results: Good results were obtained in the survival analysis, enrichment analysis, multivariable Cox regression analysis and immune-related feature analysis. When the risk score model was applied in 22 breast cancer cohorts, the univariate Cox regression analysis demonstrated that the risk score model was significantly associated with overall survival in most of the breast cancer cohorts. Conclusion: Based on these results, we could conclude that the proposed risk score model may be a promising method, and may improve the treatment stratification of breast cancer patients in the future work.

scholarly journals Impact of Early C-Reactive Protein/Albumin Ratio on Intra-Hospital Mortality Among Patients with Spontaneous Intracerebral Hemorrhage

2020 ◽  
Vol 9 (4) ◽  
pp. 1236 ◽  
Author(s):  
Michael Bender ◽  
Kristin Haferkorn ◽  
Michaela Friedrich ◽  
Eberhard Uhl ◽  
Marco Stein
Keyword(s):  
Regression Analysis ◽  
Intracerebral Hemorrhage ◽  
Hospital Mortality ◽  
Cox Regression ◽  
Spontaneous Intracerebral Hemorrhage ◽  
C Reactive Protein ◽  
Albumin Ratio ◽  
Cox Regression Analysis ◽  
Reactive Protein ◽  
The Impact

Objective: The impact of increased C-reactive protein (CRP)/albumin ratio on intra-hospital mortality has been investigated among patients admitted to general intensive care units (ICU). However, it was not investigated among patients with spontaneous intracerebral hemorrhage (ICH). This study aimed to investigate the impact of CRP/albumin ratio on intra-hospital mortality in patients with ICH. Patients and Methods: This retrospective study was conducted on 379 ICH patients admitted between 02/2008 and 12/2017. Blood samples were drawn upon admission and the patients’ demographic, medical, and radiological data were collected. The identification of the independent prognostic factors for intra-hospital mortality was calculated using binary logistic regression and COX regression analysis. Results: Multivariate regression analysis shows that higher CRP/albumin ratio (odds ratio (OR) = 1.66, 95% confidence interval (CI) = 1.193–2.317, p = 0.003) upon admission is an independent predictor of intra-hospital mortality. Multivariate Cox regression analysis indicated that an increase of 1 in the CRP/albumin ratio was associated with a 15.3% increase in the risk of intra-hospital mortality (hazard ratio = 1.153, 95% CI = 1.005–1.322, p = 0.42). Furthermore, a CRP/albumin ratio cut-off value greater than 1.22 was associated with increased intra-hospital mortality (Youden’s Index = 0.19, sensitivity = 28.8, specificity = 89.9, p = 0.007). Conclusions: A CRP/albumin ratio greater than 1.22 upon admission was significantly associated with intra-hospital mortality in the ICH patients.

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