Increased Expression of Integrin Subunit α3 is Correlated with Worse Recurrence-Free Survival in Thyroid Cancer

Abstract Objective: To investigate the potential effect of integrin subunit α3 (ITGA3) on thyroid cancer (THCA). Materials and Methods: Based on bioinformatics databases, the expression levels of ITGA3 were firstly analyzed, followed by evaluating the prognostic significance of ITGA3 in THCA patients. Cox regression analysis predicted the independent prognostic factors for THCA. Then, cBioportal and GSCA databases were applied to evaluate genetic alterations of ITGA3. Functional enrichment analysis was conducted using the R package. Finally, the upstream microRNAs of ITGA3 were determined. Results: ITGA3 gene and protein levels were higher in the THCA group than normal group (all P <0.05). And ITGA3 mRNA expression was significantly related to cancer stage and histological subtype (all P <0.01). Moreover, high expression of ITGA3 was associated with poor recurrence-free survival (RFS) of THCA patients in all subgroups (all P <0.01). Cox regression analysis presented that ITGA3 overexpression was an independent prognostic factor for worse RFS in THCA patients. Besides, significant relations were observed between ITGA3 and genetic alterations (FDR <0.01). Functional enrichment analysis indicated ECM-receptor interaction, and cell adhesion molecules were the shared regulatory pathways. We also found that ITGA3 might be the target gene of hsa-miR-3129, hsa-miR-181d, hsa-miR-181b, hsa-miR-199a, and hsa-miR-199b, which were all correlated with THCA patient prognosis. Conclusions: ITGA3 could be a reliable biomarker and promising therapeutic target for improving the diagnosis and clinical outcomes of THCA patients.

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Predictive Proteomic Signature for the Prognosis of Cervical Cancer

10.21203/rs.3.rs-327396/v1 ◽

2021 ◽

Author(s):

Xiaoyu Ji ◽

Guangdi Chu ◽

Jinwen Jiao ◽

Teng Lv ◽

Yulong Chen ◽

...

Keyword(s):

Cervical Cancer ◽

Regression Analysis ◽

Cox Regression ◽

Predictive Ability ◽

Enrichment Analysis ◽

Functional Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Functional Enrichment ◽

Cox Regression Analysis ◽

Incidence And Mortality

Abstract Objective: Cervical cancer (CC) is one of the most common types of malignant female cancer, and its incidence and mortality are not optimistic. Protein panels can be a powerful prognostic factor for many types of cancer. The purpose of our study was to investigate a proteomic panel to predict survival of patients with common CC. Methods and results: The protein expression and clinicopathological data of CC were downloaded from The Cancer Proteome Atlas (TCPA) and The Cancer Genome Atlas (TCGA) database, respectively. We selected the prognosis-related proteins (PRPs) by univariate Cox regression analysis and found that the results of functional enrichment analysis were mainly related to apoptosis. We used Kaplan–Meier(K-M) analysis and multivariable Cox regression analysis further to screen PRPs to establish a prognostic model, including BCL2, SMAD3, and 4EBP1-pT70. The signature was verified to be independent predictors of OS by Cox regression analysis and the Area Under Curves. Nomogram and subgroup classification were established based on the signature to verify its clinical application. Furthermore, we looked for the co-expressed proteins of three-protein panel as potential prognostic proteins.Conclusion: A proteomic signature independently predicted OS of CC patients, and the predictive ability was better than the clinicopathological characteristics. This signature can help improve prediction for clinical outcome and provides new targets for CC treatment.

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Construction of a prognostic model with histone modification-related genes and identification of potential drugs in pancreatic cancer

Cancer Cell International ◽

10.1186/s12935-021-01928-6 ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Yuan Chen ◽

Ruiyuan Xu ◽

Rexiati Ruze ◽

Jinshou Yang ◽

Huanyu Wang ◽

...

Keyword(s):

Regression Analysis ◽

Histone Modification ◽

Cox Regression ◽

Enrichment Analysis ◽

Functional Enrichment Analysis ◽

Functional Enrichment ◽

Training Set ◽

Test Set ◽

Cox Regression Analysis ◽

Small Molecule Drugs

Abstract Background Pancreatic cancer (PC) is a highly fatal and aggressive disease with its incidence and mortality quite discouraging. An effective prediction model is urgently needed for the accurate assessment of patients’ prognosis to assist clinical decision-making. Methods Gene expression data and clinicopathological data of the samples were acquired from The Cancer Genome Atlas (TCGA), Genotype-Tissue Expression (GTEx), and Gene Expression Omnibus (GEO) databases. Differential expressed genes (DEGs) analysis, univariate Cox regression analysis, least absolute shrinkage and selection operator (LASSO) regression analysis, random forest screening and multivariate Cox regression analysis were applied to construct the risk signature. The effectiveness and independence of the model were validated by time-dependent receiver operating characteristic (ROC) curve, Kaplan–Meier (KM) survival analysis and survival point graph in training set, test set, TCGA entire set and GSE57495 set. The validity of the core gene was verified by immunohistochemistry and our own independent cohort. Meanwhile, functional enrichment analysis of DEGs between the high and low risk groups revealed the potential biological pathways. Finally, CMap database and drug sensitivity assay were utilized to identify potential small molecular drugs as the risk model-related treatments for PC patients. Results Four histone modification-related genes were identified to establish the risk signature, including CBX8, CENPT, DPY30 and PADI1. The predictive performance of risk signature was validated in training set, test set, TCGA entire set and GSE57495 set, with the areas under ROC curve (AUCs) for 3-year survival were 0.773, 0.729, 0.775 and 0.770 respectively. Furthermore, KM survival analysis, univariate and multivariate Cox regression analysis proved it as an independent prognostic factor. Mechanically, functional enrichment analysis showed that the poor prognosis of high-risk population was related to the metabolic disorders caused by inadequate insulin secretion, which was fueled by neuroendocrine aberration. Lastly, a cluster of small molecule drugs were identified with significant potentiality in treating PC patients. Conclusions Based on a histone modification-related gene signature, our model can serve as a reliable prognosis assessment tool and help to optimize the treatment for PC patients. Meanwhile, a cluster of small molecule drugs were also identified with significant potentiality in treating PC patients.

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Over-expression of SRD5A3 and its prognostic significance in breast cancer

World Journal of Surgical Oncology ◽

10.1186/s12957-021-02377-1 ◽

2021 ◽

Vol 19 (1) ◽

Cited By ~ 1

Author(s):

Yong-ping Zhang ◽

Wen-ting Na ◽

Xiao-qiang Dai ◽

Ruo-fei Li ◽

Jian-xiong Wang ◽

...

Keyword(s):

Breast Cancer ◽

Regression Analysis ◽

Mrna Expression ◽

Prognostic Value ◽

Cox Regression ◽

Enrichment Analysis ◽

Genetic Alterations ◽

Functional Enrichment ◽

Cox Regression Analysis ◽

Expression Levels

Abstract Objective The study aimed to compare the Steroid 5 alpha-reductase 3 (SRD5A3) expression levels in breast cancer (BC) and normal tissues, to investigate the prognostic value of SRD5A3 mRNA expression in BC patients and to identify the SRD5A3-related signaling pathways using bioinformatics approaches. Methods We evaluated the expression levels of SRD5A3 and survival data in BC patients using different bioinformatic databases. Further, Cox regression analysis was conducted to predict the independent prognostic factors for BC. Moreover, the association of SRD5A3 with clinicopathological factors was measured through LinkedOmics database. And the potential role of SRD5A3 was determined by Gene Ontology and KEGG pathway enrichment analysis. Finally, protein network of SRD5A3 was constructed and genetic alterations were analyzed. Results Bioinformatic data indicated that both mRNA and protein expression levels of SRD5A3 were higher in BC group than those in the normal group (P < 0.05). Besides, BC patients with higher SRD5A3 mRNA expression levels had a lower overall survival (all P < 0.05). Cox regression analysis further demonstrated the independent prognostic value of SRD5A3 in BC (P = 0.015). SRD5A3 mRNA expression was significantly associated with N stage (P < 0.001), age (P < 0.05), and histologic subtype (P < 0.001) but had no significant relationship with other clinical characteristics (all P > 0.05). Moreover, the functional enrichment analysis revealed that the SRD5A3 was involved in metabolism-related pathways (all P < 0.05). Conclusions SRD5A3 was highly expressed in BC tissues and high SRD5A3 expression was related to poorer prognosis. SRD5A3 serves as an oncogene and might function as a potential biomarker for prognosis and a therapeutic target for BC.

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Identification of a prognostic long non-coding RNA signature in breast cancer

10.21203/rs.3.rs-27286/v1 ◽

2020 ◽

Author(s):

Gaochen Lan ◽

Xiaoling Yu ◽

Yanna Zhao ◽

Jinjian Lan ◽

Wan Li ◽

...

Keyword(s):

Breast Cancer ◽

Cox Regression ◽

Prognostic Biomarker ◽

Expression Profiles ◽

Enrichment Analysis ◽

Functional Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Functional Enrichment ◽

Differentially Expressed ◽

Cox Regression Analysis

Abstract Background: Breast cancer is the most common malignant disease among women. At present, more and more attention has been paid to long non-coding RNAs (lncRNAs) in the field of breast cancer research. We aimed to investigate the expression profiles of lncRNAs and construct a prognostic lncRNA for predicting the overall survival (OS) of breast cancer.Methods: The expression profiles of lncRNAs and clinical data with breast cancer were obtained from The Cancer Genome Atlas (TCGA). Differentially expressed lncRNAs were screened out by R package (limma). The survival probability was estimated by the Kaplan‑Meier Test. The Cox Regression Model was performed for univariate and multivariate analysis. The risk score (RS) was established on the basis of the lncRNAs’ expression level (exp) multiplied regression coefficient (β) from the multivariate cox regression analysis with the following formula: RS=exp a1 * β a1 + exp a2 * β a2 +……+ exp an * β an. Functional enrichment analysis was performed by Metascape.Results: A total of 3404 differentially expressed lncRNAs were identified. Among them, CYTOR, MIR4458HG and MAPT-AS1 were significantly associated with the survival of breast cancer. Finally, The RS could predict OS of breast cancer (RS=exp CYTOR * β CYTOR + exp MIR4458HG * β MIR4458HG + exp MAPT-AS1 * β MAPT-AS1). Moreover, it was confirmed that the three-lncRNA signature could be an independent prognostic biomarker for breast cancer (HR=3.040, P=0.000).Conclusions: This study established a three-lncRNA signature, which might be a novel prognostic biomarker for breast cancer.

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Identification and Validation of a Potential Prognostic 7-lncRNA Signature for Predicting Survival in Patients with Multiple Myeloma

BioMed Research International ◽

10.1155/2020/3813546 ◽

2020 ◽

Vol 2020 ◽

pp. 1-16 ◽

Cited By ~ 1

Author(s):

Yun Zhong ◽

Zhe Liu ◽

Dangchi Li ◽

Qinyuan Liao ◽

Jingao Li

Keyword(s):

Gene Expression ◽

Risk Score ◽

Cox Regression ◽

External Validation ◽

Survival Rates ◽

Enrichment Analysis ◽

Functional Enrichment Analysis ◽

Functional Enrichment ◽

Test Set ◽

Cox Regression Analysis

Background. An increasing number of studies have indicated that the abnormal expression of certain long noncoding RNAs (lncRNAs) is linked to the overall survival (OS) of patients with myeloma. Methods. Gene expression data of myeloma patients were downloaded from the Gene Expression Omnibus (GEO) database (GSE4581 and GSE57317). Cox regression analysis, Kaplan-Meier, and receiver operating characteristic (ROC) analysis were performed to construct and validate the prediction model. Single sample gene set enrichment (ssGSEA) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis were used to predict the function of a specified lncRNA. Results. In this study, a seven-lncRNA signature was identified and used to construct a risk score system for myeloma prognosis. This system was used to stratify patients with different survival rates in the training set into high-risk and low-risk groups. Test set, the entire test set, the external validation set, and the myeloma subtype achieved the authentication of the results. In addition, functional enrichment analysis indicated that 7 prognostic lncRNAs may be involved in the tumorigenesis of myeloma through cancer-related pathways and biological processes. The results of the immune score showed that IF_I was negatively correlated with the risk score. Compared with the published gene signature, the 7-lncRNA model has a higher C-index (above 0.8). Conclusion. In summary, our data provide evidence that seven lncRNAs could be used as independent biomarkers to predict the prognosis of myeloma, which also indicated that these 7 lncRNAs may be involved in the progression of myeloma.

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Construction and Analysis of Survival-Associated Competing Endogenous RNA Network in Lung Adenocarcinoma

BioMed Research International ◽

10.1155/2021/4093426 ◽

2021 ◽

Vol 2021 ◽

pp. 1-17

Author(s):

Lixian Chen ◽

Zhonglu Ren ◽

Yongming Cai

Keyword(s):

Prognostic Factors ◽

Lung Adenocarcinoma ◽

Molecular Mechanisms ◽

Cox Regression ◽

Enrichment Analysis ◽

Functional Enrichment Analysis ◽

Functional Enrichment ◽

Competing Endogenous Rna ◽

Cox Regression Analysis ◽

Cerna Network

Increasing evidence has shown that noncoding RNAs play significant roles in the initiation, progression, and metastasis of tumours via participating in competing endogenous RNA (ceRNA) networks. However, the survival-associated ceRNA in lung adenocarcinoma (LUAD) remains poorly understood. In this study, we aimed to investigate the regulatory mechanisms underlying ceRNA in LUAD to identify novel prognostic factors. mRNA, lncRNA, and miRNA sequencing data obtained from the GDC data portal were utilized to identify differentially expressed (DE) RNAs. Survival-related RNAs were recognized using univariate Kaplan-Meier survival analysis. We performed functional enrichment analysis of survival-related mRNAs using the clusterProfiler package of R and STRING. lncRNA-miRNA and miRNA-mRNA interactions were predicted based on miRcode, Starbase, and miRanda. Subsequently, the survival-associated ceRNA network was constructed for LUAD. Multivariate Cox regression analysis was used to identify prognostic factors. Finally, we acquired 15 DE miRNAs, 49 DE lncRNAs, and 843 DE mRNAs associated with significant overall survival. Functional enrichment analysis indicated that survival-related DE mRNAs were enriched in cell cycle. The survival-associated lncRNA-miRNA-mRNA ceRNA network was constructed using five miRNAs, 49 mRNAs, and 21 lncRNAs. Furthermore, seven hub RNAs (LINC01936, miR-20a-5p, miR-31-5p, TNS1, TGFBR2, SMAD7, and NEDD4L) were identified based on the ceRNA network. LINC01936 and miR-31-5p were found to be significant using the multifactorial Cox regression model. In conclusion, we successfully constructed a survival-related lncRNA-miRNA-mRNA ceRNA regulatory network in LUAD and identified seven hub RNAs, which provide novel insights into the regulatory molecular mechanisms associated with survival of LUAD, and identified two independent prognostic predictors for LUAD.

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Six-long Non-coding RNA Signature to Predict the Prognosis of Lung Adenocarcinoma

10.21203/rs.3.rs-56767/v1 ◽

2020 ◽

Author(s):

Yang Wang ◽

Chengping Hu

Keyword(s):

Lung Adenocarcinoma ◽

Cox Regression ◽

Survival Rates ◽

Enrichment Analysis ◽

Functional Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Functional Enrichment ◽

Protein Coding ◽

Cox Regression Analysis ◽

Protein Coding Genes

Abstract Background: Long non-coding RNAs (lncRNAs) have been reported to play essential roles in tumorigenesis and cancers prognosis, and they can be a potential cancer prognostic markers. However, in lung adenocarcinoma(LUAD), how lncRNA signatures predict the survival of patients is poorly understood. Our study aims to explore lncRNA signatures and prognostic function in LUAD.Methods: The expression and prognosis data of lncRNAs in LUAD patients was collected from the Cancer Genome Atlas (TCGA) data. All analyses were performed using the R package (version 3.6.2). Metascape, STRING and Cytoscape were used for enrichment analysis and function prediction of the lncRNA co-expressed protein-coding genes.Results: We have collected lncRNA expression data in 466 LUAD tumors, and a six-lncRNA signature(RP11-79H23.3, RP11-309M7.1, CTD-2357A8.3, RP11-108P20.4, U47924.29, LHFPL3-AS2) has been shown to be significantly related to LUAD patients’ overall survival. According to the lncRNA signatures, the high-risk and low-risk groups were divided in LUAD patients with different survival rates. Further multivariable cox regression analysis showed that the prognostic value of this signature was independent of clinical factors. The potential functional roles and hub co-expressed protein-coding genes in the six prognostic lncRNAs are shown in the functional enrichment analysis.Conclusions: These results showed that these six lncRNAs could be independent predicted prognostic biomarkers in LUAD patients.

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Prognostic impact of LDH and HCG levels in marker-positive seminomas.

Journal of Clinical Oncology ◽

10.1200/jco.2020.38.6_suppl.392 ◽

2020 ◽

Vol 38 (6_suppl) ◽

pp. 392-392 ◽

Cited By ~ 2

Author(s):

Christoph Alexander Seidel ◽

Gedske Daugaard ◽

Tim Nestler ◽

Alexey Tryakin ◽

Christian Daniel Fankhauser ◽

...

Keyword(s):

Regression Analysis ◽

Cox Regression ◽

Serum Levels ◽

Rank Test ◽

Prognostic Impact ◽

Recurrence Free Survival ◽

Free Survival ◽

Cox Regression Analysis ◽

Oncological Outcomes ◽

Log Rank Test

392 Background: The prognostic impact of LDH and HCG serum levels in marker positive metastatic seminoma patients is uncertain. This analysis evaluated the association between LDH and HCG levels with oncological outcomes in this patient population. Methods: Seminoma patients with elevated HCG levels were retrospectively analyzed. After stratification according to tumor marker levels pre- and post-orchiectomy, outcomes of subgroups were compared using log-rank test and cox-regression analysis. Study endpoints were cancer specific- (CSS) and recurrence-free survival (RFS). Results: In total, 429 HCG-positive metastatic seminoma patients (stage II n=291; stage III n=138) diagnosed between 1981 and 2018 were included. LDH + HCG levels ranged from 124 U/l to 8833 U/l (median: 619; IQR: 955) + 2 IU/l to 283,782 IU/l (median: 20; IQR: 63) pre- and from 107 U/l to 8650 U/l (median: 324; IQR: 481) + 0 IU/l to 36700 IU/l post-orchiectomy (median: 30; IQR: 121), respectively. Five-year CSS and RFS rates were 90% and 79%, respectively. Patients with LDH levels pre-orchiectomy <1.5 UNL (n=142) had a 5-year CSS (RFS) rate of 97% (88%), compared to 86% (81%) for ≥1.5 to 3 UNL (n=40), 83% (77%) for >3 to 5 UNL (n=44) and 83% (72%) for >5 UNL (n=44) (CSS p <0.001; RFS p=0.142). Concerning LDH levels post-orchiectomy this stratification was not significant but patients with LDH levels ≥3 UNL (n=77) displayed an impaired prognosis associated with a 5-year CSS (RFS) rate of 85% (79%) compared to 94% (82%) for levels <3 UNL (n=186) (CSS p=0.025; RFS p=0.447). Patients with HCG levels ≥2000 IU/l (n=17) pre- but not post-orchiectomy had a 5-year CSS (RFS) rate of 73% (60%) compared to 94% (79%) for patients with HCG levels <2000 IU/l (n=855) (CSS p=0.09; RFS p=0.04). In cox-regression analysis LDH ≥1.5 UNL (p=0.037; HR 3.32, CI95%1.08-10.26) and HCG levels ≥2000 IU/l (p=0.044; HR 3.69, 95%CI1.04-13.13) pre-orchiectomy were confirmed as prognostic factors for CSS. Conclusions: LDH levels inversely correlate with survival outcomes, suggesting ≥1.5 UNL pre- and ≥3 UNL post-orchiectomy as potential cut-off values for further risk assessment. Patients with extensive HCG elevations may represent an unfavorable subgroup concerning RFS and CSS, but only few patients were affected.

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Clinical impact of abdominal versus mediastinal metastases as a prognostic factor for poor outcomes following esophageal cancer surgery: a retrospective study

BMC Cancer ◽

10.1186/s12885-021-08484-2 ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Yutaka Miyawaki ◽

Hiroshi Sato ◽

Shuichiro Oya ◽

Hirofumi Sugita ◽

Yasumitsu Hirano ◽

...

Keyword(s):

Esophageal Cancer ◽

Regression Analysis ◽

Lymph Node ◽

Prognostic Factor ◽

Cox Regression ◽

Recurrence Free Survival ◽

Free Survival ◽

Cox Regression Analysis ◽

Systemic Recurrence ◽

Significant Difference

Abstract Background Surgery is still the mainstay of radical treatment for resectable esophageal cancer (EC). It is apparent that the presence or spread of lymph node metastasis (LNM) is a powerful prognostic factor in patients with EC who are eligible for curative treatment. Although the importance and efficacy of lymph node dissection in radical esophagectomy have been reported, the clinical or prognostic relevance of specific metastatic patterns within the mediastinal cavity and abdomen remains unclear. Methods We retrospectively analyzed the association of postoperative survival with clinical mediastinal LNM (cMLNM) and abdominal LNM (cALNM) in 157 patients who underwent radical EC surgery at our hospital between May 2012 and March 2018. Results A significant difference in cause-specific survival (CSS) was observed between patients with and without cALNM (log-rank p = 0.000). A multivariate Cox regression analysis revealed that cALNM and thoracic surgery (mediastinal lymphadenectomy via conventional open right thoracotomy or video-assisted thoracoscopic surgery) independently predicted CSS (p = 0.0007 and 0.021, respectively). Moreover, a significant difference in systemic recurrence-free survival was observed between those with and without cALNM (log-rank p = 0.000). Multivariate Cox regression analysis revealed that cALNM and sex independently predicted systemic recurrence-free survival (p = 0.000 and 0.015, respectively). Conclusion cALNM was an independent poor prognostic factor for CSS after EC surgery. It may also be an independent prognostic factor for postoperative systemic recurrence, which can shorten the CSS. For patients with cALNM-positive EC who have a high potential risk of systemic metastases, more extensive treatment besides the conventional perioperative systemic chemotherapy may be necessary.

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Sonographic Features of Triple-Negative Breast Carcinomas Are Correlated With mRNA–lncRNA Signatures and Risk of Tumor Recurrence

Frontiers in Oncology ◽

10.3389/fonc.2020.587422 ◽

2021 ◽

Vol 10 ◽

Author(s):

Jia-wei Li ◽

Jin Zhou ◽

Zhao-ting Shi ◽

Na Li ◽

Shi-chong Zhou ◽

...

Keyword(s):

Regression Analysis ◽

Breast Imaging ◽

Tumor Recurrence ◽

Triple Negative ◽

Cox Regression ◽

Multivariate Logistic Regression Analysis ◽

Recurrence Free Survival ◽

Free Survival ◽

Cox Regression Analysis ◽

Risk Of Recurrence

BackgroundTo determine a correlation between mRNA and lncRNA signatures, sonographic features, and risk of recurrence in triple-negative breast cancers (TNBC).MethodsWe retrospectively reviewed the data from 114 TNBC patients having undergone transcriptome analysis. The risk of tumor recurrence was determined based on the correlation between transcriptome profiles and recurrence-free survival. Ultrasound (US) features were described according to the Breast Imaging Reporting and Data System. Multivariate logistic regression analysis determined the correlation between US features and risk of recurrence. The predictive value of sonographic features in determining tumor recurrence was analyzed using receiver operating characteristic curves.ResultsThree mRNAs (CHRDL1, FCGR1A, and RSAD2) and two lncRNAs (HIF1A-AS2 and AK124454) were correlated with recurrence-free survival in patients with TNBC. Among the three mRNAs, two were upregulated (FCGR1A and RSAD2) and one was downregulated (CHRDL1) in TNBCs. LncRNAs HIF1A-AS2 and AK124454 were upregulated in TNBCs. Based on these signatures, an integrated mRNA–lncRNA model was established using Cox regression analysis to determine the risk of tumor recurrence. Benign-like sonographic features, such as regular shape, circumscribed margin, posterior acoustic enhancement, and no calcifications, were associated with HIF1A-AS2 expression and high risk of tumor recurrence (P<0.05). Malignant-like features, such as irregular shape, uncircumscribed margin, no posterior acoustic enhancement, and calcifications, were correlated with CHRDL1 expression and low risk of tumor recurrence (P<0.05).ConclusionsSonographic features and mRNA–lncRNA signatures in TNBCs represent the risk of tumor recurrence. Taken together, US may be a promising technique in determining the prognosis of patients with TNBC.

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