Creating prognostic systems for cancer patients: A demonstration using breast cancer

Hueman, Mathew T.; Wang, Huan; Yang, Charles; Sheng, Li; Henson, Donald E.; Schwartz, Arnold M.; Chen, Dechang

doi:10.1002/cam4.1629

Cited by 30 publications

(33 citation statements)

References 10 publications

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“…The age of the patient, size of the tumor and molecular biological factors such as ER, PR or Her-2 expression are notable factors affecting the prognosis of breast cancer (50,51). In addition, whether the tumor was associated with lymph nodes and distant metastases also had an important impact on the patient's prognosis (52). According to the Surveillance, Epidemiology and End Results Program, patients with BC with regional lymph node metastasis exhibit a 5-year survival rate of 85.5%, which is lower compared with the 5-year survival rate in patients with a localized tumor (98.8%) (53).…”

Section: Discussionmentioning

confidence: 99%

Elevated mRNA expression levels of DLGAP5 are associated with poor prognosis in breast cancer

Dong

Zhang

et al. 2020

Oncol Lett

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Breast cancer is the most commonly diagnosed type of cancer and one of the leading causes of cancer-associated mortality in women. In addition, the underlying molecular mechanisms of the occurrence and development of breast cancer requires further investigation. In the present study, bioinformatics analysis was performed to identify differentially expressed genes (DEGs) between breast cancer and normal breast tissues to investigate the underlying molecular mechanisms. In addition, reverse transcription-quantitative PCR and immunohistochemistry (IHC) were performed to investigate the protein and mRNA expression levels of a specific DEG, discs large-associated protein 5 (DLGAP5). A Cell Counting Kit-8 assay and flow cytometry analysis were used to assess the effects of DLGAP5 on cell proliferation. In total, 85 DEGs were identified in the three Gene Expression Omnibus datasets, including 40 upregulated and 45 downregulated genes. In addition, 30 hub genes were identified following the construction of a protein-protein interaction network, and 28 of the 30 hub genes were established to be indicators of breast cancer prognosis. DLGAP5 was highly expressed in breast cancer specimens, and its expression levels were correlated with clinical stage and lymph node status. In addition, downregulation of DLGAP5 repressed the proliferation of breast cancer MDA-MB-231 cells and induced cell cycle arrest. Additionally, DLGAP5 was identified to be localized in the mitochondria, and the presence of a conserved microtubule-associated proteins 1A/1B light chain 3B-interacting region motif suggested that DLGAP5 may serve a role in mitophagy. The present results demonstrated an association between DLGAP5 expression levels and the clinicopathological characteristics of patients with breast cancer using IHC. In conclusion, DLGAP5 may be a promising target in the diagnosis and treatment of breast cancer.

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Section: Discussionmentioning

confidence: 99%

Elevated mRNA expression levels of DLGAP5 are associated with poor prognosis in breast cancer

Dong

Zhang

et al. 2020

Oncol Lett

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“…At present, the prediction of the survival of cancer patients is mainly based on clinical stages, which were determined by tumor size, lymph node metastasis, and distant metastasis. 14 Development of novel prognostic factors may guide the selection of treatment options and the prediction of outcomes, which in turn benefit patients’ survival. 14 The expression pattern and functionality of NLIPMT have only been investigated in breast cancer, in which NLIPMT was downregulated, and overexpression of NLIPMT was shown to inhibit cancer metastasis.…”

Section: Discussionmentioning

confidence: 99%

“… 14 Development of novel prognostic factors may guide the selection of treatment options and the prediction of outcomes, which in turn benefit patients’ survival. 14 The expression pattern and functionality of NLIPMT have only been investigated in breast cancer, in which NLIPMT was downregulated, and overexpression of NLIPMT was shown to inhibit cancer metastasis. 12 This study is the first to report the downregulation of NLIPMT in CRC and the increased invasion and migration rates of CRC cells.…”

Section: Discussionmentioning

confidence: 99%

<p>Overexpression of lncRNA NLIPMT Inhibits Colorectal Cancer Cell Migration and Invasion by Downregulating TGF-β1</p>

Zhang

et al. 2020

CMAR

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Background: NLIPMT, as a tumor suppressive lncRNA, has only been investigated in breast cancer, while its roles in other types of cancer remain unknown. This study aimed to explore the role of NLIPMT in colorectal cancer (CRC). Methods: Expression levels of NLIPMT and TGF-β1 in two types of CRC tissue (Non-tumor tissues and tumor tissues) were measured and compared by qRT-PCR and paired t-test, respectively. Correlations between the expression of NLIPMT and TGF-β1 were analyzed by performing linear regression. The effects of transfections on cell invasion and migration were evaluated by Transwell assays. Results: We found that NLIPMT was downregulated, while TGF-β1 was upregulated in CRC. In CRC tumor, a negative correlation was found between the expression of NLIPMT and TGF-β1. In CRC cells, overexpression of NLIPMT resulted in downregulation, while silencing of NLIPMT resulted in upregulation of TGF-β1. Analysis of cell invasion and migration showed that overexpression of NLIPMT suppressed the tumor cell invasion and migration. In contrast, overexpression of TGF-β1 could promote CRC cell invasion and migration and also reduce the role of NLIPMT. Through the overall survival evaluation, NLIPMT-high groups of CRC represented better survival rate compared to that of the NLIPMT-low group patients. Conclusion: The expression of lncRNA NLIPMT was negatively correlated with TGF-β1 in CRC. Overexpression of NLIPMT inhibited the colorectal cancer cell migration and invasion by downregulating TGF-β1. Furthermore, the expression of NLIPMT in CRC patients predicted better prognosis, which suggested that NLIPMT could be considered as a novel diagnosis biomarker.

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“…In previous studies, other approaches such as nomogram and the Cancer Data Clustering Integration Algorithm (EACCD) were also applied to identify independent prognostic factors. Nomogram is a graphical prediction tool based on the Cox proportional hazard model that attempts to combine all proven prognostic factors and quantify the risk as accurately as possible . Because it does not require risk factors to be independent of each other, RPA outperforms the proportional risk model in identifying prognostic factors, and as a nonparametric technique, it makes no requirement on the underlying distribution of variables.…”

Section: Discussionmentioning

confidence: 99%

Development and validation of a new staging system for node‐negative gastric cancer based on recursive partitioning analysis: An international multi‐institutional study

Wang

et al. 2019

Cancer Medicine

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Background Whether the tumor‐node‐metastasis (TNM) staging system is appropriate for patients with node‐negative gastric cancer (GC) is still inconclusive. The modified staging system developed by recursive partitioning analysis (RPA) showed good prognostic performance in a variety of cancers. The application of RPA has not been reported in the prognostic prediction of GC. Methods Node‐negative GC patients who underwent radical resection at Fujian Medical University Union Hospital (n = 862) and Sun Yat‐sen University Cancer Center (n = 311) with at least 5 years of follow‐up were selected as the training set. RPA was used to develop a modified staging system. Patients from the Surveillance, Epidemiology, and End Results database (n = 1415) were selected as the validation set. Results The 5‐year overall survival (OS) rates of patients with 8th AJCC‐TNM stage IA‐IIIA in the training set were IA 95.2%, IB 87.1%, IIA 78.3%, IIB 75.8%, and IIIA 72.6%. Multivariate analysis (MVA) showed that larger tumor size, elder age, and deeper depth of invasion were independent predictors for OS in patients with node‐negative GC (all P < 0.05). Patients were reclassified into RPA I, RPA II, RPA III, and RPA IV stages based on RPA; the 5‐year OS rates were 96.1%, 87.2%, 81.0%, and 64.3%, respectively, with significant difference (P < 0.05). Two‐step MVA showed that the RPA staging system was an independent predictor of OS (P < 0.05). Compared with the 8th AJCC‐TNM staging system, the RPA staging system had a smaller AIC value (2544.9 vs 2576.2), higher χ2 score (104.2 vs 69.6) and higher Harrell's C‐index (0.697 vs 0.669, P = 0.007). The similar results were found in the validation set. Conclusions A new prognostic predictive system based on RPA was successfully developed and validated, which may be suggested for staging node‐negative GC in future.

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Creating prognostic systems for cancer patients: A demonstration using breast cancer

Cited by 30 publications

References 10 publications

Elevated mRNA expression levels of DLGAP5 are associated with poor prognosis in breast cancer

Elevated mRNA expression levels of DLGAP5 are associated with poor prognosis in breast cancer

<p>Overexpression of lncRNA NLIPMT Inhibits Colorectal Cancer Cell Migration and Invasion by Downregulating TGF-β1</p>

Development and validation of a new staging system for node‐negative gastric cancer based on recursive partitioning analysis: An international multi‐institutional study

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