scholarly journals Tamoxifen resistance mechanisms in breast cancer treatment

2020 ◽  
Vol 8 (2) ◽  
pp. 224-232
Author(s):  
Asima Tayyeb
Keyword(s):  
Breast Cancer ◽  
Cancer Treatment ◽  
Molecular Mechanisms ◽  
Tamoxifen Resistance ◽  
Resistance Mechanisms ◽  
Breast Cancer Treatment ◽  
Therapeutic Interventions ◽  
Survival Outcomes ◽  
Breast Cancer Patients ◽  
Current Review

Therapies targeting estrogen receptor (ER) are being widely used to treat ER+ breast cancer patients. Despite early detection and improved survival outcomes, tamoxifen resistance, either intrinsic or acquired- is a major obstacle in effective disease management. Current review will summarize different molecular mechanisms of tamoxifen resistance both intrinsic and acquired in breast cancer treatment. This review not only provides basis to understand the nature of tamoxifen drug resistance but also suggests the mechanisms for its control leading to improved therapeutic interventions.

scholarly journals Tamoxifen resistance mechanisms in breast cancer treatment

2020 ◽  
Vol 8 (2) ◽  
pp. 224-232
Author(s):  
Asima Tayyeb
Keyword(s):  
Breast Cancer ◽  
Cancer Treatment ◽  
Molecular Mechanisms ◽  
Tamoxifen Resistance ◽  
Resistance Mechanisms ◽  
Breast Cancer Treatment ◽  
Therapeutic Interventions ◽  
Survival Outcomes ◽  
Breast Cancer Patients ◽  
Current Review

Therapies targeting estrogen receptor (ER) are being widely used to treat ER+ breast cancer patients. Despite early detection and improved survival outcomes, tamoxifen resistance, either intrinsic or acquired- is a major obstacle in effective disease management. Current review will summarize different molecular mechanisms of tamoxifen resistance both intrinsic and acquired in breast cancer treatment. This review not only provides basis to understand the nature of tamoxifen drug resistance but also suggests the mechanisms for its control leading to improved therapeutic interventions.

scholarly journals Data-Driven Treatment Pathways Mining for Early Breast Cancer Using cSPADE Algorithm and System Clustering

2020 ◽  
Author(s):  
Qing Yang ◽  
Ting Luo ◽  
Wei Zhang ◽  
Xiaorong Zhong ◽  
Ping He ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Cancer Treatment ◽  
Early Breast Cancer ◽  
Breast Cancer Treatment ◽  
Breast Cancer Patients ◽  
Treatment Pathways ◽  
Kolmogorov Smirnov ◽  
System Clustering ◽  
Sequence Rules ◽  
Smirnov Test

Abstract Background: Due to the multidimensional, multilayered, and chronological order of the cancer data in this study, it was challenging for us to extract treatment paths. Therefore, it was necessary to design a new data mining scheme to effectively extract the treatment path of breast cancer. To determine whether the cSPADE algorithm and system clustering proposed in this study can effectively identify the treatment pathways for early breast cancer. Methods: We applied data mining technology to the electronic medical records of 6891 early breast cancer patients to mine treatment pathways. We provided a method of extracting data from EMR and performed three-stage mining: determining the treatment stage through the cSPADE algorithm → system clustering for treatment plan extraction → cSPADE mining sequence pattern for treatment. The Kolmogorov-Smirnov test and correlation analysis were used to cross-validate the sequence rules of early breast cancer treatment pathways.Results: We unearthed 55 sequence rules for early breast cancer treatment, 3 preoperative neoadjuvant chemotherapy regimens, 3 postoperative chemotherapy regimens, and 2 chemotherapy regimens for patients without surgery. Through 5-fold cross-validation, Pearson and Spearman correlation tests were performed. At the significance level of P <0.05, all correlation coefficients of support, confidence and lift were greater than 0.89. Using the Kolmogorov-Smirnov test, we found no significant differences between the sequence distributions.Conclusions: The cSPADE algorithm combined with system clustering can achieve hierarchical and vertical mining of breast cancer treatment models. By uncovering the treatment pathways of early breast cancer patients by this method, the real-world breast cancer treatment behavior model can be evaluated, and it can provide a reference for the redesign and optimization of the treatment pathways.

scholarly journals Probiotics for the Treatment of Docetaxel-Related Weight Gain of Breast Cancer Patients—A Single-Center, Randomized, Double-Blind, and Placebo-Controlled Trial

2021 ◽  
Vol 8 ◽  
Author(s):  
Zhang Juan ◽  
Zhang Qing ◽  
Liang Yongping ◽  
Liyuan Qian ◽  
Wei Wu ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Body Weight ◽  
Weight Gain ◽  
Cancer Treatment ◽  
Cancer Patients ◽  
Body Fat ◽  
Breast Cancer Treatment ◽  
Body Fat Percentage ◽  
Breast Cancer Patients ◽  
Fat Percentage

Background: Docetaxel is an important chemotherapy-agent for breast cancer treatment. One of its side-effects is weight gain, which increases the all-cause mortality rate. Considering gut microbiota is one important factor for weight regulation, we hypothesized that probiotics could be potentially used to reduce the docetaxel-related weight gain in breast cancer patients.Methods: From 10/8/2018 to 10/17/2019, 100 breast cancer (Stage I-III) patients underwent four cycles of docetaxel-based chemotherapy were enrolled and randomly assigned to receive probiotics (Bifidobacterium longum, Lactobacillus acidophilus, and Enterococcus faecalis) or placebo (supplementary material of the probiotics capsule) treatment for 84 days with three capsules per time, twice/day. The primary outcome: the changes in body weight and body-fat percentage of the patients were measured by a designated physician using a fat analyzer, and the secondary outcomes: the fasting insulin, plasma glucose, and lipids were directly obtained from the Hospital Information System (HIS); The metabolites were measured using liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS); The fecal microbiome was analyzed using bacterial 16S ribosomal RNA (rRNA) gene sequence. All indicators were measured 1 day before the first cycle of docetaxel-based chemotherapy and 21 days after the last cycle of docetaxel-based chemotherapy.Results: Compared with the placebo group, the probiotic group showed significantly smaller changes in body weight (Mean [SD] 0.77 [2.58] vs. 2.70 [3.08], P = 0.03), body-fat percentage (Mean [SD] 0.04 [1.14] vs. 3.86 [11.09], P = 0.02), and low density lipoprotein (LDL) (Mean [SD]−0.05[0.68] vs. 0.39 [0.58], P = 0.002). Moreover, five of the 340 detected plasma metabolites showed significant differences between the two groups. The change of biliverdin dihydrochloride (B = −0.724, P = 0.02) was inverse correlated with weight gain. One strain of the phylum and three strains of the genus were detected to be significantly different between the two groups. Also, the changes of Bacteroides (B = −0.917, P &lt; 0.001) and Anaerostipes (B = −0.894, P &lt; 0.001) were inverse correlated with the change of LDL.Conclusions: Probiotics supplement during docetaxel-based chemotherapy for breast cancer treatment may help to reduce the increase in body weight, body-fat percentage, plasma LDL, and minimize the metabolic changes and gut dysbacteriosis.Clinical Trial Registration:http://www.chictr.org.cn/showproj.aspx?proj=24294, ChiCTR-INQ-17014181.

Factors influencing options in primary breast cancer treatment.

1987 ◽  
Vol 5 (1) ◽  
pp. 68-74 ◽  
Author(s):  
W H Wolberg ◽  
M A Tanner ◽  
E P Romsaas ◽  
D L Trump ◽  
J F Malec
Keyword(s):  
Breast Cancer ◽  
Cancer Treatment ◽  
Cancer Patients ◽  
Primary Breast Cancer ◽  
Breast Cancer Treatment ◽  
Cancer Information ◽  
Breast Cancer Patients ◽  
Term Survival ◽  
Tumor Excision ◽  
Factors Influencing

Primary breast cancer treatment is determined by tumor factors and by patient preference. Breast cancer treatments that preserve the cosmetic appearance of the breast are appealing and effective for appropriately selected patients; long-term survival following tumor excision and breast irradiation appears to be comparable to that for mastectomy. Since April 1981, when a protocol was developed and treatment options were offered, factors influencing treatment selection have been analyzed in 206 consecutive primary breast cancer patients. Mastectomy was dictated by tumor-related factors in 96 patients (47%); 110 patients (53%) had the option of mastectomy or conservation--tumor excision plus radiotherapy to the breast. Among these 110 eligible patients, 54 chose conservation (49%) and 56 chose mastectomy (51%). Intraoperative findings for ten patients electing conservation necessitated mastectomy, so conservation was accomplished for 44 (21%) of those treated for breast cancer. Beginning in July 1982, breast cancer patients took a battery of psychosexual assessments before any operation (Profile of Mood States [POMS], Health Locus of Control Scale [HLCS] Locke-Wallace Marital Adjustment Test [MAT], Psychosocial Adjustment to Illness Scale [PAIS], Derogatis Sexual Function Inventory [DSFI], Millon Clinical Multiaxial Inventory [MCMI], and a Breast Cancer Information Test [BCIT]). Comparisons of psychologic and demographic variables were made between patients who chose mastectomy and those who chose conservation. No demographic variable was statistically significantly related to choice, although older women tended to select mastectomy more than younger women. Compared with those who elected conservation, women who elected mastectomy were more tense and anxious (P less than .01), more introverted (P less than .01), felt more depressed and dejected (P less than .05), and reported more sexual problems (P less than .05). Those who elected conservation valued their physical appearance more highly (P less than .01) and were generally more self-interested (P less than .05). Mastectomy was dictated by medical considerations for approximately half of patients with breast cancer. Among candidates for breast conservation, the importance of retaining the breast appeared to be determined to a significant degree by measurable psychological factors.

pN0(i+) Breast Cancer: Treatment Patterns, Locoregional Recurrence, and Survival Outcomes

2013 ◽  
Vol 87 (4) ◽  
pp. 731-737 ◽  
Author(s):  
Irene Karam ◽  
Maria F. Lesperance ◽  
Tanya Berrang ◽  
Caroline Speers ◽  
Scott Tyldesley ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Cancer Treatment ◽  
Locoregional Recurrence ◽  
Breast Cancer Treatment ◽  
Treatment Patterns ◽  
Survival Outcomes

Serum metabolism during breast cancer treatment.

2017 ◽  
Vol 35 (15_suppl) ◽  
pp. e23043-e23043
Author(s):  
Guro Fanneløb Giskeødegård ◽  
Torfinn Støve Madssen ◽  
Riyas Vettukattil ◽  
Vidar Gordon Flote ◽  
Anders Husøy ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Weight Gain ◽  
Cancer Treatment ◽  
Cancer Patients ◽  
Breast Cancer Treatment ◽  
Post Treatment ◽  
Breast Cancer Patients ◽  
National Guidelines ◽  
Lipoprotein Subfractions ◽  
Metabolite Profiles

e23043 Serum metabolism during breast cancer treatment Background: Breast cancer treatment may include surgery, systemic therapy and radiation, often involving side-effects. Many patients experience weight gain during treatment, which is associated with decreased survival rates1. The purpose of this study was to describe serum metabolic alterations in breast cancer patients undergoing treatment, and relate these alterations to weight gain during treatment. Methods: This pilot study includes 60 breast cancer patients, aged 35-75 years, with histologically verified stage I/II disease. All patients underwent tumor surgery, and were treated according to national guidelines. Samples were collected before and 6 months after surgery, and analyzed by MR spectroscopy (MRS) and mass spectrometry (MS). 170 metabolites and 105 lipoprotein subfractions were quantified by combined MRS and MS analyses. Results: Multilevel PLS-DA showed significant alterations in serum metabolite profiles post-treatment, both in patients receiving (n = 35) and not receiving (n = 25) chemotherapy (classification accuracy: 86.7% and 77.0%, resp., p < 0.001). Lipoprotein profiles were also significantly altered in both groups (p < 0.001). Chemotherapy recipients had decreased levels of citrate, ornithine, and methionine after treatment, while non-recipients had increased levels of glutamate, alanine, proline and two biogenic amines, and decreased levels of acylcarnitines. 17/52 patients (32.7%) gained weight (≥ 1.5 kg) during treatment. Weight gain was predicted from pre-treatment samples with accuracy 67.0% (p = 0.020). Weight gain patients had lower levels of three acylcarnitines and 20 phosphocholines, and higher levels of lysine and isoleucine, suggesting aberrant lipid and amino acid metabolism. Weight gain was also reflected in the post-treatment samples (accuracy 66.8%, p = 0.015), with weight gain patients having higher levels of five acylcarnitines, and lower levels of glycine, isoleucine and valine. Conclusions: This study indicates that treatment induces changes in serum metabolite levels. Patients gaining weight had significantly different metabolite profiles than those not gaining weight both before and after treatment. 1. Chan et al, Ann Oncol 25: 1901-14, 2014.

scholarly journals Survival outcomes are associated with genomic instability in luminal breast cancers

PLoS ONE ◽  
2021 ◽  
Vol 16 (2) ◽  
pp. e0245042
Author(s):  
Lydia King ◽  
Andrew Flaus ◽  
Emma Holian ◽  
Aaron Golden
Keyword(s):  
Breast Cancer ◽  
Genomic Instability ◽  
Cancer Survival ◽  
Molecular Taxonomy ◽  
Gene Signature ◽  
Therapeutic Interventions ◽  
Survival Outcomes ◽  
Breast Cancers ◽  
Breast Cancer Patients ◽  
Luminal A

Breast cancer is the leading cause of cancer related death among women. Breast cancers are generally diagnosed and treated based on clinical and histopathological features, along with subtype classification determined by the Prosigna Breast Cancer Prognostic Gene Signature Assay (also known as PAM50). Currently the copy number alteration (CNA) landscape of the tumour is not considered. We set out to examine the role of genomic instability (GI) in breast cancer survival since CNAs reflect GI and correlate with survival in other cancers. We focused on the 70% of breast cancers classified as luminal and carried out a comprehensive survival and association analysis using Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) data to determine whether CNA Score Quartiles derived from absolute CNA counts are associated with survival. Analysis revealed that patients diagnosed with luminal A breast cancer have a CNA landscape associated with disease specific survival, suggesting that CNA Score can provide a statistically robust prognostic factor. Furthermore, stratification of patients into subtypes based on gene expression has shown that luminal A and B cases overlap, and it is in this region we largely observe luminal A cases with reduced survival outlook. Therefore, luminal A breast cancer patients with quantitatively elevated CNA counts may benefit from more aggressive therapy. This demonstrates how individual genomic landscapes can facilitate personalisation of therapeutic interventions to optimise survival outcomes.

Breast cancer treatment resources and guideline-concordant treatment in Appalachia.

2011 ◽  
Vol 29 (27_suppl) ◽  
pp. 216-216
Author(s):  
N. Yao ◽  
M. M. Hillemeier ◽  
R. T. Anderson
Keyword(s):  
Breast Cancer ◽  
Radiation Therapy ◽  
Cancer Treatment ◽  
Resource Availability ◽  
Breast Cancer Treatment ◽  
County Level ◽  
Breast Cancer Patients ◽  
Central Appalachia ◽  
Appalachian Kentucky ◽  
Per Capita

216 Background: Appalachia has poorer cancer outcomes, but little research has been done regarding availability of cancer care resources in this region and how resource availability may relate to cancer outcomes. This study 1) examines associations between radiation therapy resources and receipt of radiotherapy after BCS in counties within Kentucky - a SEER state; and 2) describes spatial patterning of breast cancer treatment resources in all 13 Appalachian states. Methods: For the Kentucky analyses, county-level data from the Area Resource File and SEER registry are analyzed. Bivariate analyses and spatial lag regression using a 6-nearest neighboring counties matrix are conducted. The sample includes stage I or II primary breast cancer patients age 18+ years diagnosed in Kentucky during 2000-2007. The dependent variable is the county-level percentage of patients received BCS without radiation; independent variables include density of radiation therapy providers and facilities and other socioeconomic covariates. For the analyses of entire Appalachian region, descriptive analyses and exploratory spatial data analysis are conducted including 420 Appalachian counties and 644 non-Appalachian counties in 13 states. Results: In Kentucky 16.44% of 17,227 early stage breast cancer patients received BCS without radiation therapy (21.08% in Appalachia versus 14.80% in non-Appalachia, p<0.001). Appalachian Kentucky had significantly fewer radiation oncologists and radiation therapy facilities per capita than non-Appalachian Kentucky. The number of radiation therapy facilities per capita is negatively associated with rates of BCS without radiation when controlling for covariates. Analysis of 13 Appalachian states shows that Appalachian counties, especially in the Central and Southern regions, had significant fewer physicians per capita in Surgery, Anesthesia, Clinical Pathology, and Radiation Oncology. Clustering of scarce breast cancer care resources was observed in Central Appalachia. Conclusions: Appalachian counties, especially in central Appalachia, have fewer breast cancer treatment resources than non-Appalachian counties, and resource availability is associated with cancer health disparities.

Sign in / Sign up

Export Citation Format

Share Document