Complementary role of Ki67 index and 70-gene signature (MammaPrint) high-risk patients in the St Gallen risk group with uncertain chemotherapy suggestion.

579 Background: St Gallen (SG) Consensus Panel on adjuvant treatment recommends the use of proliferation markers and multigene assays when choosing the appropriate treatment in addition to traditional parameters. Ki67 predictive/prognostic value is widely accepted; we tested its role in increasing the accuracy of risk prediction among Mammaprint (MP) /High(HR) or /Low Risk (LR) breast cancer patients with a SG risk uncertain for chemotherapy selection. Methods: MP was determined (courtesy of Agendia, Amsterdam) in 3 Italian Hospitals on 305 consecutive samples of breast cancer patients. We focused on SG “Intermediate Risk” Group (HER2 neg, no VI and: ER>10<50%, or G2 or Ki67 >15<30% or N1a or T>2<5cm), where the indication for adjuvant CHT still remains uncertain. In MP/HR cases, a “low” Ki67 value (<15%) was used to eliminate CHT suggestion and viceversa an “intermediate” Ki67 value (>15<30%) in MP/LR cases. Results: Overall, 72/305 pts (26.6%) were in SG intermediate risk group with a median age of 64 years (26-98). Ki67 was non available in 4.1% of cases, MP rejected in 16.6%, HR was detected in 39 (54.2%), whereas LR in 21 (29.2%). Ki67 resulted low in 23 MP/HR cases (59%), intermediate in 6 MP/LR cases (28.5%) and in 3 out 12 MP/Rejected cases (25%). The overall concordance between MP and Ki67 was 28/57 (49.1%), MP rejected excluded. Overall MP suggested 39/60 CHT (65%), Ki67 29/69 (42%). Conclusions: The risk of relapse is a continous variable and MP evaluates it in a dichotomy (low vs high) wich could decrease the accuracy of the test. In the selected SG Group, the average risk of 5 yr relapse is around 20% (EBCTCG, Lancet 2011) and MP HR cases in our experience account for 55%. A low Ki67 value could help avoid more than 20% of cytotoxic treatments suggested by MP. In the same way, according to an ER value <50% (2 cases), an intermediate Ki67 value could suggest a more aggressive treatment in a further 13% of cases MP LR (6/21) or Rejected (3/12). MP probably overestimates the risk in 20% of cases and underestimates it in further 20%. Ki67 could be usefull for a more personalized treatment in patients where the indication for adjuvant chemotherapy added to endocrine treatment is uncertain.

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

10.21203/rs.3.rs-27021/v1 ◽

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.

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201P 70-gene signature to select breast cancer patients for neoadjuvant endocrine treatment

Annals of Oncology ◽

10.1016/j.annonc.2020.08.323 ◽

2020 ◽

Vol 31 ◽

pp. S322-S323

Author(s):

C.F. Jacobs ◽

S.A.L. Bartels ◽

C.E. Loo ◽

C. Smorenburg ◽

S. Linn ◽

...

Keyword(s):

Breast Cancer ◽

Cancer Patients ◽

Gene Signature ◽

Endocrine Treatment ◽

Breast Cancer Patients

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MCM3 upregulation confers endocrine resistance in breast cancer and is a predictive marker of diminished tamoxifen benefit

npj Breast Cancer ◽

10.1038/s41523-020-00210-8 ◽

2021 ◽

Vol 7 (1) ◽

Author(s):

Sanne Løkkegaard ◽

Daniel Elias ◽

Carla L. Alves ◽

Martin V. Bennetzen ◽

Anne-Vibeke Lænkholm ◽

...

Keyword(s):

Breast Cancer ◽

Cell Cycle ◽

Cancer Patients ◽

Endocrine Therapy ◽

Endocrine Resistance ◽

Predictive Marker ◽

Endocrine Treatment ◽

Breast Cancer Patients ◽

Minichromosome Maintenance ◽

Primary Tumors

AbstractResistance to endocrine therapy in estrogen receptor-positive (ER+) breast cancer is a major clinical problem with poorly understood mechanisms. There is an unmet need for prognostic and predictive biomarkers to allow appropriate therapeutic targeting. We evaluated the mechanism by which minichromosome maintenance protein 3 (MCM3) influences endocrine resistance and its predictive/prognostic potential in ER+ breast cancer. We discovered that ER+ breast cancer cells survive tamoxifen and letrozole treatments through upregulation of minichromosome maintenance proteins (MCMs), including MCM3, which are key molecules in the cell cycle and DNA replication. Lowering MCM3 expression in endocrine-resistant cells restored drug sensitivity and altered phosphorylation of cell cycle regulators, including p53(Ser315,33), CHK1(Ser317), and cdc25b(Ser323), suggesting that the interaction of MCM3 with cell cycle proteins is an important mechanism of overcoming replicative stress and anti-proliferative effects of endocrine treatments. Interestingly, the MCM3 levels did not affect the efficacy of growth inhibitory by CDK4/6 inhibitors. Evaluation of MCM3 levels in primary tumors from four independent cohorts of breast cancer patients receiving adjuvant tamoxifen mono-therapy or no adjuvant treatment, including the Stockholm tamoxifen (STO-3) trial, showed MCM3 to be an independent prognostic marker adding information beyond Ki67. In addition, MCM3 was shown to be a predictive marker of response to endocrine treatment. Our study reveals a coordinated signaling network centered around MCM3 that limits response to endocrine therapy in ER+ breast cancer and identifies MCM3 as a clinically useful prognostic and predictive biomarker that allows personalized treatment of ER+ breast cancer patients.

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

Current Problems in Cancer ◽

10.1016/j.currproblcancer.2021.100709 ◽

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

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141P Cognitive impairment among breast cancer patients receiving endocrine treatment: A comparative study between aromatase inhibitors and tamoxifen

Annals of Oncology ◽

10.1016/j.annonc.2021.03.155 ◽

2021 ◽

Vol 32 ◽

pp. S82

Author(s):

I. Ben Abdallah ◽

H. Rachdi ◽

N. Mejri ◽

Y. Berrazega ◽

H. El Benna ◽

...

Keyword(s):

Breast Cancer ◽

Cognitive Impairment ◽

Comparative Study ◽

Cancer Patients ◽

Aromatase Inhibitors ◽

Endocrine Treatment ◽

Breast Cancer Patients

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Clinical CYP2D6 Genotyping to Personalize Adjuvant Tamoxifen Treatment in ER-Positive Breast Cancer Patients: Current Status of a Controversy

Cancers ◽

10.3390/cancers13040771 ◽

2021 ◽

Vol 13 (4) ◽

pp. 771

Author(s):

Tessa A. M. Mulder ◽

Mirjam de With ◽

Marzia del Re ◽

Romano Danesi ◽

Ron H. J. Mathijssen ◽

...

Keyword(s):

Breast Cancer ◽

Clinical Outcome ◽

Cancer Patients ◽

Plasma Concentrations ◽

Tamoxifen Treatment ◽

Current Status ◽

Endocrine Treatment ◽

Breast Cancer Patients ◽

Er Positive ◽

Positive Breast Cancer

Tamoxifen is a major option for adjuvant endocrine treatment in estrogen receptor (ER) positive breast cancer patients. The conversion of the prodrug tamoxifen into the most active metabolite endoxifen is mainly catalyzed by the enzyme cytochrome P450 2D6 (CYP2D6). Genetic variation in the CYP2D6 gene leads to altered enzyme activity, which influences endoxifen formation and thereby potentially therapy outcome. The association between genetically compromised CYP2D6 activity and low endoxifen plasma concentrations is generally accepted, and it was shown that tamoxifen dose increments in compromised patients resulted in higher endoxifen concentrations. However, the correlation between CYP2D6 genotype and clinical outcome is still under debate. This has led to genotype-based tamoxifen dosing recommendations by the Clinical Pharmacogenetic Implementation Consortium (CPIC) in 2018, whereas in 2019, the European Society of Medical Oncology (ESMO) discouraged the use of CYP2D6 genotyping in clinical practice for tamoxifen therapy. This paper describes the latest developments on CYP2D6 genotyping in relation to endoxifen plasma concentrations and tamoxifen-related clinical outcome. Therefore, we focused on Pharmacogenetic publications from 2018 (CPIC publication) to 2021 in order to shed a light on the current status of this debate.

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Evaluation of malignancy-risk gene signature in breast cancer patients

Breast Cancer Research and Treatment ◽

10.1007/s10549-009-0357-6 ◽

2009 ◽

Vol 120 (1) ◽

pp. 25-34 ◽

Cited By ~ 8

Author(s):

Dung-Tsa Chen ◽

Aejaz Nasir ◽

Chinnambally Venkataramu ◽

William Fulp ◽

Mike Gruidl ◽

...

Keyword(s):

Breast Cancer ◽

Cancer Patients ◽

Gene Signature ◽

Breast Cancer Patients ◽

Malignancy Risk ◽

Risk Gene

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Integrated immune-related gene signature to predict clinical outcome for patients with luminal B breast cancer.

Journal of Clinical Oncology ◽

10.1200/jco.2021.39.15_suppl.e12526 ◽

2021 ◽

Vol 39 (15_suppl) ◽

pp. e12526-e12526

Author(s):

Xiaying Kuang ◽

Du Cai ◽

Ying Lin ◽

Feng Gao

Keyword(s):

Breast Cancer ◽

Cancer Patients ◽

Validation Cohort ◽

Risk Groups ◽

Gene Signature ◽

Breast Cancer Patients ◽

Training Cohort ◽

Luminal B ◽

Immune Related Gene ◽

Immune Related Genes

e12526 Background: Luminal B breast cancer is always routinely treated with chemotherapy and endocrine therapy but heterogeneous with respect to sensitivity to treatment, identification of patients who may most benefit remains a matter of controversy. Immune-related genes (IRGs) was found to be associated with the prognosis of breast cancer. The aim of this study is to evaluate the impact of IRGs in predicting the outcome of luminal B breast cancer patients. Methods: According to the Metabric microarray dataset also as a training cohort, 488 luminal B breast cancer patients were selected for generation of immune-related gene signature (IRGS). Another independent dataset (n=250) of patients with complete prognostic information was analyzed as a validation cohort. Prognostic analysis was assessed to test the predictive value of IRGS. Results: A model of prognostic IRGS containing 12 immune-related genes was developed. In both training and validation cohorts, IRGS significantly stratified luminal B breast cancer patients into immune low- and high-risk groups in terms of disease free survival (DFS, HR=4.95, 95% CI=3.22-7.62, P<0.001 in training cohort, HR=2.47, 95% CI=1.29-4.75, P<0.001 in validation cohort). Multivariate analysis revealed IRGS as an independent prognostic factor (HR=4.96, 95% CI=3.00-8.18, P<0.001 in training cohort, HR=2.56, 95% CI=1.28-5.09, P=0.007 in validation cohort). Furthermore, those 12 genes mostly related with response to chemical, and the expression levels of them were completely opposite in patients of immune low- and high-risk groups. Conclusions: The proposed IRGS is a satisfactory prognostic model for estimating DFS of luminal B breast cancer patients. Further studies are needed to assess the clinical effectiveness of this system in predicting prognosis and treatment options for luminal B breast cancer patients. This work was supported by National Natural Science Foundation of China (No. 81602520), Natural Science Foundation of Guangdong Province (No. 2017A030313596).

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

10.21203/rs.3.rs-154913/v1 ◽

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.

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