Development of prognostic signature and nomogram for patients with breast cancer

Su, Jie; Miao, Lifeng; Ye, Xianghua; Cui, Meng-Shen; He, Xiaofeng

doi:10.1097/md.0000000000014617

Cited by 32 publications

(25 citation statements)

References 28 publications

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“…Nomograms have been widely used in clinical oncology as reliable tools for estimating numerical probabilities for individual patients by incorporating and illustrating important prognostic factors . This has been demonstrated in several types of cancers, including breast, lung, and gastric cancers, and the predictions of these nomograms may be more accurate than those based on the traditional TNM staging systems for various tumor types . Furthermore, we have thus far found relatively few nomograms for predicting survival in patients with stage II‐III CRC.…”

Section: Introductionmentioning

confidence: 99%

Nomogram for predicting overall survival in stage II‐III colorectal cancer

et al. 2020

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Purpose The 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 Methods Based 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. Results Preoperative 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). Conclusion We 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.

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Section: Introductionmentioning

confidence: 99%

Nomogram for predicting overall survival in stage II‐III colorectal cancer

et al. 2020

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“…Powell et al (2018) demonstrated that CEACAM5 was a clinically relevant driver of breast cancer metastasis. NKAIN1 is associated with OS in breast cancer (Su et al, 2019). DSCAM-AS1 promotes tumor growth in breast cancer by reducing miR-204-5p and upregulating RRM2 (Liang et al, 2019).…”

Section: Resultsmentioning

confidence: 99%

IBI: Identification of Biomarker Genes in Individual Tumor Samples

Wang

2019

Front. Genet.

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Individual patient biomarkers have an important role in personalized treatment. Although various high-throughput sequencing technologies are widely used in biological experiments, these are usually conducted only once or a few times for each patient, which makes it a challenging problem to identify biomarkers in individual patients. At present, there is a lack of effective methods to identify biomarkers in individual sample data. Here, we propose a novel method, IBI, to identify biomarkers in individual tumor samples. Experimental results from several tumor data sets showed that the proposed method could effectively find biomarker genes for individual patients, including common biomarkers related to the mechanisms of the development of cancer, which can be used to predict survival and drug response in patients. In summary, these results demonstrate that the proposed method offers a new perspective for analyzing individual samples.

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“…Recently, many biomarkers for breast cancer have been developed. A study developed a prognostic signature for the 19 gene associated with clinical prognosis in patients with BRCA (Su, Miao, Ye, Cui, & He, 2019). In addition, BCL2 and CD82 are both considered as potential and reliable biomarkers for breast cancer diagnosis (Wang et al, 2019).…”

Section: Discussionmentioning

confidence: 99%

Identification of Prognostic Alternative Splicing Signature in Triple-negative breast cancer

Zhou¹,

Guan²,

Lv³

et al. 2020

Preprint

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Background: Alternative splicing (AS) is a pervasive and vital mechanism involved in the progression of various cancer. Studies confirm the importance of prognostic value of AS events in tumor patients, but systematic analysis of AS in triple-negative breast cancer (TNBC) is still lacking. Methods: Information from 115 TNBC patients from the Cancer Genome Atlas (TCGA) database were extracted. And we performed a comprehensive analysis of whole-genome AS events with corresponding clinical information to evaluate the roles of seven AS patterns. Prognostic analyses were performed with predictive models and splicing network built for TNBC patients. Results: Among 28,744 mRNA AS events in 20,353 genes, we detected 1,428 AS in 138 important survival genes related to the overall survival of TNBC patients event. Through functional and pathway enrichment analysis, we found that these genes are involved in ubiquitin-mediated proteolytic pathways. At 1800 days overall survival, the area under the ROC curve for prognostic signatures was 0.8. It shows that this model is very effective in differentiating patient prognosis. The use of Spearman's test to establish a potential regulatory network between survival-related AS events and abnormal SF indicates a clear trend in the role of SF in TNBC. Conclusions: In summary, we established a reliable and powerful TNBC prognostic signature. A splicing network that could be its underlying mechanism was discovered. Keywords: Alternative splicing; Triple-negative breast cancer; Prognosis; Splicing factor

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Development of prognostic signature and nomogram for patients with breast cancer

Abstract: Supplemental Digital Content is available in the text

Cited by 32 publications

References 28 publications

Nomogram for predicting overall survival in stage II‐III colorectal cancer

Nomogram for predicting overall survival in stage II‐III colorectal cancer

IBI: Identification of Biomarker Genes in Individual Tumor Samples

Identification of Prognostic Alternative Splicing Signature in Triple-negative breast cancer

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