Adjuvant Chemotherapy Guidance for pT1-3N0-1 Breast Cancer Patients with HR+, HER2- subtype: a study based on SEER database

2021 ◽  
Author(s):  
juanjuan Qiu ◽  
Li Xu ◽  
Yu Wang ◽  
Jia Zhang ◽  
Jiqiao Yang ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Prognostic Factors ◽  
High Risk ◽  
Cancer Patients ◽  
Risk Group ◽  
High Risk Group ◽  
Low Risk ◽  
Rank Test ◽  
Breast Cancer Patients ◽  
Group Score

Abstract Background Although the results of gene testing can guide early breast cancer patients with HR+, HER2- to decide whether they need chemotherapy, there are still many patients worldwide whose problems cannot be solved well by genetic testing. Methods 144 735 patients with HR+, HER2-, pT1-3N0-1 breast cancer from the Surveillance, Epidemiology, and End Results database were included from 2010 to 2015. They were divided into chemotherapy (n = 38 392) and no chemotherapy (n = 106 343) group, and after propensity score matching, 23 297 pairs of patients were left. Overall survival (OS) and breast cancer-specific survival (BCSS) were tested by Kaplan–Meier plot and log-rank test and Cox proportional hazards regression model was used to identify independent prognostic factors. A nomogram was constructed and validated by C-index and calibrate curves. Patients were divided into high- or low-risk group according to their nomogram score using X-tile. Results Patients receiving chemotherapy had better OS before and after matching (p < 0.05) but BCSS was not significantly different between patients with and without chemotherapy after matching: hazard ratio (HR) 1.005 (95%CI 0.897, 1.126). Independent prognostic factors were included to construct the nomogram to predict BCSS of patients without chemotherapy. Patients in the high-risk group (score > 238) can get better OS HR 0.583 (0.507, 0.671) and BCSS HR 0.791 (0.663, 0.944) from chemotherapy but the low-risk group (score ≤ 238) cannot. Conclusion The well-validated nomogram and a risk stratification model was built. Patients in the high-risk group should receive chemotherapy while patients in low-risk group may be exempt from chemotherapy.

scholarly journals Identification and Validation of an Autophagy-Related lncRNA Signature for Patients With Breast Cancer

2021 ◽  
Vol 10 ◽  
Author(s):  
Ruyue Zhang ◽  
Qingwen Zhu ◽  
Detao Yin ◽  
Zhe Yang ◽  
Jinxiu Guo ◽  
...  
Keyword(s):  
Breast Cancer ◽  
High Risk ◽  
Cancer Patients ◽  
Roc Curve ◽  
Prognostic Model ◽  
Risk Group ◽  
High Risk Group ◽  
Potential Functions ◽  
Low Risk ◽  
Breast Cancer Patients

BackgroundAutophagy is a “self-feeding” phenomenon of cells, which is crucial in mammalian development. Long non-coding RNA (lncRNA) is a new regulatory factor for cell autophagy, which can regulate the process of autophagy to affect tumor progression. However, poor attention has been paid to the roles of autophagy-related lncRNAs in breast cancer.ObjectiveThis study aimed to construct an autophagy-related lncRNA signature that can effectively predict the prognosis of breast cancer patients and explore the potential functions of these lncRNAs.MethodsThe RNA sequencing (RNA-Seq) data of breast cancer patients was collected from The Cancer Genome Atlas (TCGA) database and the GSE20685 database. Multivariate Cox analysis was implemented to produce an autophagy-related lncRNA signature in the TCGA cohort. The signature was then validated in the GSE20685 cohort. The receiver operator characteristic (ROC) curve was performed to evaluate the predictive ability of the signature. Gene set enrichment analysis (GSEA) was used to explore the potential functions based on the signature. Finally, the study developed a nomogram and internal verification based on the autophagy-related lncRNAs.ResultsA signature composed of 9 autophagy-related lncRNAs was determined as a prognostic model, and 1,109 breast cancer patients were divided into high-risk group and low-risk group based on median risk score of the signature. Further analysis demonstrated that the over survival (OS) of breast cancer patients in the high-risk group was poorer than that in the low-risk group based on the prognostic signature. The area under the curve (AUC) of ROC curve verified the sensitivity and specificity of this signature. Additionally, we confirmed the signature is an independent factor and found it may be correlated to the progression of breast cancer. GSEA showed gene sets were notably enriched in carcinogenic activation pathways and autophagy-related pathways. The qRT-PCR identified 5 lncRNAs with significantly differential expression in breast cancer cells based on the 9 lncRNAs of the prognostic model, and the results were consistent with the tissues.ConclusionIn summary, our signature has potential predictive value in the prognosis of breast cancer and these autophagy-related lncRNAs may play significant roles in the diagnosis and treatment of breast cancer.

Clinical impact of LncRNA XIST and LncRNA NEAT1 for diagnosis of high-risk group breast cancer patients

2021 ◽  
pp. 100709
Author(s):  
Menha Swellam ◽  
Hekmat M EL Magdoub ◽  
May A Shawki ◽  
Marwa Adel ◽  
Mona M Hefny ◽  
...  
Keyword(s):  
Breast Cancer ◽  
High Risk ◽  
Cancer Patients ◽  
Risk Group ◽  
High Risk Group ◽  
Clinical Impact ◽  
Breast Cancer Patients ◽  
Lncrna Xist ◽  
Lncrna Neat1

scholarly journals A glycolysis-related gene expression signature in predicting recurrence of breast cancer

2020 ◽  
Author(s):  
Jianing Tang ◽  
Gaosong Wu
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
High Risk ◽  
Cancer Patients ◽  
Risk Group ◽  
Gene Signature ◽  
Low Risk ◽  
Individual Treatment ◽  
Breast Cancer Patients ◽  
Related Gene

Abstract Background Metabolic change is the hallmark of cancer. Even in the presence of oxygen, cancer cells reprogram their glucose metabolism to enhance glycolysis and reduce oxidative phosphorylation. In the present study, we aimed to develop a glycolysis-related gene signature to predict the prognosis of breast cancer patients.Methods Gene expression profiles and clinical data of breast cancer patients were obtained from the GEO database. Univariate, Lasso-penalized, and multivariate Cox analysis were performed to construct the glycolysis-related gene signature.Results A four-gene based signature (ALDH2, PRKACB, STMN1 and ZNF292) was developed to separate patients into high-risk and low-risk groups. Kaplan-Meier survival analysis demonstrated that patients in low-risk group had significantly better prognosis than those in the high-risk group. Time-dependent ROC analysis demonstrated that the glycolysis-related gene signature had excellent prognostic accuracy. We further confirmed the expression of the four prognostic genes in breast cancer and paracancerous tissues samples using qRT-PCR analysis. Expression level of PRKACB was higher in paracancerous tissues, while STMN1 and ZNF292 were overexpressed in tumor samples. No difference was found in ALDH2 expression. The same results were observed in the IHC data from the human protein atlas. Global proteome data of 105 TCGA breast cancer samples obtained from the Clinical Proteomic Tumor Analysis Consortium were used to evaluate the prognostic value of their protein levels. Consistently, high expression of PRKACB protein level was associated with better prognosis, while high ZNF292 and STMN1 protein expression levels indicated poor prognosis.Conclusions The glycolysis-related gene signature might provide an effective prognostic predictor and a new view for individual treatment of breast cancer patients.

A prognostic 10-miRNA risk score (10-miRNA RS) in predicting neoadjuvant chemotherapy sensitivity of luminal breast cancer.

2019 ◽  
Vol 37 (15_suppl) ◽  
pp. 3139-3139
Author(s):  
Chang Gong ◽  
Luyuan Tan ◽  
Na You ◽  
Kai Chen ◽  
Weige Tan ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
High Risk ◽  
Risk Group ◽  
High Risk Group ◽  
Low Risk ◽  
Luminal Breast Cancer ◽  
Breast Cancer Patients ◽  
Luminal B ◽  
Risk Patients

3139 Background: The 10-miRNA risk score is a prognostic 10-gene expression signature specifically developed in luminal breast cancer associated with relapse-free survival. Since high-risk patients identified by10-miRNA RS had worse prognosis but better outcome with chemotherapy than low-risk patients (Gong C et al, EBioMedicine. 2016), this model may facilitate personalized therapy-decision making for luminal breast cancer patients. Therefore, we seek to validate whether high-risk group are more sensitive to chemotherapy than low-risk group by assessing the predictive value of 10-miRNA RS for pathological complete response (pCR) in patients receiving neoadjuvant chemotherapy (NAC). Methods: The 10-miRNA gene expression and clinicopathological data were prospectively gathered from 251 pretreated biopsy-diagnosed luminal breast cancer patients from 4 breast cancer centers. Formalin-fixed paraffin-embedded tissues from basal line biopsy were used for the detection of 10-miRNA expression to calculate the RS. The correlation between pCR and the 10-miRNA RS classification were identified. Results: In this prospective, multicenter study, the overall pCR rate was 13.6% (34/251). The 10-miRNA RS of the pCR group was significantly higher than the non-pCR group ( P = 0.015). Fifty-one percent of patients were classified as low-risk according to the 10-miRNA RS classification and 49% as high-risk with a RS cut-off point of 2.144. The 10-miRNA RS classification was associated with a pCR rate of 9.4% in the low-risk group and 17.8% in the high-risk group ( P = 0.041). The correlation between the pCR and the 10-miRNA RS classification was significant in subgroup analysis stratified by molecular subtypes (8% vs. 13.2% in luminal B1; 14.7% vs. 30.1% in luminal B2; no pCR was observed in all 13 luminal A subtype). In multivariate analysis, the 10-miRNA RS remained significantly associated with pCR and independent from subtype, ki67 and other clinicopathological characteristics. Conclusions: 10-miRNA RS clearly defined that high-risk patients are more sensitive to chemotherapy which leads to a higher pCR rate in NAC patients. Thus, 10-miRNA RS is not only a prognostic factor but an effective method in determining whether a patient would undergo surgery or receive NAC prior to surgery. Clinical trial information: ChiCTR-DDD-17013651.

scholarly journals Integrated Multiparametric Radiomics and Informatics System for Characterizing Breast Tumor Characteristics with the OncotypeDX Gene Assay

Cancers ◽  
2020 ◽  
Vol 12 (10) ◽  
pp. 2772
Author(s):  
Michael A. Jacobs ◽  
Christopher B. Umbricht ◽  
Vishwa S. Parekh ◽  
Riham H. El Khouli ◽  
Leslie Cope ◽  
...  
Keyword(s):  
Breast Cancer ◽  
High Risk ◽  
Risk Group ◽  
Area Under The Curve ◽  
Risk Groups ◽  
High Risk Group ◽  
Low Risk ◽  
Intermediate Risk ◽  
Breast Cancer Patients ◽  
Gene Assay

Optimal use of multiparametric magnetic resonance imaging (mpMRI) can identify key MRI parameters and provide unique tissue signatures defining phenotypes of breast cancer. We have developed and implemented a new machine-learning informatic system, termed Informatics Radiomics Integration System (IRIS) that integrates clinical variables, derived from imaging and electronic medical health records (EHR) with multiparametric radiomics (mpRad) for identifying potential risk of local or systemic recurrence in breast cancer patients. We tested the model in patients (n = 80) who had Estrogen Receptor positive disease and underwent OncotypeDX gene testing, radiomic analysis, and breast mpMRI. The IRIS method was trained using the mpMRI, clinical, pathologic, and radiomic descriptors for prediction of the OncotypeDX risk score. The trained mpRad IRIS model had a 95% and specificity was 83% with an Area Under the Curve (AUC) of 0.89 for classifying low risk patients from the intermediate and high-risk groups. The lesion size was larger for the high-risk group (2.9 ± 1.7 mm) and lower for both low risk (1.9 ± 1.3 mm) and intermediate risk (1.7 ± 1.4 mm) groups. The lesion apparent diffusion coefficient (ADC) map values for high- and intermediate-risk groups were significantly (p < 0.05) lower than the low-risk group (1.14 vs. 1.49 × 10−3 mm2/s). These initial studies provide deeper insight into the clinical, pathological, quantitative imaging, and radiomic features, and provide the foundation to relate these features to the assessment of treatment response for improved personalized medicine.

scholarly journals Surgery for primary tumor benefits survival for breast cancer patients with bone metastases: a large cohort retrospective study

BMC Cancer ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Zhangheng Huang ◽  
Xin Zhou ◽  
Yuexin Tong ◽  
Lujian Zhu ◽  
Ruhan Zhao ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Prognostic Factors ◽  
Bone Metastases ◽  
Cancer Patients ◽  
Primary Tumor ◽  
Predictive Accuracy ◽  
Rank Test ◽  
Breast Cancer Patients ◽  
Risk Of Death ◽  
The Impact

Abstract Background The role of surgery for the primary tumor in breast cancer patients with bone metastases (BM) remains unclear. The purpose of this study was to determine the impact of surgery for the primary tumor in breast cancer patients with BM and to develop prognostic nomograms to predict the overall survival (OS) of breast cancer patients with BM. Methods A total of 3956 breast cancer patients with BM from the Surveillance, Epidemiology, and End Results database between 2010 and 2016 were included. Propensity score matching (PSM) was used to eliminate the bias between the surgery and non-surgery groups. The Kaplan-Meier analysis and the log-rank test were performed to compare the OS between two groups. Cox proportional risk regression models were used to identify independent prognostic factors. Two nomograms were constructed for predicting the OS of patients in the surgery and non-surgery groups, respectively. In addition, calibration curve, receiver operating characteristic (ROC) curve, and decision curve analysis (DCA) were used to evaluate the performance of nomograms. Result The survival analysis showed that the surgery of the primary tumor significantly improved the OS for breast cancer patients with BM. Based on independent prognostic factors, separate nomograms were constructed for the surgery and non-surgery groups. The calibration and ROC curves of these nomograms indicated that both two models have high predictive accuracy, with the area under the curve values ≥0.700 on both the training and validation cohorts. Moreover, DCA showed that nomograms have strong clinical utility. Based on the results of the X-tile analysis, all patients were classified in the low-risk-of-death subgroup had a better prognosis. Conclusion The surgery of the primary tumor may provide survival benefits for breast cancer patients with BM. Furthermore, these prognostic nomograms we constructed may be used as a tool to accurately assess the long-term prognosis of patients and help clinicians to develop individualized treatment strategies.

Accuracy of the CARG chemotherapy toxicity risk prediction tool in older Indian patients with cancer.

2021 ◽  
Vol 39 (15_suppl) ◽  
pp. e24023-e24023
Author(s):  
Shreya Gattani ◽  
Vanita Noronha ◽  
Anant Ramaswamy ◽  
Renita Castelino ◽  
Vandhita Nair ◽  
...  
Keyword(s):  
High Risk ◽  
Cancer Patients ◽  
Risk Prediction ◽  
Risk Group ◽  
High Risk Group ◽  
Low Risk ◽  
Chemotherapy Toxicity ◽  
Patients With Cancer ◽  
Indian Patients ◽  
Grade 3

e24023 Background: Clinical judgement alone is inadequate in accurately predicting chemotherapy toxicity in older adult cancer patients. Hurria and colleagues developed and validated, the CARG score (range, 0–17) as a convenient and reliable tool for predicting chemotherapy toxicity in older cancer patients in America, however, its applicability in Indian patients is unknown. Methods: An observational retrospective and prospective study between 2018 and 2020 was conducted in the Department of Medical Oncology at Tata Memorial Hospital, Mumbai, India. The study was approved by the institutional ethics committee (IEC-III; Project No. 900596) and registered in the Clinical Trials Registry of India (CTRI/2020/04/024675). Written informed consent was obtained in the prospective part of the study. Patients aged ≥ 60 years and planned for systemic therapy were evaluated in the geriatric oncology clinic and their CARG score was calculated. Patients were stratified into low (0-4), intermediate (5-9) and high risk (10-17) based on the CARG scores. The CARG score was provided to the treating physicians, along with the results of the geriatric assessment. Chemotherapy-related toxicities were captured from the electronic medical record and graded as per the NCI CTCAE, version 4.0. Results: We assessed 130 patients, with a median age 69 years (IQR, 60 to 84); 72% patients were males. The common malignancies included gastrointestinal (52%) and lung (30%). Approximately 78% patients received polychemotherapy and 53% received full dose chemotherapy. Based on the CARG score, 28 (22%) patients belonged to low risk, 80 (61%) to intermediate risk and 22 (17%) to the high risk category. The AU-ROC of the CARG score in predicting grade 3-5 toxicities was 0.61 (95% CI, 0.51-0.71). The sensitivity and specificity of the CARG score in predicting grade 3-5 toxicities were 60.8% and 78.6%. Grade 3-5 toxicities occurred in 6/28 patients (21%) in the low risk group, compared to 62/102 patients (61%) in the intermediate /high risk group, p = 0.0002. There was also a significant difference in the time to development of grade 3-5 toxicities, which occurred at a median of 2.5 cycles (IQR, 1-3.8) in the intermediate /high risk group and at a median of 6 cycles (IQR, 3.5-8) in the low risk group, p = 0.0011. Conclusions: In older Indian patients with cancer, the CARG score reliably stratifies patients into low risk and intermediate/high risk categories, predicting both the occurrence and the time to occurrence of grade 3-5 toxicities from chemotherapy. The CARG score may aid the oncologist in estimating the risk-benefit ratio of chemotherapy. An important limitation was that we provided the CARG score to the treating oncologists prior to the start of chemotherapy, which may have resulted in alterations in the chemotherapy regimen and dose and may have impacted the CARG risk prediction model. Clinical trial information: CTRI/2020/04/024675.

scholarly journals Impact of Different Modules of 21-Gene Assay in Early Breast Cancer Patients

2021 ◽  
Vol 12 ◽  
Author(s):  
Mengdi Chen ◽  
Deyue Liu ◽  
Weilin Chen ◽  
Weiguo Chen ◽  
Kunwei Shen ◽  
...  
Keyword(s):  
Breast Cancer ◽  
High Risk ◽  
Cancer Patients ◽  
Low Risk ◽  
Breast Cancer Patients ◽  
Younger Patients ◽  
Gene Assay ◽  
Risk Patients ◽  
Gene Modules ◽  
The Impact

BackgroundThe 21-gene assay recurrence score (RS) provides additional information on recurrence risk of breast cancer patients and prediction of chemotherapy benefit. Previous studies that examined the contribution of the individual genes and gene modules of RS were conducted mostly in postmenopausal patients. We aimed to evaluate the gene modules of RS in patients of different ages.MethodsA total of 1,078 estrogen receptor (ER)-positive and human epidermal growth factor receptor 2 (HER2)-negative breast cancer patients diagnosed between January 2009 and March 2017 from Shanghai Jiao Tong University Breast Cancer Data Base were included. All patients were divided into three subgroups: Group A, ≤40 years and premenopausal (n = 97); Group B, &gt;40 years and premenopausal (n = 284); Group C, postmenopausal (n = 697). The estrogen, proliferation, invasion, and HER2 module scores from RS were used to characterize the respective molecular features. Spearman correlation and analysis of the variance tests were conducted for RS and its constituent modules.ResultsIn patients &gt;40 years, RS had a strong negative correlation with its estrogen module (ρ = −0.76 and −0.79 in Groups B and C) and a weak positive correlation with its invasion module (ρ = 0.29 and 0.25 in Groups B and C). The proliferation module mostly contributed to the variance in young patients (37.3%) while the ER module contributed most in old patients (54.1% and 53.4% in Groups B and C). In the genetic high-risk (RS &gt;25) group, the proliferation module was the leading driver in all patients (ρ = 0.38, 0.53, and 0.52 in Groups A, B, and C) while the estrogen module had a weaker correlation with RS. The impact of ER module on RS was stronger in clinical low-risk patients while the effect of the proliferation module was stronger in clinical high-risk patients. The association between the RS and estrogen module was weaker among younger patients, especially in genetic low-risk patients.ConclusionsRS was primarily driven by the estrogen module regardless of age, but the proliferation module had a stronger impact on RS in younger patients. The impact of modules varied in patients with different genetic and clinical risks.

Abstract TP387: Abcd 2 Score Predicts The Long-term Risk Of Stroke After Transient Ischemic Attack: Fukuoka Stroke Registry

Stroke ◽  
2013 ◽  
Vol 44 (suppl_1) ◽  
Author(s):  
Yasuhiro Kumai ◽  
Takuya Kiyohara ◽  
Masahiro Kamouchi ◽  
Sohei Yoshimura ◽  
Hiroshi Sugimori ◽  
...  
Keyword(s):  
High Risk ◽  
Transient Ischemic Attack ◽  
Risk Group ◽  
High Risk Group ◽  
Low Risk ◽  
Rank Test ◽  
Moderate Risk ◽  
Stroke Registry ◽  
Ischemic Attack

Background and Purpose— ABCD 2 score has been developed to predict the early risk of stroke after transient ischemic attack (TIA). The aim of this study was to clarify whether ABCD 2 score predicts the occurrence of stroke in the long term after TIA. Methods— Fukuoka Stroke Registry (FSR) is a multicenter epidemiological study database on acute stoke. From June 2007 to June 2011, 496 (305 males, 70 ± 13 years of age) patients who had suffered from TIA and were hospitalized in the 7 stroke centers within 7 days after the onset of TIA were enrolled in this study. The patients were divided into three groups according to the risk: low-risk (ABCD 2 score 0-3; n=72), moderate-risk (4-5; n=229) and high-risk group (6-7; n=195). They were followed up prospectively for up to 3 years. Cox proportional hazard regression model was used to elucidate whether ABCD 2 score was a predictor for stroke after TIA after adjusting for confounding factors. Results— Among three groups, there were significant differences in age, hypertension, diabetes mellitus and the decrease in estimated glomerular filtration rate (P<0.01, significantly). During a mean follow-up of 1.3 years, Kaplan-Meier analysis demonstrated that the stroke rate in TIA patients was significantly lower in low-risk group than in moderate-risk or high-risk group (log rank test, p<0.001). The adjusted hazard ratios for stroke in patients with TIA increased with moderate-risk group (Hazard ratio [HR]: 3.47, 95% CI: 1.03-21.66, P<0.05) and high-risk group (HR: 4.46, 95% CI: 1.31-27.85, P<0.05), compared to low-risk group. Conclusions— The ABCD 2 score is able to predict the long-term risk of stroke after TIA.

Utilization of oncotype DX in node-negative, ER-positive breast cancer patients

2007 ◽  
Vol 25 (18_suppl) ◽  
pp. 11067-11067 ◽  
Author(s):  
H. Patel ◽  
K. Hook ◽  
C. Kaplan ◽  
R. Davidson ◽  
A. DeMichele ◽  
...  
Keyword(s):  
High Risk ◽  
Risk Group ◽  
High Risk Group ◽  
Low Risk ◽  
Oncotype Dx ◽  
Intermediate Risk ◽  
Breast Cancers ◽  
Breast Cancer Patients ◽  
Node Negative ◽  
Er Positive

11067 Background: The 21 gene RT-PCR assay Oncotype DX (Genomic Health, CA) stratifies patients into low, intermediate and high risk for systemic recurrence. The objective of this study was to examine the patterns of use of Oncotype DX in a single institution. Methods: All patients who had ODX testing requested by the University of Pennsylvania were identified and recurrence scores (RS) obtained. Patient and tumor characteristics, as well as treatment administered, were obtained by chart review for analysis. Results: 100 ODX tests were ordered between 1/1/05–11/30/06. RS results classified 51% of breast cancers as low risk, 38% intermediate risk, and 11% high risk. Characteristics of the tumors of the overall population and by RS group are shown in Table . 99% of patients received hormonal therapy. Of the low risk patients, only one patient was treated with chemotherapy (2%) while 34% of the intermediate risk group and 80% of the high risk group received chemotherapy. Notably, only 4/100 patients with ODX were under age 35 and 17/100 had tumors over 2cm. Conclusions: In this series, ODX use is accelerating. The results of the ODX tests appear to be used clinically as demonstrated by the very low use of chemotherapy in the low risk group. Comparison to the overall population of ER positive, node negative patients seen at this institution is underway. [Table: see text] No significant financial relationships to disclose.

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