Prediction of overall survival in stage II and III colon cancer through machine learning of rapidly-acquired proteomics.
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SUBMITTER: Xu K
PROVIDER: S-EPMC11319451 | biostudies-literature | 2024 Aug
REPOSITORIES: biostudies-literature
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Prediction of overall survival in stage II and III colon cancer through machine learning of rapidly-acquired proteomics.
Xu Kailun K Yin Xiaoyang X Chen Hui H Huang Yuhui Y Zheng Xi X Zhou Biting B Cai Xue X Gao Huanhuan H Tian Miaomiao M Hu Sijun S Zheng Shu S Yuan Changzheng C Nie Yongzhan Y Guo Tiannan T Shao Yingkuan Y
Cell discovery 20240813 1
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Project description:BackgroundTNM staging alone does not accurately predict outcome in colon cancer (CC) patients who may be eligible for adjuvant chemotherapy. It is unknown to what extent the molecular markers microsatellite instability (MSI) and mutations in BRAF or KRAS improve prognostic estimation in multivariable models that include detailed clinicopathological annotation.Patients and methodsAfter imputation of missing at random data, a subset of patients accrued in phase 3 trials with adjuvant chemotherapy (n = 3016)-N0147 (NCT00079274) and PETACC3 (NCT00026273)-was aggregated to construct multivariable Cox models for 5-year overall survival that were subsequently validated internally in the remaining clinical trial samples (n = 1499), and also externally in different population cohorts of chemotherapy-treated (n = 949) or -untreated (n = 1080) CC patients, and an additional series without treatment annotation (n = 782).ResultsTNM staging, MSI and BRAFV600E mutation status remained independent prognostic factors in multivariable models across clinical trials cohorts and observational studies. Concordance indices increased from 0.61-0.68 in the TNM alone model to 0.63-0.71 in models with added molecular markers, 0.65-0.73 with clinicopathological features and 0.66-0.74 with all covariates. In validation cohorts with complete annotation, the integrated time-dependent AUC rose from 0.64 for the TNM alone model to 0.67 for models that included clinicopathological features, with or without molecular markers. In patient cohorts that received adjuvant chemotherapy, the relative proportion of variance explained (R2) by TNM, clinicopathological features and molecular markers was on an average 65%, 25% and 10%, respectively.ConclusionsIncorporation of MSI, BRAFV600E and KRAS mutation status to overall survival models with TNM staging improves the ability to precisely prognosticate in stage II and III CC patients, but only modestly increases prediction accuracy in multivariable models that include clinicopathological features, particularly in chemotherapy-treated patients.
| S-EPMC5406760 | biostudies-literature
Project description:Cancer metastases accounts for most cancer deaths. The secreting glycoprotein Wnt5a impairs tumor cell migration and reduces invasiveness and metastasis. High Wnt5a expression in tumor cells is correlated to better outcomes in patients with breast, prostate and epithelial ovarian cancer. We aimed to investigate the association between the Wnt5a expression and outcomes in patients with colon cancer (CC) stage II/III. We performed a retrospective single-center study evaluating 345 patients with radical resection for primary CC, stage II/III, who started 6 months of adjuvant chemotherapy with 5-FU or capecitabine ± oxaliplatin between 2001 and 2015. Archived formalin-fixed paraffin embedded tumor tissue from resection specimens were stained with Wnt5a antibody using immunohistochemistry. Cytoplasmatic Wnt5a staining was assessed according to intensity and percentage of stained cells. Patients were divided in groups depending on high (n = 230) or low (n = 115) Wnt5a expression. Disease free survival (DFS) and overall survival (OS) were analyzed for the two groups using Kaplan-Meier plots and Long rank test. Patients with Wnt5a-negative tumors had significantly poorer performance status (PS) than patients with high Wnt5a expression (p = 0.046). No significant difference was seen between patients with low and high Wnt5a expression in terms of 5-year DFS (p = 0.517) or 5-year OS (p = 0.415). Poor PS was associated with lower DFS (p = 0.002) and OS (p < 0.001). In conclusion, we found no significant difference in prognosis for patients with stage II/III CC depending on their Wnt5a expression. Patients with Wnt5a-negative tumors had significant poorer PS than patients with higher levels. Poor PS was associated with lower DFS and OS.
| S-EPMC7553443 | biostudies-literature
Project description:PurposeThe overall survival (OS) of patients diagnosed with stage II-III colorectal cancer (CRC) can vary greatly, even between patients with the same tumor stage. We aimed to design a nomogram to predict OS in resected, stage II-III CRC and stratify patients with CRC into different risk groups.Patients and methodsBased on data from 873 patients with CRC, we used univariate Cox regression analysis to select the significant prognostic features, which were subjected to the least absolute shrinkage and selection operator (LASSO) regression algorithm for feature selection. Cross-validation was used to confirm suitable tuning parameters (λ) for LASSO logistic regression. Then, the nomogram was used to estimate 3- and 5-year OS based on the multivariable Cox regression model. The survival curves of the two groups were produced using the Kaplan-Meier method. Risk group stratification was performed to assess the predictive capacity of the nomogram.ResultsPreoperative mean platelet volume, preoperative platelet distribution width, monocytes, and postoperative adjuvant chemotherapy were identified as independent prognostic factors by LASSO regression and integrated for the construction of the nomogram. The nomogram provided good discrimination, with C-indices of 0.67 and 0.69 for the training and validation sets, respectively. Calibration plots illustrated excellent agreement between the nomogram predictions and actual observations for 3- and 5-year OS. Moreover, a significant difference in OS was shown between patients stratified into different risk groups (P < .001).ConclusionWe constructed and validated an original predictive nomogram for OS in patients with CRC after surgery, facilitating physicians to appraise the individual survival of postoperative patients accurately and identify high-risk patients who need more aggressive treatment and follow-up strategies.
| S-EPMC7131840 | biostudies-literature
Project description:Limited biomarkers have been identified as prognostic predictors for stage III colon cancer. To combat this shortfall, we developed a computer-aided approach which combing convolutional neural network with machine classifier to predict the prognosis of stage III colon cancer from routinely haematoxylin and eosin (H&E) stained tissue slides. We trained the model by using 101 cancers from West China Hospital (WCH). The predictive effectivity of the model was validated by using 67 cancers from WCH and 47 cancers from The Cancer Genome Atlas Colon Adenocarcinoma database. The selected model (Gradient Boosting-Colon) provided a hazard ratio (HR) for high- vs. low-risk recurrence of 8.976 (95% confidence interval (CI), 2.824-28.528; P, 0.000), and 10.273 (95% CI, 2.177-48.472; P, 0.003) in the two test groups, from the multivariate Cox proportional hazards analysis. It gave a HR value of 10.687(95% CI, 2.908-39.272; P, 0.001) and 5.033 (95% CI,1.792-14.132; P, 0.002) for the poor vs. good prognosis groups. Gradient Boosting-Colon is an independent machine prognostic predictor which allows stratification of stage III colon cancer into high- and low-risk recurrence groups, and poor and good prognosis groups directly from the H&E tissue slides. Our findings could provide crucial information to aid treatment planning during stage III colon cancer.
| S-EPMC7316723 | biostudies-literature
Project description:Background The identification of high-risk stage II colon cancers is key to the selection of patients who require adjuvant treatment after surgery. Microarray-based multigene-expression signatures derived from stem cells and progenitor cells hold promise, but they are difficult to use in clinical practice. Methods We used a new bioinformatics approach to search for biomarkers of colon epithelial differentiation across gene-expression arrays and then ranked candidate genes according to the availability of clinical-grade diagnostic assays. With the use of subgroup analysis involving independent and retrospective cohorts of patients with stage II or stage III colon cancer, the top candidate gene was tested for its association with disease-free survival and a benefit from adjuvant chemotherapy. Results The transcription factor CDX2 ranked first in our screening test. A group of 87 of 2115 tumor samples (4.1%) lacked CDX2 expression. In the discovery data set, which included 466 patients, the rate of 5-year disease-free survival was lower among the 32 patients (6.9%) with CDX2-negative colon cancers than among the 434 (93.1%) with CDX2-positive colon cancers (hazard ratio for disease recurrence, 3.44; 95% confidence interval [CI], 1.60 to 7.38; P=0.002). In the validation data set, which included 314 patients, the rate of 5-year disease-free survival was lower among the 38 patients (12.1%) with CDX2 protein-negative colon cancers than among the 276 (87.9%) with CDX2 protein-positive colon cancers (hazard ratio, 2.42; 95% CI, 1.36 to 4.29; P=0.003). In both these groups, these findings were independent of the patient's age, sex, and tumor stage and grade. Among patients with stage II cancer, the difference in 5-year disease-free survival was significant both in the discovery data set (49% among 15 patients with CDX2-negative tumors vs. 87% among 191 patients with CDX2-positive tumors, P=0.003) and in the validation data set (51% among 15 patients with CDX2-negative tumors vs. 80% among 106 patients with CDX2-positive tumors, P=0.004). In a pooled database of all patient cohorts, the rate of 5-year disease-free survival was higher among 23 patients with stage II CDX2-negative tumors who were treated with adjuvant chemotherapy than among 25 who were not treated with adjuvant chemotherapy (91% vs. 56%, P=0.006). Conclusions Lack of CDX2 expression identified a subgroup of patients with high-risk stage II colon cancer who appeared to benefit from adjuvant chemotherapy. (Funded by the National Comprehensive Cancer Network, the National Institutes of Health, and others.).
| S-EPMC4784450 | biostudies-literature
Project description:Tumor profiling of DNA alterations, i.e. gene point mutations, somatic copy number aberrations (CNAs) and structural variants (SVs), improves insight into the molecular pathology of cancer and clinical outcome. Here, associations between genomic aberrations and disease recurrence in stage II and III colon cancers were investigated. A series of 114 stage II and III microsatellite stable colon cancer samples were analyzed by high-resolution array-comparative genomic hybridization (array-CGH) to detect CNAs and CNA-associated chromosomal breakpoints (SVs). For 60 of these samples mutation status of APC, TP53, KRAS, PIK3CA, FBXW7, SMAD4, BRAF and NRAS was determined using targeted massive parallel sequencing. Loss of chromosome 18q12.1-18q12.2 occurred more frequently in tumors that relapsed than in relapse-free tumors (p < 0.001; FDR = 0.13). In total, 267 genes were recurrently affected by SVs (FDR < 0.1). CNAs and SVs were not associated with disease-free survival (DFS). Mutations in APC and TP53 were associated with increased CNAs. APC mutations were associated with poor prognosis in (5-fluorouracil treated) stage III colon cancers (p = 0.005; HR = 4.1), an effect that was further enhanced by mutations in MAPK pathway (KRAS, NRAS, BRAF) genes. We conclude that among multiple genomic alterations in CRC, strongest associations with clinical outcome were observed for common mutations in APC.
| S-EPMC5342020 | biostudies-literature
Project description:Current prognostic tools in colon cancer use relatively few patient characteristics. We constructed and validated clinical calculators for overall survival (OS) and time to recurrence (TTR) for stage III colon cancer and compared their performance against an existing tool (Numeracy) and American Joint Committee on Cancer (AJCC) version 7 staging. Data from 15936 stage III patients accrued to phase III clinical trials since 1989 were used to construct Cox models for TTR and OS. Variables included age, sex, race, body mass index, performance status, tumor grade, tumor stage, ratio of positive lymph nodes to nodes examined, number and location of primary tumors, and adjuvant treatment (fluoropyrimidine single agent or in combination). Missing data were imputed, and final models internally validated for optimism-corrected calibration and discrimination and compared with AJCC. External validation and comparisons against Numeracy were performed using stage III patients from NSABP trial C-08. All statistical tests were two-sided. All variables were statistically and clinically significant for OS prediction, while age and race did not predict TTR. No meaningful interactions existed. Models for OS and TTR were well calibrated and associated with C-indices of 0.66 and 0.65, respectively, compared with C-indices of 0.58 and 0.59 for AJCC. These tools, available online, better predicted patient outcomes than Numeracy, both overall and within patient subgroups, in external validation. The proposed ACCENT calculators are internally and externally valid, better discriminate patient risk than AJCC version 7 staging, and better predict patient outcomes than Numeracy. These tools have replaced Numeracy for online clinical use and will aid prognostication and patient/physician communication.
| S-EPMC4334801 | biostudies-literature
Project description:Accurate risk stratification for patients with stage II/III colon cancer is pivotal for postoperative treatment decisions. Here, we aimed to identify and validate a circRNA-based signature that could improve postoperative prognostic stratification for these patients. In current retrospective analysis, we included 667 patients with R0 resected stage II/III colon cancer. Using RNA-seq analysis of 20 paired frozen tissues collected postoperation, we profiled differential circRNA expression between patients with and without recurrence, followed by quantitative validation. With clinical information, we generated a four-circRNA-based cirScore to classify patients into high-risk and low-risk groups in the training cohort. The patients with high cirScores in the training cohort had a shorter disease-free survival (DFS) and overall survival (OS) than patients with low cirScores. The prognostic capacity of the classifier was validated in the internal and external cohorts. Loss-of-function assays indicated that the selected circRNAs played functional roles in colon cancer progression. Overall, our four-circRNA-based classifier is a reliable prognostic tool for postoperative disease recurrence in patients with stage II/III colon cancer.
| S-EPMC6783650 | biostudies-literature
Project description:Accurate risk stratification for patients with stage II/III colon cancer is pivotal for postoperative treatment decisions. Here, we aimed to identify and validate a circRNA-based signature that could improve postoperative prognostic stratification for these patients. In current retrospective analysis, we included 667 patients with R0 resected stage II/III colon cancer. Using RNA-seq analysis of 20 paired frozen tissues collected post-operation, we profiled differential circRNA expression between patients with and without recurrence, followed by quantitative validation. With clinical information, we generated a four-circRNA-based cirScore to classify patients into high-risk and low-risk groups in the training cohort. The patients with high cirScores in the training cohort had a shorter disease-free survival (DFS) and overall survival (OS) than patients with low cirScores. The prognostic capacity of the classifier was validated in the internal and external cohorts. Loss-of-function assays indicated that the selected circRNAs played functional roles in colon cancer progression. Overall, our four-circRNA-based classifier is a reliable prognostic tool for postoperative disease recurrence in patients with stage II/III colon cancer.
| S-SCDT-EMM-2018-10168 | biostudies-other
Project description:Background & aimsMany genetic variants have been associated with colorectal cancer risk, although few have been associated with survival times of patients. Identification of genetic variants associated with survival times might improve our understanding of disease progression and aid in outcome prediction. We performed a genome-wide association study to identify variants associated with colon cancer survival time.MethodsWe performed a post hoc analysis of data from NCCTG N0147 (Alliance), a randomized phase 3 trial of patients with resected stage III colon cancer, and from NSABP C-08 (NRG), a phase 3 trial that compared therapy regimens for patients with resected stage II or III colon cancer. Genotype analyses were performed on DNA from blood samples from 4974 patients. We used Cox proportional hazards regression to evaluate the association of each single nucleotide polymorphism with times of overall survival and disease-free survival, adjusting for age at diagnosis, sex, treatment group, and principal components of genetic ancestry. We performed the analysis for studies N0147 and C-08 separately, and results were combined in a fixed-effects meta-analysis.ResultsA locus on chromosome 7p15.2 was significantly associated with overall survival time (P ≤ 5x10-08). The most significant variant at this locus, rs76766811 (P = 1.6x10-08), is common among African Americans (minor allele frequency, approximately 18%) but rare in European Americans (minor allele frequency <0.1%). Within strata of self-reported ancestry, this variant was associated with times of overall survival and disease-free survival in only African Americans (hazard ratio for overall survival, 2.82; 95% CI, 1.88-4.23; P = 5.0x10-07 and hazard ratio for disease-free survival, 2.27; 95% CI, 1.62-3.18; P = 1.8x10-06).ConclusionsIn an analysis of data from 2 trials of patients with stage II or III colon cancer, we identified rs76766811 as a potential prognostic variant in African American patients. This finding should be confirmed in additional study populations. ClinicalTrials.gov Identifiers: NCT00096278 (NSABP C-08) and NCT00079274 (NCCTG N0147).
| S-EPMC7269796 | biostudies-literature