scholarly journals Transcription factor expression as a predictor of colon cancer prognosis: a machine learning practice

2020 ◽  
Vol 13 (S9) ◽  
Author(s):  
Jiannan Liu ◽  
Chuanpeng Dong ◽  
Guanglong Jiang ◽  
Xiaoyu Lu ◽  
Yunlong Liu ◽  
...  
Keyword(s):  
Colon Cancer ◽  
Transcription Factor ◽  
Transcription Factors ◽  
High Risk ◽  
Predictive Model ◽  
Risk Groups ◽  
Colon Cancer Patient ◽  
Cancer Prognosis ◽  
Kaplan Meier ◽  
The Difference

Abstract Background Colon cancer is one of the leading causes of cancer deaths in the USA and around the world. Molecular level characters, such as gene expression levels and mutations, may provide profound information for precision treatment apart from pathological indicators. Transcription factors function as critical regulators in all aspects of cell life, but transcription factors-based biomarkers for colon cancer prognosis were still rare and necessary. Methods We implemented an innovative process to select the transcription factors variables and evaluate the prognostic prediction power by combining the Cox PH model with the random forest algorithm. We picked five top-ranked transcription factors and built a prediction model by using Cox PH regression. Using Kaplan-Meier analysis, we validated our predictive model on four independent publicly available datasets (GSE39582, GSE17536, GSE37892, and GSE17537) from the GEO database, consisting of 925 colon cancer patients. Results A five-transcription-factors based predictive model for colon cancer prognosis has been developed by using TCGA colon cancer patient data. Five transcription factors identified for the predictive model is HOXC9, ZNF556, HEYL, HOXC4 and HOXC6. The prediction power of the model is validated with four GEO datasets consisting of 1584 patient samples. Kaplan-Meier curve and log-rank tests were conducted on both training and validation datasets, the difference of overall survival time between predicted low and high-risk groups can be clearly observed. Gene set enrichment analysis was performed to further investigate the difference between low and high-risk groups in the gene pathway level. The biological meaning was interpreted. Overall, our results prove our prediction model has a strong prediction power on colon cancer prognosis. Conclusions Transcription factors can be used to construct colon cancer prognostic signatures with strong prediction power. The variable selection process used in this study has the potential to be implemented in the prognostic signature discovery of other cancer types. Our five TF-based predictive model would help with understanding the hidden relationship between colon cancer patient survival and transcription factor activities. It will also provide more insights into the precision treatment of colon cancer patients from a genomic information perspective.

scholarly journals Establishment of an immune-related gene pairs model to predict colon adenocarcinoma prognosis

2020 ◽  
Author(s):  
Jihang Luo ◽  
Puyu Liu ◽  
Leibo Wang ◽  
Yi Huang ◽  
Yuanyan Wang ◽  
...  
Keyword(s):  
Colon Cancer ◽  
High Risk ◽  
Risk Group ◽  
Colon Adenocarcinoma ◽  
Risk Groups ◽  
High Risk Group ◽  
Related Gene ◽  
Immune Genes ◽  
Gene Pairs ◽  
Immune Related Gene

Abstract Background Colon cancer is the most common type of gastrointestinal cancer and has high morbidity and mortality. Colon adenocarcinoma(COAD) is the main pathological type of colon cancer. There is a lot of evidence describing the correlation between the prognosis of COAD and the immune system. The objective of the current study was the development of a robust prognostic immune-related gene pairs (IRGPs) model for estimating overall survival of COAD. Methods The gene expression profiles and clinical information of patients with colon adenocarcinoma come from TCGA and GEO databases and are divided into training and validation cohorts. Immune genes were selected which show significantly association with prognosis. Results Among 1647 immune genes, a 17 IRGPs model was built which was significantly associated with OS in the training cohort. In the training and validation data set, the IRGPs model divided patients into high-risk groups and low-risk groups, and the prognosis of the high-risk group was significantly worse( P <0.001). Univariate and multivariate Cox proportional hazard analysis confirmed the feasibility of this model. Functional analysis confirmed that multiple tumor progression and stem cell growth-related pathways in high-risk groups were up-regulated. T cells regulatory and Macrophage M0 were significantly highly expressed in the high-risk group. Conclusion We successfully constructed an IRGPs model that can predict the prognosis of COAD, which provides new insights into the treatment strategy of COAD.

scholarly journals An immune-related lncRNA signature as a prognostic immunotherapy target for colon cancer

2020 ◽  
Author(s):  
Bin Wu ◽  
Yi Yao ◽  
Yi Dong ◽  
Si Qi Yang ◽  
Deng Jing Zhou ◽  
...  
Keyword(s):  
Colon Cancer ◽  
High Risk ◽  
Risk Score ◽  
Enrichment Analysis ◽  
Risk Groups ◽  
Low Risk ◽  
Gene Set Enrichment Analysis ◽  
Risk Scores ◽  
Gene Set Enrichment ◽  
Immunotherapy Target

Abstract Background：We aimed to investigate an immune-related long non-coding RNA (lncRNA) signature that may be exploited as a potential immunotherapy target in colon cancer. Materials and methods: Colon cancer samples from The Cancer Genome Atlas (TCGA) containing available clinical information and complete genomic mRNA expression data were used in our study. We then constructed immune-related lncRNA co-expression networks to identify the most promising immune-related lncRNAs. According to the risk score developed from screened immune-related lncRNAs, the high-risk and low-risk groups were separated on the basis of the median risk score, which served as the cutoff value. An overall survival analysis was then performed to confirm that the risk score developed from screened immune-related lncRNAs could predict colon cancer prognosis. The prediction reliability was further evaluated in the independent prognostic analysis and receiver operating characteristic curve (ROC). A principal component analysis (PCA) and gene set enrichment analysis (GSEA) were performed for functional annotation. Results: Information for a total of 514 patients was included in our study. After multiplex analysis, 12 immune-related lncRNAs were confirmed as a signature to evaluate the risk scores for each patient with cancer. Patients in the low-risk group exhibited a longer overall survival (OS) than those in the high-risk group. Additionally, the risk scores were an independent factor, and the Area Under Curve (AUC) of ROC for accuracy prediction was 0.726. Moreover, the low-risk and high-risk groups displayed different immune statuses based on principal components and gene set enrichment analysis.Conclusions: Our study suggested that the signature consisting of 12 immune-related lncRNAs can provide an accessible approach to measuring the prognosis of colon cancer and may serve as a valuable antitumor immunotherapy.

Revalidation of the Flipi Score in the Era of Immunotherapy.

Blood ◽  
2007 ◽  
Vol 110 (11) ◽  
pp. 4437-4437
Author(s):  
German Stemmelin ◽  
Carlos Doti ◽  
Claudia Shanley ◽  
Jose Ceresetto ◽  
Oscar Rabinovich ◽  
...  
Keyword(s):  
Bone Marrow ◽  
High Risk ◽  
Univariate Analysis ◽  
Risk Groups ◽  
Marrow Transplant ◽  
Intermediate Risk ◽  
Significant Difference ◽  
The Difference ◽  
The One ◽  
The Impact

Abstract The FLIPI prognosis score for follicular lymphoma (FL) was developed based on cases diagnosed between 1985 and 1992, and treated with different schemes that did not include rituximab (R). In the present study, we report the evolution of all FL treated in a single institution through the last decade and analize whether FLIPI mantains its effectiveness to identify different risk groups within patients treated with the new therapeutic alternatives available. Material and Methods: We identified sixty two patients with diagnosis of grade I-II-IIIa FL. Patients characteristics: median age 57.5 yr (r, 30–80); 36 males; 63% stages III–IV, and 37% with bone marrow infiltration at the time of diagnosis. Thirty eight percent had a low risk by FLIPI, 34% had an intermediate risk and 27.4% had a high risk. In 19 pts (30.6%) the initial decision was “watch and wait” but 82% received a form of treatment at some point. R was used in 36 pts (58%) with some of the following regimes: chemotherapy (chemo) + R and/or R as consolidation therapy and/or R as monotherapy and/or R as maintenance therapy. Of all prescribed treatments (excluding R as monotherapy and/or maintenance treatment), 52.8% were chemo alone, 20.2% chemo + R, 21.3% radiotherapy and 5.6% received a bone marrow transplant. Results: we considered the analysis of overall survival (OS) the most appropiate approach, since most treatments were seeking the control of the FL, and not the complete remission or cure. The follow up median time was 53.2 months ± 34.8 1SD. The 5-yr OS for the 62 pts was 81.8% ± 11.3 CI 95%. The 5-yr OS for those with a low, intermediate and high risk FLIPI was 100% −5, 84.2% ± 21 and 52% ±26.2, respectively. The difference in 5-yr OS was statistically significant between low and high risk, intermediate and high risk, but failed to prove a significant difference between low and intermediate risk. Among the different risk factors tested in a univariate analysis only age ≥ < 60 yr old demonstrated a significant difference, 60.7% vs 90%, respectively. Conclusions: The 5-yr OS in our series is higher than the one described in the original FLIPI study (Blood2004; 104:1258–65) which was 81.8% vs 71% for the whole group; 90% vs 78.1% for pts <60 yr old; 60.7% vs 57.7% for ≥ 60 yr old; 100% vs 90.6% for low FLIPI and 84.2% vs 77.6% for intermediate FLIPI. The only group that failed to prove an improvement was the high risk FLIPI with 52% vs 52.5%. The impact of novel therapies was more evident in patients with a low or intermediate FLIPI and was even more evident in patients younger than 60 yr old. According to our results, FLIPI maintains its effectiveness in differentiating two risk groups, i.e., low-intermediate vs high. We believe that the OS curves will probably continue to improve as the treatments that are considered today as the most effective ones, were just included in our series in the last three years.

Racial differences in delay of treatment for localized prostate cancer (CaP): A population-based study.

2012 ◽  
Vol 30 (15_suppl) ◽  
pp. 6037-6037
Author(s):  
William Allen Stokes ◽  
Laura H Hendrix ◽  
Trevor Joseph Royce ◽  
Ian M. Allen ◽  
Andrew Wang ◽  
...  
Keyword(s):  
High Risk ◽  
Racial Differences ◽  
Large Scale ◽  
Multivariable Analysis ◽  
Risk Groups ◽  
Population Based ◽  
Sensitivity Analyses ◽  
Treatment Delays ◽  
Time To Treatment ◽  
The Difference

6037 Background: African-Americans (AA) are diagnosed with more advanced CaP than Caucasians (CA) and are more likely to die from CaP. Treatment delay is a potentially modifiable obstacle to care and clinically may be more important in AA patients because of more aggressive cancer at diagnosis. We examined time from diagnosis to curative treatment (surgery or radiation) in AA and CA patients in the Surveillance, Epidemiologic and End Results (SEER)-Medicare linked database. Methods: 21,454 CA and 2,506 AA patients who were diagnosed with non-metastatic CaP from 2004-08 and received treatment within 12 months of diagnosis were included. Linear regression was used to examine factors associated with number of days from diagnosis to treatment initiation, and logistic regression to assess odds of treatment within 6 months of diagnosis. Results: AA patients were more likely to have high-risk CaP than CA patients (39 vs. 35%), and less likely to have low-risk CaP (27 vs. 31%) (p<.001). Time to treatment was significantly prolonged for AA patients in all risk groups of CaP, and the difference was most prominent for high-risk patients (median 105 days for AA vs. 96 days for CA, p=.002). Racial differences in time to treatment persisted in multivariable analysis (Table). Sensitivity analyses examining the proportion of AA and CA patients initiating treatment within 6 months of diagnosis revealed similar results. Conclusions: AA patients, especially those with high-risk CaP, experience longer treatment delays than CA patients. This is the first large-scale study to examine treatment delays in AA and CA patients with CaP. The differences found may contribute to our understanding of racial disparities in CaP treatment outcomes. [Table: see text]

Ability of the combined clinical cell-cycle risk score to identify patients that benefit from multi versus single modality therapy in NCCN intermediate and high-risk prostate cancer.

2020 ◽  
Vol 38 (6_suppl) ◽  
pp. 346-346
Author(s):  
Jonathan David Tward ◽  
Thorsten Schlomm ◽  
Stephen Bardot ◽  
Stephen J. Freedland ◽  
Lauren Lenz ◽  
...  
Keyword(s):  
Cell Cycle ◽  
High Risk ◽  
Risk Score ◽  
Cell Cycle Progression ◽  
Full Cohort ◽  
Treatment Benefit ◽  
High Risk Prostate Cancer ◽  
Kaplan Meier ◽  
Risk Prostate Cancer ◽  
The Difference

346 Background: Prolaris combines RNA expression analysis of cell cycle progression genes with clinicopathologic information to create a combined clinical cell-cycle risk score (CCR). We evaluated the ability of CCR to predict metastasis (mets) in men for whom guidelines indicate that multimodality therapy (MTx) should be considered. Methods: A commercial cohort (N=15669) of National Comprehensive Cancer Network unfavorable intermediate-risk (UFI) and high-risk (HR) men revealed a distribution of 70.5% and 29.5% respectively. A CCR threshold of 2.112 was selected so that 29.5% of these men were above the threshold. MTx was defined as combined use of androgen deprivation therapy with radiation (RT) or surgery, or with adjuvant RT. Associations were evaluated in a 718-person retrospective, multi-institutional database of Prolaris-tested UFI and HR men. Kaplan-Meier (KM) analyses and Cox regressions were used to estimate the effects of prognostic covariates. Results: Median follow-up was 5.13 years. CCR predicted mets in the full cohort (HR =3.8 [2.7,5.2], p<10−15) and after accounting for CAPRA (HR=4.3 [2.7,7.0], p< 10−7). CCR also was a significant predictor of mets in patients who received STx, as a continuous predictor (HR=4.0 [2.6,6.1], p<10−9) and when dichotomized at the threshold (HR=15.9 [5.4,46.5], p< 10−9). The KM probability of mets by 10 years for those below and above the threshold was 4.3% and 20.4% respectively. MTx reduced patients’ risk of mets (HR=0.46 [0.22,0.97], p=0.04), and treatment benefit can be evaluated as a function of CCR score (Table). Conclusions: The CCR score prognosticates a clinically meaningful different risk of metastasis for those receiving MTx versus STx. Approximately 27% and 73% of people with HR or UFI risk cancer have CCR scores below the risk threshold and may consider STx after considering the difference in risk of mets.[Table: see text]

scholarly journals Analysis of the Results of Gastrin-17 and its Related Influencing Factors in Health Check-Up Population

2021 ◽  
Author(s):  
Yan Shen ◽  
Junchao Zeng ◽  
Sanping Xu ◽  
Rui Yang
Keyword(s):  
Helicobacter Pylori ◽  
High Risk ◽  
Risk Groups ◽  
Gastrointestinal Diseases ◽  
Inflammatory Factors ◽  
Early Screening ◽  
Amyloid A ◽  
Significant Difference ◽  
High Risk Factor ◽  
The Difference

Abstract Background: To analyze the difference of serum gastrin-17 levels in different sexs, ages, and body mass index (BMI) of healthy people, and to explore the correlation between gastrin 17 and pepsinogen, in addition to study the influence of Helicobacter pylori infection and various inflammatory factors on the secretion level of gastrin-17. Methods: 531 subjects who received physical examination in our center from April 2019 to December 2019 were enrolled in the study. All the staff were tested for gastrin 17 (G17), pepsinogen I (PGI), pepsinogen II (PGII), PGI / PGII (PGR), Helicobacter pylori (Hp) and C-reactive protein (CRP) and other inflammatory factors. To compare the difference of G17 secretion in different populations and its correlation with PG, then to understand the HP infection and the influence of inflammatory indicators on G17. Results: There was no significant difference in the secretion level of G17 in different sex, age and BMI (P > 0.05); G17 was positively correlated with PGI and PGII, but negatively correlated with PGR; the level of G17 in Helicobacter pylori positive patients was 10.16±12.84, which was significantly higher than that in negative patients(3.27±6.65), P =0.017, 95% CI: 1.713 (1.100, 2.668); the increase of serum amyloid A(SAA) in different inflammatory indicators was the high-risk factor of G17 abnormality, P=0.016, 95% CI: 2.692 (1.202, 6.028), obviously CRP and erythrocyte sedimentation rate (ESR) had no effect on G17 abnormalities. Conclusions: The secretion of G17 is closely related to PG and HP. Combined screening is helpful for early screening of gastrointestinal diseases in healthy or high-risk groups of gastric cancer, but the influence of inflammatory indicators on G17 should be excluded to improve the reliability of the results.

scholarly journals Establishment of an immune-related gene pairs model to predict colon adenocarcinoma prognosis

2020 ◽  
Author(s):  
Jihang Luo ◽  
Puyu Liu ◽  
Leibo Wang ◽  
Yi Huang ◽  
Yuanyan Wang ◽  
...  
Keyword(s):  
Colon Cancer ◽  
High Risk ◽  
Risk Group ◽  
Colon Adenocarcinoma ◽  
Risk Groups ◽  
High Risk Group ◽  
Related Gene ◽  
Immune Genes ◽  
Gene Pairs ◽  
Immune Related Gene

Abstract Background. Colon cancer is the most common type of gastrointestinal cancer and has high morbidity and mortality. Colon adenocarcinoma(COAD) is the main pathological type of colon cancer. There is a lot of evidence describing the correlation between the prognosis of COAD and the immune system. The objective of the current study was the development of a robust prognostic immune-related gene pairs (IRGPs) model for estimating overall survival of COAD. Methods. The gene expression profiles and clinical information of patients with colon adenocarcinoma come from TCGA and GEO databases and are divided into training and validation cohorts. Immune genes were selected which show significantly association with prognosis. Results. Among 1647 immune genes, a 17 IRGPs model was built which was significantly associated with OS in the training cohort. In the training and validation data set, the IRGPs model divided patients into high-risk groups and low-risk groups, and the prognosis of the high-risk group was significantly worse(P＜0.001). Univariate and multivariate Cox proportional hazard analysis confirmed the feasibility of this model. Functional analysis confirmed that multiple tumor progression and stem cell growth-related pathways in high-risk groups were up-regulated. T cells regulatory and Macrophage M0 were significantly highly expressed in the high-risk group. Conclusion. We successfully constructed an IRGPs model that can predict the prognosis of COAD, which provides new insights into the treatment strategy of COAD.

scholarly journals Inflammation-Related Long Non-Coding RNA Signature Predicts the Prognosis of Gastric Carcinoma

2021 ◽  
Vol 12 ◽  
Author(s):  
ShuQiao Zhang ◽  
XinYu Li ◽  
ChunZhi Tang ◽  
WeiHong Kuang
Keyword(s):  
High Risk ◽  
Gastric Carcinoma ◽  
Risk Groups ◽  
Cytolytic Activity ◽  
Immune Checkpoints ◽  
Type I ◽  
Kaplan Meier ◽  
Non Coding Rna ◽  
Prognostic Prediction ◽  
Long Non Coding Rna

Background: Gastric carcinoma (GC) is a molecularly and phenotypically highly heterogeneous disease, making the prognostic prediction challenging. On the other hand, Inflammation as part of the active cross-talk between the tumor and the host in the tumor or its microenvironment could affect prognosis.Method: We established a prognostic multi lncRNAs signature that could better predict the prognosis of GC patients based on inflammation-related differentially expressed lncRNAs in GC.Results: We identified 10 differently expressed lncRNAs related to inflammation associated with GC prognosis. Kaplan-Meier survival analysis demonstrated that high-risk inflammation-related lncRNAs signature was related to poor prognosis of GC. Moreover, the inflammation-related lncRNAs signature had an AUC of 0.788, proving their utility in predicting GC prognosis. Indeed, our risk signature is more precise in predicting the prognosis of GC patients than traditional clinicopathological manifestations. Immune and tumor-related pathways for individuals in the low and high-risk groups were further revealed by GSEA. Moreover, TCGA based analysis revealed significant differences in HLA, MHC class-I, cytolytic activity, parainflammation, co-stimulation of APC, type II INF response, and type I INF response between the two risk groups. Immune checkpoints revealed CD86, TNFSF18, CD200, and LAIR1 were differently expressed between lowand high-risk groups.Conclusion: A novel inflammation-related lncRNAs (AC015660.1, LINC01094, AL512506.1, AC124067.2, AC016737.1, AL136115.1, AP000695.1, AC104695.3, LINC00449, AC090772.1) signature may provide insight into the new therapies and prognosis prediction for GC patients.

scholarly journals Pentraxin-3 Levels Relate to the Wells Score and Prognosis in Patients with Acute Pulmonary Embolism

2019 ◽  
Vol 2019 ◽  
pp. 1-6 ◽  
Author(s):  
Haotian Yang ◽  
Jun Zhang ◽  
Ying Huan ◽  
Yawei Xu ◽  
Rong Guo
Keyword(s):  
Pulmonary Embolism ◽  
High Risk ◽  
Acute Pulmonary Embolism ◽  
Risk Groups ◽  
Low Risk ◽  
Recurrent Pulmonary Embolism ◽  
Medium Risk ◽  
Wells Score ◽  
The Difference

Objective. To investigate the value of the PTX-3 test in evaluating the prognosis of acute pulmonary embolism (APE). Method. 117 APE patients were selected and divided into two groups according to plasma PTX-3 levels, including the group in which PTX−3≥3.0 ng/mL (n=42) and the group in which PTX−3<3.0 ng/mL (n=75). Patients were stratified into high-risk, medium-risk, and low-risk groups according to the Wells scores, and the PTX-3 levels were compared among the groups. Patients had been followed-up as well. Results. According to the Wells scores, 11 patients were classified as high-risk (9.4%) and 68 were medium-risk (58.1%), while 38 were low-risk (32.5%). The PTX-3 levels in different risk groups were statistically different (all P<0.05). During the follow-up period, 6 deaths occurred in the group with elevated PTX-3 (≥3.0 ng/mL), while 2 deaths occurred in the group with nonelevated PTX-3 (<3.0 ng/mL). The difference between the two groups was statistically significant (P<0.01). 13 patients were hospitalized due to recurrent pulmonary embolism, of which 12 were in the group with elevated PTX-3 (≥3.0 ng/mL), while 1 patient was in the group with nonelevated PTX-3 (<3.0 ng/mL). The difference was statistically significant (P<0.01). Conclusion. The plasma PTX-3 level in APE patients is correlated with PE risk stratification. There is a significant correlation between PTX-3 levels and PE-related cardiac deaths, as well as the prognosis of recurrent PE. PTX-3 can be used as a clinical indicator of PE prognosis.

A new look at the IDEA classification: Defining novel predictive and prognostic markers in stage III colon cancer.

2018 ◽  
Vol 36 (4_suppl) ◽  
pp. 845-845
Author(s):  
Ofer Margalit ◽  
Ronac Mamtani ◽  
Yu-Xiao Yang ◽  
Kim Anna Reiss ◽  
Talia Golan ◽  
...  
Keyword(s):  
Colon Cancer ◽  
High Risk ◽  
Cox Regression ◽  
Secondary Analysis ◽  
Risk Groups ◽  
Low Risk ◽  
Stage Iii ◽  
Stage Iii Colon Cancer ◽  
Risk Patients ◽  
Doublet Chemotherapy

845 Background: The IDEA pooled analysis compared 3 to 6 months of adjuvant chemotherapy for newly defined low- and high-risk stage III colon cancer patients, suggesting low-risk patients may be offered only 3 months of treatment. We aimed to evaluate the benefit of monotherapy vs doublet chemotherapy in low and high IDEA risk groups. Methods: Using the NCDB (2004-2014) we identified 56,728 and 47,557 individuals as low and high IDEA risk groups, respectively. We used multivariate COX regression to evaluate the magnitude of survival differences between IDEA risk groups, according to treatment intensity (doublet vs monotherapy). In a secondary analysis, we examined the predictive value of subgroups of age. Results: Low and high IDEA risk groups derived similar benefit from doublet chemotherapy compared to monotherapy, with hazard ratios of 0.83 (95%CI 0.79-0.86) and 0.80 (95%CI 0.78-0.83), respectively. The only subpopulations that did not benefit from doublet chemotherapy were low-risk patients above the age of 72 (HR = 0.95, 95%CI 0.90-1.01) and high-risk patients above the age of 85 (HR = 0.90, 95%CI 0.77-1.05). Conclusions: IDEA risk classification does not predict benefit from doublet chemotherapy in stage III colon cancer. However, omission of oxaliplatin can be considered in IDEA low-risk patients above the age of 72.

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